diff --git a/docs/Makefile b/docs/Makefile index c0618dfc..2811ca1a 100644 --- a/docs/Makefile +++ b/docs/Makefile @@ -7,15 +7,15 @@ SPHINXBUILD ?= sphinx-build SPHINXPROJ = shenfun SOURCEDIR = source BUILDDIR = build -DEMO = Poisson/poisson.rst \ - KleinGordon/kleingordon.rst \ - Poisson3D/poisson3d.rst \ +DEMO = Poisson/poisson.ipynb \ + KleinGordon/kleingordon.ipynb \ + Poisson3D/poisson3d.ipynb \ PolarHelmholtz/polarhelmholtz.ipynb \ SphereHelmholtz/sphericalhelmholtz.ipynb \ - KuramatoSivashinsky/kuramatosivashinsky.rst \ - Stokes/stokes.rst \ - DrivenCavity/drivencavity.rst \ - RayleighBenard/rayleighbenard.rst \ + KuramatoSivashinsky/kuramatosivashinsky.ipynb \ + Stokes/stokes.ipynb \ + DrivenCavity/drivencavity.ipynb \ + RayleighBenard/rayleighbenard.ipynb \ Functions/functions.ipynb \ Integration/surfaceintegration.ipynb \ Moebius/moebius.ipynb \ @@ -50,24 +50,13 @@ help: ./recite.sh $(notdir $@) %.ipynb: - doconce format ipynb demos/$(basename $@).do.txt - python add_metadata.py demos/$(basename $@).ipynb jupyter nbconvert --inplace --execute demos/${basename $@}.ipynb cp demos/$(basename $@).ipynb source/ %.ipynb2: - doconce format ipynb demos/$(basename $@).do.txt - python add_metadata.py demos/$(basename $@).ipynb jupyter nbconvert --inplace --clear-output demos/${basename $@}.ipynb - #jupyter nbconvert --inplace --execute demos/${basename $@}.ipynb - doconce subst 'XXX' ' ' demos/$(basename $@).ipynb - doconce subst "" "a>" demos/$(basename $@).ipynb - #doconce subst '' '' demos/$(basename $@).ipynb - #python add_metadata.py demos/$(basename $@).ipynb cp demos/$(basename $@).ipynb ../../shenfun-demos/content/ - cp demos/$(basename $@).ipynb notebooks/ - + publish: cd demos && publish export papers.bib && cd .. cp demos/papers.bib source/ diff --git a/docs/demos/DrivenCavity/drivencavity.ipynb b/docs/demos/DrivenCavity/drivencavity.ipynb new file mode 100644 index 00000000..e04f2391 --- /dev/null +++ b/docs/demos/DrivenCavity/drivencavity.ipynb @@ -0,0 +1,1517 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "20be7199", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - Lid driven cavity\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **May 6, 2019**\n", + "\n", + "**Summary.** The lid driven cavity is a classical benchmark for Navier Stokes solvers.\n", + "This is a demonstration of how the Python module [shenfun](https://github.com/spectralDNS/shenfun) can be used to solve the lid\n", + "driven cavity problem with full spectral accuracy using a mixed (coupled) basis\n", + "in a 2D tensor product domain. The demo also shows how to use mixed\n", + "tensor product spaces for vector valued equations. Note that the regular\n", + "lid driven cavity, where the top wall has constant velocity and the\n", + "remaining three walls are stationary, has a singularity at the two\n", + "upper corners, where the velocity is discontinuous.\n", + "Due to their global nature, spectral methods\n", + "are usually not very good at handling problems with discontinuities, and\n", + "for this reason we will also look at a regularized lid driven cavity,\n", + "where the top lid moves according to $(1-x)^2(1+x)^2$, thus removing\n", + "the corner discontinuities.\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "

Figure 1: Velocity vectors for the lid driven cavity at Reynolds number 100.

\n", + "" + ] + }, + { + "cell_type": "markdown", + "id": "ffa812f1", + "metadata": { + "editable": true + }, + "source": [ + "## Navier Stokes equations\n", + "\n", + "\n", + "The nonlinear steady Navier Stokes equations are given in strong form as" + ] + }, + { + "cell_type": "markdown", + "id": "853e2f60", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{align*}\n", + "\\nu \\nabla^2 \\boldsymbol{u} - \\nabla p &= \\nabla \\cdot \\boldsymbol{u} \\boldsymbol{u} \\quad \\text{in } \\Omega , \\\\ \n", + "\\nabla \\cdot \\boldsymbol{u} &= 0 \\quad \\text{in } \\Omega, \\\\ \n", + "\\int_{\\Omega} p dx &= 0, \\\\ \n", + "\\boldsymbol{u}(x, y=1) = (1, 0) \\, &\\text{ or }\\, \\boldsymbol{u}(x, y=1) = ((1-x)^2(1+x)^2, 0), \\\\ \n", + "\\boldsymbol{u}(x, y=-1) &= (0, 0), \\\\ \n", + "\\boldsymbol{u}(x=\\pm 1, y) &= (0, 0),\n", + "\\end{align*}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "282c8f88", + "metadata": { + "editable": true + }, + "source": [ + "where $\\boldsymbol{u}, p$ and $\\nu$ are, respectively, the\n", + "fluid velocity vector, pressure and kinematic viscosity. The domain\n", + "$\\Omega = (-1, 1)^2$ and the nonlinear term $\\boldsymbol{u} \\boldsymbol{u}$ is the\n", + "outer product of vector $\\boldsymbol{u}$ with itself. Note that the final\n", + "$\\int_{\\Omega} p dx = 0$ is there because there is no Dirichlet boundary\n", + "condition on the pressure and the system of equations would otherwise be\n", + "ill conditioned.\n", + "\n", + "We want to solve these steady nonlinear Navier Stokes equations with the Galerkin\n", + "method, using the [shenfun](https://github.com/spectralDNS/shenfun) Python\n", + "package. The first thing we need to do then is to import all of shenfun's\n", + "functionality" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ab478fd9", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:01.761472Z", + "iopub.status.busy": "2024-05-24T12:37:01.761132Z", + "iopub.status.idle": "2024-05-24T12:37:02.592257Z", + "shell.execute_reply": "2024-05-24T12:37:02.591704Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "from shenfun import *" + ] + }, + { + "cell_type": "markdown", + "id": "9ae78d5e", + "metadata": { + "editable": true + }, + "source": [ + "Note that MPI for Python ([mpi4py](https://bitbucket.org/mpi4py/mpi4py))\n", + "is a requirement for shenfun, but the current solver cannot be used with more\n", + "than one processor." + ] + }, + { + "cell_type": "markdown", + "id": "a178b88b", + "metadata": { + "editable": true + }, + "source": [ + "## Tensor product spaces\n", + "\n", + "\n", + "With the Galerkin method we need function spaces for both velocity and\n", + "pressure, as well as for the\n", + "nonlinear right hand side. A Dirichlet space will be used for velocity,\n", + "whereas there is no boundary restriction on the pressure space. For both\n", + "two-dimensional spaces we will use one basis function for the $x$-direction,\n", + "$\\mathcal{X}_k(x)$, and one for the $y$-direction, $\\mathcal{Y}_l(y)$. And\n", + "then we create two-dimensional basis functions like" + ] + }, + { + "cell_type": "markdown", + "id": "027c6861", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "v_{kl}(x, y) = \\mathcal{X}_k(x) \\mathcal{Y}_l(y), \\label{eq:nstestfunction} \\tag{1}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e5e81b40", + "metadata": { + "editable": true + }, + "source": [ + "and solutions (trial functions) as" + ] + }, + { + "cell_type": "markdown", + "id": "481b9ff7", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " u(x, y) = \\sum_{k}\\sum_{l} \\hat{u}_{kl} v_{kl}(x, y). \\label{eq:nstrialfunction} \\tag{2}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "7d65380f", + "metadata": { + "editable": true + }, + "source": [ + "For the homogeneous Dirichlet boundary condition the basis functions\n", + "$\\mathcal{X}_k(x)$ and $\\mathcal{Y}_l(y)$ are chosen as composite\n", + "Legendre polynomials (we could also use Chebyshev):" + ] + }, + { + "cell_type": "markdown", + "id": "182499a2", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\mathcal{X}_k(x) = L_k(x) - L_{k+2}(x), \\quad \\forall \\, k \\in \\boldsymbol{k}^{N_0-2}, \\label{eq:D0} \\tag{3} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "dbf64c5f", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\mathcal{Y}_l(y) = L_l(y) - L_{l+2}(y), \\quad \\forall \\, l \\in \\boldsymbol{l}^{N_1-2}, \\label{eq:D1} \\tag{4}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "b5c336dd", + "metadata": { + "editable": true + }, + "source": [ + "where $\\boldsymbol{k}^{N_0-2} = (0, 1, \\ldots, N_0-3)$, $\\boldsymbol{l}^{N_1-2} = (0, 1, \\ldots, N_1-3)$\n", + "and $N = (N_0, N_1)$ is the number\n", + "of quadrature points in each direction. Note that $N_0$ and $N_1$ do not need\n", + "to be the same. The basis funciton ([3](#eq:D0)) satisfies\n", + "the homogeneous Dirichlet boundary conditions at $x=\\pm 1$ and ([4](#eq:D1)) the same\n", + "at $y=\\pm 1$. As such, the basis function $v_{kl}(x, y)$ satisfies the homogeneous Dirichlet boundary\n", + "condition for the entire domain.\n", + "\n", + "With shenfun we create these homogeneous spaces, $D_0^{N_0}(x)=\\text{span}\\{L_k-L_{k+2}\\}_{k=0}^{N_0-2}$ and\n", + "$D_0^{N_1}(y)=\\text{span}\\{L_l-L_{l+2}\\}_{l=0}^{N_1-2}$ as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f1e8664d", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.595414Z", + "iopub.status.busy": "2024-05-24T12:37:02.595158Z", + "iopub.status.idle": "2024-05-24T12:37:02.619319Z", + "shell.execute_reply": "2024-05-24T12:37:02.618530Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "N = (45, 45)\n", + "family = 'Legendre' # or use 'Chebyshev'\n", + "quad = 'GL' # for Chebyshev use 'GC' or 'GL'\n", + "D0X = FunctionSpace(N[0], family, quad=quad, bc=(0, 0))\n", + "D0Y = FunctionSpace(N[1], family, quad=quad, bc=(0, 0))" + ] + }, + { + "cell_type": "markdown", + "id": "53084c3b", + "metadata": { + "editable": true + }, + "source": [ + "The spaces are here the same, but we will use `D0X` in the $x$-direction and\n", + "`D0Y` in the $y$-direction. But before we use these bases in\n", + "tensor product spaces, they remain identical as long as $N_0 = N_1$.\n", + "\n", + "Special attention is required by the moving lid. To get a solution\n", + "with nonzero boundary condition at $y=1$ we need to add one more basis function\n", + "that satisfies that solution. In general, a nonzero boundary condition\n", + "can be added on both sides of the domain using the following basis" + ] + }, + { + "cell_type": "markdown", + "id": "68d54031", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\mathcal{Y}_l(y) = L_l(y) - L_{l+2}(y), \\quad \\forall \\, l \\in \\boldsymbol{l}^{N_1-2}. \n", + "\\label{_auto1} \\tag{5}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f2e3221a", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\mathcal{Y}_{N_1-2}(y) = (L_0+L_1)/2 \\quad \\left(=(1+y)/2\\right), \n", + "\\label{_auto2} \\tag{6}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "de119ec2", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\mathcal{Y}_{N_1-1}(y) = (L_0-L_1)/2 \\quad \\left(=(1-y)/2\\right).\n", + "\\label{_auto3} \\tag{7}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "7ac8f98b", + "metadata": { + "editable": true + }, + "source": [ + "And then the unknown component $N_1-2$ decides the value at $y=1$, whereas\n", + "the unknown at $N_1-1$ decides the value at $y=-1$. Here we only need to\n", + "add the $N_1-2$ component, but for generality this is implemented in shenfun\n", + "using both additional basis functions. We create the space\n", + "$D_1^{N_1}(y)=\\text{span}\\{\\mathcal{Y}_l(y)\\}_{l=0}^{N_1-1}$ as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "496fa575", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.625766Z", + "iopub.status.busy": "2024-05-24T12:37:02.624855Z", + "iopub.status.idle": "2024-05-24T12:37:02.630379Z", + "shell.execute_reply": "2024-05-24T12:37:02.628970Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "D1Y = FunctionSpace(N[1], family, quad=quad, bc=(0, 1))" + ] + }, + { + "cell_type": "markdown", + "id": "53280b56", + "metadata": { + "editable": true + }, + "source": [ + "where `bc=(0, 1)` fixes the values for $y=-1$ and $y=1$, respectively.\n", + "For a regularized lid driven cavity the velocity of the top lid is\n", + "$(1-x)^2(1+x)^2$ and not unity. To implement this boundary condition\n", + "instead, we can make use of [sympy](https://www.sympy.org) and\n", + "quite straight forward do" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "522a6cb6", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.636290Z", + "iopub.status.busy": "2024-05-24T12:37:02.635531Z", + "iopub.status.idle": "2024-05-24T12:37:02.639151Z", + "shell.execute_reply": "2024-05-24T12:37:02.638734Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "import sympy\n", + "x = sympy.symbols('x')\n", + "#D1Y = FunctionSpace(N[1], family, quad=quad, bc=(0, (1-x)**2*(1+x)**2))" + ] + }, + { + "cell_type": "markdown", + "id": "eeab4c31", + "metadata": { + "editable": true + }, + "source": [ + "Uncomment the last line to run the regularized boundary conditions.\n", + "Otherwise, there is no difference at all between the regular and the\n", + "regularized lid driven cavity implementations.\n", + "\n", + "The pressure basis that comes with no restrictions for the boundary is a\n", + "little trickier. The reason for this has to do with\n", + "inf-sup stability. The obvious choice of basis functions are the\n", + "regular Legendre polynomials $L_k(x)$ in $x$ and $L_l(y)$ in the\n", + "$y$-directions. The problem is that for the natural choice of\n", + "$(k, l) \\in \\boldsymbol{k}^{N_0} \\times \\boldsymbol{l}^{N_1}$\n", + "there are nullspaces and the problem is not well-defined. It turns out\n", + "that the proper choice for the pressure basis is simply the regular\n", + "Legendre basis functions, but for\n", + "$(k, l) \\in \\boldsymbol{k}^{N_0-2} \\times \\boldsymbol{l}^{N_1-2}$.\n", + "The bases $P^{N_0}(x)=\\text{span}\\{L_k(x)\\}_{k=0}^{N_0-3}$ and\n", + "$P^{N_1}(y)=\\text{span}\\{L_l(y)\\}_{l=0}^{N_1-3}$ are created as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "395ae9db", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.641461Z", + "iopub.status.busy": "2024-05-24T12:37:02.641396Z", + "iopub.status.idle": "2024-05-24T12:37:02.646911Z", + "shell.execute_reply": "2024-05-24T12:37:02.645999Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "PX = FunctionSpace(N[0], family, quad=quad)\n", + "PY = FunctionSpace(N[1], family, quad=quad)\n", + "PX.slice = lambda: slice(0, N[0]-2)\n", + "PY.slice = lambda: slice(0, N[1]-2)" + ] + }, + { + "cell_type": "markdown", + "id": "b046d361", + "metadata": { + "editable": true + }, + "source": [ + "Note that we still use these spaces with the same $N_0 \\cdot N_1$\n", + "quadrature points in real space, but the two highest frequencies have\n", + "been set to zero.\n", + "\n", + "We have now created all relevant function spaces for the problem at hand.\n", + "It remains to combine these spaces into tensor product spaces, and to\n", + "combine tensor product spaces into mixed (coupled) tensor product\n", + "spaces. From the Dirichlet bases we create two different tensor\n", + "product spaces, whereas one is enough for the pressure" + ] + }, + { + "cell_type": "markdown", + "id": "9bd40c28", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "V_{1}^{\\boldsymbol{N}}(\\boldsymbol{x}) = D_0^{N_0}(x) \\otimes D_1^{N_1}(y), \n", + "\\label{_auto4} \\tag{8}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "8b9eeee7", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "V_{0}^{\\boldsymbol{N}}(\\boldsymbol{x}) = D_0^{N_0}(x) \\otimes D_0^{N_1}(y), \n", + "\\label{_auto5} \\tag{9}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "41f3ed7e", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "P^{\\boldsymbol{N}}(\\boldsymbol{x}) = P^{N_0}(x) \\otimes P^{N_1}(y).\n", + "\\label{_auto6} \\tag{10}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e27ae020", + "metadata": { + "editable": true + }, + "source": [ + "With shenfun the tensor product spaces are created as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "76747afc", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.651785Z", + "iopub.status.busy": "2024-05-24T12:37:02.651528Z", + "iopub.status.idle": "2024-05-24T12:37:02.680042Z", + "shell.execute_reply": "2024-05-24T12:37:02.679352Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "V1 = TensorProductSpace(comm, (D0X, D1Y))\n", + "V0 = TensorProductSpace(comm, (D0X, D0Y))\n", + "P = TensorProductSpace(comm, (PX, PY), modify_spaces_inplace=True)" + ] + }, + { + "cell_type": "markdown", + "id": "2ff12ff2", + "metadata": { + "editable": true + }, + "source": [ + "where ``modify_spaces_inplace=True`` makes use of ``PX`` and\n", + "``PY`` directly. These spaces have now been modified to fit in\n", + "the TensorProductSpace ``P``, along two different directions and as such\n", + "the original spaces have been modified. The default behavior in shenfun\n", + "is to make copies of the 1D spaces under the hood, and thus leave ``PX``\n", + "and ``PY`` untouched. In that case the two new and modified spaces would be accessible\n", + "from ``P.bases``.\n", + "\n", + "Note that all these tensor product spaces are scalar valued.\n", + "The velocity is a vector, and a vector requires a mixed vector basis like\n", + "$W_1^{\\boldsymbol{N}} = V_1^{\\boldsymbol{N}} \\times V_0^{\\boldsymbol{N}}$. The vector basis is created\n", + "in shenfun as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9cdaa7ab", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.685079Z", + "iopub.status.busy": "2024-05-24T12:37:02.684937Z", + "iopub.status.idle": "2024-05-24T12:37:02.688920Z", + "shell.execute_reply": "2024-05-24T12:37:02.687442Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "W1 = VectorSpace([V1, V0])\n", + "W0 = VectorSpace([V0, V0])" + ] + }, + { + "cell_type": "markdown", + "id": "d6ac99c7", + "metadata": { + "editable": true + }, + "source": [ + "Note that the second vector basis, $W_0^{\\boldsymbol{N}} = V_0^{\\boldsymbol{N}} \\times V_0^{\\boldsymbol{N}}$, uses\n", + "homogeneous boundary conditions throughout." + ] + }, + { + "cell_type": "markdown", + "id": "8a6e6122", + "metadata": { + "editable": true + }, + "source": [ + "## Mixed variational form\n", + "\n", + "\n", + "We now formulate a variational problem using the\n", + "Galerkin method: Find\n", + "$\\boldsymbol{u} \\in W_1^{\\boldsymbol{N}}$ and $p \\in P^{\\boldsymbol{N}}$ such that" + ] + }, + { + "cell_type": "markdown", + "id": "9247bcd5", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\int_{\\Omega} (\\nu \\nabla^2 \\boldsymbol{u} - \\nabla p ) \\cdot \\boldsymbol{v} \\, dxdy = \\int_{\\Omega} (\\nabla \\cdot \\boldsymbol{u}\\boldsymbol{u}) \\cdot \\boldsymbol{v}\\, dxdy \\quad\\forall \\boldsymbol{v} \\, \\in \\, W_0^{\\boldsymbol{N}}, \\label{eq:nsvarform} \\tag{11} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "10e0c889", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\int_{\\Omega} \\nabla \\cdot \\boldsymbol{u} \\, q \\, dxdy = 0 \\quad\\forall q \\, \\in \\, P^{\\boldsymbol{N}}.\n", + "\\label{_auto7} \\tag{12}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "0ecae3eb", + "metadata": { + "editable": true + }, + "source": [ + "Note that we are using test functions $\\boldsymbol{v}$ with homogeneous\n", + "boundary conditions.\n", + "\n", + "The first obvious issue with Eq ([11](#eq:nsvarform)) is the nonlinearity.\n", + "In other words we will\n", + "need to linearize and iterate to be able to solve these equations with\n", + "the Galerkin method. To this end we will introduce the solution on\n", + "iteration $k \\in [0, 1, \\ldots]$ as $\\boldsymbol{u}^k$ and compute the nonlinearity\n", + "using only known solutions\n", + "$\\int_{\\Omega} (\\nabla \\cdot \\boldsymbol{u}^k\\boldsymbol{u}^k) \\cdot \\boldsymbol{v}\\, dxdy$.\n", + "Using further integration by parts we end up with the equations to solve\n", + "for iteration number $k+1$ (using $\\boldsymbol{u} = \\boldsymbol{u}^{k+1}$ and $p=p^{k+1}$\n", + "for simplicity)" + ] + }, + { + "cell_type": "markdown", + "id": "6194c91b", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "-\\int_{\\Omega} \\nu \\nabla \\boldsymbol{u} \\, \\colon \\nabla \\boldsymbol{v} \\, dxdy + \\int_{\\Omega} p \\nabla \\cdot \\boldsymbol{v} \\, dxdy = \\int_{\\Omega} (\\nabla \\cdot \\boldsymbol{u}^k\\boldsymbol{u}^k) \\cdot \\boldsymbol{v}\\, dxdy \\quad\\forall \\boldsymbol{v} \\, \\in \\, W_0^{\\boldsymbol{N}}, \\label{eq:nsvarform2} \\tag{13} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "9a1bc12e", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\int_{\\Omega} \\nabla \\cdot \\boldsymbol{u} \\, q \\, dxdy = 0 \\quad\\forall q \\, \\in \\, P^{\\boldsymbol{N}}.\n", + "\\label{_auto8} \\tag{14}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "3ad1369a", + "metadata": { + "editable": true + }, + "source": [ + "Note that the nonlinear term may also be integrated by parts and\n", + "evaluated as $\\int_{\\Omega}-\\boldsymbol{u}^k\\boldsymbol{u}^k \\, \\colon \\nabla \\boldsymbol{v} \\, dxdy$. All\n", + "boundary integrals disappear since we are using test functions with\n", + "homogeneous boundary conditions.\n", + "\n", + "Since we are to solve for $\\boldsymbol{u}$ and $p$ at the same time, we formulate a\n", + "mixed (coupled) problem: find $(\\boldsymbol{u}, p) \\in W_1^{\\boldsymbol{N}} \\times P^{\\boldsymbol{N}}$\n", + "such that" + ] + }, + { + "cell_type": "markdown", + "id": "9d7704be", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "a((\\boldsymbol{u}, p), (\\boldsymbol{v}, q)) = L((\\boldsymbol{v}, q)) \\quad \\forall (\\boldsymbol{v}, q) \\in W_0^{\\boldsymbol{N}} \\times P^{\\boldsymbol{N}},\n", + "\\label{_auto9} \\tag{15}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1004cd02", + "metadata": { + "editable": true + }, + "source": [ + "where bilinear ($a$) and linear ($L$) forms are given as" + ] + }, + { + "cell_type": "markdown", + "id": "9bd71ce1", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " a((\\boldsymbol{u}, p), (\\boldsymbol{v}, q)) = -\\int_{\\Omega} \\nu \\nabla \\boldsymbol{u} \\, \\colon \\nabla \\boldsymbol{v} \\, dxdy + \\int_{\\Omega} p \\nabla \\cdot \\boldsymbol{v} \\, dxdy + \\int_{\\Omega} \\nabla \\cdot \\boldsymbol{u} \\, q \\, dxdy, \n", + "\\label{_auto10} \\tag{16}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "068f2a78", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " L((\\boldsymbol{v}, q); \\boldsymbol{u}^{k}) = \\int_{\\Omega} (\\nabla \\cdot \\boldsymbol{u}^{k}\\boldsymbol{u}^{k}) \\cdot \\boldsymbol{v}\\, dxdy.\n", + "\\label{_auto11} \\tag{17}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "55eeb8fb", + "metadata": { + "editable": true + }, + "source": [ + "Note that the bilinear form will assemble to a block matrix, whereas the right hand side\n", + "linear form will assemble to a block vector. The bilinear form does not change\n", + "with the solution and as such it does not need to be reassembled inside\n", + "an iteration loop.\n", + "\n", + "The algorithm used to solve the equations are:\n", + "\n", + " * Set $k = 0$\n", + "\n", + " * Guess $\\boldsymbol{u}^0 = (0, 0)$\n", + "\n", + " * while not converged:\n", + "\n", + " * assemble $L((\\boldsymbol{v}, q); \\boldsymbol{u}^{k})$\n", + "\n", + " * solve $a((\\boldsymbol{u}, p), (\\boldsymbol{v}, q)) = L((\\boldsymbol{v}, q); \\boldsymbol{u}^{k})$ for $\\boldsymbol{u}^{k+1}, p^{k+1}$\n", + "\n", + " * compute error = $\\int_{\\Omega} (\\boldsymbol{u}^{k+1}-\\boldsymbol{u}^{k})^2 \\, dxdy$\n", + "\n", + " * if error $<$ some tolerance then converged = True\n", + "\n", + " * $k$ += $1$" + ] + }, + { + "cell_type": "markdown", + "id": "352eed28", + "metadata": { + "editable": true + }, + "source": [ + "## Implementation of solver\n", + "\n", + "We will now implement the coupled variational problem described in previous\n", + "sections. First of all, since we want to solve for the velocity and pressure\n", + "in a coupled solver, we have to\n", + "create a mixed tensor product space $VQ = W_1^{\\boldsymbol{N}} \\times P^{\\boldsymbol{N}}$ that\n", + "couples velocity and pressure" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "53b8bee6", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.694219Z", + "iopub.status.busy": "2024-05-24T12:37:02.694096Z", + "iopub.status.idle": "2024-05-24T12:37:02.696046Z", + "shell.execute_reply": "2024-05-24T12:37:02.695694Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "VQ = CompositeSpace([W1, P]) # Coupling velocity and pressure" + ] + }, + { + "cell_type": "markdown", + "id": "eb737566", + "metadata": { + "editable": true + }, + "source": [ + "We can now create test- and trialfunctions for the coupled space $VQ$,\n", + "and then split them up into components afterwards:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8aa77ff2", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.701366Z", + "iopub.status.busy": "2024-05-24T12:37:02.700775Z", + "iopub.status.idle": "2024-05-24T12:37:02.705052Z", + "shell.execute_reply": "2024-05-24T12:37:02.703879Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "up = TrialFunction(VQ)\n", + "vq = TestFunction(VQ)\n", + "u, p = up\n", + "v, q = vq" + ] + }, + { + "cell_type": "markdown", + "id": "980d2ae6", + "metadata": { + "editable": true + }, + "source": [ + ":::{note}\n", + "The test function `v` is using homogeneous Dirichlet boundary conditions even\n", + "though it is derived from `VQ`, which contains `W1`. It is currently not (and will\n", + "probably never be) possible to use test functions with inhomogeneous\n", + "boundary conditions.\n", + ":::\n", + "\n", + "With the basisfunctions in place we may assemble the different blocks of the\n", + "final coefficient matrix. For this we also need to specify the kinematic\n", + "viscosity, which is given here in terms of the Reynolds number:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "31f39748", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.709539Z", + "iopub.status.busy": "2024-05-24T12:37:02.709325Z", + "iopub.status.idle": "2024-05-24T12:37:02.732543Z", + "shell.execute_reply": "2024-05-24T12:37:02.731445Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "Re = 100.\n", + "nu = 2./Re\n", + "if family.lower() == 'legendre':\n", + " A = inner(grad(v), -nu*grad(u))\n", + " G = inner(div(v), p)\n", + "else:\n", + " A = inner(v, nu*div(grad(u)))\n", + " G = inner(v, -grad(p))\n", + "D = inner(q, div(u))" + ] + }, + { + "cell_type": "markdown", + "id": "89cba222", + "metadata": { + "editable": true + }, + "source": [ + "The assembled subsystems `A, G` and `D` are lists containg the different blocks of\n", + "the complete, coupled, coefficient matrix. `A` actually contains 4\n", + "tensor product matrices of type [TPMatrix](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.matrixbase.TPMatrix). The first two\n", + "matrices are for vector component zero of the test function `v[0]` and\n", + "trial function `u[0]`, the\n", + "matrices 2 and 3 are for components 1. The first two matrices are as such for" + ] + }, + { + "cell_type": "markdown", + "id": "b2f5defb", + "metadata": { + "editable": true + }, + "source": [ + " A[0:2] = inner(grad(v[0]), -nu*grad(u[0]))\n" + ] + }, + { + "cell_type": "markdown", + "id": "62fb6b73", + "metadata": { + "editable": true + }, + "source": [ + "Breaking it down the inner product is mathematically" + ] + }, + { + "cell_type": "markdown", + "id": "e8508c5a", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\label{eq:partialeq1} \\tag{18}\n", + "\\int_{\\Omega}-\\nu \\left(\\frac{\\partial \\boldsymbol{v}[0]}{\\partial x}, \\frac{\\partial \\boldsymbol{v}[0]}{\\partial y}\\right) \\cdot \\left(\\frac{\\partial \\boldsymbol{u}[0]}{\\partial x}, \\frac{\\partial \\boldsymbol{u}[0]}{\\partial y}\\right) dx dy .\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "232abb61", + "metadata": { + "editable": true + }, + "source": [ + "We can now insert for test function $\\boldsymbol{v}[0]$" + ] + }, + { + "cell_type": "markdown", + "id": "9eb8662d", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\boldsymbol{v}[0]_{kl} = \\mathcal{X}_k \\mathcal{Y}_l, \\quad (k, l) \\in \\boldsymbol{k}^{N_0-2} \\times \\boldsymbol{l}^{N_1-2}\n", + "\\label{_auto12} \\tag{19}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "4e50aac5", + "metadata": { + "editable": true + }, + "source": [ + "and trialfunction" + ] + }, + { + "cell_type": "markdown", + "id": "ced7ddd5", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\boldsymbol{u}[0]_{mn} = \\sum_{m=0}^{N_0-3} \\sum_{n=0}^{N_1-1} \\hat{\\boldsymbol{u}}[0]_{mn} \\mathcal{X}_m \\mathcal{Y}_n,\n", + "\\label{_auto13} \\tag{20}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "4cf2aa34", + "metadata": { + "editable": true + }, + "source": [ + "where $\\hat{\\boldsymbol{u}}$ are the unknown degrees of freedom for the velocity vector.\n", + "Notice that the sum over the second\n", + "index runs all the way to $N_1-1$, whereas the other indices runs to either\n", + "$N_0-3$ or $N_1-3$. This is because of the additional basis functions required\n", + "for the inhomogeneous boundary condition.\n", + "\n", + "Inserting for these basis functions into ([18](#eq:partialeq1)), we obtain after a few trivial\n", + "manipulations" + ] + }, + { + "cell_type": "markdown", + "id": "ff48c66d", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " -\\sum_{m=0}^{N_0-3} \\sum_{n=0}^{N_1-1} \\nu \\Big( \\underbrace{\\int_{-1}^{1} \\frac{\\partial \\mathcal{X}_k}{\\partial x} \\frac{\\partial \\mathcal{X}_m}{\\partial x} dx \\int_{-1}^{1} \\mathcal{Y}_l \\mathcal{Y}_n dy}_{A[0]} + \\underbrace{\\int_{-1}^{1} \\mathcal{X}_k X_m dx \\int_{-1}^{1} \\frac{\\partial \\mathcal{Y}_l}{\\partial y} \\frac{\\partial \\mathcal{Y}_n}{\\partial y} dy}_{A[1]} \\Big) \\hat{\\boldsymbol{u}}[0]_{mn}.\n", + "\\label{_auto14} \\tag{21}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e5db0d4c", + "metadata": { + "editable": true + }, + "source": [ + "We see that each tensor product matrix (both A[0] and A[1]) is composed as\n", + "outer products of two smaller matrices, one for each dimension.\n", + "The first tensor product matrix, A[0], is" + ] + }, + { + "cell_type": "markdown", + "id": "57725c54", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\underbrace{\\int_{-1}^{1} \\frac{\\partial \\mathcal{X}_k}{\\partial x} \\frac{\\partial \\mathcal{X}_m}{\\partial x} dx}_{c_{km}} \\underbrace{\\int_{-1}^{1} \\mathcal{Y}_l \\mathcal{Y}_n dy}_{f_{ln}}\n", + "\\label{_auto15} \\tag{22}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "6c7aa78d", + "metadata": { + "editable": true + }, + "source": [ + "where $C\\in \\mathbb{R}^{N_0-2 \\times N_1-2}$ and $F \\in \\mathbb{R}^{N_0-2 \\times N_1}$.\n", + "Note that due to the inhomogeneous boundary conditions this last matrix $F$\n", + "is actually not square. However, remember that all contributions from the two highest\n", + "degrees of freedom ($\\hat{\\boldsymbol{u}}[0]_{m,N_1-2}$ and $\\hat{\\boldsymbol{u}}[0]_{m,N_1-1}$) are already\n", + "known and they can, as such, be moved directly over to the right hand side of the\n", + "linear algebra system that is to be solved. More precisely, we can split the\n", + "tensor product matrix into two contributions and obtain" + ] + }, + { + "cell_type": "markdown", + "id": "7a9bb9a5", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\sum_{m=0}^{N_0-3}\\sum_{n=0}^{N_1-1} c_{km}f_{ln} \\hat{\\boldsymbol{u}}[0]_{m, n} = \\sum_{m=0}^{N_0-3}\\sum_{n=0}^{N_1-3}c_{km}f_{ln}\\hat{\\boldsymbol{u}}[0]_{m, n} + \\sum_{m=0}^{N_0-3}\\sum_{n=N_1-2}^{N_1-1}c_{km}f_{ln}\\hat{\\boldsymbol{u}}[0]_{m, n}, \\quad \\forall (k, l) \\in \\boldsymbol{k}^{N_0-2} \\times \\boldsymbol{l}^{N_1-2},\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "479af7cb", + "metadata": { + "editable": true + }, + "source": [ + "where the first term on the right hand side is square and the second term is known and\n", + "can be moved to the right hand side of the linear algebra equation system.\n", + "\n", + "At this point all matrices, both regular and boundary matrices, are\n", + "contained within the three lists A, G and D. We can now create a solver\n", + "for block matrices that incorporates these boundary conditions\n", + "automatically" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7e7fa5c6", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.741024Z", + "iopub.status.busy": "2024-05-24T12:37:02.740461Z", + "iopub.status.idle": "2024-05-24T12:37:02.743649Z", + "shell.execute_reply": "2024-05-24T12:37:02.743228Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "sol = la.BlockMatrixSolver(A+G+D)" + ] + }, + { + "cell_type": "markdown", + "id": "8fc81725", + "metadata": { + "editable": true + }, + "source": [ + "In the solver `sol` there is now a regular block matrix found in\n", + "`sol.mat`, which is the symmetric" + ] + }, + { + "cell_type": "markdown", + "id": "2bdc1587", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{bmatrix}\n", + " A[0]+A[1] & 0 & G[0] \\\\ \n", + " 0 & A[2]+A[3] & G[1] \\\\ \n", + " D[0] & D[1] & 0\n", + " \\end{bmatrix}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "98bab253", + "metadata": { + "editable": true + }, + "source": [ + "The boundary matrices are similarly collected in a boundary block matrix\n", + "in `sol.bc_mat`. This matrix is used under the hood to modify the\n", + "right hand side.\n", + "\n", + "We now have all the matrices we need in order to solve the Navier Stokes equations.\n", + "However, we also need some work arrays for iterations" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bd70fd5d", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.748478Z", + "iopub.status.busy": "2024-05-24T12:37:02.748287Z", + "iopub.status.idle": "2024-05-24T12:37:02.754294Z", + "shell.execute_reply": "2024-05-24T12:37:02.752368Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "# Create Function to hold solution. Use set_boundary_dofs to fix the degrees\n", + "# of freedom in uh_hat that determines the boundary conditions.\n", + "uh_hat = Function(VQ).set_boundary_dofs()\n", + "ui_hat = uh_hat[0]\n", + "\n", + "# New solution (iterative)\n", + "uh_new = Function(VQ).set_boundary_dofs()\n", + "ui_new = uh_new[0]" + ] + }, + { + "cell_type": "markdown", + "id": "e6879887", + "metadata": { + "editable": true + }, + "source": [ + "The nonlinear right hand side also requires some additional attention.\n", + "Nonlinear terms are usually computed in physical space before transforming\n", + "to spectral. For this we need to evaluate the velocity vector on the\n", + "quadrature mesh. We also need a rank 2 Array to hold the outer\n", + "product $\\boldsymbol{u}\\boldsymbol{u}$. The required arrays and spaces are\n", + "created as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "38b7fc85", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.758467Z", + "iopub.status.busy": "2024-05-24T12:37:02.758100Z", + "iopub.status.idle": "2024-05-24T12:37:02.761979Z", + "shell.execute_reply": "2024-05-24T12:37:02.761600Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "bh_hat = Function(VQ)\n", + "\n", + "# Create arrays to hold velocity vector solution\n", + "ui = Array(W1)\n", + "\n", + "# Create work arrays for nonlinear part\n", + "QT = CompositeSpace([W1, W0]) # for uiuj\n", + "uiuj = Array(QT)\n", + "uiuj_hat = Function(QT)" + ] + }, + { + "cell_type": "markdown", + "id": "fcb47ed7", + "metadata": { + "editable": true + }, + "source": [ + "The right hand side $L((\\boldsymbol{v}, q);\\boldsymbol{u}^{k});$ is computed in its\n", + "own function `compute_rhs` as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bf45c299", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.763955Z", + "iopub.status.busy": "2024-05-24T12:37:02.763889Z", + "iopub.status.idle": "2024-05-24T12:37:02.766473Z", + "shell.execute_reply": "2024-05-24T12:37:02.766041Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "def compute_rhs(ui_hat, bh_hat):\n", + " global ui, uiuj, uiuj_hat, V1, bh_hat0\n", + " bh_hat.fill(0)\n", + " ui = W1.backward(ui_hat, ui)\n", + " uiuj = outer(ui, ui, uiuj)\n", + " uiuj_hat = uiuj.forward(uiuj_hat)\n", + " bi_hat = bh_hat[0]\n", + " bi_hat = inner(v, div(uiuj_hat), output_array=bi_hat)\n", + " #bi_hat = inner(grad(v), -uiuj_hat, output_array=bi_hat)\n", + " return bh_hat" + ] + }, + { + "cell_type": "markdown", + "id": "880ad1d9", + "metadata": { + "editable": true + }, + "source": [ + "Here [outer()](https://shenfun.readthedocs.io/en/latest/shenfun.utilities.html#shenfun.utilities.outer) is a shenfun function that computes the\n", + "outer product of two vectors and returns the product in a rank two\n", + "array (here `uiuj`). With `uiuj` forward transformed to `uiuj_hat`\n", + "we can assemble the linear form either as `inner(v, div(uiuj_hat)` or\n", + "`inner(grad(v), -uiuj_hat)`.\n", + "\n", + "Now all that remains is to guess an initial solution and solve\n", + "iteratively until convergence. For initial solution we simply set the\n", + "velocity and pressure to zero. With an initial solution we are ready\n", + "to start iterating.\n", + "However, for convergence it is necessary to add some underrelaxation $\\alpha$,\n", + "and update the solution each time step as" + ] + }, + { + "cell_type": "markdown", + "id": "7222104f", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{align*}\n", + "\\hat{\\boldsymbol{u}}^{k+1} &= \\alpha \\hat{\\boldsymbol{u}}^* + (1-\\alpha)\\hat{\\boldsymbol{u}}^{k},\\\\ \n", + "\\hat{p}^{k+1} &= \\alpha \\hat{p}^* + (1-\\alpha)\\hat{p}^{k},\n", + "\\end{align*}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "387876a5", + "metadata": { + "editable": true + }, + "source": [ + "where $\\hat{\\boldsymbol{u}}^*$ and $\\hat{p}^*$ are the newly computed velocity\n", + "and pressure returned from `M.solve`. Without underrelaxation the solution\n", + "will quickly blow up. The iteration loop goes as follows" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cf3cb47b", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:02.771196Z", + "iopub.status.busy": "2024-05-24T12:37:02.770737Z", + "iopub.status.idle": "2024-05-24T12:37:05.592939Z", + "shell.execute_reply": "2024-05-24T12:37:05.592568Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "converged = False\n", + "count = 0\n", + "alfa = 0.5\n", + "while not converged:\n", + " count += 1\n", + " bh_hat = compute_rhs(ui_hat, bh_hat)\n", + " uh_new = sol(bh_hat, u=uh_new, constraints=((2, 0, 0),))\n", + " error = np.linalg.norm(ui_hat-ui_new)\n", + " uh_hat[:] = alfa*uh_new + (1-alfa)*uh_hat\n", + " converged = abs(error) < 1e-8 or count >= 100\n", + " print('Iteration %d Error %2.4e' %(count, error))\n", + "\n", + "up = uh_hat.backward()\n", + "u, p = up\n", + "\n", + "X = V0.local_mesh(True)\n", + "plt.figure()\n", + "plt.quiver(X[0], X[1], u[0], u[1])" + ] + }, + { + "cell_type": "markdown", + "id": "f392e652", + "metadata": { + "editable": true + }, + "source": [ + "Note that the `constraints=((2, 0, 0),)` keyword argument\n", + "ensures that the pressure integrates to zero, i.e., $\\int_{\\Omega} p \\omega dxdy=0$.\n", + "Here the number 2 tells us that block component 2 in the mixed space\n", + "(the pressure) should be integrated, dof 0 should be fixed, and it\n", + "should be fixed to 0.\n", + "\n", + "The last three lines plots velocity vectors, like also seen in the [figure 1](#fig:drivencavity)\n", + "in the top of this demo. The solution is apparently nice\n", + "and smooth, but hidden underneath are Gibbs oscillations from the\n", + "corner discontinuities. This is painfully obvious when switching from\n", + "Legendre to Chebyshev polynomials. With Chebyshev the same plot looks\n", + "like the [Figure 2](#fig:drivencavitycheb) below. However, choosing instead the\n", + "regularized lid, with no discontinuities, the solutions will be nice and\n", + "smooth, both for Legendre and Chebyshev polynomials.\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "

Figure 2: Velocity vectors for Re=100 using Chebyshev.

\n", + "" + ] + }, + { + "cell_type": "markdown", + "id": "b02c599f", + "metadata": { + "editable": true + }, + "source": [ + "## Complete solver\n", + "\n", + "\n", + "A complete solver can be found in demo [NavierStokesDrivenCavity.py](https://github.com/spectralDNS/shenfun/blob/master/demo/NavierStokesDrivenCavity.py)." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/Functions/functions.ipynb b/docs/demos/Functions/functions.ipynb new file mode 100644 index 00000000..57e3059c --- /dev/null +++ b/docs/demos/Functions/functions.ipynb @@ -0,0 +1,1327 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "f3038a60", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - Working with Functions\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **August 7, 2020**\n", + "\n", + "**Summary.** This is a demonstration of how the Python module [shenfun](https://github.com/spectralDNS/shenfun) can be used to work with\n", + "global spectral functions in one and several dimensions." + ] + }, + { + "cell_type": "markdown", + "id": "be63430d", + "metadata": { + "editable": true + }, + "source": [ + "## Construction\n", + "\n", + "A global spectral function $u(x)$ can be represented on the real line as" + ] + }, + { + "cell_type": "markdown", + "id": "75869282", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "u(x) = \\sum_{k=0}^{N-1} \\hat{u}_k \\psi_k(x), \\quad x \\in \\Omega = [a, b],\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "174c39e0", + "metadata": { + "editable": true + }, + "source": [ + "where the domain $\\Omega$ has to be defined such that $b > a$.\n", + "The array $\\{\\hat{u}_k\\}_{k=0}^{N-1}$ contains the\n", + "expansion coefficient for the series, often referred to as the\n", + "degrees of freedom. There is one degree of freedom per basis function and\n", + "$\\psi_k(x)$ is the $k$'th basis function.\n", + "We can use any number of basis functions,\n", + "and the span of the chosen basis is then a function space. Also part of the\n", + "function space is the domain, which is\n", + "specified when a function space is created. To create a function space\n", + "$T=\\text{span}\\{T_k\\}_{k=0}^{N-1}$ for\n", + "the first N Chebyshev polynomials of the first kind on the default domain $[-1, 1]$,\n", + "do" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f17eb498", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:24.305451Z", + "iopub.status.busy": "2024-05-24T12:37:24.305372Z", + "iopub.status.idle": "2024-05-24T12:37:24.897648Z", + "shell.execute_reply": "2024-05-24T12:37:24.897199Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from shenfun import *\n", + "N = 8\n", + "T = FunctionSpace(N, 'Chebyshev', domain=(-1, 1))" + ] + }, + { + "cell_type": "markdown", + "id": "51d18e17", + "metadata": { + "editable": true + }, + "source": [ + "The function $u(x)$ can now be created with all N coefficients\n", + "equal to zero as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b77b3fc9", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:24.900143Z", + "iopub.status.busy": "2024-05-24T12:37:24.899852Z", + "iopub.status.idle": "2024-05-24T12:37:24.901950Z", + "shell.execute_reply": "2024-05-24T12:37:24.901605Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u = Function(T)" + ] + }, + { + "cell_type": "markdown", + "id": "791e8067", + "metadata": { + "editable": true + }, + "source": [ + "When using Chebyshev polynomials the computational domain is always\n", + "$[-1, 1]$. However, we can still use a different physical domain,\n", + "like" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8ec4daad", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:24.903967Z", + "iopub.status.busy": "2024-05-24T12:37:24.903849Z", + "iopub.status.idle": "2024-05-24T12:37:24.906523Z", + "shell.execute_reply": "2024-05-24T12:37:24.905958Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "T = FunctionSpace(N, 'Chebyshev', domain=(0, 1))" + ] + }, + { + "cell_type": "markdown", + "id": "c08835aa", + "metadata": { + "editable": true + }, + "source": [ + "and under the hood shenfun will then map this domain to the reference\n", + "domain through" + ] + }, + { + "cell_type": "markdown", + "id": "ab3b7822", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "u(x) = \\sum_{k=0}^{N-1} \\hat{u}_k \\psi_k(2(x-0.5))\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "ca3cb4d4", + "metadata": { + "editable": true + }, + "source": [ + "## Approximating analytical functions\n", + "\n", + "The `u` function above was created with only zero\n", + "valued coefficients, which is the default. Alternatively,\n", + "a [Function](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Function) may be initialized using a constant\n", + "value" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "761f5f53", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:24.909043Z", + "iopub.status.busy": "2024-05-24T12:37:24.908934Z", + "iopub.status.idle": "2024-05-24T12:37:24.911054Z", + "shell.execute_reply": "2024-05-24T12:37:24.910669Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "T = FunctionSpace(N, 'Chebyshev', domain=(-1, 1))\n", + "u = Function(T, val=1)" + ] + }, + { + "cell_type": "markdown", + "id": "36f77fe7", + "metadata": { + "editable": true + }, + "source": [ + "but that is not very useful. A third method to initialize\n", + "a [Function](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Function) is to interpolate using an analytical\n", + "Sympy function." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b9ad36a9", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:24.913202Z", + "iopub.status.busy": "2024-05-24T12:37:24.913100Z", + "iopub.status.idle": "2024-05-24T12:37:24.921840Z", + "shell.execute_reply": "2024-05-24T12:37:24.921468Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "import sympy as sp\n", + "x = sp.Symbol('x', real=True)\n", + "u = Function(T, buffer=4*x**3-3*x)\n", + "print(u)" + ] + }, + { + "cell_type": "markdown", + "id": "4a9048d9", + "metadata": { + "editable": true + }, + "source": [ + "Here the analytical Sympy function will first be evaluated\n", + "on the entire quadrature mesh of the `T` function space,\n", + "and then forward transformed to get the coefficients. This\n", + "corresponds to a finite-dimensional projection to `T`.\n", + "The projection is\n", + "\n", + "Find $u_h \\in T$, such that" + ] + }, + { + "cell_type": "markdown", + "id": "27a6add1", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "(u_h - u, v)^{N}_w = 0 \\quad \\forall v \\in T, \\label{eq:proj1} \\tag{1} \n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e76306fe", + "metadata": { + "editable": true + }, + "source": [ + "where $v$ is a test function and\n", + "$u_h=\\sum_{k=0}^{N-1} \\hat{u}_k T_k$ is a trial function. The\n", + "notation $(\\cdot, \\cdot)^N_w$ represents a discrete version of\n", + "the weighted inner product $(u, v)_w$ defined as" + ] + }, + { + "cell_type": "markdown", + "id": "3ed95d25", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "(u, v)_{\\omega} = \\int_{\\Omega} u \\overline{v} \\omega d\\Omega,\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "a26f170f", + "metadata": { + "editable": true + }, + "source": [ + "where $\\omega(x)$ is a weight functions and $\\overline{v}$ is the\n", + "complex conjugate of $v$. If $v$ is\n", + "a real function, then $\\overline{v}=v$.\n", + "With quadrature we approximate the integral such that" + ] + }, + { + "cell_type": "markdown", + "id": "b801c1d1", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "(u, v)_{\\omega} \\approx (u, v)^N_{\\omega} = \\sum_{j\\in\\mathcal{I}^N} u(x_j) v(x_j) w_j.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "c2a63677", + "metadata": { + "editable": true + }, + "source": [ + "where the index set $\\mathcal{I}^N = \\{0, 1, \\ldots, N-1\\}$ and $\\{x_j\\}_{j\\in \\mathcal{I}^N}$ and $\\{w_j\\}_{j\\in \\mathcal{I}^N}$\n", + "are the quadrature points and weights.\n", + "\n", + "A linear system of equations arise when inserting for the chosen\n", + "basis functions in Eq. ([1](#eq:proj1)). We get" + ] + }, + { + "cell_type": "markdown", + "id": "aee62172", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\sum_{k\\in \\mathcal{I}^N} \\left( T_k, T_i\\right)^N_{\\omega} \\hat{u}_k =\n", + "\\left(u, T_i\\right)^N_{\\omega}\\, \\forall \\, i \\in \\mathcal{I}^N,\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "0b6dffc4", + "metadata": { + "editable": true + }, + "source": [ + "In matrix notation the solution becomes" + ] + }, + { + "cell_type": "markdown", + "id": "35773a2f", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\boldsymbol{\\hat{u}} = A^{-1} \\boldsymbol{\\tilde{u}},\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "09d7d46b", + "metadata": { + "editable": true + }, + "source": [ + "where we use two column vectors $\\boldsymbol{\\hat{u}}=(\\hat{u}_i)^T_{i\\in \\mathcal{I}^N}$,\n", + "$\\boldsymbol{\\tilde{u}}=\\left(\\tilde{u}_i\\right)^T_{i \\in \\mathcal{I}^N}$,\n", + "$\\tilde{u}_i = (u, T_i)^N_{\\omega}$ and the matrix\n", + "$A=(a_{ik}) \\in \\mathbb{R}^{N \\times N}$, that is diagonal with\n", + "$a_{ik}=\\left( T_k, T_i\\right)^N_{\\omega}$. For the default\n", + "Gauss-Chebyshev quadrature this matrix is $a_{ik} = c_i \\pi/2 \\delta_{ik}$,\n", + "where $c_0=2$ and $c_i=1$ for $i>0$." + ] + }, + { + "cell_type": "markdown", + "id": "a93601a6", + "metadata": { + "editable": true + }, + "source": [ + "## Adaptive function size\n", + "\n", + "The number of basis functions can also be left open during creation\n", + "of the function space, through" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6b3431b4", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:24.925102Z", + "iopub.status.busy": "2024-05-24T12:37:24.924966Z", + "iopub.status.idle": "2024-05-24T12:37:24.928595Z", + "shell.execute_reply": "2024-05-24T12:37:24.927405Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "T = FunctionSpace(0, 'Chebyshev', domain=(-1, 1))" + ] + }, + { + "cell_type": "markdown", + "id": "b919c637", + "metadata": { + "editable": true + }, + "source": [ + "This is useful if you want to approximate a function and\n", + "are uncertain how many basis functions that are required.\n", + "For example, you may want to approximate the function $\\cos(20 x)$.\n", + "You can then find the required [Function](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Function) using" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9a55e6d5", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:24.931772Z", + "iopub.status.busy": "2024-05-24T12:37:24.931577Z", + "iopub.status.idle": "2024-05-24T12:37:24.960845Z", + "shell.execute_reply": "2024-05-24T12:37:24.960343Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u = Function(T, buffer=sp.cos(20*x))\n", + "print(len(u))" + ] + }, + { + "cell_type": "markdown", + "id": "07d341ea", + "metadata": { + "editable": true + }, + "source": [ + "We see that $N=45$ is required to resolve this function. This agrees\n", + "well with what is reported also by [Chebfun](https://www.chebfun.org/docs/guide/guide01.html).\n", + "Note that in this process a new [FunctionSpace()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.FunctionSpace) has been\n", + "created under the hood. The function space of `u` can be\n", + "extracted using" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d6cdcdb9", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:24.964705Z", + "iopub.status.busy": "2024-05-24T12:37:24.964158Z", + "iopub.status.idle": "2024-05-24T12:37:24.967976Z", + "shell.execute_reply": "2024-05-24T12:37:24.967525Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "Tu = u.function_space()\n", + "print(Tu.N)" + ] + }, + { + "cell_type": "markdown", + "id": "cd42b044", + "metadata": { + "editable": true + }, + "source": [ + "To further show that shenfun is compatible with Chebfun we can also\n", + "approximate the Bessel function" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f3f6e277", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:24.970095Z", + "iopub.status.busy": "2024-05-24T12:37:24.970019Z", + "iopub.status.idle": "2024-05-24T12:37:25.000706Z", + "shell.execute_reply": "2024-05-24T12:37:24.999982Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "T1 = FunctionSpace(0, 'Chebyshev', domain=(0, 100))\n", + "u = Function(T1, buffer=sp.besselj(0, x))\n", + "print(len(u))" + ] + }, + { + "cell_type": "markdown", + "id": "527bcff6", + "metadata": { + "editable": true + }, + "source": [ + "which gives 83 basis functions, in close agreement with Chebfun (89).\n", + "The difference lies only in the cut-off criteria. We cut frequencies\n", + "with a relative tolerance of 1e-12 by default, but if we make this criteria\n", + "a little bit stronger, then we will also arrive at a slightly higher number:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f909dbb0", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:25.004338Z", + "iopub.status.busy": "2024-05-24T12:37:25.004225Z", + "iopub.status.idle": "2024-05-24T12:37:25.015645Z", + "shell.execute_reply": "2024-05-24T12:37:25.015180Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u = Function(T1, buffer=sp.besselj(0, x), reltol=1e-14)\n", + "print(len(u))" + ] + }, + { + "cell_type": "markdown", + "id": "631b5bda", + "metadata": { + "editable": true + }, + "source": [ + "Plotting the function on its quadrature points looks\n", + "a bit ragged, though:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "24ce622f", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:25.017665Z", + "iopub.status.busy": "2024-05-24T12:37:25.017590Z", + "iopub.status.idle": "2024-05-24T12:37:25.314535Z", + "shell.execute_reply": "2024-05-24T12:37:25.312802Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "Tu = u.function_space()\n", + "plt.plot(Tu.mesh(), u.backward());" + ] + }, + { + "cell_type": "markdown", + "id": "0c9b4803", + "metadata": { + "editable": true + }, + "source": [ + "To improve the quality of this plot we can instead evaluate the\n", + "function on more points" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "aa3f4008", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:25.322315Z", + "iopub.status.busy": "2024-05-24T12:37:25.321796Z", + "iopub.status.idle": "2024-05-24T12:37:25.406543Z", + "shell.execute_reply": "2024-05-24T12:37:25.402731Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "xj = np.linspace(0, 100, 1000)\n", + "plt.plot(xj, u(xj));" + ] + }, + { + "cell_type": "markdown", + "id": "f56c9597", + "metadata": { + "editable": true + }, + "source": [ + "Alternatively, we can refine the function, which simply\n", + "pads zeros to $\\hat{u}$" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "39cb107e", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:25.413155Z", + "iopub.status.busy": "2024-05-24T12:37:25.412715Z", + "iopub.status.idle": "2024-05-24T12:37:25.621446Z", + "shell.execute_reply": "2024-05-24T12:37:25.620380Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "up = u.refine(200)\n", + "Tp = up.function_space()\n", + "plt.plot(Tp.mesh(), up.backward());" + ] + }, + { + "cell_type": "markdown", + "id": "df254f80", + "metadata": { + "editable": true + }, + "source": [ + "The padded expansion coefficients are now given as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "760bd263", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:25.625839Z", + "iopub.status.busy": "2024-05-24T12:37:25.625660Z", + "iopub.status.idle": "2024-05-24T12:37:25.633356Z", + "shell.execute_reply": "2024-05-24T12:37:25.630655Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "print(up)" + ] + }, + { + "cell_type": "markdown", + "id": "2773efbb", + "metadata": { + "editable": true + }, + "source": [ + "## More features\n", + "\n", + "Since we have used a regular Chebyshev basis above, there\n", + "are many more features that could be explored simply by going through\n", + "[Numpy's Chebyshev module](https://numpy.org/doc/stable/reference/routines.polynomials.chebyshev.html).\n", + "For example, we can create a Chebyshev series like" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ef085fb4", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:25.637493Z", + "iopub.status.busy": "2024-05-24T12:37:25.636911Z", + "iopub.status.idle": "2024-05-24T12:37:25.641331Z", + "shell.execute_reply": "2024-05-24T12:37:25.640169Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "import numpy.polynomial.chebyshev as cheb\n", + "c = cheb.Chebyshev(u, domain=(0, 100))" + ] + }, + { + "cell_type": "markdown", + "id": "a07fd640", + "metadata": { + "editable": true + }, + "source": [ + "The Chebyshev series in Numpy has a wide range of possibilities,\n", + "see [here](https://numpy.org/doc/stable/reference/generated/numpy.polynomial.chebyshev.Chebyshev.html#numpy.polynomial.chebyshev.Chebyshev).\n", + "However, we may also work directly with the Chebyshev\n", + "coefficients already in `u`. To find the roots of the\n", + "polynomial that approximates the Bessel function on\n", + "domain $[0, 100]$, we can do" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "66dcc5f2", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:25.645719Z", + "iopub.status.busy": "2024-05-24T12:37:25.645526Z", + "iopub.status.idle": "2024-05-24T12:37:25.651103Z", + "shell.execute_reply": "2024-05-24T12:37:25.650379Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "z = Tu.map_true_domain(cheb.chebroots(u))" + ] + }, + { + "cell_type": "markdown", + "id": "a20a2384", + "metadata": { + "editable": true + }, + "source": [ + "Note that the roots are found on the reference domain $[-1, 1]$\n", + "and as such we need to move the result to the physical domain using\n", + "`map_true_domain`. The resulting roots `z` are both real and imaginary,\n", + "so to extract the real roots we need to filter a little bit" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "33dc7c82", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:25.655373Z", + "iopub.status.busy": "2024-05-24T12:37:25.655119Z", + "iopub.status.idle": "2024-05-24T12:37:25.660950Z", + "shell.execute_reply": "2024-05-24T12:37:25.658643Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "z2 = z[np.where((z.imag == 0)*(z.real > 0)*(z.real < 100))].real\n", + "print(z2[:5])" + ] + }, + { + "cell_type": "markdown", + "id": "04171337", + "metadata": { + "editable": true + }, + "source": [ + "Here `np.where` returns the indices where the condition is true. The condition\n", + "is that the imaginary part is zero, whereas the real part is within the\n", + "true domain $[0, 100]$.\n", + "\n", + ":::{note}\n", + "Using directly `cheb.chebroots(c)` does not seem to work (even though the\n", + "series has been generated with the non-standard domain) because\n", + "Numpy only looks for roots in the reference domain $[-1, 1]$.\n", + ":::\n", + "\n", + "We could also use a function space with boundary conditions built\n", + "in, like" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "23287700", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:25.663414Z", + "iopub.status.busy": "2024-05-24T12:37:25.663322Z", + "iopub.status.idle": "2024-05-24T12:37:25.713724Z", + "shell.execute_reply": "2024-05-24T12:37:25.713011Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "Td = FunctionSpace(0, 'C', bc=(sp.besselj(0, 0), sp.besselj(0, 100)), domain=(0, 100))\n", + "ud = Function(Td, buffer=sp.besselj(0, x))\n", + "print(len(ud))" + ] + }, + { + "cell_type": "markdown", + "id": "28a0c752", + "metadata": { + "editable": true + }, + "source": [ + "As we can see this leads to a function space of dimension\n", + "very similar to the orthogonal space.\n", + "\n", + "The major advantages of working with a space with boundary conditions\n", + "built in only comes to life when solving differential equations. As\n", + "long as we are only interested in approximating functions, we are better off\n", + "sticking to the orthogonal spaces. This goes for Legendre as\n", + "well as Chebyshev." + ] + }, + { + "cell_type": "markdown", + "id": "cbfe6a4e", + "metadata": { + "editable": true + }, + "source": [ + "## Multidimensional functions\n", + "\n", + "Multidimensional tensor product spaces are created\n", + "by taking the tensor products of one-dimensional function spaces.\n", + "For example" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "00e8b329", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:25.718425Z", + "iopub.status.busy": "2024-05-24T12:37:25.718290Z", + "iopub.status.idle": "2024-05-24T12:37:25.738958Z", + "shell.execute_reply": "2024-05-24T12:37:25.738633Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "C0 = FunctionSpace(20, 'C')\n", + "C1 = FunctionSpace(20, 'C')\n", + "T = TensorProductSpace(comm, (C0, C1))\n", + "u = Function(T)" + ] + }, + { + "cell_type": "markdown", + "id": "0ca369f5", + "metadata": { + "editable": true + }, + "source": [ + "Here $\\text{T} = \\text{C0} \\otimes \\text{C1}$, the basis function is\n", + "$T_i(x) T_j(y)$ and the Function `u` is" + ] + }, + { + "cell_type": "markdown", + "id": "c6501f71", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "u(x, y) = \\sum_{i=0}^{N-1} \\sum_{j=0}^{N-1} \\hat{u}_{ij} T_i(x) T_j(y).\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "9baa4116", + "metadata": { + "editable": true + }, + "source": [ + "The multidimensional Functions work more or less exactly like for the\n", + "1D case. We can here interpolate 2D Sympy functions" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f8c1a6c4", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:25.742441Z", + "iopub.status.busy": "2024-05-24T12:37:25.742326Z", + "iopub.status.idle": "2024-05-24T12:37:25.860399Z", + "shell.execute_reply": "2024-05-24T12:37:25.858077Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "y = sp.Symbol('y', real=True)\n", + "u = Function(T, buffer=sp.cos(10*x)*sp.cos(10*y))\n", + "X = T.local_mesh(True)\n", + "plt.contourf(X[0], X[1], u.backward());" + ] + }, + { + "cell_type": "markdown", + "id": "99390331", + "metadata": { + "editable": true + }, + "source": [ + "Like for 1D the coefficients are computed through projection,\n", + "where the exact function is evaluated on all quadrature points\n", + "in the mesh.\n", + "\n", + "The Cartesian mesh represents the quadrature points of the\n", + "two function spaces, and can be visualized as follows" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6f50c502", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:25.864167Z", + "iopub.status.busy": "2024-05-24T12:37:25.863483Z", + "iopub.status.idle": "2024-05-24T12:37:26.030734Z", + "shell.execute_reply": "2024-05-24T12:37:26.030410Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "X = T.mesh()\n", + "for xj in X[0]:\n", + " for yj in X[1]:\n", + " plt.plot((xj, xj), (X[1][0, 0], X[1][0, -1]), 'k')\n", + " plt.plot((X[0][0], X[0][-1]), (yj, yj), 'k')" + ] + }, + { + "cell_type": "markdown", + "id": "205be2c5", + "metadata": { + "editable": true + }, + "source": [ + "We may alternatively plot on a uniform mesh" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f40fd289", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:26.033855Z", + "iopub.status.busy": "2024-05-24T12:37:26.033556Z", + "iopub.status.idle": "2024-05-24T12:37:26.123275Z", + "shell.execute_reply": "2024-05-24T12:37:26.122760Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "X = T.local_mesh(bcast=True, kind='uniform')\n", + "plt.contourf(X[0], X[1], u.backward(mesh='uniform'));" + ] + }, + { + "cell_type": "markdown", + "id": "88538f19", + "metadata": { + "editable": true + }, + "source": [ + "## Curvilinear coordinates\n", + "\n", + "With shenfun it is possible to use curvilinear coordinates,\n", + "and not necessarily with orthogonal basis vectors. With\n", + "curvilinear coordinates the computational coordinates are\n", + "always straight lines, rectangles and cubes. But the physical\n", + "coordinates can be very complex.\n", + "\n", + "Consider the unit disc with polar coordinates. Here\n", + "the position vector $\\mathbf{r}$ is given by" + ] + }, + { + "cell_type": "markdown", + "id": "45580ada", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\mathbf{r} = r\\cos \\theta \\mathbf{i} + r\\sin \\theta \\mathbf{j}.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "42e1822a", + "metadata": { + "editable": true + }, + "source": [ + "The physical domain is $\\Omega = \\{(x, y): x^2 + y^2 < 1\\}$,\n", + "whereas the computational domain is the Cartesian product\n", + "$D = [0, 1] \\times [0, 2 \\pi] = \\{(r, \\theta) | r \\in [0, 1] \\text{ and } \\theta \\in [0, 2 \\pi]\\}$.\n", + "\n", + "We create this domain in shenfun through" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "abe72e5b", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:26.127527Z", + "iopub.status.busy": "2024-05-24T12:37:26.127418Z", + "iopub.status.idle": "2024-05-24T12:37:26.297581Z", + "shell.execute_reply": "2024-05-24T12:37:26.297216Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "r, theta = psi = sp.symbols('x,y', real=True, positive=True)\n", + "rv = (r*sp.cos(theta), r*sp.sin(theta))\n", + "B0 = FunctionSpace(20, 'C', domain=(0, 1))\n", + "F0 = FunctionSpace(20, 'F')\n", + "T = TensorProductSpace(comm, (B0, F0), coordinates=(psi, rv))" + ] + }, + { + "cell_type": "markdown", + "id": "cf97987a", + "metadata": { + "editable": true + }, + "source": [ + "Note that we are using a Fourier space for the azimuthal\n", + "direction, since the solution here needs to be periodic.\n", + "We can now create functions on the space using an\n", + "analytical function in computational coordinates" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0a65ffc2", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:26.299837Z", + "iopub.status.busy": "2024-05-24T12:37:26.299661Z", + "iopub.status.idle": "2024-05-24T12:37:26.309064Z", + "shell.execute_reply": "2024-05-24T12:37:26.308249Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u = Function(T, buffer=(1-r)*r*sp.sin(sp.cos(theta)))" + ] + }, + { + "cell_type": "markdown", + "id": "02962d83", + "metadata": { + "editable": true + }, + "source": [ + "However, when this is plotted it may not be what you expect" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c32f1808", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:26.311147Z", + "iopub.status.busy": "2024-05-24T12:37:26.311031Z", + "iopub.status.idle": "2024-05-24T12:37:26.379378Z", + "shell.execute_reply": "2024-05-24T12:37:26.377774Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "X = T.local_mesh(True)\n", + "plt.contourf(X[0], X[1], u.backward(), 100);" + ] + }, + { + "cell_type": "markdown", + "id": "4ef74e8d", + "metadata": { + "editable": true + }, + "source": [ + "We see that the function has been plotted in computational coordinates,\n", + "and not on the disc, as you probably expected. To plot on\n", + "the disc we need the physical mesh, and not the computational" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a42a0a42", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:26.386950Z", + "iopub.status.busy": "2024-05-24T12:37:26.386314Z", + "iopub.status.idle": "2024-05-24T12:37:26.483051Z", + "shell.execute_reply": "2024-05-24T12:37:26.481112Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "X = T.local_cartesian_mesh()\n", + "plt.contourf(X[0], X[1], u.backward(), 100);" + ] + }, + { + "cell_type": "markdown", + "id": "e45366c2", + "metadata": { + "editable": true + }, + "source": [ + ":::{note}\n", + "The periodic plot does not wrap all around the circle. This is\n", + "not wrong, we have simply not used the same point twice, but it\n", + "does not look very good. To overcome this problem we can wrap the\n", + "grid all the way around and re-plot.\n", + ":::" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b9f6cc53", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:26.487365Z", + "iopub.status.busy": "2024-05-24T12:37:26.487223Z", + "iopub.status.idle": "2024-05-24T12:37:26.580996Z", + "shell.execute_reply": "2024-05-24T12:37:26.579877Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "up = u.backward()\n", + "xp, yp, up = wrap_periodic([X[0], X[1], up], axes=[1])\n", + "plt.contourf(xp, yp, up, 100);" + ] + }, + { + "cell_type": "markdown", + "id": "39be30cc", + "metadata": { + "editable": true + }, + "source": [ + "## Adaptive functions in multiple dimensions\n", + "\n", + "If you want to find a good resolution for a function in multiple\n", + "dimensions, the procedure is exactly like in 1D. First create function\n", + "spaces with 0 quadrature points, and then call [Function](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Function)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f896255d", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:26.586756Z", + "iopub.status.busy": "2024-05-24T12:37:26.585661Z", + "iopub.status.idle": "2024-05-24T12:37:26.695543Z", + "shell.execute_reply": "2024-05-24T12:37:26.693180Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "B0 = FunctionSpace(0, 'C', domain=(0, 1))\n", + "F0 = FunctionSpace(0, 'F')\n", + "T = TensorProductSpace(comm, (B0, F0), coordinates=(psi, rv))\n", + "u = Function(T, buffer=((1-r)*r)**2*sp.sin(sp.cos(theta)))\n", + "print(u.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "d0e41011", + "metadata": { + "editable": true + }, + "source": [ + "The algorithm used to find the approximation in multiple dimensions\n", + "simply treat the problem one direction at the time. So in this case\n", + "we would first find a space in the first direction by using\n", + "a function ` ~ ((1-r)*r)**2`, and then along the second using\n", + "a function ` ~ sp.sin(sp.cos(theta))`.\n", + "\n", + "" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/Integration/surfaceintegration.ipynb b/docs/demos/Integration/surfaceintegration.ipynb new file mode 100644 index 00000000..74dcfd23 --- /dev/null +++ b/docs/demos/Integration/surfaceintegration.ipynb @@ -0,0 +1,1161 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "f69832df", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - Integration of functions\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **August 7, 2020**\n", + "\n", + "**Summary.** This is a demonstration of how the Python module [shenfun](https://github.com/spectralDNS/shenfun) can be used to\n", + "integrate over 1D curves and 2D surfaces in 3D space.\n", + "We make use of\n", + "curvilinear coordinates, and reproduce some integrals\n", + "performed by Behnam Hashemi with [Chebfun](http://www.chebfun.org/examples/approx3/SurfaceIntegral3D.html).\n", + "\n", + ":::{note}\n", + "For all the examples below we could just as well\n", + "use Legendre polynomials instead of Chebyshev.\n", + "Just replace 'C' with 'L' when creating function spaces.\n", + "The accuracy ought to be similar.\n", + ":::" + ] + }, + { + "cell_type": "markdown", + "id": "fc9ceef2", + "metadata": { + "editable": true + }, + "source": [ + "## The inner product\n", + "\n", + "A lesser known fact about [shenfun](https://github.com/spectralDNS/shenfun) is\n", + "that it can be used to perform regular, unweighted, integrals with\n", + "spectral accuracy. With the newly added curvilinear coordinates\n", + "feature, we can now also integrate over highly complex lines and surfaces\n", + "embedded in a higher dimensional space.\n", + "\n", + "To integrate over a domain in shenfun we use the\n", + "[inner()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.inner.inner)\n", + "function, with a constant test function. The [inner()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.inner.inner)\n", + "function in shenfun is defined as an integral over the\n", + "entire domain $\\Omega$ in question" + ] + }, + { + "cell_type": "markdown", + "id": "3ab8310f", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "(u, v)_w = \\int_{\\Omega} u \\overline{v} w d\\Omega,\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "43bf0ffb", + "metadata": { + "editable": true + }, + "source": [ + "for trial function $u$, test function $v$ and weight $w$.\n", + "Also, $\\overline{v}$ represents the complex conjugate of $v$, in case\n", + "we are working with complex functions (like Fourier exponentials).\n", + "\n", + "The functions and weights take on different form, but if\n", + "the test function $v$ is chosen to be a constant, e.g., $v=1$,\n", + "then the weight is also constant, $w=1$, and the inner product becomes\n", + "an unweighted integral of $u$ over the domain" + ] + }, + { + "cell_type": "markdown", + "id": "8cc37f68", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "(u, 1)_w = \\int_{\\Omega} u d\\Omega.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "0819d555", + "metadata": { + "editable": true + }, + "source": [ + "Note that the integral in the inner product either can be computed\n", + "exactly using Sympy, adaptively using Scipy or with quadrature\n", + "using Shenfun. The quadrature can be computed with any fixed resolution,\n", + "see [inner()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.inner.inner)." + ] + }, + { + "cell_type": "markdown", + "id": "dacc0e7d", + "metadata": { + "editable": true + }, + "source": [ + "### Curve integrals\n", + "\n", + "For example, if we create some function space on the line from\n", + "0 to 1, then we can get the length of this domain using `inner`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "239b46e9", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:29.095433Z", + "iopub.status.busy": "2024-05-24T12:37:29.095328Z", + "iopub.status.idle": "2024-05-24T12:37:29.619934Z", + "shell.execute_reply": "2024-05-24T12:37:29.618171Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from shenfun import *\n", + "B = FunctionSpace(10, 'C', domain=(0, 1))\n", + "u = Array(B, val=1)\n", + "length = inner(u, 1)\n", + "print('Length of domain =', length)" + ] + }, + { + "cell_type": "markdown", + "id": "4e59fb61", + "metadata": { + "editable": true + }, + "source": [ + "Note that we cannot simply do `inner(1, 1)`, because the\n", + "`inner` function does not know about the domain, which is part\n", + "of the [FunctionSpace](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.FunctionSpace). So to integrate `u=1`, we need to\n", + "create `u` as an [Array](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Array) with the constant value 1.\n", + "\n", + "Since the function space `B` is Cartesian the computed\n", + "length is simply the domain length.\n", + "Not very impressive, but the same goes for multidimensional\n", + "tensor product domains" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c247086b", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:29.622827Z", + "iopub.status.busy": "2024-05-24T12:37:29.622618Z", + "iopub.status.idle": "2024-05-24T12:37:29.633687Z", + "shell.execute_reply": "2024-05-24T12:37:29.633005Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "F = FunctionSpace(10, 'F', domain=(0, 2*np.pi))\n", + "T = TensorProductSpace(comm, (B, F))\n", + "area = inner(1, Array(T, val=1))\n", + "print('Area of domain =', area)" + ] + }, + { + "cell_type": "markdown", + "id": "16e1cce2", + "metadata": { + "editable": true + }, + "source": [ + "Still not very impressive, but moving to curvilinear coordinates\n", + "it all starts to become more interesting. Lets\n", + "look at a spiral $C$ embedded in $\\mathbb{R}^3$, parametrized\n", + "by one single parameter $t$" + ] + }, + { + "cell_type": "markdown", + "id": "0bea4158", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{align*}\n", + "x(t) &= \\sin 2t \\\\ \n", + "y(t) &= \\cos 2t \\\\ \n", + "z(t) &= \\frac{t}{2} \\\\ \n", + "0 \\le & t \\le 2\\pi\n", + "\\end{align*}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "b13e1f89", + "metadata": { + "editable": true + }, + "source": [ + "What is the length of this spiral? The spiral can be\n", + "seen as the red curve in the figure a few cells below.\n", + "\n", + "The integral over the parametrized curve $C$ can\n", + "be written as" + ] + }, + { + "cell_type": "markdown", + "id": "158ad02c", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\int_C ds = \\int_{t=0}^{2\\pi} \\sqrt{\\left(\\frac{d x}{d t}\\right)^2 + \\left(\\frac{d y}{d t}\\right)^2 + \\left(\\frac{d z}{d t}\\right)^2} dt.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e5871ca3", + "metadata": { + "editable": true + }, + "source": [ + "We can find this integral easily using shenfun. Create\n", + "a function space in curvilinear coordinates, providing\n", + "the position vector $\\mathbf{r} = x(t)\\mathbf{i} + y(t) \\mathbf{j} + z(t) \\mathbf{k}$\n", + "as input. Also, choose to work with covariant basis vectors, which\n", + "is really not important unless you work with vector equations. The\n", + "alternative is the default 'normal', where the basis vectors\n", + "are normalized to unit length." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ab2ff2d7", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:29.639262Z", + "iopub.status.busy": "2024-05-24T12:37:29.638874Z", + "iopub.status.idle": "2024-05-24T12:37:29.865919Z", + "shell.execute_reply": "2024-05-24T12:37:29.865077Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "import sympy as sp\n", + "from shenfun import *\n", + "config['basisvectors'] = 'covariant'\n", + "t = sp.Symbol('x', real=True, positive=True)\n", + "rv = (sp.sin(2*t), sp.cos(2*t), 0.5*t)\n", + "C = FunctionSpace(100, 'C', domain=(0, 2*np.pi), coordinates=((t,), rv))" + ] + }, + { + "cell_type": "markdown", + "id": "99693b79", + "metadata": { + "editable": true + }, + "source": [ + "Then compute the arclength using [inner()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.inner.inner), again by using a constant\n", + "testfunction 1, and a constant [Array](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Array) u=1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b86162bf", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:29.869354Z", + "iopub.status.busy": "2024-05-24T12:37:29.869219Z", + "iopub.status.idle": "2024-05-24T12:37:29.943484Z", + "shell.execute_reply": "2024-05-24T12:37:29.943016Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "length = inner(1, Array(C, val=1))\n", + "print('Length of spiral =', length)" + ] + }, + { + "cell_type": "markdown", + "id": "7c5ffdd2", + "metadata": { + "editable": true + }, + "source": [ + "The arclength is found to be slightly longer than $4 \\pi$. Looking at the\n", + "spiral below, the result looks reasonable." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0d9a6b65", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:29.947584Z", + "iopub.status.busy": "2024-05-24T12:37:29.947060Z", + "iopub.status.idle": "2024-05-24T12:37:30.262307Z", + "shell.execute_reply": "2024-05-24T12:37:30.260469Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "fig = plt.figure(figsize=(4, 3))\n", + "X = C.cartesian_mesh(kind='uniform')\n", + "ax = fig.add_subplot(111, projection='3d')\n", + "p = ax.plot(X[0], X[1], X[2], 'r')\n", + "hx = ax.set_xticks(np.linspace(-1, 1, 5))\n", + "hy = ax.set_yticks(np.linspace(-1, 1, 5))" + ] + }, + { + "cell_type": "markdown", + "id": "5fb91f88", + "metadata": { + "editable": true + }, + "source": [ + "The term $\\sqrt{\\left(\\frac{d x}{d t}\\right)^2 + \\left(\\frac{d y}{d t}\\right)^2 + \\left(\\frac{d z}{d t}\\right)^2}$\n", + "is actually here a constant $\\sqrt{4.25}$, found in shenfun as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b12c0f09", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:30.272963Z", + "iopub.status.busy": "2024-05-24T12:37:30.272739Z", + "iopub.status.idle": "2024-05-24T12:37:30.277663Z", + "shell.execute_reply": "2024-05-24T12:37:30.276492Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "C.coors.sg" + ] + }, + { + "cell_type": "markdown", + "id": "231ddeac", + "metadata": { + "editable": true + }, + "source": [ + "We could also integrate a non-constant function over the spiral.\n", + "For example, lets integrate the function $f(x, y, z)= \\sin^2 x$" + ] + }, + { + "cell_type": "markdown", + "id": "d549c0c8", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\int_C \\sin^2 x ds = \\int_{t=0}^{2\\pi} \\sin^2 (\\sin 2t) \\sqrt{\\left(\\frac{d x}{d t}\\right)^2 + \\left(\\frac{d y}{d t}\\right)^2 + \\left(\\frac{d z}{d t}\\right)^2} dt\n", + "$$" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "70f98c31", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:30.282411Z", + "iopub.status.busy": "2024-05-24T12:37:30.282314Z", + "iopub.status.idle": "2024-05-24T12:37:30.287922Z", + "shell.execute_reply": "2024-05-24T12:37:30.286973Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "inner(1, Array(C, buffer=sp.sin(rv[0])**2))" + ] + }, + { + "cell_type": "markdown", + "id": "79f71b48", + "metadata": { + "editable": true + }, + "source": [ + "which can be easily verified using, e.g., Wolfram Alpha" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "feb65bc7", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:30.293347Z", + "iopub.status.busy": "2024-05-24T12:37:30.293234Z", + "iopub.status.idle": "2024-05-24T12:37:30.301585Z", + "shell.execute_reply": "2024-05-24T12:37:30.299955Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from IPython.display import IFrame\n", + "IFrame(\"https://www.wolframalpha.com/input/?i=integrate+sin%5E2%28sin%282t%29%29+sqrt%284.25%29+from+t%3D0+to+2pi\", width=\"500px\", height=\"350px\")" + ] + }, + { + "cell_type": "markdown", + "id": "f0402f37", + "metadata": { + "editable": true + }, + "source": [ + "### Surface integrals\n", + "\n", + "Consider a 3D function $f(x,y,z) \\in \\mathbb{R}^3$ and\n", + "a 2D surface (not neccessarily plane) $S(u, v)$,\n", + "parametrized in two new coordinates $u$ and $v$. A position\n", + "vector $\\mathbf{r}$ can be used to parametrize $S$" + ] + }, + { + "cell_type": "markdown", + "id": "d2282d36", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\mathbf{r} = x(u, v) \\,\\mathbf{i} + y(u, v) \\,\\mathbf{j} + z(u, v) \\,\\mathbf{k},\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "309a3f3f", + "metadata": { + "editable": true + }, + "source": [ + "where $\\mathbf{i}, \\mathbf{j}, \\mathbf{k}$ are the Cartesian unit vectors.\n", + "The two new coordinates $u$ and $v$ are functions of $x, y, z$,\n", + "and they each have a one-dimensional domain" + ] + }, + { + "cell_type": "markdown", + "id": "9e1f19ca", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "u \\in D_u \\quad v \\in D_v.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "73f360d4", + "metadata": { + "editable": true + }, + "source": [ + "The exact size of the domain depends on the problem at hand. The computational\n", + "domain of the surface $S$ is $D=D_u \\times D_v$.\n", + "\n", + "A surface integral of $f$ over $S$ can now be written" + ] + }, + { + "cell_type": "markdown", + "id": "a9a5dbe0", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\int_S f(x, y, z) dS = \\int_D f(x(u, v), y(u, v), z(u, v)) \\left|\\frac{\\partial \\mathbf{r}}{\\partial u} \\times \\frac{\\partial \\mathbf{r}}{\\partial v} \\right| dudv,\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "d4873da3", + "metadata": { + "editable": true + }, + "source": [ + "where $dS$ is a surface area element. With shenfun such integrals\n", + "are trivial, even for highly complex domains." + ] + }, + { + "cell_type": "markdown", + "id": "c6775cbe", + "metadata": { + "editable": true + }, + "source": [ + "## Example 1\n", + "\n", + "Consider first the surface integral of $f(x,y,z)=x^2$\n", + "over the unit sphere. We use regular spherical coordinates," + ] + }, + { + "cell_type": "markdown", + "id": "82604644", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{align*}\n", + "0 &\\le \\theta \\le \\pi \\\\ \n", + "0 &\\le \\phi \\le 2\\pi \\\\ \n", + "x(\\theta, \\phi) &= \\sin \\theta \\cos \\phi \\\\ \n", + "y(\\theta, \\phi) &= \\sin \\theta \\sin \\phi \\\\ \n", + "z(\\theta, \\phi) &= \\cos \\theta\n", + "\\end{align*}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "bcf630fd", + "metadata": { + "editable": true + }, + "source": [ + "The straight forward implementation of a function space for\n", + "the unit sphere reads" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5a4c60c4", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:30.307215Z", + "iopub.status.busy": "2024-05-24T12:37:30.306907Z", + "iopub.status.idle": "2024-05-24T12:37:30.509139Z", + "shell.execute_reply": "2024-05-24T12:37:30.508243Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "import sympy as sp\n", + "\n", + "theta, phi = psi =sp.symbols('x,y', real=True, positive=True)\n", + "rv = (sp.sin(theta)*sp.cos(phi), sp.sin(theta)*sp.sin(phi), sp.cos(theta))\n", + "\n", + "B0 = FunctionSpace(0, 'C', domain=(0, np.pi))\n", + "B1 = FunctionSpace(0, 'F', dtype='d')\n", + "T = TensorProductSpace(comm, (B0, B1), coordinates=(psi, rv, sp.Q.positive(sp.sin(theta))))" + ] + }, + { + "cell_type": "markdown", + "id": "39dc8175", + "metadata": { + "editable": true + }, + "source": [ + "where `sp.Q.positive(sp.sin(theta))` is a restriction that\n", + "helps `Sympy` in computing the Jacobian required for the integral.\n", + "We can now approximate the function $f$ on this surface" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8bd8dca7", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:30.513561Z", + "iopub.status.busy": "2024-05-24T12:37:30.513425Z", + "iopub.status.idle": "2024-05-24T12:37:30.660833Z", + "shell.execute_reply": "2024-05-24T12:37:30.659114Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "f = Array(T, buffer=rv[0]**2)" + ] + }, + { + "cell_type": "markdown", + "id": "c1b22719", + "metadata": { + "editable": true + }, + "source": [ + "and we can integrate over $S$" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "10a07f12", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:30.667258Z", + "iopub.status.busy": "2024-05-24T12:37:30.667151Z", + "iopub.status.idle": "2024-05-24T12:37:30.670566Z", + "shell.execute_reply": "2024-05-24T12:37:30.670263Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "I = inner(1, f)" + ] + }, + { + "cell_type": "markdown", + "id": "007dc278", + "metadata": { + "editable": true + }, + "source": [ + "and finally compare to the exact result, which is $4 \\pi / 3$" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7b8f9179", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:30.672382Z", + "iopub.status.busy": "2024-05-24T12:37:30.672311Z", + "iopub.status.idle": "2024-05-24T12:37:30.675604Z", + "shell.execute_reply": "2024-05-24T12:37:30.674377Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "print('Error =', abs(I-4*np.pi/3))" + ] + }, + { + "cell_type": "markdown", + "id": "1382ae60", + "metadata": { + "editable": true + }, + "source": [ + "Note that we can here achieve better accuracy by using\n", + "more quadrature points. For example by refining `f`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6ac0a284", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:30.678450Z", + "iopub.status.busy": "2024-05-24T12:37:30.678337Z", + "iopub.status.idle": "2024-05-24T12:37:30.816866Z", + "shell.execute_reply": "2024-05-24T12:37:30.815613Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "T = T.get_refined(2*np.array(f.global_shape))\n", + "f = Array(T, buffer=rv[0]**2)\n", + "print('Error =', abs(inner(1, f)-4*np.pi/3))" + ] + }, + { + "cell_type": "markdown", + "id": "8b74e9dc", + "metadata": { + "editable": true + }, + "source": [ + "Not bad at all:-)\n", + "\n", + "To go a little deeper into the integral, we can get the\n", + "term $\\left|\\frac{\\partial \\mathbf{r}}{\\partial u} \\times \\frac{\\partial \\mathbf{r}}{\\partial v} \\right|$\n", + "as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dc0793f7", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:30.819288Z", + "iopub.status.busy": "2024-05-24T12:37:30.819155Z", + "iopub.status.idle": "2024-05-24T12:37:30.822928Z", + "shell.execute_reply": "2024-05-24T12:37:30.821197Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "print(T.coors.sg)" + ] + }, + { + "cell_type": "markdown", + "id": "0b5dcced", + "metadata": { + "editable": true + }, + "source": [ + "Here the printed variable is `x`, but this is because `theta`\n", + "is named `x` internally by `Sympy`. This is because of the definition\n", + "used above: `theta, phi = sp.symbols('x,y', real=True, positive=True)`.\n", + "\n", + "Note that $\\mathbf{b}_u = \\frac{\\partial \\mathbf{r}}{\\partial u}$ and\n", + "$\\mathbf{b}_v = \\frac{\\partial \\mathbf{r}}{\\partial v}$ are the two\n", + "basis vectors used by shenfun for the surface $S$. The basis\n", + "vectors are obtainable as `T.coors.b`, and can also be printed\n", + "in latex using:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "985cee68", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:30.827054Z", + "iopub.status.busy": "2024-05-24T12:37:30.826526Z", + "iopub.status.idle": "2024-05-24T12:37:30.834909Z", + "shell.execute_reply": "2024-05-24T12:37:30.833751Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from IPython.display import Math\n", + "Math(T.coors.latex_basis_vectors(symbol_names={theta: '\\\\theta', phi: '\\\\phi'}))" + ] + }, + { + "cell_type": "markdown", + "id": "29294d79", + "metadata": { + "editable": true + }, + "source": [ + "where we tell latex to print `theta` as $\\theta$, and not `x`:-)\n", + "\n", + "From the basis vectors it should be easy to see that $\\left| \\mathbf{b}_{\\theta} \\times \\mathbf{b}_{\\phi} \\right| = \\sin \\theta$." + ] + }, + { + "cell_type": "markdown", + "id": "4b3a42b8", + "metadata": { + "editable": true + }, + "source": [ + "## Example 2\n", + "\n", + "Next, we solve [Example 5](http://www.math24.net/surface-integrals-of-first-kind.html)\n", + "from the online resources at math24.net. Here" + ] + }, + { + "cell_type": "markdown", + "id": "11067437", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "f = \\sqrt{1+x^2+y^2}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e3d6ffcd", + "metadata": { + "editable": true + }, + "source": [ + "and the surface is defined by" + ] + }, + { + "cell_type": "markdown", + "id": "9f68a0da", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\mathbf{r} = u \\cos v \\mathbf{i} + u \\sin v \\mathbf{j} + v \\mathbf{k}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1fd1537c", + "metadata": { + "editable": true + }, + "source": [ + "with $0 \\le u \\le 2, 0 \\le v \\le 2\\pi$.\n", + "\n", + "The implementation is only a few lines, and we end by comparing\n", + "to the exact solution $14 \\pi /3$" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "40e3a695", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:30.838953Z", + "iopub.status.busy": "2024-05-24T12:37:30.838820Z", + "iopub.status.idle": "2024-05-24T12:37:30.990399Z", + "shell.execute_reply": "2024-05-24T12:37:30.989744Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u, v = psi =sp.symbols('x,y', real=True, positive=True)\n", + "rv = (u*sp.cos(v), u*sp.sin(v), v)\n", + "B0 = FunctionSpace(0, 'C', domain=(0, 2))\n", + "B1 = FunctionSpace(0, 'C', domain=(0, np.pi))\n", + "T = TensorProductSpace(comm, (B0, B1), coordinates=(psi, rv))\n", + "f = Array(T, buffer=sp.sqrt(1+rv[0]**2+rv[1]**2))\n", + "print('Error =', abs(inner(1, f)-14*np.pi/3))" + ] + }, + { + "cell_type": "markdown", + "id": "80153aef", + "metadata": { + "editable": true + }, + "source": [ + "In this case the integral measure is" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dc0793f7_1", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:30.994138Z", + "iopub.status.busy": "2024-05-24T12:37:30.994014Z", + "iopub.status.idle": "2024-05-24T12:37:30.996861Z", + "shell.execute_reply": "2024-05-24T12:37:30.996305Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "print(T.coors.sg)" + ] + }, + { + "cell_type": "markdown", + "id": "ed8752ba", + "metadata": { + "editable": true + }, + "source": [ + "## Example 3\n", + "\n", + "In this third example we use a surface that\n", + "looks like a seashell. Again, the example is taken from\n", + "[chebfun](http://www.chebfun.org/examples/approx3/SurfaceIntegral3D.html).\n", + "\n", + "The surface of the seashell is parametrized with position\n", + "vector" + ] + }, + { + "cell_type": "markdown", + "id": "9d475c23", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{align*}\n", + "\\mathbf{r} &= \\left(\\left(\\frac{5}{4}-\\frac{5 v}{8 \\pi}\\right) \\cos 2v(1+\\cos u) + \\cos 2v \\right) \\mathbf{i} \\\\ \n", + " &+\\left(\\left(\\frac{5}{4}-\\frac{5 v}{8 \\pi}\\right) \\sin 2v (1+\\cos u) + \\sin 2v \\right) \\mathbf{j},\\\\ \n", + " &+\\left(\\frac{10 v}{2 \\pi} + \\left(\\frac{5}{4}-\\frac{5 v}{8 \\pi}\\right) \\sin u + 15\\right) \\mathbf{k}\n", + "\\end{align*}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "d845d419", + "metadata": { + "editable": true + }, + "source": [ + "for $0 \\le u \\le 2 \\pi, -2 \\pi \\le v \\le 2 \\pi$.\n", + "\n", + "The function $f$ is now defined as" + ] + }, + { + "cell_type": "markdown", + "id": "2735adb0", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "f(x,y,z) = x+y+z\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "ceb7c81d", + "metadata": { + "editable": true + }, + "source": [ + "The implementation is" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "89c0e257", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:31.011160Z", + "iopub.status.busy": "2024-05-24T12:37:31.011061Z", + "iopub.status.idle": "2024-05-24T12:37:34.282054Z", + "shell.execute_reply": "2024-05-24T12:37:34.281286Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "rv = (5*(1-v/(2*sp.pi))*sp.cos(2*v)*(1+sp.cos(u))/4 + sp.cos(2*v),\n", + " 5*(1-v/(2*sp.pi))*sp.sin(2*v)*(1+sp.cos(u))/4 + sp.sin(2*v),\n", + " 10*v/(2*sp.pi) + 5*(1-v/(2*sp.pi))*sp.sin(u)/4 + 15)\n", + "\n", + "B0 = FunctionSpace(100, 'C', domain=(0, 2*np.pi))\n", + "B1 = FunctionSpace(100, 'C', domain=(-2*np.pi, 2*np.pi))\n", + "T = TensorProductSpace(comm, (B0, B1), coordinates=(psi, rv, sp.Q.positive(v-2*sp.pi)))\n", + "\n", + "f = rv[0]+rv[1]+rv[2]\n", + "fb = Array(T, buffer=f)\n", + "I = inner(1, fb)\n", + "print(I)" + ] + }, + { + "cell_type": "markdown", + "id": "737091ab", + "metadata": { + "editable": true + }, + "source": [ + "which agrees very well with chebfun's result. The basis vectors\n", + "for the surface of the seashell are" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "60cc5783", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:34.286063Z", + "iopub.status.busy": "2024-05-24T12:37:34.285874Z", + "iopub.status.idle": "2024-05-24T12:37:34.293189Z", + "shell.execute_reply": "2024-05-24T12:37:34.292493Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "Math(T.coors.latex_basis_vectors(symbol_names={u: 'u', v: 'v'}))" + ] + }, + { + "cell_type": "markdown", + "id": "feec2b32", + "metadata": { + "editable": true + }, + "source": [ + "which, if nothing else, shows the power of symbolic\n", + "computing in Sympy.\n", + "\n", + "We can plot the\n", + "seashell using either plotly or mayavi. Here we choose\n", + "plotly since it integrates well with the executable\n", + "jupyter book." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0aceb331", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:34.295369Z", + "iopub.status.busy": "2024-05-24T12:37:34.295236Z", + "iopub.status.idle": "2024-05-24T12:37:34.576905Z", + "shell.execute_reply": "2024-05-24T12:37:34.573387Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "import plotly\n", + "fig = surf3D(fb, colorscale=plotly.colors.sequential.Jet)\n", + "fig.update_layout(scene_camera_eye=dict(x=1.6, y=-1.4, z=0))\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "id": "3e83de81", + "metadata": { + "editable": true + }, + "source": [ + "" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/KleinGordon/kleingordon.ipynb b/docs/demos/KleinGordon/kleingordon.ipynb new file mode 100644 index 00000000..e2048ce9 --- /dev/null +++ b/docs/demos/KleinGordon/kleingordon.ipynb @@ -0,0 +1,1384 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "755b1597", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - Cubic nonlinear Klein-Gordon equation\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **April 13, 2018**\n", + "\n", + "**Summary.** This is a demonstration of how the Python module [shenfun](https://github.com/spectralDNS/shenfun) can be used to solve the time-dependent,\n", + "nonlinear Klein-Gordon equation, in a triply periodic domain. The demo is implemented in\n", + "a single Python file [KleinGordon.py](https://github.com/spectralDNS/shenfun/blob/master/demo/KleinGordon.py), and it may be run\n", + "in parallel using MPI. The Klein-Gordon equation is solved using a mixed\n", + "formulation. The discretization, and some background on the spectral Galerkin\n", + "method is given first, before we turn to the actual details of the `shenfun`\n", + "implementation.\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "

Figure 1

\n", + "\n", + "\n", + "Movie showing the evolution of the solution $u$ from the Klein-Gordon equation, in a slice through the center of the domain, computed with the code described in this demo." + ] + }, + { + "cell_type": "markdown", + "id": "8ae995a4", + "metadata": { + "editable": true + }, + "source": [ + "## The nonlinear Klein-Gordon equation\n", + "\n", + "The cubic nonlinear Klein-Gordon equation is a wave equation important for many\n", + "scientific applications such as solid state physics, nonlinear optics and\n", + "quantum field theory [[abdul08]](#abdul08). The equation is given as" + ] + }, + { + "cell_type": "markdown", + "id": "83b245d3", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\frac{\\partial^2 u}{\\partial t^2} = \\nabla^2 u - \\gamma(u - u|u|^2) \\quad\n", + "\\text{for} \\, u \\in\n", + "\\Omega, \\label{eq:kg} \\tag{1}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "10fb3c95", + "metadata": { + "editable": true + }, + "source": [ + "with initial conditions" + ] + }, + { + "cell_type": "markdown", + "id": "e4bb65b4", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(\\boldsymbol{x}, t=0) = u^0 \\quad \\text{and} \\quad \\frac{\\partial u(\\boldsymbol{x},\n", + "t=0)}{\\partial t} = u_t^0. \\label{eq:init} \\tag{2}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "10adb615", + "metadata": { + "editable": true + }, + "source": [ + "The spatial coordinates are here denoted as $\\boldsymbol{x} = (x, y, z)$, and\n", + "$t$ is time. The parameter $\\gamma=\\pm 1$ determines whether the equations are focusing\n", + "($+1$) or defocusing ($-1$) (in the movie we have used $\\gamma=1$).\n", + "The domain $\\Omega=[-2\\pi, 2\\pi)^3$ is triply\n", + "periodic and initial conditions will here be set as" + ] + }, + { + "cell_type": "markdown", + "id": "40131bb3", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u^0 = 0.1 \\exp \\left( -\\boldsymbol{x} \\cdot \\boldsymbol{x} \\right), \n", + "\\label{_auto1} \\tag{3}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "53595408", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "u_t^0 = 0.\n", + "\\label{_auto2} \\tag{4}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "4c365136", + "metadata": { + "editable": true + }, + "source": [ + "We will solve these equations using a mixed formulation and a spectral Galerkin\n", + "method. The mixed formulation reads" + ] + }, + { + "cell_type": "markdown", + "id": "66f1256e", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\frac{\\partial f}{\\partial t} = \\nabla^2 u - \\gamma (u - u|u|^2), \\label{eq:df} \\tag{5}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "8eb65116", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\frac{\\partial u}{\\partial t} = f. \\label{eq:du} \\tag{6}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "ea17eddc", + "metadata": { + "editable": true + }, + "source": [ + "The energy of the solution can be computed as" + ] + }, + { + "cell_type": "markdown", + "id": "9e81800c", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "E(u) = \\int_{\\Omega} \\left( \\frac{1}{2} f^2 + \\frac{1}{2}|\\nabla u|^2 + \\gamma(\\frac{1}{2}u^2 - \\frac{1}{4}u^4) \\right) dx\n", + "\\label{_auto3} \\tag{7}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "b53f8a5b", + "metadata": { + "editable": true + }, + "source": [ + "and it is crucial that this energy remains constant in time.\n", + "\n", + "The movie above is showing the solution $u$, computed with the\n", + "code shown below." + ] + }, + { + "cell_type": "markdown", + "id": "c6e00bc7", + "metadata": { + "editable": true + }, + "source": [ + "## Spectral Galerkin formulation\n", + "\n", + "The PDEs in ([5](#eq:df)) and ([6](#eq:du)) can be solved with many different\n", + "numerical methods. We will here use the [shenfun](https://github.com/spectralDNS/shenfun) software and this software makes use of\n", + "the spectral Galerkin method. Being a Galerkin method, we need to reshape the\n", + "governing equations into proper variational forms, and this is done by\n", + "multiplying ([5](#eq:df)) and ([6](#eq:du)) with the complex conjugate of proper\n", + "test functions and then integrating\n", + "over the domain. To this end we make use of the triply periodic tensor product\n", + "function space $W^{\\boldsymbol{N}}(\\Omega)$ (defined in Eq. ([14](#eq:kg:Wn)))\n", + "and use testfunctions $g \\in W^{\\boldsymbol{N}}$\n", + "with Eq. ([5](#eq:df)) and $v \\in W^{\\boldsymbol{N}}$ with Eq. ([6](#eq:du)),\n", + "and obtain" + ] + }, + { + "cell_type": "markdown", + "id": "fedc6701", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\frac{\\partial}{\\partial t} \\int_{\\Omega} f\\, \\overline{g}\\, w \\,d\\Omega = \\int_{\\Omega}\n", + "\\left(\\nabla^2 u - \\gamma( u\\, - u|u|^2) \\right) \\overline{g} \\, w \\,d\\Omega, \\label{eq:df_var} \\tag{8} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "08ad1175", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\frac{\\partial }{\\partial t} \\int_{\\Omega} u\\, \\overline{v}\\, w \\, dx =\n", + "\\int_{\\Omega} f\\, \\overline{v} \\, w \\, d\\Omega. \\label{eq:kg:du_var} \\tag{9}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "fbf5fa50", + "metadata": { + "editable": true + }, + "source": [ + "Note that the overline is used to indicate a complex conjugate, and\n", + "$w$ is a weight function associated with the test functions. The functions\n", + "$f$ and $u$ are now\n", + "to be considered as trial functions, and the integrals over the\n", + "domain are referred to as inner products. With inner product notation" + ] + }, + { + "cell_type": "markdown", + "id": "4979f581", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\left(u, v\\right) = \\int_{\\Omega} u \\, \\overline{v} \\, w\\, dx.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "3e695b09", + "metadata": { + "editable": true + }, + "source": [ + "and an integration by parts on the Laplacian, the variational problem can be\n", + "formulated as:" + ] + }, + { + "cell_type": "markdown", + "id": "36f5f08f", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\frac{\\partial}{\\partial t} (f, g) = -(\\nabla u, \\nabla g)\n", + "-\\gamma \\left( u - u|u|^2, g \\right), \\label{eq:df_var2} \\tag{10} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "781f3602", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\frac{\\partial }{\\partial t} (u, v) = (f, v). \\label{eq:kg:du_var2} \\tag{11}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "24226db7", + "metadata": { + "editable": true + }, + "source": [ + "The time and space discretizations are\n", + "still left open. There are numerous different approaches that one could take for\n", + "discretizing in time, and the first two terms on the right hand side of\n", + "([10](#eq:df_var2)) can easily be treated implicitly as well as explicitly. However,\n", + "the approach we will follow in Sec. ([Runge-Kutta integrator](#sec:rk)) is a fully explicit 4th order [Runge-Kutta](https://en.wikipedia.org/wiki/Runge-Kutta_methods) method. Also note that\n", + "the inner product in the demo will be computed numerically with quadrature\n", + "through fast Fourier transforms, and the integrals are thus not computed exactly\n", + "for all terms." + ] + }, + { + "cell_type": "markdown", + "id": "1465f0a3", + "metadata": { + "editable": true + }, + "source": [ + "## Discretization\n", + "To find a numerical solution we need to discretize the continuous problem\n", + "([10](#eq:df_var2)) and ([11](#eq:kg:du_var2)) in space as well as time. Since the\n", + "problem is triply periodic, Fourier exponentials are normally the best choice\n", + "for trial and test functions, and as such we use basis functions" + ] + }, + { + "cell_type": "markdown", + "id": "4d5445cd", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\phi_l(x) = e^{\\imath \\underline{l} x}, \\quad -\\infty < l < \\infty,\n", + "\\label{_auto4} \\tag{12}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "5f2a57dd", + "metadata": { + "editable": true + }, + "source": [ + "where $l$ is the wavenumber, and\n", + "$\\underline{l}=\\frac{2\\pi}{L}l$ is the scaled wavenumber, scaled with domain\n", + "length $L$ (here $4\\pi$). Since we want to solve these equations on a computer, we need to choose\n", + "a finite number of test functions. A function space $V^N$ can be defined as" + ] + }, + { + "cell_type": "markdown", + "id": "b90d937b", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "V^N(x) = \\text{span} \\{\\phi_l(x)\\}_{l\\in \\boldsymbol{l}}, \\label{eq:kg:Vn} \\tag{13}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "01bd92d5", + "metadata": { + "editable": true + }, + "source": [ + "where $N$ is chosen as an even positive integer and $\\boldsymbol{l} = -N/2,\n", + "-N/2+1, \\ldots, N/2-1$. And now, since $\\Omega$ is a\n", + "three-dimensional domain, we can create tensor products of such bases to get,\n", + "e.g., for three dimensions" + ] + }, + { + "cell_type": "markdown", + "id": "59d5f2f3", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "W^{\\boldsymbol{N}}(x, y, z) = V^N(x) \\otimes V^N(y) \\otimes V^N(z), \\label{eq:kg:Wn} \\tag{14}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "68961d5f", + "metadata": { + "editable": true + }, + "source": [ + "where $\\boldsymbol{N} = (N, N, N)$. Obviously, it is not necessary to use the\n", + "same number ($N$) of basis functions for each direction, but it is done here\n", + "for simplicity. A 3D tensor product basis function is now defined as" + ] + }, + { + "cell_type": "markdown", + "id": "04821397", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\Phi_{lmn}(x,y,z) = e^{\\imath \\underline{l} x} e^{\\imath \\underline{m} y}\n", + "e^{\\imath \\underline{n} z} = e^{\\imath\n", + "(\\underline{l}x + \\underline{m}y + \\underline{n}z)},\n", + "\\label{_auto5} \\tag{15}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e9a3ffab", + "metadata": { + "editable": true + }, + "source": [ + "where the indices for $y$- and $z$-direction are $\\underline{m}=\\frac{2\\pi}{L}m,\n", + "\\underline{n}=\\frac{2\\pi}{L}n$, and $\\boldsymbol{m}$ and $\\boldsymbol{n}$ are the same as\n", + "$\\boldsymbol{l}$ due to using the same number of basis functions for each direction. One\n", + "distinction, though, is that for the $z$-direction expansion coefficients are only stored for\n", + "$n=0, 1, \\ldots, N/2$ due to Hermitian symmetry (real input data). However, for simplicity,\n", + "we still write the sum in Eq. ([16](#eq:usg)) over the entire range of basis functions.\n", + "\n", + "We now look for solutions of the form" + ] + }, + { + "cell_type": "markdown", + "id": "382c00cb", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(x, y, z, t) = \\sum_{l=-N/2}^{N/2-1}\\sum_{m=-N/2}^{N/2-1}\\sum_{n=-N/2}^{N/2-1}\n", + "\\hat{u}_{lmn} (t)\\Phi_{lmn}(x,y,z). \\label{eq:usg} \\tag{16}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "016c1249", + "metadata": { + "editable": true + }, + "source": [ + "The expansion coefficients $\\hat{\\boldsymbol{u}} = \\{\\hat{u}_{lmn}(t)\\}_{(l,m,n) \\in \\boldsymbol{l} \\times \\boldsymbol{m} \\times \\boldsymbol{n}}$\n", + "can be related directly to the solution $u(x, y, z, t)$ using Fast\n", + "Fourier Transforms (FFTs) if we are satisfied with obtaining\n", + "the solution in quadrature points corresponding to" + ] + }, + { + "cell_type": "markdown", + "id": "84463f92", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " x_i = \\frac{4 \\pi i}{N}-2\\pi \\quad \\forall \\, i \\in \\boldsymbol{i},\n", + "\\text{where}\\, \\boldsymbol{i}=(0,1,\\ldots,N-1), \n", + "\\label{_auto6} \\tag{17}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1f16ed28", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " y_j = \\frac{4 \\pi j}{N}-2\\pi \\quad \\forall \\, j \\in \\boldsymbol{j},\n", + "\\text{where}\\, \\boldsymbol{j}=(0,1,\\ldots,N-1), \n", + "\\label{_auto7} \\tag{18}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "28257dfb", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " z_k = \\frac{4 \\pi k}{N}-2\\pi \\quad \\forall \\, k \\in \\boldsymbol{k},\n", + "\\text{where}\\, \\boldsymbol{k}=(0,1,\\ldots,N-1).\n", + "\\label{_auto8} \\tag{19}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "df5dd8f4", + "metadata": { + "editable": true + }, + "source": [ + "Note that these points are different from the standard (like $2\\pi j/N$) since\n", + "the domain\n", + "is set to $[-2\\pi, 2\\pi]^3$ and not the more common $[0, 2\\pi]^3$. We have" + ] + }, + { + "cell_type": "markdown", + "id": "e5ad43ee", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\boldsymbol{u} = \\mathcal{F}_x^{-1}\\left(\\mathcal{F}_y^{-1}\\left(\\mathcal{F}_z^{-1}\\left(\\hat{\\boldsymbol{u}}\\right)\\right)\\right) \\label{eq:uxyz} \\tag{20}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "332d71ce", + "metadata": { + "editable": true + }, + "source": [ + "with $\\boldsymbol{u} = \\{u(x_i, y_j, z_k)\\}_{(i,j,k)\\in \\boldsymbol{i} \\times \\boldsymbol{j} \\times \\boldsymbol{k}}$\n", + "and where $\\mathcal{F}_x^{-1}$ is the inverse Fourier transform along the direction $x$, for\n", + "all indices in the other direction. Note that the three\n", + "inverse FFTs are performed sequentially, one direction at the time, and that there is no\n", + "scaling factor due to\n", + "the definition used for the inverse [Fourier transform](https://mpi4py-fft.readthedocs.io/en/latest/dft.html)" + ] + }, + { + "cell_type": "markdown", + "id": "e18610fd", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(x_j) = \\sum_{l=-N/2}^{N/2-1} \\hat{u}_l e^{\\imath \\underline{l}\n", + "x_j}, \\quad \\,\\, \\forall \\, j \\in \\, \\boldsymbol{j}.\n", + "\\label{_auto9} \\tag{21}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f384ac43", + "metadata": { + "editable": true + }, + "source": [ + "Note that this differs from the definition used by, e.g.,\n", + "[Numpy](https://docs.scipy.org/doc/numpy-1.13.0/reference/routines.fft.html).\n", + "\n", + "The inner products used in Eqs. ([10](#eq:df_var2)), ([11](#eq:kg:du_var2)) may be\n", + "computed using forward FFTs. However, there is a tiny detail that deserves\n", + "a comment. The regular Fourier inner product is given as" + ] + }, + { + "cell_type": "markdown", + "id": "928dbba0", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\int_{0}^{L} e^{\\imath \\underline{k}x} e^{- \\imath \\underline{l}x} dx = L\\, \\delta_{kl}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "157f8783", + "metadata": { + "editable": true + }, + "source": [ + "where a weight function is chosen as $w(x) = 1$ and $\\delta_{kl}$ equals unity\n", + "for $k=l$ and zero otherwise. In Shenfun we choose instead to use a weight\n", + "function $w(x)=1/L$, such that the weighted inner product integrates to\n", + "unity:" + ] + }, + { + "cell_type": "markdown", + "id": "6b9f5897", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\int_{0}^{L} e^{\\imath \\underline{k}x} e^{- \\imath \\underline{l}x} \\frac{1}{L} dx = \\delta_{kl}.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "84026af7", + "metadata": { + "editable": true + }, + "source": [ + "With this weight function the (discrete) scalar product and the forward transform\n", + "are the same and we obtain:" + ] + }, + { + "cell_type": "markdown", + "id": "98b58094", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\left(u, v \\right) = \\boldsymbol{\\hat{u}} =\n", + "\\left(\\frac{1}{N}\\right)^3\n", + "\\mathcal{F}_z\\left(\\mathcal{F}_y\\left(\\mathcal{F}_x\\left(\\boldsymbol{u}\\right)\\right)\\right).\n", + "\\label{_auto10} \\tag{22}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "736c335d", + "metadata": { + "editable": true + }, + "source": [ + "From this we see that the variational forms ([10](#eq:df_var2)) and ([11](#eq:kg:du_var2))\n", + "may be written in terms of the Fourier transformed quantities $\\hat{\\boldsymbol{u}}$ and\n", + "$\\hat{\\boldsymbol{f}}$. Expanding the exact derivatives of the nabla operator, we have" + ] + }, + { + "cell_type": "markdown", + "id": "e0edb86f", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "(\\nabla u, \\nabla v) =\n", + "\\left((\\underline{l}^2+\\underline{m}^2+\\underline{n}^2)\\hat{u}_{lmn}\\right), \n", + "\\label{_auto11} \\tag{23}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "3d2ba41c", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "(u, v) = \\left(\\hat{u}_{lmn}\\right), \n", + "\\label{_auto12} \\tag{24}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "6ecb4c2c", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "(u|u|^2, v) = \\left(\\widehat{u|u|^2}_{lmn}\\right)\n", + "\\label{_auto13} \\tag{25}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "fdc7f2d9", + "metadata": { + "editable": true + }, + "source": [ + "where the indices on the right hand side run over $(l, m, n) \\in \\boldsymbol{l} \\times \\boldsymbol{m} \\times \\boldsymbol{n}$.\n", + "The equations to be solved for each wavenumber can now be found directly as" + ] + }, + { + "cell_type": "markdown", + "id": "19dc93b3", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\frac{\\partial \\hat{f}_{lmn}}{\\partial t} =\n", + "\\left(-(\\underline{l}^2+\\underline{m}^2+\\underline{n}^2+\\gamma)\\hat{u}_{lnm} + \\gamma \\widehat{u|u|^2}_{lnm}\\right), \\label{eq:df_var3} \\tag{26} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "95c68d2a", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\frac{\\partial \\hat{u}_{lnm}}{\\partial t} = \\hat{f}_{lnm}. \\label{eq:kg:du_var3} \\tag{27}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "04ae7faf", + "metadata": { + "editable": true + }, + "source": [ + "There is more than one way to arrive at these equations. Taking the 3D Fourier\n", + "transform of both equations ([5](#eq:df)) and ([6](#eq:du)) is one obvious way.\n", + "With the Python module [shenfun](https://github.com/spectralDNS/shenfun), one can work with the\n", + "inner products as seen in ([10](#eq:df_var2)) and ([11](#eq:kg:du_var2)), or the Fourier\n", + "transforms directly. See for example Sec. [Runge-Kutta integrator](#sec:rk) for how $(\\nabla u, \\nabla\n", + "v)$ can be\n", + "implemented. In short, [shenfun](https://shenfun.readthedocs.io/en/latest/shenfun.html#module-shenfun) contains all the tools required to work with\n", + "the spectral Galerkin method, and we will now see how [shenfun](https://shenfun.readthedocs.io/en/latest/shenfun.html#module-shenfun) can be used to solve\n", + "the Klein-Gordon equation.\n", + "\n", + "For completion, we note that the discretized problem to solve can be formulated\n", + "with the Galerkin method as:\n", + "for all $t>0$, find $(f, u) \\in W^N \\times W^N$ such that" + ] + }, + { + "cell_type": "markdown", + "id": "4df82afa", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\frac{\\partial}{\\partial t} (f, g) = -(\\nabla u, \\nabla g)\n", + "-\\gamma \\left( u - u|u|^2, g \\right) \\quad \\forall \\, g \\in W^{N}, \\label{eq:dff} \\tag{28} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "b08ed918", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\frac{\\partial }{\\partial t} (u, v) = (f, v) \\quad \\forall \\, v \\in W^N. \\label{eq:kg:duu} \\tag{29}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "a339ed0f", + "metadata": { + "editable": true + }, + "source": [ + "where $u(x, y, z, 0)$ and $f(x, y, z, 0)$ are given as the initial conditions\n", + "according to Eq. ([2](#eq:init))." + ] + }, + { + "cell_type": "markdown", + "id": "847c4d2e", + "metadata": { + "editable": true + }, + "source": [ + "## Implementation\n", + "\n", + "To solve the Klein-Gordon equations we need to make use of the Fourier function\n", + "spaces defined in\n", + "[shenfun](https://shenfun.readthedocs.io/en/latest/shenfun.html#module-shenfun), and these are found in submodule\n", + "[shenfun.fourier.bases](https://shenfun.readthedocs.io/en/latest/shenfun.fourier.html#module-shenfun.fourier.bases).\n", + "The triply periodic domain allows for Fourier in all three directions, and we\n", + "can as such create one instance of this space using [FunctionSpace()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.FunctionSpace) with\n", + "family ``Fourier``\n", + "for each direction. However, since the initial data are real, we\n", + "can take advantage of Hermitian symmetries and thus make use of a\n", + "real to complex class for one (but only one) of the directions, by specifying\n", + "``dtype='d'``. We can only make use of the\n", + "real-to-complex class for the direction that we choose to transform first with the forward\n", + "FFT, and the reason is obviously that the output from a forward transform of\n", + "real data is now complex. We may start implementing the solver as follows" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "82b448d1", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:26.278317Z", + "iopub.status.busy": "2024-05-24T12:36:26.277928Z", + "iopub.status.idle": "2024-05-24T12:36:26.919575Z", + "shell.execute_reply": "2024-05-24T12:36:26.917868Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from shenfun import *\n", + "import numpy as np\n", + "import sympy as sp\n", + "\n", + "# Set size of discretization\n", + "N = (32, 32, 32)\n", + "\n", + "# Defocusing or focusing\n", + "gamma = 1\n", + "\n", + "rank = comm.Get_rank()\n", + "\n", + "# Create function spaces\n", + "K0 = FunctionSpace(N[0], 'F', domain=(-2*np.pi, 2*np.pi), dtype='D')\n", + "K1 = FunctionSpace(N[1], 'F', domain=(-2*np.pi, 2*np.pi), dtype='D')\n", + "K2 = FunctionSpace(N[2], 'F', domain=(-2*np.pi, 2*np.pi), dtype='d')" + ] + }, + { + "cell_type": "markdown", + "id": "6be0674c", + "metadata": { + "editable": true + }, + "source": [ + "We now have three instances `K0`, `K1` and `K2`, corresponding to the space\n", + "([13](#eq:kg:Vn)), that each can be used to solve\n", + "one-dimensional problems. However, we want to solve a 3D problem, and for this\n", + "we need a tensor product space, like ([14](#eq:kg:Wn)), created as a tensor\n", + "product of these three spaces" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "31bae268", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:26.923540Z", + "iopub.status.busy": "2024-05-24T12:36:26.923329Z", + "iopub.status.idle": "2024-05-24T12:36:26.946586Z", + "shell.execute_reply": "2024-05-24T12:36:26.945459Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "T = TensorProductSpace(comm, (K0, K1, K2), **{'planner_effort':\n", + " 'FFTW_MEASURE'})" + ] + }, + { + "cell_type": "markdown", + "id": "bf3976b2", + "metadata": { + "editable": true + }, + "source": [ + "Here the `planner_effort`, which is a flag used by [FFTW](http://www.fftw.org), is optional. Possibel choices are from the list\n", + "(`FFTW_ESTIMATE`, `FFTW_MEASURE`, `FFTW_PATIENT`, `FFTW_EXHAUSTIVE`), and the\n", + "flag determines how much effort FFTW puts in looking for an optimal algorithm\n", + "for the current platform. Note that it is also possible to use FFTW [wisdom](http://www.fftw.org/fftw3_doc/Wisdom.html#Wisdom) with\n", + "`shenfun`, and as such, for production, one may perform exhaustive planning once\n", + "and then simply import the result of that planning later, as wisdom.\n", + "\n", + "The [TensorProductSpace](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.tensorproductspace.TensorProductSpace) instance `T` contains pretty much all we need for\n", + "computing inner products or fast transforms between real and wavenumber space.\n", + "However, since we are going to solve for a mixed system, it is convenient to also use the\n", + "[CompositeSpace](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.tensorproductspace.CompositeSpace) class" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7eb29c91", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:26.951144Z", + "iopub.status.busy": "2024-05-24T12:36:26.950928Z", + "iopub.status.idle": "2024-05-24T12:36:26.955036Z", + "shell.execute_reply": "2024-05-24T12:36:26.954215Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "TT = CompositeSpace([T, T])\n", + "TV = VectorSpace(T)" + ] + }, + { + "cell_type": "markdown", + "id": "5e029c38", + "metadata": { + "editable": true + }, + "source": [ + "Here the space `TV` will be used to compute gradients, which\n", + "explains why it is a vector.\n", + "\n", + "We need containers for the solution as well as intermediate work arrays for,\n", + "e.g., the Runge-Kutta method. Arrays are created using\n", + "[Sympy](http://www.sympy.org/en/index.html) for\n", + "initialization. Below `f` is initialized to 0,\n", + "whereas `u = 0.1*sp.exp(-(x**2 + y**2 + z**2))`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ce384d37", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:26.958453Z", + "iopub.status.busy": "2024-05-24T12:36:26.958340Z", + "iopub.status.idle": "2024-05-24T12:36:27.131100Z", + "shell.execute_reply": "2024-05-24T12:36:27.130042Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "# Use sympy to set up initial condition\n", + "x, y, z = sp.symbols(\"x,y,z\", real=True)\n", + "ue = 0.1*sp.exp(-(x**2 + y**2 + z**2))\n", + "\n", + "fu = Array(TT, buffer=(0, ue)) # Solution array in physical space\n", + "f, u = fu # Split solution array by creating two views u and f\n", + "dfu = Function(TT) # Array for right hand sides\n", + "df, du = dfu # Split into views\n", + "Tp = T.get_dealiased((1.5, 1.5, 1.5))\n", + "up = Array(Tp) # Work array\n", + "\n", + "fu_hat = Function(TT) # Solution in spectral space\n", + "fu_hat = fu.forward()\n", + "f_hat, u_hat = fu_hat\n", + "\n", + "gradu = Array(TV) # Solution array for gradient" + ] + }, + { + "cell_type": "markdown", + "id": "0f7e0745", + "metadata": { + "editable": true + }, + "source": [ + "The [Array](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Array) class is a subclass of Numpy's [ndarray](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html),\n", + "without much more functionality than constructors that return arrays of the\n", + "correct shape according to the basis used in the construction. The\n", + "[Array](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Array) represents the left hand side of ([16](#eq:usg)),\n", + "evaluated on the quadrature mesh. A different type\n", + "of array is returned by the [Function](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Function)\n", + "class, that subclasses both Nympy's ndarray as well as an internal\n", + "[BasisFunction](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.BasisFunction)\n", + "class. An instance of the [Function](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Function) represents the entire\n", + "spectral Galerkin function ([16](#eq:usg))." + ] + }, + { + "cell_type": "markdown", + "id": "cf89575c", + "metadata": { + "editable": true + }, + "source": [ + "### Runge-Kutta integrator\n", + "\n", + "\n", + "\n", + "We use an explicit fourth order Runge-Kutta integrator,\n", + "imported from [shenfun.utilities.integrators](https://shenfun.readthedocs.io/en/latest/shenfun.utilities.html#module-shenfun.utilities.integrators). The solver\n", + "requires one function to compute nonlinear terms,\n", + "and one to compute linear. But here we will make\n", + "just one function that computes both, and call it\n", + "`NonlinearRHS`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e982a934", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:27.133933Z", + "iopub.status.busy": "2024-05-24T12:36:27.133807Z", + "iopub.status.idle": "2024-05-24T12:36:27.148529Z", + "shell.execute_reply": "2024-05-24T12:36:27.148100Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "uh = TrialFunction(T)\n", + "vh = TestFunction(T)\n", + "L = inner(grad(vh), -grad(uh)) + [inner(vh, -gamma*uh)]\n", + "L = la.SolverDiagonal(L).mat.scale\n", + "\n", + "def NonlinearRHS(self, fu, fu_hat, dfu_hat, **par):\n", + " global count, up\n", + " dfu_hat.fill(0)\n", + " f_hat, u_hat = fu_hat\n", + " df_hat, du_hat = dfu_hat\n", + " up = Tp.backward(u_hat, up)\n", + " df_hat = Tp.forward(gamma*up**3, df_hat)\n", + " df_hat += L*u_hat\n", + " du_hat[:] = f_hat\n", + " return dfu_hat" + ] + }, + { + "cell_type": "markdown", + "id": "29c06ebf", + "metadata": { + "editable": true + }, + "source": [ + "Note that `L` now is an array that represents the linear\n", + "coefficients in ([27](#eq:kg:du_var3)).\n", + "\n", + "All that is left is to write a function that is called\n", + "on each time step, which will allow us to store intermediate\n", + "solutions, compute intermediate energies, and plot\n", + "intermediate solutions. Since we will plot the same plot\n", + "many times, we create the figure first, and then simply update\n", + "the plotted arrays in the `update` function." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1f4ce1d4", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:27.150490Z", + "iopub.status.busy": "2024-05-24T12:36:27.150385Z", + "iopub.status.idle": "2024-05-24T12:36:27.471764Z", + "shell.execute_reply": "2024-05-24T12:36:27.470806Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "X = T.local_mesh(True)\n", + "if rank == 0:\n", + " plt.figure()\n", + " image = plt.contourf(X[1][..., 0], X[0][..., 0], u[..., N[2]//2], 100)\n", + " plt.draw()\n", + " plt.pause(1e-6)" + ] + }, + { + "cell_type": "markdown", + "id": "09b92d8a", + "metadata": { + "editable": true + }, + "source": [ + "The actual `update` function is" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0547e688", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:27.474593Z", + "iopub.status.busy": "2024-05-24T12:36:27.474345Z", + "iopub.status.idle": "2024-05-24T12:36:27.481967Z", + "shell.execute_reply": "2024-05-24T12:36:27.481560Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "# Get wavenumbers\n", + "K = np.array(T.local_wavenumbers(True, True, True))\n", + "\n", + "def update(self, fu, fu_hat, t, tstep, **params):\n", + " global gradu\n", + "\n", + " transformed = False\n", + " if rank == 0 and tstep % params['plot_tstep'] == 0 and params['plot_tstep'] > 0:\n", + " fu = fu_hat.backward(fu)\n", + " f, u = fu[:]\n", + " self.image = plt.contourf(X[1][..., 0], X[0][..., 0], u[..., N[2]//2], 100)\n", + " display(self.image, clear=True)\n", + " plt.pause(1e-6)\n", + " transformed = True\n", + "\n", + " if tstep % params['Compute_energy'] == 0:\n", + " if transformed is False:\n", + " fu = fu_hat.backward(fu)\n", + " f, u = fu\n", + " f_hat, u_hat = fu_hat\n", + " ekin = 0.5*energy_fourier(f_hat, T)\n", + " es = 0.5*energy_fourier(1j*(K*u_hat), T)\n", + " eg = gamma*np.sum(0.5*u**2 - 0.25*u**4)/np.prod(np.array(N))\n", + " eg = comm.allreduce(eg)\n", + " gradu = TV.backward(1j*(K[0]*u_hat[0]+K[1]*u_hat[1]+K[2]*u_hat[2]), gradu)\n", + " ep = comm.allreduce(np.sum(f*gradu)/np.prod(np.array(N)))\n", + " ea = comm.allreduce(np.sum(np.array(X)*(0.5*f**2 + 0.5*gradu**2 - (0.5*u**2 - 0.25*u**4)*f))/np.prod(np.array(N)))\n", + " if rank == 0:\n", + " params['energy'][0] += \"Time = %2.2f Total energy = %2.8e Linear momentum %2.8e Angular momentum %2.8e \\n\" %(t, ekin+es+eg, ep, ea)\n", + " print(params['energy'][0])\n", + " comm.barrier()" + ] + }, + { + "cell_type": "markdown", + "id": "2654c25b", + "metadata": { + "editable": true + }, + "source": [ + "With all functions in place, the actual integrator\n", + "can be created and called as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b5ab745a", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:27.484111Z", + "iopub.status.busy": "2024-05-24T12:36:27.484008Z", + "iopub.status.idle": "2024-05-24T12:36:31.573499Z", + "shell.execute_reply": "2024-05-24T12:36:31.572872Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "par = {'Compute_energy': 10,\n", + " 'plot_tstep': 10,\n", + " 'end_time': 1}\n", + "dt = 0.005\n", + "integrator = RK4(TT, N=NonlinearRHS, update=update, energy=[\"\"], **par)\n", + "integrator.setup(dt)\n", + "fu_hat = integrator.solve(fu, fu_hat, dt, (0, par['end_time']))" + ] + }, + { + "cell_type": "markdown", + "id": "57859b90", + "metadata": { + "editable": true + }, + "source": [ + "A complete solver is found [here](https://github.com/spectralDNS/shenfun/blob/master/demo/KleinGordon.py).\n", + "\n", + "\n", + "\n", + "1. **A.-M. Wazwaz**. New Travelling Wave Solutions to the Boussinesq and the Klein-Gordon Equations, *Communications in Nonlinear Science and Numerical Simulation*, 13(5), pp. 889-901, [doi: 10.1016/j.cnsns.2006.08.005](https://dx.doi.org/10.1016/j.cnsns.2006.08.005), 2008." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/KuramatoSivashinsky/kuramatosivashinsky.ipynb b/docs/demos/KuramatoSivashinsky/kuramatosivashinsky.ipynb new file mode 100644 index 00000000..02787a75 --- /dev/null +++ b/docs/demos/KuramatoSivashinsky/kuramatosivashinsky.ipynb @@ -0,0 +1,961 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "0495226a", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - Kuramato-Sivashinsky equation\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **April 13, 2018**\n", + "\n", + "**Summary.** This is a demonstration of how the Python module [shenfun](https://github.com/spectralDNS/shenfun) can be used to solve the time-dependent,\n", + "nonlinear Kuramato-Sivashinsky equation, in a doubly periodic domain. The demo is implemented in\n", + "a single Python file [KuramatoSivashinsky.py](https://github.com/spectralDNS/shenfun/blob/master/demo/Kuramato_Sivashinsky.py), and it may be run\n", + "in parallel using MPI.\n", + "\n", + "\n", + "\n", + "\n", + "

Figure 1: Movie showing the evolution of the solution of the Kuramato-Sivashinsky equation.

\n", + "" + ] + }, + { + "cell_type": "markdown", + "id": "1b82a490", + "metadata": { + "editable": true + }, + "source": [ + "## The Kuramato-Sivashinsky equation\n", + "\n", + "The Kuramato-Sivashinsky (KS) equation is known for its chaotic bahaviour, and it is\n", + "often used in study of turbulence or turbulent combustion. We will here solve\n", + "the KS equation in a doubly periodic domain $\\Omega=[-30\\pi, 30\\pi)^2$, starting from a\n", + "single Gaussian pulse" + ] + }, + { + "cell_type": "markdown", + "id": "40f1ebeb", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\frac{\\partial u(\\boldsymbol{x},t)}{\\partial t} + \\nabla^2 u(\\boldsymbol{x},t) + \\nabla^4\n", + "u(\\boldsymbol{x},t) + |\\nabla u(\\boldsymbol{x},t)|^2 = 0 \\quad \\text{for }\\, \\boldsymbol{x} \\in \\Omega\n", + "\\label{eq:ks} \\tag{1} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "0bf3843e", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "u(\\boldsymbol{x}, 0) = \\exp(-0.01 \\boldsymbol{x} \\cdot \\boldsymbol{x}) \\notag\n", + "\\label{_auto1} \\tag{2}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "a3f91340", + "metadata": { + "editable": true + }, + "source": [ + "## Spectral Galerkin method\n", + "\n", + "\n", + "The PDE in ([1](#eq:ks)) can be solved with many different\n", + "numerical methods. We will here use the [shenfun](https://github.com/spectralDNS/shenfun) software and this software makes use of\n", + "the spectral Galerkin method. Being a Galerkin method, we need to reshape the\n", + "governing equations into proper variational forms, and this is done by\n", + "multiplying ([1](#eq:ks)) with the complex conjugate of a proper\n", + "test function and then integrating\n", + "over the domain. To this end we use testfunction $v\\in W^N(\\Omega)$, where $W^N(\\Omega)$\n", + "is a suitable function space (defined in Eq. ([7](#eq:Wn))), and obtain" + ] + }, + { + "cell_type": "markdown", + "id": "36175e5e", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\frac{\\partial}{\\partial t} \\int_{\\Omega} u\\, \\overline{v}\\, w \\,dx = -\\int_{\\Omega}\n", + "\\left(\\nabla^2 u + \\nabla^4 u \\ + |\\nabla u|^2 \\right) \\overline{v} \\, w \\,dx.\n", + "\\label{eq:du_var} \\tag{3}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "0b70e9df", + "metadata": { + "editable": true + }, + "source": [ + "Note that the overline is used to indicate a complex conjugate, whereas $w$\n", + "is a weight function. The function $u$\n", + "is now to be considered a trial function, and the integrals over the\n", + "domain are often referred to as inner products. With inner product notation" + ] + }, + { + "cell_type": "markdown", + "id": "ce485733", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\left(u, v\\right) = \\int_{\\Omega} u \\, \\overline{v} \\, w \\, dx.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "571d5c61", + "metadata": { + "editable": true + }, + "source": [ + "the variational problem can be formulated as" + ] + }, + { + "cell_type": "markdown", + "id": "e0115f99", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\frac{\\partial}{\\partial t} (u, v) = -\\left(\\nabla^2 u + \\nabla^4 u + |\\nabla u|^2,\n", + "v \\right). \\label{eq:du_var2} \\tag{4}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "4bd736f6", + "metadata": { + "editable": true + }, + "source": [ + "The space and time discretizations are\n", + "still left open. There are numerous different approaches that one could take for\n", + "discretizing in time. Here we will use a fourth order exponential Runge-Kutta\n", + "method." + ] + }, + { + "cell_type": "markdown", + "id": "a3163d74", + "metadata": { + "editable": true + }, + "source": [ + "## Discretization\n", + "\n", + "We discretize the model equation in space using continuously differentiable\n", + "Fourier basis functions" + ] + }, + { + "cell_type": "markdown", + "id": "1316d7f3", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\phi_l(x) = e^{\\imath \\underline{l} x}, \\quad -\\infty < l < \\infty,\n", + "\\label{_auto2} \\tag{5}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "cbfa19f1", + "metadata": { + "editable": true + }, + "source": [ + "where $l$ is the wavenumber, and $\\underline{l}=\\frac{2\\pi}{L}l$ is the scaled wavenumber, scaled with domain\n", + "length $L$ (here $60\\pi$). Since we want to solve these equations on a computer, we need to choose\n", + "a finite number of test functions. A discrete function space $V^N$ can be defined as" + ] + }, + { + "cell_type": "markdown", + "id": "fdce7ce9", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "V^N(x) = \\text{span} \\{\\phi_l(x)\\}_{l\\in \\boldsymbol{l}}, \\label{eq:Vn} \\tag{6}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "621c6e53", + "metadata": { + "editable": true + }, + "source": [ + "where $N$ is chosen as an even positive integer and $\\boldsymbol{l} = (-N/2,\n", + "-N/2+1, \\ldots, N/2-1)$. And now, since $\\Omega$ is a\n", + "two-dimensional domain, we can create a tensor product of two such one-dimensional\n", + "spaces:" + ] + }, + { + "cell_type": "markdown", + "id": "d595ac98", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "W^{\\boldsymbol{N}}(x, y) = V^N(x) \\otimes V^N(y), \\label{eq:Wn} \\tag{7}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "aa8262e9", + "metadata": { + "editable": true + }, + "source": [ + "where $\\boldsymbol{N} = (N, N)$. Obviously, it is not necessary to use the\n", + "same number ($N$) of basis functions for each direction, but it is done here\n", + "for simplicity. A 2D tensor product basis function is now defined as" + ] + }, + { + "cell_type": "markdown", + "id": "46887195", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\Phi_{lm}(x,y) = e^{\\imath \\underline{l} x} e^{\\imath \\underline{m} y}\n", + "= e^{\\imath (\\underline{l}x + \\underline{m}y )},\n", + "\\label{_auto3} \\tag{8}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "90815bf3", + "metadata": { + "editable": true + }, + "source": [ + "where the indices for $y$-direction are $\\underline{m}=\\frac{2\\pi}{L}m$, and\n", + "$\\boldsymbol{m}$ is the same set as $\\boldsymbol{l}$ due to using the same number of basis functions for each direction. One\n", + "distinction, though, is that for the $y$-direction expansion coefficients are only stored for\n", + "$m=(0, 1, \\ldots, N/2)$ due to Hermitian symmetry (real input data).\n", + "\n", + "We now look for solutions of the form" + ] + }, + { + "cell_type": "markdown", + "id": "74359e27", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(x, y) = \\sum_{l=-N/2}^{N/2-1}\\sum_{m=-N/2}^{N/2-1}\n", + "\\hat{u}_{lm} \\Phi_{lm}(x,y).\n", + "\\label{_auto4} \\tag{9}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "4d8a5f2b", + "metadata": { + "editable": true + }, + "source": [ + "The expansion coefficients $\\hat{u}_{lm}$ can be related directly to the solution $u(x,\n", + "y)$ using Fast Fourier Transforms (FFTs) if we are satisfied with obtaining\n", + "the solution in quadrature points corresponding to" + ] + }, + { + "cell_type": "markdown", + "id": "fa50c86c", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " x_i = \\frac{60 \\pi i}{N}-30\\pi \\quad \\forall \\, i \\in \\boldsymbol{i},\n", + "\\text{where}\\, \\boldsymbol{i}=(0,1,\\ldots,N-1), \n", + "\\label{_auto5} \\tag{10}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "66c43e0d", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " y_j = \\frac{60 \\pi j}{N}-30\\pi \\quad \\forall \\, j \\in \\boldsymbol{j},\n", + "\\text{where}\\, \\boldsymbol{j}=(0,1,\\ldots,N-1).\n", + "\\label{_auto6} \\tag{11}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "bdd44fd7", + "metadata": { + "editable": true + }, + "source": [ + "Note that these points are different from the standard (like $2\\pi j/N$) since\n", + "the domain\n", + "is set to $[-30\\pi, 30\\pi]^2$ and not the more common $[0, 2\\pi]^2$. We now have" + ] + }, + { + "cell_type": "markdown", + "id": "ae46333a", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\boldsymbol{u} =\n", + "\\mathcal{F}_x^{-1}\\left(\\mathcal{F}_y^{-1}\\left(\\boldsymbol{\\hat{u}}\\right)\\right),\n", + "\\label{_auto7} \\tag{12}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "9ce62293", + "metadata": { + "editable": true + }, + "source": [ + "where $\\boldsymbol{u} = \\{u(x_i, y_j)\\}_{(i,j)\\in \\boldsymbol{i} \\times \\boldsymbol{j}}$,\n", + "$\\boldsymbol{\\hat{u}} = \\{\\hat{u}_{lm}\\}_{(l,m)\\in \\boldsymbol{l} \\times \\boldsymbol{m}}$\n", + "and $\\mathcal{F}_x^{-1}$ is the inverse Fourier transform along direction\n", + "$x$, for all indices in the other direction. Note that the two\n", + "inverse FFTs are performed sequentially, one direction at the time, and that\n", + "there is no scaling factor due\n", + "the definition used for the inverse\n", + "[Fourier transform](https://mpi4py-fft.readthedocs.io/en/latest/dft.html):" + ] + }, + { + "cell_type": "markdown", + "id": "2da0c841", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(x_j) = \\sum_{l=-N/2}^{N/2-1} \\hat{u}_l e^{\\imath \\underline{l}\n", + "x_j}, \\quad \\,\\, \\forall \\, j \\in \\, \\boldsymbol{j}.\n", + "\\label{_auto8} \\tag{13}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "bde1ab80", + "metadata": { + "editable": true + }, + "source": [ + "Note that this differs from the definition used by, e.g.,\n", + "[Numpy](https://docs.scipy.org/doc/numpy-1.13.0/reference/routines.fft.html).\n", + "\n", + "The inner products used in Eq. ([4](#eq:du_var2)) may be\n", + "computed using forward FFTs (using weight functions $w=1/L$):" + ] + }, + { + "cell_type": "markdown", + "id": "ff7d3819", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\boldsymbol{\\hat{u}} =\n", + "\\frac{1}{N^2}\n", + "\\mathcal{F}_y\\left(\\mathcal{F}_x\\left(\\boldsymbol{u}\\right)\\right),\n", + "\\label{_auto9} \\tag{14}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e3dcec3c", + "metadata": { + "editable": true + }, + "source": [ + "From this we see that the variational forms\n", + "may be written in terms of the Fourier transformed $\\hat{u}$. Expanding the\n", + "exact derivatives of the nabla operator, we have" + ] + }, + { + "cell_type": "markdown", + "id": "125917d9", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "(\\nabla^2 u, v) =\n", + "\\left(-(\\underline{l}^2+\\underline{m}^2)\\hat{u}_{lm}\\right), \n", + "\\label{_auto10} \\tag{15}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "de4984ae", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "(\\nabla^4 u, v) = \\left((\\underline{l}^2+\\underline{m}^2)^2\\hat{u}_{lm}\\right), \n", + "\\label{_auto11} \\tag{16}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "c7b90c06", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "(|\\nabla u|^2, v) = \\left(\\widehat{|\\nabla u|^2}_{lm}\\right),\n", + "\\label{_auto12} \\tag{17}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "72605910", + "metadata": { + "editable": true + }, + "source": [ + "where the indices on the right hand side run over $\\boldsymbol{l} \\times \\boldsymbol{m}$.\n", + "We find that the equation to be solved for each wavenumber can be found directly as" + ] + }, + { + "cell_type": "markdown", + "id": "f50b3d25", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\frac{\\partial \\hat{u}_{lm}}{\\partial t} =\n", + "\\left(\\underline{l}^2+\\underline{m}^2 -\n", + "(\\underline{l}^2+\\underline{m}^2)^2\\right)\\hat{u}_{lm} - \\widehat{|\\nabla u|^2}_{lm},\n", + "\\label{eq:du_var3} \\tag{18}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "20229c39", + "metadata": { + "editable": true + }, + "source": [ + "## Implementation\n", + "\n", + "The model equation ([1](#eq:ks)) is implemented in shenfun using Fourier basis functions for\n", + "both $x$ and $y$ directions. We start the solver by implementing necessary\n", + "functionality from required modules like [Numpy](https://numpy.org), [Sympy](https://sympy.org)\n", + "and [matplotlib](https://matplotlib.org), in\n", + "addition to [shenfun](https://github.com/spectralDNS/shenfun):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0c1a7c93", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:48.231256Z", + "iopub.status.busy": "2024-05-24T12:36:48.231055Z", + "iopub.status.idle": "2024-05-24T12:36:49.052248Z", + "shell.execute_reply": "2024-05-24T12:36:49.051521Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from sympy import symbols, exp, lambdify\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import time\n", + "from shenfun import *" + ] + }, + { + "cell_type": "markdown", + "id": "b9d76d97", + "metadata": { + "editable": true + }, + "source": [ + "The size of the problem (in real space) is then specified, before creating\n", + "the [TensorProductSpace](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.tensorproductspace.TensorProductSpace), which is using a tensor product of two\n", + "one-dimensional Fourier function spaces. We also\n", + "create a [VectorSpace](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.tensorproductspace.VectorSpace), since this is required for computing the\n", + "gradient of the scalar field `u`. The gradient is required for the nonlinear\n", + "term." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "063c35c2", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:49.056546Z", + "iopub.status.busy": "2024-05-24T12:36:49.056261Z", + "iopub.status.idle": "2024-05-24T12:36:49.629121Z", + "shell.execute_reply": "2024-05-24T12:36:49.624514Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "# Size of discretization\n", + "N = (128, 128)\n", + "\n", + "K0 = FunctionSpace(N[0], 'F', domain=(-30*np.pi, 30*np.pi), dtype='D')\n", + "K1 = FunctionSpace(N[1], 'F', domain=(-30*np.pi, 30*np.pi), dtype='d')\n", + "T = TensorProductSpace(comm, (K0, K1), **{'planner_effort': 'FFTW_MEASURE'})\n", + "TV = VectorSpace([T, T])\n", + "Tp = T.get_dealiased((1.5, 1.5))\n", + "TVp = VectorSpace(Tp)" + ] + }, + { + "cell_type": "markdown", + "id": "a3411ce3", + "metadata": { + "editable": true + }, + "source": [ + "Test and trialfunctions are required for assembling the variational forms:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3102955a", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:49.632923Z", + "iopub.status.busy": "2024-05-24T12:36:49.632713Z", + "iopub.status.idle": "2024-05-24T12:36:49.637407Z", + "shell.execute_reply": "2024-05-24T12:36:49.635009Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u = TrialFunction(T)\n", + "v = TestFunction(T)" + ] + }, + { + "cell_type": "markdown", + "id": "7ad972cb", + "metadata": { + "editable": true + }, + "source": [ + "and some arrays are required to hold the solution. We also create an array\n", + "`gradu`, that will be used to compute the gradient in the nonlinear term.\n", + "Finally, the wavenumbers are collected in an array `K`. Here one feature is worth\n", + "mentioning. The gradient in spectral space can be computed as `1j*K*U_hat`.\n", + "However, since this is an odd derivative, and we are using an even number `N`\n", + "for the size of the domain, the highest wavenumber must be set to zero. This is\n", + "the purpose of the last keyword argument to `local_wavenumbers` below." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b9035407", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:49.643702Z", + "iopub.status.busy": "2024-05-24T12:36:49.643494Z", + "iopub.status.idle": "2024-05-24T12:36:49.665807Z", + "shell.execute_reply": "2024-05-24T12:36:49.664650Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "x, y = symbols(\"x,y\", real=True)\n", + "ue = exp(-0.01*(x**2+y**2))\n", + "U = Array(T, buffer=ue)\n", + "U_hat = Function(T)\n", + "U_hat = U.forward(U_hat)\n", + "mask = T.get_mask_nyquist()\n", + "U_hat.mask_nyquist(mask)\n", + "gradu = Array(TVp)\n", + "K = np.array(T.local_wavenumbers(True, True, eliminate_highest_freq=True))\n", + "X = T.local_mesh(True)" + ] + }, + { + "cell_type": "markdown", + "id": "5681887e", + "metadata": { + "editable": true + }, + "source": [ + "Note that using this `K` in computing derivatives has the same effect as\n", + "achieved by symmetrizing the Fourier series by replacing the first sum below\n", + "with the second when computing odd derivatives." + ] + }, + { + "cell_type": "markdown", + "id": "573e1d22", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u = \\sum_{k=-N/2}^{N/2-1} \\hat{u}_k e^{\\imath k x}\n", + "\\label{_auto13} \\tag{19}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "434519b9", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "u = \\sideset{}{'}\\sum_{k=-N/2}^{N/2} \\hat{u}_k e^{\\imath k x}\n", + "\\label{_auto14} \\tag{20}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "06e92d12", + "metadata": { + "editable": true + }, + "source": [ + "Here $\\sideset{}{'}\\sum$ means that the first and last items in the sum are\n", + "divided by two. Note that the two sums are equal as they stand (due to aliasing), but only the\n", + "latter (known as the Fourier interpolant) gives the correct (zero) derivative of\n", + "the basis with the highest wavenumber.\n", + "\n", + "Shenfun has a few integrators implemented in the [shenfun.utilities.integrators](https://shenfun.readthedocs.io/en/latest/shenfun.utilities.html#module-shenfun.utilities.integrators)\n", + "submodule. Two such integrators are the 4th order explicit Runge-Kutta method\n", + "`RK4`, and the exponential 4th order Runge-Kutta method `ETDRK4`. Both these\n", + "integrators need two methods provided by the problem being solved, representing\n", + "the linear and nonlinear terms in the problem equation. We define two methods\n", + "below, called `LinearRHS` and `NonlinearRHS`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "80301cc6", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:49.669821Z", + "iopub.status.busy": "2024-05-24T12:36:49.669721Z", + "iopub.status.idle": "2024-05-24T12:36:49.673327Z", + "shell.execute_reply": "2024-05-24T12:36:49.672288Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "def LinearRHS(self, u,**params):\n", + " # Assemble diagonal bilinear forms\n", + " return -(div(grad(u))+div(grad(div(grad(u)))))\n", + "\n", + "def NonlinearRHS(self, U, U_hat, dU, gradu, **params):\n", + " # Assemble nonlinear term\n", + " gradu = TVp.backward(1j*K*U_hat, gradu)\n", + " dU = Tp.forward(0.5*(gradu[0]*gradu[0]+gradu[1]*gradu[1]), dU)\n", + " dU.mask_nyquist(mask)\n", + " dU *= -1\n", + " return dU" + ] + }, + { + "cell_type": "markdown", + "id": "762040be", + "metadata": { + "editable": true + }, + "source": [ + "The code should, hopefully, be self-explanatory.\n", + "\n", + "All that remains now is to setup the\n", + "integrator plus some plotting functionality for visualizing the results. Note\n", + "that visualization is only nice when running the code in serial. For parallel,\n", + "it is recommended to use [HDF5File](https://shenfun.readthedocs.io/en/latest/mpi4py_fft.io.html#mpi4py_fft.io.h5py_file.HDF5File), to store intermediate results to the HDF5\n", + "format, for later viewing in, e.g., Paraview.\n", + "\n", + "We create an update function for plotting intermediate results with a\n", + "cool colormap:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8f63facd", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:49.676464Z", + "iopub.status.busy": "2024-05-24T12:36:49.676184Z", + "iopub.status.idle": "2024-05-24T12:36:49.679948Z", + "shell.execute_reply": "2024-05-24T12:36:49.678987Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from IPython.display import display\n", + "\n", + "# Integrate using an exponential time integrator\n", + "def update(self, u, u_hat, t, tstep, **params):\n", + " if tstep % params['plot_step'] == 0 and params['plot_step'] > 0:\n", + " u = u_hat.backward(u)\n", + " self.image = plt.contourf(X[0], X[1], u, 256, cmap=plt.get_cmap('hot'))\n", + " self.image.axes.set_title(f'Energy {dx(u**2)}')\n", + " display(self.image, clear=True)\n", + " plt.pause(1e-6)" + ] + }, + { + "cell_type": "markdown", + "id": "2d717922", + "metadata": { + "editable": true + }, + "source": [ + "Now all that remains is to create the integrator and call it" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ab20ac9d", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:49.682688Z", + "iopub.status.busy": "2024-05-24T12:36:49.682515Z", + "iopub.status.idle": "2024-05-24T12:36:55.442780Z", + "shell.execute_reply": "2024-05-24T12:36:55.441648Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "par = {'plot_step': 100, 'gradu': gradu}\n", + "dt = 0.01\n", + "end_time = 10\n", + "integrator = ETDRK4(T, L=LinearRHS, N=NonlinearRHS, update=update, image=None, **par)\n", + "#integrator = RK4(T, L=LinearRHS, N=NonlinearRHS, update=update, **par)\n", + "integrator.setup(dt)\n", + "U_hat = integrator.solve(U, U_hat, dt, (0, end_time))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "shenfun", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/MixingBases/mixingbases.ipynb b/docs/demos/MixingBases/mixingbases.ipynb new file mode 100644 index 00000000..05590caa --- /dev/null +++ b/docs/demos/MixingBases/mixingbases.ipynb @@ -0,0 +1,652 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "d22ffe10", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - Mixed bases for the Helmholtz problem\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **March 22, 2021**\n", + "\n", + "**Summary.** This demo shows how to solve the Helmholtz equation using different\n", + "bases for test and trial spaces. The use of different bases leads for\n", + "some optimal combinations to highly sparse and well-conditioned\n", + "coefficient matrices." + ] + }, + { + "cell_type": "markdown", + "id": "e66d8420", + "metadata": { + "editable": true + }, + "source": [ + "## The Helmholtz problem\n", + "\n", + "We will consider Helmholtz equation with homogeneous Dirichlet boundary conditions" + ] + }, + { + "cell_type": "markdown", + "id": "fc92d314", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\alpha u - u^{''} = f \\quad \\text{in} \\, {I}=(-1, 1), \\quad u(\\pm 1) = 0,\n", + "\\label{_auto1} \\tag{1}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "df92a93f", + "metadata": { + "editable": true + }, + "source": [ + "where $\\alpha \\in \\mathbb{R^+}$. The relevant function space for the Dirichlet problem is" + ] + }, + { + "cell_type": "markdown", + "id": "c0ee2909", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " S_N=\\text{span}\\{T_k\\}_{k=0}^{N-1}, \\quad V_{N} = \\{v \\in {S}_N\\,|\\, v(\\pm 1) = 0\\},\n", + "\\label{_auto2} \\tag{2}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "cfb1e1a0", + "metadata": { + "editable": true + }, + "source": [ + "and the Chebyshev-Galerkin (CG) method is to find $u_N \\in V_N$ such that" + ] + }, + { + "cell_type": "markdown", + "id": "c0137bd8", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\label{eq:dirGalerkin} \\tag{3}\n", + " \\alpha (u_N, v)_{\\omega^{\\sigma}} -(u^{''}_N, v)_{\\omega^{\\sigma}} = (f, v)_{\\omega^{\\sigma}}, \\forall \\, v \\in V_N,\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "118ec8b5", + "metadata": { + "editable": true + }, + "source": [ + "where $(u,v)_{\\omega^{\\sigma}}=\\int_{{I}}uv\\omega^{\\sigma} dx$ is the scalar product in the weighted space $L^2_{\\omega^{\\sigma}}({I})$.\n", + "\n", + "Shenfun has implemented three different Chebyshev Dirichlet\n", + "basis functions" + ] + }, + { + "cell_type": "markdown", + "id": "8a6ae7d4", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\label{eq:shen} \\tag{4}\n", + "\\phi_k = T_k-T_{k+2}, \\quad k=0,1, \\ldots, N-3,\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "56b8b2b8", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\label{eq:heinrichs} \\tag{5}\n", + "\\varphi_k = (1-x^2)T_k, \\quad k=0,1, \\ldots, N-3,\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "4bb15362", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\label{eq:dirichletU} \\tag{6}\n", + "\\psi_k = U_k-\\frac{k+1}{k+3}U_{k+2}, \\quad k=0,1, \\ldots, N-3.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f0bf61eb", + "metadata": { + "editable": true + }, + "source": [ + "These three bases are all linearly dependent and they are all bases\n", + "for $V_N$." + ] + }, + { + "cell_type": "markdown", + "id": "0df870c4", + "metadata": { + "editable": true + }, + "source": [ + "## Implementation\n", + "\n", + "We can get all three function spaces as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f1f9ca5d", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:51.609457Z", + "iopub.status.busy": "2024-05-24T12:37:51.609305Z", + "iopub.status.idle": "2024-05-24T12:37:52.333091Z", + "shell.execute_reply": "2024-05-24T12:37:52.331537Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from shenfun import *\n", + "N = 40\n", + "V0 = FunctionSpace(N, 'C', basis='ShenDirichlet')\n", + "V1 = FunctionSpace(N, 'C', basis='Heinrichs')\n", + "V2 = FunctionSpace(N, 'U', basis='CompactDirichlet')" + ] + }, + { + "cell_type": "markdown", + "id": "e31306bc", + "metadata": { + "editable": true + }, + "source": [ + "where $V0 = \\text{span}\\{\\phi_k\\}_{k=0}^{N-3}$,\n", + "$V1 = \\text{span}\\{\\varphi_k\\}_{k=0}^{N-3}$ and\n", + "$V2 = \\text{span}\\{\\psi_k\\}_{k=0}^{N-3}$. Now, to solve the Helmholtz problem we simply need to choose\n", + "test and trial bases. Shen's original method is using\n", + "`V0` for both. To assemble the stiffness and mass matrices\n", + "for this choice do" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c0a4b817", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:52.340208Z", + "iopub.status.busy": "2024-05-24T12:37:52.339832Z", + "iopub.status.idle": "2024-05-24T12:37:52.345709Z", + "shell.execute_reply": "2024-05-24T12:37:52.344619Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u = TrialFunction(V0)\n", + "v = TestFunction(V0)\n", + "A = inner(v, div(grad(u)))\n", + "B = inner(v, u)" + ] + }, + { + "cell_type": "markdown", + "id": "ebc3bfe4", + "metadata": { + "editable": true + }, + "source": [ + "A manufactured solution can be chosen using [Sympy](https://www.sympy.org)\n", + "We choose" + ] + }, + { + "cell_type": "markdown", + "id": "116f1647", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(x) = \\sin \\left( 2 \\pi \\cos \\left( 2 \\pi x \\right) \\right)\n", + "\\label{_auto3} \\tag{7}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "3ac72ba9", + "metadata": { + "editable": true + }, + "source": [ + "implemented as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b621fdd7", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:52.350040Z", + "iopub.status.busy": "2024-05-24T12:37:52.349833Z", + "iopub.status.idle": "2024-05-24T12:37:52.356609Z", + "shell.execute_reply": "2024-05-24T12:37:52.356261Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "import sympy as sp\n", + "x = sp.Symbol('x', real=True)\n", + "ue = sp.sin(2*sp.pi*sp.cos(2*sp.pi*x))" + ] + }, + { + "cell_type": "markdown", + "id": "8ed01c45", + "metadata": { + "editable": true + }, + "source": [ + "The right hand side $f$ of Helmholtz equation is" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b7648fc4", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:52.358262Z", + "iopub.status.busy": "2024-05-24T12:37:52.358166Z", + "iopub.status.idle": "2024-05-24T12:37:52.748000Z", + "shell.execute_reply": "2024-05-24T12:37:52.747339Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "alpha = 1\n", + "f = sp.simplify(alpha*ue-ue.diff(x, 2))" + ] + }, + { + "cell_type": "markdown", + "id": "5c02f31e", + "metadata": { + "editable": true + }, + "source": [ + "To solve the problem we can do" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "341119de", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:52.754670Z", + "iopub.status.busy": "2024-05-24T12:37:52.754529Z", + "iopub.status.idle": "2024-05-24T12:37:52.780628Z", + "shell.execute_reply": "2024-05-24T12:37:52.777201Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "fj = Array(V0, buffer=f) # Get f on quadrature mesh\n", + "f_hat = inner(v, fj) # Compute right hand side\n", + "M = alpha*B - A # Get coefficient matrix\n", + "u_hat = Function(V0) # Container for the solution\n", + "sol = la.Solver(M) # Solver\n", + "u_hat = sol(f_hat, u_hat) # Solve" + ] + }, + { + "cell_type": "markdown", + "id": "ff687ebc", + "metadata": { + "editable": true + }, + "source": [ + "Compare with exact solution." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c29b3b52", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:52.791460Z", + "iopub.status.busy": "2024-05-24T12:37:52.791020Z", + "iopub.status.idle": "2024-05-24T12:37:52.852240Z", + "shell.execute_reply": "2024-05-24T12:37:52.849580Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "uj = Array(V0, buffer=ue)\n", + "error = inner(1, (u_hat.backward()-uj)**2)\n", + "print('Error =', error)" + ] + }, + { + "cell_type": "markdown", + "id": "d3104bb4", + "metadata": { + "editable": true + }, + "source": [ + "Now that was the solution for test and trial bases from the same\n", + "basis ([4](#eq:shen)). Let us create a function that takes any\n", + "test and any trial basis, any manufactured solution and any $\\alpha$\n", + "in the Helmholtz equation. We let the function return either\n", + "the L2-error norm, the condition number of the Helmholtz\n", + "coefficient matrix, or the matrix itself." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e7fc2aff", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:52.855887Z", + "iopub.status.busy": "2024-05-24T12:37:52.855234Z", + "iopub.status.idle": "2024-05-24T12:37:52.862642Z", + "shell.execute_reply": "2024-05-24T12:37:52.861860Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "def main(N, test, trial, alpha=1, method=0, ue=sp.sin(2*sp.pi*sp.cos(2*sp.pi*x))):\n", + " \"\"\"Solve Helmholtz problem and return L2-error, condition number or matrix\n", + "\n", + " Parameters\n", + " ----------\n", + " N : int\n", + " Number of quadrature points\n", + " test, trial : int\n", + " Test and trial functions.\n", + " 0 = :math:`T_k-T_{k+2}`\n", + " 1 = :math:`(1-x^2)T_k`\n", + " 2 = :math:`U_k-\\frac{k+1}{k+3}U_{k+2}`\n", + " alpha : Helmholtz parameter\n", + " method : int\n", + " 0 = Return L2-error norm\n", + " 1 = Return condition number of matrix\n", + " 2 = Return Helmholtz matrix\n", + " ue : Sympy function, optional\n", + " The manufactured solution with homogeneous boundary conditions.\n", + "\n", + " Note\n", + " ----\n", + " Inhomogeneous boundary conditions require a small rewrite, but is\n", + " not difficult.\n", + "\n", + " \"\"\"\n", + " bases = {0: ('C', 'ShenDirichlet'), 1: ('C', 'Heinrichs'), 2: ('U', 'CompactDirichlet')}\n", + " test = FunctionSpace(N, bases[test][0], basis=bases[test][1])\n", + " trial= FunctionSpace(N, bases[trial][0], basis=bases[trial][1])\n", + " # Check that boundary conditions are homogeneous\n", + " assert abs(ue.subs(x, -1)) < 1e-8 and abs(ue.subs(x, 1)) < 1e-8\n", + " u = TrialFunction(trial)\n", + " v = TestFunction(test)\n", + " f = sp.simplify(alpha*ue-ue.diff(x, 2))\n", + " fj = Array(test, buffer=f) # Get f on quadrature mesh\n", + " f_hat = inner(v, fj) # Compute right hand side\n", + " B = inner(v, u)\n", + " A = inner(v, div(grad(u)))\n", + " M = alpha*B-A\n", + " if method == 1:\n", + " return np.linalg.cond(M.diags('csr').toarray())\n", + " if method == 2:\n", + " return M\n", + "\n", + " u_hat = Function(trial)\n", + " sol = la.Solver(M)\n", + " u_hat = sol(f_hat, u_hat)\n", + " uj = Array(trial, buffer=ue)\n", + " error = np.sqrt(inner(1, (u_hat.backward()-uj)**2))\n", + " return error" + ] + }, + { + "cell_type": "markdown", + "id": "311641c8", + "metadata": { + "editable": true + }, + "source": [ + "Let us first try basis ([4](#eq:shen)) as test function and\n", + "([5](#eq:heinrichs)) as trial function. Use otherwise\n", + "default parameters." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6a61d76e", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:52.865623Z", + "iopub.status.busy": "2024-05-24T12:37:52.865527Z", + "iopub.status.idle": "2024-05-24T12:37:53.192373Z", + "shell.execute_reply": "2024-05-24T12:37:53.191860Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "error = main(100, 0, 1)\n", + "print(error)" + ] + }, + { + "cell_type": "markdown", + "id": "19538c44", + "metadata": { + "editable": true + }, + "source": [ + "So the error is small in deed. Perhaps more interesting, let's\n", + "look at the sparsity pattern of the coefficient matrix" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "21ff1456", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:53.197472Z", + "iopub.status.busy": "2024-05-24T12:37:53.197343Z", + "iopub.status.idle": "2024-05-24T12:37:53.909816Z", + "shell.execute_reply": "2024-05-24T12:37:53.908747Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "M = main(100, 0, 1, method=2)\n", + "import plotly.express as px\n", + "z = np.where(abs(M.diags().toarray()) > 1e-6, 0, 1).astype(bool)\n", + "fig = px.imshow(z, binary_string=True)\n", + "fig.show()\n", + "#plt.spy(M.diags(), markersize=0.2) # or use matplotlib" + ] + }, + { + "cell_type": "markdown", + "id": "07f47d49", + "metadata": { + "editable": true + }, + "source": [ + "The coefficient matrix has 4 non-zero diagonals. You can now experiment\n", + "with different test and trial functions, but you will not get a better\n", + "result than that. Try basis ([5](#eq:heinrichs)) for both test and trial\n", + "function, and you'll get 5 nonzero diagonals.\n", + "\n", + "To see the convergence rate call `main` for a range of\n", + "different mesh sizes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2e593550", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:53.922707Z", + "iopub.status.busy": "2024-05-24T12:37:53.922459Z", + "iopub.status.idle": "2024-05-24T12:37:55.101281Z", + "shell.execute_reply": "2024-05-24T12:37:55.099980Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "error = []\n", + "N = (2**4, 2**6, 2**8, 2**10)\n", + "for n in N:\n", + " error.append(main(n, 0, 1))\n", + "fig = px.line(x=N, y=error, log_y=True)\n", + "fig.update_layout(yaxis=dict(showexponent='all', exponentformat='e'))\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "id": "3e83de81", + "metadata": { + "editable": true + }, + "source": [ + "" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/Moebius/moebius.ipynb b/docs/demos/Moebius/moebius.ipynb new file mode 100644 index 00000000..e6487081 --- /dev/null +++ b/docs/demos/Moebius/moebius.ipynb @@ -0,0 +1,1051 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a36d0733", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - Eigenvalues on the Möbius strip\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **October 15, 2020**\n", + "\n", + "**Summary.** This is a demonstration of how the Python module [shenfun](https://github.com/spectralDNS/shenfun) can be used to\n", + "compute eigenvalues and vectors of the Laplace-Beltrami\n", + "operator on a Möbius strip. The absolute value of the eigenvector\n", + "corresponding to the eigth smallest eigenvalue $\\lambda=8.054788196$\n", + "is shown in the figure below, read on to see how it was computed.\n", + "\n", + "\n", + "\n", + "\n", + "

Figure 1

\n", + "" + ] + }, + { + "cell_type": "markdown", + "id": "e10f07d5", + "metadata": { + "editable": true + }, + "source": [ + "## The Möbius strip\n", + "\n", + "A Möbius strip is the simplest non-orientable surface embedded in\n", + "$\\mathbb{R}^3$. There are several realizations possible, and we\n", + "will here consider the one parametrized by [[Kalvoda2020]](#Kalvoda2020)" + ] + }, + { + "cell_type": "markdown", + "id": "aace7270", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " x(\\theta, t) = \\left(R-t\\cos\\frac{\\theta}{2R}\\right) \\cos \\frac{\\theta}{R}, \n", + "\\label{_auto1} \\tag{1}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1bc99e64", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " y(\\theta, t) = \\left(R-t\\cos\\frac{\\theta}{2R}\\right) \\sin \\frac{\\theta}{R}, \n", + "\\label{_auto2} \\tag{2}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "b12752a5", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " z(\\theta, t) = -t \\sin \\frac{\\theta}{2 R},\n", + "\\label{_auto3} \\tag{3}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "eeaf8367", + "metadata": { + "editable": true + }, + "source": [ + "where $R$ is the main radius of the strip. $\\theta$ is the parameter that determines\n", + "the angle for moving around the strip, like the angle of a circle.\n", + "For one trip around the strip move $\\theta$ from $\\theta_0$ to $\\theta_0+2\\pi R$.\n", + "A function in Cartesian coordinates $u(\\mathbf{x})$ for $\\mathbf{x} \\in \\mathbb{R}^3$\n", + "is mapped to computational coordinates as $u(\\mathbf{x}) = \\tilde{u}(\\theta, t)$.\n", + "By moving once around the strip a function can be seen to be twisted periodic,\n", + "such that" + ] + }, + { + "cell_type": "markdown", + "id": "24159786", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\tilde{u}(\\theta_0, t) = \\tilde{u}(\\theta_0 + 2\\pi R, -t), \n", + "\\label{_auto4} \\tag{4}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "3d69bbdd", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " \\frac{\\partial \\tilde{u}}{\\partial \\theta}(\\theta_0, t) = \\frac{\\partial \\tilde{u}}{\\partial \\theta}(\\theta_0 + 2\\pi R, -t).\n", + "\\label{_auto5} \\tag{5}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "cdaec92b", + "metadata": { + "editable": true + }, + "source": [ + "The twisted condition does not lend itself easily to a regular tensor\n", + "product basis. On the other hand, by moving twice around the strip,\n", + "regular periodic boundary conditions" + ] + }, + { + "cell_type": "markdown", + "id": "c17b95fe", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\tilde{u}(\\theta_0, t) = \\tilde{u}(\\theta_0 + 4\\pi R, t),\n", + "\\label{_auto6} \\tag{6}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "63e6eb39", + "metadata": { + "editable": true + }, + "source": [ + "will apply [[Kalvoda2020]](#Kalvoda2020), and we can discretize using Fourier\n", + "exponentials in the $\\theta$-direction. Since the reference domain of periodic Fourier\n", + "exponentials is $[-\\pi, \\pi)$ we define $\\varphi = \\theta /(2 R)$, such that\n", + "the computational domain is $(\\varphi, t) \\in \\mathbb{I}^2 = [-\\pi, \\pi) \\times (-1, 1)$,\n", + "with the parametrization" + ] + }, + { + "cell_type": "markdown", + "id": "851f9be7", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " x(\\varphi, t) = \\left(R-t\\cos {\\varphi}\\right) \\cos {2 \\varphi}, \n", + "\\label{_auto7} \\tag{7}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "60def052", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " y(\\varphi, t) = \\left(R-t\\cos {\\varphi}\\right) \\sin {2 \\varphi}, \n", + "\\label{_auto8} \\tag{8}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "ac99c073", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " z(\\varphi, t) = -t \\sin {\\varphi}.\n", + "\\label{_auto9} \\tag{9}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "86946617", + "metadata": { + "editable": true + }, + "source": [ + "Note that the reference domain corresponds to $(\\theta, t) \\in = [-2\\pi R, 2\\pi R) \\times (-1, 1)$.\n", + "It is also trivial to adjust the $t$-domain with an affine map for a more narrow or\n", + "wider strip, but this added complexity is not discussed here. One can simply\n", + "choose the width of the strip below when choosing function space for the\n", + "$t$-direction.\n", + "\n", + "For the $t$-direction, a mixed Legendre,\n", + "$\\psi_{i} = L_{i} - L_{i+2}$, or Chebyshev, $\\psi_{i} = T_{i} - T_{i+2}$,\n", + "basis can be used and we obtain a regular tensor product basis.\n", + "The Legendre basis leads to more sparse matrices, and will be chosen\n", + "as default, but Chebyshev also works just fine.\n", + "Note that the same problem is\n", + "solved by Kalvoda et al. [[Kalvoda2020]](#Kalvoda2020) using a tensor product\n", + "basis with Fourier exponentials for the $\\theta$-direction and a mix\n", + "of cosines and sines for the $t$-direction. Kalvoda et al. cannot\n", + "make use of tensor product matrices and integrates using a\n", + "two-dimensional quadrature scheme over the entire domain, leading\n", + "to a dense matrix. We will here only use 1D quadrature and\n", + "tensor products to get the coefficient matrix." + ] + }, + { + "cell_type": "markdown", + "id": "c77d91c1", + "metadata": { + "editable": true + }, + "source": [ + "## The Laplace Beltrami operator\n", + "\n", + "We consider the eigenvalue problem of the\n", + "Laplace Beltrami operator by solving" + ] + }, + { + "cell_type": "markdown", + "id": "85cf3c0c", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " -\\nabla^2 u(\\mathbf{x}) = \\lambda u(\\mathbf{x}), \\quad \\text{ for } \\mathbf{x} \\in \\Omega,\n", + "\\label{_auto10} \\tag{10}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "c079b32b", + "metadata": { + "editable": true + }, + "source": [ + "where $u$ is the solution, $\\lambda$ the eigenvalues and $\\Omega$ the Möbius\n", + "strip. We consider only homogeneous Dirichlet boundary conditions on the boundary.\n", + "\n", + "To solve this problem with the spectral Galerkin method we\n", + "choose an appropriate space $V$ and find $u\\in V$ such that" + ] + }, + { + "cell_type": "markdown", + "id": "2e00a064", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\int_{\\Omega} -\\nabla^2 u \\, v^* \\omega d\\sigma = \\int_{\\Omega} \\lambda u v^* \\omega d\\sigma, \\quad \\forall v \\in V\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "659c1475", + "metadata": { + "editable": true + }, + "source": [ + "where $v^*$ is the complex conjugate of the test function $v$.\n", + "\n", + "With shenfun it is enough to operate in general coordinates as above\n", + "and let the curvilinear mathematics all happen under the hood.\n", + "However, for this example it is interesting to see what the\n", + "Laplace-Beltrami operator looks like in computational coordinates.\n", + "This is quite a bit of work by hand, and the starting point\n", + "is the position vector" + ] + }, + { + "cell_type": "markdown", + "id": "a9152953", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\mathbf{r} = x(\\varphi, t) \\mathbf{i} + y(\\varphi, t) \\mathbf{j} + z(\\varphi, t) \\mathbf{k}.\n", + "\\label{_auto11} \\tag{11}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e19d947e", + "metadata": { + "editable": true + }, + "source": [ + "From the position vector we compute the he covariant\n", + "basis vectors $\\mathbf{b}_i = \\partial \\mathbf{r} / \\partial X^{i}$,\n", + "where $\\mathbf{X} = (X^{i})_{i\\in(1,2)} = (\\varphi, t)$,\n", + "and get the covariant metric tensor $g_{ij}=\\mathbf{b}_i \\cdot \\mathbf{b}_j$\n", + "and its determinant $g = \\text{det}(g_{ij})$. We get" + ] + }, + { + "cell_type": "markdown", + "id": "88f9eed6", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " {g} = (2R-2t\\cos \\varphi)^2+t^2.\n", + "\\label{_auto12} \\tag{12}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "d478e8e2", + "metadata": { + "editable": true + }, + "source": [ + "and" + ] + }, + { + "cell_type": "markdown", + "id": "0382744f", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "(g_{ij}) =\n", + "\\begin{pmatrix}\n", + " g & 0 \\\\ \n", + " 0 & 1\n", + "\\end{pmatrix}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1edbc444", + "metadata": { + "editable": true + }, + "source": [ + "Likewise, the contravariant metric tensor $g^{ij}$ is the\n", + "inverse of the covariant" + ] + }, + { + "cell_type": "markdown", + "id": "8e3ccac6", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "(g^{ij}) =\n", + "\\begin{pmatrix}\n", + " \\frac{1}{g} & 0 \\\\ \n", + " 0 & 1\n", + "\\end{pmatrix}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "a3d85733", + "metadata": { + "editable": true + }, + "source": [ + "Please note that all these metrics and other terms are computed\n", + "under the hood by shenfun, and a user does not normally have to worry\n", + "about these.\n", + "\n", + "It can be shown that the Laplace-Beltrami operator in curvilinear coordinates\n", + "is given as" + ] + }, + { + "cell_type": "markdown", + "id": "d2caccd3", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\nabla^2 \\tilde{u} = \\frac{1}{\\sqrt{g}}\\frac{\\partial}{\\partial X^{i}}\\left( g^{ij}\\sqrt{g} \\frac{\\partial \\tilde{u}}{\\partial X^{j}}\\right),\n", + "\\label{_auto13} \\tag{13}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "856b5034", + "metadata": { + "editable": true + }, + "source": [ + "with summation on repeated indices.\n", + "Using this and the surface element $d\\sigma=\\sqrt{g} d\\varphi dt$, the\n", + "variational form in computational coordinates becomes" + ] + }, + { + "cell_type": "markdown", + "id": "fbdc9605", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " -\\int_{\\mathbb{I}^2}\\frac{\\partial}{\\partial X^{i}}\\left( g^{ij}\\sqrt{g} \\frac{\\partial \\tilde{u}}{\\partial X^{j}}\\right) \\, \\tilde{v}^*\\, \\tilde{\\omega} d\\varphi dt = \\int_{\\mathbb{I}^2} \\lambda \\tilde{u} \\tilde{v}^*\\, \\tilde{\\omega}\\sqrt{g} d\\varphi dt,\n", + "\\label{_auto14} \\tag{14}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "346133c3", + "metadata": { + "editable": true + }, + "source": [ + "Summing and expanding some derivatives, we get" + ] + }, + { + "cell_type": "markdown", + "id": "2fa380d8", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{align*}\n", + " -\\int_{\\mathbb{I}^2} \\Big\\{ \\frac{1}{\\sqrt{g}}\\frac{\\partial^2 \\tilde{u}}{\\partial \\varphi^2 } &+\\frac{4 t \\sin \\varphi \\left(t \\cos {\\varphi} -R \\right) }{g^{\\frac{3}{2}}}\\frac{\\partial \\tilde{u}}{\\partial \\varphi } \\notag \\\\ \n", + " & +\\sqrt{g}\\frac{\\partial^2 \\tilde{u}}{\\partial t^2 }\n", + " +\\frac{4 \\cos {\\varphi} (t \\cos \\varphi -R) + t}{ \\sqrt{g}}\\frac{\\partial \\tilde{u}}{\\partial t } \\Big\\} \\tilde{v}^* \\tilde{\\omega} d\\varphi dt \\notag \\\\ \n", + " &= \\int_{\\mathbb{I}^2} \\lambda \\tilde{u} \\tilde{v}^* \\tilde{\\omega} \\sqrt{g} d\\varphi dt,\n", + "\\end{align*}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "8eb40114", + "metadata": { + "editable": true + }, + "source": [ + "Note that the variational problem contains unseparable variable coefficients,\n", + "like $1/\\sqrt{g}$ and $\\sqrt{g}$ and as such cannot\n", + "easily be solved using efficient tensor product algebra.\n", + "However, note that both $g$ and $g^2$ are separable (i.e., they can\n", + "be written as products of simpler functions separated by the arguments\n", + "$g(\\varphi, t) = \\sum_k g_1^k(\\varphi)g_2^k(t)$),\n", + "and using the unconventional weight $\\tilde{\\omega} = g^{3/2}$ we get" + ] + }, + { + "cell_type": "markdown", + "id": "c2f7c6b4", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{align*}\n", + " -\\int_{\\mathbb{I}^2} \\Big\\{ g \\frac{\\partial^2 \\tilde{u}}{\\partial \\varphi^2 } &+ {4 t \\sin \\varphi \\left(t \\cos {\\varphi} -R \\right) } \\frac{\\partial \\tilde{u}}{\\partial \\varphi } \\notag \\\\ \n", + " & + g^2 \\frac{\\partial^2 \\tilde{u}}{\\partial t^2 }\n", + " +g \\left({4 \\cos {\\varphi} (t \\cos \\varphi -R) + t} \\right) \\frac{\\partial \\tilde{u}}{\\partial t } \\Big\\} \\tilde{v}^* d\\varphi dt \\notag \\\\ \n", + " &= \\int_{\\mathbb{I}^2} \\lambda g^{2} \\tilde{u} \\tilde{v}^* d\\varphi dt,\n", + "\\end{align*}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1c9b6780", + "metadata": { + "editable": true + }, + "source": [ + "where the left hand side can be assembled using tensor product matrices,\n", + "where no single 1D matrix has more than 9 diagonals.\n", + "\n", + "Fortunately we do not have to do all this by hand since we have a\n", + "software that automatically assembles such matrices for us.\n", + "Now let's see how this problem can be handled with shenfun." + ] + }, + { + "cell_type": "markdown", + "id": "13451900", + "metadata": { + "editable": true + }, + "source": [ + "## Implementation\n", + "\n", + "First we need to create function spaces for each direction $\\varphi$\n", + "and $t$, and then a tensor product space from the two. We use the\n", + "parametrization given above and shenfun will then automatically\n", + "differentiate to create basis functions and metrics, like $g$.\n", + "One important factor, though. Sympy's [simplify](https://docs.sympy.org/latest/modules/simplify/simplify.html)\n", + "will sometimes have problems finding the best possible simplification\n", + "of a term, like $g$. And in this particular case we need\n", + "to discourage the use of powers, or else sympy will end up with a\n", + "much more complicated $g$ than we get below." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e3a23ab5", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:37.171159Z", + "iopub.status.busy": "2024-05-24T12:37:37.171038Z", + "iopub.status.idle": "2024-05-24T12:37:39.065982Z", + "shell.execute_reply": "2024-05-24T12:37:39.065026Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from shenfun import *\n", + "import sympy as sp\n", + "from IPython.display import Math, Latex, display\n", + "from scipy.sparse.linalg import eigs\n", + "config['basisvectors'] = 'covariant'\n", + "\n", + "phi, t = psi = sp.symbols('x,y', real=True)\n", + "\n", + "RR = sp.Rational(132, 20)/sp.pi # Same as Kalvoda et al\n", + "#RR = 2\n", + "# Use a symbolic R first, then later substitute for the value in RR\n", + "R = sp.Symbol('R', real=True, positive=True)\n", + "rv = ((R-t*sp.cos(phi))*sp.cos(2*phi),\n", + " (R-t*sp.cos(phi))*sp.sin(2*phi),\n", + " -t*sp.sin(phi))\n", + "\n", + "def discourage_powers(expr):\n", + " POW = sp.Symbol('POW')\n", + " count = sp.count_ops(expr, visual=True)\n", + " count = count.replace(POW, 100)\n", + " count = count.replace(sp.Symbol, type(sp.S.One))\n", + " return count\n", + "\n", + "N = (80, 40)\n", + "B0 = FunctionSpace(N[0], 'F', domain=(-np.pi, np.pi), dtype='D')\n", + "B1 = FunctionSpace(N[1], 'L', bc=(0, 0), domain=(-0.75, 0.75)) # Use same domain as Kalvoda et al\n", + "T = TensorProductSpace(comm, (B0, B1), coordinates=(psi, rv, True, (), discourage_powers), axes=(1, 0))\n", + "\n", + "u = TrialFunction(T)\n", + "v = TestFunction(T)" + ] + }, + { + "cell_type": "markdown", + "id": "0aeb1ce8", + "metadata": { + "editable": true + }, + "source": [ + "Note the `discourage_powers` function. Try to turn it off (if\n", + "you are watching this in an interactive setting) and see what happens\n", + "to, e.g., `T.coors.sg`, which is $\\sqrt{g}$.\n", + "\n", + "We can now check to see what the Laplace-Beltrami operator\n", + "looks like when computed with shenfun:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "64eca61f", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:39.070341Z", + "iopub.status.busy": "2024-05-24T12:37:39.070123Z", + "iopub.status.idle": "2024-05-24T12:37:40.239472Z", + "shell.execute_reply": "2024-05-24T12:37:40.238667Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "g = sp.Function('g')(phi, t)\n", + "replace = [(T.coors.sg**2, g)]\n", + "Math((div(grad(u))).tolatex(funcname='f', symbol_names={phi:'\\\\varphi', t:'t'}, replace=replace))" + ] + }, + { + "cell_type": "markdown", + "id": "c452170c", + "metadata": { + "editable": true + }, + "source": [ + "Not surprisingly, this is the same (except not multiplied by $\\sqrt{g}$) as what\n", + "is seen in the variational form above.\n", + "\n", + "At this point we replace the symbol R with a number in order to\n", + "assemble floating point matrices. The number R can be changed\n", + "above as the variable `RR`. For now it is set to use a value used also\n", + "by Kalvoda et al., such that we can doublecheck our eigenvalues.\n", + "We multiply forms with\n", + "$g^{3/2}$ before assembling to get separable variational forms,\n", + "leading to sparse tensor product matrices." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5568ddd3", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:40.243819Z", + "iopub.status.busy": "2024-05-24T12:37:40.243126Z", + "iopub.status.idle": "2024-05-24T12:37:45.447890Z", + "shell.execute_reply": "2024-05-24T12:37:45.447177Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "T.coors.subs(R, RR)\n", + "M = inner(v*T.coors.sg**3, -div(grad(u)))\n", + "B = inner(v*T.coors.sg**3, u)" + ] + }, + { + "cell_type": "markdown", + "id": "5d2d4f1d", + "metadata": { + "editable": true + }, + "source": [ + "Here `M` and `B` are lists of instances of the tensor product\n", + "matrix class [TPMatrix](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.matrixbase.TPMatrix)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "012ce144", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:45.451324Z", + "iopub.status.busy": "2024-05-24T12:37:45.451107Z", + "iopub.status.idle": "2024-05-24T12:37:45.457623Z", + "shell.execute_reply": "2024-05-24T12:37:45.456845Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "print(f'Number of matrices for M = {len(M)} and B = {len(B)}')" + ] + }, + { + "cell_type": "markdown", + "id": "b9a0e776", + "metadata": { + "editable": true + }, + "source": [ + "So quite a few matrices, but they are all sparse. We solve by\n", + "using a Kronecker product solver [Solver2D](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.la.Solver2D) that flattens the\n", + "tensor product matrices and solution vector C-style." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c49c9da3", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:45.461979Z", + "iopub.status.busy": "2024-05-24T12:37:45.461853Z", + "iopub.status.idle": "2024-05-24T12:37:45.509512Z", + "shell.execute_reply": "2024-05-24T12:37:45.508584Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "mm = la.Solver2D(M)\n", + "bb = la.Solver2D(B)\n", + "Mc = mm.mat.copy()\n", + "Bc = bb.mat.copy()" + ] + }, + { + "cell_type": "markdown", + "id": "14c43ce3", + "metadata": { + "editable": true + }, + "source": [ + "Finally, solve the eigenvalue problem using a sparse eigenvalue solver\n", + "from scipy, which is wrapping ARPACK. Note that ARPACK is better at\n", + "finding large than small eigenvalues and for this reason we use a shift-inverted\n", + "version, see [https://docs.scipy.org/doc/scipy/reference/tutorial/arpack.html](https://docs.scipy.org/doc/scipy/reference/tutorial/arpack.html)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "414ed1ba", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:45.514216Z", + "iopub.status.busy": "2024-05-24T12:37:45.513770Z", + "iopub.status.idle": "2024-05-24T12:37:45.913357Z", + "shell.execute_reply": "2024-05-24T12:37:45.912704Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "f = eigs(Mc, k=40, M=Bc, which='LM', sigma=0)" + ] + }, + { + "cell_type": "markdown", + "id": "6e97a182", + "metadata": { + "editable": true + }, + "source": [ + "We have now found all eigenvalues on the Möbius strip with two rotations. So\n", + "some of the eigenvalues/eigenvectors will not have the correct twisted\n", + "periodic boundary conditions. To get only the correct eigenvalues, we filter a little\n", + "bit, checking the boundary:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a3bde988", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:45.919641Z", + "iopub.status.busy": "2024-05-24T12:37:45.919203Z", + "iopub.status.idle": "2024-05-24T12:37:46.026567Z", + "shell.execute_reply": "2024-05-24T12:37:46.025606Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u_hat = Function(T)\n", + "eigvals = []\n", + "for i in range(f[1].shape[1]):\n", + " u_hat[:, :-2] = np.reshape(f[1][:, i], T.dims())\n", + " tt = u_hat.eval(np.array([[-np.pi, 0, -np.pi, 0], [0.5, -0.5, 0.65, -0.65]]))\n", + " dt = Dx(u_hat, 0, 1).eval(np.array([[-np.pi, 0, -np.pi, 0], [0.5, -0.5, 0.65, -0.65]]))\n", + " # Check for twisted periodic\n", + " if abs(tt[0]-tt[1]+tt[2]-tt[3]) < 1e-7 and abs(dt[0]-dt[1]+dt[2]-dt[3]) < 1e-8:\n", + " eigvals.append((i, f[0][i].real))\n", + " print(f'Twisted eigenvalue {len(eigvals):2d} {i:2d} {f[0][i].real:2.12e} Error {np.linalg.norm(Mc*f[1][:, i] - f[0][i]*Bc*f[1][:, i]):2.4e}')" + ] + }, + { + "cell_type": "markdown", + "id": "ba3f01ab", + "metadata": { + "editable": true + }, + "source": [ + "These are the lowest true eigenvalues of the Möbius strip.\n", + "We note that they are very similar to Table 2 in [[Kalvoda2020]](#Kalvoda2020). We can now\n", + "plot the eigenvectors using, e.g., mayavi or plotly.\n", + "Choose the eigenvalue number first and then the rest follows" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ab3e23af", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:46.029624Z", + "iopub.status.busy": "2024-05-24T12:37:46.029438Z", + "iopub.status.idle": "2024-05-24T12:37:48.270078Z", + "shell.execute_reply": "2024-05-24T12:37:48.269173Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "l = 7\n", + "u_hat[:, :-2] = np.reshape(f[1][:, eigvals[l][0]], T.dims())\n", + "u_hat2 = u_hat.refine([2*N[0], 2*N[1]])\n", + "N0 = u_hat2.function_space().shape(False)[0]//2+1\n", + "fig = surf3D(u_hat2, slices=(slice(0, N0), slice(None)))\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "id": "f5d256cd", + "metadata": { + "editable": true + }, + "source": [ + "Or make subplot of several of the eigenvectors:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d8db1163", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:48.286444Z", + "iopub.status.busy": "2024-05-24T12:37:48.286228Z", + "iopub.status.idle": "2024-05-24T12:37:48.449232Z", + "shell.execute_reply": "2024-05-24T12:37:48.448749Z" + } + }, + "outputs": [], + "source": [ + "import plotly\n", + "from plotly.subplots import make_subplots\n", + "import plotly.graph_objects as go\n", + "rows = 3\n", + "cols = 2\n", + "fig = make_subplots(rows=rows, cols=cols, start_cell=\"top-left\", specs=[[dict(type='surface')]*cols]*rows,\n", + " subplot_titles=(f'$\\\\lambda_1={eigvals[0][1]:2.5f}$', f'$\\\\lambda_3={eigvals[2][1]:2.5f}$',\n", + " f'$\\\\lambda_5={eigvals[4][1]:2.5f}$', f'$\\\\lambda_7={eigvals[6][1]:2.5f}$',\n", + " f'$\\\\lambda_9={eigvals[8][1]:2.5f}$', f'$\\\\lambda_{{11}}={eigvals[10][1]:2.5f}$'))\n", + "N0 = T.shape(False)[0]//2+1 # Remember, data is for two rounds around the strip, we need only 1\n", + "x, y, z = T.local_cartesian_mesh()\n", + "x, y, z = x[:N0], y[:N0], z[:N0]\n", + "d = {'visible': False, 'showgrid': False, 'zeroline': False}\n", + "for l in range(rows*cols):\n", + " u_hat[:, :-2] = np.reshape(f[1][:, eigvals[2*l][0]], T.dims())\n", + " s = go.Surface(x=x, y=y, z=z, surfacecolor=abs(u_hat.backward()[:N0]),\n", + " colorscale=plotly.colors.sequential.Jet,\n", + " showscale=False)\n", + " fig.add_trace(s, row=l//cols+1, col=l%cols+1)\n", + " scene = 'scene' if l == 0 else f'scene{l+1}'\n", + " fig.update_layout({scene: {'xaxis': d, 'yaxis': d, 'zaxis': d, 'camera': {'eye': dict(x=0.85, y=0.85, z=0.85)}}})\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "id": "5ebf31d6", + "metadata": { + "editable": true + }, + "source": [ + "Finally, plot the sparsity pattern of the coefficient matrix. You\n", + "need to zoom in order to see the pattern properly and for\n", + "this reason we use plotly instead of the more convenient\n", + "matplotlib [spy](https://matplotlib.org/3.3.1/api/_as_gen/matplotlib.pyplot.spy.html)\n", + "function (`%matplotlib notebook` does not work in an\n", + "interactive jupyterlab and as such a jupyter book session).\n", + "If you are curious, then please change basis to Chebyshev and\n", + "note the difference from Legendre. Otherwise, results should be very\n", + "much alike." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b6e92933", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:48.475989Z", + "iopub.status.busy": "2024-05-24T12:37:48.475786Z", + "iopub.status.idle": "2024-05-24T12:37:49.046941Z", + "shell.execute_reply": "2024-05-24T12:37:49.045911Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "import plotly.express as px\n", + "z = np.where(abs(mm.mat.toarray()) > 1e-6, 0, 1).astype(bool)\n", + "fig = px.imshow(z, binary_string=True)\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "id": "880a1632", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "1. **T. Kalvoda, D. Krejcirik and K. Zahradová**. Effective Quantum Dynamics on the Möbius Strip, *Journal of Physics A: Mathematical and Theoretical*, 53(37), pp. 375201, [doi: 10.1088/1751-8121/ab8b3a](https://dx.doi.org/10.1088/1751-8121/ab8b3a), 2020." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/Poisson/poisson.ipynb b/docs/demos/Poisson/poisson.ipynb new file mode 100644 index 00000000..23912169 --- /dev/null +++ b/docs/demos/Poisson/poisson.ipynb @@ -0,0 +1,961 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "191f070c", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - 1D Poisson's equation\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **April 13, 2018**\n", + "\n", + "**Summary.** This is a demonstration of how the Python module [shenfun](https://github.com/spectralDNS/shenfun) can be used to solve Poisson's\n", + "equation with Dirichlet boundary conditions in one dimension. Spectral convergence, as\n", + "shown in the figure below, is demonstrated.\n", + "The demo is implemented in slightly more generic terms (more boundary conditions)\n", + "in [poisson1D.py](https://github.com/spectralDNS/shenfun/blob/master/demo/poisson1D.py), and\n", + "the numerical method is is described in more detail by J. Shen [[shen1]](#shen1) and [[shen95]](#shen95).\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "

Figure 1: Convergence of 1D Poisson solvers for both Legendre and Chebyshev modified basis function.

\n", + "" + ] + }, + { + "cell_type": "markdown", + "id": "5c9e928b", + "metadata": { + "editable": true + }, + "source": [ + "## Poisson's equation\n", + "\n", + "Poisson's equation is given as" + ] + }, + { + "cell_type": "markdown", + "id": "88a950ff", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\nabla^2 u(x) = f(x) \\quad \\text{for }\\, x \\in (-1, 1), \\label{eq:poisson} \\tag{1}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "04929b21", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "u(-1)=a, u(1)=b, \\notag\n", + "\\label{_auto1} \\tag{2}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "6dff101a", + "metadata": { + "editable": true + }, + "source": [ + "where $u(x)$ is the solution, $f(x)$ is a function and $a, b$ are two possibly\n", + "non-zero constants.\n", + "\n", + "To solve Eq. ([1](#eq:poisson)) with the Galerkin method we need smooth continuously\n", + "differentiable basis functions, $v_k$, that satisfy the given boundary conditions.\n", + "And then we look for solutions like" + ] + }, + { + "cell_type": "markdown", + "id": "40cbe4bb", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(x) = \\sum_{k=0}^{N-1} \\hat{u}_k v_k(x), \\label{eq:u} \\tag{3}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "75b794d4", + "metadata": { + "editable": true + }, + "source": [ + "where $N$ is the size of the discretized problem,\n", + "$\\{\\hat{u}_k\\}_{k=0}^{N-1}$ are the unknown expansion\n", + "coefficients, and the function space is $\\text{span}\\{v_k\\}_{k=0}^{N-1}$.\n", + "\n", + "The basis functions of the function space can, for example, be constructed from\n", + "[Chebyshev](https://en.wikipedia.org/wiki/Chebyshev_polynomials), $T_k(x)$, or\n", + "[Legendre](https://en.wikipedia.org/wiki/Legendre_polynomials), $L_k(x)$, polynomials\n", + "and we use the common notation $\\phi_k(x)$ to represent either one of them. It turns out that\n", + "it is easiest to use basis functions with homogeneous Dirichlet boundary conditions" + ] + }, + { + "cell_type": "markdown", + "id": "daad7929", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "v_k(x) = \\phi_k(x) - \\phi_{k+2}(x),\n", + "\\label{_auto2} \\tag{4}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "49939654", + "metadata": { + "editable": true + }, + "source": [ + "for $k=0, 1, \\ldots N-3$. This gives the function space\n", + "$V^N_0 = \\text{span}\\{v_k(x)\\}_{k=0}^{N-3}$.\n", + "We can then add two more linear basis functions (that belong to the kernel of Poisson's equation)" + ] + }, + { + "cell_type": "markdown", + "id": "c2eb52a2", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "v_{N-2} = \\frac{1}{2}(\\phi_0 - \\phi_1), \n", + "\\label{_auto3} \\tag{5}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "19b3c0c6", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "v_{N-1} = \\frac{1}{2}(\\phi_0 + \\phi_1).\n", + "\\label{_auto4} \\tag{6}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f9753564", + "metadata": { + "editable": true + }, + "source": [ + "which gives the inhomogeneous space $V^N = \\text{span}\\{v_k\\}_{k=0}^{N-1}$.\n", + "With the two linear basis functions it is easy to see that the last two degrees\n", + "of freedom, $\\hat{u}_{N-2}$ and $\\hat{u}_{N-1}$, now are given as" + ] + }, + { + "cell_type": "markdown", + "id": "7ee320eb", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(-1) = \\sum_{k=0}^{N-1} \\hat{u}_k v_k(-1) = \\hat{u}_{N-2} = a,\n", + "\\label{eq:dirichleta} \\tag{7} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "5bfbba11", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "u(+1) = \\sum_{k=0}^{N-1} \\hat{u}_k v_k(+1) = \\hat{u}_{N-1} = b,\n", + "\\label{eq:dirichletb} \\tag{8}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "a377dc2d", + "metadata": { + "editable": true + }, + "source": [ + "and, as such, we only have to solve for $\\{\\hat{u}_k\\}_{k=0}^{N-3}$, just like\n", + "for a problem with homogeneous boundary conditions (for homogeneous boundary condition\n", + "we simply have $\\hat{u}_{N-2} = \\hat{u}_{N-1} = 0$).\n", + "We now formulate a variational problem using the Galerkin method: Find $u \\in V^N$ such that" + ] + }, + { + "cell_type": "markdown", + "id": "bc16986e", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\int_{-1}^1 \\nabla^2 u \\, v \\, w\\, dx = \\int_{-1}^1 f \\, v\\, w\\, dx \\quad \\forall v \\, \\in \\, V^N_0. \\label{eq:varform} \\tag{9}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "c56593b5", + "metadata": { + "editable": true + }, + "source": [ + "Note that since we only have $N-3$ unknowns we are only using the homogeneous test\n", + "functions from $V^N_0$.\n", + "\n", + "The weighted integrals, weighted by $w(x)$, are called inner products, and a\n", + "common notation is" + ] + }, + { + "cell_type": "markdown", + "id": "e7f282db", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\int_{-1}^1 u \\, v \\, w\\, dx = \\left( u, v\\right)_w.\n", + "\\label{_auto5} \\tag{10}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "2aae170f", + "metadata": { + "editable": true + }, + "source": [ + "The integral can either be computed exactly, or with quadrature. The advantage\n", + "of the latter is that it is generally faster, and that non-linear terms may be\n", + "computed just as quickly as linear. For a linear problem, it does not make much\n", + "of a difference, if any at all. Approximating the integral with quadrature, we\n", + "obtain" + ] + }, + { + "cell_type": "markdown", + "id": "0597485b", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{align*}\n", + "\\int_{-1}^1 u \\, v \\, w\\, dx &\\approx \\left( u, v \\right)_w^N, \\\\ \n", + "&\\approx \\sum_{j=0}^{N-1} u(x_j) v(x_j) w(x_j),\n", + "\\end{align*}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1820492f", + "metadata": { + "editable": true + }, + "source": [ + "where $\\{w(x_j)\\}_{j=0}^{N-1}$ are quadrature weights.\n", + "The quadrature points $\\{x_j\\}_{j=0}^{N-1}$\n", + "are specific to the chosen basis, and even within basis there are two different\n", + "choices based on which quadrature rule is selected, either Gauss or Gauss-Lobatto.\n", + "\n", + "Inserting for test and trialfunctions, we get the following bilinear form and\n", + "matrix $A=(a_{jk})\\in\\mathbb{R}^{N-2\\times N-2}$ for the Laplacian" + ] + }, + { + "cell_type": "markdown", + "id": "0f03aa15", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{align*}\n", + "\\left( \\nabla^2u, v \\right)_w^N &= \\left( \\nabla^2\\sum_{k=0}^{N-3}\\hat{u}_k v_{k}, v_j \\right)_w^N, \\quad j=0,1,\\ldots, N-3\\\\ \n", + " &= \\sum_{k=0}^{N-3}\\left(\\nabla^2 v_{k}, v_j \\right)_w^N \\hat{u}_k, \\\\ \n", + " &= \\sum_{k=0}^{N-3}a_{jk} \\hat{u}_k.\n", + "\\end{align*}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "08f3c800", + "metadata": { + "editable": true + }, + "source": [ + "Note that the sum runs over $k=0, 1, \\ldots, N-3$ since\n", + "the second derivatives of $v_{N-2}$ and $v_{N-1}$ are zero.\n", + "The right hand side linear form and vector is computed as $\\tilde{f}_j = (f,\n", + "v_j)_w^N$, for $j=0,1,\\ldots, N-3$, where a tilde is used because this is not\n", + "a complete transform of the function $f$, but only an inner product.\n", + "\n", + "By defining the column vectors $\\boldsymbol{\\hat{u}}=(\\hat{u}_0, \\hat{u}_1, \\ldots, \\hat{u}_{N-3})^T$\n", + "and $\\boldsymbol{\\tilde{f}}=(\\tilde{f}_0, \\tilde{f}_1, \\ldots, \\tilde{f}_{N-3})^T$\n", + "we get the linear system of equations" + ] + }, + { + "cell_type": "markdown", + "id": "65e0bcc0", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "A \\hat{\\boldsymbol{u}} = \\tilde{\\boldsymbol{f}}.\n", + "\\label{_auto6} \\tag{11}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "998ba60a", + "metadata": { + "editable": true + }, + "source": [ + "Now, when the expansion coefficients $\\boldsymbol{\\hat{u}}$ are found by\n", + "solving this linear system, they may be\n", + "transformed to real space $u(x)$ using ([3](#eq:u)), and here the contributions\n", + "from $\\hat{u}_{N-2}$ and $\\hat{u}_{N-1}$ must be accounted for. Note that the matrix\n", + "$A$ (different for Legendre or Chebyshev) has a very special structure that\n", + "allows for a solution to be found very efficiently in order of $\\mathcal{O}(N)$\n", + "operations, see [[shen1]](#shen1) and [[shen95]](#shen95). These solvers are implemented in\n", + "shenfun for both bases." + ] + }, + { + "cell_type": "markdown", + "id": "81e844aa", + "metadata": { + "editable": true + }, + "source": [ + "## Method of manufactured solutions\n", + "\n", + "In this demo we will use the method of manufactured\n", + "solutions to demonstrate spectral accuracy of the `shenfun` Dirichlet bases. To\n", + "this end we choose an analytical function that satisfies the given boundary\n", + "conditions:" + ] + }, + { + "cell_type": "markdown", + "id": "a7b27de2", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u_e(x) = \\sin(k\\pi x)(1-x^2) + a(1-x)/2 + b(1+x)/2, \\label{eq:u_e} \\tag{12}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "14a5e799", + "metadata": { + "editable": true + }, + "source": [ + "where $k$ is an integer and $a$ and $b$ are constants. Now, feeding $u_e$ through\n", + "the Laplace operator, we see that the last two linear terms disappear, whereas the\n", + "first term results in" + ] + }, + { + "cell_type": "markdown", + "id": "d45e3287", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\nabla^2 u_e(x) = \\frac{d^2 u_e}{dx^2}, \n", + "\\label{_auto7} \\tag{13}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "d0f28dd7", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " = -4k \\pi x \\cos(k\\pi x) - 2\\sin(k\\pi x) - k^2 \\pi^2 (1 -\n", + "x^2) \\sin(k \\pi x). \\label{eq:solution} \\tag{14}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "91f8eb49", + "metadata": { + "editable": true + }, + "source": [ + "Now, setting $f_e(x) = \\nabla^2 u_e(x)$ and solving for $\\nabla^2 u(x) = f_e(x)$,\n", + "we can compare the numerical solution $u(x)$ with the analytical solution $u_e(x)$\n", + "and compute error norms." + ] + }, + { + "cell_type": "markdown", + "id": "fc08f897", + "metadata": { + "editable": true + }, + "source": [ + "## Implementation" + ] + }, + { + "cell_type": "markdown", + "id": "dc126f5a", + "metadata": { + "editable": true + }, + "source": [ + "### Preamble\n", + "\n", + "We will solve Poisson's equation using the [shenfun](https://github.com/spectralDNS/shenfun) Python module. The first thing needed\n", + "is then to import some of this module's functionality\n", + "plus some other helper modules, like [Numpy](https://numpy.org) and [Sympy](https://sympy.org):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "659b5c0d", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:22.136214Z", + "iopub.status.busy": "2024-05-24T12:36:22.135738Z", + "iopub.status.idle": "2024-05-24T12:36:22.727867Z", + "shell.execute_reply": "2024-05-24T12:36:22.726320Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from shenfun import inner, div, grad, TestFunction, TrialFunction, Function, \\\n", + " project, Dx, Array, FunctionSpace, dx\n", + "import numpy as np\n", + "from sympy import symbols, cos, sin, exp, lambdify" + ] + }, + { + "cell_type": "markdown", + "id": "cfc9c744", + "metadata": { + "editable": true + }, + "source": [ + "We use `Sympy` for the manufactured solution and `Numpy` for testing." + ] + }, + { + "cell_type": "markdown", + "id": "40d4aa04", + "metadata": { + "editable": true + }, + "source": [ + "### Manufactured solution\n", + "\n", + "The exact solution $u_e(x)$ and the right hand side $f_e(x)$ are created using\n", + "`Sympy` as follows" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "38c3edf0", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:22.732881Z", + "iopub.status.busy": "2024-05-24T12:36:22.732459Z", + "iopub.status.idle": "2024-05-24T12:36:22.760490Z", + "shell.execute_reply": "2024-05-24T12:36:22.759813Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "a = -1\n", + "b = 1\n", + "k = 4\n", + "x = symbols(\"x\")\n", + "ue = sin(k*np.pi*x)*(1-x**2) + a*(1 - x)/2. + b*(1 + x)/2.\n", + "fe = ue.diff(x, 2)" + ] + }, + { + "cell_type": "markdown", + "id": "a66d4067", + "metadata": { + "editable": true + }, + "source": [ + "These solutions are now valid for a continuous domain. The next step is thus to\n", + "discretize, using a discrete mesh $\\{x_j\\}_{j=0}^{N-1}$ and a finite number of\n", + "basis functions.\n", + "\n", + "Note that it is not mandatory to use `Sympy` for the manufactured solution. Since the\n", + "solution is known ([14](#eq:solution)), we could just as well simply use `Numpy`\n", + "to compute $f_e$ at $\\{x_j\\}_{j=0}^{N-1}$. However, with `Sympy` it is much\n", + "easier to experiment and quickly change the solution." + ] + }, + { + "cell_type": "markdown", + "id": "e2cfe44f", + "metadata": { + "editable": true + }, + "source": [ + "### Discretization\n", + "\n", + "We create a basis with a given number of basis functions, and extract the computational\n", + "mesh from the basis itself" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9328ec31", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:22.764302Z", + "iopub.status.busy": "2024-05-24T12:36:22.764200Z", + "iopub.status.idle": "2024-05-24T12:36:22.776711Z", + "shell.execute_reply": "2024-05-24T12:36:22.776055Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "N = 32\n", + "SD = FunctionSpace(N, 'Chebyshev', bc=(a, b))\n", + "#SD = FunctionSpace(N, 'Legendre', bc=(a, b))" + ] + }, + { + "cell_type": "markdown", + "id": "db6ef1ac", + "metadata": { + "editable": true + }, + "source": [ + "Note that we can either choose a Legendre or a Chebyshev basis." + ] + }, + { + "cell_type": "markdown", + "id": "37f9d1b5", + "metadata": { + "editable": true + }, + "source": [ + "### Variational formulation\n", + "\n", + "The variational problem ([9](#eq:varform)) can be assembled using `shenfun`'s\n", + "[TrialFunction](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.TrialFunction), [TestFunction](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.TestFunction) and [inner()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.inner.inner) functions." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d3f0a739", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:22.781790Z", + "iopub.status.busy": "2024-05-24T12:36:22.781550Z", + "iopub.status.idle": "2024-05-24T12:36:22.797059Z", + "shell.execute_reply": "2024-05-24T12:36:22.796536Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u = TrialFunction(SD)\n", + "v = TestFunction(SD)\n", + "# Assemble left hand side matrix\n", + "A = inner(v, div(grad(u)))\n", + "# Assemble right hand side\n", + "fj = Array(SD, buffer=fe)\n", + "f_hat = Function(SD)\n", + "f_hat = inner(v, fj, output_array=f_hat)" + ] + }, + { + "cell_type": "markdown", + "id": "5ecdef9b", + "metadata": { + "editable": true + }, + "source": [ + "Note that the `sympy` function `fe` can be used to initialize the [Array](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Array)\n", + "`fj`. We wrap this Numpy array in an [Array](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Array) class\n", + "(`fj = Array(SD, buffer=fe)`), because an Array\n", + "is required as input to the [inner()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.inner.inner) function." + ] + }, + { + "cell_type": "markdown", + "id": "ee8d601e", + "metadata": { + "editable": true + }, + "source": [ + "### Solve linear equations\n", + "\n", + "Finally, solve linear equation system and transform solution from spectral\n", + "$\\boldsymbol{\\hat{u}}$ vector to the real space $\\{u(x_j)\\}_{j=0}^{N-1}$\n", + "and then check how the solution corresponds with the exact solution $u_e$.\n", + "To this end we compute the $L_2$-errornorm using the `shenfun` function\n", + "[dx()](https://shenfun.readthedocs.io/en/latest/shenfun.utilities.html#shenfun.utilities.dx)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3efea157", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:22.801607Z", + "iopub.status.busy": "2024-05-24T12:36:22.800978Z", + "iopub.status.idle": "2024-05-24T12:36:22.818568Z", + "shell.execute_reply": "2024-05-24T12:36:22.817851Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u_hat = A.solve(f_hat)\n", + "uj = SD.backward(u_hat)\n", + "ua = Array(SD, buffer=ue)\n", + "print(\"Error=%2.16e\" %(np.sqrt(dx((uj-ua)**2))))" + ] + }, + { + "cell_type": "markdown", + "id": "3c8908a6", + "metadata": { + "editable": true + }, + "source": [ + "### Convergence test\n", + "\n", + "To do a convergence test we will now create a function `main`, that takes the\n", + "number of quadrature points as parameter, and prints out\n", + "the error." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c69c9d1e", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:22.824094Z", + "iopub.status.busy": "2024-05-24T12:36:22.823418Z", + "iopub.status.idle": "2024-05-24T12:36:22.832489Z", + "shell.execute_reply": "2024-05-24T12:36:22.831137Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "def main(N, family='Chebyshev'):\n", + " SD = FunctionSpace(N, family=family, bc=(a, b))\n", + " u = TrialFunction(SD)\n", + " v = TestFunction(SD)\n", + "\n", + " # Get f on quad points\n", + " fj = Array(SD, buffer=fe)\n", + "\n", + " # Compute right hand side of Poisson's equation\n", + " f_hat = Function(SD)\n", + " f_hat = inner(v, fj, output_array=f_hat)\n", + "\n", + " # Get left hand side of Poisson's equation\n", + " A = inner(v, div(grad(u)))\n", + "\n", + " f_hat = A.solve(f_hat)\n", + " uj = SD.backward(f_hat)\n", + "\n", + " # Compare with analytical solution\n", + " ua = Array(SD, buffer=ue)\n", + " l2_error = np.linalg.norm(uj-ua)\n", + " return l2_error" + ] + }, + { + "cell_type": "markdown", + "id": "8199b9c0", + "metadata": { + "editable": true + }, + "source": [ + "For example, we find the error of a Chebyshev discretization\n", + "using 12 quadrature points as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e2444fa7", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:22.834406Z", + "iopub.status.busy": "2024-05-24T12:36:22.834268Z", + "iopub.status.idle": "2024-05-24T12:36:22.844487Z", + "shell.execute_reply": "2024-05-24T12:36:22.843460Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "main(12, 'Chebyshev')" + ] + }, + { + "cell_type": "markdown", + "id": "41161308", + "metadata": { + "editable": true + }, + "source": [ + "To get the convergence we call `main` for a list\n", + "of $N=[12, 16, \\ldots, 48]$, and collect the errornorms in\n", + "arrays to be plotted. The error can be plotted using\n", + "[matplotlib](https://matplotlib.org), and the generated\n", + "figure is also shown in this demos summary." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "be4c522a", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:22.848466Z", + "iopub.status.busy": "2024-05-24T12:36:22.848366Z", + "iopub.status.idle": "2024-05-24T12:36:23.839597Z", + "shell.execute_reply": "2024-05-24T12:36:23.837516Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "N = range(12, 50, 4)\n", + "error = {}\n", + "for basis in ('legendre', 'chebyshev'):\n", + " error[basis] = []\n", + " for i in range(len(N)):\n", + " errN = main(N[i], basis)\n", + " error[basis].append(errN)\n", + "\n", + "plt.figure(figsize=(6, 4))\n", + "for basis, col in zip(('legendre', 'chebyshev'), ('r', 'b')):\n", + " plt.semilogy(N, error[basis], col, linewidth=2)\n", + "plt.title('Convergence of Poisson solvers 1D')\n", + "plt.xlabel('N')\n", + "plt.ylabel('Error norm')\n", + "plt.legend(('Legendre', 'Chebyshev'))\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "09bd3e41", + "metadata": { + "editable": true + }, + "source": [ + "The spectral convergence is evident and we can see that\n", + "after $N=40$ roundoff errors dominate as the errornorm trails off around $10^{-14}$." + ] + }, + { + "cell_type": "markdown", + "id": "d778fc61", + "metadata": { + "editable": true + }, + "source": [ + "## Complete solver\n", + "\n", + "\n", + "A complete solver, that can use any family of bases (Chebyshev, Legendre, Jacobi, Chebyshev second kind),\n", + "and any kind of boundary condition, can be found [here](https://github.com/spectralDNS/shenfun/blob/master/demo/poisson1D.py).\n", + "\n", + "\n", + "\n", + "1. **J. Shen**. Efficient Spectral-Galerkin Method I. Direct Solvers of Second- and Fourth-Order Equations Using Legendre Polynomials, *SIAM Journal on Scientific Computing*, 15(6), pp. 1489-1505, [doi: 10.1137/0915089](https://dx.doi.org/10.1137/0915089), 1994.\n", + "\n", + "2. **J. Shen**. Efficient Spectral-Galerkin Method II. Direct Solvers of Second- and Fourth-Order Equations Using Chebyshev Polynomials, *SIAM Journal on Scientific Computing*, 16(1), pp. 74-87, [doi: 10.1137/0916006](https://dx.doi.org/10.1137/0916006), 1995." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/Poisson3D/poisson3d.ipynb b/docs/demos/Poisson3D/poisson3d.ipynb new file mode 100644 index 00000000..1dd32e0a --- /dev/null +++ b/docs/demos/Poisson3D/poisson3d.ipynb @@ -0,0 +1,1440 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "8da58369", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - 3D Poisson's equation\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **April 13, 2018**\n", + "\n", + "**Summary.** This is a demonstration of how the Python module [shenfun](https://github.com/spectralDNS/shenfun) can be used to solve a 3D Poisson\n", + "equation in a 3D tensor product domain that has homogeneous Dirichlet boundary\n", + "conditions in one direction and periodicity in the\n", + "remaining two. The solver described runs with MPI without any further\n", + "considerations required from the user. Spectral convergence, as shown in [Figure 1](#fig:3d:ct0), is demonstrated.\n", + "The demo is implemented in slightly more generic terms (more boundary conditions) in\n", + "[poisson3D.py](https://github.com/spectralDNS/shenfun/blob/master/demo/poisson3D.py), and the numerical method is is described in more detail by J. Shen [[shen1]](#shen1) and [[shen95]](#shen95).\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "

Figure 1: Convergence of 3D Poisson solvers for both Legendre and Chebyshev modified basis function.

\n", + "" + ] + }, + { + "cell_type": "markdown", + "id": "f0074255", + "metadata": { + "editable": true + }, + "source": [ + "## Poisson's equation\n", + "\n", + "\n", + "Poisson's equation is given as" + ] + }, + { + "cell_type": "markdown", + "id": "89ac398c", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\nabla^2 u(\\boldsymbol{x}) = f(\\boldsymbol{x}) \\quad \\text{for }\\, \\boldsymbol{x}=(x, y, z) \\in \\Omega, \\label{eq:3d:poisson} \\tag{1}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "daa1a9ef", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "u(\\pm 1 ,y, z) =0, \n", + "\\label{_auto1} \\tag{2}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "9d4a83ba", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "u(x, 2\\pi, z) = u(x, 0, z), \n", + "\\label{_auto2} \\tag{3}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e210d64c", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "u(x, y, 2\\pi) = u(x, y, 0),\n", + "\\label{_auto3} \\tag{4}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "4e547b1b", + "metadata": { + "editable": true + }, + "source": [ + "where $u(\\boldsymbol{x})$ is the solution and $f(\\boldsymbol{x})$ is a function. The domain\n", + "$\\Omega = (-1, 1)\\times [0, 2\\pi)^2$.\n", + "\n", + "To solve Eq. ([1](#eq:3d:poisson)) with the Galerkin method we will make use of\n", + "smooth basis functions, $v(\\boldsymbol{x})$, that satisfy the given boundary\n", + "conditions. To this end we will use one basis function for the $x$-direction,\n", + "$\\mathcal{X}(x)$,\n", + "one for the $y$-direction, $\\mathcal{Y}(y)$, and one for the $z$-direction,\n", + "$\\mathcal{Z}(z)$. And\n", + "then we create three-dimensional basis functions like" + ] + }, + { + "cell_type": "markdown", + "id": "db6636f2", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "v(x, y, z) = \\mathcal{X}(x) \\mathcal{Y}(y) \\mathcal{Z} (z).\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "551b7efa", + "metadata": { + "editable": true + }, + "source": [ + "The basis functions $\\mathcal{Y}(y)$ and $\\mathcal{Z}(z)$ are chosen as Fourier exponentials, since these\n", + "functions are periodic. Likewise, the basis functions $\\mathcal{X}(x)$ are chosen as\n", + "modified Legendre or Chebyshev polynomials, using $\\phi_l(x)$ to refer to either\n", + "one" + ] + }, + { + "cell_type": "markdown", + "id": "ef225f31", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\mathcal{X}_l(x) = \\phi_l(x) - \\phi_{l+2}(x), \\forall \\, l \\in \\boldsymbol{l}^{N_0},\n", + "\\label{_auto4} \\tag{5}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e3f328da", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\mathcal{Y}_m(y) = e^{\\imath m y}, \\forall \\, m \\in \\boldsymbol{m}^{N_1}, \n", + "\\label{_auto5} \\tag{6}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "8da83855", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\mathcal{Z}_n(z) = e^{\\imath n z}, \\forall \\, n \\in \\boldsymbol{n}^{N_2},\n", + "\\label{_auto6} \\tag{7}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "be2ba56e", + "metadata": { + "editable": true + }, + "source": [ + "where the size of the discretized problem is $\\boldsymbol{N} = (N_0, N_1, N_2)$,\n", + "$\\boldsymbol{l}^{N_0} = (0, 1, \\ldots, N_0-3)$, $\\boldsymbol{m}^{N_1} =\n", + "(-N_1/2, -N_1/2+1, \\ldots, N_1/2-1)$ and $\\boldsymbol{n}^{N_2} = (-N_2/2, -N_2/2+1,\n", + "\\ldots, N_2/2-1)$. However, due to [Hermitian symmetry](https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.fft.rfft.html#numpy.fft.rfft), we only store $N_2/2+1$\n", + "wavenumbers in the $z$-direction, such that $\\boldsymbol{n}^{N_2} = (0, 1, \\ldots,\n", + "N_2/2)$. We refer to the Cartesian wavenumber mesh on vector form as $\\boldsymbol{k}$:" + ] + }, + { + "cell_type": "markdown", + "id": "552b4035", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\boldsymbol{k} = \\{(l, m, n)\\, | \\,(l, m, n) \\in \\boldsymbol{l}^{N_0} \\times \\boldsymbol{m}^{N_1} \\times \\boldsymbol{n}^{N_2}\\}.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f3af3fa7", + "metadata": { + "editable": true + }, + "source": [ + "We have the one-dimensional spaces" + ] + }, + { + "cell_type": "markdown", + "id": "1035ba0c", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "V^{N_0} = \\text{span}\\{ \\mathcal{X}_l \\}_{l\\in\\boldsymbol{l}^{N_0}}, \n", + "\\label{_auto7} \\tag{8}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "bc0ac2da", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "V^{N_1} = \\text{span}\\{ \\mathcal{Y}_m \\}_{m\\in\\boldsymbol{m}^{N_1}}, \n", + "\\label{_auto8} \\tag{9}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "92916e18", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "V^{N_2} = \\text{span}\\{ \\mathcal{Z}_n \\}_{n\\in\\boldsymbol{n}^{N_2}},\n", + "\\label{_auto9} \\tag{10}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "dbcb49ab", + "metadata": { + "editable": true + }, + "source": [ + "and from these we create a tensor product space $W^{\\boldsymbol{N}}(\\boldsymbol{x})$" + ] + }, + { + "cell_type": "markdown", + "id": "fd8d4ee7", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "W^{\\boldsymbol{N}}(\\boldsymbol{x}) = V^{N_0}(x) \\otimes V^{N_1}(y) \\otimes V^{N_2}(z).\n", + "\\label{_auto10} \\tag{11}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "a8e11dc8", + "metadata": { + "editable": true + }, + "source": [ + "And then we look for discrete solutions $u \\in W^{\\boldsymbol{N}}$ like" + ] + }, + { + "cell_type": "markdown", + "id": "acaedc94", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(\\boldsymbol{x}) = \\sum_{l\\in \\boldsymbol{l}^{N_0}} \\sum_{m\\in \\boldsymbol{m}^{N_1}}\\sum_{n\\in\n", + "\\boldsymbol{n}^{N_2}}\\hat{u}_{lmn} \\mathcal{X}_l(x) \\mathcal{Y}_m(y) \\mathcal{Z}_n(z), \\label{eq:3d:u} \\tag{12} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "423c7214", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " = \\sum_{\\boldsymbol{\\textsf{k}} \\in \\boldsymbol{k}}\\hat{u}_{\\boldsymbol{\\textsf{k}}} v_{\\boldsymbol{\\textsf{k}}}(\\boldsymbol{x}),\n", + "\\label{_auto11} \\tag{13}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "5ccbfa50", + "metadata": { + "editable": true + }, + "source": [ + "where $\\hat{u}_{lmn}$ are components of the expansion coefficients for $u$ and\n", + "the second form, $\\{\\hat{u}_{\\boldsymbol{\\textsf{k}}}\\}_{\\boldsymbol{\\textsf{k}}\\in\\boldsymbol{k}}$, is a shorter,\n", + "simplified notation, with sans-serif $\\boldsymbol{\\textsf{k}}=(l, m, n)$.\n", + "The expansion coefficients are the unknowns in the spectral Galerkin method.\n", + "\n", + "We now formulate a variational problem using the Galerkin method: Find $u \\in\n", + "W^{\\boldsymbol{N}}$ such that" + ] + }, + { + "cell_type": "markdown", + "id": "8dc22608", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\int_{\\Omega} \\nabla^2 u \\, \\overline{v} \\, w\\, \\boldsymbol{dx} = \\int_{\\Omega} f \\,\n", + "\\overline{v}\\, w\\, \\boldsymbol{dx} \\quad\n", + "\\forall v \\, \\in \\, W^{\\boldsymbol{N}}. \\label{eq:3d:varform} \\tag{14}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "2dc04875", + "metadata": { + "editable": true + }, + "source": [ + "Here $\\boldsymbol{dx}=dxdydz$, and the overline represents a complex conjugate, which is needed here because\n", + "the Fourier exponentials are complex functions.\n", + "The weighted integrals, weighted by $w(\\boldsymbol{x})$, are called inner products, and a common notation is" + ] + }, + { + "cell_type": "markdown", + "id": "92d21ff5", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\int_{\\Omega} u \\, \\overline{v} \\, w\\, \\boldsymbol{dx} = \\langle u, v\\rangle _w.\n", + "\\label{_auto12} \\tag{15}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "96f41098", + "metadata": { + "editable": true + }, + "source": [ + "The integral can either be computed exactly, or with quadrature. The advantage\n", + "of the latter is that it is faster (through Fast Fourier transforms),\n", + "and that non-linear terms may be computed just as quickly as linear.\n", + "For a linear problem, it does not make much of a difference, if any at all.\n", + "Approximating the integral with quadrature, we obtain" + ] + }, + { + "cell_type": "markdown", + "id": "e83fdfbe", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{align*}\n", + "\\int_{\\Omega} u \\, \\overline{v} \\, w\\, \\boldsymbol{dx} &\\approx \\langle u, v\n", + "\\rangle_w^{\\boldsymbol{N}}, \\\\ \n", + "&\\approx \\sum_{i=0}^{N_0-1} \\sum_{j=0}^{N_1-1}\\sum_{k=0}^{N_2-1} u(x_i, y_j, z_k) \\overline{v}(x_i, y_j, z_k) w(x_i, y_j, z_k),\n", + "\\end{align*}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "c9146845", + "metadata": { + "editable": true + }, + "source": [ + "where $w(\\boldsymbol{x})$ now are the quadrature weights. The quadrature points\n", + "$\\{x_i\\}_{i=0}^{N_0-1}$ are specific to the chosen basis, and even within basis there\n", + "are two different choices based on which quadrature rule is selected, either\n", + "Gauss or Gauss-Lobatto. The quadrature points for the Fourier bases are simply\n", + "uniformly distributed throughout the domain.\n", + "\n", + "Inserting for test function ([12](#eq:3d:u)) and trialfunction\n", + "$v_{pqr} = \\mathcal{X}_{p} \\mathcal{Y}_q \\mathcal{Z}_r$ on the\n", + "left hand side of ([14](#eq:3d:varform)), we get (with summation on repeated indices\n", + "to avoid too much clutter)" + ] + }, + { + "cell_type": "markdown", + "id": "21fc36e3", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{align*}\n", + "\\langle \\nabla^2u, v \\rangle_w^{\\boldsymbol{N}} &= \\left\\langle \\nabla^2\\sum_{l\\in \\boldsymbol{l}^{N_0}}\n", + "\\sum_{m\\in \\boldsymbol{m}^{N_1}}\\sum_{n\\in \\boldsymbol{n}^{N_2}}\\hat{u}_{lmn}\n", + "\\mathcal{X}_{l} \\mathcal{Y}_m \\mathcal{Z}_n,\n", + "\\mathcal{X}_{p} \\mathcal{Y}_q \\mathcal{Z}_r \\right\\rangle_w^{\\boldsymbol{N}}, \\\\ \n", + " &= \\left[\\left(\\mathcal{X}_l^{''}, \\mathcal{X}_p \\right)_w^N - (m^2+n^2)\\left(\\mathcal{X}_l, \\mathcal{X}_p \\right)_w^N \\right]\\delta_{mq} \\delta_{nr} \\hat{u}_{lmn}, \\\\ \n", + " &= \\left( a_{pl} - (m^2 + n^2)b_{pl}\\right) \\hat{u}_{lqr}, \\quad \\forall (p,q,r) \\in \\boldsymbol{k},\n", + "\\end{align*}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "bad9c02f", + "metadata": { + "editable": true + }, + "source": [ + "where the notation $(\\cdot, \\cdot)_w^{N_0}$" + ] + }, + { + "cell_type": "markdown", + "id": "f5ec1f67", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "b_{pl} = \\left( \\mathcal{X}_l, \\mathcal{X}_p \\right)_w^{N_0} = \\sum_{i=0}^{N_0-1} \\mathcal{X}_l(x_i)\n", + "\\mathcal{X}_p(x_i) w(x_i),\n", + "\\label{_auto13} \\tag{16}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "d98f0d68", + "metadata": { + "editable": true + }, + "source": [ + "is used to represent a discrete $L_2$ inner product along only the first, nonperiodic,\n", + "direction. The delta functions above come from integrating over the two periodic\n", + "directions, where we use constant weight functions $w=1/(2\\pi)$ in the\n", + "inner products" + ] + }, + { + "cell_type": "markdown", + "id": "31a7b9e0", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\int_0^{2\\pi} \\mathcal{Y}_m(y) \\overline{\\mathcal{Y}}_q(y) \\frac{1}{2\\pi} dy = \\delta_{mq}, \\label{eq:delta0} \\tag{17}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "9fd98dac", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\int_0^{2\\pi} \\mathcal{Z}_n(z) \\overline{\\mathcal{Z}}_r(z) \\frac{1}{2\\pi} dz = \\delta_{nr}. \\label{eq:delta1} \\tag{18}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "ca9501a2", + "metadata": { + "editable": true + }, + "source": [ + "The Kronecker delta-function $\\delta_{ij}$ is one for $i=j$ and\n", + "zero otherwise.\n", + "\n", + "The right hand side of Eq. ([14](#eq:3d:varform)) is computed as" + ] + }, + { + "cell_type": "markdown", + "id": "f7ae0369", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\tilde{f}_{pqr} = \\left\\langle f, \\mathcal{X}_{p}\n", + "\\mathcal{Y}_q \\mathcal{Z}_r \\right \\rangle_w^{\\boldsymbol{N}},\n", + "\\label{_auto14} \\tag{19}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "654013fb", + "metadata": { + "editable": true + }, + "source": [ + "where a tilde is used because this is not a complete transform of the function\n", + "$f$, but only an inner product.\n", + "\n", + "The linear system of equations to solve for the expansion coefficients can now\n", + "be found as follows" + ] + }, + { + "cell_type": "markdown", + "id": "a41c8cd2", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\left(a_{lp} - (m^2+n^2)b_{lp}\\right) \\hat{u}_{pmn} =\n", + "\\tilde{f}_{lmn}\\quad \\forall \\, (l,m,n) \\in \\boldsymbol{k}. \\label{eq:AB} \\tag{20}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f6850f1c", + "metadata": { + "editable": true + }, + "source": [ + "Now, when $\\hat{\\boldsymbol{u}} = \\{\\hat{u}_{\\boldsymbol{\\textsf{k}}}\\}_{\\boldsymbol{\\textsf{k}} \\in \\boldsymbol{k}}$ is\n", + "found by solving this linear system over the\n", + "entire computational mesh, it may be\n", + "transformed to real space $u(\\boldsymbol{x})$ using ([12](#eq:3d:u)). Note that the matrices\n", + "$A \\in \\mathbb{R}^{N_0-2 \\times N_0-2}$ and $B \\in \\mathbb{R}^{N_0-2 \\times N_0-2}$\n", + "differ for Legendre or Chebyshev bases, but\n", + "for either case they have a\n", + "special structure that allows for a solution to be found very efficiently\n", + "in the order of $\\mathcal{O}(N_0-3)$ operations given $m$ and $n$, see\n", + "[[shen1]](#shen1) and [[shen95]](#shen95). Fast solvers for ([20](#eq:AB)) are implemented in `shenfun` for both bases." + ] + }, + { + "cell_type": "markdown", + "id": "cc81feaf", + "metadata": { + "editable": true + }, + "source": [ + "### Method of manufactured solutions\n", + "\n", + "In this demo we will use the method of manufactured\n", + "solutions to demonstrate spectral accuracy of the `shenfun` bases. To\n", + "this end we choose a smooth analytical function that satisfies the given boundary\n", + "conditions:" + ] + }, + { + "cell_type": "markdown", + "id": "f7eae13e", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u_e(x, y, z) = \\left(\\cos(4x) + \\sin(2y) + \\sin(4z)\\right)(1-x^2). \\label{eq:3d:u_e} \\tag{21}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "7cc93b44", + "metadata": { + "editable": true + }, + "source": [ + "Sending $u_e$ through the Laplace operator, we obtain the right hand side" + ] + }, + { + "cell_type": "markdown", + "id": "b64405fc", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\nabla^2 u_e(x,y,z) = -16(1 - x^2) \\cos(4 x) + 16 x \\sin(4 x) - 2 \\cos(4 x)\n", + " - (1-x^2)(4 \\sin(2y) + 16\\sin(4z)). \\label{eq:3d:solution} \\tag{22}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "bc33b415", + "metadata": { + "editable": true + }, + "source": [ + "Now, setting $f_e(\\boldsymbol{x}) = \\nabla^2 u_e(\\boldsymbol{x})$ and solving for $\\nabla^2\n", + "u(\\boldsymbol{x}) = f_e(\\boldsymbol{x})$, we can compare the numerical solution $u(\\boldsymbol{x})$ with\n", + "the analytical solution $u_e(\\boldsymbol{x})$ and compute error norms." + ] + }, + { + "cell_type": "markdown", + "id": "fc08f897", + "metadata": { + "editable": true + }, + "source": [ + "## Implementation" + ] + }, + { + "cell_type": "markdown", + "id": "09a2f0ce", + "metadata": { + "editable": true + }, + "source": [ + "### Preamble\n", + "\n", + "We will solve the Poisson problem using the [shenfun](https://github.com/spectralDNS/shenfun) Python module. The first thing needed\n", + "is then to import some of this module's functionality\n", + "plus some other helper modules, like [Numpy](https://numpy.org) and [Sympy](https://sympy.org):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "edf17730", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:33.748091Z", + "iopub.status.busy": "2024-05-24T12:36:33.747969Z", + "iopub.status.idle": "2024-05-24T12:36:34.269454Z", + "shell.execute_reply": "2024-05-24T12:36:34.267728Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from sympy import symbols, cos, sin, exp, lambdify\n", + "import numpy as np\n", + "from shenfun.tensorproductspace import TensorProductSpace\n", + "from shenfun import inner, div, grad, TestFunction, TrialFunction, Function, \\\n", + " project, Dx, FunctionSpace, comm, Array, chebyshev, dx, la" + ] + }, + { + "cell_type": "markdown", + "id": "c73b4c22", + "metadata": { + "editable": true + }, + "source": [ + "We use `Sympy` for the manufactured solution and `Numpy` for testing. MPI for\n", + "Python (`mpi4py`) is required for running the solver with MPI." + ] + }, + { + "cell_type": "markdown", + "id": "5f7917d3", + "metadata": { + "editable": true + }, + "source": [ + "### Manufactured solution\n", + "\n", + "The exact solution $u_e(x, y, z)$ and the right hand side $f_e(x, y, z)$ are created using `Sympy` as follows" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "31c9285d", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:34.276484Z", + "iopub.status.busy": "2024-05-24T12:36:34.275848Z", + "iopub.status.idle": "2024-05-24T12:36:34.305900Z", + "shell.execute_reply": "2024-05-24T12:36:34.304019Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "x, y, z = symbols(\"x,y,z\")\n", + "ue = (cos(4*x) + sin(2*y) + sin(4*z))*(1-x**2)\n", + "fe = ue.diff(x, 2) + ue.diff(y, 2) + ue.diff(z, 2)" + ] + }, + { + "cell_type": "markdown", + "id": "bd9f1e6e", + "metadata": { + "editable": true + }, + "source": [ + "These solutions are now valid for a continuous domain. The next step is thus to\n", + "discretize, using the computational mesh" + ] + }, + { + "cell_type": "markdown", + "id": "dd64ad46", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "(x_i, y_j, z_k)\\, \\forall \\, (i, j, k) \\in [0, 1,\\ldots, N_0-1] \\times [0, 1, \\ldots, N_1-1] \\times [0, 1, \\ldots, N_2-1]\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "61577524", + "metadata": { + "editable": true + }, + "source": [ + "and a finite number of basis functions.\n", + "\n", + "Note that it is not mandatory to use `Sympy` for the manufactured solution. Since the\n", + "solution is known ([22](#eq:3d:solution)), we could just as well simply use `Numpy`\n", + "to compute $f_e$. However, with `Sympy` it is much\n", + "easier to experiment and quickly change the solution." + ] + }, + { + "cell_type": "markdown", + "id": "995b9608", + "metadata": { + "editable": true + }, + "source": [ + "### Discretization and MPI\n", + "\n", + "We create three function spaces with given size, one for each dimension of the problem.\n", + "From these three spaces a [TensorProductSpace](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.tensorproductspace.TensorProductSpace) is created." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d7ae8f20", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:34.313301Z", + "iopub.status.busy": "2024-05-24T12:36:34.313171Z", + "iopub.status.idle": "2024-05-24T12:36:34.329047Z", + "shell.execute_reply": "2024-05-24T12:36:34.328465Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "# Size of discretization\n", + "N = [14, 15, 16]\n", + "\n", + "SD = FunctionSpace(N[0], 'Chebyshev', bc=(0, 0))\n", + "#SD = FunctionSpace(N[0], 'Legendre', bc=(0, 0))\n", + "K1 = FunctionSpace(N[1], 'Fourier', dtype='D')\n", + "K2 = FunctionSpace(N[2], 'Fourier', dtype='d')\n", + "T = TensorProductSpace(comm, (SD, K1, K2), axes=(0, 1, 2))\n", + "X = T.local_mesh()" + ] + }, + { + "cell_type": "markdown", + "id": "072f1919", + "metadata": { + "editable": true + }, + "source": [ + "Note that we can either choose a Legendre or a Chebyshev basis for the\n", + "nonperiodic direction. The\n", + "[TensorProductSpace](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.tensorproductspace.TensorProductSpace) class takes an MPI communicator as first argument and the\n", + "computational mesh is distributed internally using the `pencil` method. The\n", + "`T.local_mesh` method returns the mesh local to each processor. The `axes`\n", + "keyword determines the order of transforms going back and forth between real and\n", + "spectral space. With `axes=(0, 1, 2)` and a forward transform (from real space\n", + "to spectral, i.e., from $u$ to $\\hat{u}$) axis 2 is transformed first and then 1\n", + "and 0, respectively.\n", + "\n", + "The manufactured solution is created with Dirichlet boundary conditions in the\n", + "$x$-direction, and for this reason `SD` is the first space in `T`. We could just\n", + "as well have put the nonperiodic direction along either $y$- or $z$-direction,\n", + "though, but this would then require that the order of the transformed axes be\n", + "changed as well. For example, putting the Dirichlet direction along $y$, we\n", + "would need to create the tensorproductspace as" + ] + }, + { + "cell_type": "markdown", + "id": "28775815", + "metadata": { + "editable": true + }, + "source": [ + "```Python\n", + " T = TensorProductSpace(comm, (K1, SD, K2), axes=(1, 0, 2))\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "3ee1fe90", + "metadata": { + "editable": true + }, + "source": [ + "such that the Dirichlet direction is the last to be transformed. The reason for\n", + "this is that only the Dirichlet direction leads to matrices that need to be\n", + "inverted (or solved). And for this we need the entire data array along the Dirichlet\n", + "direction to be local to the processor. If the `SD` basis is the last to be\n", + "transformed, then the data will be aligned in this direction, whereas the other\n", + "two directions may both, or just one of them, be distributed.\n", + "\n", + "Note that `X` is a list containing local values of the arrays $\\{x_i\\}_{i=0}^{N_0-1}$,\n", + "$\\{y_j\\}_{j=0}^{N_1-1}$ and $\\{z_k\\}_{k=0}^{N_2-1}$.\n", + "Now, it's not possible to run a jupyter notebook with more than one process,\n", + "but we can imagine running [the complete solver](https://github.com/spectralDNS/shenfun/blob/master/demo/poisson3D.py)\n", + "with 4 procesors and a processor mesh of shape $2\\times 2$.\n", + "We would then get the following local slices for\n", + "each processor in spectral space" + ] + }, + { + "cell_type": "markdown", + "id": "ef84f575", + "metadata": { + "editable": true + }, + "source": [ + "```Python\n", + " print(comm.Get_rank(), T.local_slice())\n", + " 3 [slice(0, 14, None), slice(8, 15, None), slice(5, 9, None)]\n", + " 1 [slice(0, 14, None), slice(0, 8, None), slice(5, 9, None)]\n", + " 2 [slice(0, 14, None), slice(8, 15, None), slice(0, 5, None)]\n", + " 0 [slice(0, 14, None), slice(0, 8, None), slice(0, 5, None)]\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "dce94b33", + "metadata": { + "editable": true + }, + "source": [ + "where the global shape is $\\boldsymbol{N}=(14, 15, 9)$ after taking advantage of\n", + "Hermitian symmetry in the $z$-direction. So, all processors have the complete first dimension available locally, as they\n", + "should. Furthermore, processor three owns the slices from $8:15$ and $5:9$ along\n", + "axes $y$ and $z$, respectively. Processor 2 owns slices $0:8$ and $0:5$ etc. In\n", + "real space the mesh is distributed differently. First of all the global mesh\n", + "shape is $\\boldsymbol{N}=(14, 15, 16)$, and it is distributed along the first two\n", + "dimensions. The local slices can be inspected as" + ] + }, + { + "cell_type": "markdown", + "id": "dce14f99", + "metadata": { + "editable": true + }, + "source": [ + "```Python\n", + " print(comm.Get_rank(), T.local_slice(False))\n", + " 0 [slice(0, 7, None), slice(0, 8, None), slice(0, 16, None)]\n", + " 1 [slice(0, 7, None), slice(8, 15, None), slice(0, 16, None)]\n", + " 2 [slice(7, 14, None), slice(0, 8, None), slice(0, 16, None)]\n", + " 3 [slice(7, 14, None), slice(8, 15, None), slice(0, 16, None)]\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "2d326fe7", + "metadata": { + "editable": true + }, + "source": [ + "Since two directions are distributed, both in spectral and real space, we say\n", + "that we have a two-dimensional decomposition (here a $2\\times 2$ shaped\n", + "processor mesh) and the\n", + "MPI distribution is of type *pencil*. It is also possible to choose a *slab*\n", + "decomposition, where only one dimension of the array is distributed. This choice\n", + "needs to be made when creating the tensorproductspace as" + ] + }, + { + "cell_type": "markdown", + "id": "28b8a840", + "metadata": { + "editable": true + }, + "source": [ + "```Python\n", + " T = TensorProductSpace(comm, (SD, K1, K2), axes=(0, 1, 2), slab=True)\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "38b546dd", + "metadata": { + "editable": true + }, + "source": [ + "which would lead to a mesh that is distributed along $x$-direction in real space\n", + "and $y$-direction in spectral space. The local slices would then be" + ] + }, + { + "cell_type": "markdown", + "id": "f68d8c78", + "metadata": { + "editable": true + }, + "source": [ + " print(comm.Get_rank(), T.local_slice()) # spectral space\n", + " 1 [slice(0, 14, None), slice(4, 8, None), slice(0, 9, None)]\n", + " 2 [slice(0, 14, None), slice(8, 12, None), slice(0, 9, None)]\n", + " 0 [slice(0, 14, None), slice(0, 4, None), slice(0, 9, None)]\n", + " 3 [slice(0, 14, None), slice(12, 15, None), slice(0, 9, None)]\n", + " print(comm.Get_rank(), T.local_slice(False)) # real space\n", + " 3 [slice(11, 14, None), slice(0, 15, None), slice(0, 16, None)]\n", + " 0 [slice(0, 4, None), slice(0, 15, None), slice(0, 16, None)]\n", + " 2 [slice(8, 11, None), slice(0, 15, None), slice(0, 16, None)]\n", + " 1 [slice(4, 8, None), slice(0, 15, None), slice(0, 16, None)]\n" + ] + }, + { + "cell_type": "markdown", + "id": "f4c9f423", + "metadata": { + "editable": true + }, + "source": [ + "Note that the *slab* decomposition is usually the fastest choice. However, the maximum\n", + "number of processors with *slab* is $\\min \\{N_0, N_1\\}$, whereas a *pencil*\n", + "approach can be used with up to $\\min \\{N_1(N_2/2+1), N_0 N_1\\}$ processors." + ] + }, + { + "cell_type": "markdown", + "id": "3530d3aa", + "metadata": { + "editable": true + }, + "source": [ + "### Variational formulation\n", + "\n", + "The variational problem ([14](#eq:3d:varform)) can be assembled using `shenfun`'s\n", + "form language, which is perhaps surprisingly similar to FEniCS." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4c0bbdd5", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:34.354941Z", + "iopub.status.busy": "2024-05-24T12:36:34.354656Z", + "iopub.status.idle": "2024-05-24T12:36:34.377303Z", + "shell.execute_reply": "2024-05-24T12:36:34.374818Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u = TrialFunction(T)\n", + "v = TestFunction(T)\n", + "# Get f on quad points\n", + "fj = Array(T, buffer=fe)\n", + "# Compute right hand side of Poisson equation\n", + "f_hat = inner(v, fj)\n", + "# Get left hand side of Poisson equation\n", + "matrices = inner(v, div(grad(u)))" + ] + }, + { + "cell_type": "markdown", + "id": "8d0bf840", + "metadata": { + "editable": true + }, + "source": [ + "The Laplacian operator is recognized as `div(grad)`. The `matrices` object is a\n", + "list of two tensor product matrices, stored as instances of the class [TPMatrix](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.matrixbase.TPMatrix).\n", + "The two tensor product matrices represents" + ] + }, + { + "cell_type": "markdown", + "id": "956b3de7", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "a_{pl} \\delta_{mq} \\delta_{nr}\\, \\text{ and }\\, -(m^2 + n^2)b_{pl} \\delta_{mq} \\delta_{nr}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "debfb9d2", + "metadata": { + "editable": true + }, + "source": [ + "from Eqs. ([20](#eq:AB)), ([17](#eq:delta0)) and ([18](#eq:delta1)).\n", + "The second matrix ($-(m^2 + n^2)b_{pl} \\delta_{mq} \\delta_{nr}$) has an\n", + "attribute `scale` that is equal to $-(m^2+n^2)$.\n", + "This `scale` is stored as a numpy array of shape $(1, 15, 9)$, representing the set\n", + "$\\{-(m^2+n^2): (m, n) \\in \\boldsymbol{m}^{N_1} \\times \\boldsymbol{n}^{N_2}\\}$. Note that $\\boldsymbol{n}^{N_2}$ is stored\n", + "simply as an array of length $N_2/2+1$ (here 9), since the transform in direction $z$\n", + "takes a real signal and transforms it taking advantage of Hermitian symmetry,\n", + "see [rfft](https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.fft.rfft.html)." + ] + }, + { + "cell_type": "markdown", + "id": "42f47488", + "metadata": { + "editable": true + }, + "source": [ + "### Solve linear equations\n", + "\n", + "Finally, solve linear equation system and transform solution from spectral\n", + "$\\hat{u}_{\\boldsymbol{\\textsf{k}}}$ vector to the real space $u(\\boldsymbol{x})$ and then check how the solution corresponds with the exact solution $u_e$." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "abc14f5d", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:34.387713Z", + "iopub.status.busy": "2024-05-24T12:36:34.387515Z", + "iopub.status.idle": "2024-05-24T12:36:34.407210Z", + "shell.execute_reply": "2024-05-24T12:36:34.402354Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "# Create Helmholtz linear algebra solver\n", + "Solver = chebyshev.la.Helmholtz\n", + "#Solver = la.SolverGeneric1ND # For Legendre\n", + "H = Solver(matrices)\n", + "\n", + "# Solve and transform to real space\n", + "u_hat = Function(T) # Solution spectral space\n", + "u_hat = H(u_hat, f_hat) # Solve\n", + "uq = T.backward(u_hat)\n", + "\n", + "# Compare with analytical solution\n", + "uj = Array(T, buffer=ue)\n", + "error = comm.reduce(np.linalg.norm(uj-uq)**2)\n", + "if comm.Get_rank() == 0:\n", + " print(\"Error=%2.16e\" %(np.sqrt(error)))" + ] + }, + { + "cell_type": "markdown", + "id": "3c8908a6", + "metadata": { + "editable": true + }, + "source": [ + "### Convergence test\n", + "\n", + "To do a convergence test we will now create a function `main`, that takes the\n", + "number of quadrature points as parameter, and prints out\n", + "the error." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "88433058", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:34.414789Z", + "iopub.status.busy": "2024-05-24T12:36:34.414577Z", + "iopub.status.idle": "2024-05-24T12:36:34.420760Z", + "shell.execute_reply": "2024-05-24T12:36:34.420018Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "def main(N, family='Chebyshev'):\n", + " Solver = chebyshev.la.Helmholtz if family.lower() == 'chebyshev' else la.SolverGeneric1ND\n", + " SD = FunctionSpace(N, family=family, bc=(0, 0))\n", + " K1 = FunctionSpace(N, family='F', dtype='D')\n", + " K2 = FunctionSpace(N, family='F', dtype='d')\n", + " T = TensorProductSpace(comm, (SD, K1, K2), axes=(0, 1, 2))\n", + "\n", + " u = TrialFunction(T)\n", + " v = TestFunction(T)\n", + "\n", + " # Get f on quad points\n", + " fj = Array(T, buffer=fe)\n", + "\n", + " # Compute right hand side of Poisson's equation\n", + " f_hat = Function(T)\n", + " f_hat = inner(v, fj, output_array=f_hat)\n", + " if family == 'legendre':\n", + " f_hat *= -1.\n", + "\n", + " # Get left hand side of Poisson equation\n", + " if family.lower() == 'chebyshev':\n", + " matrices = inner(v, div(grad(u)))\n", + " else:\n", + " matrices = inner(grad(v), grad(u))\n", + "\n", + " # Create Helmholtz linear algebra solver\n", + " H = Solver(matrices)\n", + "\n", + " # Solve and transform to real space\n", + " u_hat = Function(T) # Solution spectral space\n", + " u_hat = H(f_hat, u_hat) # Solve\n", + "\n", + " uj = Array(T)\n", + " uj = u_hat.backward(uj)\n", + "\n", + " # Compare with analytical solution\n", + " ua = Array(T, buffer=ue)\n", + " #l2_error = np.linalg.norm(uj-ua)\n", + " L2_error = np.sqrt(dx((uj-ua)**2))\n", + " return L2_error" + ] + }, + { + "cell_type": "markdown", + "id": "8199b9c0", + "metadata": { + "editable": true + }, + "source": [ + "For example, we find the error of a Chebyshev discretization\n", + "using 12 quadrature points as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e2444fa7", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:34.426574Z", + "iopub.status.busy": "2024-05-24T12:36:34.426367Z", + "iopub.status.idle": "2024-05-24T12:36:34.449511Z", + "shell.execute_reply": "2024-05-24T12:36:34.448639Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "main(12, 'Chebyshev')" + ] + }, + { + "cell_type": "markdown", + "id": "41161308", + "metadata": { + "editable": true + }, + "source": [ + "To get the convergence we call `main` for a list\n", + "of $N=[12, 16, \\ldots, 48]$, and collect the errornorms in\n", + "arrays to be plotted. The error can be plotted using\n", + "[matplotlib](https://matplotlib.org), and the generated\n", + "figure is also shown in this demos summary." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "be4c522a", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:34.454817Z", + "iopub.status.busy": "2024-05-24T12:36:34.454583Z", + "iopub.status.idle": "2024-05-24T12:36:37.054986Z", + "shell.execute_reply": "2024-05-24T12:36:37.050754Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "N = range(12, 50, 4)\n", + "error = {}\n", + "for basis in ('legendre', 'chebyshev'):\n", + " error[basis] = []\n", + " for i in range(len(N)):\n", + " errN = main(N[i], basis)\n", + " error[basis].append(errN)\n", + "\n", + "plt.figure(figsize=(6, 4))\n", + "for basis, col in zip(('legendre', 'chebyshev'), ('r', 'b')):\n", + " plt.semilogy(N, error[basis], col, linewidth=2)\n", + "plt.title('Convergence of Poisson solvers 1D')\n", + "plt.xlabel('N')\n", + "plt.ylabel('Error norm')\n", + "plt.legend(('Legendre', 'Chebyshev'))\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "2e83be02", + "metadata": { + "editable": true + }, + "source": [ + "The spectral convergence is evident and we can see that\n", + "after $N=24$ roundoff errors dominate as the errornorm trails off around $10^{-14}$." + ] + }, + { + "cell_type": "markdown", + "id": "bdbe8c88", + "metadata": { + "editable": true + }, + "source": [ + "## Complete solver\n", + "\n", + "\n", + "A complete solver, that can use any family of bases (Chebyshev, Legendre, Jacobi, Chebyshev second kind),\n", + "and any kind of boundary condition, can be found [here](https://github.com/spectralDNS/shenfun/blob/master/demo/poisson3D.py).\n", + "\n", + "\n", + "\n", + "1. **J. Shen**. Efficient Spectral-Galerkin Method I. Direct Solvers of Second- and Fourth-Order Equations Using Legendre Polynomials, *SIAM Journal on Scientific Computing*, 15(6), pp. 1489-1505, [doi: 10.1137/0915089](https://dx.doi.org/10.1137/0915089), 1994.\n", + "\n", + "2. **J. Shen**. Efficient Spectral-Galerkin Method II. Direct Solvers of Second- and Fourth-Order Equations Using Chebyshev Polynomials, *SIAM Journal on Scientific Computing*, 16(1), pp. 74-87, [doi: 10.1137/0916006](https://dx.doi.org/10.1137/0916006), 1995." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/PolarHelmholtz/polarhelmholtz.ipynb b/docs/demos/PolarHelmholtz/polarhelmholtz.ipynb new file mode 100644 index 00000000..8a40a30f --- /dev/null +++ b/docs/demos/PolarHelmholtz/polarhelmholtz.ipynb @@ -0,0 +1,1456 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "1d07c42c", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - Helmholtz equation in polar coordinates\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **April 8, 2020**\n", + "\n", + "**Summary.** This is a demonstration of how the Python module [shenfun](https://github.com/spectralDNS/shenfun) can be used to solve the\n", + "Helmholtz equation on a circular disc, using polar coordinates. This demo is implemented in\n", + "a single Python file [unitdisc_helmholtz.py](https://github.com/spectralDNS/shenfun/blob/master/demo/unitdisc_helmholtz.py),\n", + "and the numerical method is described in more detail by J. Shen [[shen3]](#shen3).\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "

Figure 1: Helmholtz on the unit disc.

\n", + "" + ] + }, + { + "cell_type": "markdown", + "id": "a8436390", + "metadata": { + "editable": true + }, + "source": [ + "## Helmholtz equation\n", + "\n", + "\n", + "The Helmholtz equation is given as" + ] + }, + { + "cell_type": "markdown", + "id": "5432fbb6", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "-\\nabla^2 u(\\boldsymbol{x}) + \\alpha u(\\boldsymbol{x}) = f(\\boldsymbol{x}) \\quad \\text{for }\\, \\boldsymbol{x}=(x, y) \\in \\Omega, \\label{eq:helmholtz} \\tag{1}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "74c368e2", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "u =0 \\text{ on } \\partial \\Omega,\n", + "\\label{_auto1} \\tag{2}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "28ce39e0", + "metadata": { + "editable": true + }, + "source": [ + "where $u(\\boldsymbol{x})$ is the solution, $f(\\boldsymbol{x})$ is a function and $\\alpha$ a constant.\n", + "The domain is a circular disc $\\Omega = \\{(x, y): x^2+y^2 < a^2\\}$ with radius $a$.\n", + "We use polar coordinates $(\\theta, r)$, defined as" + ] + }, + { + "cell_type": "markdown", + "id": "abcc039f", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " x = r \\cos \\theta, \n", + "\\label{_auto2} \\tag{3}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "efcb355f", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " y = r \\sin \\theta,\n", + "\\label{_auto3} \\tag{4}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "ec76706d", + "metadata": { + "editable": true + }, + "source": [ + "which leads to a Cartesian product mesh $(\\theta, r) \\in [0, 2\\pi) \\times (0, a)$\n", + "suitable for numerical implementations. Note that the\n", + "two directions are ordered with $\\theta$ first and then $r$, which is less common\n", + "than $(r, \\theta)$. This has to do with the fact that we will need to\n", + "solve linear equation systems along the radial direction, but not\n", + "the $\\theta$-direction, since Fourier matrices are diagonal. When\n", + "the radial direction is placed last, the data in the radial direction\n", + "will be contigeous in a row-major C memory, leading to faster memory\n", + "access where it is needed the most. Note that it takes very few\n", + "changes in `shenfun` to switch the directions to $(r, \\theta)$ if this\n", + "is still desired.\n", + "\n", + "We will use Chebyshev\n", + "or Legendre basis functions $\\psi_j(r)$ for the radial direction and\n", + "a periodic Fourier expansion in $\\exp(\\imath k \\theta)$ for the\n", + "azimuthal direction. The polar basis functions are as such" + ] + }, + { + "cell_type": "markdown", + "id": "f1e0f267", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "v_{kj}(\\theta, r) = \\exp(\\imath k \\theta) \\psi_j(r),\n", + "\\label{_auto4} \\tag{5}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "c73ec530", + "metadata": { + "editable": true + }, + "source": [ + "and we look for solutions" + ] + }, + { + "cell_type": "markdown", + "id": "9af694a9", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(\\mathbf{x}) = \\tilde{u}(\\theta, r) = \\sum_{k} \\sum_{j} \\hat{u}_{kj} v_{kj}(\\theta, r).\n", + "\\label{_auto5} \\tag{6}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "7dc44a76", + "metadata": { + "editable": true + }, + "source": [ + "Note that $\\tilde{u}$ is the function $u$ mapped to computational space.\n", + "From now on we will simply use $u(\\theta, r)$ without the tilde, and assume that\n", + "the proper version of the function is understood from its arguments.\n", + "\n", + "A discrete Fourier approximation space with $N$ basis functions is then" + ] + }, + { + "cell_type": "markdown", + "id": "e2c0c9b8", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "V_F^N = \\text{span} \\{\\exp(\\imath k \\theta)| \\text{ for } k \\in K\\},\n", + "\\label{_auto6} \\tag{7}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "b675c87a", + "metadata": { + "editable": true + }, + "source": [ + "where the index set $K = \\{-N/2, -N/2+1, \\ldots, N/2-1\\}$. Since the solution $u(\\theta, r)$\n", + "is real, there is Hermitian symmetry and $\\hat{u}_{k,j} = \\hat{u}_{k,-j}^*$\n", + "(with $*$ denoting a complex conjugate).\n", + "For this reason we use only $k \\in K=\\{0, 1, \\ldots, N/2\\}$ in solving for\n", + "$\\hat{u}_{kj}$, and then use Hermitian symmetry to get the remaining\n", + "unknowns. This is handled under the hood by fast Fourier transforms.\n", + "\n", + "The radial basis is more tricky, because there is a nontrivial 'boundary'\n", + "condition (pole condition) that needs to be applied at the center of the disc $(r=0)$" + ] + }, + { + "cell_type": "markdown", + "id": "a2a580a7", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\frac{\\partial u(\\theta, 0)}{\\partial \\theta} = 0.\n", + "\\label{_auto7} \\tag{8}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "29ba05d7", + "metadata": { + "editable": true + }, + "source": [ + "To apply this condition we split the solution into Fourier\n", + "coefficients with wavenumber 0 and $K\\backslash \\{0\\}$,\n", + "remembering that the Fourier basis function with $k=0$ is\n", + "simply 1" + ] + }, + { + "cell_type": "markdown", + "id": "8acc3dc5", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(\\theta, r) = \\sum_{j} \\left( \\hat{u}_{0j} \\psi_{j}(r) + \\sum_{k=1}^{N/2} \\hat{u}_{kj} \\exp(\\imath k \\theta) \\psi_j(r) \\right).\n", + "\\label{_auto8} \\tag{9}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "3712274c", + "metadata": { + "editable": true + }, + "source": [ + "We then apply a different radial basis for the two $\\psi$'s in\n", + "the above equation (renaming the first $\\overline{\\psi}$)" + ] + }, + { + "cell_type": "markdown", + "id": "38afaa1e", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(\\theta, r) = \\sum_{j} \\left( \\hat{u}_{0j} \\overline{\\psi}_{j}(r) + \\sum_{k=1}^{N/2} \\hat{u}_{kj} \\exp(\\imath k \\theta) \\psi_j(r) \\right).\n", + "\\label{_auto9} \\tag{10}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f444ab42", + "metadata": { + "editable": true + }, + "source": [ + "Note that the first term $\\sum_{j} \\hat{u}_{0j} \\overline{\\psi}_{j}(r)$ is independent\n", + "of $\\theta$. Now, to enforce conditions" + ] + }, + { + "cell_type": "markdown", + "id": "eec46081", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(\\theta, a) = 0, \n", + "\\label{_auto10} \\tag{11}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "6a63be68", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\frac{\\partial u(\\theta, 0)}{\\partial \\theta} = 0,\n", + "\\label{_auto11} \\tag{12}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f41e1913", + "metadata": { + "editable": true + }, + "source": [ + "it is sufficient for the two bases ($\\overline{\\psi}$ and $\\psi$) to\n", + "satisfy" + ] + }, + { + "cell_type": "markdown", + "id": "06d79350", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\overline{\\psi}_j(a) = 0, \n", + "\\label{_auto12} \\tag{13}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "869ecbbc", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\psi_j(a) = 0,\n", + "\\label{_auto13} \\tag{14}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "21ee8cae", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\psi_j(0) = 0.\n", + "\\label{_auto14} \\tag{15}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "4319dd50", + "metadata": { + "editable": true + }, + "source": [ + "Bases that satisfy these conditions can be found both with Legendre and\n", + "Chebyshev polynomials.\n", + "If $\\phi_j(x)$ is used for either the Legendre polynomial $L_j(x)$ or the\n", + "Chebyshev polynomial of the first kind $T_j(x)$, we can have" + ] + }, + { + "cell_type": "markdown", + "id": "8227d2da", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\overline{\\psi}_j(r) = \\phi_j(2r/a-1) - \\phi_{j+1}(2r/a-1), \\text{ for } j \\in 0, 1, \\ldots N-1, \n", + "\\label{_auto15} \\tag{16}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "0aac6186", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\psi_j(r) = \\phi_j(2r/a-1) - \\phi_{j+2}(2r/a-1), \\text{ for } j \\in 0, 1, \\ldots N-2.\n", + "\\label{eq:psi} \\tag{17}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "d6161bd1", + "metadata": { + "editable": true + }, + "source": [ + "Define the following approximation spaces for the radial direction" + ] + }, + { + "cell_type": "markdown", + "id": "ed53c2c4", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "V_D^N = \\text{span} \\{\\psi_j\\}_{j=0}^{N-3} \n", + "\\label{_auto16} \\tag{18}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "b6fdf5eb", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "V_U^N = \\text{span} \\{\\overline{\\psi}_j\\}_{j=0}^{N-2} \n", + "\\label{_auto17} \\tag{19}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "976a21cf", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\label{_auto18} \\tag{20}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "86adfe7c", + "metadata": { + "editable": true + }, + "source": [ + "and split the function space for the azimuthal direction into" + ] + }, + { + "cell_type": "markdown", + "id": "6c997fcf", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "V_F^0 = \\text{span}\\{1\\}, \n", + "\\label{_auto19} \\tag{21}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e0a07851", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "V_F^{1} = \\text{span} \\{\\exp(\\imath k \\theta)\\}, \\text{ for } k \\in K \\backslash \\{0\\}.\n", + "\\label{_auto20} \\tag{22}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "c171d086", + "metadata": { + "editable": true + }, + "source": [ + "We then look for solutions" + ] + }, + { + "cell_type": "markdown", + "id": "42be4adc", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(\\theta, r) = u^0(r) + u^1(\\theta, r),\n", + "\\label{_auto21} \\tag{23}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "ab4aeed8", + "metadata": { + "editable": true + }, + "source": [ + "where" + ] + }, + { + "cell_type": "markdown", + "id": "5d3b3e3d", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u^0(r) = \\sum_{j=0}^{N-2} \\hat{u}^0_j \\overline{\\psi}_j(r), \n", + "\\label{_auto22} \\tag{24}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "5d6431c2", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "u^1(\\theta, r) = \\sum_{j=0}^{N-3}\\sum_{k=1}^{N/2} \\hat{u}^1_{kj} \\exp(\\imath k \\theta) \\psi_j(r) .\n", + "\\label{_auto23} \\tag{25}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "6188851a", + "metadata": { + "editable": true + }, + "source": [ + "As such the Helmholtz problem is split in two smaller problems.\n", + "The two problems read with the spectral Galerkin method:\n", + "\n", + "Find $u^0 \\in V_F^0 \\otimes V_U^N$ such that" + ] + }, + { + "cell_type": "markdown", + "id": "5d4eec5a", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\int_{\\Omega} (-\\nabla^2 u^0 + \\alpha u^0) v^0 w d\\sigma = \\int_{\\Omega} f v^0 w d\\sigma, \\quad \\forall \\, v^0 \\in V_F^0 \\otimes V_U^N.\n", + "\\label{eq:u0} \\tag{26}\n", + " \\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1283888c", + "metadata": { + "editable": true + }, + "source": [ + "Find $u^1 \\in V_F^1 \\otimes V_D^N$ such that" + ] + }, + { + "cell_type": "markdown", + "id": "c629c307", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\int_{\\Omega} (-\\nabla^2 u^1 + \\alpha u^1) v^1 w d\\sigma = \\int_{\\Omega} f v^1 w d\\sigma, \\quad \\forall \\, v^1 \\in V_F^1 \\otimes V_D^N.\n", + "\\label{eq:u1} \\tag{27}\n", + " \\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "9d10377e", + "metadata": { + "editable": true + }, + "source": [ + "Note that integration over the domain is done using\n", + "polar coordinates with an integral measure of $d\\sigma=rdrd\\theta$.\n", + "However, the integral in the radial direction needs to be mapped\n", + "to $t=2r/a-1$, where $t \\in [-1, 1]$, which suits the basis functions used,\n", + "see ([17](#eq:psi)). This leads to a measure of $0.5(t+1)adtd\\theta$.\n", + "Furthermore, the weight $w(t)$ will be unity for the Legendre basis and\n", + "$(1-t^2)^{-0.5}$ for the Chebyshev bases." + ] + }, + { + "cell_type": "markdown", + "id": "be46f19c", + "metadata": { + "editable": true + }, + "source": [ + "## Implementation\n", + "\n", + "\n", + "A complete implementation is found in the file [unitdisc_helmholtz.py](https://github.com/spectralDNS/shenfun/blob/master/demo/unitdisc_helmholtz.py).\n", + "Here we give a brief explanation for the implementation. Start by\n", + "importing all functionality from [shenfun](https://github.com/spectralDNS/shenfun)\n", + "and [sympy](https://sympy.org), where Sympy is required for handeling the\n", + "polar coordinates. Also, we choose to work with covariant\n", + "basis vectors." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1acc570e", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:39.272297Z", + "iopub.status.busy": "2024-05-24T12:36:39.272099Z", + "iopub.status.idle": "2024-05-24T12:36:39.851249Z", + "shell.execute_reply": "2024-05-24T12:36:39.849428Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from shenfun import *\n", + "import sympy as sp\n", + "config['basisvectors'] = 'covariant'\n", + "\n", + "# Define polar coordinates using angle along first axis and radius second\n", + "theta, r = psi = sp.symbols('x,y', real=True, positive=True)\n", + "rv = (r*sp.cos(theta), r*sp.sin(theta)) # Map to Cartesian (x, y)" + ] + }, + { + "cell_type": "markdown", + "id": "355e26ca", + "metadata": { + "editable": true + }, + "source": [ + "Note that Sympy symbols are both positive and real, $\\theta$ is\n", + "chosen to be along the first axis and $r$ second. This has to agree with\n", + "the next step, which is the creation of tensorproductspaces\n", + "$V_F^0 \\otimes V_U^N$ and $V_F^1 \\otimes V_D^N$. We use\n", + "`domain=(0, 1)` for the radial direction to get a unit disc, whereas\n", + "the default domain for the Fourier bases is already the\n", + "required $(0, 2\\pi)$." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3162ee49", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:39.855609Z", + "iopub.status.busy": "2024-05-24T12:36:39.855339Z", + "iopub.status.idle": "2024-05-24T12:36:40.098105Z", + "shell.execute_reply": "2024-05-24T12:36:40.097499Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "N = 32\n", + "F = FunctionSpace(N, 'F', dtype='d')\n", + "F0 = FunctionSpace(1, 'F', dtype='d')\n", + "L = FunctionSpace(N, 'L', bc=(0, 0), domain=(0, 1))\n", + "L0 = FunctionSpace(N, 'L', bc=(None, 0), domain=(0, 1))\n", + "T = TensorProductSpace(comm, (F, L), axes=(1, 0), coordinates=(psi, rv))\n", + "T0 = TensorProductSpace(MPI.COMM_SELF, (F0, L0), axes=(1, 0), coordinates=(psi, rv))" + ] + }, + { + "cell_type": "markdown", + "id": "6b19eba1", + "metadata": { + "editable": true + }, + "source": [ + "Note that since `F0` only has one component we could actually use\n", + "`L0` without creating `T0`. But the code turns out to be simpler\n", + "if we use `T0`, much because the additional $\\theta$-direction is\n", + "required for the polar coordinates to apply. Using one single basis\n", + "function for the $\\theta$ direction is as such a generic way to handle\n", + "polar 1D problems (i.e., problems that are only functions of the\n", + "radial direction, but still using polar coordinates).\n", + "Also note that `F` is created using the entire range of wavenumbers\n", + "even though it should not include wavenumber 0.\n", + "As such we need to make sure that the coefficient created for\n", + "$k=0$ (i.e., $\\hat{u}^1_{0,j}$) will be exactly zero.\n", + "Finally, note that\n", + "`T0` is not distributed with MPI, which is accomplished using\n", + "`MPI.COMM_SELF` instead of `comm` (which equals `MPI.COMM_WORLD`).\n", + "The purely radial problem ([26](#eq:u0)) is only solved on the one\n", + "processor with rank = 0.\n", + "\n", + "Polar coordinates are ensured by feeding `coordinates=(psi, rv)`\n", + "to [TensorProductSpace](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.tensorproductspace.TensorProductSpace). Operators like [div()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.operators.div)\n", + "[grad()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.operators.grad) and [curl()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.operators.curl) will now work on\n", + "items of [Function](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Function), [TestFunction](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.TestFunction) and\n", + "[TrialFunction](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.TrialFunction) using a polar coordinate system.\n", + "\n", + "To define the equations ([26](#eq:u0)) and ([27](#eq:u1)) we first declare\n", + "these test- and trialfunctions, and then use code that\n", + "is remarkably similar to the mathematics." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a9f683c4", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:40.100829Z", + "iopub.status.busy": "2024-05-24T12:36:40.100639Z", + "iopub.status.idle": "2024-05-24T12:36:40.241550Z", + "shell.execute_reply": "2024-05-24T12:36:40.240621Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "v = TestFunction(T)\n", + "u = TrialFunction(T)\n", + "v0 = TestFunction(T0)\n", + "u0 = TrialFunction(T0)\n", + "alpha = 1\n", + "\n", + "mats = inner(v, -div(grad(u))+alpha*u)\n", + "if comm.Get_rank() == 0:\n", + " mats0 = inner(v0, -div(grad(u0))+alpha*u0)" + ] + }, + { + "cell_type": "markdown", + "id": "ac2378ec", + "metadata": { + "editable": true + }, + "source": [ + "Here `mats` and `mats0` will contain several tensor product\n", + "matrices in the form of\n", + "[TPMatrix](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.matrixbase.TPMatrix). Since there is only one non-periodic direction\n", + "the matrices can be easily solved using [SolverGeneric1ND](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.la.SolverGeneric1ND).\n", + "But first we need to define the function $f(\\theta, r)$.\n", + "To this end we use sympy and the method of\n", + "manufactured solution to define a possible solution `ue`,\n", + "and then compute `f` exactly using exact differentiation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "56e8f67f", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:40.248259Z", + "iopub.status.busy": "2024-05-24T12:36:40.247680Z", + "iopub.status.idle": "2024-05-24T12:36:40.411690Z", + "shell.execute_reply": "2024-05-24T12:36:40.410356Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "\n", + "# Manufactured solution\n", + "ue = (r*(1-r))**2*sp.cos(8*theta)-0.1*(r-1)\n", + "#f = -ue.diff(r, 2) - (1/r)*ue.diff(r, 1) - (1/r**2)*ue.diff(theta, 2) + alpha*ue\n", + "f = (-div(grad(u))+alpha*u).tosympy(basis=ue, psi=psi)\n", + "\n", + "# Compute the right hand side on the quadrature mesh\n", + "fj = Array(T, buffer=f)\n", + "\n", + "# Take scalar product\n", + "f_hat = Function(T)\n", + "f_hat = inner(v, fj, output_array=f_hat)\n", + "if T.local_slice(True)[0].start == 0: # The processor that owns k=0\n", + " f_hat[0] = 0\n", + "\n", + "# For k=0 we solve only a 1D equation. Do the scalar product for Fourier\n", + "# coefficient 0 by hand (or sympy).\n", + "if comm.Get_rank() == 0:\n", + " f0_hat = Function(T0)\n", + " gt = sp.lambdify(r, sp.integrate(f, (theta, 0, 2*sp.pi))/2/sp.pi)(L0.mesh())\n", + " f0_hat = T0.scalar_product(gt, f0_hat)" + ] + }, + { + "cell_type": "markdown", + "id": "ebf9e1dc", + "metadata": { + "editable": true + }, + "source": [ + "Note that for $u^0$ we perform the interal in the $\\theta$ direction\n", + "exactly using sympy. This is necessary since one Fourier coefficient\n", + "is not sufficient to do this integral numerically. For the $u^1$\n", + "case we do the integral numerically as part of the [inner()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.inner.inner) product.\n", + "With the correct right hand side assembled we can solve the\n", + "linear system of equations" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "62ab606c", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:40.417767Z", + "iopub.status.busy": "2024-05-24T12:36:40.417652Z", + "iopub.status.idle": "2024-05-24T12:36:40.430418Z", + "shell.execute_reply": "2024-05-24T12:36:40.430025Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u_hat = Function(T)\n", + "Sol1 = la.SolverGeneric1ND(mats)\n", + "u_hat = Sol1(f_hat, u_hat)\n", + "\n", + "# case k = 0\n", + "u0_hat = Function(T0)\n", + "if comm.Get_rank() == 0:\n", + " Sol0 = la.SolverGeneric1ND(mats0)\n", + " u0_hat = Sol0(f0_hat, u0_hat)\n", + "comm.Bcast(u0_hat, root=0)" + ] + }, + { + "cell_type": "markdown", + "id": "8923490d", + "metadata": { + "editable": true + }, + "source": [ + "Having found the solution in spectral space all that is\n", + "left is to transform it back to real space." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "410b965c", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:40.435602Z", + "iopub.status.busy": "2024-05-24T12:36:40.434831Z", + "iopub.status.idle": "2024-05-24T12:36:40.439685Z", + "shell.execute_reply": "2024-05-24T12:36:40.438992Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "# Transform back to real space. Broadcast 1D solution\n", + "sl = T.local_slice(False)\n", + "uj = u_hat.backward() + u0_hat.backward()[:, sl[1]]" + ] + }, + { + "cell_type": "markdown", + "id": "4c5f0cee", + "metadata": { + "editable": true + }, + "source": [ + "## Postprocessing\n", + "The solution can now be compared with the exact solution\n", + "through" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e8feed8f", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:40.443008Z", + "iopub.status.busy": "2024-05-24T12:36:40.442858Z", + "iopub.status.idle": "2024-05-24T12:36:40.447524Z", + "shell.execute_reply": "2024-05-24T12:36:40.446000Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "uq = Array(T, buffer=ue)\n", + "print('Error =', np.linalg.norm(uj-uq))" + ] + }, + { + "cell_type": "markdown", + "id": "fe9d2c70", + "metadata": { + "editable": true + }, + "source": [ + "We can also get the gradient of the solution. For this we need\n", + "a space without boundary conditions, and a vector space" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "de99b93f", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:40.452089Z", + "iopub.status.busy": "2024-05-24T12:36:40.451919Z", + "iopub.status.idle": "2024-05-24T12:36:40.507857Z", + "shell.execute_reply": "2024-05-24T12:36:40.507238Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "TT = T.get_orthogonal()\n", + "V = VectorSpace(TT)" + ] + }, + { + "cell_type": "markdown", + "id": "f090f9c5", + "metadata": { + "editable": true + }, + "source": [ + "Notice that we do not have the solution in one single space\n", + "in spectral space, since it is a combination of `u_hat` and\n", + "`u0_hat`. For this reason we first transform the solution from\n", + "real space `uj` to the new orthogonal space `TT`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cf17f776", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:40.513274Z", + "iopub.status.busy": "2024-05-24T12:36:40.512761Z", + "iopub.status.idle": "2024-05-24T12:36:40.519993Z", + "shell.execute_reply": "2024-05-24T12:36:40.519353Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "ua = Array(TT, buffer=uj)\n", + "uh = ua.forward()" + ] + }, + { + "cell_type": "markdown", + "id": "355a95e5", + "metadata": { + "editable": true + }, + "source": [ + "With the solution as a [Function](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Function) we can simply project\n", + "the gradient to `V`" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "79ac588b", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:40.523056Z", + "iopub.status.busy": "2024-05-24T12:36:40.522966Z", + "iopub.status.idle": "2024-05-24T12:36:40.579605Z", + "shell.execute_reply": "2024-05-24T12:36:40.579234Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "dv = project(grad(uh), V)\n", + "du = dv.backward()" + ] + }, + { + "cell_type": "markdown", + "id": "24534131", + "metadata": { + "editable": true + }, + "source": [ + "Note that the gradient `du` now contains the contravariant components\n", + "of the covariant basis vector `b`. The basis vector `b` is not normalized\n", + "(it's length is not unity), because we have set\n", + "`config['basisvectors']='covariant'`. The basisvectors can\n", + "be seen as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9d570561", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:40.583233Z", + "iopub.status.busy": "2024-05-24T12:36:40.582564Z", + "iopub.status.idle": "2024-05-24T12:36:40.589089Z", + "shell.execute_reply": "2024-05-24T12:36:40.586422Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from IPython.display import Math\n", + "Math(T.coors.latex_basis_vectors(symbol_names={theta: '\\\\theta', r: 'r'}))" + ] + }, + { + "cell_type": "markdown", + "id": "367c0496", + "metadata": { + "editable": true + }, + "source": [ + "and we see that they are given in terms of the Cartesian unit vectors.\n", + "The gradient we have computed is (and yes, it should be $r^2$ because we\n", + "do not have unit vectors)" + ] + }, + { + "cell_type": "markdown", + "id": "4a3b34ad", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\nabla u = \\underbrace{\\frac{1}{r^2}\\frac{\\partial u}{\\partial \\theta}}_{du[0]}\\mathbf{b}_{\\theta} + \\underbrace{\\frac{\\partial u}{\\partial r}}_{du[1]} \\mathbf{b}_{r}\n", + "\\label{eq:gradu} \\tag{28}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "2a34bbe0", + "metadata": { + "editable": true + }, + "source": [ + "Now it makes sense to plot the solution and its gradient in Cartesian\n", + "instead of computational coordinates. To this end we need to\n", + "project the gradient to a Cartesian basis" + ] + }, + { + "cell_type": "markdown", + "id": "57f82ae3", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{align*}\n", + "\\frac{\\partial u}{\\partial x} &= \\nabla u \\cdot \\mathbf{i},\\\\ \n", + "\\frac{\\partial u}{\\partial y} &= \\nabla u \\cdot \\mathbf{j}.\n", + "\\end{align*}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "83087c4c", + "metadata": { + "editable": true + }, + "source": [ + "We compute the Cartesian gradient by assembling ([28](#eq:gradu))\n", + "on the computational grid" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9a44ca48", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:40.593424Z", + "iopub.status.busy": "2024-05-24T12:36:40.593172Z", + "iopub.status.idle": "2024-05-24T12:36:40.599643Z", + "shell.execute_reply": "2024-05-24T12:36:40.599014Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "ui, vi = TT.local_mesh(True)\n", + "b = T.coors.get_covariant_basis()\n", + "bij = np.zeros((2, 2, N, N))\n", + "for i in (0, 1):\n", + " for j in (0, 1):\n", + " bij[i, j] = sp.lambdify(psi, b[i, j])(ui, vi)\n", + "gradu = du[0]*bij[0] + du[1]*bij[1]" + ] + }, + { + "cell_type": "markdown", + "id": "35993847", + "metadata": { + "editable": true + }, + "source": [ + "Because of the way the vectors are stored, `gradu[0]` will now\n", + "contain $\\nabla u \\cdot \\mathbf{i}$ and\n", + "`gradu[1]` will contain $\\nabla u \\cdot \\mathbf{j}$.\n", + "\n", + "To validate the gradient we compute the $L^2$ error norm" + ] + }, + { + "cell_type": "markdown", + "id": "1135b831", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\sqrt{\\int_{\\Omega} |\\nabla u - \\nabla u_e|^2 d\\sigma}\n", + " = \\sqrt{\\int_{\\theta=0}^{2\\pi}\\int_{r=0}^{1} \\left(\\left(\\frac{1}{r^2}\\frac{\\partial u-u_e}{\\partial \\theta}\\right)^2\\mathbf{b}_{\\theta}\\cdot \\mathbf{b}_{\\theta} + \\left(\\frac{\\partial u-u_e}{\\partial r}\\right)^2\\mathbf{b}_{r}\\cdot \\mathbf{b}_{r} \\right)rd\\theta dr}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "3ac72ba9", + "metadata": { + "editable": true + }, + "source": [ + "implemented as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7b048206", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:40.603085Z", + "iopub.status.busy": "2024-05-24T12:36:40.602998Z", + "iopub.status.idle": "2024-05-24T12:36:40.643923Z", + "shell.execute_reply": "2024-05-24T12:36:40.643534Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "gradue = Array(V, buffer=grad(u).tosympy(basis=ue, psi=psi))\n", + "gij = T.coors.get_covariant_metric_tensor()\n", + "ui, vi = TT.local_mesh(True, kind='uniform')\n", + "# Evaluate metric on computational mesh\n", + "gij[0, 0] = sp.lambdify(psi, gij[0, 0])(ui, vi)\n", + "# Compute L2 error\n", + "errorg = inner(1, (du[0]-gradue[0])**2*gij[0, 0]+ (du[1]-gradue[1])**2*gij[1, 1])\n", + "print('Error gradient', np.sqrt(float(errorg)))" + ] + }, + { + "cell_type": "markdown", + "id": "1d940058", + "metadata": { + "editable": true + }, + "source": [ + "We now refine the solution to make it look better,\n", + "and plot on the unit disc." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "70bfca20", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:40.648719Z", + "iopub.status.busy": "2024-05-24T12:36:40.648563Z", + "iopub.status.idle": "2024-05-24T12:36:41.468520Z", + "shell.execute_reply": "2024-05-24T12:36:41.467794Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "u_hat2 = u_hat.refine([N*3, N*3])\n", + "u0_hat2 = u0_hat.refine([1, N*3])\n", + "sl = u_hat2.function_space().local_slice(False)\n", + "ur = u_hat2.backward() + u0_hat2.backward()[:, sl[1]]\n", + "\n", + "# Wrap periodic plot around since it looks nicer\n", + "xx, yy = u_hat2.function_space().local_cartesian_mesh()\n", + "xp = np.vstack([xx, xx[0]])\n", + "yp = np.vstack([yy, yy[0]])\n", + "up = np.vstack([ur, ur[0]])\n", + "# For vector no need to wrap around and no need to refine:\n", + "xi, yi = TT.local_cartesian_mesh()\n", + "\n", + "# plot\n", + "import matplotlib.pyplot as plt\n", + "plt.figure()\n", + "plt.contourf(xp, yp, up)\n", + "plt.quiver(xi, yi, gradu[0], gradu[1], scale=40, pivot='mid', color='white')\n", + "plt.colorbar()\n", + "plt.title('Helmholtz - unitdisc')\n", + "plt.xticks([])\n", + "plt.yticks([])\n", + "plt.axis('off')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "709ed573", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "1. **J. Shen**. Efficient Spectral-Galerkin Methods III: Polar and Cylindrical Geometries, *SIAM Journal on Scientific Computing*, 18(6), pp. 1583-1604, [doi: 10.1137/S1064827595295301](https://dx.doi.org/10.1137/S1064827595295301), 1997." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/RayleighBenard/rayleighbenard.ipynb b/docs/demos/RayleighBenard/rayleighbenard.ipynb new file mode 100644 index 00000000..cfb0150a --- /dev/null +++ b/docs/demos/RayleighBenard/rayleighbenard.ipynb @@ -0,0 +1,1709 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "7f6234eb", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - Rayleigh Benard\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **November 21, 2019**\n", + "\n", + "**Summary.** Rayleigh-Benard convection arise\n", + "due to temperature gradients in a fluid. The governing equations are\n", + "Navier-Stokes coupled (through buoyancy) with an additional temperature\n", + "equation derived from the first law of thermodynamics, using a linear\n", + "correlation between density and temperature.\n", + "\n", + "This is a demonstration of how the Python module [shenfun](https://github.com/spectralDNS/shenfun) can be used to solve for\n", + "these Rayleigh-Benard cells in a 2D channel with two walls of\n", + "different temperature in one direction, and periodicity in the other direction.\n", + "The solver described runs with MPI\n", + "without any further considerations required from the user.\n", + "Note that there is also a more physically realistic [3D solver](https://github.com/spectralDNS/shenfun/blob/master/demo/RayleighBenard.py).\n", + "The solver described in this demo has been implemented in a class in the\n", + "[RayleighBenard2D.py](https://github.com/spectralDNS/shenfun/blob/master/demo/RayleighBenard2D.py)\n", + "module in the demo folder of shenfun. Below is an example solution, which has been run at a very high\n", + "Rayleigh number (*Ra*).\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "

Figure 1: Temperature fluctuations in the Rayleigh Benard flow. The top and bottom walls are kept at different temperatures and this sets up the Rayleigh-Benard convection. The simulation is run at Ra =1,000,000, Pr =0.7 with 256 and 512 quadrature points in x and y-directions, respectively.

\n", + "" + ] + }, + { + "cell_type": "markdown", + "id": "177a6e73", + "metadata": { + "editable": true + }, + "source": [ + "## The Rayleigh Bénard equations\n", + "\n", + "\n", + "The governing equations solved in domain $\\Omega=(-1, 1)\\times [0, 2\\pi)$ are" + ] + }, + { + "cell_type": "markdown", + "id": "ad1449b2", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\frac{\\partial \\boldsymbol{u}}{\\partial t} + (\\boldsymbol{u} \\cdot \\nabla) \\boldsymbol{u} = - \\nabla p + \\sqrt{\\frac{Pr}{Ra}} \\nabla^2 \\boldsymbol{u} + T \\boldsymbol{i}, \\label{eq:momentum} \\tag{1}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "59b6c4c7", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " \\frac{\\partial T}{\\partial t} +\\boldsymbol{u} \\cdot \\nabla T = \\frac{1}{\\sqrt{RaPr}} \\nabla^2 T, \\label{eq:T} \\tag{2}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "5d7e6701", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " \\nabla \\cdot \\boldsymbol{u} = 0, \\label{eq:div} \\tag{3}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "2a91fb26", + "metadata": { + "editable": true + }, + "source": [ + "where $\\boldsymbol{u}(x, y, t) (= u\\boldsymbol{i} + v\\boldsymbol{j})$ is the velocity vector, $p(x, y, t)$ is pressure, $T(x, y, t)$ is the temperature, and $\\boldsymbol{i}$ and\n", + "$\\boldsymbol{j}$ are the unity vectors for the $x$ and $y$-directions, respectively.\n", + "\n", + "The equations are complemented with boundary conditions $\\boldsymbol{u}(\\pm 1, y, t) = (0, 0), \\boldsymbol{u}(x, 2 \\pi, t) = \\boldsymbol{u}(x, 0, t), T(-1, y, t) = 1, T(1, y, t) = 0, T(x, 2 \\pi, t) = T(x, 0, t)$.\n", + "Note that these equations have been non-dimensionalized according to [[pandey18]](#pandey18), using dimensionless\n", + "Rayleigh number $Ra=g \\alpha \\Delta T h^3/(\\nu \\kappa)$ and Prandtl number $Pr=\\nu/\\kappa$. Here\n", + "$g \\boldsymbol{i}$ is the vector accelleration of gravity, $\\Delta T$ is the temperature difference between\n", + "the top and bottom walls, $h$ is the hight of the channel in $x$-direction, $\\nu$ is the\n", + "dynamic viscosity coefficient, $\\kappa$ is the heat transfer coefficient and $\\alpha$ is the\n", + "thermal expansion coefficient. Note that the\n", + "governing equations have been non-dimensionalized using the free-fall velocityscale\n", + "$U=\\sqrt{g \\alpha \\Delta T h}$. See [[pandey18]](#pandey18) for more details.\n", + "\n", + "The governing equations contain a non-trivial coupling between velocity, pressure and temperature.\n", + "This coupling can be simplified by eliminating the pressure from the equation for the wall-normal velocity\n", + "component $u$. We accomplish this by taking the Laplace of the momentum equation in wall normal\n", + "direction, using the pressure from the divergence of the momentum equation\n", + "$\\nabla^2 p = -\\nabla \\cdot \\boldsymbol{H}+\\partial T/\\partial x$, where\n", + "$\\boldsymbol{H} = (H_x, H_y) = (\\boldsymbol{u} \\cdot \\nabla) \\boldsymbol{u}$" + ] + }, + { + "cell_type": "markdown", + "id": "f838dca0", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\frac{\\partial \\nabla^2 {u}}{\\partial t} = \\frac{\\partial^2 H_y}{\\partial x \\partial y} - \\frac{\\partial^2 H_x}{\\partial y\\partial y} + \\sqrt{\\frac{Pr}{Ra}} \\nabla^4 {u} + \\frac{\\partial^2 T}{\\partial y^2} . \\label{eq:rb:u} \\tag{4}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "ca6ea1f7", + "metadata": { + "editable": true + }, + "source": [ + "This equation is solved with $u(\\pm 1,y,t) = \\partial u/\\partial x(\\pm 1,y,t) = 0$, where the latter follows from the\n", + "divergence constraint. In summary, we now seem to have the following equations to solve:" + ] + }, + { + "cell_type": "markdown", + "id": "0afef1df", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\frac{\\partial \\nabla^2 {u}}{\\partial t} = \\frac{\\partial^2 H_y}{\\partial x \\partial y} - \\frac{\\partial^2 H_x}{\\partial y\\partial y} + \\sqrt{\\frac{Pr}{Ra}} \\nabla^4 {u} + \\frac{\\partial^2 T}{\\partial y^2}, \\label{eq:rb:u2} \\tag{5}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "3d483309", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " \\frac{\\partial v}{\\partial t} + H_y = - \\frac{\\partial p}{\\partial y} + \\sqrt{\\frac{Pr}{Ra}} \\nabla^2 v, \\label{eq:v} \\tag{6}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "9f1801e4", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " \\frac{\\partial T}{\\partial t} +\\boldsymbol{u} \\cdot \\nabla T = \\frac{1}{\\sqrt{RaPr}} \\nabla^2 T, \\label{eq:T2} \\tag{7}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "2d815654", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " \\nabla \\cdot \\boldsymbol{u} = 0 \\label{eq:div2} \\tag{8}.\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "87c1dd49", + "metadata": { + "editable": true + }, + "source": [ + "However, we note that Eqs. ([5](#eq:rb:u2)) and ([7](#eq:T2)) and ([8](#eq:div2)) do not depend on pressure, and,\n", + "apparently, on each time step we can solve ([5](#eq:rb:u2)) for $u$, then ([8](#eq:div2)) for $v$ and finally ([7](#eq:T2)) for $T$.\n", + "So what do we need ([6](#eq:v)) for? It appears to have become redundant from the elimination of the\n", + "pressure from Eq. ([5](#eq:rb:u2)). It turns out that this is actually almost completely true, but\n", + "([5](#eq:rb:u2)), ([7](#eq:T2)) and ([8](#eq:div2)) can only provide closure for all but one of the\n", + "Fourier coefficients. To see this it is necessary to introduce some discretization and basis functions\n", + "that will be used to solve the problem. To this end we use $P_N$, which is the set of all real polynomials\n", + "of degree less than or equal to N and introduce the following finite-dimensional approximation spaces" + ] + }, + { + "cell_type": "markdown", + "id": "469f8896", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " V_N^B(x) = \\{v \\in P_N | v(\\pm 1) = v´(\\pm 1) = 0\\}, \\label{eq:VB} \\tag{9} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "c8f804cb", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " V_N^D(x) = \\{v \\in P_N | v(\\pm 1) = 0\\}, \\label{eq:VD} \\tag{10} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f3d0a11f", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " V_N^T(x) = \\{v \\in P_N | v(-1) = 0, v(1) = 1\\}, \\label{eq:VT} \\tag{11} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "eae8e9d1", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " V_N^W(x) = \\{v \\in P_N\\}, \\label{eq:VW} \\tag{12} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "7be2b88e", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " V_M^F(y) = \\{\\exp(\\imath l y) | l \\in [-M/2, -M/2+1, \\ldots M/2-1]\\}. \\label{eq:VF} \\tag{13}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "a5e83417", + "metadata": { + "editable": true + }, + "source": [ + "Here $\\text{dim}(V_N^B) = N-4, \\text{dim}(V_N^D) = \\text{dim}(V_N^W) = \\text{dim}(V_N^T) = N-2$\n", + "and $\\text{dim}(V_M^F)=M$. We note that\n", + "$V_N^B, V_N^D, V_N^W$ and $V_N^T$ can be used to approximate $u, v, T$ and $p$, respectively, in the $x$-direction.\n", + "Also note that for $V_M^F$ it is assumed that $M$ is an even number.\n", + "\n", + "We can now choose basis functions for the spaces, using Shen's composite bases for either Legendre or\n", + "Chebyshev polynomials. For the Fourier space the basis functions are already given. We leave the actual choice\n", + "of basis as an implementation option for later. For now we use $\\phi^B(x), \\phi^D(x), \\phi^W$ and $\\phi^T(x)$\n", + "as common notation for basis functions in spaces $V_N^B, V_N^D, V_N^W$ and $V_N^T$, respectively.\n", + "\n", + "To get the required approximation spaces for the entire domain we use tensor products of the\n", + "one-dimensional spaces in ([9](#eq:VB))-([13](#eq:VF))" + ] + }, + { + "cell_type": "markdown", + "id": "38df0fa1", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " W_{BF} = V_N^B \\otimes V_M^F, \\label{eq:WBF} \\tag{14} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "ba2319bf", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " W_{DF} = V_N^D \\otimes V_M^F, \\label{eq:WDF} \\tag{15} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "97c4f4bc", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " W_{TF} = V_N^T \\otimes V_M^F, \\label{eq:WTF} \\tag{16} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "25acfc6e", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " W_{WF} = V_N^W \\otimes V_M^F. \\label{eq:WWF} \\tag{17}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "827f02da", + "metadata": { + "editable": true + }, + "source": [ + "Space $W_{BF}$ has 2D tensor product basis functions $\\phi_k^B(x) \\exp (\\imath l y)$ and\n", + "similar for the others. All in all\n", + "we get the following approximations for the unknowns" + ] + }, + { + "cell_type": "markdown", + "id": "fc1fc414", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " u_N(x, y, t) = \\sum_{k \\in \\boldsymbol{k}_B} \\sum_{l \\in \\boldsymbol{l}} \\hat{u}_{kl}(t) \\phi_k^B(x) \\exp(\\imath l y), \n", + "\\label{_auto1} \\tag{18}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "b3e1db16", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " v_N(x, y, t) = \\sum_{k \\in \\boldsymbol{k}_D} \\sum_{l \\in \\boldsymbol{l}} \\hat{v}_{kl}(t) \\phi_k^D(x) \\exp(\\imath l y), \n", + "\\label{_auto2} \\tag{19}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "bfc89552", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " p_N(x, y, t) = \\sum_{k \\in \\boldsymbol{k}_W} \\sum_{l \\in \\boldsymbol{l}} \\hat{p}_{kl}(t) \\phi_k^W(x) \\exp(\\imath l y), \n", + "\\label{_auto3} \\tag{20}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "d37af4a7", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " T_N(x, y, t) = \\sum_{k \\in \\boldsymbol{k}_T} \\sum_{l \\in \\boldsymbol{l}} \\hat{T}_{kl}(t) \\phi_k^T(x) \\exp(\\imath l y),\n", + "\\label{_auto4} \\tag{21}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "3d0a241c", + "metadata": { + "editable": true + }, + "source": [ + "where $\\boldsymbol{k}_{x} = \\{0, 1, \\ldots \\text{dim}(V_N^x)-1\\}, \\, \\text{for} \\, x\\in(B, D, W, T)$\n", + "and $\\boldsymbol{l} = \\{-M/2, -M/2+1, \\ldots, M/2-1\\}$.\n", + "Note that since the problem is defined in real space we will have Hermitian symmetry. This means\n", + "that $\\hat{u}_{k, l} = \\overline{\\hat{u}}_{k, -l}$, with an overbar being a complex conjugate,\n", + "and similar for $\\hat{v}_{kl}, \\hat{p}_{kl}$ and\n", + "$\\hat{T}_{kl}$. For this reason we can get away with\n", + "solving for only the positive $l$'s, as long as we remember that the sum in the end goes over both positive\n", + "and negative $l's$. This is actually automatically taken care of by the FFT provider and is\n", + "not much of an additional complexity in the implementation. So from now on $\\boldsymbol{l} = \\{0, 1, \\ldots, M/2\\}$.\n", + "\n", + "We can now take a look at why Eq. ([6](#eq:v)) is needed. If we first solve ([5](#eq:rb:u2)) for\n", + "$\\hat{u}_{kl}(t), (k, l) \\in \\boldsymbol{k}_B \\times \\boldsymbol{l}$, then we can use ([8](#eq:div2)) to\n", + "solve for $\\hat{v}_{kl}(t)$. But here there is a problem. We can see this by creating the variational\n", + "form required to solve ([8](#eq:div2)) by the spectral Galerkin method. To this end make $v=v_N$ in ([8](#eq:div2))\n", + "a trial function, use $u=u_N$ a known function and take the weighted inner product over the\n", + "domain using test function $q \\in W_{DF}$" + ] + }, + { + "cell_type": "markdown", + "id": "4b48d850", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\left < \\frac{\\partial u_N}{\\partial x} + \\frac{\\partial v_N}{\\partial y}, q \\right > _w = 0.\n", + "\\label{_auto5} \\tag{22}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "6505d4f0", + "metadata": { + "editable": true + }, + "source": [ + "Here we are using the inner product notation" + ] + }, + { + "cell_type": "markdown", + "id": "9150f8b5", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\left < a, b \\right > _w = \\int_{-1}^1 \\int_0^{2\\pi} a \\overline{b} dx_wdy_w \\left(\\approx \\sum_{i}\\sum_{j} a(x_i, y_j) \\overline{b}(x_i, y_j) w(x_i) w(y_j)\\right),\n", + "\\label{_auto6} \\tag{23}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "d98142bf", + "metadata": { + "editable": true + }, + "source": [ + "where the exact form of the\n", + "weighted scalar product depends on the chosen basis; Legendre has $dx_w=dx$, Chebyshev\n", + "$dx_w = dx/\\sqrt{1-x^2}$ and Fourier $dy_w=dy/2/\\pi$. The bases also have associated quadrature weights\n", + "$\\{w(x_i) \\}_{i=0}^{N-1}$ and $\\{w(y_j)\\}_{j=0}^{M-1}$ that are used to approximate the integrals.\n", + "\n", + "Inserting now for the known $u_N$, the unknown $v_N$, and $q=\\phi_m^D(x) \\exp(\\imath n y)$ the\n", + "continuity equation becomes" + ] + }, + { + "cell_type": "markdown", + "id": "2ac1d624", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\int_{-1}^1 \\int_{0}^{2\\pi} \\frac{\\partial}{\\partial x} \\left(\\sum_{k \\in \\boldsymbol{k}_B} \\sum_{l \\in \\boldsymbol{l}} \\hat{u}_{kl}(t) \\phi_k^B(x) \\exp(\\imath l y) \\right) \\phi_m^D(x) \\exp(-\\imath n y) dx_w dy_w + \\\\ \n", + " \\int_{-1}^1 \\int_{0}^{2\\pi} \\frac{\\partial}{\\partial y} \\left(\\sum_{k \\in \\boldsymbol{k}_D} \\sum_{l \\in \\boldsymbol{l}} \\hat{v}_{kl}(t) \\phi_k^D(x) \\exp(\\imath l y) \\right) \\phi_m^D(x) \\exp(-\\imath n y) dx_w dy_w = 0.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1a8e691c", + "metadata": { + "editable": true + }, + "source": [ + "The $x$ and $y$ domains are separable, so we can rewrite as" + ] + }, + { + "cell_type": "markdown", + "id": "1cf1221d", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\sum_{k \\in \\boldsymbol{k}_B} \\sum_{l \\in \\boldsymbol{l}} \\int_{-1}^1 \\frac{\\partial \\phi_k^B(x)}{\\partial x} \\phi_m^D(x) dx_w \\int_{0}^{2\\pi} \\exp(\\imath l y) \\exp(-\\imath n y) dy_w \\hat{u}_{kl} + \\\\ \n", + " \\sum_{k \\in \\boldsymbol{k}_D} \\sum_{l \\in \\boldsymbol{l}} \\int_{-1}^1 \\phi_k^D(x) \\phi_m^D(x) dx_w \\int_{0}^{2\\pi} \\frac{\\partial \\exp(\\imath l y)}{\\partial y} \\exp(-\\imath n y) dy_w \\hat{v}_{kl} = 0.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "4df1a6eb", + "metadata": { + "editable": true + }, + "source": [ + "Now perform some exact manipulations in the Fourier direction and introduce the\n", + "1D inner product notation for the $x$-direction" + ] + }, + { + "cell_type": "markdown", + "id": "a3eb4492", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\left(a, b\\right)_w = \\int_{-1}^1 a(x) b(x) dx_w \\left(\\approx \\sum_{j = 0}^{N-1} a(x_j)b(x_j) w(x_j)\\right).\n", + "\\label{_auto7} \\tag{24}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1b5d5113", + "metadata": { + "editable": true + }, + "source": [ + "By also simplifying the notation using summation of repeated indices,\n", + "we get the following equation" + ] + }, + { + "cell_type": "markdown", + "id": "26b6a18f", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\delta_{ln} \\left(\\frac{\\partial \\phi_k^B}{\\partial x}, \\phi_m^D \\right)_w \\hat{u}_{kl}\n", + " + \\imath l \\delta_{ln} \\left(\\phi_k^D, \\phi_m^D \\right)_w \\hat{v}_{kl} = 0.\n", + "\\label{_auto8} \\tag{25}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e486aa6d", + "metadata": { + "editable": true + }, + "source": [ + "Now $l$ must equal $n$ and we can simplify some more" + ] + }, + { + "cell_type": "markdown", + "id": "f4c027ba", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\left(\\frac{\\partial \\phi_k^B}{\\partial x}, \\phi_m^D \\right)_w \\hat{u}_{kl}\n", + " + \\imath l \\left(\\phi_k^D, \\phi_m^D \\right)_w \\hat{v}_{kl} = 0. \\label{eq:div3} \\tag{26}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "fb8eb364", + "metadata": { + "editable": true + }, + "source": [ + "We see that this equation can be solved for\n", + "$\\hat{v}_{kl} \\text{ for } (k, l) \\in \\boldsymbol{k}_D \\times [1, 2, \\ldots, M/2]$, but try with\n", + "$l=0$ and you hit division by zero, which obviously is not allowed. And this is the reason\n", + "why Eq. ([6](#eq:v)) is still needed, to solve for $\\hat{v}_{k,0}$! Fortunately,\n", + "since $\\exp(\\imath 0 y) = 1$, the pressure derivative $\\frac{\\partial p}{\\partial y} = 0$,\n", + "and as such the pressure is still not required. When used only for\n", + "Fourier coefficient 0, Eq. ([6](#eq:v)) becomes" + ] + }, + { + "cell_type": "markdown", + "id": "e1966ab1", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\frac{\\partial v}{\\partial t} + N_y = \\sqrt{\\frac{Pr}{Ra}} \\frac{\\partial^2 v}{\\partial x^2}. \\label{eq:vx} \\tag{27}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "69a9f741", + "metadata": { + "editable": true + }, + "source": [ + "There is still one more revelation to be made from Eq. ([26](#eq:div3)). When $l=0$ we get" + ] + }, + { + "cell_type": "markdown", + "id": "440cd498", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\left(\\frac{\\partial \\phi_k^B}{\\partial x}, \\phi_m^D \\right)_w \\hat{u}_{k,0} = 0,\n", + "\\label{_auto9} \\tag{28}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "200607d9", + "metadata": { + "editable": true + }, + "source": [ + "which is trivially satisfied if $\\hat{u}_{k,0}=0$ for $k\\in\\boldsymbol{k}_B$. Bottom line is\n", + "that we only need to solve Eq. ([5](#eq:rb:u2)) for $l \\in \\boldsymbol{l}/\\{0\\}$, whereas we can use\n", + "directly $\\hat{u}_{k,0}=0 \\text{ for } k \\in \\boldsymbol{k}_B$.\n", + "\n", + "To sum up, with the solution known at $t = t - \\Delta t$, we solve\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
Equation For unknown With indices
(5) $\\hat{u}_{kl}(t)$ $(k, l) \\in \\boldsymbol{k}_B \\times \\boldsymbol{l}/\\{0\\}$
(8) $\\hat{v}_{kl}(t)$ $(k, l) \\in \\boldsymbol{k}_D \\times \\boldsymbol{l}/\\{0\\}$
(27) $\\hat{v}_{kl}(t)$ $(k, l) \\in \\boldsymbol{k}_D \\times \\{0\\}$
(7) $\\hat{T}_{kl}(t)$ $(k, l) \\in \\boldsymbol{k}_T \\times \\boldsymbol{l}$
" + ] + }, + { + "cell_type": "markdown", + "id": "b943e520", + "metadata": { + "editable": true + }, + "source": [ + "## Temporal discretization\n", + "\n", + "The governing equations are integrated in time using any one of the time steppers available in\n", + "shenfun. There are several possible IMEX Runge Kutta methods, see [integrators.py](https://github.com/spectralDNS/shenfun/blob/master/shenfun/utilities/integrators.py).\n", + "The time steppers are used for any generic equation" + ] + }, + { + "cell_type": "markdown", + "id": "b6237baa", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\frac{\\partial \\psi}{\\partial t} = \\mathcal{N} + \\mathcal{L}\\psi \\label{eq:genericpsi} \\tag{29},\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f42997a8", + "metadata": { + "editable": true + }, + "source": [ + "where $\\mathcal{N}$ and $\\mathcal{L}$ represents the nonlinear and linear contributions, respectively.\n", + "The timesteppers are provided with $\\psi, \\mathcal{L}$ and $\\mathcal{N}$, and possibly some tailored\n", + "linear algebra solvers, and solvers are then further assembled under the hood.\n", + "\n", + "All the timesteppers split one time step into one or several stages.\n", + "The classes [IMEXRK222](https://shenfun.readthedocs.io/en/latest/shenfun.utilities.html#shenfun.utilities.integrators.IMEXRK222), [IMEXRK3](https://shenfun.readthedocs.io/en/latest/shenfun.utilities.html#shenfun.utilities.integrators.IMEXRK3) and [IMEXRK443](https://shenfun.readthedocs.io/en/latest/shenfun.utilities.html#shenfun.utilities.integrators.IMEXRK443)\n", + "have 2, 3 and 4 steps, respectively, and the cost is proportional." + ] + }, + { + "cell_type": "markdown", + "id": "1b1d02c6", + "metadata": { + "editable": true + }, + "source": [ + "## Implementation\n", + "\n", + "To get started we need instances of the approximation spaces discussed in\n", + "Eqs. ([9](#eq:VB)) - ([17](#eq:WWF)). When the spaces are created we also need\n", + "to specify the family and the dimension of each space. Here we simply\n", + "choose Chebyshev and Fourier with 100 and 256 quadrature points in $x$ and\n", + "$y$-directions, respectively. We could replace 'Chebyshev' by 'Legendre',\n", + "but the former is known to be faster due to the existence of fast transforms." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4917abcd", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:08.111092Z", + "iopub.status.busy": "2024-05-24T12:37:08.110785Z", + "iopub.status.idle": "2024-05-24T12:37:08.792581Z", + "shell.execute_reply": "2024-05-24T12:37:08.791935Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from shenfun import *\n", + "\n", + "N, M = 64, 128\n", + "family = 'Chebyshev'\n", + "VB = FunctionSpace(N, family, bc=(0, 0, 0, 0))\n", + "VD = FunctionSpace(N, family, bc=(0, 0))\n", + "VW = FunctionSpace(N, family)\n", + "VT = FunctionSpace(N, family, bc=(1, 0))\n", + "VF = FunctionSpace(M, 'F', dtype='d')" + ] + }, + { + "cell_type": "markdown", + "id": "b7122e43", + "metadata": { + "editable": true + }, + "source": [ + "And then we create tensor product spaces by combining these bases (like in Eqs. ([14](#eq:WBF))-([17](#eq:WWF)))." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "32a0a207", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:08.799525Z", + "iopub.status.busy": "2024-05-24T12:37:08.797537Z", + "iopub.status.idle": "2024-05-24T12:37:09.189267Z", + "shell.execute_reply": "2024-05-24T12:37:09.188578Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "W_BF = TensorProductSpace(comm, (VB, VF)) # Wall-normal velocity\n", + "W_DF = TensorProductSpace(comm, (VD, VF)) # Streamwise velocity\n", + "W_WF = TensorProductSpace(comm, (VW, VF)) # No bc\n", + "W_TF = TensorProductSpace(comm, (VT, VF)) # Temperature\n", + "BD = VectorSpace([W_BF, W_DF]) # Velocity vector\n", + "DD = VectorSpace([W_DF, W_DF]) # Convection vector\n", + "W_DFp = W_DF.get_dealiased(padding_factor=1.5)\n", + "BDp = BD.get_dealiased(padding_factor=1.5)" + ] + }, + { + "cell_type": "markdown", + "id": "3e9e1f8d", + "metadata": { + "editable": true + }, + "source": [ + "Here the `VectorSpae` create mixed tensor product spaces by the\n", + "Cartesian products `BD = W_BF` $\\times$ `W_DF` and `DD = W_DF` $\\times$ `W_DF`.\n", + "These mixed space will be used to hold the velocity and convection vectors,\n", + "but we will not solve the equations in a coupled manner and continue in the\n", + "segregated approach outlined above.\n", + "\n", + "We also need containers for the computed solutions. These are created as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "be8b51ce", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:09.191855Z", + "iopub.status.busy": "2024-05-24T12:37:09.191720Z", + "iopub.status.idle": "2024-05-24T12:37:09.194654Z", + "shell.execute_reply": "2024-05-24T12:37:09.193903Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u_ = Function(BD) # Velocity vector, two components\n", + "T_ = Function(W_TF) # Temperature\n", + "H_ = Function(DD) # Convection vector\n", + "uT_ = Function(BD) # u times T" + ] + }, + { + "cell_type": "markdown", + "id": "4c90842d", + "metadata": { + "editable": true + }, + "source": [ + "### Wall-normal velocity equation\n", + "\n", + "We implement Eq. ([5](#eq:rb:u2)) using a generic time stepper.\n", + "To this end we first need to declare some test- and trial functions, as well as\n", + "some model constants and the length of the time step. We store the\n", + "PDE time stepper in a dictionary called `pdes` just for convenience:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b3ee1794", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:09.198222Z", + "iopub.status.busy": "2024-05-24T12:37:09.197359Z", + "iopub.status.idle": "2024-05-24T12:37:09.235664Z", + "shell.execute_reply": "2024-05-24T12:37:09.233971Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "\n", + "# Specify viscosity and time step size using dimensionless Ra and Pr\n", + "Ra = 1000000\n", + "Pr = 0.7\n", + "nu = np.sqrt(Pr/Ra)\n", + "kappa = 1./np.sqrt(Pr*Ra)\n", + "dt = 0.025\n", + "\n", + "# Choose timestepper and create instance of class\n", + "\n", + "PDE = IMEXRK3 # IMEX222, IMEXRK443\n", + "\n", + "v = TestFunction(W_BF) # The space we're solving for u in\n", + "\n", + "pdes = {\n", + " 'u': PDE(v, # test function\n", + " div(grad(u_[0])), # u\n", + " lambda f: nu*div(grad(f)), # linear operator on u\n", + " [Dx(Dx(H_[1], 0, 1), 1, 1)-Dx(H_[0], 1, 2), Dx(T_, 1, 2)],\n", + " dt=dt,\n", + " solver=chebyshev.la.Biharmonic if family == 'Chebyshev' else la.SolverGeneric1ND,\n", + " latex=r\"\\frac{\\partial \\nabla^2 u}{\\partial t} = \\nu \\nabla^4 u + \\frac{\\partial^2 N_y}{\\partial x \\partial y} - \\frac{\\partial^2 N_x}{\\partial y^2}\")\n", + "}\n", + "pdes['u'].assemble()" + ] + }, + { + "cell_type": "markdown", + "id": "7b8ac028", + "metadata": { + "editable": true + }, + "source": [ + "Notice the one-to-one resemblance with ([5](#eq:rb:u2)).\n", + "\n", + "The right hand side depends on the convection vector $\\boldsymbol{H}$, which can be computed in many different ways.\n", + "Here we will make use of\n", + "the identity $(\\boldsymbol{u} \\cdot \\nabla) \\boldsymbol{u} = -\\boldsymbol{u} \\times (\\nabla \\times \\boldsymbol{u}) + 0.5 \\nabla\\boldsymbol{u} \\cdot \\boldsymbol{u}$,\n", + "where $0.5 \\nabla \\boldsymbol{u} \\cdot \\boldsymbol{u}$ can be added to the eliminated pressure and as such\n", + "be neglected. Compute $\\boldsymbol{H} = -\\boldsymbol{u} \\times (\\nabla \\times \\boldsymbol{u})$ by first evaluating\n", + "the velocity and the curl in real space. The curl is obtained by projection of $\\nabla \\times \\boldsymbol{u}$\n", + "to the no-boundary-condition space `W_TF`, followed by a backward transform to real space.\n", + "The velocity is simply transformed backwards with padding." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1edae12b", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:09.239208Z", + "iopub.status.busy": "2024-05-24T12:37:09.239104Z", + "iopub.status.idle": "2024-05-24T12:37:09.253543Z", + "shell.execute_reply": "2024-05-24T12:37:09.251192Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "# Get a mask for setting Nyquist frequency to zero\n", + "mask = W_DF.get_mask_nyquist()\n", + "Curl = Project(curl(u_), W_WF) # Instance used to compute curl\n", + "\n", + "def compute_convection(u, H):\n", + " up = u.backward(padding_factor=1.5).v\n", + " curl = Curl().backward(padding_factor=1.5)\n", + " H[0] = W_DFp.forward(-curl*up[1])\n", + " H[1] = W_DFp.forward(curl*up[0])\n", + " H.mask_nyquist(mask)\n", + " return H" + ] + }, + { + "cell_type": "markdown", + "id": "4833c72d", + "metadata": { + "editable": true + }, + "source": [ + "Note that the convection has a homogeneous Dirichlet boundary condition in the\n", + "non-periodic direction." + ] + }, + { + "cell_type": "markdown", + "id": "4bf47890", + "metadata": { + "editable": true + }, + "source": [ + "### Streamwise velocity\n", + "\n", + "The streamwise velocity is computed using Eq. ([26](#eq:div3)) and ([27](#eq:vx)).\n", + "The first part is done fastest by projecting $f=\\frac{\\partial u}{\\partial x}$\n", + "to the same Dirichlet space `W_DF` used by $v$. This is most efficiently\n", + "done by creating a class to do it" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ef83143c", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:09.257574Z", + "iopub.status.busy": "2024-05-24T12:37:09.257466Z", + "iopub.status.idle": "2024-05-24T12:37:09.269942Z", + "shell.execute_reply": "2024-05-24T12:37:09.268913Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "f = dudx = Project(Dx(u_[0], 0, 1), W_DF)" + ] + }, + { + "cell_type": "markdown", + "id": "15d1dd66", + "metadata": { + "editable": true + }, + "source": [ + "Since $f$ now is in the same space as the streamwise velocity, Eq. ([26](#eq:div3))\n", + "simplifies to" + ] + }, + { + "cell_type": "markdown", + "id": "0cc5e0c5", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\imath l \\left(\\phi_k^D, \\phi_m^D \\right)_w \\hat{v}_{kl}\n", + " = -\\left( \\phi_k^D, \\phi_m^D \\right)_w \\hat{f}_{kl}, \\label{eq:fdiv} \\tag{30} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "6f940ea9", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " \\hat{v}_{kl} = \\frac{\\imath \\hat{f}_{kl}}{ l}.\n", + "\\label{_auto10} \\tag{31}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "93c20b46", + "metadata": { + "editable": true + }, + "source": [ + "We thus compute $\\hat{v}_{kl}$ for all $k$ and $l>0$ as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0a919817", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:09.272850Z", + "iopub.status.busy": "2024-05-24T12:37:09.272735Z", + "iopub.status.idle": "2024-05-24T12:37:09.277113Z", + "shell.execute_reply": "2024-05-24T12:37:09.276555Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "K = W_BF.local_wavenumbers(scaled=True)\n", + "K[1][0, 0] = 1 # to avoid division by zero. This component is computed later anyway.\n", + "u_[1] = 1j*dudx()/K[1]" + ] + }, + { + "cell_type": "markdown", + "id": "df413965", + "metadata": { + "editable": true + }, + "source": [ + "which leaves only $\\hat{v}_{k0}$. For this we use ([27](#eq:vx)) and get" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "115a2254", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:09.278870Z", + "iopub.status.busy": "2024-05-24T12:37:09.278806Z", + "iopub.status.idle": "2024-05-24T12:37:09.285778Z", + "shell.execute_reply": "2024-05-24T12:37:09.285461Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "v00 = Function(VD)\n", + "v0 = TestFunction(VD)\n", + "h1 = Function(VD) # convection equal to H_[1, :, 0]\n", + "pdes1d = {\n", + " 'v0': PDE(v0,\n", + " v00,\n", + " lambda f: nu*div(grad(f)),\n", + " -Expr(h1),\n", + " dt=dt,\n", + " solver=chebyshev.la.Helmholtz if family == 'Chebyshev' else la.Solver,\n", + " latex=r\"\\frac{\\partial v}{\\partial t} = \\nu \\frac{\\partial^2 v}{\\partial x^2} - N_y \"),\n", + "}\n", + "pdes1d['v0'].assemble()" + ] + }, + { + "cell_type": "markdown", + "id": "6dafd2a3", + "metadata": { + "editable": true + }, + "source": [ + "A function that computes `v` for an integration stage `rk` is" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d52d2548", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:09.288176Z", + "iopub.status.busy": "2024-05-24T12:37:09.288047Z", + "iopub.status.idle": "2024-05-24T12:37:09.291139Z", + "shell.execute_reply": "2024-05-24T12:37:09.290863Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "def compute_v(rk):\n", + " v00[:] = u_[1, :, 0].real\n", + " h1[:] = H_[1, :, 0].real\n", + " u_[1] = 1j*dudx()/K[1]\n", + " pdes1d['v0'].compute_rhs(rk)\n", + " u_[1, :, 0] = pdes1d['v0'].solve_step(rk)" + ] + }, + { + "cell_type": "markdown", + "id": "c2709468", + "metadata": { + "editable": true + }, + "source": [ + "### Temperature\n", + "\n", + "The temperature equation ([2](#eq:T)) is implemented using a Helmholtz solver.\n", + "The main difficulty with the temperature is the non-homogeneous boundary\n", + "condition that requires special attention. A non-zero Dirichlet boundary\n", + "condition is implemented by adding two basis functions to the\n", + "basis of the function space" + ] + }, + { + "cell_type": "markdown", + "id": "54e16ff6", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\phi^D_{N-2} = 0.5(1+x), \n", + "\\label{_auto11} \\tag{32}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "cf5b8b0b", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " \\phi^D_{N-1} = 0.5(1-x),\n", + "\\label{_auto12} \\tag{33}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f036c207", + "metadata": { + "editable": true + }, + "source": [ + "with the approximation now becoming" + ] + }, + { + "cell_type": "markdown", + "id": "e4e54760", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " T_N(x, y, t) = \\sum_{k=0}^{N-1} \\sum_{l \\in \\boldsymbol{l}} \\hat{T}_{kl} \\phi^D_k(x)\\exp(\\imath l y), \n", + "\\label{_auto13} \\tag{34}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "7711f3a7", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " = \\sum_{k=0}^{N-3} \\sum_{l \\in \\boldsymbol{l}} \\hat{T}_{kl} \\phi^D_k(x)\\exp(\\imath l y) + \\sum_{k=N-2}^{N-1} \\sum_{l \\in \\boldsymbol{l}} \\hat{T}_{kl} \\phi^D_k(x)\\exp(\\imath l y).\n", + "\\label{_auto14} \\tag{35}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "9c0495e0", + "metadata": { + "editable": true + }, + "source": [ + "The boundary condition requires" + ] + }, + { + "cell_type": "markdown", + "id": "de20a9ca", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "T_N(1, y, t) = \\sum_{k=N-2}^{N-1} \\sum_{l \\in \\boldsymbol{l}} \\hat{T}_{kl} \\phi^D_k(1)\\exp(\\imath l y), \n", + "\\label{_auto15} \\tag{36}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "7a45e061", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " = \\sum_{l \\in \\boldsymbol{l}} \\hat{T}_{N-2, l} \\exp(\\imath l y), \\label{eq:TN0} \\tag{37}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "d478e8e2", + "metadata": { + "editable": true + }, + "source": [ + "and" + ] + }, + { + "cell_type": "markdown", + "id": "46da00c4", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "T_N(-1, y, t) = \\sum_{k=N-2}^{N-1} \\sum_{l \\in \\boldsymbol{l}} \\hat{T}_{kl} \\phi^D_k(-1)\\exp(\\imath l y), \n", + "\\label{_auto16} \\tag{38}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "08f254e3", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " = \\sum_{l \\in \\boldsymbol{l}} \\hat{T}_{N-1, l} \\exp(\\imath l y). \\label{eq:TN1} \\tag{39}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "6ba8d915", + "metadata": { + "editable": true + }, + "source": [ + "We find $\\hat{T}_{N-2, l}$ and $\\hat{T}_{N-1, l}$ using orthogonality. Multiply ([37](#eq:TN0)) and\n", + "([39](#eq:TN1)) by $\\exp(-\\imath m y)$ and integrate over the domain $[0, 2\\pi]$. We get" + ] + }, + { + "cell_type": "markdown", + "id": "37475efa", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\hat{T}_{N-2, l} = \\int_{0}^{2\\pi} T_N(1, y, t) \\exp(-\\imath l y) dy, \n", + "\\label{_auto17} \\tag{40}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "11a34479", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " \\hat{T}_{N-1, l} = \\int_{0}^{2\\pi} T_N(-1, y, t) \\exp(-\\imath l y) dy.\n", + "\\label{_auto18} \\tag{41}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "802c82db", + "metadata": { + "editable": true + }, + "source": [ + "Using this approach it is easy to see that any inhomogeneous function $T_N(\\pm 1, y, t)$\n", + "of $y$ and $t$ can be used for the boundary condition, and not just a constant.\n", + "However, we will not get into this here.\n", + "And luckily for us all this complexity with boundary conditions will be\n", + "taken care of under the hood by shenfun.\n", + "\n", + "A time stepper for the temperature equation is implemented as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "174a1ac5", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:09.295698Z", + "iopub.status.busy": "2024-05-24T12:37:09.295557Z", + "iopub.status.idle": "2024-05-24T12:37:09.351589Z", + "shell.execute_reply": "2024-05-24T12:37:09.351196Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "uT_ = Function(BD)\n", + "q = TestFunction(W_TF)\n", + "pdes['T'] = PDE(q,\n", + " T_,\n", + " lambda f: kappa*div(grad(f)),\n", + " -div(uT_),\n", + " dt=dt,\n", + " solver=chebyshev.la.Helmholtz if family == 'Chebyshev' else la.SolverGeneric1ND,\n", + " latex=r\"\\frac{\\partial T}{\\partial t} = \\kappa \\nabla^2 T - \\nabla \\cdot \\vec{u}T\")\n", + "pdes['T'].assemble()" + ] + }, + { + "cell_type": "markdown", + "id": "d1745f18", + "metadata": { + "editable": true + }, + "source": [ + "The `uT_` term is computed with dealiasing as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "62dc1037", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:09.358586Z", + "iopub.status.busy": "2024-05-24T12:37:09.357534Z", + "iopub.status.idle": "2024-05-24T12:37:09.362536Z", + "shell.execute_reply": "2024-05-24T12:37:09.361341Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "def compute_uT(u_, T_, uT_):\n", + " up = u_.backward(padding_factor=1.5)\n", + " Tp = T_.backward(padding_factor=1.5)\n", + " uT_ = BDp.forward(up*Tp, uT_)\n", + " return uT_" + ] + }, + { + "cell_type": "markdown", + "id": "7db1c217", + "metadata": { + "editable": true + }, + "source": [ + "Finally all that is left is to initialize the solution and\n", + "integrate it forward in time." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1a2cfb7b", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:09.366812Z", + "iopub.status.busy": "2024-05-24T12:37:09.366589Z", + "iopub.status.idle": "2024-05-24T12:37:22.082684Z", + "shell.execute_reply": "2024-05-24T12:37:22.081096Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "# initialization\n", + "T_b = Array(W_TF)\n", + "X = W_TF.local_mesh(True)\n", + "#T_b[:] = 0.5*(1-X[0]) + 0.001*np.random.randn(*T_b.shape)*(1-X[0])*(1+X[0])\n", + "T_b[:] = 0.5*(1-X[0]+0.25*np.sin(np.pi*X[0]))+0.001*np.random.randn(*T_b.shape)*(1-X[0])*(1+X[0])\n", + "T_ = T_b.forward(T_)\n", + "T_.mask_nyquist(mask)\n", + "\n", + "t = 0\n", + "tstep = 0\n", + "end_time = 15\n", + "while t < end_time-1e-8:\n", + " for rk in range(PDE.steps()):\n", + " compute_convection(u_, H_)\n", + " compute_uT(u_, T_, uT_)\n", + " pdes['u'].compute_rhs(rk)\n", + " pdes['T'].compute_rhs(rk)\n", + " pdes['u'].solve_step(rk)\n", + " compute_v(rk)\n", + " pdes['T'].solve_step(rk)\n", + " t += dt\n", + " tstep += 1\n", + "plt.contourf(X[1], X[0], T_.backward(), 100)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "33635218", + "metadata": { + "editable": true + }, + "source": [ + "A complete solver implemented in a solver class can be found in\n", + "[RayleighBenard2D.py](https://github.com/spectralDNS/shenfun/blob/master/demo/RayleighBenard2D.py).\n", + "Note that in the final solver it is also possible to use a $(y, t)$-dependent boundary condition\n", + "for the hot wall. And the solver can also be configured to store intermediate results to\n", + "an `HDF5` format that later can be visualized in, e.g., Paraview. The movie in the\n", + "beginning of this demo has been created in Paraview.\n", + "\n", + "\n", + "\n", + "1. **A. Pandey, J. D. Scheel and J. Schumacher**. Turbulent Superstructures in Rayleigh-B\\'enard Convection, *Nature Communications*, 9(1), pp. 2118, [doi: 10.1038/s41467-018-04478-0](https://dx.doi.org/10.1038/s41467-018-04478-0), 2018." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/SparsityChebyshev/sparsity.ipynb b/docs/demos/SparsityChebyshev/sparsity.ipynb new file mode 100644 index 00000000..b857d2c7 --- /dev/null +++ b/docs/demos/SparsityChebyshev/sparsity.ipynb @@ -0,0 +1,1077 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "2bb2025a", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - Sparse Chebyshev-Petrov-Galerkin methods for differentiation\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **October 26, 2021**\n", + "\n", + "**Summary.** This demo explores how to use sparse Chebyshev-Petrov-Galerkin methods for finding Chebyshev coefficients of\n", + "the derivatives of smooth functions. We will compare the methods to the more commonly adopted\n", + "recursion methods that are found in most spectral textbooks." + ] + }, + { + "cell_type": "markdown", + "id": "4838d7e1", + "metadata": { + "editable": true + }, + "source": [ + "## Introduction\n", + "\n", + "The Chebyshev polynomials of the first kind can be defined as" + ] + }, + { + "cell_type": "markdown", + "id": "1af52674", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\label{eq:chebTU} \\tag{1}\n", + " T_k(x) = \\cos(k\\theta),\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "747a43e9", + "metadata": { + "editable": true + }, + "source": [ + "where $\\theta = \\cos^{-1} x$, $k$ is a positive integer and $x \\in [-1, 1]$.\n", + "The Chebyshev polynomials span the discrete space $S_N = \\text{span}\\{T_k\\}_{k=0}^{N-1}$,\n", + "and a function $u(x)$ can be approximated in this space as" + ] + }, + { + "cell_type": "markdown", + "id": "65fce623", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u_N(x) = \\sum_{k=0}^{N-1} \\hat{u}_k T_k(x).\n", + "\\label{eq:uT} \\tag{2}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1f1b1a55", + "metadata": { + "editable": true + }, + "source": [ + "Consider the expansion of the function $u(x)=\\sin(\\pi x)$, created in `shenfun` as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e8d08068", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:38:02.063676Z", + "iopub.status.busy": "2024-05-24T12:38:02.063468Z", + "iopub.status.idle": "2024-05-24T12:38:02.638338Z", + "shell.execute_reply": "2024-05-24T12:38:02.636455Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from shenfun import *\n", + "import sympy as sp\n", + "x = sp.Symbol('x')\n", + "ue = sp.sin(sp.pi*x)\n", + "N = 16\n", + "SN = FunctionSpace(N, 'C')\n", + "uN = Function(SN, buffer=ue)\n", + "uN" + ] + }, + { + "cell_type": "markdown", + "id": "bb86e5fd", + "metadata": { + "editable": true + }, + "source": [ + "The Python Function `uN` represents the expansion ([2](#eq:uT)), and the printed\n", + "values represent $\\boldsymbol{\\hat{u}} = \\{\\hat{u}_k\\}_{k=0}^{N-1}$. The expansion is fairly well resolved since\n", + "the highest values of $\\{\\hat{u}_k\\}_{k=0}^{N-1}$ approach 0.\n", + "Note that the coefficients obtained are based on interpolation at\n", + "quadrature points and they do not agree completely with the coefficients truncated from an\n", + "infinite series $u(x) = \\sum_{k=0}^{\\infty} \\hat{u}_k T_k$. The obtained series is\n", + "often denoted as $u_N(x) = I_N u(x)$, where $I_N$ is an interpolation operator.\n", + "Under the hood the coefficients are found by projection using quadrature for the integrals:\n", + "find $u_N \\in S_N$ such that" + ] + }, + { + "cell_type": "markdown", + "id": "563fe691", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "(u_N-u, v)_{\\omega^{-1/2}} = 0, \\quad \\forall v \\in S_N,\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "846b9e53", + "metadata": { + "editable": true + }, + "source": [ + "where $\\omega = (1-x^2)$ and the scalar product notation\n", + "$(a, b)_{\\omega^{-1/2}} = \\sum_{j=0}^{N-1} a(x_j)b(x_j)\\omega_j \\approx \\int_{-1}^{1} a(x)b(x) \\omega(x)^{-1/2} dx$,\n", + "where $\\{\\omega_j\\}_{j=0}^{N-1}$ are the quadrature weights. The quadrature approach ensures\n", + "that $u(x_j) = u_N(x_j)$ for all quadrature points $\\{x_j\\}_{j=0}^{N-1}$.\n", + "In `shenfun` we compute the following under the hood: insert for $u_N = \\sum_{j=0}^{N-1} \\hat{u}_j T_j$,\n", + "$u=\\sin(\\pi x)$ and $v = T_k$ to get" + ] + }, + { + "cell_type": "markdown", + "id": "833df5cb", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\sum_{j=0}^{N-1}(T_j, T_k)_{\\omega^{-1/2}} \\hat{u}_j = (\\sin(\\pi x), T_k)_{\\omega^{-1/2}},\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "54d5f8e3", + "metadata": { + "editable": true + }, + "source": [ + "This has now become a linear algebra problem, and we recognise the matrix $d^{(0)}_{kj} = (T_j, T_k)_{\\omega^{-1/2}}=c_k \\pi /2 \\delta_{kj}$,\n", + "where $\\delta_{kj}$ is the Kronecker delta function, and $c_0=2$ and $c_k=1$ for $k>0$.\n", + "The problem is solved trivially since $d^{(0)}_{kj}$ is diagonal,\n", + "and thus" + ] + }, + { + "cell_type": "markdown", + "id": "1ad4aac0", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\hat{u}_k = \\frac{2}{c_k \\pi} (\\sin(\\pi x), T_k)_{\\omega^{-1/2}}, \\quad \\forall \\, k\\in I^N,\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "ced04b4b", + "metadata": { + "editable": true + }, + "source": [ + "where $I^N = \\{0, 1, \\ldots, N-1\\}$.\n", + "We can compare this to the truncated coefficients, where the integral $(\\sin(\\pi x), T_k)_{\\omega^{-1/2}}$\n", + "is computed with high precision. To this end we could use adaptive quadrature, or symbolic integration\n", + "with sympy, but it is sufficient to use a large enough number of polynomials to fully resolve the\n", + "function. Below we find this number to be 22 and we see that the absolute error in\n", + "the highest wavenumber $\\hat{u}_{15} \\approx 10^{-11}$." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cd4b2ee5", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:38:02.646303Z", + "iopub.status.busy": "2024-05-24T12:38:02.645378Z", + "iopub.status.idle": "2024-05-24T12:38:02.663126Z", + "shell.execute_reply": "2024-05-24T12:38:02.661550Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "SM = FunctionSpace(0, 'C')\n", + "uM = Function(SM, buffer=ue, abstol=1e-16, reltol=1e-16)\n", + "print(uM[:N] - uN[:N])\n", + "print(len(uM))" + ] + }, + { + "cell_type": "markdown", + "id": "bef631d0", + "metadata": { + "editable": true + }, + "source": [ + "## Differentiation\n", + "\n", + "Let us now consider the $n$'th derivative of $u(x)$ instead, denoted here as $u^{(n)}$.\n", + "We want to find $u^{(n)}$ in the space $S_N$, which means that we want to obtain\n", + "the following expansion" + ] + }, + { + "cell_type": "markdown", + "id": "2c78531f", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "u_N^{(n)} = \\sum_{k=0}^{N-1} \\hat{u}^{(n)}_k T_k.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "6bacc81d", + "metadata": { + "editable": true + }, + "source": [ + "First note that this expansion is not the same as the derivative of\n", + "the previously found $u_N$, which is" + ] + }, + { + "cell_type": "markdown", + "id": "aa75f2fd", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "(u_N)^{(n)} = \\sum_{k=0}^{N-1} \\hat{u}_k T^{(n)}_k,\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "311527fa", + "metadata": { + "editable": true + }, + "source": [ + "where $T^{(n)}_k$ is the $n$'th derivative of $T_k$, a polynomial of order $k-n$.\n", + "We again use projection to find $u_N^{(n)} \\in S_N$ such that" + ] + }, + { + "cell_type": "markdown", + "id": "5bf2f5d1", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "(u_N^{(n)}-u^{(n)}, v)_{\\omega^{-1/2}} = 0, \\quad \\forall v \\in S_N.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f7e7d354", + "metadata": { + "editable": true + }, + "source": [ + "Inserting for $u_N^{(n)}$ and $u^{(n)} = (u_N)^{(n)}$ we get" + ] + }, + { + "cell_type": "markdown", + "id": "45bc180f", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\sum_{j=0}^{N-1}(T_j, T_k)_{\\omega^{-1/2}} \\hat{u}_j^{(n)} = (T_j^{(n)}, T_k)_{\\omega^{-1/2}} \\hat{u}_j, \n", + "\\label{_auto1} \\tag{3}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "bd058277", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " \\sum_{j=0}^{N-1} d^{(0)}_{kj} \\hat{u}_j^{(n)} = \\sum_{j=0}^{N-1} d^{(n)}_{kj} \\hat{u}_j,\n", + "\\label{_auto2} \\tag{4}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1dc093f5", + "metadata": { + "editable": true + }, + "source": [ + "where $d^{(n)}_{kj} = (T_j^{(n)}, T_k)_{\\omega^{-1/2}}$.\n", + "We compute $\\hat{u}_k^{(n)}$ by inverting the diagonal $d^{(0)}_{kj}$" + ] + }, + { + "cell_type": "markdown", + "id": "f6025179", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\hat{u}_k^{(n)} = \\frac{2}{c_k \\pi} \\sum_{j=0}^{N-1} d^{(n)}_{kj} \\hat{u}_j, \\quad \\forall \\, k \\in I^{N}.\n", + "\\label{eq:fhat} \\tag{5}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "7eea7af8", + "metadata": { + "editable": true + }, + "source": [ + "The matrix $d^{(n)}_{kj}$ is upper triangular, and the last $n$ rows are zero. Since $d^{(n)}_{kj}$ is\n", + "dense the matrix vector product $\\sum_{j=0}^{N-1} d^{(n)}_{kj} \\hat{u}_j$ is costly\n", + "and also susceptible to roundoff errors if the structure of the matrix is\n", + "not taken advantage of. But computing it in shenfun\n", + "is straightforward, for $n=1$ and $2$:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4f6c7409", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:38:02.672049Z", + "iopub.status.busy": "2024-05-24T12:38:02.671899Z", + "iopub.status.idle": "2024-05-24T12:38:02.677371Z", + "shell.execute_reply": "2024-05-24T12:38:02.676910Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "uN1 = project(Dx(uN, 0, 1), SN)\n", + "uN2 = project(Dx(uN, 0, 2), SN)\n", + "uN1" + ] + }, + { + "cell_type": "markdown", + "id": "ed23d795", + "metadata": { + "editable": true + }, + "source": [ + "where `uN1` $=u_N^{(1)}$ and `uN2` $=u_N^{(2)}$.\n", + "Alternatively, doing all the work that goes on under the hood" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "85617695", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:38:02.680031Z", + "iopub.status.busy": "2024-05-24T12:38:02.679906Z", + "iopub.status.idle": "2024-05-24T12:38:02.687433Z", + "shell.execute_reply": "2024-05-24T12:38:02.685429Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u = TrialFunction(SN)\n", + "v = TestFunction(SN)\n", + "D0 = inner(u, v)\n", + "D1 = inner(Dx(u, 0, 1), v)\n", + "D2 = inner(Dx(u, 0, 2), v)\n", + "w0 = Function(SN) # work array\n", + "uN1 = Function(SN)\n", + "uN2 = Function(SN)\n", + "uN1 = D0.solve(D1.matvec(uN, w0), uN1)\n", + "uN2 = D0.solve(D2.matvec(uN, w0), uN2)\n", + "uN1" + ] + }, + { + "cell_type": "markdown", + "id": "8203a97b", + "metadata": { + "editable": true + }, + "source": [ + "We can look at the sparsity patterns of $(d^{(1)}_{kj})$ and $(d^{(2)}_{kj})$" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0288b4fe", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:38:02.691434Z", + "iopub.status.busy": "2024-05-24T12:38:02.691315Z", + "iopub.status.idle": "2024-05-24T12:38:03.088709Z", + "shell.execute_reply": "2024-05-24T12:38:03.086306Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "fig, (ax1, ax2) = plt.subplots(1, 2)\n", + "ax1.spy(D1.diags(), markersize=2, color='r')\n", + "ax2.spy(D2.diags(), markersize=2, color='b')" + ] + }, + { + "cell_type": "markdown", + "id": "798dcfdd", + "metadata": { + "editable": true + }, + "source": [ + "just to see that they are upper triangular. We now ask is there a better and faster\n", + "way to get `uN1` and `uN2`? A better approach would involve only sparse\n", + "matrices, like the diagonal $(d^{(0)}_{kj})$. But how do we get there?\n", + "Most textbooks on spectral methods use fast recursive methods to\n", + "find the coefficients $\\{\\hat{u}_k^{(n)}\\}$. Here we will show a fast Galerkin approach.\n", + "\n", + "It turns out that a simple change of test space/function will be sufficient.\n", + "Let us first replace the test space $S_N$ with\n", + "the Dirichlet space $D_N=\\{v \\in S_N | v(\\pm 1) = 0\\}$ using basis\n", + "functions $v=T_k-T_{k+2}$ and see\n", + "what happens. Because of the two boundary conditions,\n", + "the number of degrees of freedom is reduced by two, and we need to use a\n", + "space with $N+2$ quadrature points in order to get a square matrix system.\n", + "The method now becomes classified as Chebyshev-Petrov-Galerkin, as we\n", + "wish to find $u_N^{(1)} \\in S_N$ such that" + ] + }, + { + "cell_type": "markdown", + "id": "a0edfd85", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "(u_N^{(1)}-u^{(1)}, v)_{\\omega^{-1/2}} = 0, \\quad \\forall v \\in D_{N+2}.\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "6fb9034a", + "metadata": { + "editable": true + }, + "source": [ + "The implementation is straightforward" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "78eb36cf", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:38:03.097765Z", + "iopub.status.busy": "2024-05-24T12:38:03.097566Z", + "iopub.status.idle": "2024-05-24T12:38:03.115215Z", + "shell.execute_reply": "2024-05-24T12:38:03.114393Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "DN = FunctionSpace(N+2, 'C', bc=(0, 0))\n", + "v = TestFunction(DN)\n", + "D0 = inner(u, v)\n", + "D1 = inner(Dx(u, 0, 1), v)\n", + "uN11 = Function(SN)\n", + "uN11 = D0.solve(D1.matvec(uN, w0), uN11)\n", + "print(uN11-uN1)" + ] + }, + { + "cell_type": "markdown", + "id": "6fc6f39f", + "metadata": { + "editable": true + }, + "source": [ + "and since `uN11 = uN1` we see that we have achived the same result as in\n", + "the regular projection. However, the matrices in use now look like" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d5e3bb84", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:38:03.119267Z", + "iopub.status.busy": "2024-05-24T12:38:03.118778Z", + "iopub.status.idle": "2024-05-24T12:38:03.302255Z", + "shell.execute_reply": "2024-05-24T12:38:03.301865Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "fig, (ax1, ax2) = plt.subplots(1, 2)\n", + "ax1.spy(D0.diags(), markersize=2, color='r')\n", + "ax2.spy(D1.diags(), markersize=2, color='b')" + ] + }, + { + "cell_type": "markdown", + "id": "f9c99379", + "metadata": { + "editable": true + }, + "source": [ + "So $(d^{(0)}_{kj})$ now contains two nonzero diagonals, whereas $(d^{(1)}_{kj})$ is\n", + "a matrix with one single diagonal. There is no longer a `full` differentiation\n", + "matrix, and we can easily perform this projection for millions of degrees of freedom.\n", + "What about $(d^{(2)}_{kj})$? We can now use biharmonic test functions that\n", + "satisfy four boundary conditions in the space $B_N = \\{v \\in S_N | v(\\pm 1) = v'(\\pm 1) =0\\}$,\n", + "and continue in a similar fashion:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6a5b8db9", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:38:03.307791Z", + "iopub.status.busy": "2024-05-24T12:38:03.307221Z", + "iopub.status.idle": "2024-05-24T12:38:03.334290Z", + "shell.execute_reply": "2024-05-24T12:38:03.331755Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "BN = FunctionSpace(N+4, 'C', bc=(0, 0, 0, 0))\n", + "v = TestFunction(BN)\n", + "D0 = inner(u, v)\n", + "D2 = inner(Dx(u, 0, 2), v)\n", + "uN22 = Function(SN)\n", + "uN22 = D0.solve(D2.matvec(uN, w0), uN22)\n", + "print(uN22-uN2)" + ] + }, + { + "cell_type": "markdown", + "id": "83944e9d", + "metadata": { + "editable": true + }, + "source": [ + "We get that `uN22 = uN2`, so the Chebyshev-Petrov-Galerkin projection works. The matrices involved are now" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "138b71ea", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:38:03.339328Z", + "iopub.status.busy": "2024-05-24T12:38:03.339153Z", + "iopub.status.idle": "2024-05-24T12:38:03.573813Z", + "shell.execute_reply": "2024-05-24T12:38:03.572191Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "fig, (ax1, ax2) = plt.subplots(1, 2)\n", + "ax1.spy(D0.diags(), markersize=2, color='r')\n", + "ax2.spy(D2.diags(), markersize=2, color='b')" + ] + }, + { + "cell_type": "markdown", + "id": "99a670bc", + "metadata": { + "editable": true + }, + "source": [ + "So there are now three nonzero diagonals in $(d^{(0)}_{kj})$, whereas the differentiation matrix\n", + "$(d^{(2)}_{kj})$ contains only one nonzero diagonal.\n", + "\n", + "Why does this work so well? The Chebyshev polynomials and their derivatives satisfy the following orthogonality relation" + ] + }, + { + "cell_type": "markdown", + "id": "e9c66875", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\label{eq:orthon} \\tag{6}\n", + " \\int_{-1}^{1} T^{(n)}_j T^{(n)}_k \\omega^{n-1/2} dx = \\alpha^{n}_k \\delta_{kj}, \\quad \\text{for}\\, n \\ge 0,\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "ab4aeed8", + "metadata": { + "editable": true + }, + "source": [ + "where" + ] + }, + { + "cell_type": "markdown", + "id": "2e7f11e2", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\alpha^n_k = \\frac{c_{k+n}\\pi k (k+n-1)!}{2(k-n)!}.\n", + "\\label{_auto3} \\tag{7}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "ec8e259a", + "metadata": { + "editable": true + }, + "source": [ + "So when we choose a test function $\\omega^n T^{(n)}_k$ and a trial function $T_j$,\n", + "we get the diagonal differentiation matrix" + ] + }, + { + "cell_type": "markdown", + "id": "0a9845f8", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " d^{(n)}_{kj} = \\int_{-1}^{1} T^{(n)}_j (\\omega^n T^{(n)}_k) \\omega^{-1/2} dx = \\alpha^{n}_k \\delta_{kj}, \\quad \\text{for}\\, n \\ge 0.\n", + "\\label{_auto4} \\tag{8}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1faaf249", + "metadata": { + "editable": true + }, + "source": [ + "The two chosen test functions above are both proportional to $\\omega^n T^{(n)}_k$. More precisely,\n", + "$T_k-T_{k+2} = \\frac{2}{k+1} \\omega T^{(1)}_{k+1}$ and the biharmonic test function is\n", + "$T_k-\\frac{2(k+2)}{k+3}T_{k+2} + \\frac{k+1}{k+3}T_{k+4} = \\frac{4 \\omega^2T^{(2)}_{k+2}}{(k+2)(k+3)}$.\n", + "Using these very specific test functions correponds closely to using the Chebyshev\n", + "recursion formulas that are found in most textbooks. Here they are adapted to\n", + "a Chebyshev-Petrov-Galerkin method, where we simply choose test and trial functions and everything\n", + "else falls into place in a few lines of code." + ] + }, + { + "cell_type": "markdown", + "id": "505a7c63", + "metadata": { + "editable": true + }, + "source": [ + "## Recursion\n", + "\n", + "Let us for completion show how to\n", + "find $\\hat{u}_N^{(1)}$ with a recursive approach. The Chebyshev polynomials\n", + "satisfy" + ] + }, + { + "cell_type": "markdown", + "id": "e01fad08", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "2T_k = \\frac{1}{k+1}T'_{k+1}- \\frac{1}{k-1} T'_{k-1}, \\quad k \\ge 1.\n", + "\\label{eq:Trec1} \\tag{9}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "a5e54439", + "metadata": { + "editable": true + }, + "source": [ + "By using this and setting $u' = \\sum_{k=0}^{\\infty} \\hat{u}^{(1)}_k T_k = \\sum_{k=0}^{\\infty} \\hat{u}_k T'_k$\n", + "we get" + ] + }, + { + "cell_type": "markdown", + "id": "c6be810e", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "2k\\hat{u}_k = c_{k-1}\\hat{u}^{(1)}_{k-1} - \\hat{u}^{(1)}_{k+1}, \\quad k \\ge 1.\n", + "\\label{eq:Trec2} \\tag{10}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "235acf35", + "metadata": { + "editable": true + }, + "source": [ + "Using this recursion on a discrete series, together with $\\hat{u}^{(1)}_{N} = \\hat{u}^{(1)}_{N-1} = 0$, we get\n", + "(see [[canuto]](#canuto) Eq. (2.4.24))" + ] + }, + { + "cell_type": "markdown", + "id": "a3b2391d", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "c_k \\hat{u}^{(1)}_k = \\hat{u}^{(1)}_{k+2} + 2(k+1)\\hat{u}_{k+1}, \\quad 0 \\le k \\le N-2,\n", + "\\label{eq:Trec3} \\tag{11}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "acbd18e5", + "metadata": { + "editable": true + }, + "source": [ + "which is easily implemented in a (slow) for-loop" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b62bbb21", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:38:03.577529Z", + "iopub.status.busy": "2024-05-24T12:38:03.577429Z", + "iopub.status.idle": "2024-05-24T12:38:03.581284Z", + "shell.execute_reply": "2024-05-24T12:38:03.580257Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "f1 = np.zeros(N+1)\n", + "ck = np.ones(N); ck[0] = 2\n", + "for k in range(N-2, -1, -1):\n", + " f1[k] = (f1[k+2]+2*(k+1)*uN[k+1])/ck[k]\n", + "print(f1[:-1]-uN1)" + ] + }, + { + "cell_type": "markdown", + "id": "4dcda2f1", + "metadata": { + "editable": true + }, + "source": [ + "which evidently is exactly the same result. It turns out that this is not strange. If we multiply\n", + "([11](#eq:Trec3)) by $\\pi/2$, rearrange a little bit and move to a matrix form we get" + ] + }, + { + "cell_type": "markdown", + "id": "eaeaa2a8", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "c_k \\pi/2 \\hat{u}^{(1)}_k - \\pi/2 \\hat{u}^{(1)}_{k+2} = (k+1)\\pi \\hat{u}_{k+1} \n", + "\\label{_auto5} \\tag{12}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1eddc342", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\underbrace{(c_k \\pi/2 \\delta_{kj} - \\pi/2 \\delta_{k, j-2})}_{(D^0)_{kj}} \\hat{u}^{(1)}_j = \\underbrace{(k+1)\\pi \\delta_{k,j-1}}_{(D^1)_{kj}} \\hat{u}_{j} \n", + "\\label{_auto6} \\tag{13}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f3e68c7c", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "D^0 \\boldsymbol{\\hat{u}} = D^1 \\boldsymbol{\\hat{u}} \n", + "\\label{_auto7} \\tag{14}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e4d34134", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\boldsymbol{\\hat{u}^{(1)}} = (D^0)^{-1} D^1 \\boldsymbol{\\hat{u}}\n", + "\\label{_auto8} \\tag{15}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "b2e1a8af", + "metadata": { + "editable": true + }, + "source": [ + "which is exactly how $\\boldsymbol{\\hat{u}^{(1)}}$ was computed above with the Chebyshev-Petrov-Galerkin approach\n", + "(compare with the code line `uN11 = D0.solve(D1.matvec(uN, w0), uN11)`). Not convinced? Check that the matrices\n", + "`D0` and `D1` are truly as stated above. The matrices below are printed as dictionaries with diagonal\n", + "number as key (main is 0, first upper is 1 etc) and diagonal values as values:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f76f13c5", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:38:03.587180Z", + "iopub.status.busy": "2024-05-24T12:38:03.587025Z", + "iopub.status.idle": "2024-05-24T12:38:03.590613Z", + "shell.execute_reply": "2024-05-24T12:38:03.590196Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "import pprint\n", + "DN = FunctionSpace(N+2, 'C', bc=(0, 0))\n", + "v = TestFunction(DN)\n", + "D0 = inner(u, v)\n", + "D1 = inner(Dx(u, 0, 1), v)\n", + "pprint.pprint(dict(D0))\n", + "pprint.pprint(dict(D1))" + ] + }, + { + "cell_type": "markdown", + "id": "a43c5ad2", + "metadata": { + "editable": true + }, + "source": [ + "In conclusion, we have shown that we can use an efficient Chebyshev-Petrov-Galerkin approach to obtain\n", + "the discrete Chebyshev coefficients for the derivatives\n", + "of a function. By inspection, it turns out that this approach is identical to the common methods based on\n", + "well-known Chebyshev recursion formulas.\n", + "\n", + "\n", + "\n", + "1. **C. Canuto, M. Hussaini, A. Quarteroni and J. T. A.**. *Spectral Methods in Fluid Dynamics*, *Scientific Computation*, Springer, 2012." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/SphereHelmholtz/sphericalhelmholtz.ipynb b/docs/demos/SphereHelmholtz/sphericalhelmholtz.ipynb new file mode 100644 index 00000000..df7c22fb --- /dev/null +++ b/docs/demos/SphereHelmholtz/sphericalhelmholtz.ipynb @@ -0,0 +1,591 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "b2ae13fb", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - Helmholtz equation on the unit sphere\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **April 20, 2020**\n", + "\n", + "**Summary.** This is a demonstration of how the Python module [shenfun](https://github.com/spectralDNS/shenfun) can be used to solve the\n", + "Helmholtz equation on a unit sphere, using spherical\n", + "coordinates. This demo is implemented in\n", + "a single Python file [sphere_helmholtz.py](https://github.com/spectralDNS/shenfun/blob/master/demo/sphere_helmholtz.py).\n", + "If requested the solver will run in parallel using MPI.\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "

Figure 1: Helmholtz on the unit sphere.

\n", + "" + ] + }, + { + "cell_type": "markdown", + "id": "621e1394", + "metadata": { + "editable": true + }, + "source": [ + "## Helmholtz equation\n", + "\n", + "\n", + "The Helmholtz equation is given as" + ] + }, + { + "cell_type": "markdown", + "id": "6f206c3b", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "-\\nabla^2 u(\\boldsymbol{x}) + \\alpha u(\\boldsymbol{x}) = f(\\boldsymbol{x}) \\quad \\text{for }\\, \\boldsymbol{x} \\in \\Omega = \\{(x, y, z): x^2+y^2+z^2 = 1\\}, \\label{eq:helmholtz} \\tag{1}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "627e0395", + "metadata": { + "editable": true + }, + "source": [ + "where $u(\\boldsymbol{x})$ is the solution, $f(\\boldsymbol{x})$ is a function and $\\alpha$ a constant.\n", + "We use spherical coordinates $(\\theta, \\phi)$, defined as" + ] + }, + { + "cell_type": "markdown", + "id": "f30f6090", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " x = r \\sin \\theta \\cos \\phi , \n", + "\\label{_auto1} \\tag{2}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "eccfd3f2", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " y = r \\sin \\theta \\sin \\phi, \n", + "\\label{_auto2} \\tag{3}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "5922a3fb", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " z = r \\cos \\theta\n", + "\\label{_auto3} \\tag{4}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "c9ee85b3", + "metadata": { + "editable": true + }, + "source": [ + "which (with $r=1$) leads to a 2D Cartesian product mesh $(\\theta, \\phi) \\in (0, \\pi) \\times [0, 2\\pi)$\n", + "suitable for numerical implementations. There are no boundary\n", + "conditions on the problem under consideration.\n", + "However, with the chosen Cartesian mesh, periodic\n", + "boundary conditions are required for the $\\phi$-direction. As such,\n", + "the $\\phi$-direction will use a Fourier basis $\\exp(\\imath k \\phi)$.\n", + "\n", + "A regular Chebyshev or Legendre basis\n", + "$\\psi_j(\\theta) = \\gamma_j(2\\theta/\\pi-1)$ will be\n", + "used for the $\\theta$-direction, where $\\gamma_j$ could be either\n", + "the Chebyshev polynomial of first kind $T_j$ or the Legendre\n", + "polynomial $L_j$. Note the mapping from real coordinates $\\theta$\n", + "to computational coordinates in domain $[-1, 1]$.\n", + "\n", + "The spherical basis functions are as such" + ] + }, + { + "cell_type": "markdown", + "id": "5fffe062", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "v_{jk}(\\theta, \\phi) = \\psi_j(\\theta) \\exp(\\imath k \\phi),\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "c73ec530", + "metadata": { + "editable": true + }, + "source": [ + "and we look for solutions" + ] + }, + { + "cell_type": "markdown", + "id": "175dfb12", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "u(\\theta, \\phi) = \\sum_{j} \\sum_{k} \\hat{u}_{jk} v_{jk}(\\theta, \\phi).\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "82a9884f", + "metadata": { + "editable": true + }, + "source": [ + "A discrete Fourier approximation space with $N$ basis functions is then" + ] + }, + { + "cell_type": "markdown", + "id": "c3cc267f", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "V_F^N = \\text{span} \\{\\exp(\\imath k \\theta)\\,|\\,\\text{ for } k \\in K\\},\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "971d6346", + "metadata": { + "editable": true + }, + "source": [ + "where the index set $K = \\{-N/2, -N/2+1, \\ldots, N/2-1\\}$. For this demo we assume\n", + "that the solution is complex, and as such there is no simplification\n", + "possible for Hermitian symmetry.\n", + "\n", + "The following approximation space is used for the $\\theta$-direction" + ] + }, + { + "cell_type": "markdown", + "id": "71b72efd", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "V^N = \\text{span} \\{\\psi_j\\}_{j=0}^{N-1},\n", + "\\label{_auto4} \\tag{5}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "d8ee4a77", + "metadata": { + "editable": true + }, + "source": [ + "and the variational formulation of the problem reads:\n", + "find $u \\in V^N \\otimes V_F^N$ such that" + ] + }, + { + "cell_type": "markdown", + "id": "4e96bb4d", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\int_{\\Omega} (-\\nabla^2 u + \\alpha u) v w d\\sigma = \\int_{\\Omega} f v w d\\sigma, \\quad \\forall \\, v \\in V^N \\otimes V_F^N.\n", + "\\label{eq:u0} \\tag{6}\n", + " \\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "9f805cf9", + "metadata": { + "editable": true + }, + "source": [ + "Note that integration over the domain is done using\n", + "spherical coordinates with an integral measure of $d\\sigma=\\sin \\theta d\\theta d\\phi$." + ] + }, + { + "cell_type": "markdown", + "id": "eb297602", + "metadata": { + "editable": true + }, + "source": [ + "## Implementation\n", + "\n", + "\n", + "A complete implementation is found in the file [sphere_helmholtz.py](https://github.com/spectralDNS/shenfun/blob/master/demo/sphere_helmholtz.py).\n", + "Here we give a brief explanation for the implementation. Start by\n", + "importing all functionality from [shenfun](https://github.com/spectralDNS/shenfun)\n", + "and [sympy](https://sympy.org), where Sympy is required for handeling the\n", + "spherical coordinates." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4580c8b3", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:44.032453Z", + "iopub.status.busy": "2024-05-24T12:36:44.032257Z", + "iopub.status.idle": "2024-05-24T12:36:44.630842Z", + "shell.execute_reply": "2024-05-24T12:36:44.629282Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from shenfun import *\n", + "import sympy as sp\n", + "\n", + "# Define spherical coordinates with unit radius\n", + "r = 1\n", + "theta, phi = sp.symbols('x,y', real=True, positive=True)\n", + "psi = (theta, phi)\n", + "rv = (r*sp.sin(theta)*sp.cos(phi), r*sp.sin(theta)*sp.sin(phi), r*sp.cos(theta))" + ] + }, + { + "cell_type": "markdown", + "id": "fced4ffa", + "metadata": { + "editable": true + }, + "source": [ + "Note that the position vector `rv` has three components (for $(x, y, z)$)\n", + "even though the computational domain is only 2D.\n", + "Also note that Sympy symbols are both positive and real, and $\\theta$ is\n", + "chosen to be along the first axis and $\\phi$ second. This has to agree with\n", + "the next step, which is the creation of tensorproductspaces\n", + "$V^N \\otimes V_F^N$." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7cbc4b2a", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:44.636422Z", + "iopub.status.busy": "2024-05-24T12:36:44.636108Z", + "iopub.status.idle": "2024-05-24T12:36:45.005876Z", + "shell.execute_reply": "2024-05-24T12:36:45.003827Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "N, M = 40, 30\n", + "L0 = FunctionSpace(N, 'C', domain=(0, np.pi))\n", + "F1 = FunctionSpace(M, 'F', dtype='D')\n", + "T = TensorProductSpace(comm, (L0, F1), coordinates=(psi, rv, sp.Q.positive(sp.sin(theta))))" + ] + }, + { + "cell_type": "markdown", + "id": "2ed0d981", + "metadata": { + "editable": true + }, + "source": [ + "Spherical coordinates are ensured by feeding `coordinates=(psi, rv, sp.Q.positive(sp.sin(theta)))`\n", + "to [TensorProductSpace](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.tensorproductspace.TensorProductSpace), where the restriction `sp.Q.positive(sp.sin(theta))` is there\n", + "to help sympy. Operators like [div()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.operators.div),\n", + "[grad()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.operators.grad) and [curl()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.operators.curl) will now work on\n", + "items of [Function](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Function), [TestFunction](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.TestFunction) and\n", + "[TrialFunction](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.TrialFunction) using a spherical coordinate system.\n", + "\n", + "To define the equation ([6](#eq:u0)) we first declare\n", + "these test- and trialfunctions, and then use code that\n", + "is very similar to the mathematics." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2118b5f7", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:45.015743Z", + "iopub.status.busy": "2024-05-24T12:36:45.015606Z", + "iopub.status.idle": "2024-05-24T12:36:45.186310Z", + "shell.execute_reply": "2024-05-24T12:36:45.184483Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "alpha = 2\n", + "v = TestFunction(T)\n", + "u = TrialFunction(T)\n", + "mats = inner(v, -div(grad(u))+alpha*u)" + ] + }, + { + "cell_type": "markdown", + "id": "c747054e", + "metadata": { + "editable": true + }, + "source": [ + "Here `mats` will be a list containing several tensor product\n", + "matrices in the form of\n", + "[TPMatrix](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.matrixbase.TPMatrix). Since there is only one directions with\n", + "non-diagonal matrices ($\\theta$-direction) we\n", + "can use the generic [SolverGeneric1ND](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.la.SolverGeneric1ND) solver.\n", + "Note that some of the non-diagonal matrices will be dense,\n", + "which is a weakness of the current method. Also note\n", + "that with Legendre one can use integration by parts\n", + "instead" + ] + }, + { + "cell_type": "markdown", + "id": "7760f7dc", + "metadata": { + "editable": true + }, + "source": [ + "```Python\n", + " mats = inner(grad(v), grad(u))\n", + " mats += [inner(v, alpha*u)]\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "b002e5c4", + "metadata": { + "editable": true + }, + "source": [ + "To solve the problem we also need to define the function $f(\\theta, r)$.\n", + "To this end we use sympy and the method of\n", + "manufactured solution to define a possible solution `ue`,\n", + "and then compute `f` exactly using exact differentiation. We use\n", + "the [spherical harmonics function](https://docs.sympy.org/latest/modules/functions/special.html#spherical-harmonics)\n", + "to define an analytical solution" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "50e8d4d1", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:45.191391Z", + "iopub.status.busy": "2024-05-24T12:36:45.191284Z", + "iopub.status.idle": "2024-05-24T12:36:45.288513Z", + "shell.execute_reply": "2024-05-24T12:36:45.287729Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "alpha = 2\n", + "sph = sp.functions.special.spherical_harmonics.Ynm\n", + "ue = sph(6, 3, theta, phi)\n", + "\n", + "# Compute the right hand side on the quadrature mesh\n", + "# That is, compute f = -div(grad(ue)) + alpha*ue\n", + "f = (-div(grad(u))+alpha*u).tosympy(basis=ue, psi=psi)\n", + "fj = Array(T, buffer=f)\n", + "\n", + "# Take scalar product\n", + "f_hat = Function(T)\n", + "f_hat = inner(v, fj, output_array=f_hat)\n", + "\n", + "u_hat = Function(T)\n", + "Sol = la.SolverGeneric1ND(mats)\n", + "u_hat = Sol(f_hat, u_hat)" + ] + }, + { + "cell_type": "markdown", + "id": "8923490d", + "metadata": { + "editable": true + }, + "source": [ + "Having found the solution in spectral space all that is\n", + "left is to transform it back to real space." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8d0a59de", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:45.296292Z", + "iopub.status.busy": "2024-05-24T12:36:45.295845Z", + "iopub.status.idle": "2024-05-24T12:36:45.303401Z", + "shell.execute_reply": "2024-05-24T12:36:45.302897Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "uj = u_hat.backward()\n", + "uq = Array(T, buffer=ue)\n", + "print('Error =', np.linalg.norm(uj-uq))" + ] + }, + { + "cell_type": "markdown", + "id": "9db642db", + "metadata": { + "editable": true + }, + "source": [ + "## Postprocessing\n", + "We can refine the solution to make it look better,\n", + "and plot on the unit sphere using either [mayavi](https://docs.enthought.com/mayavi/mayavi/)\n", + "or [plotly](https://plotly.com/) using the shenfun function\n", + "[surf3D()](https://shenfun.readthedocs.io/en/latest/shenfun.utilities.html#shenfun.utilities.surf3D)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f91cfdf0", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:45.307987Z", + "iopub.status.busy": "2024-05-24T12:36:45.307854Z", + "iopub.status.idle": "2024-05-24T12:36:45.786269Z", + "shell.execute_reply": "2024-05-24T12:36:45.785235Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u_hat2 = u_hat.refine([N*2, M*2])\n", + "fig = surf3D(u_hat2.backward().real, wrapaxes=[1])\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "id": "e31669b2", + "metadata": { + "editable": true + }, + "source": [ + "" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/Stokes/stokes.ipynb b/docs/demos/Stokes/stokes.ipynb new file mode 100644 index 00000000..e535c801 --- /dev/null +++ b/docs/demos/Stokes/stokes.ipynb @@ -0,0 +1,1138 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "4787e292", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - Stokes equations\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **January 23, 2019**\n", + "\n", + "**Summary.** The Stokes equations describe the flow of highly viscous fluids.\n", + "This is a demonstration of how the Python module [shenfun](https://github.com/spectralDNS/shenfun) can be used to solve Stokes\n", + "equations using a mixed (coupled) basis in a 3D tensor product domain.\n", + "We assume homogeneous Dirichlet boundary conditions in one direction\n", + "and periodicity in the remaining two. The solver described runs with MPI\n", + "without any further considerations required from the user.\n", + "The solver assembles a block matrix with sparsity pattern as shown below\n", + "for the Legendre basis.\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "

Figure 1: Coupled block matrix for Stokes equations.

\n", + "" + ] + }, + { + "cell_type": "markdown", + "id": "5313c3e5", + "metadata": { + "editable": true + }, + "source": [ + "## Stokes' equations\n", + "\n", + "\n", + "Stokes' equations are given in strong form as" + ] + }, + { + "cell_type": "markdown", + "id": "b5b12363", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "\\begin{align*}\n", + "\\nabla^2 \\boldsymbol{u} - \\nabla p &= \\boldsymbol{f} \\quad \\text{in } \\Omega, \\\\ \n", + "\\nabla \\cdot \\boldsymbol{u} &= h \\quad \\text{in } \\Omega, \\\\ \n", + "\\int_{\\Omega} p dx &= 0,\n", + "\\end{align*}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "30593271", + "metadata": { + "editable": true + }, + "source": [ + "where $\\boldsymbol{u}$ and $p$ are, respectively, the\n", + "fluid velocity vector and pressure, and the domain\n", + "$\\Omega = [0, 2\\pi)^2 \\times (-1, 1)$. The flow is assumed periodic\n", + "in $x$ and $y$-directions, whereas there is a no-slip homogeneous Dirichlet\n", + "boundary condition on $\\boldsymbol{u}$ on the boundaries of the $z$-direction, i.e.,\n", + "$\\boldsymbol{u}(x, y, \\pm 1) = (0, 0, 0)$. (Note that we can configure shenfun with\n", + "non-periodicity in any of the three directions. However, since we are to\n", + "solve linear algebraic systems in the non-periodic direction, there is a speed\n", + "benefit from having the nonperiodic direction last. This has to do with Numpy\n", + "using a C-style row-major storage of arrays by default.)\n", + "The right hand side vector $\\boldsymbol{f}(\\boldsymbol{x})$ is an external applied body force.\n", + "The right hand side $h$ is usually zero in the regular Stokes equations. Here\n", + "we include it because it will be nonzero in the verification, which is using the\n", + "method of manufactured solutions. Note that the final $\\int_{\\Omega} p dx = 0$\n", + "is there because there is no Dirichlet boundary condition on the pressure\n", + "and the system of equations would otherwise be ill conditioned.\n", + "\n", + "To solve Stokes' equations with the Galerkin method we need basis\n", + "functions for both velocity and pressure. A\n", + "Dirichlet basis will be used for velocity, whereas there is no boundary restriction\n", + "on the pressure basis. For both three-dimensional bases we will use one basis\n", + "function for the $x$-direction,\n", + "$\\mathcal{X}(x)$, one for the $y$-direction, $\\mathcal{Y}(y)$, and one for the\n", + "$z$-direction, $\\mathcal{Z}(z)$. And\n", + "then we create three-dimensional basis functions like" + ] + }, + { + "cell_type": "markdown", + "id": "9b3a39c1", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "v(x, y, z) = \\mathcal{X}(x) \\mathcal{Y}(y) \\mathcal{Z} (z).\n", + "\\label{_auto1} \\tag{1}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "c64794c9", + "metadata": { + "editable": true + }, + "source": [ + "The basis functions $\\mathcal{X}(x)$ and $\\mathcal{Y}(y)$ are chosen as Fourier\n", + "exponentials, since these functions are periodic:" + ] + }, + { + "cell_type": "markdown", + "id": "73fff69f", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\mathcal{X}_l(x) = e^{\\imath l x}, \\forall \\, l \\in \\boldsymbol{l}^{N_0}, \n", + "\\label{_auto2} \\tag{2}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "296be640", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\mathcal{Y}_m(y) = e^{\\imath m y}, \\forall \\, m \\in \\boldsymbol{m}^{N_1},\n", + "\\label{_auto3} \\tag{3}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "239fe816", + "metadata": { + "editable": true + }, + "source": [ + "where $\\boldsymbol{l}^{N_0} = (-N_0/2, -N_0/2+1, \\ldots, N_0/2-1)$ and\n", + "$\\boldsymbol{m}^{N_1} = (-N_1/2, -N_1/2+1, \\ldots, N_1/2-1)$.\n", + "The size of the discretized problem in real physical space is\n", + "$\\boldsymbol{N} = (N_0, N_1, N_2)$, i.e., there are $N_0 \\cdot N_1 \\cdot N_2$ quadrature points\n", + "in total.\n", + "\n", + "The basis functions for $\\mathcal{Z}(z)$ remain to be decided.\n", + "For the velocity we need homogeneous Dirichlet boundary conditions, and for this\n", + "we use composite Legendre or Chebyshev polynomials" + ] + }, + { + "cell_type": "markdown", + "id": "e5ca554b", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\mathcal{Z}^0_n(z) = \\phi_n(z) - \\phi_{n+2}(z), \\forall \\, n \\in \\boldsymbol{n}^{N_2-2},\n", + "\\label{_auto4} \\tag{4}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "92673646", + "metadata": { + "editable": true + }, + "source": [ + "where $\\phi_n$ is the n'th Legendre or Chebyshev polynomial of the first kind.\n", + "$\\boldsymbol{n}^{N_2-2} = (0, 1, \\ldots, N_2-3)$, and the zero on $\\mathcal{Z}^0$\n", + "is there to indicate the zero value on the boundary.\n", + "\n", + "The pressure basis that comes with no restrictions for the boundary is a\n", + "little trickier. The reason for this has to do with\n", + "inf-sup stability. The obvious choice of basis is the regular Legendre or\n", + "Chebyshev basis, which is denoted as" + ] + }, + { + "cell_type": "markdown", + "id": "80f5311e", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\mathcal{Z}_n(z) = \\phi_n(z), \\forall \\, n \\in \\boldsymbol{n}^{N_2}. \\label{eq:Zn} \\tag{5}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f9b26f94", + "metadata": { + "editable": true + }, + "source": [ + "The problem is that for the natural choice of $n \\in (0, 1, \\ldots, N_2-1)$\n", + "there is a nullspace and one degree of freedom remains unresolved. It turns out\n", + "that the proper choice for the pressure basis is simply ([5](#eq:Zn)) for\n", + "$n \\in \\boldsymbol{n}^{N_2-2}$. (Also remember that we have to fix $\\int_{\\Omega} p dx = 0$.)\n", + "\n", + "With given basis functions we obtain the spaces" + ] + }, + { + "cell_type": "markdown", + "id": "1c89537b", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "V^{N_0} = \\text{span}\\{ \\mathcal{X}_l \\}_{l\\in\\boldsymbol{l}^{N_0}}, \n", + "\\label{_auto5} \\tag{6}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "b9543bc1", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "V^{N_1} = \\text{span}\\{ \\mathcal{Y}_m \\}_{m\\in\\boldsymbol{m}^{N_1}}, \n", + "\\label{_auto6} \\tag{7}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "04e128fa", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "V^{N_2} = \\text{span}\\{ \\mathcal{Z}_n \\}_{n\\in\\boldsymbol{n}^{N_2-2}}, \n", + "\\label{_auto7} \\tag{8}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "fd062fd8", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "V_0^{N_2} = \\text{span}\\{ \\mathcal{Z}^0_n \\}_{n\\in\\boldsymbol{n}^{N_2-2}},\n", + "\\label{_auto8} \\tag{9}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "b3191743", + "metadata": { + "editable": true + }, + "source": [ + "and from these we create two different tensor product spaces" + ] + }, + { + "cell_type": "markdown", + "id": "409bd586", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "W_0^{\\boldsymbol{N}}(\\boldsymbol{x}) = V^{N_0}(x) \\otimes V^{N_1}(y) \\otimes V_0^{N_2}(z), \n", + "\\label{_auto9} \\tag{10}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "07f1eaf9", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "W^{\\boldsymbol{N}}(\\boldsymbol{x}) = V^{N_0}(x) \\otimes V^{N_1}(y) \\otimes V^{N_2}(z).\n", + "\\label{_auto10} \\tag{11}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "98494595", + "metadata": { + "editable": true + }, + "source": [ + "The velocity vector is using a mixed basis, such that we will look for\n", + "solutions $\\boldsymbol{u} \\in [W_0^{\\boldsymbol{N}}]^3 \\, (=W_0^{\\boldsymbol{N}} \\times W_0^{\\boldsymbol{N}} \\times W_0^{\\boldsymbol{N}})$,\n", + "whereas we look for the pressure\n", + "$p \\in W^{\\boldsymbol{N}}$. We now formulate a variational problem using the Galerkin method: Find\n", + "$\\boldsymbol{u} \\in [W_0^{\\boldsymbol{N}}]^3$ and $p \\in W^{\\boldsymbol{N}}$ such that" + ] + }, + { + "cell_type": "markdown", + "id": "4da4b026", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\int_{\\Omega} (\\nabla^2 \\boldsymbol{u} - \\nabla p ) \\cdot \\overline{\\boldsymbol{v}} \\, dx_w = \\int_{\\Omega} \\boldsymbol{f} \\cdot \\overline{\\boldsymbol{v}}\\, dx_w \\quad\\forall \\boldsymbol{v} \\, \\in \\, [W_0^{\\boldsymbol{N}}]^3, \n", + "\\label{_auto11} \\tag{12}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "6be286f4", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "\\int_{\\Omega} \\nabla \\cdot \\boldsymbol{u} \\, \\overline{q} \\, dx_w = \\int_{\\Omega} h \\overline{q} \\, dx_w \\quad\\forall q \\, \\in \\, W^{\\boldsymbol{N}}.\n", + "\\label{_auto12} \\tag{13}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "fb3800cf", + "metadata": { + "editable": true + }, + "source": [ + "Here $dx_w=w_xdxw_ydyw_zdz$ represents a weighted measure, with weights $w_x(x), w_y(y), w_z(z)$.\n", + "Note that it is only Chebyshev polynomials that\n", + "make use of a non-constant weight $w_x=1/\\sqrt{1-x^2}$. The Fourier weights are $w_y=w_z=1/(2\\pi)$\n", + "and the Legendre weight is $w_x=1$.\n", + "The overline in $\\boldsymbol{\\overline{v}}$ and $\\overline{q}$ represents a complex conjugate, which is needed here because\n", + "the Fourier exponentials are complex functions." + ] + }, + { + "cell_type": "markdown", + "id": "a2d2a7f1", + "metadata": { + "editable": true + }, + "source": [ + "### Mixed variational form\n", + "\n", + "\n", + "\n", + "Since we are to solve for $\\boldsymbol{u}$ and $p$ at the same time, we formulate a\n", + "mixed (coupled) problem: find $(\\boldsymbol{u}, p) \\in [W_0^{\\boldsymbol{N}}]^3 \\times W^{\\boldsymbol{N}}$\n", + "such that" + ] + }, + { + "cell_type": "markdown", + "id": "718bc7d5", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "a((\\boldsymbol{u}, p), (\\boldsymbol{v}, q)) = L((\\boldsymbol{v}, q)) \\quad \\forall (\\boldsymbol{v}, q) \\in [W_0^{\\boldsymbol{N}}]^3 \\times W^{\\boldsymbol{N}},\n", + "\\label{_auto13} \\tag{14}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "1004cd02", + "metadata": { + "editable": true + }, + "source": [ + "where bilinear ($a$) and linear ($L$) forms are given as" + ] + }, + { + "cell_type": "markdown", + "id": "eb0cfab3", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " a((\\boldsymbol{u}, p), (\\boldsymbol{v}, q)) = \\int_{\\Omega} (\\nabla^2 \\boldsymbol{u} - \\nabla p) \\cdot \\overline{\\boldsymbol{v}} \\, dx_w + \\int_{\\Omega} \\nabla \\cdot \\boldsymbol{u} \\, \\overline{q} \\, dx_w, \n", + "\\label{_auto14} \\tag{15}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e4cbbbb0", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + " L((\\boldsymbol{v}, q)) = \\int_{\\Omega} \\boldsymbol{f} \\cdot \\overline{\\boldsymbol{v}}\\, dx_w + \\int_{\\Omega} h \\overline{q} \\, dx_w.\n", + "\\label{_auto15} \\tag{16}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "edb90ba3", + "metadata": { + "editable": true + }, + "source": [ + "Note that the bilinear form will assemble to block matrices, whereas the right hand side\n", + "linear form will assemble to block vectors." + ] + }, + { + "cell_type": "markdown", + "id": "fc08f897", + "metadata": { + "editable": true + }, + "source": [ + "## Implementation" + ] + }, + { + "cell_type": "markdown", + "id": "7815b6dd", + "metadata": { + "editable": true + }, + "source": [ + "### Preamble\n", + "\n", + "We will solve the Stokes equations using the [shenfun](https://github.com/spectralDNS/shenfun) Python module. The first thing needed\n", + "is then to import some of this module's functionality\n", + "plus some other helper modules, like [Numpy](https://numpy.org) and [Sympy](https://sympy.org):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b8b3dc6a", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:57.974335Z", + "iopub.status.busy": "2024-05-24T12:36:57.974080Z", + "iopub.status.idle": "2024-05-24T12:36:58.579798Z", + "shell.execute_reply": "2024-05-24T12:36:58.579102Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "import os\n", + "import sys\n", + "import numpy as np\n", + "from sympy import symbols, sin, cos\n", + "from shenfun import *" + ] + }, + { + "cell_type": "markdown", + "id": "cfc9c744", + "metadata": { + "editable": true + }, + "source": [ + "We use `Sympy` for the manufactured solution and `Numpy` for testing." + ] + }, + { + "cell_type": "markdown", + "id": "4cf8185b", + "metadata": { + "editable": true + }, + "source": [ + "### Manufactured solution\n", + "\n", + "\n", + "\n", + "The exact solutions $\\boldsymbol{u}_e(\\boldsymbol{x})$ and $p(\\boldsymbol{x})$ are chosen to satisfy boundary\n", + "conditions, and the right hand sides $\\boldsymbol{f}(\\boldsymbol{x})$ and $h(\\boldsymbol{x})$ are then\n", + "computed exactly using `Sympy`. These exact right hand sides will then be used to\n", + "compute a numerical solution that can be verified against the manufactured\n", + "solution. The chosen solution with computed right hand sides are:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1f71c237", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:58.584520Z", + "iopub.status.busy": "2024-05-24T12:36:58.584015Z", + "iopub.status.idle": "2024-05-24T12:36:58.610477Z", + "shell.execute_reply": "2024-05-24T12:36:58.608925Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "x, y, z = symbols('x,y,z')\n", + "uex = sin(2*y)*(1-z**2)\n", + "uey = sin(2*x)*(1-z**2)\n", + "uez = sin(2*z)*(1-z**2)\n", + "pe = -0.1*sin(2*x)*cos(4*y)\n", + "fx = uex.diff(x, 2) + uex.diff(y, 2) + uex.diff(z, 2) - pe.diff(x, 1)\n", + "fy = uey.diff(x, 2) + uey.diff(y, 2) + uey.diff(z, 2) - pe.diff(y, 1)\n", + "fz = uez.diff(x, 2) + uez.diff(y, 2) + uez.diff(z, 2) - pe.diff(z, 1)\n", + "h = uex.diff(x, 1) + uey.diff(y, 1) + uez.diff(z, 1)" + ] + }, + { + "cell_type": "markdown", + "id": "561baab9", + "metadata": { + "editable": true + }, + "source": [ + "### Tensor product spaces\n", + "\n", + "One-dimensional spaces are created using the [FunctionSpace()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.FunctionSpace) function. A choice of\n", + "polynomials between Legendre or Chebyshev can be made, and the size\n", + "of the domain is given" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "720b3abc", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:58.615823Z", + "iopub.status.busy": "2024-05-24T12:36:58.615488Z", + "iopub.status.idle": "2024-05-24T12:36:58.668880Z", + "shell.execute_reply": "2024-05-24T12:36:58.668494Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "N = (20, 20, 20)\n", + "family = 'Legendre'\n", + "K0 = FunctionSpace(N[0], 'Fourier', dtype='D', domain=(0, 2*np.pi))\n", + "K1 = FunctionSpace(N[1], 'Fourier', dtype='d', domain=(0, 2*np.pi))\n", + "SD = FunctionSpace(N[2], family, bc=(0, 0))\n", + "ST = FunctionSpace(N[2], family)" + ] + }, + { + "cell_type": "markdown", + "id": "a97e7e01", + "metadata": { + "editable": true + }, + "source": [ + "Next the one-dimensional spaces are used to create two tensor product spaces Q = $W^{\\boldsymbol{N}}$\n", + "and TD = $W_0^{\\boldsymbol{N}}$, one vector V = $[W_0^{\\boldsymbol{N}}]^3$ and one mixed\n", + "space VQ = V $\\times$ Q." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "494c44b1", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:58.673299Z", + "iopub.status.busy": "2024-05-24T12:36:58.672989Z", + "iopub.status.idle": "2024-05-24T12:36:58.703106Z", + "shell.execute_reply": "2024-05-24T12:36:58.700404Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "TD = TensorProductSpace(comm, (K0, K1, SD), axes=(2, 0, 1))\n", + "Q = TensorProductSpace(comm, (K0, K1, ST), axes=(2, 0, 1))\n", + "V = VectorSpace(TD)\n", + "VQ = CompositeSpace([V, Q])" + ] + }, + { + "cell_type": "markdown", + "id": "2da1c004", + "metadata": { + "editable": true + }, + "source": [ + "Note that we choose to transform axes in the order $1, 0, 2$. This is to ensure\n", + "that the fully transformed arrays are aligned in the non-periodic direction 2.\n", + "And we need the arrays aligned in this direction, because this is the only\n", + "direction where there are tensor product matrices that are non-diagonal. All\n", + "Fourier matrices are, naturally, diagonal.\n", + "\n", + "Test- and trialfunctions are created much like in a regular, non-mixed,\n", + "formulation. However, one has to create one test- and trialfunction for\n", + "the mixed space, and then split them up afterwards" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8aa77ff2", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:58.708414Z", + "iopub.status.busy": "2024-05-24T12:36:58.708262Z", + "iopub.status.idle": "2024-05-24T12:36:58.712476Z", + "shell.execute_reply": "2024-05-24T12:36:58.711486Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "up = TrialFunction(VQ)\n", + "vq = TestFunction(VQ)\n", + "u, p = up\n", + "v, q = vq" + ] + }, + { + "cell_type": "markdown", + "id": "8ad54e51", + "metadata": { + "editable": true + }, + "source": [ + "With the basisfunctions in place we may assemble the different blocks of the\n", + "final coefficient matrix. Since Legendre is using a constant weight function,\n", + "the equations may also be integrated by parts to obtain a symmetric system:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2ac850ce", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:58.715685Z", + "iopub.status.busy": "2024-05-24T12:36:58.715547Z", + "iopub.status.idle": "2024-05-24T12:36:58.752475Z", + "shell.execute_reply": "2024-05-24T12:36:58.751430Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "if family.lower() == 'chebyshev':\n", + " A = inner(v, div(grad(u)))\n", + " G = inner(v, -grad(p))\n", + "else:\n", + " A = inner(grad(v), -grad(u))\n", + " G = inner(div(v), p)\n", + "D = inner(q, div(u))" + ] + }, + { + "cell_type": "markdown", + "id": "33919078", + "metadata": { + "editable": true + }, + "source": [ + "The assembled subsystems `A, G` and `D` are lists containg the different blocks of\n", + "the complete, coupled matrix. `A` actually contains 6\n", + "tensor product matrices of type [TPMatrix](https://shenfun.readthedocs.io/en/latest/shenfun.html#shenfun.matrixbase.TPMatrix). The first two\n", + "matrices are for vector component zero of the test function `v[0]` and\n", + "trial function `u[0]`, the\n", + "matrices 2 and 3 are for components 1 and the last two are for components\n", + "2. The first two matrices are as such for" + ] + }, + { + "cell_type": "markdown", + "id": "4147ee57", + "metadata": { + "editable": true + }, + "source": [ + "```Python\n", + " A[0:2] = inner(v[0], div(grad(u[0])))\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "4da1d67d", + "metadata": { + "editable": true + }, + "source": [ + "Breaking it down this inner product is mathematically" + ] + }, + { + "cell_type": "markdown", + "id": "e0b99e63", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\label{eq:partialeq1} \\tag{17}\n", + "\\int_{\\Omega} \\boldsymbol{\\overline{v}}[0] \\left(\\frac{\\partial^2 \\boldsymbol{u}[0]}{\\partial x^2} + \\frac{\\partial^2 \\boldsymbol{u}[0]}{\\partial y^2} + \\frac{\\partial^2 \\boldsymbol{u}[0]}{\\partial z^2}\\right) w_x dx w_y dy w_z dz.\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "d7af7337", + "metadata": { + "editable": true + }, + "source": [ + "If we now use test function $\\boldsymbol{v}[0]$" + ] + }, + { + "cell_type": "markdown", + "id": "39548089", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\boldsymbol{v}[0]_{lmn} = \\mathcal{X}_l \\mathcal{Y}_m \\mathcal{Z}_n,\n", + "\\label{_auto16} \\tag{18}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "4e50aac5", + "metadata": { + "editable": true + }, + "source": [ + "and trialfunction" + ] + }, + { + "cell_type": "markdown", + "id": "ab1d7887", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\boldsymbol{u}[0]_{pqr} = \\sum_{p} \\sum_{q} \\sum_{r} \\hat{\\boldsymbol{u}}[0]_{pqr} \\mathcal{X}_p \\mathcal{Y}_q \\mathcal{Z}_r,\n", + "\\label{_auto17} \\tag{19}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f54f63d9", + "metadata": { + "editable": true + }, + "source": [ + "where $\\hat{\\boldsymbol{u}}$ are the unknown degrees of freedom, and then insert these functions\n", + "into ([17](#eq:partialeq1)), then we obtain after\n", + "performing some exact evaluations over the periodic directions" + ] + }, + { + "cell_type": "markdown", + "id": "a02a38ee", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + " \\Big( \\underbrace{-\\left(l^2 \\delta_{lp} + m^2 \\delta_{mq} \\right) \\int_{-1}^{1} \\mathcal{Z}_r(z) \\mathcal{Z}_n(z) w_z dz}_{A[0]} + \\underbrace{\\delta_{lp} \\delta_{mq} \\int_{-1}^{1} \\frac{\\partial^2 \\mathcal{Z}_r(z)}{\\partial z^2} \\mathcal{Z}_n(z) w_z dz}_{A[1]} \\Big) \\hat{\\boldsymbol{u}}[0]_{pqr}.\n", + "\\label{_auto18} \\tag{20}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "31d48e12", + "metadata": { + "editable": true + }, + "source": [ + "Similarly for components 1 and 2 of the test and trial vectors, leading to 6 tensor\n", + "product matrices in total for `A`. Similarly, we get three components of `G`\n", + "and three of `D`.\n", + "\n", + "Eliminating the Fourier diagonal matrices, we are left with block matrices like" + ] + }, + { + "cell_type": "markdown", + "id": "7448136c", + "metadata": { + "editable": true + }, + "source": [ + "$$\n", + "H(l, m) =\n", + " \\begin{bmatrix}\n", + " A[0]+A[1] & 0 & 0 & G[0] \\\\ \n", + " 0 & A[2]+A[3] & 0 & G[1] \\\\ \n", + " 0 & 0 & A[4]+A[5] & G[2] \\\\ \n", + " D[0] & D[1] & D[2] & 0\n", + " \\end{bmatrix}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "6032e16f", + "metadata": { + "editable": true + }, + "source": [ + "Note that there will be one large block matrix $H(l, m)$ for each Fourier\n", + "wavenumber combination $(l, m)$. To solve the problem in the end we will need to\n", + "loop over these wavenumbers and solve the assembled linear systems one by one.\n", + "An example of the block matrix, for $l=m=5$ and $\\boldsymbol{N}=(20, 20, 20)$ is given\n", + "in Fig. [fig:BlockMat](#fig:BlockMat).\n", + "\n", + "In the end we create a block matrix through" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6b446033", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:58.757316Z", + "iopub.status.busy": "2024-05-24T12:36:58.757061Z", + "iopub.status.idle": "2024-05-24T12:36:58.769296Z", + "shell.execute_reply": "2024-05-24T12:36:58.768240Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "M = BlockMatrix(A+G+D)" + ] + }, + { + "cell_type": "markdown", + "id": "2b82783f", + "metadata": { + "editable": true + }, + "source": [ + "The right hand side can easily be assembled since we have already\n", + "defined the functions $\\boldsymbol{f}$ and $h$, see Sec. [Manufactured solution](#sec:mansol)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c00af279", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:58.772359Z", + "iopub.status.busy": "2024-05-24T12:36:58.772110Z", + "iopub.status.idle": "2024-05-24T12:36:58.801098Z", + "shell.execute_reply": "2024-05-24T12:36:58.800368Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "# Get mesh (quadrature points)\n", + "X = TD.local_mesh(True)\n", + "\n", + "# Get f and h on quad points\n", + "fh = Array(VQ, buffer=(fx, fy, fz, h))\n", + "f_, h_ = fh\n", + "\n", + "# Compute inner products\n", + "fh_hat = Function(VQ)\n", + "f_hat, h_hat = fh_hat\n", + "f_hat = inner(v, f_, output_array=f_hat)\n", + "h_hat = inner(q, h_, output_array=h_hat)" + ] + }, + { + "cell_type": "markdown", + "id": "2acb39c6", + "metadata": { + "editable": true + }, + "source": [ + "In the end all that is left is to solve and compare with\n", + "the exact solution." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ce3a912d", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:36:58.804096Z", + "iopub.status.busy": "2024-05-24T12:36:58.803860Z", + "iopub.status.idle": "2024-05-24T12:36:59.489334Z", + "shell.execute_reply": "2024-05-24T12:36:59.488644Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "# Solve problem\n", + "up_hat = M.solve(fh_hat, constraints=((3, 0, 0), (3, N[2]-1, 0)))\n", + "up = up_hat.backward()\n", + "u_, p_ = up\n", + "\n", + "# Exact solution\n", + "ux, uy, uz = Array(V, buffer=(uex, uey, uez))\n", + "pe = Array(Q, buffer=pe)\n", + "\n", + "error = [comm.reduce(np.linalg.norm(ux-u_[0])),\n", + " comm.reduce(np.linalg.norm(uy-u_[1])),\n", + " comm.reduce(np.linalg.norm(uz-u_[2])),\n", + " comm.reduce(np.linalg.norm(pe-p_))]\n", + "print(error)" + ] + }, + { + "cell_type": "markdown", + "id": "1241e64b", + "metadata": { + "editable": true + }, + "source": [ + "Note that solve has a keyword argument\n", + "`constraints=((3, 0, 0), (3, N[2]-1), 0)` that takes care of the restriction\n", + "$\\int_{\\Omega} p \\omega dx = 0$ by indenting the rows in M corresponding to the\n", + "first and last degree of freedom for the pressure. The value $(3, 0, 0)$\n", + "indicates that pressure is\n", + "in block 3 of the block vector solution (the velocity vector holds\n", + "positions 0, 1 and 2), whereas the two zeros ensures that the first dof\n", + "(dof 0) should obtain value 0. The constraint on the highest\n", + "wavenumber `(3, N[2]-1, 0)` is required to get a non-singular\n", + "matrix." + ] + }, + { + "cell_type": "markdown", + "id": "eff53300", + "metadata": { + "editable": true + }, + "source": [ + "## Complete solver\n", + "\n", + "\n", + "A complete solver can be found in demo [Stokes3D.py](https://github.com/spectralDNS/shenfun/blob/master/demo/Stokes3D.py)." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/demos/Tau/tau.ipynb b/docs/demos/Tau/tau.ipynb new file mode 100644 index 00000000..63279e9e --- /dev/null +++ b/docs/demos/Tau/tau.ipynb @@ -0,0 +1,800 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "03e210dc", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "# Demo - The Tau method\n", + "**Mikael Mortensen** (email: `mikaem@math.uio.no`), Department of Mathematics, University of Oslo.\n", + "\n", + "Date: **June 15, 2021**\n", + "\n", + "**Summary.** Shenfun has primarily been developed for the spectral Galerkin method.\n", + "However, there are other methods out there that make use of global basis\n", + "functions and variational principles. One such method, which has a lot in\n", + "common with the spectral Galerkin method, is the Tau method. The\n", + "principle difference between a Tau method and a spectral Galerkin method\n", + "is in the choice of basis functions. The spectral Galerkin method is\n", + "usually defined through function spaces where the boundary conditions\n", + "of the problem are already built in. The tau-method, on the other hand,\n", + "usually considers\n", + "only the orthogonal basis, like pure Chebyshev or Legendre polynomials,\n", + "and derives differentiation matrices for these bases. The boundary conditions\n", + "are then usually fixed through manipulation of a couple of rows of the\n", + "differentiation matrix. In this demo we will show how the original\n", + "tau-method can be easily implemented using [shenfun](https://github.com/spectralDNS/shenfun)." + ] + }, + { + "cell_type": "markdown", + "id": "4032d1d0", + "metadata": { + "editable": true + }, + "source": [ + "## The tau method for Poisson's equation in 1D\n", + "\n", + "Poisson's equation is given on a domain $\\Omega = (-1, 1)$ as" + ] + }, + { + "cell_type": "markdown", + "id": "6860396a", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\nabla^2 u(x) = f(x) \\quad \\text{for }\\, x \\in \\Omega, \\label{eq:poisson} \\tag{1}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "04929b21", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "u(-1)=a, u(1)=b, \\notag\n", + "\\label{_auto1} \\tag{2}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "b722d3fb", + "metadata": { + "editable": true + }, + "source": [ + "where $u(x)$ is the solution, $f(x)$ is a function and $a, b$ are two possibly\n", + "non-zero constants. To solve Eq. ([1](#eq:poisson)) with the tau method we choose either\n", + "Legendre of Chebyshev basis functions $\\phi_k$, and then look for\n", + "solutions" + ] + }, + { + "cell_type": "markdown", + "id": "c9f32970", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(x) = \\sum_{k=0}^{N-1} \\hat{u}_k \\phi_k(x), \\label{eq:u} \\tag{3}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f10d071a", + "metadata": { + "editable": true + }, + "source": [ + "where $N$ is the size of the discretized problem and\n", + "$\\hat{\\mathbf{u}} = \\{\\hat{u}_k\\}_{k=0}^{N-1}$ are the unknown expansion\n", + "coefficients. For this function to satisfy the given boundary conditions, it is necessary\n", + "that" + ] + }, + { + "cell_type": "markdown", + "id": "fe13714e", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "u(-1) = \\sum_{k=0}^{N-1} \\hat{u}_k \\phi_k(-1) = \\sum_{k=0}^{N-1}\\hat{u}_{k}(-1)^k = a,\n", + "\\label{eq:dirichleta} \\tag{4} \n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "e0a0c7d7", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "u(+1) = \\sum_{k=0}^{N-1} \\hat{u}_k \\phi_k(+1) = \\sum_{k=0}^{N-1} \\hat{u}_{k} = b,\n", + "\\label{eq:dirichletb} \\tag{5}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "c7ad046f", + "metadata": { + "editable": true + }, + "source": [ + "where we have use that $\\phi_k(1) = 1$ and $\\phi_k(-1)=(-1)^k$ for $k=0,1, \\ldots, N-1$,\n", + "for either Chebyshev or Legendre polynomials $\\phi_k$. This gives two equations\n", + "for the $N$ unknowns in $\\{\\hat{u}_k\\}_{k=0}^{N-1}$.\n", + "We will now use variational principles, like in the Galerkin method, in order to\n", + "derive equations that can be used to close the remaining $N-2$ unknowns.\n", + "To this end we multiply Poisson's equation by a\n", + "test function $v$, a weight $w$, and integrate over the domain" + ] + }, + { + "cell_type": "markdown", + "id": "389e6324", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\int_{-1}^1 \\nabla^2 u \\, v \\, w\\, dx = \\int_{-1}^1 f \\, v\\, w\\, dx. \\label{eq:varform} \\tag{6}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "29046d76", + "metadata": { + "editable": true + }, + "source": [ + "The weight function depends on the choice of basis functions. For Chebyshev\n", + "it will be $1/\\sqrt{1-x^2}$, whereas it is unity for Legendre.\n", + "\n", + "Finally, we insert the trial function $u=\\sum_{j=0}^{N-1}\\hat{u}_j \\phi_j$ and\n", + "the test function $v=\\phi_k$, to get" + ] + }, + { + "cell_type": "markdown", + "id": "c390a448", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "\\int_{-1}^1 \\nabla^2 \\sum_{j=0}^{N-1} \\phi_j \\, \\, \\phi_k \\, w\\, dx \\hat{u}_j = \\int_{-1}^1 f \\, \\phi_k\\, w\\, dx. \\label{eq:varform2} \\tag{7}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "9d4a27c7", + "metadata": { + "editable": true + }, + "source": [ + "This problem can be reformulated as a linear algebra problem," + ] + }, + { + "cell_type": "markdown", + "id": "1dd2760c", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation}\n", + "a_{kj} \\hat{u}_j = \\tilde{f}_k, \n", + "\\label{_auto2} \\tag{8}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "f79f7562", + "metadata": { + "editable": true + }, + "source": [ + "\n", + "\n", + "\n", + "$$\n", + "\\begin{equation} \n", + "A \\hat{\\mathbf{{u}}} = \\tilde{\\mathbf{{f}}}.\n", + "\\label{_auto3} \\tag{9}\n", + "\\end{equation}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "id": "3949a751", + "metadata": { + "editable": true + }, + "source": [ + "However, the matrix $A\\in \\mathbb{R}^{N \\times N}$ is singular because it\n", + "contains two zero rows. These two rows are used to implement the two boundary\n", + "conditions. Setting $a_{N-2, j}=1$ and\n", + "$a_{N-1, j}= (-1)^j$ for $j=0, 1, \\ldots, N-1$, and also fixing\n", + "the right hand sides $\\tilde{f}_{N-2}=a$ and $\\tilde{f}_{N-1}=b$, the\n", + "two boundary conditions will be satisfied." + ] + }, + { + "cell_type": "markdown", + "id": "fc08f897", + "metadata": { + "editable": true + }, + "source": [ + "## Implementation" + ] + }, + { + "cell_type": "markdown", + "id": "6f3913f0", + "metadata": { + "editable": true + }, + "source": [ + "### Preamble\n", + "\n", + "We will solve Poisson's equation using the [shenfun](https://github.com/spectralDNS/shenfun) Python module. The first thing needed\n", + "is then to import some of this module's functionality\n", + "plus some other helper modules, like [Numpy](https://numpy.org) and [Sympy](https://sympy.org), and the [scipy.sparse](https://docs.scipy.org/doc/scipy/reference/sparse.html)\n", + "for handeling sparse matrices:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d2f50904", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:57.417744Z", + "iopub.status.busy": "2024-05-24T12:37:57.417107Z", + "iopub.status.idle": "2024-05-24T12:37:57.994366Z", + "shell.execute_reply": "2024-05-24T12:37:57.993910Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "from shenfun import inner, div, grad, TestFunction, TrialFunction, Function, \\\n", + " project, Dx, Array, FunctionSpace, dx\n", + "import numpy as np\n", + "import scipy.sparse as scp\n", + "from sympy import symbols, cos, sin, exp, lambdify" + ] + }, + { + "cell_type": "markdown", + "id": "40fcaf01", + "metadata": { + "editable": true + }, + "source": [ + "We use `Sympy` for a manufactured solution and `Numpy` for testing.\n", + "The exact manufactured solution $u_e(x)$ and the right hand side\n", + "$f_e(x)$ are created using `Sympy` as follows" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b7f66a59", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:57.997044Z", + "iopub.status.busy": "2024-05-24T12:37:57.996688Z", + "iopub.status.idle": "2024-05-24T12:37:58.002233Z", + "shell.execute_reply": "2024-05-24T12:37:58.001879Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "x = symbols(\"x\")\n", + "ue = sin(4*np.pi*x)\n", + "fe = ue.diff(x, 2)" + ] + }, + { + "cell_type": "markdown", + "id": "739884be", + "metadata": { + "editable": true + }, + "source": [ + "Note that we compute the right hand side function `fe` that corresponds to\n", + "the manufactured solution `ue`." + ] + }, + { + "cell_type": "markdown", + "id": "377d957f", + "metadata": { + "editable": true + }, + "source": [ + "### Discretization\n", + "\n", + "We create a basis with a given number of basis functions," + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "12458aa3", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:58.004548Z", + "iopub.status.busy": "2024-05-24T12:37:58.004432Z", + "iopub.status.idle": "2024-05-24T12:37:58.020773Z", + "shell.execute_reply": "2024-05-24T12:37:58.017891Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "N = 32\n", + "T = FunctionSpace(N, 'Chebyshev')\n", + "#T = FunctionSpace(N, 'Legendre')" + ] + }, + { + "cell_type": "markdown", + "id": "736218b2", + "metadata": { + "editable": true + }, + "source": [ + "Note that we can either choose a Legendre or a Chebyshev basis. The\n", + "remaining code will work either way." + ] + }, + { + "cell_type": "markdown", + "id": "37f9d1b5", + "metadata": { + "editable": true + }, + "source": [ + "### Variational formulation\n", + "\n", + "The variational problem ([6](#eq:varform)) can be assembled using `shenfun`'s\n", + "[TrialFunction](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.TrialFunction), [TestFunction](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.TestFunction) and [inner()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.inner.inner) functions." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fa34ca27", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:58.025759Z", + "iopub.status.busy": "2024-05-24T12:37:58.025521Z", + "iopub.status.idle": "2024-05-24T12:37:58.034151Z", + "shell.execute_reply": "2024-05-24T12:37:58.033814Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u = TrialFunction(T)\n", + "v = TestFunction(T)\n", + "# Assemble differentiation matrix\n", + "A = inner(v, div(grad(u)))\n", + "# Assemble right hand side\n", + "fj = Array(T, buffer=fe)\n", + "f_hat = Function(T)\n", + "f_hat = inner(v, fj, output_array=f_hat)" + ] + }, + { + "cell_type": "markdown", + "id": "a10787e4", + "metadata": { + "editable": true + }, + "source": [ + "Note that the `sympy` function `fe` is be used to initialize the [Array](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Array)\n", + "`fj`, because an Array\n", + "is required as input to the [inner()](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.inner.inner) function. An\n", + "[Array](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Array) contains the solution evaluated on the\n", + "quadrature mesh. A [Function](https://shenfun.readthedocs.io/en/latest/shenfun.forms.html#shenfun.forms.arguments.Function) represents a global\n", + "expansion, like Eq. ([3](#eq:u)), and its values are the\n", + "expansion coefficients $\\{\\hat{u}_{k}\\}_{k=0}^{N-1}$." + ] + }, + { + "cell_type": "markdown", + "id": "4a47d951", + "metadata": { + "editable": true + }, + "source": [ + "### Fix boundary conditions\n", + "\n", + "We fix two rows of the differentiation matrix in order to satisfy\n", + "Eqs. ([4](#eq:dirichleta)) and ([5](#eq:dirichletb))." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7da80e99", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:58.038581Z", + "iopub.status.busy": "2024-05-24T12:37:58.038166Z", + "iopub.status.idle": "2024-05-24T12:37:58.059598Z", + "shell.execute_reply": "2024-05-24T12:37:58.054103Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "A = A.diags('lil')\n", + "A[-2] = (-1)**np.arange(N)\n", + "A[-1] = np.ones(N)\n", + "A = A.tocsc()\n", + "f_hat[-2] = ue.subs(x, T.domain[0])\n", + "f_hat[-1] = ue.subs(x, T.domain[1])" + ] + }, + { + "cell_type": "markdown", + "id": "0e3b7fe8", + "metadata": { + "editable": true + }, + "source": [ + "Note that the last two lines uses evaluation of the sympy function\n", + "`ue` at the borders of the domain. Implemented like this it is\n", + "easy to change to a nonstandard domain size.\n", + "The sparsity pattern of the matrix A is now modified\n", + "with the typical tau-lines that we can visualize using [plotly](https://plotly.com/)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "454473fc", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:58.065264Z", + "iopub.status.busy": "2024-05-24T12:37:58.065121Z", + "iopub.status.idle": "2024-05-24T12:37:58.588358Z", + "shell.execute_reply": "2024-05-24T12:37:58.587519Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "import plotly.express as px\n", + "z = np.where(abs(A.toarray()) > 1e-6, 0, 1).astype(bool)\n", + "fig = px.imshow(z, binary_string=True)\n", + "fig.show()" + ] + }, + { + "cell_type": "markdown", + "id": "5a1ae665", + "metadata": { + "editable": true + }, + "source": [ + "### Solve linear equations\n", + "\n", + "Finally, solve the linear equation system and transform the solution from the spectral\n", + "$\\{\\hat{u}_k\\}_{k=0}^{N-1}$ vector to the real space $\\{u(x_j)\\}_{j=0}^{N-1}$\n", + "and then check how the solution corresponds with the exact solution $u_e$.\n", + "To this end we compute the $L_2$-errornorm using the `shenfun` function\n", + "[dx()](https://shenfun.readthedocs.io/en/latest/shenfun.utilities.html#shenfun.utilities.dx)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c55f7862", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:58.600186Z", + "iopub.status.busy": "2024-05-24T12:37:58.599966Z", + "iopub.status.idle": "2024-05-24T12:37:58.615932Z", + "shell.execute_reply": "2024-05-24T12:37:58.615360Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "u_hat = Function(T)\n", + "u_hat[:] = scp.linalg.spsolve(A, f_hat)\n", + "uj = u_hat.backward()\n", + "ua = Array(T, buffer=ue)\n", + "\n", + "print(\"Error=%2.16e\" %(np.sqrt(dx((uj-ua)**2))))" + ] + }, + { + "cell_type": "markdown", + "id": "3c8908a6", + "metadata": { + "editable": true + }, + "source": [ + "### Convergence test\n", + "\n", + "To do a convergence test we will now create a function `main`, that takes the\n", + "number of quadrature points as parameter, and prints out\n", + "the error." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c5417c91", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:58.618506Z", + "iopub.status.busy": "2024-05-24T12:37:58.618386Z", + "iopub.status.idle": "2024-05-24T12:37:58.621491Z", + "shell.execute_reply": "2024-05-24T12:37:58.620785Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "def main(N, family='Chebyshev'):\n", + " T = FunctionSpace(N, family=family)\n", + " u = TrialFunction(T)\n", + " v = TestFunction(T)\n", + "\n", + " # Get f on quad points\n", + " fj = Array(T, buffer=fe)\n", + "\n", + " # Compute right hand side of Poisson's equation\n", + " f_hat = Function(T)\n", + " f_hat = inner(v, fj, output_array=f_hat)\n", + "\n", + " # Get left hand side of Poisson's equation\n", + " A = inner(v, div(grad(u)))\n", + " A = A.diags('lil')\n", + " A[-2] = (-1)**np.arange(N)\n", + " A[-1] = np.ones(N)\n", + " A = A.tocsc()\n", + " f_hat[-2] = ue.subs(x, T.domain[0])\n", + " f_hat[-1] = ue.subs(x, T.domain[1])\n", + "\n", + " u_hat = Function(T)\n", + " u_hat[:] = scp.linalg.spsolve(A, f_hat)\n", + " uj = u_hat.backward()\n", + "\n", + " # Compare with analytical solution\n", + " ua = Array(T, buffer=ue)\n", + " l2_error = np.linalg.norm(uj-ua)\n", + " return l2_error" + ] + }, + { + "cell_type": "markdown", + "id": "8199b9c0", + "metadata": { + "editable": true + }, + "source": [ + "For example, we find the error of a Chebyshev discretization\n", + "using 12 quadrature points as" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e2444fa7", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:58.625346Z", + "iopub.status.busy": "2024-05-24T12:37:58.625172Z", + "iopub.status.idle": "2024-05-24T12:37:58.632543Z", + "shell.execute_reply": "2024-05-24T12:37:58.632211Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "main(12, 'Chebyshev')" + ] + }, + { + "cell_type": "markdown", + "id": "e42b9a11", + "metadata": { + "editable": true + }, + "source": [ + "To get the convergence we call `main` for a list\n", + "of $N=[12, 16, \\ldots, 48]$, and collect the errornorms in\n", + "arrays to be plotted. The error can be plotted using\n", + "[matplotlib](https://matplotlib.org)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1215522e", + "metadata": { + "editable": true, + "execution": { + "iopub.execute_input": "2024-05-24T12:37:58.634874Z", + "iopub.status.busy": "2024-05-24T12:37:58.634740Z", + "iopub.status.idle": "2024-05-24T12:37:59.519571Z", + "shell.execute_reply": "2024-05-24T12:37:59.516997Z" + }, + "tags": [ + "thebe-init" + ] + }, + "outputs": [], + "source": [ + "%matplotlib inline\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "N = range(12, 50, 4)\n", + "error = {}\n", + "for basis in ('legendre', 'chebyshev'):\n", + " error[basis] = []\n", + " for i in range(len(N)):\n", + " errN = main(N[i], basis)\n", + " error[basis].append(errN)\n", + "\n", + "plt.figure(figsize=(6, 4))\n", + "for basis, col in zip(('legendre', 'chebyshev'), ('r', 'b')):\n", + " plt.semilogy(N, error[basis], col, linewidth=2)\n", + "plt.title('Convergence of Tau Poisson solvers 1D')\n", + "plt.xlabel('N')\n", + "plt.ylabel('Error norm')\n", + "plt.legend(('Legendre', 'Chebyshev'))\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "09bd3e41", + "metadata": { + "editable": true + }, + "source": [ + "The spectral convergence is evident and we can see that\n", + "after $N=40$ roundoff errors dominate as the errornorm trails off around $10^{-14}$." + ] + }, + { + "cell_type": "markdown", + "id": "914025e4", + "metadata": { + "editable": true + }, + "source": [ + "## Complete solver\n", + "\n", + "\n", + "A complete solver, that can use either Legendre or Chebyshev bases, chosen as a\n", + "command-line argument, can also be found [here](https://github.com/spectralDNS/shenfun/blob/master/demo/poisson1D_tau.py).\n", + "\n", + "" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/source/functions.ipynb b/docs/source/functions.ipynb index 33808893..701a1666 100644 --- a/docs/source/functions.ipynb +++ b/docs/source/functions.ipynb @@ -69,14 +69,16 @@ "execution_count": 1, "id": "f17eb498", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:50.074095Z", - "iopub.status.busy": "2024-02-19T13:47:50.073828Z", - "iopub.status.idle": "2024-02-19T13:47:50.913544Z", - "shell.execute_reply": "2024-02-19T13:47:50.912771Z" - } + "iopub.execute_input": "2024-05-24T12:37:24.305451Z", + "iopub.status.busy": "2024-05-24T12:37:24.305372Z", + "iopub.status.idle": "2024-05-24T12:37:24.897648Z", + "shell.execute_reply": "2024-05-24T12:37:24.897199Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [], "source": [ @@ -101,14 +103,16 @@ "execution_count": 2, "id": "b77b3fc9", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:50.917037Z", - "iopub.status.busy": "2024-02-19T13:47:50.916634Z", - "iopub.status.idle": "2024-02-19T13:47:50.920164Z", - "shell.execute_reply": "2024-02-19T13:47:50.919412Z" - } + "iopub.execute_input": "2024-05-24T12:37:24.900143Z", + "iopub.status.busy": "2024-05-24T12:37:24.899852Z", + "iopub.status.idle": "2024-05-24T12:37:24.901950Z", + "shell.execute_reply": "2024-05-24T12:37:24.901605Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [], "source": [ @@ -132,14 +136,16 @@ "execution_count": 3, "id": "8ec4daad", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:50.923125Z", - "iopub.status.busy": "2024-02-19T13:47:50.922882Z", - "iopub.status.idle": "2024-02-19T13:47:50.926517Z", - "shell.execute_reply": "2024-02-19T13:47:50.925967Z" - } + "iopub.execute_input": "2024-05-24T12:37:24.903967Z", + "iopub.status.busy": "2024-05-24T12:37:24.903849Z", + "iopub.status.idle": "2024-05-24T12:37:24.906523Z", + "shell.execute_reply": "2024-05-24T12:37:24.905958Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [], "source": [ @@ -189,14 +195,16 @@ "execution_count": 4, "id": "761f5f53", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:50.929251Z", - "iopub.status.busy": "2024-02-19T13:47:50.929055Z", - "iopub.status.idle": "2024-02-19T13:47:50.932325Z", - "shell.execute_reply": "2024-02-19T13:47:50.931883Z" - } + "iopub.execute_input": "2024-05-24T12:37:24.909043Z", + "iopub.status.busy": "2024-05-24T12:37:24.908934Z", + "iopub.status.idle": "2024-05-24T12:37:24.911054Z", + "shell.execute_reply": "2024-05-24T12:37:24.910669Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [], "source": [ @@ -221,22 +229,24 @@ "execution_count": 5, "id": "b9ad36a9", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:50.934594Z", - "iopub.status.busy": "2024-02-19T13:47:50.934409Z", - "iopub.status.idle": "2024-02-19T13:47:50.947211Z", - "shell.execute_reply": "2024-02-19T13:47:50.946640Z" - } + "iopub.execute_input": "2024-05-24T12:37:24.913202Z", + "iopub.status.busy": "2024-05-24T12:37:24.913100Z", + "iopub.status.idle": "2024-05-24T12:37:24.921840Z", + "shell.execute_reply": "2024-05-24T12:37:24.921468Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[-6.93889390e-17 -5.47405982e-17 -1.82237827e-18 1.00000000e+00\n", - " 1.96261557e-17 -3.33066907e-16 1.49457239e-16 -2.93881977e-16]\n" + "[-8.32667268e-17 -5.47405982e-17 2.38204300e-17 1.00000000e+00\n", + " 0.00000000e+00 -3.20040096e-16 1.60078838e-16 -2.93881977e-16]\n" ] } ], @@ -271,10 +281,10 @@ }, "source": [ "\n", - "
\n", + "\n", "\n", "$$\n", - "(u_h - u, v)^{N}_w = 0 \\quad \\forall v \\in T, \\label{eq:proj1} \\tag{1}\n", + "(u_h - u, v)^{N}_w = 0 \\quad \\forall v \\in T, \\label{eq:proj1} \\tag{1} \n", "$$" ] }, @@ -411,14 +421,16 @@ "execution_count": 6, "id": "6b3431b4", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:50.950753Z", - "iopub.status.busy": "2024-02-19T13:47:50.950522Z", - "iopub.status.idle": "2024-02-19T13:47:50.954325Z", - "shell.execute_reply": "2024-02-19T13:47:50.953799Z" - } + "iopub.execute_input": "2024-05-24T12:37:24.925102Z", + "iopub.status.busy": "2024-05-24T12:37:24.924966Z", + "iopub.status.idle": "2024-05-24T12:37:24.928595Z", + "shell.execute_reply": "2024-05-24T12:37:24.927405Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [], "source": [ @@ -443,21 +455,23 @@ "execution_count": 7, "id": "9a55e6d5", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:50.956650Z", - "iopub.status.busy": "2024-02-19T13:47:50.956470Z", - "iopub.status.idle": "2024-02-19T13:47:50.971292Z", - "shell.execute_reply": "2024-02-19T13:47:50.970532Z" - } + "iopub.execute_input": "2024-05-24T12:37:24.931772Z", + "iopub.status.busy": "2024-05-24T12:37:24.931577Z", + "iopub.status.idle": "2024-05-24T12:37:24.960845Z", + "shell.execute_reply": "2024-05-24T12:37:24.960343Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "37\n" + "45\n" ] } ], @@ -485,21 +499,23 @@ "execution_count": 8, "id": "d6cdcdb9", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:50.973843Z", - "iopub.status.busy": "2024-02-19T13:47:50.973655Z", - "iopub.status.idle": "2024-02-19T13:47:50.976913Z", - "shell.execute_reply": "2024-02-19T13:47:50.976395Z" - } + "iopub.execute_input": "2024-05-24T12:37:24.964705Z", + "iopub.status.busy": "2024-05-24T12:37:24.964158Z", + "iopub.status.idle": "2024-05-24T12:37:24.967976Z", + "shell.execute_reply": "2024-05-24T12:37:24.967525Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "37\n" + "45\n" ] } ], @@ -524,14 +540,16 @@ "execution_count": 9, "id": "f3f6e277", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:50.979208Z", - "iopub.status.busy": "2024-02-19T13:47:50.979025Z", - "iopub.status.idle": "2024-02-19T13:47:51.014287Z", - "shell.execute_reply": "2024-02-19T13:47:51.013761Z" - } + "iopub.execute_input": "2024-05-24T12:37:24.970095Z", + "iopub.status.busy": "2024-05-24T12:37:24.970019Z", + "iopub.status.idle": "2024-05-24T12:37:25.000706Z", + "shell.execute_reply": "2024-05-24T12:37:24.999982Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { @@ -566,14 +584,16 @@ "execution_count": 10, "id": "f909dbb0", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:51.016776Z", - "iopub.status.busy": "2024-02-19T13:47:51.016584Z", - "iopub.status.idle": "2024-02-19T13:47:51.030924Z", - "shell.execute_reply": "2024-02-19T13:47:51.030480Z" - } + "iopub.execute_input": "2024-05-24T12:37:25.004338Z", + "iopub.status.busy": "2024-05-24T12:37:25.004225Z", + "iopub.status.idle": "2024-05-24T12:37:25.015645Z", + "shell.execute_reply": "2024-05-24T12:37:25.015180Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { @@ -605,19 +625,21 @@ "execution_count": 11, "id": "24ce622f", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:51.033552Z", - "iopub.status.busy": "2024-02-19T13:47:51.033365Z", - "iopub.status.idle": "2024-02-19T13:47:51.628468Z", - "shell.execute_reply": "2024-02-19T13:47:51.627423Z" - } + "iopub.execute_input": "2024-05-24T12:37:25.017665Z", + "iopub.status.busy": "2024-05-24T12:37:25.017590Z", + "iopub.status.idle": "2024-05-24T12:37:25.314535Z", + "shell.execute_reply": "2024-05-24T12:37:25.312802Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { "data": { - "image/png": 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", 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YvJhAnDbinBciIiLrMXgxATMvREREqcPgxQTMvBAREaUOgxcTMPNCRESUOgxeTOBi5oWIiChlGLyYwM3MCxERUcoweDGBMueFQ+qIiIgsx+DFBO7oeoAODqkjIiKyHIMXE7jSomUjZl6IiIgsx+DFBG6uByAiIkoZBi8mUI5KM/NCRERkOQYvJnCx54WIiChlGLyYwM2eFyIiopRh8GICkXlhzwsREZH1GLyYQGReOph5ISIishyDFxMw80JERJQ6DF5MwMwLERFR6jB4MUF85kWW5X6+GiIiorMbgxcTiDkvYRkIhBi8EBERWYnBiwnEYkaAfS9ERERWY/BiAlE2AgB/kH0vREREVmLwYgJJkmJTdgPMvBAREVmJwYtJYk27zLwQERFZicGLSWLHpZl5ISIishKDF5OIpl1mXoiIiKzF4MUk4rg0lzMSERFZi8GLSdzRzEsHj0oTERFZisGLSZh5ISIiSg0GLyZxp3E5IxERUSoweDEJMy9ERESpweDFJOx5ISIiSg0GLyZh5oWIiCg1GLyYJDZhl5kXIiIiKzF4MUlswi4zL0RERFZKSfDy1FNPYeTIkXC73SgvL8eGDRtUfd37778Ph8OBadOmWXuBJmDmhYiIKDUsD15eeeUVPPDAA3jsscewdetWzJkzB9dddx0qKyt7/Tqv14sFCxbgyiuvtPoSTeFi5oWIiCglLA9eli1bhoULF+LOO+/ExIkTsXz5cpSWlmLFihW9ft3dd9+N22+/HTNnzrT6Ek3BzAsREVFqWBq8dHZ2oqKiAnPnzu1y+9y5c7Fx48akX/f73/8ehw4dwve///0+H8Pv98Pn83X56A/seSEiIkoNS4OX+vp6hEIhFBcXd7m9uLgYtbW1Cb/mwIEDeOSRR/DSSy/B4XD0+RhLly6Fx+NRPkpLS025dq2YeSEiIkqNlDTsSpLU5f/LstzjNgAIhUK4/fbb8YMf/ADjxo1T9b2XLFkCr9erfFRVVZlyzVrFghdmXoiIiKzUd2rDgMLCQtjt9h5Zlrq6uh7ZGABobm7G5s2bsXXrVtx7770AgHA4DFmW4XA48NZbb+GKK67o8jUulwsul8u6H0KlWNmImRciIiIrWZp5cTqdKC8vx5o1a7rcvmbNGsyaNavH/XNycrBjxw5s27ZN+Vi0aBHGjx+Pbdu24cILL7Tycg1h5oWIiCg1LM28AMDixYsxf/58zJgxAzNnzsTvfvc7VFZWYtGiRQAiZZ/q6mr84Q9/gM1mw+TJk7t8fVFREdxud4/bzzRs2CUiIkoNy4OX2267DQ0NDXjiiSdQU1ODyZMnY9WqVSgrKwMA1NTU9DnzZSBgwy4REVFqSLIsy/19EWby+XzweDzwer3IyclJ2eN+UtWEm3/7PobmpuP9R67o+wuIiIhIoeX1m7uNTOJKY+aFiIgoFRi8mMTliPS8+NnzQkREZCkGLyZxRzMvHcy8EBERWYrBi0lE5iUQkhEKn1VtRERERGcUBi8mEZkXgH0vREREVmLwYhKReQHY90JERGQlBi8msdskpNkj+5rY90JERGQdBi8m4okjIiIi6zF4MRH3GxEREVmPwYuJuFmaiIjIegxeTCQyLwxeiIiIrMPgxUSuaOaFZSMiIiLrMHgxEXteiIiIrMfgxUTKigCWjYiIiCzD4MVEylFpZl6IiIgsw+DFRLGyETMvREREVmHwYqLYUWlmXoiIiKzC4MVEzLwQERFZj8GLiZh5ISIish6DFxNZlXnxtgdwpL7V1O9JREQ0UDF4MZHIvJi9mPEbL23B1cvWYVtVk6nfl4iIaCBi8GIiqzIvO094EQzLeHrtIVO/LxER0UDE4MVEruiQOjMzL4FQGE1tAQDAm7trcZTlIyIi+pRj8GIipWHXxMzL6dZO5b9lGXjuvcOmfW8iIqKBiMGLiZSykYmZl/oWPwDAJkX+/183H0dD9DYiIqJPIwYvJrIi89LQEsm8jCvOxpShHviDYfzpw0rTvj8REdFAw+DFRFZmXgqzXPj6JaMAAH/44CiXPxIR0acWgxcTWbGYUWReCrKcuH7yYAzNTUdDaydWbqk27TGIiIgGEgYvJhKnjczMisRnXhx2GxbOHgkAeG7DYYTDsmmPQ0RENFAweDGRFZmX+rjMCwDcen4pctwOHK5vxbr9p0x7HCIiooGCwYuJ3FZmXjJdAIAslwNXTSwGAOyp9Zn2OERERAMFgxcTWdLz0hoNXrKdym2F2ZFApjFuBgwREdGnBYMXE1mReVEadqOZFwDIy4gEMqdbA6Y9DhER0UDB4MVE8ZkXWTbeTCvLshK8iGwLAORnpgEAGtuYeSEiok8fBi8mEqeNAKAzZLx05OsIKt+nIDNWNoplXhi8EBHRpw+DFxO5o5kXAOgwYVCdaNbNdjmU6b0AkB8NZJh5ISKiTyMGLyZKs0uQojuI/CasCGjodkxayMtk5oWIiD69UhK8PPXUUxg5ciTcbjfKy8uxYcOGpPdduXIlrr76agwaNAg5OTmYOXMm3nzzzVRcpmGSJCnZFzNWBMQPqIsnykbNHUEETChPJfK3iuN4teK4Jd+biIjICMuDl1deeQUPPPAAHnvsMWzduhVz5szBddddh8rKxMsF169fj6uvvhqrVq1CRUUFLr/8ctx4443YunWr1ZdqCtH3Yk7mJRK8dM+8eNLTlAxPU5v5J468bQF852+f4Ft//QR1vg7Tvz8REZERlgcvy5Ytw8KFC3HnnXdi4sSJWL58OUpLS7FixYqE91++fDm+853v4Pzzz8fYsWPxk5/8BGPHjsUbb7xh9aWaQmRezOh5OaWUjbpmXuw2Cbnp1p04Ot7UBrF54MMjp03//kREREZYGrx0dnaioqICc+fO7XL73LlzsXHjRlXfIxwOo7m5Gfn5+Qk/7/f74fP5unz0JysyL93LRoC1fS8nmmLZlg8PN5j+/YmIiIywNHipr69HKBRCcXFxl9uLi4tRW1ur6nv88pe/RGtrK2699daEn1+6dCk8Ho/yUVpaavi6jXA5osGLCZkXZcZLt7IRAORH+16smLJ7oqld+W8GL0REdKZJScOuJBo0omRZ7nFbIi+//DIef/xxvPLKKygqKkp4nyVLlsDr9SofVVVVplyzXuJIc4cJmZdkDbtAXObFgrJRfPBy+FQr+16IiOiMYmnwUlhYCLvd3iPLUldX1yMb090rr7yChQsX4n//939x1VVXJb2fy+VCTk5Ol4/+ZGrmpVWsBkht5qU6LngB2PdCRERnFkuDF6fTifLycqxZs6bL7WvWrMGsWbOSft3LL7+Mr3zlK/jzn/+MefPmWXmJpjM189IsljL21vNi/mkjkXkZlpcOgKUjIiI6s1heNlq8eDGee+45vPDCC9izZw8efPBBVFZWYtGiRQAiZZ8FCxYo93/55ZexYMEC/PKXv8RFF12E2tpa1NbWwuv1Wn2ppjAr89IRCKHZHwQAFGYmCF4yrDttJBp2Pzt9KIDUBi/vHajH+v2nUvZ4REQ08FgevNx2221Yvnw5nnjiCUybNg3r16/HqlWrUFZWBgCoqanpMvPlmWeeQTAYxDe+8Q0MGTJE+bj//vutvlRTxC9nNEKUjNLsEnLSHT0+n2fRioBAKIyTzZHg5ebpQyFJqet78XUE8LUXP8ad/7MZ3nZuzCYiosR6vipa4J577sE999yT8HMvvvhil/+/du1a6y/IQuKodEfAWNlIGVCX6UrY3GxVz0uttwOyDDgdNowqzMQ5Q3Kw64QPHx45jZumlpj6WN3trPYqiygPn2rB9OF5lj4eERENTNxtZDLTMi9J9hoJVp02Es26Q3PTIUkSLhpVACA1paOd1bHS4KFTrZY/HhERDUwMXkzmNinzcqqXY9JA3GZpkxt2RbNuSa4bAFIavGw/HgteDp9qsfzxiIhoYGLwYrJUZV5E2ajFHzRlmq+gBC+eyEmjC0bkp6zvJT7zcpiZFyIiSoLBi8nMyryIAXWDkmRest0O2G2RXhgzlzNWR08aleRGghdPRhrOGRKZnWPlvBdfRwBHG9qU/38oBZmX5987gut/tYFD+IiIBhgGLyYzL/OSeKO0YLNJynFpM/cbnYjreRFSUToSWZcMZ+T5O9bQhmDI+KC/3vzxg6PYXePDqh01lj4OERGZi8GLyZQ5LwaDl3plr1HizAsA5Fpw4ijW89I/wcvsMYVwp9nQGQrjeGN7H1+lX0cghGOnI5mebVVNlj0OERGZj8GLyZQJuyaVjQp6CV6U49ImlY1kWY5lXvJiwUsq+l52VEe2gU8tzcWIgkwAwOF660pHh061QJYj/83ghYhoYGHwYjKzMi9iSF2ijdJCXma0bGTScWlfexCtnZGga4jHrdyeir4XkXmZPNSD0UVZAKxt2j1YFwuMjja0ocmCScWJeNsD+Mxv38eyNftT8nhERGcjBi8mMyPzEg7LSh9Lb2Wj2HFpc154jze1RR/TqfwcgpWlI19HAEfqI4HKlKEejC6MZF6sbNo9cLLr905V9uXfe05iW1UTfv/+Ecgi9UNERJoweDGZGZmXpvYAQuHIC1t+go3SQl6GWM5oTvByottJo3hWBi8i6zI0Nx35mU6MGhTJvFg5qO5AXTMAwBE9sZWq4GXzsUYAQHNHECe8POVERKQHgxeTifUAfgOZF9HvkpuRhjR78j+ifJP3G3Wf8RLPyr4XEbxMGeoBAIweZH3Z6EC0bHTZ+CIAqQteKo42Kv+954QvJY9JRHS2YfBiMlFuMZJ5UZp1e8m6AFZkXnqeNBKs7HsRzbpThkWCl5GDImWj+ha/JQsa/cEQjkVnynx+xjAAwCdVTZaXcbztAeyPZnwAYG8tgxciIj0YvJhMKRsZyrz03e8CmJ95qe62GqA7UTr62OTgJb5ZFwCyXA4U50R+divWBBypb0UoLCPb5cBl4wfB6bChsS2gBDRW2VLZiPj4aE9Nc/I7D1AvfXQM//3mXvbzEJGlGLyYTGnYNZB5aehjr5GQGx1SZ9Z+o0QD6uKNK46Uc443mvci371ZVxhtYd+LaNYdW5wFl8OOSSWRjJLVpaMt0X4XcZJrz1mWeekIhPD9f+zCb989hC2VjX1/ARGRTgxeTGZO5kUEL72XjUTmJRUNuwAwKDsSTNU1+015PADYFS0ZiWZdYVS0dGRF5kX0u4wtygYATCvNBWB98LI52u/yxQuGAwCO1reivdO8vVT9bXeND8Foo/mGA/X9fDVEdDZj8GIyczIvYilj75mXvOiLfXsgZHgoXiAUxsnm3oOXouxIxsDM4GVHdROArlkXwNqm3YPRvpOx0UxSKoKXQCisfP9rJw9GYZYTYRnYd/LsKR3tiNsKfjYHL//aXoP3zuKfj2ggYPBiMpF5CYVl3bt51Pa8ZLscylFfo30vtd4OyDLgdNiSNgoXRTMvDS1+5Si3Ud2bdYXYcWkLMi/RstGYoq7By+4TPlM3dMfbU+NDeyCEHLcDYwZlYcLgSKlqb83ZUzraEbcVfFtVE3wd5jdb97ej9a34xp+3YOH/fIwWf7C/L4foU4vBi8nEYkZA/4mjhtZIZqO3GS8AIEmSkn0xWjpSmnU9btiiAVF3BVku2CQgLMeu0ajuzbrCqOigumMNbaYFSkAkAyJ6bMYWR8pGw/MzkJ/pRGcobFkTrSgZlZflwWaTMHFI5LH3nE3BS1zmJRSW8eEh63Zh9ZdN0WZ1fzDM7AtRP2LwYjKReQH0T9n1RY8Hi4bc3ij7jQw27SbaadSd3SYppaw6n/HgJVmzLhDpgXE5xIJG8xqEj9a3IhiWkem0oyTaOCtJEqZGMz/bLGo0rYg2684YkQ8AmBg9dr6nNnVlo3BYxj+2VeOtXbWmf++2zqAy+O+aScUAzs7S0cdHYyft3tl7sh+vhOjTjcGLyWw2CU67sSm7zR2RdHSWy9Hnfc3ab9TbgLp4g6LByykT+l6SNesCkedxpAVrAkSz7pjibEhSLMM0rTQPgDV9L7IsY/OxyIteeVnkcUTZaE+NLyXHivefbMbnn/kA9/9lG+55aQuaTS7p7D7hQ1iOlBY/d15kds57B8++4EVMSAaAd/aeQtjErCARqcfgxQJiyq7ezIuopWe7+w5ezNpvVN3HSSOhKEecODI+Zbf7ZN3urGjaVY5JR/tdhGnDcwFYE7xUN7XjpM8Ph03C1GGRxxlTlAWHTbJ8TUBHIIRfvrUP857coGR/gmFZCeLMsj1aMjp3mAcXjS6A3SbhSH0rqk5bOzsnlU41+3GkvhWSBGQ47ahv8Xfp8yHtOoNh/Pebe7tktMg8Z3NwzeDFAqLvRU/mJRSW0RY9Ppvt7rtslGvSlN2+ZrwIomnXjLKR+MXfvVlXGD3IisxL9KRRt+BFlI2s2DAtgoZJJTlId0b+bjgdNqVh2Ko1AR8ebsD1v9qAX79zEIGQjKsmFis/536Ty1WxQDQXOe40pQk61dmXt3efxGd++z7etKA0VhHNno0vzsal4wYBAP69t870x+lN1ek23Pk/m/HP7SdM/9413nZc96sNeGrtQdO/dzJvfHICv333EBa++LEpb4go5tf/PoAJ31uNt3efneVNBi8WcBvIvMSfYMh02Xu5Z4TS82JW2ajP4MW849I7kjTrClYsaDxYFxtQFy83w6mUqczOvsSadfO73C76XsxeE+BtC+CRV7fjC7/7EIfrWzEo24UVXzoPzy4oV3pu9p80OfNSHcu8AMCcsYUAkLKm1s5gGD/6527c+YfN2FbVhP/ZeNT0x/j4qOhbysMVEyI7sVLZ93K6tRMLXtiEt/ecxPK3D5j+/f/5SQ321Pjw89X78NrW46Z//0TEoldfRxBPvLE7JY/Z3zqDYVSdbrO0XHy8sQ2/fucgOoNhPPS3T87KwJDBiwWMbJYWwYvTYetycimZPGVFgP4eBlmW44KXxKsBBFE2Mtrz0luzrhAbVGdO8BIMhZXvJQbUxbNq3svmY7EXvXgTBosTR+ZlQd7dV4crl63DXz6uAgDcfuFwvL34Ulw3ZQgkScL46Amr/SbOl2nxB5XsmAhERfDy/qF6U0+LJXK8sQ23PvMBnnvviHLbzmqv6S8Om6OljfNH5OOy8UWQJGBntQ8nTV5UmkhbZxBfe/Fj5d/MoVMtph9Fj5+K/PCrO1KyrDS+XPTP7TUpb4LeV9uMJSu34/JfrMX6/acse5wabzte3lSJu/+4Gef9cA3m/PxdvLypyrLHW/bWfnRGR3U0tgXw8N+2n3UrOxi8WMBI2agl2qybraJZFwDyM8WKAP2ZF197EK3RUlVfmRfRsGs0ku+tWVcQmRezFjRWnm5DZyiM9DR7wvKYFcFLc0cA+6KZlRllXYOX2IkjczIvobCM+1/eivoWP8YUZeGvi2biJ7dMgSc9Vn4UGSczg5dd1V7IcmTtgZjCPHVYLrJdDjS1BbDrhHV9IWt2n8T1v9qAbVVNyHE78JvbpyPNLsHXEcTxxnbTHqetM4id0fLejBH5GJTtUvqX3rW4dBQMhfHNP2/Ftqom5GakoSDTCVnuejTdDFsrmwBEyrWdwTDu/uNmSwOzk74OHG1ogyQBX7ygFADw3dd2otXi+TmhsIw1u0/i9mc/xDXL1+PlTVU4Ut9qSbZu/f5TuHb5esxc+g6WrNyBN3edVN6gvv5JtemPB0Sa51/bFvnev/j8VDgdNry77xT+vKnSksfrLwxeLGCkbCROgWSpaNYFzNksLWa8FGQ6lQnBycQado1lXmLzXXKS3sfsBY3744bTJZplI4IXMzdMb6tqQlgGSvPTUZTTNas1ITrrxaw1AZWn2+DrCMLlsOGf35yN80fk97iPmG1T1+w3rbdnR4LGa4fdhpmjI4s8rTgyLcpEX//DZvg6gphamot/3TcHN5xbgvHRjNZOE5tpt1U2IRSWUeJxK4HvldHSkZV9L7Is47t/34l/762Dy2HD83fMwEXR59XMIPtEUztqfR2w2yS8fNdFGFechZM+P+76Y4Xh6d3JiJk55wzJwX/dcA6G5aXjhLcDv3hrnyWP19YZxHMbDuPyX6zF1/+wGRsPNcAmAReNivw72XT0tOlZwl++tQ97a5shScD04bl48KpxeOpL5wEAthxrQlun+YHaz1bvhSwDN5w7BP9RPgwPXzsBAPCjf+5RMndnAwYvFjCSeWn2qz8mDZizWbpaZb8L0LXnxcgL/A6lRyK31/uNKjTvxNHBJM26wsQhOaZvmBb9LjPKegYSRdluZU2AGZkQ8T1GD8pKGoRmuRzKi69ZfS87uvW7CKJ0tOGAuen4qtNt+HxcmWjh7JH4690zUZqfAQCYXBK5jp0mZnxi/S6xP8fLo8HLewfqLXuB/9W/D+AvH1fBJgFPfnE6ysvyMT0aZItMiRlEyWjikGwUZbvx7IIZyM1IwydVTXh05Q5LSg4ieLlgZD4ynA785JYpAIAXNx61pGT16Mod+NG/9qDydBs86Wm4+9JR2PDwFfjTwguR6bSjuSOIfSY2srf4Y9m6fy++FK/dczHuv2osrps8GENz09EZCivPgVk2HqzHuv2n4LBJeOia8QCAr84agVmjC9AeCOF7/9hp6uP1JwYvFjDUsNuh/pg00DXzovcXjNp+FyC2nLEzGIavXf+7hmSTdbsbXWTeiaPYjJfEwYvTYTN9w7Q4aXRet5KRED/vxSjRjDwuyc8niMyEWaUjUb6Y0i0QnT02ciKn4lijae8wd1Z7Me/JDfgkWib63fxy/NcN58AZNxxyUvTv1M5q8xqhxZye8+P6liaV5KA4x4X2QEhpPDXTy5sqlcbcJ26ejGsmDQbQtbxpVlAhAqHp0XlHZQWZ+O3t58Fuk7ByazWe23Ckl6/WR7xwXzgyEhBeMm4Qbpk+FLIMPPLqdgR0rldJRJZlJQP4nWvH48MlV2LJdRMxNDcdDrsN5dGgdNMR8/4cN0czOaX56UoJHIgMxZw9JtoTZuJpvHBYxk9X7wUAfOnC4SgriPzutNkkJTDceKjB9BlP/YXBiwUM9bwomZe+j0kDscyLPxhGu853f2pPGgGRxZM50cDqVIu+enhzRwCH+2jWFczMvMRmvPRs1hVEH4MZwUswFMbWSpF5SRy8iDUBe014xyeCEVEaSsbMvhdfL3+WIwoyMCwvHYGQjI8Om/MO8/n3jsDXEcS5wzz4131zMDf6gh5vcjQANatpNxgKY8uxnpkXSZJwxYTINOF3TC4d/XvPSTz22g4AwDevGIMvX1SmfG7yUA8cNgn1LX4la2qUyLycV5ar3HbxmEL817yJAICl/7cHa/eZ9zM2tnYqS0njy5vfnTcReRlp2FvbjGc3HDbt8Y42tKGhtRNOuw0LZ49URhYIIoDaZOK8mY+U4Kygx+cuVrKS5gUv6w+cwvbjXmQ67fjmlWO7fG5EYSZGFmYiFDbv32J/Y/BiATGkzp+CzEuG065M9NXb91KtcsaLMMjgrJedKpp1hVEmzXoJhWXleyQrGwGRujRgTvCyt7YZrZ0hZLscGJckoBCZl90mZF5EGSjZYwnjiszLvIgMWqI/S0mS4kpH5vyS3n68CQDw4NXjlDJRdxOH5MBuk9DQ2omTJswjUv4c3T3/HK9UjkzXmZYF2VLZiG/8eQvCMvAf5cOw+OpxXT7vTrMr/VJm/D31B0NKA/15w7sG2XfMGoEvnF+KsAx88+Wtps1cEqeMxhRlKStHgMj+tO/OOwcA8Ku3D+CoST0aIgM6ZZgn4SnOC0TwcuS0aX+O3TNL8S6O9i3trW02ZVo5EBtLcNO0oQmX+l48JvKYZ8vkawYvFnAb6XkRDbsqe14iyxnFiSN96UC1A+oEo7NexFwTUaLpjZiya3RB4/HGNviDYbgctqQveoC5G6bFL8zpZXmwJ1l2qcx6MbgmID44U182Mv5CtDNJv4swe0ykdPTeQeN9L2ozdu40O8ZE/96Y0bQrXmjLE/w5XjymEC6HDccb202ZWuxtD+DO/9mMjkAYl40fhKWfndJljYUQ31xu1K4TPnSGwsjPdGJ4t38bkiThiZsnY0ZZHpo7gvj6Hzab0t8T3+/S3WfPG4rZYwrhD4bx6Gvm9NuIAYPJMqDnDvPA6bChvqVT+TtmRHtnSAm0E2VeCrJcOCf6b3/jIXOCCZHpEQ3I3YlSFYMXSspI5kVp2FWZeQHi+l50Nu2eULkaQDC6IkAES91/USZi1oJGUTIaPSgraSAhrsmsDdPKMsYkvzCBSE+PwxY52mtkTcCxhlZ0RoOzYXm9P6+jB2VBkiKZuvoWY+/6tiv9LomDiYvHFECSIoFSrcE1CLtO+CDLkb8Tid5ZxhO9VGY07Yqm60Snt9KddsyKvov+9x7jZZUPDjXgdGsnhuWl47e3n4c0e+Jf0WaWN0VJ7LzhuQkDJafDhhVfLkdhlhOHT7XiAxP6e0R5JlFWQpIk/PiWyXCn2bDxUANWbjF+pDh+q3siLoddaYQ2o4l2S2UjAiEZQzxulOYn/r1q5iDH5o7YSIJEASEAzBxVCEmK9MYZ/bd4JmDwYgFx0qPDwJwXtZkXINb3oufoayAUxslmjcGLwbKRlmDJrAWN+8VJoz6yEmZumBbBS7JfmEDkl6ZYE7DXQOlIaUYu6j04AyIvuGXRwNFo6Ug5aTQ0N+HnczOcODcaSBh9x6fmeL0g7mO0aVeWZSXzkiwINXParsgQXDJuEDJ7+R0gyps7qr2GG1u3RgOg6cOT/z0dlO3C5eMjP+dmg30hLf6g8meZKCAEIg3D914+BgDwv5uNDXPztgWUfx/JGueBuL4XE4KXj6IB3oUj8xMGhEAkawdE/l0YzS5VHGtEWI68+RqSZLmuJyNN+bdoZqNwf2HwYgF39OSDntkdomE3R0vmJVP/rJdabwdkOfLuqqCP/hNBlI1O6XzXruVoNmDOgsaDSRYyJmLGhukabzuqm9pht0lKij+Z2KRdA8FLNAjpq99FEE29RnYceeOOlPdWxpmtvMM0VjqKLX/M7fO+IvNidEBe1el21DX7kWaXMDXJn6M4Ml1xrNHwglQl4O0lkAAijezZbgc6AmHDx3u3ivJmNCBKRgQa4ti4XuKFtjQ/vdffAddOHgIg8u/QSAlXNCOPLMzsNWN3QbS8Y0bw8qHodxnVs2QUe7x8OB021Hg7DK9A6a0MF+9iC0459RcGLxZwRzvZjew20lI2UvYb6fjFqZw08rgTDm5LxGjDbo1X/dFsIL5pV/8/8Fhmou8X96ml0cyLgeBFpKknDsnu9R105D5i0q7+FyHRv9JXZkkQfTH7DfRpiJLM8PwMeDKSn46bM1b0vdQb2nKbaBheMhOH5ECSgBpvh6HSmMi6TBnqSTo7Z1heBiYMzkZYBtYZGDHfEQgpmaLuqyS6s8VtKDfy97TW24ET3g7YpFgpKhlxTZ8YDCbEceQLRiR/YQcik34LMp3wB8OGepfEMffeMqBA5KSVwyahuqndUIm6IxBS/kwSlcUEd5pdyeYZDSbUBi+zTcz29DcGLxbIiP6Sa9M1YVfbUWkgLvOio2ykNQsCxJWNdPS8dAbDSqOv1syL3rJROCwnXciYiMiUGNkwHet36f2XCRAXvBjIvIjyzzgVwRkQy9AYybz01e8inDc8DxlOO+pbOnUfCVezCytelsuhlBt3GdjaHZvv0vuf4xVxp4702lntRWcojMKsno2ziZixzkIc5R8/OKfPIHtkYXwwof857e0UTjxJkpSAyUi2R035FgAynA4lY2ck+/JJVRM6g2EMynYpfweTmW3CabyOQAifKM3BvT+n55XlwZ1mQ12zX/mdqMeZMCuGwYsFxAyBDh1lI62njQAgP0P/aaPa6O6SwTnqsiCAsRUBJ33ay1RGFzRWN7WjPRCC025Tej16Y8aGabXv9gDjawKCobByQkJt2Whc3IJGve/AdlQ3AYBSR0/G6bApv1T1njoS77yH5aUrwXpflEm7Bt61J5qsm8iVEyPBy9p9dQjq7EFRBhoOz0vaJxHPjBNHynyXPkpGQNdgQm/fS0cghE+qem8sjaeUqnQGE4FQWPk33FvjvGBG38tHcVmQvv4c50RP4314uEH335utlU0IhGQU57j6DHrdaXblOdXbg9YRCKH8R2/jqmXrDJdJjWDwYgGRXtYzNE6UjdTOeQGM9bzUN0e+ZlBO76c34g2K9rw0dwQ1l8biy1RqfkEDUAIJvQsaxTuMUYMy4UhyeqO72AuD9he+Vn9QOanUV/ofML4moPJ0GzqDYbjTbBiWpy6bNWpQJuzRU056j7yrzbwAsdKR3neYO5R+l74fSxBNu3r7Xk63dip/d/oKQqeV5iEvIw2+jqAShGiVbPt4MqIH5+CpFt3vhMVk3e7zXZIx2veyraoJnaEwirJdKCvo+42ECHA2H2vUVXLcfcKHjkAYnvQ0JYOr5vGMBS+RsthFKoKzc0pykJuRhhZ/UMmeaBUrGRWo+p1qdLqvyCx52wPI7aVcbLWUBC9PPfUURo4cCbfbjfLycmzYsKHX+69btw7l5eVwu90YNWoUnn766VRcpmkynJHAo01Pw66O00biqLSe/Uai6XZQH0dP4+W4HXBFm5K1Dlg64dVepsp2pxla0HggetJojIpmXUHMoNldo/2F75Oq2BK/ZJ3/3YlhdXt1bJjua+FkIi6HHSOiLx56Gj4bWzuVrc19rXgAYsdCNx05rasXbLvS75Kr+mtimRd9JQ4RhIwpyupzmKLdJuGy8fpLR7IsK0eW1WTrgEjv2dDcdMhyLJDUojMYVp7Xvpp1BZGBqjh2WlcwsUlDVgKILG3McNrhbQ8oJwa1qIg7Bq7m38aMsnxIEnC4vlV3WVw8Zm/NuoLdJuHi0aKhXd8R9E1HYyeb1BBNux8ePq0r2yOC7AtGqPsztIrlwcsrr7yCBx54AI899hi2bt2KOXPm4LrrrkNlZeL13EeOHMH111+POXPmYOvWrXj00Udx33334dVXX7X6Uk2TnqavYTcUltEaDXi0ZF7EL9YGXZmXSPDR19yMeJIkxZp2Nf4DF8ek1b6oC0bWBOxXsRagu3OUPhTtvzDFP+7yPkoN8cSaAD2Pd0Bjv4sQXzrSSjTPjizMRI6773dfY4qyUJzjgj8YVpqZNT2ejszLpGjwUnm6Dd427ZkJURo5X2Um5AoDW6bjx9erCQaFaQYmQu+u8aEzGEZeRlqfvRnCpJIcuNMiy0sP12t/I/FxL/NdEnHYbUpWSE/pqCLBWofeeDLSlDcSuv6eVjehIxAZ+KfmZCMQf2Rae0m1S7Ck8jk9Z0gOst0OtMRliLX4WOO/C6tYHrwsW7YMCxcuxJ133omJEydi+fLlKC0txYoVKxLe/+mnn8bw4cOxfPlyTJw4EXfeeSe+9rWv4Re/+IXVl2qadGf0qLTG4KU1bnmdltNGBVmx00Za3w2JkxgiGFFL76yX2DRf9T02gLE1AQc0NOsKE6LBS+XpNqWUp5aa4XQ9Hs/Agsb9ys+X+uBFTfMsIFYFREtHGn9Je9sCqDwdOf0hsilqeDLSlAFhu3Rk0GLzXdS9KFwybhDsNgkH61pQqXEreV/j65MxsmFaNOtOV9ljAwBpdpuyvFFr6SgQir3Qnq/yhRbQX6qSZVlT75lgpO9F6XfRkJUQWcmtlU2af9fsqPYqwZLazLLNJim/m7TucgqFZc0BoVUsDV46OztRUVGBuXPndrl97ty52LhxY8Kv+eCDD3rc/5prrsHmzZsRCPR89+T3++Hz+bp89Lf0NH1lI3HSyGm3afoFJjIvwbAMn8batygbacm8APpXBIjgZYiGshEQO3GktUNelmUcFAsLNZSN8jOdSqlqn4ZSjizLSu1abSoe6HriSGsDbWzGi/qfL3J//WsCxOhzLZkQZc/Rfm21dhEolRX0fiQ7ERHs7NJYOuoIhJTH7eukkeBJT1PejWodWNfX+PpkjGyY3qJsks7V9HXnKyeAtL3w7TrhQ1tnCJ70NE1ZwvNHxh5Py89Y3dSOkz4/HHHHytUQfS8f6QleDqs7shyvND8Dw/MzEAzL+PCQttKRCLDOH6E+AAViwaPWxut9tc1o7ggi02lX5lP1F0uDl/r6eoRCIRQXF3e5vbi4GLW1tQm/pra2NuH9g8Eg6ut7/tJbunQpPB6P8lFaWmreD6CT3tNGSr+LhqwLEOlfEGWm+hb1paNAKIymaDq9MEvdCQ5B74qAGq+2ab6CyJoc1Jh5qfF2oLUzBIdNUlbEqyUCit0aUqvHG9vR1BaA025TdgipEb8moEbD6O5gKKyU0rSUxQBg/ODIc3pAx4kjUcZRm3kBYunx3TU+TbNXtkdPNWl5LEHvmoBPqiInOIqyXUnHuydyZXTLtNbSkdKboTF4id8wrXW9xBadjynecWstq4j5LuePyFfdmwUA00vz4LBJqPF2KH1WaojndFJJTo8t0r0RwereWp+mcmMwFFaCgQuT7BdKRhnkqLGJVpmZk2B/Um9i2SxtAaEIss8ry1N9+MEqKXn07hGhLMu9RomJ7p/odgBYsmQJvF6v8lFVZWyUtBnS4+a8aPmL0eLXfkxaEJmTBg0vCg3RQMduk5SmX7X0lo2qdZaNxAvzsYY2TQOyRMloZGEmnA5tf931zF8RjZMThmRryp7FrwnQ8njHTrehMxRGeppd9UkjoawgE2l2Ca2dIeXPRQ3xQilJwCQNAUVhlktphH5Xw4u7nn4XQTye1uPSom/pfI1NiVdEj0x/eLhB9Qufty2gZL+0lDeAbhumNZSO6nwdqG5qhyRpf16nD8+FTYqUVE/61AdMaue7dJfutCtBqJZsT2y+i7bHG5TtwqhBmZDl2MgDNXad8KG1M4Qct0MpA6t1iTLvRX1JNRSWlQBS63Mav4jyiIZFlMroAI3PqRUsDV4KCwtht9t7ZFnq6up6ZFeEwYMHJ7y/w+FAQUHP6NLlciEnJ6fLR38TUX4oLCMQUh+8iLKRlmZdoUDHcWlxUqgg06npnRCgb0VAc0dA+Rm1NuwW57iQ7XYgFJZxtF59P4EoqWjpdxH0BS9NAPRlCUQaVssgN/HzaTlpJKTZbUoj9AENpSNRThlVmKk50L5m0mAAwOqdiTOviShHsjWcNBJE0+7h+la0augnUPpdNDYljh6UhQmDsxEIyVi1s0bV12ypirwgjCjI0Fy+BeJLR+ozIaJkNL44G9kqGq7jZbvTlH8baoOJcFhWPQU2EfE1WoKXvpYx9kZP38tHShYkv8/9Yt3NHF0ImxSZIn5C5RuJPTU+NPuDyHI5lD8PtVwOO6ZFS2lqM2iyLCuZJa3/LqxgafDidDpRXl6ONWvWdLl9zZo1mDVrVsKvmTlzZo/7v/XWW5gxYwbS0vrvTLkW6XFjxLU07SqrAXRkXkTTbr2G4KVeZ78LoG9FgCiHeNLT+pzm2Z0kSUrPygENRyYPKMeItddnz4m+o91X26y6EVq80GqpsQuxMpX6YEnrWoDuxkUDpn0amnZ3aNgx1N21kyPBy4YD9aqaE0+3dipZoUkqFjJ2NyjbhcE5bsiy+iA0vilRbb9LvM9MHwoAeE3lNuSKo/oyBIKeNQFbq2LNunqcr7F0tO9kM3wdQWQ47Uo2TM/jqW3abfEHlbEDel5o9fS9xDJL2ko4QOR3opjbo3bL9PpolkZPsATEnhe1TbvHG9txwtsBh03S1M9nFcvLRosXL8Zzzz2HF154AXv27MGDDz6IyspKLFq0CECk7LNgwQLl/osWLcKxY8ewePFi7NmzBy+88AKef/55fPvb37b6Uk2TZpeUv0xaJqa2GMi85GdqLxud0nnSKP5rtDTs6llFEE+UjrRkCUSgo6VZVxhRkAmXw4a2zhCOne472xMOy0p5Qs3gtu7ECSct26VFWUztZN3uxkWfFy0njrbr6HcRxhZlYVRhJjpDYVWlo/gsj5oj2YnENkyrKx3tP2msKfHmaSWQpMiLQpWKvzdqx9cno2fD9NZjTV2+VqsZGpt2xQt7uc5eCdHIfLCuRVV2eVtlE8JyZCJzsYbp4YLoIdlZ7VWVsQvFZZa09rsI4jTeepWlo7X7Ive7fPwgXY+ntWlX/HxThnmUWWb9yfLg5bbbbsPy5cvxxBNPYNq0aVi/fj1WrVqFsrIyAEBNTU2XmS8jR47EqlWrsHbtWkybNg0//OEP8eSTT+Jzn/uc1ZdqGkmSlP1GWjIvzToG1Ami4bZBQ8PuKR0zXgTRsNvQ6lc96KgmOuOlxKP9lwkQ17Sr8sRRKCwrJRg9L0KOuKZbNe/ajza0otkfhMth0xUsiVkvR+pbVc8IOqDjJFU8kXnRErwoawF0BGiSJCnZl9W7+i4d7RBlOB2PJYjS0U6VO47EL3O9TYlDPOmYGR1Q9o9tvWdfuoyv15mK17phOhAKK03Qaifrdid6HvbU+FRN99Xb7yLkZTqV03RqAiY9R6TjDc1Nx9DcdATDsqpj6B8daYCvI4gct0OZEaXVJXFNu6E+Mr3e9oAS9IrhiFpF1lBEZgypOXhhpOxnhZQ07N5zzz04evQo/H4/KioqcMkllyife/HFF7F27dou97/00kuxZcsW+P1+HDlyRMnSDCRis7SWzEuzjo3SQoEyqE59JkQpG2Vra9aNPJ4LNgmQZfXD8U4YzLyM0ZglOFLfirbOENLT7BilYjR4IhM1zF8RWYJJJTm6XvQGZblQkKl+TUD8SSPdmZfo1x2sa1FVGqvzdeCkzw+bFBltrocIXt7dW9dnkGYkyyMoJ45UZl7MaEq8RZSOtlb32rS/t6YZ7YFIk+cYnX9H4zdMqxkxv7emWRmZP0rlcLruBnvcKM1PR1jue8aMLMtx+360l1SEGRr2HOmZtdSdCLTeP9R3GUeUCOedO0T3KZyppbnIdjnQ1Bboc6XF+9EAZ9SgTJSq2NeWiCc9NpDv4yN9l+M2aRwwaDXuNrJIupJ5Ud8k2KJjo7RQEM2eaDkqLe6rZTWAYLdJSsZG7YqA2IwXvZmXWGZCTXpc/AI4pyRHV00YiJ9823fwst1ALwgQyUpoaRI+2hA7aTRUZ0A4PD8DLocNHYEwqhr7LnGIAG1MUZbu1PGUoR6UeNxo6wz1uetop8ZheImIstGBuhZVGS2tk3UTuXbyYLgcNhw61ao8ZwkfK+7oqdaG63hK066KLIFYxjitVN3I/GTOL1NXdjhS34r6Fj+cDpuubJ1wQdzx3t6E4rIlevuIAOCy6MTkVyuO9/r7pr0zhP+LNqDfMn2Y7sdLs9tw0ehIcNfXvwtRcr1cZ9ZFUDuzp9bbgSP1rbBJxp5TMzF4sUiGknlRvztCHJXWddooS89po0iqUE/PS/zXqZ31IvYa6X2hLfG4kem0IxiWcayh7+N94oVvss4MARB/4qjvTIie2SfdiSzBehVNe/EnqfS+CNltkpLRUlNyMHLyR5AkCddM7vvU0almfUeyuxuc40ZBphOhsNznz3jgZDNOeDtgt0nK6H09st1puPqcyInK17YmLx0p/S46yzdC/LC6vsQ2SRt7zBkqm2j/VnEcQOQa3XGHGbQSPRo7T/jQ1pn8TeG+2ma0RE/haJm11N21kwajMMuFumZ/r39P1+w5iRZ/EMPy0g1legB1R6ZlWca6/ZHPX6az30UQjdB9NSavjz7eucNy4Uk/Mw7OMHixiJ7N0no2Sgt65ryIzIuenhdA+6wXsddIb9lIkmIvtGqadsVCPiMvfCKtWt3U3uvcjlBYVgahGXl3ecO5QwAAa3af7HODtrL2QMdJqniidHRARS+RyCIY+RkB4LrJkZ/z7T0nk76rFcHn6EFZuvrABEmSlL8DvQ2rk2UZ3399FwDg0nGDDDclfva8SOnojU9OJO0LU4IXg0dPtWyYFlkJoydGxLv2rVWNSf8MD51qwbMbDgMAFs4eaejxRB9KqI8+FDFIbfrwXN0ZVwBwOmy4/cLhAIA/fHA06f1e2xIJzm6ZPtRQJguINe1WHGtM2ii8u8aHumY/0tPshvtPZo4ugE2KZHp7ay4XTcSXjDMWLJmJwYtFlEF1vbxD6M5Iw67oeWlsC6huoNW710jQsiIgHJZR6xVLGfWVjYDYkee+XmhlORZMaNmH050nI03JFPW28fnwqRa0dYaQ4dTfXwNE+mXGF2ejMxjG/+3ofU7IfgMzbOKJ4KWvrEQ4LMcyLwaDl/KyPBRmOeFtD+DDw4lHoitlOAPBpzBZGVaX/M/w1S3V2HioAS6HDd+/8RzDjzln7CAUZDpR39KJDQkmp55oakdNNMuj52h9PLUbputb/Kg83QZJgqHMEhAJKnMz0tARCGNXgmZoWZbx+Ou7EAjJuHz8IMw9J/FsLy2U4729ZAqMnt6K96ULh8Nhk/Dx0caEfSinmv1KllT0ORlRVpCB0vx0BEJy0p9RnDK6eEyBpkGYiRRmuZQAKFl2KRSWlcm/IjN0JmDwYhFRNtKyWdpI8JKb4YQYBHq6re/SUWcwfjWAzuBFw4qA+lY/OkNh2CToOrooiBfqvoKXqtPtaO4Iwmm3GX5xV9P3Il4wJpd4DL3bkyQJt0Tfsa/sY06IyD5p3WnUnfj6vpqEV26tRn2LH5lOu+4TFYLdJuHqc3ovHYksj5Yty8mI75GsEbKhxY8f/2s3AOCBq8ZpXiWRSJrdhhunlgBIPPNFvMhOHJKtee5RImo2TIuMxdiiLN1Hz4X4BX+J+l7+b2ctNhyoh9Nhw+M3TdI0qTiZ81X0vWw2MXgpznErDeZ/2Hisx+df/+QEQmEZU0tzDb1pESRJwuwxvR+ZXrsv0u+i95RRd9dPiWRB/y/JUMUd1V40tQWQ7XIo5ckzAYMXi+g5bdRi4LSR3SYhP0P9cWlxKsluk5Crs4YpykZqGnZFyago2400AzsxxAvtgT5eaEXWZcKQbEOPB6jre9lhYL5Ld5+ZNlSZE5JsO3EgFMbhenPLRodPtSbN2nnbA1i6ag8A4P6rxhrqXRDEi8Kbu04mPBpq5Eh2dyL7tremOWGJ48f/2oPGtgAmDM7GnXOMlTfiiYF1b+2u7TGUL3YixpwGyOkq+l5Ev4vYDG3UjCTBRKs/iCfeiASD/3npaFOCQSB2THdrZVPCP8fnNhzG8cZ22CSY9kJ7x6wRAIC/b6tGU7c3hq9tjZSMPmtC1kWI9b30zNZ52+KPSJtTwhFTr7dUNqHG23O67zvR5uBZYwr6fZ9RvDPnSs4yGXH7jdRShtTpOG0ExJp21QQv9c2i30X7agBBy6C6GuWYtP6sCxB7oT5cn/yFFoj1S0wyUDISlOCll7KRni3LyQz2uDE7usQwWbPnsYZWBEIyMpz6TxoJQ3PTkeG0ozMUxtEkwdKyt/ahobUTY4uy8NWLzXlxnzmqADluB+pb/MqLqnDShCPZ8Urz05HtdqAzFO7RL/XegXqs3FoNSQKWfnaK4WA33tRhHowqzERHIIw3u2WY9C5jTKa3DdMt/iDe2lWLN6Ozdc4ryzXlMUXfy+ajjV0e88l3DqDW14HS/HT852WjTXksABgTLVW1B0JdSlWyLGPp/+3Bj/4VCbDvuWyM5rUHycwoy8M5Q3LgD4bxysex3XkHTjZjZ7UPDpukZNjMMCu6KuBgXUuPYGLDwVMIy5HTfsPy9B2R7q44x61k0LpnQcNhGSujPT3izcaZgsGLRfRsljbSsAtEZq8A6ma9nGqJZEL0lowAYJDoeVHRsGt0uq4wNDcd7jQbOoNhVPWyYVYMJJusY6R8dyJ42VfbnDBgCoZiNX8jJ43iiWbPlVuPJ5wTIl6Ax+rYadSdzRa3eiFBRmtntRd//DCSMv/BzZNMe3F3Omy4amKkD6L7L01xcmtsUbYp0zwlSVKyL/FNu+2dITz62g4AwIKLynSPy+/tcT8TN/NFaPUHlTUQRk+oCGLD9KlmP6qb2rGz2ovfvnsQtz7zAab94C3c9ccKZS6QnhH2yR7T6bChoTW24O/AyWY8v+EIAOAHN00yJUsnREpVXee9BENhPPS37XhmXaQx+OFrJ+Bbc8eZ9piSJOGOWZGhqn/88JiSJVwZ/fO8bPwg5Gdqn5WVjCcjtiqge/bl3b3Gpuomc51SOur67/CDww043tiObLdDabI/UzB4sUisYVdd8BIKy4bKRoDezIv+4CW+bNTX9myx18ho8GKzxZ84SlzGkWUZu6pjPShGleVnIMNphz8YxtEER7QP1LXAHwwj2+XACJPS49dMGowMpx3HGtqUJXrx9hvY2ZSI0rTb7TkNh2X81z92IiwDN00twazR5jbsxR+Zjv87ZGa/iyAC2V1xc1eefOcAKk+3YXCOG9++ZrxpjxXvM9Miwcv7h+qVLcyfHG9CKCxjiMdt+N+EEL9h+upl63HDr9/Df7+5D5uOnEYwLGNEQQYWzCzDX+66CCN0DqfrrvuCP1mW8b1/7EIwLOOqicW4YoLxJt3uzo/bydPeGcLdf6zA3yqOwyYBP//cufjPy0ab0l8T7+ZpQ5GbkYbjje14Z28dwmEZ/4gGL0ZmuyQjTh3FBy/hcPwRaXP6XQSRVfn46OkuPYz/uzmSabppaompQagZGLxYRGRe1B6Vbo07laT3WKhyXFpV5sXYSaP4r+0Mhfs81qtM1zVw0kgY28eJo1pfBxpaO2G3SYbmPAi2uO+zO0Hfi8gSTB7qMZwFETKcsXc6Im0bb390Z5PRZl1BOS7draTyt4rj2FrZhEynHY/Nm2jKY8W7ZOwgpKfZo5mCWBnArCPZ8ZRJu9Es2Z4aH55dH3m3/sTNk0wrM3Q3vCADM8ryIMuxdQEVBjYe9+aCEZGMSnsghEynHVdNLMYPb56EdQ9dhrUPXY4nbp6Mi0aZk3UR4vccvbG9Bh8cNu/EViLnx22Ynv/8R/j33jq4HDY8M38Gbj2/1JLHdKfZcduMyPf+wwdH8eGRBpzwdiDb7cCVE80NJABgTrTvZd2+Ovx89V789t2D+H9v71ca5s3e6jw0Nx1TS3Mhy8BT7x6CLMs41exXMjG3WfS8GtH/25XOUuka57yIfpc0uwSXQ19MqawIUJF5MbLXSHCn2eFJT4O3PYBTzX7kZiRPncam6xp/lykyL8l2HIkXwbFFWaa9W5g4JAdbK5uwp8aHm7rVt7eb2Fga73PnDcWrW47jjU9O4Hs3ntPlWKTIOuldC9Bdou3STW2d+OnqvQCAB68eZ+iUWDLpTjsunzAIq3bUYvWuGkwZ5oEsm3ckO57of9p9wodAKIwlK3cgGJZxzaRizJ1kbT3/lvOGYvOxRry29QTuumQ0KiqtCV7uv3IsRg7KxNiiLJw3PA9Onb9LtIicADqEjYcalMzAvZeP0T22vi+TSzxwp9nQ1BbA5mONyHE78PxXzte1AVyLL19Uht9tOIwNB+rhD0TKxzecO8SSjMS00lzld+tTaw91+dysMYWGj0gnctecUfjGn7fgxY1Hke604509degMhnHOkBzTyuFmYubFIukaTxspJSOXQ3fKMz9aNlKzIkDZa5RlrFartmn3RLRsZLS5FIgtIRQbo7uzouTQ29h+K15oAeCiUQUo8bjh6wjinT2xDcyBUFjpLzB6DFwQGZyj9a3oDEZ+Mf/irX043dqJccVZyokLK4jTDqLvpdbXgfoWP+w2yfCR7HgjCzOR4bSjPRDCE2/sxraqJmS5HPjBTZNNe4xk5k0ZAqfdhj01Puw+4cMWk08aCZ6MNMy/qAwXjSpISeACxBb8VTe1o67ZjxEFGbjr0lGWPZ7TYVOmAxfnuPC/i2ZaHrgAQGl+Bq6MlsHEnh8rSkZA5Jj983fMwDcuH42vXjwCt80oxQ3nDsG8KUOw+Grz+nnizTt3CL4bza6uWHsI+042oyjbhV/fPt30MpwZmHmxiNbMizLjRWe/C6CtYdfogDqhKNuFg3Utvc568QdDSqbHjPr+2G7LBLuXanaZsBagu3OSzHrxB0PKbecaGJmfiM0m4ebpQ7Fi7SG8uqVaaaoTJ40yTThpJAzOcSPb5UCzP4gj0QDmpY8i295/cNNkU0/gdHfFhCI47ZE9QAdONuNwfWzZpJnvakUwtPlYo9KA/J1rx2OwCaXMvuRmOHH5hEF4c9dJ/OKtffB1BJEe16MykHky0jC+OFvZ4P74TZMsyQzE+861E/DXzVVYdOloyzI8iXxl1gi8veckAJiyDqA3M0bkK0fRU+XOOaPgaw/gyXcOYnCOGy/fdRFGmtQfZTZmXiyiN/Oi95g0EMuiaCkb6VnKGE/NigAxWdflsCEvw3hfQWleOpzRZYLHE5w4Uibrmph5GR9dE3DS5++yP2p/bQsCIRme9DSU5psTSMQT8yPW7qtTVj/EmnWzTHtHJEmSUjraW+vDd/+xE7IM3DytBDNHm9sj0V22Ow2zozX+1Ttr45Yxmhd8CvF/J6YPz8WXLiwz/TGSERNYxdyMaaW5lgaFqST6aK6dNNj0ZtJEppXm4se3TElp4AJEptqOGhR5MTdjHcCZ6MGrx2HlPbOw+oE5Z2zgAjB4sYz2zEuk4dVQ5iUaiKhZzqjsNTKaecnpe0WAGFA3NDfdlBdbh92GUdF/VN1LR3XNkfkgkhQr9Zghy+XA8OgvyvjsS3y/ixWp1bHF2Th3mAfBsIw3PjkBIH4tgLnv2kXpaPnbB/BJtKTy6PXmN+kmcq0oHe2qjSvD5Zr+OJOi2TiHTcLSz04xNA1Zq8snFCEn7t+32f0u/emBq8bih5+ZjP/+/Ln9fSmWkiQJy26dhjtmluHrl1hXGutPkiThvOF5vfYwngkYvFhEc+ZFGVBnJHiJ/GVr8Qd7XUvgD4aU00FmZV56m7J7wqQZL/GSLRMU81ZGFWaaMnI9XqI1AWZsku6LyL6IuRJmrQXoTjynop/mgavGWtKkm8hV5xTDJkX+/MROFzN2GnV37eTBuGpiEX58y2Rl6WaquBx2zDs31uxtdBnjmSQ3w4n5F5VZdmLrTDKtNBc/uHmy4fUKZAyDF4toPm1kcMYLEAl8nNE0dEMv2RdRVnLYJMPrzWMNu8l7XsSUSCMLGbsbm2S79C4LmnWFRGsClOWBJjfrxrtxagkcNgnbj3txsK7ZwsxL7PuNL862tEm3u/xMpzI4rT0QQppdsqQfJNudhufuOB+3nT/c9O+thigdSRJwnkkj+ok+jRi8WERr5sXIUkZBkqS4QXXJMyGiWbfAwGoAQc1po+omcwbUxROnbA52KxuJY9JmDKfrrvuJo45ASAkkrChxCAVZLqWP4H83H1cyI2YdkxbGD85Wlns+YeIkXbWumxI7rjyuONvyps/+cP6IPNx/5Vg8fuMkeEzo/yL6tGLwYpGMtEgQksrMCwBlTHVvTbtmnTQCIosWAeBULw27J0zaaxRvTNyguvjJrKJZd5IFzZ7i2O7BuhYEQmHsqfEhGJZRmOU0Zfhebz4XXRfwhw+OIhiOnDQy+zELs1z45een4v/dNhUXmjzITI2558SCFyszWf1JkiQ8ePW4lGa1iM5GDF4s4nZGntr2QKjP0flArGHXaB1VNO3W95Z5MWE1gFCUE/kezf5g0iyTKBuZmXkpK8hAml1CW2dImSHT1NapnD4yYyFjd8Py0pHtiiz3O3SqJbZJeqg1zbrxrpgYafbsiA7HGlOcbcljfva8YZbNrujLYI9baWI1a+sxEZ2dGLxYRPS8yDLgDybffizED6kzojCaeentxNGpFuPTdYVslwPutMhfo0R9L7Iso7rR/OAlzW5TjvGJabOiWXd4fobhXp5EJCnWh7GnxmfpqZjuXA47boib7DuuyNxm3TPFf//HuXj0+gm4JZppIiJKhMGLRdLjhmup6Xsxo+cFiFvO2Fvw0mxe2UiSJOX7JDpx5OsIojX685d4zJ2DInYciTUBO5VmXetOkcQ37YqTRlaciknkc3Ev6Gb3u5wpRg3Kwl2XjD5r5p8QkTX4G8IiDrtNOfnTpqLvxayeF1VlIxMzL0Cs7yVR064oGeVlpClNzGYZ0+3EkVi4Z0XJSBDBS8WxRmXGjNlrAZI5b3ieMt8mVY9JRHQm4noAC7nTbOgMhVVlXsyY8wKoW84YW8pozhCi4mjfy77aZlwfHWEvKAsZTc66ALETRyKIsPKYtBAfvACRnz1Vs1AkScJzd8zArhM+0zcDExENJMy8WCjDGQlEehsYJyjrAQw37IqyUd+ZFzPKRgBw1cTIsrIXNx5Vht8JJyw4Ji2IstGBky1o7ggoO3EmmbjTqLvxxbHjxAAwxeR9Rn0ZNSgLN3bbak1E9GnD4MVCokzSpqXnxWjZSCxn7PWodORzRqfrCjdPG4qxRVnwtgfw7PrDXT4nMi9DTTwmLYwszITdJqHZH8S7+04BiAzCM6sclki6046RBbF9H2frkV4iojMZgxcLqZ2yGw7Lpp02im/YTXREO341gFkv8nabhG/NHQ8AeOH9I10ad5WykQWZF6fDhhEFkX1Df4+Ozrey30WI35nE3hMiotRj8GIhtVN2WzuDyn9nm5R56QyGlYAonsjIpNmNrwaId82kYkwtzUVbZwi/ffegcruYwWJF2QiIlY7W7Y9kXqw8aSRMjBtbb+VOIyIiSozBi4VimZeeQUQ8EWQ4bBJcDmN/JOlOOzKjQVOi0pGyGiDTZeo6d0mS8J1rItmXlz46hqrTbQDiputaNIFWNO2GwpEskxVrAbqbFA1YhuamW1qiIiKixBi8WCiWeel9SF1LXL+LGVNTxXHpRE27ykmjbPPXnV88phAXjylAICTjV/8+gFBYxkmftZmXMd2GtVl50ki4dOwgPHjVOPzsc+da/lhERNQTgxcLqe158Ylj0gZLRoLoe6nvJfNiVrNudw9dMwEAsHLLcXxwqAGBkAy7TUKRSSebuhNlIyBy9Fsc27aSzSbh/qvGYvbYQssfi4iIemLwYiEleOlUVzbKcpnTg9LbrBcR0FhV7phWmotrJhUjLAOP/X0HAKA42wWHRRNTRw3KhKh+TSqxfscQERH1PwYvFlLKRn1kXswaUCeIpt3TvZaNrMtQfHvueEgScKwh0vdiVckIANxpdgzPj5w4SkWzLhER9T8GLxZS3fPijxxdNjrjReitbHTK4rIRAIwtzsYt02N7eKw4Jh1v9thCSBJw2fgiSx+HiIjODAxeLKT2tJFZSxmFWMNugrJRCjIvAPDgVeOQZo+UcEosGFAX77vzzsGG71yO80fkW/o4RER0ZmDwYqEMlXNezG7YFTuLGhIsZzzVYu5eo2RK8zNw9yWjAcDyPTzuNDuG5WVY+hhERHTm4GJGC7nT1K0HaGqLZEjyMswJKHpbESAyL1ad/on3rbnjcOeckcg16eciIiICLM68NDY2Yv78+fB4PPB4PJg/fz6ampqS3j8QCODhhx/GlClTkJmZiZKSEixYsAAnTpyw8jIto/aodFNbpOclN8Ok00ZJljP6gyEly5OK4WqSJDFwISIi01kavNx+++3Ytm0bVq9ejdWrV2Pbtm2YP39+0vu3tbVhy5Yt+K//+i9s2bIFK1euxP79+3HTTTdZeZmWEWWjvrZKN0YzL2a90Iuj0qdbOxEOx/Yb1Vu0GoCIiCiVLCsb7dmzB6tXr8aHH36ICy+8EADw7LPPYubMmdi3bx/Gjx/f42s8Hg/WrFnT5bZf//rXuOCCC1BZWYnhw4dbdbmWcKvcKi0yL3kmZV7yosFLWAaa2gPIj/5/pVk3y8V5KERENGBZlnn54IMP4PF4lMAFAC666CJ4PB5s3LhR9ffxer2R8kNubsLP+/1++Hy+Lh9nCtVlo3aReTEneEmz25TvFd+0W98SC16IiIgGKsuCl9raWhQV9Zy7UVRUhNraWlXfo6OjA4888ghuv/125OQkHkC2dOlSpafG4/GgtLTU0HWbSSkb9ZV5aRU9L+b1h4jSUfysF2VAncUnjYiIiKykOXh5/PHHIUlSrx+bN28GgISlCVmWVZUsAoEAvvCFLyAcDuOpp55Ker8lS5bA6/UqH1VVVVp/JMuIzEtbL5mXQCiM5uh6gFwT+1ASLWcUwcugFJw0IiIisormnpd7770XX/jCF3q9z4gRI7B9+3acPHmyx+dOnTqF4uLiXr8+EAjg1ltvxZEjR/DOO+8kzboAgMvlgst1Zr4Yu9P6nvPibQ8o/21mE63Irmw/7sWJpnb8e08dNh9rBMDghYiIBjbNwUthYSEKC/vepjtz5kx4vV5s2rQJF1xwAQDgo48+gtfrxaxZs5J+nQhcDhw4gHfffRcFBdYOOLOSKBv5g2GEwzJstp4ZJzHjJcftMHV5oZj18rv1h7vcPmFwNm6eNjTRlxAREQ0Ilp02mjhxIq699lp8/etfxzPPPAMAuOuuu3DDDTd0OWk0YcIELF26FLfccguCwSD+4z/+A1u2bME///lPhEIhpT8mPz8fTufA6tUQu42ASNNuZoLx/7EZL+b+bFOGegBEjkVfNKoAV04owhUTijG8gJNoiYhoYLN0wu5LL72E++67D3PnzgUA3HTTTfjNb37T5T779u2D1+sFABw/fhyvv/46AGDatGld7vfuu+/isssus/JyTed29B28NJp8TFr4XPkwTC3NxdC8dNN2JhEREZ0JLH1Vy8/Px5/+9Kde7yPLsSFqI0aM6PL/BzqbTYI7zYaOQDhp34soG3lMzrzYbRLGD8429XsSERGdCbiY0WKZzkh82OJPvFna7AF1REREZzsGLxbzRIMSEaR0JwbUmbWUkYiI6GzH4MViIigR5aHuRM8Ldw0RERGpw+DFYiJ4OZ0keBFBDctGRERE6jB4sVheX2Uj0fOSybIRERGRGgxeLCaCksZWlo2IiIjMwODFYn2VjbxtbNglIiLSgsGLxfoqGzUqE3aZeSEiIlKDwYvFxNj/xgSZl45ACO3RjdNmrwcgIiI6WzF4sVh+Lz0vYqO03SYhx80R/kRERGoweLGYKBs1JigbiWyMJz0NktRz4zQRERH1xODFYqIc5OsIIBTuurepif0uREREmjF4sZgITGQ5ViYSxIC6XB6TJiIiUo3Bi8XS7DZkR/tZTnfre2lUljKyWZeIiEgtBi8pkGy/UaxsxOCFiIhILQYvKaBM2W1LUjZizwsREZFqDF5SQDlx1Jo488KljEREROoxeEmBvCSD6hqVzAvLRkRERGoxeEmBWPDSvWzEo9JERERaMXhJgaRlo3YuZSQiItKKwUsK5GYmKxtFMi8eznkhIiJSjcFLCuQrR6VjZSNZluEVDbuZzLwQERGpxeAlBWL7jWKZl7bOEDpD4S6fJyIior4xeEmB3ASnjcR/O+02pKfZ++W6iIiIBiIGLymQnxkrG8myrPw3EDlpxI3SRERE6jF4SQFxFDoYltHsDwLgMWkiIiK9GLykgDvNrpSGxHFpcUyaA+qIiIi0YfCSIvnd9hs1cjUAERGRLgxeUiS324kjr1gNkM7MCxERkRYMXlIkT5n1EglaROYlN5OZFyIiIi0YvKSIGER3ulWUjbgagIiISA8GLykielualLJRNPPC1QBERESaMHhJke6D6sT/8rQRERGRNgxeUiS2WTqSceGcFyIiIn0YvKRIftxm6X9tr8Hh+lYAQGl+Rn9eFhER0YDD4CVFRHno0KkWPPzqdgDAf142GkNz0/vzsoiIiAYcR39fwKeFKBud9PkBADPK8vCtq8f15yURERENSMy8pEj8kei8jDT8+vbpcNj59BMREWll6atnY2Mj5s+fD4/HA4/Hg/nz56OpqUn11999992QJAnLly+37BpTpTDLBacj8nQvu20ahnhYLiIiItLD0rLR7bffjuPHj2P16tUAgLvuugvz58/HG2+80efX/v3vf8dHH32EkpISKy8xZdKddjy3YAbCsozLxhf19+UQERENWJYFL3v27MHq1avx4Ycf4sILLwQAPPvss5g5cyb27duH8ePHJ/3a6upq3HvvvXjzzTcxb948qy4x5S4ZN6i/L4GIiGjAs6xs9MEHH8Dj8SiBCwBcdNFF8Hg82LhxY9KvC4fDmD9/Ph566CFMmjSpz8fx+/3w+XxdPoiIiOjsZVnwUltbi6KinuWRoqIi1NbWJv26n/3sZ3A4HLjvvvtUPc7SpUuVnhqPx4PS0lLd10xERERnPs3By+OPPw5Jknr92Lx5MwBAkqQeXy/LcsLbAaCiogK/+tWv8OKLLya9T3dLliyB1+tVPqqqqrT+SERERDSAaO55uffee/GFL3yh1/uMGDEC27dvx8mTJ3t87tSpUyguLk74dRs2bEBdXR2GDx+u3BYKhfCtb30Ly5cvx9GjR3t8jcvlgsvl0vZDEBER0YClOXgpLCxEYWFhn/ebOXMmvF4vNm3ahAsuuAAA8NFHH8Hr9WLWrFkJv2b+/Pm46qqrutx2zTXXYP78+fjqV7+q9VKJiIjoLGTZaaOJEyfi2muvxde//nU888wzACJHpW+44YYuJ40mTJiApUuX4pZbbkFBQQEKCgq6fJ+0tDQMHjy419NJRERE9Olh6ZC6l156CVOmTMHcuXMxd+5cnHvuufjjH//Y5T779u2D1+u18jKIiIjoLCLJsiz390WYyefzwePxwOv1Iicnp78vh4iIiFTQ8vrN5TpEREQ0oDB4ISIiogGFwQsRERENKAxeiIiIaEBh8EJEREQDimVzXvqLODzFBY1EREQDh3jdVnMI+qwLXpqbmwGACxqJiIgGoObmZng8nl7vc9bNeQmHwzhx4gSys7NVL3dUy+fzobS0FFVVVZwhYyE+z6nB5zl1+FynBp/n1LDqeZZlGc3NzSgpKYHN1ntXy1mXebHZbBg2bJilj5GTk8N/GCnA5zk1+DynDp/r1ODznBpWPM99ZVwENuwSERHRgMLghYiIiAYUBi8auFwufP/734fL5ervSzmr8XlODT7PqcPnOjX4PKfGmfA8n3UNu0RERHR2Y+aFiIiIBhQGL0RERDSgMHghIiKiAYXBCxEREQ0oDF5UeuqppzBy5Ei43W6Ul5djw4YN/X1JA9rSpUtx/vnnIzs7G0VFRfjMZz6Dffv2dbmPLMt4/PHHUVJSgvT0dFx22WXYtWtXP13x2WHp0qWQJAkPPPCAchufZ/NUV1fjy1/+MgoKCpCRkYFp06ahoqJC+Tyfa+OCwSC++93vYuTIkUhPT8eoUaPwxBNPIBwOK/fh86zd+vXrceONN6KkpASSJOHvf/97l8+reU79fj+++c1vorCwEJmZmbjppptw/Phxay5Ypj795S9/kdPS0uRnn31W3r17t3z//ffLmZmZ8rFjx/r70gasa665Rv79738v79y5U962bZs8b948efjw4XJLS4tyn5/+9Kdydna2/Oqrr8o7duyQb7vtNnnIkCGyz+frxysfuDZt2iSPGDFCPvfcc+X7779fuZ3PszlOnz4tl5WVyV/5ylfkjz76SD5y5Ij89ttvywcPHlTuw+fauB/96EdyQUGB/M9//lM+cuSI/Ne//lXOysqSly9frtyHz7N2q1atkh977DH51VdflQHIr732WpfPq3lOFy1aJA8dOlRes2aNvGXLFvnyyy+Xp06dKgeDQdOvl8GLChdccIG8aNGiLrdNmDBBfuSRR/rpis4+dXV1MgB53bp1sizLcjgclgcPHiz/9Kc/Ve7T0dEhezwe+emnn+6vyxywmpub5bFjx8pr1qyRL730UiV44fNsnocffliePXt20s/zuTbHvHnz5K997WtdbvvsZz8rf/nLX5Zlmc+zGboHL2qe06amJjktLU3+y1/+otynurpattls8urVq02/RpaN+tDZ2YmKigrMnTu3y+1z587Fxo0b++mqzj5erxcAkJ+fDwA4cuQIamtruzzvLpcLl156KZ93Hb7xjW9g3rx5uOqqq7rczufZPK+//jpmzJiBz3/+8ygqKsL06dPx7LPPKp/nc22O2bNn49///jf2798PAPjkk0/w3nvv4frrrwfA59kKap7TiooKBAKBLvcpKSnB5MmTLXnez7rFjGarr69HKBRCcXFxl9uLi4tRW1vbT1d1dpFlGYsXL8bs2bMxefJkAFCe20TP+7Fjx1J+jQPZX/7yF2zZsgUff/xxj8/xeTbP4cOHsWLFCixevBiPPvooNm3ahPvuuw8ulwsLFizgc22Shx9+GF6vFxMmTIDdbkcoFMKPf/xjfPGLXwTAv9NWUPOc1tbWwul0Ii8vr8d9rHitZPCikiRJXf6/LMs9biN97r33Xmzfvh3vvfdej8/xeTemqqoK999/P9566y243e6k9+PzbFw4HMaMGTPwk5/8BAAwffp07Nq1CytWrMCCBQuU+/G5NuaVV17Bn/70J/z5z3/GpEmTsG3bNjzwwAMoKSnBHXfcodyPz7P59DynVj3vLBv1obCwEHa7vUfkWFdX1yMKJe2++c1v4vXXX8e7776LYcOGKbcPHjwYAPi8G1RRUYG6ujqUl5fD4XDA4XBg3bp1ePLJJ+FwOJTnks+zcUOGDME555zT5baJEyeisrISAP9Om+Whhx7CI488gi984QuYMmUK5s+fjwcffBBLly4FwOfZCmqe08GDB6OzsxONjY1J72MmBi99cDqdKC8vx5o1a7rcvmbNGsyaNaufrmrgk2UZ9957L1auXIl33nkHI0eO7PL5kSNHYvDgwV2e987OTqxbt47PuwZXXnklduzYgW3btikfM2bMwJe+9CVs27YNo0aN4vNskosvvrjHcf/9+/ejrKwMAP9Om6WtrQ02W9eXLrvdrhyV5vNsPjXPaXl5OdLS0rrcp6amBjt37rTmeTe9BfgsJI5KP//88/Lu3bvlBx54QM7MzJSPHj3a35c2YP3nf/6n7PF45LVr18o1NTXKR1tbm3Kfn/70p7LH45FXrlwp79ixQ/7iF7/I444miD9tJMt8ns2yadMm2eFwyD/+8Y/lAwcOyC+99JKckZEh/+lPf1Luw+fauDvuuEMeOnSoclR65cqVcmFhofyd73xHuQ+fZ+2am5vlrVu3ylu3bpUByMuWLZO3bt2qjARR85wuWrRIHjZsmPz222/LW7Zska+44goele5vv/3tb+WysjLZ6XTK5513nnKkl/QBkPDj97//vXKfcDgsf//735cHDx4su1wu+ZJLLpF37NjRfxd9lugevPB5Ns8bb7whT548WXa5XPKECRPk3/3ud10+z+faOJ/PJ99///3y8OHDZbfbLY8aNUp+7LHHZL/fr9yHz7N27777bsLfyXfccYcsy+qe0/b2dvnee++V8/Pz5fT0dPmGG26QKysrLbleSZZl2fx8DhEREZE12PNCREREAwqDFyIiIhpQGLwQERHRgMLghYiIiAYUBi9EREQ0oDB4ISIiogGFwQsRERENKAxeiIiIaEBh8EJEREQDCoMXIiIiGlAYvBAREdGAwuCFiIiIBpT/DxsRVpXkvMQOAAAAAElFTkSuQmCC", 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" ] @@ -650,19 +672,21 @@ "execution_count": 12, "id": "aa3f4008", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:51.631660Z", - "iopub.status.busy": "2024-02-19T13:47:51.631293Z", - "iopub.status.idle": "2024-02-19T13:47:51.764226Z", - "shell.execute_reply": "2024-02-19T13:47:51.763705Z" - } + "iopub.execute_input": "2024-05-24T12:37:25.322315Z", + "iopub.status.busy": "2024-05-24T12:37:25.321796Z", + "iopub.status.idle": "2024-05-24T12:37:25.406543Z", + "shell.execute_reply": "2024-05-24T12:37:25.402731Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -692,19 +716,21 @@ "execution_count": 13, "id": "39cb107e", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:51.766802Z", - "iopub.status.busy": "2024-02-19T13:47:51.766604Z", - "iopub.status.idle": "2024-02-19T13:47:51.951413Z", - "shell.execute_reply": "2024-02-19T13:47:51.950859Z" - } + "iopub.execute_input": "2024-05-24T12:37:25.413155Z", + "iopub.status.busy": "2024-05-24T12:37:25.412715Z", + "iopub.status.idle": "2024-05-24T12:37:25.621446Z", + "shell.execute_reply": "2024-05-24T12:37:25.620380Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -734,14 +760,16 @@ "execution_count": 14, "id": "760bd263", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:51.954388Z", - "iopub.status.busy": "2024-02-19T13:47:51.954181Z", - "iopub.status.idle": "2024-02-19T13:47:51.958604Z", - "shell.execute_reply": "2024-02-19T13:47:51.958093Z" - } + "iopub.execute_input": "2024-05-24T12:37:25.625839Z", + "iopub.status.busy": "2024-05-24T12:37:25.625660Z", + "iopub.status.idle": "2024-05-24T12:37:25.633356Z", + "shell.execute_reply": "2024-05-24T12:37:25.630655Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { @@ -765,11 +793,11 @@ " 1.64428109e-03 9.53197714e-04 -5.45450869e-04 -2.80998822e-04\n", " 1.59136941e-04 7.38240716e-05 -4.13664358e-05 -1.74579288e-05\n", " 9.67744748e-06 3.74610168e-06 -2.05413769e-06 -7.34256601e-07\n", - " 3.98257402e-07 1.32202237e-07 -7.09282453e-08 -2.19709845e-08\n", - " 1.16601214e-08 3.38459230e-09 -1.77684428e-09 -4.85085285e-10\n", - " 2.51925667e-10 6.48958256e-11 -3.33432158e-11 -8.12799381e-12\n", - " 4.13195149e-12 9.55498771e-13 -4.80687010e-13 -1.05592419e-13\n", - " 5.24752655e-14 1.10454430e-14 -6.02774535e-15 0.00000000e+00\n", + " 3.98257402e-07 1.32202237e-07 -7.09282453e-08 -2.19709846e-08\n", + " 1.16601214e-08 3.38459233e-09 -1.77684429e-09 -4.85085275e-10\n", + " 2.51925718e-10 6.48957767e-11 -3.33432388e-11 -8.12795878e-12\n", + " 4.13189925e-12 9.55535215e-13 -4.80638850e-13 -1.05625737e-13\n", + " 5.24914276e-14 1.10219183e-14 -6.06441767e-15 0.00000000e+00\n", " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n", " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n", " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n", @@ -825,14 +853,16 @@ "execution_count": 15, "id": "ef085fb4", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:51.961468Z", - "iopub.status.busy": "2024-02-19T13:47:51.961274Z", - "iopub.status.idle": "2024-02-19T13:47:51.964404Z", - "shell.execute_reply": "2024-02-19T13:47:51.963829Z" - } + "iopub.execute_input": "2024-05-24T12:37:25.637493Z", + "iopub.status.busy": "2024-05-24T12:37:25.636911Z", + "iopub.status.idle": "2024-05-24T12:37:25.641331Z", + "shell.execute_reply": "2024-05-24T12:37:25.640169Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [], "source": [ @@ -860,14 +890,16 @@ "execution_count": 16, "id": "66dcc5f2", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:51.966744Z", - "iopub.status.busy": "2024-02-19T13:47:51.966567Z", - "iopub.status.idle": "2024-02-19T13:47:51.975599Z", - "shell.execute_reply": "2024-02-19T13:47:51.975115Z" - } + "iopub.execute_input": "2024-05-24T12:37:25.645719Z", + "iopub.status.busy": "2024-05-24T12:37:25.645526Z", + "iopub.status.idle": "2024-05-24T12:37:25.651103Z", + "shell.execute_reply": "2024-05-24T12:37:25.650379Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [], "source": [ @@ -892,14 +924,16 @@ "execution_count": 17, "id": "33dc7c82", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:51.978537Z", - "iopub.status.busy": "2024-02-19T13:47:51.978332Z", - "iopub.status.idle": "2024-02-19T13:47:51.981859Z", - "shell.execute_reply": "2024-02-19T13:47:51.981384Z" - } + "iopub.execute_input": "2024-05-24T12:37:25.655373Z", + "iopub.status.busy": "2024-05-24T12:37:25.655119Z", + "iopub.status.idle": "2024-05-24T12:37:25.660950Z", + "shell.execute_reply": "2024-05-24T12:37:25.658643Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { @@ -941,14 +975,16 @@ "execution_count": 18, "id": "23287700", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:51.984354Z", - "iopub.status.busy": "2024-02-19T13:47:51.984173Z", - "iopub.status.idle": "2024-02-19T13:47:52.045944Z", - "shell.execute_reply": "2024-02-19T13:47:52.045436Z" - } + "iopub.execute_input": "2024-05-24T12:37:25.663414Z", + "iopub.status.busy": "2024-05-24T12:37:25.663322Z", + "iopub.status.idle": "2024-05-24T12:37:25.713724Z", + "shell.execute_reply": "2024-05-24T12:37:25.713011Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { @@ -1001,14 +1037,16 @@ "execution_count": 19, "id": "00e8b329", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:52.049058Z", - "iopub.status.busy": "2024-02-19T13:47:52.048820Z", - "iopub.status.idle": "2024-02-19T13:47:52.065668Z", - "shell.execute_reply": "2024-02-19T13:47:52.064968Z" - } + "iopub.execute_input": "2024-05-24T12:37:25.718425Z", + "iopub.status.busy": "2024-05-24T12:37:25.718290Z", + "iopub.status.idle": "2024-05-24T12:37:25.738958Z", + "shell.execute_reply": "2024-05-24T12:37:25.738633Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [], "source": [ @@ -1057,19 +1095,21 @@ "execution_count": 20, "id": "f8c1a6c4", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:52.068527Z", - "iopub.status.busy": "2024-02-19T13:47:52.068297Z", - "iopub.status.idle": "2024-02-19T13:47:52.199742Z", - "shell.execute_reply": "2024-02-19T13:47:52.199164Z" - } + "iopub.execute_input": "2024-05-24T12:37:25.742441Z", + "iopub.status.busy": "2024-05-24T12:37:25.742326Z", + "iopub.status.idle": "2024-05-24T12:37:25.860399Z", + "shell.execute_reply": "2024-05-24T12:37:25.858077Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -1105,19 +1145,21 @@ "execution_count": 21, "id": "6f50c502", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:52.202908Z", - "iopub.status.busy": "2024-02-19T13:47:52.202557Z", - "iopub.status.idle": "2024-02-19T13:47:52.577756Z", - "shell.execute_reply": "2024-02-19T13:47:52.577252Z" - } + "iopub.execute_input": "2024-05-24T12:37:25.864167Z", + "iopub.status.busy": "2024-05-24T12:37:25.863483Z", + "iopub.status.idle": "2024-05-24T12:37:26.030734Z", + "shell.execute_reply": "2024-05-24T12:37:26.030410Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -1149,19 +1191,21 @@ "execution_count": 22, "id": "f40fd289", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:52.580463Z", - "iopub.status.busy": "2024-02-19T13:47:52.580204Z", - "iopub.status.idle": "2024-02-19T13:47:52.703681Z", - "shell.execute_reply": "2024-02-19T13:47:52.703212Z" - } + "iopub.execute_input": "2024-05-24T12:37:26.033855Z", + "iopub.status.busy": "2024-05-24T12:37:26.033556Z", + "iopub.status.idle": "2024-05-24T12:37:26.123275Z", + "shell.execute_reply": "2024-05-24T12:37:26.122760Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -1225,14 +1269,16 @@ "execution_count": 23, "id": "abe72e5b", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:52.706780Z", - "iopub.status.busy": "2024-02-19T13:47:52.706562Z", - "iopub.status.idle": "2024-02-19T13:47:53.048201Z", - "shell.execute_reply": "2024-02-19T13:47:53.047098Z" - } + "iopub.execute_input": "2024-05-24T12:37:26.127527Z", + "iopub.status.busy": "2024-05-24T12:37:26.127418Z", + "iopub.status.idle": "2024-05-24T12:37:26.297581Z", + "shell.execute_reply": "2024-05-24T12:37:26.297216Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [], "source": [ @@ -1261,14 +1307,16 @@ "execution_count": 24, "id": "0a65ffc2", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:53.051335Z", - "iopub.status.busy": "2024-02-19T13:47:53.050964Z", - "iopub.status.idle": "2024-02-19T13:47:53.065481Z", - "shell.execute_reply": "2024-02-19T13:47:53.065018Z" - } + "iopub.execute_input": "2024-05-24T12:37:26.299837Z", + "iopub.status.busy": "2024-05-24T12:37:26.299661Z", + "iopub.status.idle": "2024-05-24T12:37:26.309064Z", + "shell.execute_reply": "2024-05-24T12:37:26.308249Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [], "source": [ @@ -1290,19 +1338,21 @@ "execution_count": 25, "id": "c32f1808", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:53.067992Z", - "iopub.status.busy": "2024-02-19T13:47:53.067810Z", - "iopub.status.idle": "2024-02-19T13:47:53.173389Z", - "shell.execute_reply": "2024-02-19T13:47:53.172869Z" - } + "iopub.execute_input": "2024-05-24T12:37:26.311147Z", + "iopub.status.busy": "2024-05-24T12:37:26.311031Z", + "iopub.status.idle": "2024-05-24T12:37:26.379378Z", + "shell.execute_reply": "2024-05-24T12:37:26.377774Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -1333,19 +1383,21 @@ "execution_count": 26, "id": "a42a0a42", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:53.176403Z", - "iopub.status.busy": "2024-02-19T13:47:53.176104Z", - "iopub.status.idle": "2024-02-19T13:47:53.299214Z", - "shell.execute_reply": "2024-02-19T13:47:53.298486Z" - } + "iopub.execute_input": "2024-05-24T12:37:26.386950Z", + "iopub.status.busy": "2024-05-24T12:37:26.386314Z", + "iopub.status.idle": "2024-05-24T12:37:26.483051Z", + "shell.execute_reply": "2024-05-24T12:37:26.481112Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -1379,19 +1431,21 @@ "execution_count": 27, "id": "b9f6cc53", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:53.302005Z", - "iopub.status.busy": "2024-02-19T13:47:53.301738Z", - "iopub.status.idle": "2024-02-19T13:47:53.423480Z", - "shell.execute_reply": "2024-02-19T13:47:53.423025Z" - } + "iopub.execute_input": "2024-05-24T12:37:26.487365Z", + "iopub.status.busy": "2024-05-24T12:37:26.487223Z", + "iopub.status.idle": "2024-05-24T12:37:26.580996Z", + "shell.execute_reply": "2024-05-24T12:37:26.579877Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { "data": { - "image/png": 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oEUVNeiz7edZvw/XmmAzIcZuHagjeB6eOxD44btQxasNNodhQh7SJq2BQCR1+Txra2sr5kueZbKx4jNoLRxwnjRoRIzguAkcWvalC3JTd0G/4wH+8aV9uediLIFHsyNYRj2Urrgr9c6h9cww9c6LIsYPz/I57UUVYUKM2xXOZjxkmYhGT2LEVND7Fi6kM28faItRrpV8f8bnjI2IjS1X5juKUvS+Vb3GjQuW3kWESNyHFzDDzPxhlPFUE2UaCxJJ3ajQH6IgXaTRH2OMqpqzqSV2y4ZE+wNVIzK2QEq8lCiZO+bjpRYWzls/r2tyXDtnXimM+djYR17GiqgThJBNHvsSNq/F3uNk2vkLg87o6s7H4tRPHUEzIvU8sDMixyqp0YgQnYiR0Sso1HWXy6lCpIgVFuaZtBMQUSeJEXGTHZcdcevjYRnvK9Pr4Tk35EDdUURNKoHDJvg9q7xzbSJAYrZE1MBSjNzoTsi6a42pAjpEc/0QPTvTgaCnTSMw1EbtGIWwJmYKygXofqnEs7wxxLHVN0Rvjy4dj9OAQ/Dek9FSF4qZqYROickuGTQNBVdpLTGGZ/Dm23hyxa7LJmxP3sqITPTgRL7iKm6qjNjaixjX1QsG3MKIKLtU4VSRHNjZ0JKeyyitCeorT98Y0jypuyhA2ZQkVW2xKxVUmZzFaM9SaLURzgJ6wKSuaE6uswhAFTqSA75RUyKgNR9jUoQoKCCeMXISOSpBQBQ0F6VoWfXHKMBqT1rc0FocWN/0sbIZb+XufbtN+0FRpL5nQsU1b6UrKrcrJY8oqOFHgRHLUJWpTpbBptvMPrtmWed+0MnCN1MjGiSIHsKuEokZxbMRRZVGd7D0QBA8lNRVS3IQWNqL4KAPKNUURJBMsNkInRDQnt5+VoWdOrLJyJ1ZRRbr4FDdiJY9K3MgqfrjiRlU1JK+0SowvEcoclxcXagUWZZzsPMXbRBWYtttJ1B4hesPpd5PFh7ihVBpxtj8YbrWlr7qiuj/Ze5V9rSjVVuLn2WO2lVa9BeM2D6GIEZyINiXVj1Eb1QPSRkyUgeq+TJGj7PvURThMER3b6Itt+qqwjkWaqu5QfDeu4oYSsaFGa+ooYEzvT/TXpO8hG9GRRXOya6drcKM56bFg0ZyYsvJCrKKa41VUvqM2WXRRGxGOT4dzrLOWpBrG8Pu86pSICDVNRrlv392JKZVP4jqFNQzVVMYqKZcqKkP1lE3llCk1RRE3dRM2dSkzF1FVTMn8O6qKLHENl2orm0qr2AGZDuf5PWB/N0U4cMVNNuWha9qX3elaTJOY0kumXcNVKS15eqSYAuKmd8p4UaCms6hpKXpKz3xvfZFSyuLZoGwSNxQo4saUiqKmoThpp9BN/nyguj/Ze1R9fcQ1bNJWKY1W0v0ZkO5QLhkXU1ZhiCmqOUgdojY2PhsRnxGbKqGmmoD8e9NFdShrUs3IYrrKxvRrWkNMU1HSYf2CKXpD8sUYhI1xfsBIzUhF6a39QoRGVRo+3GqTjMjpGrZpK5kJmVNpRTUgx5QVnShw5hgu4sbGa+OajlIJE1XEhjJOdt0yoPSFCSl2qB4cKx9NjQWJV3+PwVxMqZoyIc5RCQ5KpIZKv4ga2T1QhI7MnwPQKq4oQkfVCdnWm0PpmROrrMxEgTOHUImbOkZtQgmbKiPt2WtXIXZ0QsckUFy2YAhBqF44Rv+NI9zUh424oQobjqixFTQjnv/D7Zf8EGbvLSt2QggdVZNAignZWzQnGpDJRJPxHDAZh0pJ1VHYqMfK1+3N8fPfILHsmcMRD9TIiC6qQ91ygW0WNnzOMRtzjMbac6ZtGlTlu5AIHE0Eh2sspvpuRFTixiRsQgsa32JGh0zo5M5LDMYyM7KqkaDMjJydH8SEbGlAnmvm47hVQ6QLRdxUFbWx9dlQhU1Zosa0JkX0iPeq+/0tvk/1ZprJgbWK15elkGzSSiFTU6WkuTgRGkLvG5/4EDchRY2LoOHMlUZtMvOpUR1uRIfrz6F2QqZEc7Tl5DFlRSZWUQ0wupSUrbhRVUiJFTji57rqKFn1jryiR15JZLpWcXyiFTfNGfOLQ3o903Vz99A2v4/e+iavET3SxY2+Ue7NZX6VcNJTvqM3ZYibkVY79zIx0mznXlTEeVxhZJpjPC+8P1nVFbXiSldtJY4XGwJmP+dUWqV0o4utpCfMMx/HKqsiMUU1gCkqm/Lv7jFm1Mb0kOSmo1wqo0yiRgdXtMiYtYyHctNapnSWetdw+XVoO3jr70E3njOX0w/HS4pK0wNHl57imItdxY2N30YlbjhRGtsITRmpKmOKSnNeTF9RU1cuaSvxXPYYt2/OXO+ZE/vgzGGoKSmOuNFFbcRr6Tw6plSWKh1l6mWji3RQozU+sI3ycCM85giVal41kRyWELXM+pDbAGiiMlrTsqS5X/faDpVTtuJG18fGVtzYRFlcojMjrRnjy3Rdm/O+IzopYsRGF81JjwH8aE7SStTRnAPEaE6HGMEZkAiOy3YLlKhNKBNxiIiNa7TGNN/WSAzYRXlM11P9sarzr1CjObaRGJe5uiiOKoKjO5dbj2gwrkP0xmdKSiVuuKkmW3Rihcr+tv4/j01UhxLNAWgRHR8mZN/RnEGM5HCe31HgDIDACWEktjERD7qw0VGG6NFdQ/e73SVl5ZKq0s0dFIHD8d5UIW50URtTBMQGH0LGRFVCh1pxZZu28lJpNQdSVlHgGBgkgWPb2yZk1MY01raXjex3bpWihoJ12bjmd7iN0ClL5NhGcajl4l4FDtV/QywN5xiLqxQ3voSNrZgZYeRv9xvUv2+x40vo6Pa2sikpV4mc7BhpNGcARU4UOAYGQeBwU1J1jdrUUdhQf8fbNr7jiB4boeND5HD62/iI4tgInM7ncqNxKIGjS09Rozc2vhuZuCkzamMjZjhChopK8PSD0KlDNGcQRE4UOAb6XeCETEn5iNqEEjahRI3vog8b4aONypQQzeGKHB9RHGqaqgyBo23wZ5GeoqamTOKm6qgNRdiEEDIUQoidfhA61s0BBySaExv9DTC+U1IUkWKbjpprwsa0rr55X1ohURQa6fuT/T7XzmvLrylroNdsJwWRo2u0Z3uOcn86ymj+Z7M9A7VySjfORdzYRG1chA1X1Iwyxk8RTWnpPYhCJ713ldBJ37eugWB6TtzvyrZZILVJoGwDT7FBYG5PK01zwMJ+VpJNOwedWCbex4jiRtV4jxK1kc2Tjac069OVfIv3r19fXTZtKsdWlV1zGuiJ6+heFCjXprxn1TzdNYvjZWP14lNXik3/etLGuc7xhqY8XAVV7HA3uJSVMwP6qI1MxOhLqE3l2TNacTPanJG+OHDnq+7JVG6uK20Xj/soLec2Ccx+rCop70IpJ5cw6GXkUeD0EdnojUzcFM7N9sRNVkyIfW3EeeL4dI7snKm/TWduvpeND2GjQjWXKmpshItsnrH/TgCho52jEDnF6Jn+PVMFD3Wccn4N/7rUpadU6Lw3qnFAMXqjEjYycaMVMAGEja2Q4UARPOk96sSOiqqEjqx3TjpO1gk5Rdo3p5l0hU5WCBVEzhzqfBxTVH0CRdyE8NrUIR0VyjAcuoIqew2VVya9P1WqxpS64qStqCkhMV0VMuWUnVNG+ikEur43KnTRG8pu4FyvjU7YaK9jiNaYoIoealpKt252DVP6CpCnsFR7XPlKXbmmrbIfZ1NShT2tJLuT5/ayyuxjVcc/JnwRIzgDiI+ojUs6yqb7sDSd5BitkYknm+hMd/5MYnyZ7pWbSsrOl85jpq3kXxfZ/ejei36urzn9jm30RoSSyrJNR8nXUkdCABijNTYRHde0luq+fEd1bCM6WXylrVKU0RzhvCqSAwxuFCcKnD6AE73JipsUk9fGVzrKh7Cx9dbI1jaN18ERL6p5yjGWQsd32io/zu189z76UMhwy8NtTMhZdD1vqKmp3OeefDZUf43teS62okc13qdXhyt0XNNWKdlzRm8O0T82yKmqmKKqOT7FjbiOaqx4XDenM889FeW7EspG0PgmXTMZkqenTBVQKWLax7biSly/uG4+RSSrrJKN7cvUkqNI6S5DKA0np60sUlMqcSOfq47YqDCJCtfzAC89Ja5nmpuOl6WvAPcKLG7qyjZtlf48zUiqq7Ifp3RTVgfSVXM1VRUjOAOMKG5U0RjbdJTPiI2MUNEa2+hM79qJ8mW6nvS8ZfrKFNERx8rWNSGaw7m4CGvvv3A9iRoXKB2LZWMB2k7gUsFjEbFxida4RFxCVVypzrlEdcTPXSI6NmkrMZoDKKKLGeMxoDcdD1oUJwqcGuMSvZFFbsS1suPS47Ry8XKEjYjJWyNdK4CYoY7X3Y8Kn0LHRuRwUlUUweKLOqa7qI39KJhSU6pqKd3nnXn+hI2tiODiu8xcdS6L7muiFohyj05+rv77ShU6prRV9l9pGTmDQRI5MUVVU3yImyziHJt0VMhUlE0llGyOa6rJJGBs1pKlebL3KUthUdJXstSVaRsI2RgxXcVJVVVBKSkxT/4bVdfi7AOK4rsRcRE3MkzRGptzPuGmplRzs/Ns01dAPoXlmrYCiqkrXdpKVmklkm0KOJdTVVHgDDAFIWSI5nB8NlUJG12khotPMUO9jk7s2Agdk8iRlZLThJBa5Kj8N9mPVeXfdfbuuJqHQ0Hx3RTn0MSNLhqjI7TooXprOHOy82RCRzyuKjUH5F4d30In67vJjpWJnPSYLz/OkVd/qi+3cRCJKaoa4jM1JRM3POOxW5M+WSqK4q2hpKG4aSdOqklc3+aluwfT9QrnNF8v2djcGEV1lWmdMum36iuuudg2emNjKnYRN7YpKt/N/lyrpygCTZfCykIpNc9+zV0rrgAU0lbZsYDcuE7y4zAYhFRVKQLnmmuuwZFHHomxsTGsWrUK99xzj3Ls3XffjUajUXj9/Oc/z4275ZZbcMwxx2B0dBTHHHMMbr311tBvoxRC+W5STOmr3lrhhI3qvqimYYqo4XpnsuvaeHVM6+nuTze3cLxEkaOL4rlW5fkit6mghMTwG07cZFN7LcsHRj+JG9mxskSNDh+Ch+Md8uHV8VFaniLzdaVChuXHYRiOB4Hgb2PLli245JJL8NGPfhQ7duzAKaecgrPOOgs7d+7Uznvsscewe/fu7uuoo47qntu+fTvOPfdcrF+/Hg8//DDWr1+Pc845B/fdd1/ot1M6nJLw4tz8v7IHjmy+T2FTVrSGK2bENUOUicuuJUN333UWObZwxE7VfgCOUdOmNDylruJGRlmiRoetCdnGgFyl0JGJHFmFlc7Y7iJy+j2K00iSJOhv9tWrV2PlypX4/Oc/3z129NFH4+1vfzs2b95cGH/33Xfj1FNPxfPPP48Xv/jF0jXPPfdcTE5O4tvf/nb32JlnnomXvOQl+MY3vmG8J85262VSdmpK9pe36q90rscmpLfG9iEbWsRwUfXHkfl0ZGNlPhrZVgniONFSYFpH9Mlk7y9RjEs/Vq3DGts0zU/Ux7J/wmUjMOIvd0Da5E9lMBb/UgZ46SnX6I2NuPEhbCiMNadJ47jsmx0mj+Vu/aAaLzuuGivz6gDFnjriLuaFzw94dLLenNR8nDUVp+eznpv0fFv4NznwHJnN+nMObOeQdJ8xjY4XB+j+mz5n6uTH4Ty/g0Zw9u/fjwceeADr1q3LHV+3bh22bdumnXv88cdj8eLFOO2003DXXXflzm3fvr2w5hlnnKFcc2pqCpOTk7lX3QghbrJQysYp4oaaipLhGq3hRGfEdUziptGe9f6i3p+IKpIjjvUVyTH2DXJIL3G8PVX7gLoYOsByojOUvjd1FzeqKMlYc1r6CgXnOtwIDyd6w01fcSM6KbJ0lasfxxiRHLBUVdDbf/bZZ9Fut7Fw4cLc8YULF2LPnj3SOYsXL8a1116LW265Bd/85jexbNkynHbaafjhD3/YHbNnzx7Wmps3b8b4+Hj3tWTJEsd3Fh6XkvDeGuox1MoqUdxkoXhsbNJQIiE8NFwxYgNV+HDes0zkUAzDXJGjS1XZNv9z9eF48/EErpYyCSBdx+I6ihuR0EKGSijB4yt9JX4fTEKnNy6frup+LBE5KbpUlQ8/Tr+mqkopE2808iHwJEkKx1KWLVuGZcuWdT9fu3Ytdu3ahU9+8pN43eteZ7Xmpk2bcOmll3Y/n5ycrJXIkUVvuKhSUza+m96x7Nx81CZ/bbtIQve4ZRqKm3IKJWS4NNqzSFr5vy1UpeKyHjSNmaQwrlAe3uaXkFPW0L8vegm463nfmAzEpvOm5n7U6E0Wrrjx7bdRiZu6It6bLqVF6avD6Z/DKTUfac0odzLPlpRny8mnhf+IaXm4rEeOWDoug1s6DvRn6XhQgTN//ny0Wq1CZOWZZ54pRGB0rFmzBl/72te6ny9atIi15ujoKEZHRxl3Xh6hfTfFtYvHTH+Rq8QNtdSY05BPu4t1nwoaGem9yYROlSKHCqf5H1co1QVTON8YqWHm3HRbMfgQNyGFzWiFwmdKIWSy92zy75j66nBEja6BYCp0siInJ2wMIme41S40A9QJILE/TipkuKQNAPtN5ARNUY2MjGDVqlXYunVr7vjWrVtx0kknkdfZsWMHFi9e3P187dq1hTW/+93vstasG3X23XSPKcSNa4m3qoqIW+VETTs1Z5LSX7p7Lhwj+o8oFVaq7436ftSiVRVd1DWI1I2lzqkTJlHDSU9xoje5czUSN6PN6UrFTfYedPdh4xNyTVXJxma/V2K6SvqxRPTKUpxOfpwBLh0PnqK69NJLsX79epxwwglYu3Ytrr32WuzcuRMbN24E0Ekf/eY3v8FXvvIVAMBVV12FI444Asceeyz279+Pr33ta7jllltwyy23dNe8+OKL8brXvQ6f+MQn8La3vQ3f+ta3cOedd+Kf//mfQ78dr2SjNzooJeHdsYF9N+IxysOTE63hRGmoERqdwCiL9B5mpd2K7aM5stQWZTuG/L3pU1UqTFEcX2mmxmzxl2uduiDL0k+cTTUBXvQmf86PkLERNnVEvC9KdAegp7OoUR0x5TXanOkeG2nOsCI5KdlITRrJkW3XIKaqZOdst3IA+iuKE1zgnHvuuXjuuedw5ZVXYvfu3VixYgVuv/12LF26FACwe/fuXE+c/fv347LLLsNvfvMbHHTQQTj22GNx22234c1vfnN3zEknnYSbb74Zf/EXf4GPfexjeOUrX4ktW7Zg9erVod+ONzipKRFTakrnu5GZRSniRubLM4kbjreGKmwooqYOgkaFSej4SlmZRAonVZUVRyphYRIc8nRZcU6Z6Sxpkz9JBZXMf8PtcwOEid6YsI3kqMQNR9iMNcoVQfuSokjxLXiookZ1jCNyUkL7cboIIkdGv6WqgvfBqSNV98Gpa78birhRRW+yxzmlzyZ8RmnK8uSIIkWHTOio1pD1whGFjjim0ANHEA/Z87r+OKoeNaaeOPmxDuM0vXDYfXB0PXAkm2xS+9/Iet+oOhcPa9IQqnRFZ6w83QGYxQxF3MiEDTdaU7awkSETOyIqsVNYSzOO0idH93nWfJyKnKzAyX3czvTFOXB8OnMsjdY49ceR9cYBpP1xqhI4temDE+HhcysGG99N75i9uCnej9pbI8PWR+Oylm8411O9B045uW4MZ88pXfWsyotj/lnye0yHTy+PzGAsi9qY0lPdY5oUVJayxI3MM+IibsYa091XHcjej+qest4dW/+OzGdDEZYp0r45BD+OrNOxeC60H6cfSsejwCkZXfSGiy41pRojO6eaayNusg9YirAZBEGjgnsvMpEjzlUZkMUx+XXopmLqub6jgt43lNJwnfcmiy41ZSNussgf3DTzMFfUVNVDJ5Tgyc+niRxZ3xzA3XTM7Y+TQhY5EuouckrpgxPpEDI15dt3E0Lc5D735KWpSsg0Zg4Yg4dofyOojMQiMo8OxZsjMx+rtoIQfS5ZP46NF0fqCSL6a7hm4RDmYu4mmjb+Gwq66E1+nD+xYxO14UZpZNcoS+So0kvZ96BKZ2W/DjrvTvYaWZ9N9mPTuRRfpmOKH4fky8kiGI5TP06diRGcCimr300Kx1QsO+ZD3OgiGr6iNI2Z2eAv2bUoUKM61GhObo5l+Xfx2up5JnykmmqzZQP04scmPaWK3lCNxZSqKdU5k7gxRi4Y0Zoytm7g3ofqXlyjOz4iOZTy8d55vVldtimneG6upKqiwCkJbrdizkOB67sR53XG0SumXMRNYV1PaSeu0AiBrdhRQfHm6ESOr1RVfv3sHPl1Zec55wYBSmm4inxKwl7A6M7JxI0MjremLqJGB+UeqYJHXDd/Xi1yVONMIqd2fpwMdRU5MUVVAjapqRROaqp4jXSMu6lYha4SylQlpRM15uvWOzaavT9TGiv7fmUprOZMok1Z6dJRuvJxam8cal8cCrpr6tJPsl443tFssqlLS+nOuUZvstimpmzEDddXw2HUoxF5ilAtpYJaGp5+LcRU1mhzOpe6EtNV+bG01JWqfDyF2umY2x/Hij5IVcUITgWU7bsRx+TX9lcOro8e5P8HqFIw1LSTEzOzfl5EfER1KFVW3bGEfkS9sdk13aI4umODglbMeMitqaI3utQUJ5LjS9ywuwI3prsvn2TX5bxkmNJZsq+LLpLDEZ2qSE7vmL3pOPtzKZqOBz1VFQVOYEypKZetGAprWPhuusdKEjf0kmiioAkoTIww1+QINIrIya9Nr6yipqq40Ty9B0g9r1RBRDAUm/agMmFKT6miN9RIjq3vxlXc1EXU+IByb3UQOZTKqpSq/ThA/UROTFEFhJKa4kLpiSOmpnybil3ETfF6cnGjpK6pqex9ESqrKCksWfVUNl1lSlXptlKgpqpc0aadCBVRddqSIQvXY8PfeFP+F73tA1OEI244KShbMXNwc4o1/vez/jZPFu85m/aSpZ3GGtOsdBWnmkpWXWXT6Ti7KWdKek5XPUXdykFGHVNVMYJTIiFSU721xTF8U3FtxU2I6AuARrtNfrGwjOzI71EfyXExHefHZa/JS1vKKDMqY9tHyrguIdpD9d+YoKamstiain2LG5tIzcHNqdyLizjf9OIgvg9Z1KqMSI4v03Gum7ZgOpZ14abQL6mqKHAC4Ts15cN30ztmXzGVH1eSuCHCESxc0WI9lyF2OCJHd55q/PbVyM9UTSVCCWaELhXXNS8Tofzyp0ZobMzFKbaN5EKIG1dRUzZcASR7XzKRI37tOCInP09+TiVyeuf5IicllB8HqI/IiQInANzUlM1fu7a+G9Nf5zbl4GWKG29RFkdCiR2qyOGUj1P9ONwoDhff7RF8wGnyRxE61N44FHSpqSyciikRrrjhiBqXKIpo+FW9fGErcoDi15Aqclx65HBMxylB/TgZglc7MqjRrQweoUrCXXw33WOGhxan101+Xhhx41PENKbbxhdrPRuhpRE6ZYgcH1Cf26GETVXVWhT/jSk9pX5AaTYEO4DqQcgtB7cRNyZ8CRrbeS6CKKTIyZ9zEzm9YzTTcfZnURQ53rpy1zRVFQWOZ7LRmyy+fDfZX+oq343rNgw+GvlZixvJg98kGiiChStefAkeI4FFTm6sIurGjeLI74t2zGZMKWh64KjgPhyo+07p0EVyspQpbmxETahIDPW6KkKJHJ/djk2VVbZNAAcxVRUFjkeoG2mGMBXLsKmYqlzcFOap36CN+LDFVvCQxE5AkWNqtmiDKU3ly4ejvr79XBNN4Zc6hfRBYZOeopiLVaJG9SAsS9xwRI0PQSN2GKZ0HDbdjwzZ+ypb5KjGpdhs51CqHwf1SFXV4BYGD1Nqyn3d4nqy6E1vHr1iKjcvkLiRVg1ZiBsWM231ywKrqJBO6JQkclyiODK4aSqX/wNVlKDahPA56SkO1NRUfk44caPDVdDYCBgb4cOJ5pQpcnxXVqXomgCm2IqcHDVJVUWB4wkxNeW7JNy3qVgcJ46lV+KoxY18g0i6mVh6bZOgsBExHkQPR/CUJXJ8EypNpbyepz8MfCD+hcvFlJ7iRm9U6CqmOOJGZybWiRsbQeMajaGurzxviOZkqbPI6R6TiBxKE0BXP04dS8ejwPFA6JLwUKZi1143JnFTuGcHcUOKlFhGY5RrOYge0/2WIXJ8RXHk13VPUxXXzP9bZ1qav4BTOOkpE5SHoGkDycIxxYPdJiXFETY+xQwrWkOI5sjeg0zkyHrlmK6nEzn5cWaBy6msSqnEj5OhCpETBY4jtiXhZTbz41RM2Yib4nr+xY0WUpRmpveyxULw6ISOVuTIvjaWfXJc4UQBOdQpQuMKNbJjEjUu0ZssuioewG9KirMzt62goaafKCLHJm1FMR+7iByq0dimsqpsP05+sV4UpwqiwPEMtSScvp78X9kYV1OxrbjRddbtzLUrA/cStZGJmqzYcRE9jCiPTuRwojmUvayqjOLY7pk2KMj+Opalpzil4dzojSk15Uvc6KI2vsWMzXzTGO15yXurs8jhmI5TvPpxMtQpVRUFjgNlpaaovpvedWmmYtsuxblxnsRNYZ5r1IYrXHyKHgU+U1bF+W6pKvP69mbjQRY0HMqK3thgI25UUAWJj2ooyvq254Hi+6SKHNPWDlSRk5+j//mgmo6D+HFqWjoeBY4l1NRU2b4b23SCa5diX+LGW9TGBzLRQ1lbI76sU1biWN/7cjG2cKA+e0M0F+wX6Fs3VB+9kYkbk99GBUVQhDAS63BNW9mIHNk88ToUkUOJ6riYjkvx42QoO1UVBY4nfJeE99bN/2vy3XSPWZqKqxY3WnxHbWyhCh7LlJV8LfPXOEQUh5P27Fua+V/U6S9o8Re6+Ite1/8mxZSe6h2jR29cjMWFtRTiRrqeZUrKLs00Q3rR13NLW8lEjo8Kq5Aih2s69unHyS9SXaoqChwLVKmpUCXhXN9N7cQNoTsxqfRbBysdJfHOuJSJ64SORTRH6cvxHLUpXNfTRpz9kpLiNPOrAmqvm94YXrqFK26U6xqiNibchAtvrks0h+LLqULkpPg0HevSWBTqkqqKAodJ6G7FHN+Nz4opm/2lfHUnNoobHZQoio14sZlXRjRHFIolR3F669LG9a4t/5fyc+8bzk7iHHQN/uTGz+IX0TZ6Y2sszsIVNy5RGxsxQ8W0dohoTpayRI7seAjTsejH6adUVRQ4jlBSUyF8Nz4rpmy6FAcXN65RG4cuxcY1bdNkhmiO9LjFBqPUEn6ZedwUxSkrJaVrl2BNSREbnf/GlJ5K4UZvuIgPYZm4MaWkVFCETVnoruViQvYlcnJzmCLHprKKajpO8eXH6QwuP1UVBQ4D29QUF8ommr2x/Iop1y7FvrZe0IobHZYiwisUoaObK4G87YMhiiNC6XDsYgimVuO50C9pryw+NtfM4it6Q9kV3HfUpmxhw7m2bdrKh8ihRoq4IieFK3K8+nEyVJWqigKHiCk1Fcp3ozMV21RMuXYpttl6QdXjpjjPITqSzi8b3T17iub4SFWpzpmiOCnUNFXvGupzLlSxHxVgZzDWQU1PyY753n1bfDBzozaUdJSOsUZb+fKJSzQnHVM4RhA5pl45qlSVCEfkcCqrUrz7cWqwIWcUOExCdCum+A90IXuqqbgqcZP7XBalqFs6yqY83CVtRcAmVZXFNorDTVN5TSlViPjXqQmu/6Z3zl7odI67RW8ou4GbojbqeabIiVnE+BY9IaI5PhoCUvw4nXNuIsdkOk4J5cfJTw6fqooCxwFOt+JQvpt+EzfFORWnozhChmpo1s1XzRNQVVfl5/kxHMvQpTGl4wmpKEp1IP16jMEM741rZRXXf5PCETUqQqamZNeyTUe5ChUf0R7fJuS6iZwUU2VV95hFE0Cb0nHdXlUhiAKHgGqn8NwxQ2rKhMl3Y9OPRPXQqYW48RG14eKtW7GD0FHNJYqcEFDFjP2eU7QqrX702ajQ+W9Mzf106Lw3XCipKc5+T6GFjQkb0eMazcl9btErRzRyU0VObk2JyPFhOtZFJU0iR4YuihOKKHAc8VE1RfHd9K7nZiqujbjR4Rq1se1AzMXFE2QpclyjOCaoaaru+AA+nCqEjswYqYLapRgIm57KEio1RTnWOV6dsNFBETwu0RzZ193VfMwtHxcJIXJ0fhwZJMNxCUSBw0BWOaU6Lx7z0cxv4MWNrWAILWRM2AoyosgR4YqcLJS+OLpjvbn18OGU+dwU/zrlGIxDp6d02KSmqOJGLw6qEzYqTEJHPY9XPVa2yKH0yEnxZTpWRXGkyDocC4Tw4USB4wGflR261FR3jEXFlHdxY9Od2KWsmiMSqsLmPRBEjmuqykcUp3dOdx2/f5mV8mwk/OI1CRldKF9El54yCR1qesrkozGlpjjiRnkPTh6bWenLJzbRnM55XjQnS5kix7fpmAN5o84SqqmiwGEi89/IxxWPUVNTvk3FFHGjfS8+etzYlFK7zLPBZbsG6n1RRY6Aa6rKFds0lXo9h5upKcOMB4QsPZXiai7OrWVITVFMxRxx4xK1MQkZ34InVDQn93mfixxqFEeGzHNT9vYopQica665BkceeSTGxsawatUq3HPPPcqx3/zmN/GmN70JL3vZyzBv3jysXbsW3/nOd3JjbrzxRjQajcJr37593u9dNBhn0YkYn4QQNyLq1IVe3JB63NhEX0JHbShbMYQSOhSR4yFVpaKMNFXhmopmlZRnYVWl5+S/RBXo0lIpvrsU6wSLje+GKm5CChvTPFfB4zuaU1eRk0KtrOJg2w8KQFCjcXCBs2XLFlxyySX46Ec/ih07duCUU07BWWedhZ07d0rH//CHP8Sb3vQm3H777XjggQdw6qmn4i1veQt27NiRGzdv3jzs3r079xobGwv2Pkz/dyk9bDjXkflpemNox1w3z6SIm9znqh43IlVEbZw203QUOqo1KdfNwE1VZb9/ZaWpxDHUn/2yRUyZf0n2/iq2j9rYVE+ZvDecrrq9Mf4Eme/Uk4vg8R3NqaPIMZmOfSD7o4BjNPbtwxnyupqET3/607jwwgvxvve9DwBw1VVX4Tvf+Q4+//nPY/PmzYXxV111Ve7zj3/84/jWt76Ff/qnf8Lxxx/fPd5oNLBo0aKg966CW/pNGWMspdX4bqjbMPSuGUbc5MdbpGJ8RmxCdDVO1xxqMefNAEOE/2qycTPt3PUa020kw5nP220krcz9zMwCQ37/bmnMJEiGGmi0EyQtfYqWMqbuuEZuTFDTUzbVUyp8+W7k98D7v+bbT8O5zj6D2SN9L/uSlnB85sBx+f/j9Gu1LxnOHct93pzGvtne5wc3p/D72dHu56nImVLMya432pzGVHo8M2a0OYOp2SHlx9ljKkaabeyfbWGk1cb+dgvDzTamZ1sYbrUx3Wb+7svSTIBZ9e+GpOnXzwoEjuDs378fDzzwANatW5c7vm7dOmzbto20xuzsLF544QUceuihueO/+93vsHTpUhx++OE4++yzCxGeLFNTU5icnMy9fCH7hlCiOfYltJqUgSdTcenixkc6yod/hopVFIhYMeXDj6OaR/re2zX485Vp8RUJ7QdCpqd00RvfvhsKoczCLveh9/v4SVv56pUjW8+lukoGNU1FKRm3MRqHIKjAefbZZ9Fut7Fw4cLc8YULF2LPnj2kNT71qU/h97//Pc4555zuseXLl+PGG2/EP/7jP+Ib3/gGxsbGcPLJJ+Pxxx+XrrF582aMj493X0uWLLF6PyaDse7nw3cIXpfCqpW4CZGOovhnysDH9T35cVS4mI1d01T9hi5tpdqDalgwY9pUoIRIT2UxeW9sfTed4/r3688Q3Mi9fKG7P5e0lfZzi145rs0AZfhKU4nl4lmqNhqXYjJuCD+QSZIUjsn4xje+gcsvvxxbtmzBggULusfXrFmDd7/73XjNa16DU045BX/3d3+HV73qVbj66qul62zatAkTExPd165du0j3zTUYu4zLYvPwMBlEKxM3KmyiNgHETDIzg8SnaVk7xp/pWOvH8VxBlbuu51Jw9XVKuYwR6800JU3UOHDTU+QtFkx7V3kSNz6EjU7Q+BY7JqEjP05vEOirV052PVt8Rw4pGBtpBhI9QQXO/Pnz0Wq1CtGaZ555phDVEdmyZQsuvPBC/N3f/R1OP/107dhms4nXvva1ygjO6Ogo5s2bl3txsDEYc35BqytM/Ib/O2vVRNxIjzMrjyxIBY0obGTHrPApwhiRnNBpKm7qKn/NA9dT/Jz7gNq+ocwuqll6Jbn+ysOV65C9M/YPyZBwhYvP6E4V0ZwsOpHDidC4No9UlYtToKanyjAaBxU4IyMjWLVqFbZu3Zo7vnXrVpx00knKed/4xjfw3ve+F1//+tfxh3/4h8brJEmChx56CIsXL3a+ZxM+fjnb+nAofz2bzMrSdcsSNxVEbVSChjInCB4FHDWK47snjgqxu7bpdyLl/4H0jwfi26E2D5P9dRnaaGwjZkKkp7L4jN5w8RmRcRU8IaI52s8dIjmA+efCpw9H7IejQ/p/SNZYM2DDv+BVVJdeeinWr1+PE044AWvXrsW1116LnTt3YuPGjQA66aPf/OY3+MpXvgKgI27e85734DOf+QzWrFnTjf4cdNBBGB8fBwBcccUVWLNmDY466ihMTk7is5/9LB566CF87nOfC/12clANxr43E9T5b2TISoSVZcMhxY30uEWkx4AvcZJdp0GpgsoiVD/lzymqqmRzxLGadQsVVR5othPMKqqimm1gtuWvcipdL9JD9Ve7Kj1lay72Fc3hiBufXhrqdfYl9D8Axxqz0qorVaVV59yMtNKqUFFlqLBS3pNhHHWdlJHmDPbPDmGkNYP9bb4cSCusWq1ZtNtyddJoJUiECKvsWAiCC5xzzz0Xzz33HK688krs3r0bK1aswO23346lS5cCAHbv3p3rifPFL34RMzMz+LM/+zP82Z/9Wff4BRdcgBtvvBEAsHfvXrz//e/Hnj17MD4+juOPPx4//OEPceKJJ3q7b90O4iEb/IXw39jiRdzYbM/AFDbBoi2Ka5DFjk7kcNCUmYtl4yoaM7NIDpSPN9qzSFqdj5szCWaHeL9oBqEUvC6E3IdKF71x6Xnjur9UWcKGcm2T4EkFm0roqEROZ86QcFwvcrKIJeTye1PPN0EpF7dhqDWLGYXQMdJKAM+ip5EkDEk7IExOTmJ8fBwTExNKP05W4DTaPYHT+fjA8dmsv6A3Vhyn26JBtT0DpXux2LnYVD1l9N9oojdacVNy1KYMQUOBJHR0Akc1XzZHHJsZIwqcXBQn0xMnyX7c6n2cFTjp8SRzLI3gJLlxjQPnhM+HVOeFtYTjvfPyc+I6SVM2Lsl/nL7FNATeSrp5/24lRzPppqjSY63WrHIjweFm21hBJRqMZf4bWfM12TFZBZXOXJyN4GQFDtdc7Ds15VvUjDZ6P79Tib90oknwqProyIRO53jx/3hWlIgCJRt9yQqcbG+c7Jjs/LQvTvZ8KmKyYkY8tj/9t51+3nsv6cf72y1MH/g47YWTCpn0eBrBSY+3283usTRaM9tudnvhJN1naqMnbNoNNGaBJz7wYaigPL9T4l5UBkw7iJvmqM6F8N/I5+n/81v5M4zVQgrfjO2u2/BnAk6mp5FM+wnHk+6phAhWCEJFBUnXDhghNaHz3nCMllxMURuK/0YlbkQolVNcyhA3o41m96U6Lp7jYvLucE3Ivjo/25qNu/M9+HDEfamsKXFn8ShwLLFt8OeKj9+xlLb91KqcAh5NxL5FTVbYyI45XSOAlyi/hnp9G7Mxd+sGFaqIYzHa6OVyfiH8og0B9WFj8yDzsU6o1JQNNsLFp9iRH+eVwNvuTs4xiOfWLKkfTqiGfz6NxlHgEKCWoMoI9UefbGPN7jnPf2nrH6CE/xTMSIWrqMmKF4qA8S12WNhGcTyUjKc0S4rMAGFLxUMRuqLKFqq52Mu1SkxN+RIoPtbiRnMoItBneb5pLZ2Y9t0Pp44N/6LAkeBjB3HfG2yaMO9lZVizpFLi3vXU4sYGXyLFZZ3gURwN3I04Odi0HvCBywa3VUPZYFOGsasx4eFo+5e/Db7EjU9RQ7kG9zqlVXxpoi+u5eK9cfzfsTYdumWU3fAvChwNoRr8cTfYLNt/o40AaD0lCt8NEY644UZpbLBZ30rkBDBN576HjJ441NSVr47GdREpsr8mbboYczoXl9FR1oe52CY1RREEZYiaKq7P9eLYRHTK8uGIP88cH45rwz8fRIFDxOUXsesGmyll+W/I2D6YJQ96iripMpUU/NouqT5LvP4szFGoe1DpOhibMDZyI5qLfWO7FUMoUTPWaGGsYdeWgXJP8i0j7L4GtrvAk9e39G/Z+nB0kBv+ZUiafozGUeBYwG3w5/36vv03mr/qQ6Y+OFTij1FgEjreUlVMH47v7xX358tla5GQe7sB8B76dq4kySD7y9qXwdgVdedeu9SUT2GTChpR2MiOUakqmpSFbwp39+G4CHCgJ/R1URuj5yZAJKf672bNsdlB3GWDzbL8N97Lw6npKQsvClvcpOXoqlcJVOnHSeGYjUMYjalbNtSNupqKs/gQQCH2ogrpVVEJGuqccPdFMxv7SFNV6cPhQE3vhjYaR4EjQDUYu6eb9NUkof036nnEN+ZRKOjEAEvcUAWMJ8Fjuje2YTqk+GII2lCpK8r/GV9/MGjvw+GXqu3u4ikuDxauIDH5b4rrE8vXlb1g9OLGJjpShkAR0d1nFV2YVWmq0D6cFN8bb8qMxjkfjkfREwWOAptfqiEa/KVU4b+pS3qKhIs4cBA71qkz2yiOBxFkE73TRQm5P5tVVWXJMFZ1lIh824Z6pKpSXHw3tPX5URoqZYokCjrB6SNN5erD8bnxppQSGv5FgUMgF7mpqMFfbz2e/8ZbeXig9JS36I0vLKI7Qf04gX040WhMI2QX47rCqZ5y8d1UEaUxwY3i+EhTUbHpeVSmD0dGVQ3/osAJBOf3YUj/jQyr8vCSYaemQkEUO9YiR3a9GhFye4a6lIhXge6BU4bB2Ko02TI1pV+zXFHDuV7ZhmNfnqiqfTh1avgXBY4Gmx3EaT4Dmv/GFh9/lTt3Lx5EXPw6ffA14xqNffXCka8dbGklXHMxtUS8Dvjy33DRR0KqidjUKVLkWi5uEsOy8z58OK6U1fAvCpwMOoNxFtcGf1Q4VSimv7SlosdH9+IA6anaRG+YWKXUbLw4JbznmLrqwBE9nCZ/dYeaniqrJLwqVO+hjDSV73JxDiYfTr80/Ov/n8AA+KqW8tXgr7ee2n8jw1vpbw12t5ZShbgpK1WVuybPh9NvUP9/9It+GCSho8PVd1MlVV9fha9ycemcgD4c6403AxuNo8BhUHWDv+J1KvDfmB7SZUZvaoqzyKlRVKquWBbz1A6bdIFqk01q11uf/pu5ACcSZbMBZ4g0VV18OHaT/RmNo8BRELrBn2qDzRD+m2Dl4Z4jB32TmprjAiSk8diGupqVuW3vdYRoytdb20JkDUBqytVw7GauDpOmoq5Rlg+naqNxf/wklgB3B3Eu1A02e+P9+W+k+CgPr4o+EBg8sWZRLt4HXwMupQoVQ2hc19uDu02Da/mtDS4PRpvNNXnr1yc9VKd7SXFJU/WTD6cMo3EUOAK+dxCvk/+mzumpQUhNUemHiqq6UNfoTEROv0RvbKBGcWzSVFQ4m2/K0lRl+HDYZP7Y8G00HtyfRg/YiB3qXFdCdYOtKj1Fpi7iIPR9eFo/J14zAtfUzThpxV8Ng4K2Yy4hVTLo/ps6RHFcIy8u2zb49uHoNt608ea47Cwef4sRof4fJ6WUauy/yVGSiBnU6E2/vK+5UhIeogw1MhhQRY7f3dCr9eHYYFMhaOXDiX1wwhHKYFxH/00d0lNk6hK9qQqi4ORu1zDXozWhdzSuEyHNyrTr+4+WjDaGta/QhEhT1cWHkyIKG5uNN6tgbv9mO4DLDuIhN9jsrRPOf9M3EMXN7PSM8lXVPdHWqvcvisjcwMUrEtJ/4yJgqCKn6lSVa7m4DK4PJyX14VArASkbb1axs3gUOBn8GYL9rKNCFgkKvj1DFstNIqs2F5cqfg5Q2vuLAikyIISIwviM5LiYjYtj/KWpXNJQvv04dWn4FwWOApsdxMvaYJOK0/YMnAdmTQy3LkKlTNETmVvsnx2q+hZqQdUREgqh7zFEmoo611c/HA5VN/yLAodJ6A02OYJHlrLibM/gzX9jic/oRhQkkbqxvz13hI2v9FRIz0w/pKps0lQ22zbY0G3010cN/6LAETDtIM5fz26eGOFx6R5L8d9Yp6dCm4vrbiwOeX91f+8RKftn6x+pcMGlg2/V+BJQPnvihE5Thfbh1Lnh35wXOL53EPe9waZIKP9Njrr4OUpITZWxbr+Ui1dN0ie6YLqdv9H9Bz4fdGEzl6hLOq3MqjdfPhzKxpsmfLV0mPMCJ4Wzg/gg+G/KTE+FNBfH1FQkS5mdj6ejoCFTF8EAhI3i+MBG1FDLxeviwynLaBwFjgGfTTzr5L/JrRU4PWVFP6Vn+uleIyRm2vX/1ViW96IsyuhZw8FGlIVOU2XhlIvLcNpwM6APJ4ej0bj+/4tLxHeDP+4Gm+J1fER42P1v6pCeqjg1VfY1+o1kyK8Ho19SU3ORQd2moR8MxzJ8+nAohPDhmPBpNJ7TAufV1/yt8pyPBn++SKM1VP+NN08ONzJRYu+bfhceccNNmrBxFj+EX5aJ4Q+biBt1Ewkpfvrr0MzGLvSzD0dGmUbjOS1wfMMRNiH9N1Js/De5+YT0lA/ig79vSFqDLwzafZCqGgTqlp7K4kOgcbdu8FUuXrUPx6Xhnw+jcfzfC3W0xmeDP3GDze7cgP4br+XhnhjY6E0UZmRm+1AYzQVDscs2Df2Kj1SVL7NxmZtvprgIG44Px6nhX4akCRz3havJ46PAIRJ6g03xOqVHeAC6/yZU75uaioTSBFUd/E8WhHj2y1JTXq8zWxRZdY7W7EuKD+IpybG6Udf0VJYQ0SPbrRvU6/FETUgfjmpHcUpZeNk7i5fyP/qaa67BkUceibGxMaxatQr33HOPdvwPfvADrFq1CmNjY3jFK16BL3zhC4Uxt9xyC4455hiMjo7imGOOwa233up0j3Vp8FdYx4f/xrU8vIwHb42MxZEBwrO/xnd11ZRkG4d9s/UXLnOREGLNd5qKfF2N2HH14QRr+GdBcIGzZcsWXHLJJfjoRz+KHTt24JRTTsFZZ52FnTt3Ssc/8cQTePOb34xTTjkFO3bswP/8n/8TH/zgB3HLLbd0x2zfvh3nnnsu1q9fj4cffhjr16/HOeecg/vuu8/7/delwV8IQqanQpiLay9uahqBKguTJ8dntZRNyaipSjJSDXXw37jegy+zsWuaiurDkc717MPx3vDPIpITXOB8+tOfxoUXXoj3ve99OProo3HVVVdhyZIl+PznPy8d/4UvfAEvf/nLcdVVV+Hoo4/G+973Pvzpn/4pPvnJT3bHXHXVVXjTm96ETZs2Yfny5di0aRNOO+00XHXVVez7q7LBX9X+mxye01O8a89tYaBljn1tZGkokzByEU6zkohMGakqWeSmXwnV8K6OuEZxuGbj/Dh3743ttg0qVOkqGT4b/lEJ+pO5f/9+PPDAA1i3bl3u+Lp167Bt2zbpnO3btxfGn3HGGbj//vsxfSACoBqjWnNqagqTk5O5lwkf7R9MG2wWxx+4diD/TZWba/Z79Kbq6/cTVT67y+qpI27XECnSD/6bLK6G4xBCz2lHcY9m5BSVDyc1Gvv04eSwbPgXVOA8++yzaLfbWLhwYe74woULsWfPHumcPXv2SMfPzMzg2Wef1Y5Rrbl582aMj493X0uWLGG9D9sGf6749t/kxtp2LyacZ5mLCWOjuOhv5kABUiQiJWSaKotrV2MVaXRnJPB2DjJ8NPwrJbbYEL7JSZIUjpnGi8c5a27atAkTExPd165du1j3zw2bp+dcy2HTjrGydZJW8VsnO4ahZuZ876aTYeJTZ8gwTnK+McT4E54wtjk8OOH8uYD4u9AhBR+J9DX7Ev5Del/C/333+9lR9hwKaSp1fwVhWR8NOIPe9fz589FqtQqRlWeeeaYQgUlZtGiRdPzQ0BBe+tKXaseo1hwdHcXoKO8HIGn624cqaemjOkmrgUY7wWyr8zBIP6+MoSHvaarG8LBTmqo5PFRpJCeKrP6g0S4nTeWjJf2gsy9p91Waaiqh/X7al8i/91OJ/yogWXsA8twA1Xj726ngaQnHO59T+kXJKhGNYiZb5cz4MgeN4IyMjGDVqlXYunVr7vjWrVtx0kknSeesXbu2MP673/0uTjjhBAwPD2vHqNbUkf1laGNm5ITf07FptYmNKJbtAzQrOZYMMb+1pkhNd5zkpqlzOWtGOsyxr41NvymXlLCsNNVXUzIdoXdwLpMQD/a6ohI39PnF38v7iIrcReykTElEj4vhXRQ6OmTmfamhX9KjypbgKapLL70U/+f//B/ccMMNePTRR/GhD30IO3fuxMaNGwF00kfvec97uuM3btyIf/u3f8Oll16KRx99FDfccAOuv/56XHbZZd0xF198Mb773e/iE5/4BH7+85/jE5/4BO68805ccskl3u9f9rOnO9ZPGwd6S1NJkKWpGsNu/0FrH0WZY2JExBR19NlCwSa66qP1e8Q/1MhJne9BJvJCpqey0ZlsekrW/JEqjHxX9qWRGpcu4LnWDhYpq+C/kc8991w899xzuPLKK7F7926sWLECt99+O5YuXQoA2L17d64nzpFHHonbb78dH/rQh/C5z30Ohx12GD772c/ij//4j7tjTjrpJNx88834i7/4C3zsYx/DK1/5SmzZsgWrV6+2vs+klXS/mKaUEm09P7/Qk6EGGjMJZluNgtk4aTULxmLZMQw1u2bjpNWiVVPp0lQBUljUNatOVUX6DM+iRreJoA2ySE6I6peIO67RG/ma6oe/j4iNcm1N+ioVOraCh1JhKIvcyFo2uNJIEguZ2edMTk5ifHwcSzf/LzTHxjJN+hq5hn3pX4nZfaTEhn6Ndra8W/5vs50U9qLS9cIRx4jVVNleOKmYaUqO5XrhKLoZF6qpslVRum7Glts1GH04NayqIkeONBEcWfSqEOWSRcp0YzTnstG5rLk8Zzo/8HHWnJ6mO7PHRLN70h3T+4tKlX7tfp6JcHbXEaKePXN+73PZue6xZv58GqFJP06a6AmcVtI932gl3V4baYqq0Uq6qan03yHh8+Fmu9e8TCiLTctku/vzdI/nq1DELrFZgZN+nBU4ad+SbLlwel5s6patpMmukZsrzMlW7Mj6scj7thT/ktaVSFN8OFU2+6NEb0ziRozgyKI3lPRUNoKTFTii2DFFcLLn07nZ9FT2vChoxH9Tg7HMf5N+vL/d6kZqUoEjRnDa7Wb3WDvzb+q/6Qqc2Ub3WKPd6EVu0gDE7/dh55//BSYmJjBv3jzomDsdmjSofDiyentbH474y7s7V3gQUPDpwyGnqTzhmqYCapqqmuPpKQ7c/dnqgEs31n6B6gUZJHykx3x5kGzSU6748N/st4zY2NCYBX668QPk8VHgeITz+4EjaLygKBenzxfmhHqgE9etpciZY1Ra6VcSZRiOI/Xw4ajwkZrimoup6Skb/41MIIXqrK3z35gMxj62VpnTAucn/99FynOm6ipKHxxffxB56YdjA1fEEHviGKM4cyAawuoVVDNk24VYrUN4bjj72Ai/JH00FIuoCeFd8UGo6I2NuVhHSC+OiC//jW5TWiv/jaXYmdMCR8RUZWGzT05nHu+bI/oZXAhWLl4DyojixEhRePppg9q5hizyMAi49rypCkp6Sh6hsYvaiP4bFS6VUiI+GvylDOZPr0d8/v+uwodDWsu2XJzYE8cqWtFPEY5+utcICd/VUiGQpST6mbqlqWzEjQ9zMZVQ3Yt1dH03DP9NSpkN/lKiwDmAr4Z/dfHhcLZt0BLo4e3DbAzECEskT5k+2blgPPZFnSIhvoRUqAaHNimpOvtvfDb4e+IDH2bdw5wXOP96yaWkcbY+HF9wfThO1CVNVbHh2Ne6vsTcoNMvqSpxmwaxRDzS/9RFkPWT/yZF57+h4sNgDESBUyDrw/EhUmw33rT14QQvF/eYpiI9+Oue/gl5f3V/7xEpgy50fJtoyyRk9CZ0eqru/ptgDf4cxE4UOExsjcamsb58OByqTlP5JKaqInUjbfI3F/CVrgnpw+kHY7Gv8vAQlOG/8WkwBqLAURKq4Z84tkofjhZOmiq0AAqcqmoOD0lfkYgPRgZoY00X6pL20eHzHl021uyMddhJvGL/TYpTgz9HgzFQwl5U/YS3/aM8raOCui8Vl2S4Vdy6QcZQS7otg2lMY2iosHVDY3jYvH2DB6oSLKX5b+rim4pEHFFFWly2c/AZGfLZ+yZ0eoqKb/+NS4M/FVyDMRAjOAD0RuM6NPxLhD2ATNj6cLRUnaZiRHFKi8b4/JpEgRKpAS7bNYSqKuqtP618meZRqDrCZJOeMhHaf5Pi03/juoN4lihwJIRu+GcuQ89vUKgda+PDcd22QbpmwJ44umvMJYgiiLu/mGvkr9/xnfevM2VW5civH0ZE2IofH9iai/Vr0r5P1PJwV1T+G58N/kIQBQ4RasM/Fx+OazrU+7YNJUUVBrWMug7viyJgvbcZqCm+Sk8jgwdVePmMUpW5uWYV/psUK4NxLBMPg2vDP+pcV7hl50DgcvGyqEsUpybGat6amcid4Wdhrkd1BgndX/SUh+ygbteQUnVqqnMPbiKmDv6bFHaDPwONWTv/DRAFDpuqGv758OGo1/ZULh66J86A0M8bbZZNmZ2JI+6E9uFUic/eN7aU6b+hQtlgU4vnHcSzRIFzAKrRWAdF6FAjL2X6cPTjaviE6QOBwBJslK8xpcFin1OqmDFUbeh+WVMMlVm4DwwfuPxF7+thrF6/+ohJSp3uJaUu/pvUYLxf8RDi+G/KbvCXEgWOAhujMW/9/Dp18uFUlabiiYIKH/CGaw96NMq1waRv6hrloVagUAhpDrbZ6FFXFt0vURyOuHGJ3siv3X/+m35q8JcSBQ6DEA3/XPDpw6lDmgoYfHFASk8NYHTGB9n/V3W2haj+4pVh86DJPrCyf8VT0xc2YmnQfTg6XAWbKSLmWh5O3Z5BRiijcdUN/lLm7k+tBo7RmLJOGT4c2TGOD0dLHdNUQDVCwCF6Y+29MX396/r9IVLXCExEj0sUp+rUUNXXV+GSnjLO0YiZ9JxtOrVuDf5SosDJEGpncc6Y/Hi6D8e8lsO2DTpkD9cyozg1inZYiRsbcVLCe54rpeMmOH+JciI3dYfqwxmEVJUO1XtwMReHSk9V4b+xbfAnI0Qbh/hbTINpZ/FQDf9C+HDYa+h8OCU8YGuZqtK871reLxNuxC/sPmrBllbCDatPW3gSqsL08LPx4VDQiZyqoih1it6ESE+Zzpflv9FRhsEYiAInGGVtvFmJD6duhBRcQ0O9lyWs1FSNIlJAWEPxXE5N6R4yPoylJnz6cGz3YerMLVdsuBqLQ+IrAlMX/03VBmMgChwSNjuLU87Z3YtnH46PcvEAaSqgoqhIVtAQxYa178amPNxwnrtNQ0xF0aiqJT31YRUC3tYCbn6c9FUX9JGn8OkpHXXz36Sw/TfSgf4MxkAUOEpsuhiH2HgzuA9HN575sKwUawMvX9BksRZhtsZgDxEem41XdZFC7s+mTdQxFMZQeYmU1TrfBV01lQ8/Tlbs+BY8dRJQgKHDtAf/jW0k0OS/SSmjwZ+LwRiIAqdA6IZ/KXX14XgrF2fgLYpDFSke0k6A+d7YVVNBU230n4dQUR3a/wu7eaz7cAiJW/8yP4CLiOGmMMQHnC8fjm3JuE3KJ6TgUcGN3oTG1n8jw4f/ph8a/KVEgWMgdMM/cZ0QPhxZmsrmr/hQaSoT7CiJGJVxjNLY4Jya8gDHU+WtpUDu+v6ij2Xi1MOjJLw0gAvQPDC0AOCKnTLEkY/0lK/y8Kr9Nyl18N8AUeBYUXXDP64Px4hG7NQlTVWnKqXG8HBY3w11bGD/Dffny6Ubt8/oqBTPv0i52zXokD1syjAaU1D5cEKnqiioojsuoqYOpe2+y8PL9N/4avDniyhwiNSh4V8VPhwtHhvXUdI5qbAwCYwQBL9u7HDcl1BLxV0eIKa/ym26GfvAJVUVQki4RGoo9+RzY03X8nDj+o7+GxMc/41Ngz+XHcSzRIGjwbfRWBxjTi2l4+2UrfkvdItycR9pKgVcz0po0WGzvlX0JoBwyX0PM99nU2qSKoB99cCpS6m4LFRu47cJvU0DF5MPp/i5JJpk8U2ipKpSUVFV1KTM6/tIT+XmBPbfdH03ws+zq/9GRogGfylR4EjgGo1djZGqjTc52PhwcvjoasxB8bC33c7AV3THZY0qfTchU4khqp58dP6uiziS0TNm8n6eTQ8hysOwLlEcjh+nDLGRvQb3OmWZi3XCpUr/Tb81+EuJAoeAyWiso298OLpruXY1Zm5T0Bgast+3KV2DIVSqSnsBoH9txHEawcRt2BjCYKy8Vo1KxKnU1XSs2nQzyLU0atKXyEnxKXZc19qXJMr3EDo9RaEO/puUOjX4S6nn/9w+oKqGf2X5cKy7GuvSMKqqKoPQCSF2fIoa4z1yozfM8XoBKk9P+fJiiVFHMa3aO+/lcn4hbPSXxVezP+pf0L6MxnzTqvz+bFJVrnAFikuURkQnbDjixjY9VVf/TYr1BpvSgX4b/KVEgWPAZmdxnw3/qvLhaKFEF7h+E90c5MWOi+DxGakh3YvWs1Rf03AZkUHltUusSBQJGa3R/aVsEj2q9IMqiqN7OJp8ODb4juLIUAkXnxGfNGKjMhSrt6vgixsO2e9t1f4b5wrCwDuIZ4kCxxHXqI3Y8K+uPpxClMAkcmRjsmMdd9f2Fd3h4u26Lu+fmp5iite4bQON7l+uQuOz1KcgPiC4fxmbKMOUahPFMYkcXbqHi88oDeXedMKGI258di/OIhPAMlFTlv+G2uAvpMEYiAJHiWg0ttlZvCxs/tq2SVNZixzP0RwRX9EdyjVY+DIWa65LNRer0lM2/puQu4jPNXw9hGRwojjyMWFSVb7Fju21Kde3jdpQxI1resol8haqgs+p03e/9cF5/vnnsX79eoyPj2N8fBzr16/H3r17leOnp6fx53/+5zjuuONw8MEH47DDDsN73vMePPXUU7lxb3jDG9BoNHKv8847L+RbkcJt+Ofbh0N90LD+Mhf+6vcicmTjsuMdozki3tJZLmvYpKYoZfYezcUUKHtQ+RI8/dbxuAxyKajMx/sUKQud2VgXIfBlfOX2xilD6NgKKl9Rm85xQ3k+MXpjGseNAqVpU9soI6XBn9Fg3K9l4u9617vw0EMP4Y477sAdd9yBhx56COvXr1eO//d//3c8+OCD+NjHPoYHH3wQ3/zmN/GLX/wCb33rWwtjN2zYgN27d3dfX/ziF0O+lS4+RIrrxps6bKpUCj6ckCIncDRHBleoBE19uYgbARtzMQVbr43KYKy8DuH/gbTXFPHtyMyKspC4LHQeunKqrI01Xb04vlNV6jn+ojrcKE1xvr+oTeccT9yI3zPX8nAb/42KMhr8+STY/7JHH30Ud9xxB+69916sXr0aAHDddddh7dq1eOyxx7Bs2bLCnPHxcWzdujV37Oqrr8aJJ56InTt34uUvf3n3+Ite9CIsWrQo1O3nSFpAQ9MgU3beNCfLbKuBZjspzElaDTTaCWaHgOYM/76l1xpqoDmTHFi/iUa78xOVDDXRmMn8dA01gcznSauFRrt3c8lwC43pzM0OtYCZ7OdDwIzipsWx2TmAfJ5qDhNRuCQHruVN0ITsd+MheqNKT9ls20BFbGwZohjHpZVDGexvD2GkNYP9s0MYUfxnnpodwqiH/+hTyTBGG9PO61RFKkrGGrSfOZ8RIK6w6ZyjCRvZMY642aeI4MlwTX363mBTRqgdxLME+zNl+/btGB8f74obAFizZg3Gx8exbds28joTExNoNBp48YtfnDt+0003Yf78+Tj22GNx2WWX4YUXXlCuMTU1hcnJydyLQlk7i4vYhOpNPhzKg620SE46toJojogfw3CLdm8eU1PU6I1vyvLf1KWs3NZToKpEoZJ9GHHTVDq4nY07x+yiOLZbOfTWkEdhXCM08muFj9r4jtzYUoX/puwGfynBIjh79uzBggULCscXLFiAPXv2kNbYt28fPvKRj+Bd73oX5s2b1z1+/vnn48gjj8SiRYvws5/9DJs2bcLDDz9ciP6kbN68GVdccYXdG8mQtBKt63u2BTQVQQbdORvS9dIoT/5cJyIEdEROQxKxKTWSA+ijOUAxOmOK5oh4iO6w8SG2HH03Jlx631D8N4NE0m6goYgEtdtNtFqzmJ5tYbjZxky7iaHWLKbbLQy32t3j+9stjLR4P4u+Ijcqfj87ioObU8rz+5JhjGUiPuLnnWNDGGsU73Ff0sKYJlSdioYxx9xDKJ+OvvKLH7XpnHNLSQFFcaOK3uQEb8n+mxQn/01g2BL78ssvLxh8xdf9998PAGhIQoxJkkiPi0xPT+O8887D7Owsrrnmmty5DRs24PTTT8eKFStw3nnn4R/+4R9w55134sEHH5SutWnTJkxMTHRfu3bt4r5tJbYN/2z/QtX9BZ2N2GQfTpVHcgBzzxcbE7I4nxpJccXmGtQyesJ7Fb/eNuZi9fe+vB3E5evZnetHfP8l7cNs3B3DiORQSCMkrlEdV7L3YWsirru4yf5chfTf+G7wFwL2T+xFF11krFg64ogj8JOf/ARPP/104dxvf/tbLFy4UDt/enoa55xzDp544gl8//vfz0VvZKxcuRLDw8N4/PHHsXLlysL50dFRjI7625+F6q+hjEvHZKMuMmQ+HFkUJxuxyV2nikgO4Ceak85VzdOtleIjwmMrnKgpMIIIMoqbitNTVINx1VCiNb7h+nAokR1ZtEWGGMXZNzuMsaYpakNb2xTFKY73E9WhXoc3h1cd1Tvv128jm+MibtKPKYLHxX+jpaQdxLOwBc78+fMxf/5847i1a9diYmICP/rRj3DiiScCAO677z5MTEzgpJNOUs5Lxc3jjz+Ou+66Cy996UuN1/qXf/kXTE9PY/HixfQ3wsTGaEydKxsrEy+pyJGlpUypquJ1/IgcAF2hkz58tSkrgCZ0uCZkEy5pLZeIkMeGftwNNeuQniJ37K65IHJh/2wLI4b8tEnMZAXJ1OwwRptm4SGajW1ETuE+FKkqG3wLHZfokK90lOp43cSNr/SUSF0a/KUE+3Pv6KOPxplnnokNGzbg3nvvxb333osNGzbg7LPPzlVQLV++HLfeeisAYGZmBv/lv/wX3H///bjpppvQbrexZ88e7NmzB/v37wcA/OpXv8KVV16J+++/H7/+9a9x++23453vfCeOP/54nHzyyd7fh4+dxV2R/eUs+0tZtgGnKlUlYpuu6oy3SFkB/k3IXExpLZd0F7e/j4XvxjZ64zs9RbqmooKK1u2bfBmvuJaKUwzGIdNUVvMtTce6tI75mnapK0q6ibaOn3SU6ngdxE0W2ZYhtqZ43Qab9EX6tA/OTTfdhOOOOw7r1q3DunXr8OpXvxpf/epXc2Mee+wxTExMAACefPJJ/OM//iOefPJJ/Kf/9J+wePHi7iutvBoZGcH3vvc9nHHGGVi2bBk++MEPYt26dbjzzjvRCtDoTIRajkpp+Cf+q9q2oXOs6HVwFTm6v+pLFTk2G1VSvTkcfPh4bN6PD9+N6JPynKrSiRmbZ/Sg+WmA4pYNOlz2pRLRlQyLD0/x4SoTRK6VVSGEjihmfHh5bBr2dc4VK6Ky53Kf10TcyHYOT6M3MlEjpqc4/puUqg3GQMAqKgA49NBD8bWvfU07Jsm444844ojc5zKWLFmCH/zgB17uzxdJ071BkejFEVNVWXR+nNyaGd8Nt7KqcH+ydBXgVmGVxdQ3B/DjzQmFi4naMJabmhIpKz3lu4S8FBE02wCa+t85acWUirSSikLqw5EhS1Nlj1HTVGLqScSUqpKuyais6pzrfPM43pze3PBGZJ9eG9W5fhM3vrw3Ve8gniXuRcXAtLO47lhxM031HHGurCW+bJdx2ThflVWdOZIfFx8VVt1zjtGc7KtMfKbaPKSmdNGbMtJTZaaUyowEtYW/XjlheV3oP+R+VACtn4qpP476mCmNU69QXaioTZ3ETe46snSUxHej+/lURW/E9JRW2JS4g3iWKHAcsUtFmc5L2snPFZEDmP0rJINuCaLHVpClcwnjXVNTPqI3tukp+1YIdvNcMDYis0T34JClqWzFjukBa0pVUdZUHesc1zW9s09buZJe27b0Wyds0vO5z2eHc1/738+OGsWNOIcrbkSopmKZ78ZHagropaKqNBgDUeCQ0O0s3j3WTM91/qVusEn14+Tn0B5CqgdTbUSObedf6nzZej5ED0XYcL1DBHETCmr0xjYyY9ofzfdmtHVA58NxqVxRdTW2wcaPozrWO6eP5oQSOqKQoV7LxkSsOu/a40ZckypubCqmbMRNFlX0htv0L3QfnChwHCiIE81XUxXF0Y0NZTrOri2eK1XkAG7RHMp8ExzRE0LYpPMEZF8r1+gNZ+8pHRwxnR8j/9fuHhiDGb9EXU2Qur9wQ6epuFEc6RrULR+0KRtz2spF6NgIGc49mqI26Zjc5yWJm8KaDhVTuWME340pNZX+W4jeZNJT3ehNv5eJDyq9X85J7nPZGNtUVZZBEDnZB3My3KpHNMd0LW60h5uOoszL4NrQb1bjp+mOsRQu+TVYw2sL5S/SLNO6iE3ANJUYxQmVqqJWDeXPuQsdH2KGd09mYWPjt/ElbkKairNwfTcmcaOL3oRo8JcSBQ6RbJpKFDm5Y4ZUFdePI0P2+1L2+082LoTI8VJGDpiFSuhojg0uURvFPJutGDjeGxtzMfVnrncN9TkXqur0L/5CtzEaZ5GlqajCxrXXjQglVQXo+77Ypq065+XpJd/pLFsTse68q5k4Xbs7vmRxk8XVd5OiEjey6E3gZtZR4HCQiZzsxyqRQ4Xjx/FlOi7cg4XI6czzJHKAckzIrlDEmG6uBGl0Szqf1/NGFb1Rmc+56Cuq/ISi+9GfQ+mHw4GywzgQNlXFrSbqndNHTkLiOx3VPR5Q3IhwxE0WU8WUT9+NLr1bEDeZsaGiN0AUOM6IqSqXqir5+ukYmunYtbJKPFepyKlT2iq7pm2UiRG16R63aF5Jjd5Iz+e+x+4pK1so/zfYlJT35/pwTGkq392OAVqqSqzuyZ1jVBblz5UrdHyno7rnPIsb3ViuuHE1FWfxmpoSxE3I1FRKFDhMTKmq7jlPqaosFD9O7h4cRE5+HUeRY2M+7s53iOak82Uv7ZoWc9J70a0pQRe1kYobT8ZiTvTGJSXau7b8X05fKF+EKlPl+nCoaSrVeZcojgyVH8d3NKdzfiiY2DGt7RK1AfyIGxFfvW504iaLLrro23cj+/8WOjWVEgWOBbapKp9+HK7pOD+X1yOnM8dB5ADuIsclmqNb00bIyK7tOWpDETe+MUVvyOv0STqp7LbxXLhRHFPZOCVVxRU5gH00pzdmSPqiwJ3nGrXh9rhJ5+nuw0bc2FRMyUzFvnw3IkrfTUmpqZQocDyhSlXZmiJtmgDmjhErq4A+ETmAuwnZF+SycvW9slNSsnRfydGbKlNWQZnN/wWa/nIW/1K1MRrL/lI2palsozgiFHHBFTkhojkqVMLHJvpjayLunrcoA5fNS6/VneMobkKYirO4lIT3Fik/NZUSBY4lulSVj9JxGbam4yyq9eskckhCR3vek9CxKRdP789XSgogiRtXONEbqiXEl8G4H6H+BWxq+kfxXLimqlQiJ0Q0J/sqC5d0FOBP3IjvO6S4yVKV76Yh8d+UlZpKiQLHAVWqSjxWhh8nf12+6Vi1PlAUOblxnkSO92gOwBM53roc86M2gLu4qSJ6oxpbvDft1DmDrh9O53xYY7EOVWWV72iObFwo4eMatQHsG/iZDMUuWzCoxnFNxVlUvhsVZHEjSQOXFb0BosDxjilVRa0O8eXHyY/jlY9TeuQAfkROZ24J0RzbqIzq2kT/DttvA1hHbrjixtZ7I/8Z0403j+l3ZH8Rm9JUdYjiAHyRo1tLdl0qrqLH1UQMyEWKTXdi2bVctmAQP3YxFVN8N5ytGFJUvpsyU1MpUeA4QklVcX7payNBTD+OyXTcDyIHIAgdajTHJW1laUa2TkkxxI3LtgsUbNOeJgZpDypqw7+yojhcw3F3nkbk2KasfERoqNEeFxNxd4zk/dh0J5bdT5nihmMqzhKqW3EVRIHjgdCl47k1FCJH5sfJYltZlb2GeM7Ub8Vma4fOXLV/RYvP3jeOlVUmUcaJ2gB0ceMremMSLeaUFd9/008RHtFoLMPkwzGJnSzcKI6Iqgsv1ZOTYpOykt2Lr7QUZx2bqA1gXwZOFTcilOo5asVUllJ9N5JuxWVHb4AocLwh7jie4rt0XLa2jemYU1mVvYZ4TmU6lp3vzLXb2qF7nJq24kRcPJSKp/dFub8yxE0ITAEF3c+o1fVqJHjEX/xcTF2N83+Fc8vD7VJVsjnduZIIRYopZWWzlURIAzKlQkp1z2WIG2pnYpuKKZ++GxV1KQmXEQVOAGxSVTpCmI5l64tjXbd0kJ3vzbcXOQAhmiPDV98b8ARNdw7TbwPYixtf0RsXc3H+fvL/2lDmPlRiqTgHXcM/gBe5yWLT3dhF5AB2vpx0veyLCzfKo0ph2aSjAH89boDw4iaLTNxkcfHd1L0kXEYUOB4JlarKzWWMUT2odJVVhbUct3SQne/Nl4gcQxl57hxDXLhiI2iAnqjRbrlQkrjxhY/0lEsfsZARnVkbQaPph8NJU1GiODapqpAih7Ibebq2i+AB7EWM7n5k+OpxA9iJm8K1HSqmgHJ8N1V2K9YRBY5nQqeqdGtSTcf5Nczl46WKHIAlcoCi+DC9KNgKmvR+jaImpURx4xK9CZWeqkP6CYD8r1ED3OiO7803RaoQOUBP6FDFTnodV8Fjg+l6dRA3PiumdOImmO+mBqmplChwAmJKVZXtx8nCqawC6iFybDaelOFLBIn3xrpHRaUU4EfciIRousdNT7mO8THHBxQfDidN5SuKI1KmyEmxETvpNW0EjzjP9DLdu0jdxE0Wn6ZiZ2qWmkqJAicA3C7HNnD9OFTTcf4adJGTnxdG5HTmtpSvMrG6bipqNL1sfIkbuiDlRW9c0lN1jOhw9qOiPAxs0lSu6B6YIUQORegAebHjKnhsBAsHX92JAX2Jvqu48Wkqlp0blNRUShQ4gQjd5Vg3Rnad/DE703FxnNqQHFLkqNCJH1dRZC2mCKKme40A4qZ4Dbm4cYErSijP+8CagLWjOEXY0LdmUDyYCPNtHo6AviQZ4IscoCd0qGIHsI/u+EAUWybxRRU3hXniGIctGICwpuJBTk2llNsPfI6TtBI02g0kLaDRRu/fZkf1pp/PtoBm9rzwb3o+v7Y4poFmO29wzs5LWg00DpyfHQKaM8IxxdhkqIHGTJJZs3cd8VzSaqLRnj1wjQaaM/n7yZ7vHhtqojEj/AmQffCL5xwJEvlh7hOl605sauJnEjfkLTeY0Rtznxz9eZ/IjPxe1m030DCs3W430WrJfyan2y0Mt9rSczr2t4cw0prpfDw7hJHmjHTc1OwQRonn9s0OY6w5feDcMEYPfNw9nwxjrJE/Js5TkRUDo5I1ZIii4uDmFGmebK5vbBr4AXRxU5xn7nVTtqnYRJ26FeuIEZyAuHY5zhLCj0M1HYvHOQ9R20iO8qGfjYh43nDSCeY9pe+RK250HaN53xe6WHGB0sXbdn6VcPvhcNNU1L441KgAoO+RA+gjOdR0kE1kBzBHWEJGf7L3XIa4cSkH55qKs3B8N/3UrVhHjZ4Qg4kpVdU9Z0hV6bD143SOH/hBJvyl7kvkUM2xFBFQEDzUlw8CiJruWIO4Ka6t/n4U16ado3hv8j9Xdv6bUkUMITVlUyqexSR+XNJUAC8aoB/L2+qA632xFTuh0QmaLFWJmyymbRiycJv5+exWnFKn6A0QU1SVECJVpRoD9NJI+WPFNFeaquqsFy5d1blWPmWVfaCLaavOevmHRiGNxaWk6A9FzHTH6qqgHCqmbFJTOuqUniobbUpqtoVh4T8VN021f7aFkQNr6FJV2RSUmI7Spa7ElBMnXSWuk2JKYQF2aSzOmj6w8SqFEDeciqmymvmZfDd1S02lxAhOCXBSVSH648jO5Y/ZVcwAdENrZz29WTY7LvuSr91kRUTKhnNfuvcJ+KuY6sylpaa4PwdUdNekRDiDoumFowvrU30L04oHEzVyI3vwpbiYjlWRHGoTPZfIjsvLFWpFlurrEFrcUCumADvfjTM1Tk2l1O/JMKBQuxzbwPHjyOZ1xtlXVnEesIV1D6SstOkXg9jpXKd6scO9B4qw8VUx1Zlrl7bK3VPu5yB7XOavUq8zyFEewO0houqLI8JLR/FFTncso1tw2Y37uHAEje5968RNcSzt+2JbMWXruxnk1FRKTFHVANdUlW6tLKZUlW1lFZBPSYkVXNlz6QNaloYSH+Zi1VV2fgolnVUnTFVRKZSUlIvvJlT0xrajce76NRI/ukqqmXYTQ0K6ypSmyp7f325h5MDxbGpKhJqqEjGlrmTpKgCFlFV3/IGHvSl9la6dQklhhYIitijiTSsAPTfyczUVl+K7qXlqKiUKnBL510suxSuu+jSArBCplx9HFC7iMR8ipzNXLXRSsg95mdjJrpOiW69KbIWNaq5J3FB9N5319dE72Tyb6I0unUolROSHUg6eRebDkR2TCSAdOf+NTvAwSscpIgeA0ZeTJSsIbMRO1REeajRKJ2q6a5UkbmxNxbJzKnFjRCJu6k59/9QdUHx0OQ7hx7HZzkE8DpjTVTJfDiUFlU1luaazyoJ7L7KojSwlxRU3tqkpH9Gb2sBo7BcalRdHh5iyoJaOUz4H5Ckr0gOeudllVeKG4ilK37PpvavSXLaNGFMo4oZiKs7C8d3YdCuuc/QGiBGcWmKK4ugQIz2ydXPVTtJxxVRV4bgh6tO7n85/DjGak9KQNP/LoorI+EpnhYAjrnRG68IxyViuuKGmporXya6pvr4I3ehOO8a9li2z7SaallEal2oqXRQnm6oS4UZu0oesazSnO5cZ1QmNa9optxbTX8MRN7YVU5X5bmrYrVhH9X/mzkFCVlVlkZ1zNR2r+6Hk++DIogzpKzdPMja/Lj/CQ10r1IuC6l45URtXceMzepOfaz21r5E9UCh/OeuiOLoKK/HhaBO54URzyIKAGdVxRTQFU6M0yvUI1VVTs0PSry/H+O3TVFy276ZfiBGciuD4cURc/Dj5dfimY9l9pMg8OUAxSqOL6ohjRUz9cjr3ao7uVIVJgBWOEaI2snEmgVIQPxbRm/x62suR/TdlGow7/9eEn43ZBtAUoooSj46uH44KldlYhGo47ozVm44pkRuZUVkWzemM1RuRc2vUoMGfjyhNby35fxKqcPRpKs5i47uxpV9SUylBIzjPP/881q9fj/HxcYyPj2P9+vXYu3evds573/teNBqN3GvNmjW5MVNTU/jABz6A+fPn4+CDD8Zb3/pWPPnkkwHfSRhsuxxLxwTy43C2c0jPyXw5nCiEKarTu5Zf/04oTNdW3T81JUWJ3HBSU/SScX56ygZZD5w6RYlMO4iHjOLIsIncyKIPgGZXcUZEp0xsfDQmcaOL1lCjOL5Nxa6+m0FPTaUEFTjvete78NBDD+GOO+7AHXfcgYceegjr1683zjvzzDOxe/fu7uv222/Pnb/kkktw66234uabb8Y///M/43e/+x3OPvtstNv8je3qhm2qSga3P46L6VgldFRiJ3+f+vRVaMET+mW658Ixy5RUZz2z54aTmuJGb0zCw4fXpkpMfwGbzk8b/hpP0aamNIbjFNv0lErkmIROlWLHt6DprEkXMKrjsmNccUM1FZfhu6l7SbiMYCmqRx99FHfccQfuvfderF69GgBw3XXXYe3atXjsscewbNky5dzR0VEsWrRIem5iYgLXX389vvrVr+L0008HAHzta1/DkiVLcOedd+KMM87w/2YCErJ0PIvsnA/TMYCc8ThFTF1lxwFQGo1l6SvZHHGejDqXkKs7NNulpDpr8sUNNTVFuSebdeqCLA0lMxpnMaWpdGkoGdm+OIVzBsOxrHScmp6iHAPMO4vXKaLDrdbSeWVU5zkpK1GEcsUN11TsXBKe0oe+myzBIjjbt2/H+Ph4V9wAwJo1azA+Po5t27Zp5959991YsGABXvWqV2HDhg145plnuuceeOABTE9PY926dd1jhx12GFasWKFcd2pqCpOTk7lXnaCmqnRQSsd1KSqu6ViM5lDSIj6iOrJ5viM8oaFGbYByxY3rlgyukRzO+bIxPRhMaSjVeU4Up/C5JJJjMh67Hqtzp2LbCI1OqHDTULKIjS9xk4Xju5ExSN2KdQT7Lb9nzx4sWLCgcHzBggXYs2ePct5ZZ52Fm266Cd///vfxqU99Cj/+8Y/xxje+EVNTU911R0ZG8JKXvCQ3b+HChcp1N2/e3PUBjY+PY8mSJQ7vrBy4qSr5GuoxMrFD2XncVuj49urIcBE8vuFUWamEDdVvE0LcFL9f+XuTHTfhKlq8iZ7APXE4aSoRMSXBFTmdMX5FDsebUyY2PhqdoBHHquabxqaiRiZsXMSNre9mLqamUti/2S+//PKCCVh83X///QCARkPyl2aSSI+nnHvuufjDP/xDrFixAm95y1vw7W9/G7/4xS9w2223ae9Lt+6mTZswMTHRfe3atYvxjsshROl4FoofR3XMVF5METrpOj6iOlQ4gqeKUnHfUZvOXNl78yduuHDSU7VJZWk23QR4lSgUs7H4V3jVIocbzZG9QhBK0IjjZccpY2WiBpALG5OhGDCLGx++m+LE/i0Jl8H24Fx00UU477zztGOOOOII/OQnP8HTTz9dOPfb3/4WCxcuJF9v8eLFWLp0KR5//HEAwKJFi7B//348//zzuSjOM888g5NOOkm6xujoKEZHR8nXrAqdH8dEaD9O+n8tW0IO5H01Yim5qgGguFZ2vLimrHxcJgBknh0RrocnBMbNR0sWN1xU0RtOeipL3VJRXGzKxQF64z8VlCaAshJygOa3kZWOq8bKKDvCQxEx1Hku3prcuUIK0SRUFULH0XejQ9etOKVfozeAhcCZP38+5s+fbxy3du1aTExM4Ec/+hFOPPFEAMB9992HiYkJpRCR8dxzz2HXrl1YvHgxAGDVqlUYHh7G1q1bcc455wAAdu/ejZ/97Gf43//7f3PfTt9gMhxT5nD746TjALrQSf+/i0bk7JjedXof25qSs/ecxUbwqNb2gX5vKL3PqHDMo7gJGb1RwRJAFbciNRmNs2S7GnOFj2hIFg3Hst44NiIHUIsXyrH0eApF7ITARtD4NBKHFDayyA1A893ImIupqZRgvz6OPvponHnmmdiwYQPuvfde3HvvvdiwYQPOPvvsXAXV8uXLceuttwIAfve73+Gyyy7D9u3b8etf/xp333033vKWt2D+/Pn4oz/6IwDA+Pg4LrzwQnz4wx/G9773PezYsQPvfve7cdxxx3WrqvoZn6kqGSY/TrZ8XPxrXUxbcfw5sjHifbmkr4rrNQovClwfD3Ut3f3p5haOVyhuuNEbSom5K4VGfQKmEDslOtq9lqV3R5WmEv8y56aqZMco6SqAn7IyGXFDw005ceZwysFVaSiAlooSvTai38YkbrLIfDdzsVuxjqA/mTfddBM++MEPdiue3vrWt+Jv//Zvc2Mee+wxTExMAABarRZ++tOf4itf+Qr27t2LxYsX49RTT8WWLVtwyCGHdOf8zd/8DYaGhnDOOefgP/7jP3DaaafhxhtvRKvV5/HuA4QuHRfHZK8jfiyWbbtGdLJjsuNSfEZ1RHxFeVzgRmu65zTC0DS2LpEbHWWIIZ9kIzTZj1VRnGyEJjtGTFXVIZIDyCMzusiN76gOVzT5Gu+ahuqMt4/YdI8pxI2T74ZJv0dvAKCRJEl9+tiXxOTkJMbHxzExMYF58+ZVfTtSUoED9MREo6u6heOz+c+zv/8KYzVjZJ+L50RRUDwvrpUfr/rdp9qsU7ambo5riokiergYO/5aCJvOuubxNuKmM0a8lp/oDXt8U3FciG4Wz2eOp2tkoz25eb2Pu71wMts1ZFNU2V452RRU9uMhxfGscMmOEb04st45Yn8cUeTItnaQbcwpipwUnSixPReSMjw3dRQ2AN13M6ipKc7zO262WVN8pKqyyPrjZFNauoeQqkRYfp6fusqO01VfcUvNbdJMNmkt0zoyTPfHTeelc0zQxojXC1tWzaWUCE+mymRW8tCg0lY8pDipKhmmhylAT1cB+lSTTa8Yn4ipJptojWuJN9BLQck8Ni6pKKDzM5CtlOKIGxlzPTWVEgVOjQnlx9H95Szz4xTnSHq0eBI6srFZqEInd96j4DE97KnNCaXnNCKvs7Za2EiFIaGRHzc1xY3G+KKOaau2xPsA0PaeEuH6cQA3keMidEL7cVzEjGk+t8QbKHprenP8ChugGLXJpqRUP2PWJeEC/baRJoXw7rBIZcj8OEDx46KPJu/Hkc3prJ/354jj03vIr2326PTWMnt1ZD4d2fjcuo7VU9yIhrkHDy8NZZpHSUuZ1u6NkaemqPhKT3mh3cinqUqC4sWRYfLjABL/jcyjc+DhLPPlAPK0lclTY+vV0Y21gWM4FuGmoHrzKMJSL1hFQauK2ABq8SwT2LoI46BtpEkhRnBqjksUB5BHcnQPGtu0VciIjmy8uC43qlNY3zG1pVtTed4iWmOcR3xecH03urF1jK4YcehmnH2IhIziyNDtOt4do/jBUUci1NELwE9UR/XiYDPfV7SmN1cvbiiVUWLERpeOylZKmcRNlrmemkqJAqcP8ClyZCkomRjJXo+SturM8yd0TOkr107JFGwED2V8KGGj8zaJ1yiOU94u6bxs7X4RQdlS8dxfwAofjiu67sYUPw61fNxW6NikryjnudiKIdtOwyphk34tXUu+TVEbajoqm5LKRm5cfTeDFr0BYoqqL5E158udz5SOA8U0lK48XDZeN05MSQF+UleAPn2lmpNdO7t+dnyKLo0lvZ5DVMcksGxSUYBeCFKvIxMfIaM3of06VUIpGRfhpqpkpA9bWQm57DigTl115pnTV6r0k03JuC/vjohtGqozVy4c82uYBanvdJT4ubQcnOi7SRlEcQNEgdM3ZHvjpMh64wD5/jidcfIeON2xgvgQxwPFOeK4MoQO4MerI5unmu+Ki7DRzTel82yu1RtXjMLJPtat7yp8+gmb7Rp0okW2jYPMjwMUy8dlHpz0OKAWOjKR05ln79MRx/jEtK4uBaWfp4h6eRY24hxdelOVjspGG1XiZq6mplJiiqqPMKWqZOmqbMpKVSIurimOT+fIzpnSVp258tRVfgyE8+rKIJ9eHdV8todHmGeab7oXG58NJ3XXGc/z3cjm+xyXm1PD30w25eK6v8JV4wCaHwdQV1dRH9S9dUzeE5pPJ6SgMV2DUuKtQvU181EZBbino9LPU7JRm1xKKpOWmsupqZQa/hqJ6NCJnPyxoi8nex4we3Nk43UeC9Uavfk8f05njN5z4suro0IlXLhCKCuwXISNj5RUZ7xsbHENm+iNjr6L7DBD/QB9t3FKvxtxPMWT0z1OfGjn13ITOoDfvjWU+T69NeK53lr2wia7h5QuaqMzEWu9NoAyalMQNwKDLG6AmKLqe3rpqY7IyaascucP/F8weXPS47r0Ux3SVllcvToGewMbG1+Jjc/GOM+juPF1Ln9N2jibtV1I2o1cx2IKVI8Nx4uj2nFclt5SpawA+7RVZz196ipF1SE5xXdkx7e3RnXOJhUF+ElHZT/npKMAYY81icipe7diX8StGmq6VQMF0ZMjbumQP5YZN1ucA6i3b9Bt5VDcmoE2rzdfst2CYfuHzhj9j63J22icTxA9tgZZTurLp9dGJQ4o4kb3eTHqxp9XGGfYoqH3OWOrBkC5XYM4JydwFNs2iONE4ULZvgEobs0gMxzLhI7KwyMTOd1zmh9s7TmF0DFhEj5cfHtrVOdthQ1A22JBHEcxEQMMrw2Qj9oMUFoqbtUwR8imqwD7lJXKmyN6esQ1xTniOVm6y0dpeWeMweNi6dURr6l7UbBJZ5nu31RmLp+juA7hfkxix8c5G0w7iYfAtlxc9zATH56yHjqyh6kuZaVLW6nQnsuke0xprPyaQ4UXB9NcW2+N6rxtKgrwk47Kfi6mo8heGyAftRkgccMlRnD6OIKToorkdD4uL5rDmac6ZhvR6YwLG9XRYdNnJ4X6O9++47Fqjnw9agRGdl2b6E1hXlNzThGl0Z1TRnCEz5URHIC0+SZAj+LIxqo248yNUURnyozmmLCN9lDxHa3prOknYiPOLSNqA0iMxMLHg5SS4jy/o8AZAIGTwklZ5c4Lv0tNQocjclTXVH3eW6OeQsdFyAB0McO5pq+oDSctJbuubjxLGCnSU8U1qxc4srGqXcaBakQOYC90bMbJr+8uegZF2MjOc7w22XFzISUlElNUcxRdykrsfJw731Q/VGTpJ1PqyTVt1VnDLnXVGWfYtJJRgWVbNi5ex5Qy011fub4mVeYqbrhw0li+rx0CXRk4J01letDpUI1VPXBVKStAv8WDKY0jjtNVHynnSlJclDSXSyWU7jwlFQWoDcSqsm/AnI7SVUil6KI2MSVFJ0ZwBiiCk8JNWWU/VqWsAFo0RzzGieaojnXWsY/odMa6RXVMuBSJsIWT4bniQ9zUIXpjXlduMC6cE3WCjdEYqCSKo5rTHes5mpMbZxmxcYn0ULGJ1gByoWdbGSXO5aSjssdi1IZHTFEZGHSBk2KbsgLCenNMc1XHOuu4CZ3OeHexUydB01tXt0Y14sY0X1c9JZ6nVlAVzgUQOIC9FweoXuQAdKHTHe+SovIgemxFTfe8p5Jvca5tOgpw8NoAyvJvYHDFDRBTVJEDUFNWsmopXcpKVWnlK22lOtZZR17STEld9cbTKrB0LyohmwJ21ld/rXrr1VPc1B1qt2LZWN1DDTA/BGUPX58pK6CXptFVXeXGu6SoPMy1Pu+hSZ9qrks6SlohBdCMxHNU3HCJjf4GHHEPq6SVbcSXdP/TpMfTB5KuOSCA7p5WxTXzERXTvOw5ca5sTGeNYrNA1bVSTHtR+dqDytaEzHnwUz0r1A0zueuWRSn3024UjccqZhu5KM5su1lIVflE1tBPtTGnqilguk6KLqojihxKhEcUFpxIDUfkcOf6TkWJ8yuP2mQ+jsJGTUxRDXCKSoTizeGmrIDy0laq47K0lXqsfN2y4f5u9yFqTGuVHb3hpKfkn3tIUQmfi5VZnDSVbHyIVJVsXm4OMfVkSmFl4aazuvM8/4cLKWyAitJRQExJMYgeHANzVeAA/gzI4hiX/jequar5quMUf47qumUQStR01rYXNrJzlNRSlQJHVyIunucIHNnaqq7GAF/gyI6FEDnduQHEDmAveEKgSq/5FDYAb4sF8ZjvqA0wN8UNwHt+xxTVHEOWsgLS9FQxZZX9OJuyEsekvwtke1qlH2evmU856dNW4nzZGp11iqkr1fzsPdcJ36KGsqZNiTdX3Ljisl5jViJybDGkqcR9rHR7T6kQ58hSVUDvIasTOukD3SR0qGmslKyoqErsVCFsZHNKidpkPp6rwsaGKHDmIKn5WObNETft7HwsCJ5mXuSkYwC9Nyc7TuWX4QgdlXjhCp2qqULUqMbIjd38tblrmKI3/YwoWMTPVb6aLCqRk84HaEIHCCt2qqROwgagRW2y42LUxj+ximoOo6qy6nxs3s+KW2kljpOd11VbycarjnXWMjcLlJ0r+0VB9l5078FmDEXcqNYzrVMrGNVRUoQHlPiXOaf6KoWS8jBVRaVVPKZmgmnFkOrhL7um7rpV49KkL7tGFlNPG1PUhlohFcVNWKIHZ455cGSIvhzAvmeOeI7jr+GYkLnHOuv11486NVoD2EdsdOdsfDeyY6R1HAzGpPM+fTgA24sDmA3HgDwKo0pxUaIrFJ8OQPfqVIXsvapEl21lFFB+1AaIRmIu0WRsIAocOS4GZMCu0ory+SALHY6IEaFGSrgeHMCfuJGtZRI3lGvVTeAA1YgcwK/QAeovdlSUKWzEYyG8NkAUNzJio7+IFdyUVeFjIWUlpp5kcyifm9JWumO61JXuRR3n+rKBmtqipqvyX5uw4oZC7VNcQOEvchmUVJXswSl7KMvGpVBSSNT0FZBPYYmvuqG6N10qykfUhlwh5WAkjuLGnRjBiRGcArqUVefj/ovmUM7VHV8RG9U4irBRHbeOAllEbzrHyo3gAHZRHNk8Suk4wI/kpFBLvjlRnTJJI0i2gorisQECpqOAGLUJSCwTjzihq7LqfKwvJwdgVWml+lycC6irrVTHxHM6QougUBEKFwHkIm6o+HrfMvHhm04VoeE6Qsk4QOtuLCsdlx2TVUdRys7Th7lJ6GQf6HUSO1xho4tK+RA2smPevDbCx1Hc+CWmqCJKfKSsbCutKGkr8byquopTrSSbp6p8Clk1xcE1ZeUqbnylpnTXDQ4hnWRTHaWaR3mIpsgewLqUVQqn+imbwuK8QmN7D6r37iMdZVMhFVNS1RBTVDFFZcR3yko8p0tZyY7ZpK2o1DGF5frQ180vS9xI5wZKT0nHyJ6DhjSVbB2Zcdg2VQXQ01WAOspCbSTI7VYckqHWrHeBpBNzMWozOMQUVcQrvlJWAK8Lsuxass9VaasUjmgpM4UVOlphWr9OkRvdteuE2KkYADlVJZtLTVcB6oaA6YOYmrpSUaYA4oob2z48JmEjG+PDawNEcVMHosCJkOFs89A73vsYcPPm5NaRCKHs/Cy+RUsdH8TcewohblRQozeVw9lZ3BKOyAGKokXX9ZgqdFRQRYRvIeSziaAudcc1EQPhozZAFDchiQInwkIUOUBPjGS3ecgeL3zczP8Hd43mZMeIvyupv4upD+wqU1g+hJXqWeLDUMwRTbaUYTDOIjMbu0RxVKiiNirzsc4ULHtQ24oeGRRBkoqgssSLDq/pKCBGbfqIKHAibFxSVgCMG3cC/A04xfnZdURc/gAtI4UVIkKke85wxY1raorivdFd3wavG24yoKaqAL8iR7aGCp/iJ4UrbGzFiwpVCoyTjgIsozZAFDc1Ieh/+eeffx7r16/H+Pg4xsfHsX79euzdu1c7p9FoSF9//dd/3R3zhje8oXD+vPPOC/lWIhJkVVa9CqOk+5evrEqq+7GhOSBnXypqxVK6rurlim11la8qK8578iFuuGv3G4WHF4oPQgDK5n+FCIBqPtQPelVDQB/VTGmlkOzlA936Pq5Dqawy7R8FFKM21imp7HYLsUqqUoJWUZ111ll48sknce211wIA3v/+9+OII47AP/3TPynn7NmzJ/f5t7/9bVx44YX45S9/iVe84hUAOgLnVa96Fa688sruuIMOOgjj4+Ok+4pVVH7xUWUF0JsDys6rjsnwmWaqujDFdzm2TpToBCN1PDV6o5wvrXQijqNUUimOkRr/pRCrqnRrqKIqnGhLyN426X34jryI2Io33X2xojYArWkfEKM2JVGLKqpHH30Ud9xxB+69916sXr0aAHDddddh7dq1eOyxx7Bs2TLpvEWLFuU+/9a3voVTTz21K25SXvSiFxXGRqqBm7IC7AzIgNqEnJ2ThdLsz0XwcASGqxjyFV3inuOWmZvmUOiH6I8q1SRD5cfRpauAoqDhGIll4sCX6HERNr7Lw6n3wjIRA85GYiCKm6oJJr+3b9+O8fHxrrgBgDVr1mB8fBzbtm0jrfH000/jtttuw4UXXlg4d9NNN2H+/Pk49thjcdlll+GFF15QrjM1NYXJycncK+IfasoqPSf9WNMcECimrEypHUoKKESaSIYpNRYydUb5GqnO6d4LZ04tK6eIyNJUShipKgC5pnAiupSVjcgI1ayvrOaA1PSWaZz4NTdFbWyqpKK4qZ5gEZw9e/ZgwYIFheMLFiwopKFUfPnLX8YhhxyCd7zjHbnj559/Po488kgsWrQIP/vZz7Bp0yY8/PDD2Lp1q3SdzZs344orruC/iQgbXZVV52OzARngRXOy1xGxjeCYRE4dGwLKsInYmM5ZeXoUzzWep6ekCipGubgyiiOpqgJ6D1If0Zz0nKtJWCU6QjTj4+ASmZEhE5FeojbC51HY1Ae2wLn88suNYuHHP/4xgI5hWCRJEulxGTfccAPOP/98jI2N5Y5v2LCh+/GKFStw1FFH4YQTTsCDDz6IlStXFtbZtGkTLr20F12YnJzEkiVLSPcQ4UNJWQFpCS4OfCwZR6i0SlGlf2zFjEnAuEZ5Qggk6j2ZxlUtbuqanlLtT8UVOYA+ZQXIvTmmtJXsnAuhxY1NBMpFzIiEKv8GoripC2yBc9FFFxkrlo444gj85Cc/wdNPP10499vf/hYLFy40Xueee+7BY489hi1bthjHrly5EsPDw3j88celAmd0dBSjo6PGdSJ+0TUG7HxuH83Jngfo/W9sozyqcbZU9RAvM2oDhE9LOX8dVdEaxfEyRI52PZgjOjJClIKHNhj7FDOAOkXos/wbiOKmTrAFzvz58zF//nzjuLVr12JiYgI/+tGPcOKJJwIA7rvvPkxMTOCkk04yzr/++uuxatUqvOY1rzGO/Zd/+RdMT09j8eLF5jcQKRVuygqgRXOy47NzUijRHdk6qvU44+qIrbABwogbfnl6/bfMsxU5gDplBagrrTjpKVXzv9AihYpvMZOiFDWAVtgAMSU1CAQvE3/qqafwxS9+EUCnTHzp0qW5MvHly5dj8+bN+KM/+qPuscnJSSxevBif+tSnsHHjxtyav/rVr3DTTTfhzW9+M+bPn49HHnkEH/7wh3HQQQfhxz/+MVot8590sUy8GkShU9xEk1ZO3j2u+d1uEh42FU1VlKG74pKOAsoVN7pzKoHDHk8tFTec0wkubWWVQugA6lJy45oIE6EJRSgxA/AEje5aMSVVXzjP76Dy/aabbsJxxx2HdevWYd26dXj1q1+Nr371q7kxjz32GCYmJnLHbr75ZiRJgv/6X/9rYc2RkRF873vfwxlnnIFly5bhgx/8INatW4c777yTJG4i1aGrsup8rq6yUvVUyb5ka6vm2lQpUautbJr7+XqJ1ze9FxW2DQIB/+ImOBYPUl1VlfbBrHnI6h7OukorwL6qKjTUqqf0/WVfJtJmfNlXfkAj/9JcL6XRbvS+t9mmfenn6bgobvqCoBGcuhIjONXCaQwonqMcB9yiOyLcaE+dIjgyXKI2lPllRW9s5ijvrcwoDmAdySGvj3qloLJ4j8zkBtoJT6rXBogpqaqpRaO/SESFqsoKSBsAFjftTJFttCkeB4oPMpV3RzZXhLufVV29OpQISd3ETZ1RGY4BvUkYgLUvh7w+wpuAqXj1zRQGW0bSoInCxajNwFCP/wGROYmYsgKKKavCTs6K9IspdaRKZenW1MFNcVHTW76hXI/zHrTnLcWNLV7X1D0MOX/5ZzA+2DUPZ8D8oKemcsqEm2oyppmkk+RpJ/H6Imn6KZeGSknTUVHcDBQxghOpFFPPnM7nPZGT/cWkjeBoojQ+oztZfER6yoTqO6LgUg6uj+zUP4MeKpID5EWOrqS8ey8lfr044ooVlSlM9pR2EpGdlwmjmJLqW6LAidQCVc8cwF3smM6HEjwAX/SEhrrlg09hU7WQy9KYtRRjjO7GIiSRk0IQO6bUVdU4iRkgTNophShqgBi1GQSiwInUBlnPHCCs2JGNyT4ARbOyD3+NSmSEEj6+RQ3gT9jUSfy4iBhdFAfoPZiNEZb04e4Y1SkLZzHTXajEKI3muPj/PQqb/iYKnEityPpyyhA7pjG66I5svulaOnxGezibc/oWNtQ1zT16apaeMgignineo9ABaiN2yhAzQKAojea47P90FDaDQRQ4kdpStdiRjdNFd3TrmK6rwnUXcRXcyIlPYUMZZxI3wSI/pigOIcpjiuYADKEDkKI6gD+xU5aQyeIUpQHYogaI0Zq5QBQ4kb5AZkbOki0zzx+3FzumcZTojm693NySfDmhhA1n7VqlpWwgihyAINRshA7AEjvBYQiZFOcoDeBF1ABR2AwyUeBE+grbqE7nnD+xI13fQvCo1qbcj+va2jkVCpvQqSmj0ZjixSH6dSjRHIApdAByVMc7FmIG8CRogChqIiyiwIn0LdSoDuBf7IhjpdcgprM416Dcl2oe6XrMP/yrEDelRIA8ixyA+N5shQ7gV+xYCpkszmmnlChqIpZEgRPpe0xRHSC82DFewyG6o7uOL0IJG+7YWkEVOYDXaA5gIXQAO7HjQcikeIvSAFaiBojCJpInCpzIQMERO/IScv9iRzZHJihcRA+HUE35XMeXWTVl3Q9HRYBoDmApdACvwkWFV0EDRFET8U4UOJGBxSWF1TnvR+xQ54QQPT4e4tbprgDipvRoEKc3DmMsJ5oDyMVEmV2LVfcgEkVNpE5EgRMZeFxTWJ3zZrGjmqu7lmmOSqBI+/FUKGZc1qhdvxuRgCInC/frEEr0cLohswUN4FXUAFHYRNREgROZU4QUO5S5putR59VFzIRYqyy8p6lSGL6c3P1IHvAhRY/Ntg5WggaIoiZSCVHgROYsphQWoPfrdM7TxI5uDdU1OXM4a/rCdU32w7tKEWWzjUP258FhCwgRH6LH9R6M6OZQUl0xBRXxQBQ4kTmPj6hOZ4xa7Ihr6NZxnSOb5ws/Kayap6RUWEZmcnNt52fwIXq46xux3T4he90YrYl4JgqcSCQDJ6oD2Isd6jq6OWXh65ouD+FQ79sqTeUidLLzXdYQcPXzRFETGUSiwIlEJFCiOkAYsaNbqwx8iwnX6EJoUWftxXEVOtk1XNcR0AmWpJWEETTEMbrKwChsIj6JAicSMVC22KGu5Ytw6SwPFT0lRaycDMc+hE52nZRAqTwvDfe4YxCjNZHyiQInEmFASWEBZnNyZwxf7KjWrFMVky8/SNnvybmqypfQEdfLEtq/5LonlEAUNZEqiQInErHAZ1SnM44mdsQ164RPo2tV79FL6bhvoSNb2wbZ/fiO5iCmoCL1IQqcSMSRKsVOSPq22qkuBPLXWBPKd4MoaiL1JAqcSMQj3BQWUK7Y6QfRUnWEKkgDQM73rurvURQ1kQEhCpxIJADUqA5gJ3YGiaoFjYxgXY4pcIWsj58LD6IGiMImUi+iwIlEAhNC7PQ7dRQ1IuLDvDLBY6KENGaM1kT6kShwIpESoaawgMESO/0gaExkH/K1FTseiaIm0u9EgROJVAAnqgP4FQhliaVBEDUq+ia6wySmoCKDRBQ4kUjFcKI6Phhk4VEVVUV3TILEB1HURPqVKHAikZrAjepE6kkZoqMMorCJ9DtR4EQiNSSKnUgVRFETGSSiwIlEak5W7IhE8RPhEkVMZK4QBU4k0sfoxA8QBdBcI4qXSKRHFDiRyABjEkBAFEH9RBQwkQidKHAikTlOjALVgyheIhG/RIETiUS0xCiQH6KAiUTKJQqcSCTizFyPAkXxEonUjyhwIpFIcPo9ChQFTCTSf8xJgZMknd13JycnK76TSCSS8tCfvk97/tXX/C15raRJ32H7pxs/YBwTf1dEIvUg/b+YPsd1NBLKqAHjySefxJIlS6q+jUgkEolEIhbs2rULhx9+uHbMnBQ4s7OzeOqpp3DIIYeg0WhUfTulMTk5iSVLlmDXrl2YN29e1bdTGvF9x/c9F5ir7xuYu+99Lr7vJEnwwgsv4LDDDkOzqd/4bU6mqJrNplH5DTLz5s2bM/8ZssT3PbeI73vuMVff+1x73+Pj46RxJe57G4lEIpFIJFIOUeBEIpFIJBIZOKLAmUOMjo7iL//yLzE6Olr1rZRKfN/xfc8F5ur7Bubue5+r75vKnDQZRyKRSCQSGWxiBCcSiUQikcjAEQVOJBKJRCKRgSMKnEgkEolEIgNHFDiRSCQSiUQGjihwBojnn38e69evx/j4OMbHx7F+/Xrs3btXO6fRaEhff/3Xf90d84Y3vKFw/rzzzgv8bujYvO/3vve9hfe0Zs2a3JipqSl84AMfwPz583HwwQfjrW99K5588smA74QH931PT0/jz//8z3Hcccfh4IMPxmGHHYb3vOc9eOqpp3Lj6vj9vuaaa3DkkUdibGwMq1atwj333KMd/4Mf/ACrVq3C2NgYXvGKV+ALX/hCYcwtt9yCY445BqOjozjmmGNw6623hrp9azjv+5vf/Cbe9KY34WUvexnmzZuHtWvX4jvf+U5uzI033ij9/75v377Qb4UF533ffffd0vf085//PDdu0L7fst9hjUYDxx57bHdMv3y/g5FEBoYzzzwzWbFiRbJt27Zk27ZtyYoVK5Kzzz5bO2f37t251w033JA0Go3kV7/6VXfM61//+mTDhg25cXv37g39dsjYvO8LLrggOfPMM3Pv6bnnnsuN2bhxY/IHf/AHydatW5MHH3wwOfXUU5PXvOY1yczMTMi3Q4b7vvfu3ZucfvrpyZYtW5Kf//znyfbt25PVq1cnq1atyo2r2/f75ptvToaHh5PrrrsueeSRR5KLL744Ofjgg5N/+7d/k47/13/91+RFL3pRcvHFFyePPPJIct111yXDw8PJP/zDP3THbNu2LWm1WsnHP/7x5NFHH00+/vGPJ0NDQ8m9995b1tsywn3fF198cfKJT3wi+dGPfpT84he/SDZt2pQMDw8nDz74YHfMl770pWTevHmF//d1gvu+77rrrgRA8thjj+XeU/b/6SB+v/fu3Zt7v7t27UoOPfTQ5C//8i+7Y/rh+x2SKHAGhEceeSQBkPsPu3379gRA8vOf/5y8ztve9rbkjW98Y+7Y61//+uTiiy/2datesX3fF1xwQfK2t71NeX7v3r3J8PBwcvPNN3eP/eY3v0mazWZyxx13eLl3F3x9v3/0ox8lAHK/ROv2/T7xxBOTjRs35o4tX748+chHPiId/z/+x/9Ili9fnjv23/7bf0vWrFnT/fycc85JzjzzzNyYM844IznvvPM83bU73Pct45hjjkmuuOKK7udf+tKXkvHxcV+3GATu+04FzvPPP69ccy58v2+99dak0Wgkv/71r7vH+uH7HZKYohoQtm/fjvHxcaxevbp7bM2aNRgfH8e2bdtIazz99NO47bbbcOGFFxbO3XTTTZg/fz6OPfZYXHbZZXjhhRe83bsLLu/77rvvxoIFC/CqV70KGzZswDPPPNM998ADD2B6ehrr1q3rHjvssMOwYsUK8tczJD6+3wAwMTGBRqOBF7/4xbnjdfl+79+/Hw888EDu+wAA69atU77P7du3F8afccYZuP/++zE9Pa0dU4fvLWD3vkVmZ2fxwgsv4NBDD80d/93vfoelS5fi8MMPx9lnn40dO3Z4u29XXN738ccfj8WLF+O0007DXXfdlTs3F77f119/PU4//XQsXbo0d7zO3+/QzMnNNgeRPXv2YMGCBYXjCxYswJ49e0hrfPnLX8YhhxyCd7zjHbnj559/Po488kgsWrQIP/vZz7Bp0yY8/PDD2Lp1q5d7d8H2fZ911ll45zvfiaVLl+KJJ57Axz72MbzxjW/EAw88gNHRUezZswcjIyN4yUtekpu3cOFC8tczJD6+3/v27cNHPvIRvOtd78pt1Fen7/ezzz6LdruNhQsX5o7rvg979uyRjp+ZmcGzzz6LxYsXK8fU4XsL2L1vkU996lP4/e9/j3POOad7bPny5bjxxhtx3HHHYXJyEp/5zGdw8skn4+GHH8ZRRx3l9T3YYPO+Fy9ejGuvvRarVq3C1NQUvvrVr+K0007D3Xffjde97nUA1D8Tg/L93r17N7797W/j61//eu543b/foYkCp+ZcfvnluOKKK7RjfvzjHwPoGIZFkiSRHpdxww034Pzzz8fY2Fju+IYNG7ofr1ixAkcddRROOOEEPPjgg1i5ciVpbS6h3/e5557b/XjFihU44YQTsHTpUtx2220FgcdZ15Wyvt/T09M477zzMDs7i2uuuSZ3rorvtwnxPZnep2y8eJy7ZhXY3uM3vvENXH755fjWt76VE8Jr1qzJmelPPvlkrFy5EldffTU++9nP+rtxRzjve9myZVi2bFn387Vr12LXrl345Cc/2RU43DWrwvYeb7zxRrz4xS/G29/+9tzxfvl+hyIKnJpz0UUXGStYjjjiCPzkJz/B008/XTj329/+tvBXgYx77rkHjz32GLZs2WIcu3LlSgwPD+Pxxx8P9sAr632nLF68GEuXLsXjjz8OAFi0aBH279+P559/PhfFeeaZZ3DSSSeR1+VSxvuenp7GOeecgyeeeALf//73c9EbGWV8v1XMnz8frVar8FfsM888o3yfixYtko4fGhrCS1/6Uu0Yzs9MSGzed8qWLVtw4YUX4u///u9x+umna8c2m0289rWv7f7cV43L+86yZs0afO1rX+t+Psjf7yRJcMMNN2D9+vUYGRnRjq3b9zs41Vh/Ir5JTaf33Xdf99i9995LNp1ecMEFhWoaFT/96U8TAMkPfvAD6/v1hev7Tnn22WeT0dHR5Mtf/nKSJD2T8ZYtW7pjnnrqqdqZjLnve//+/cnb3/725Nhjj02eeeYZ0rWq/n6feOKJyX//7/89d+zoo4/WmoyPPvro3LGNGzcWTMZnnXVWbsyZZ55ZO9Mp530nSZJ8/etfT8bGxpJbb72VdI3Z2dnkhBNOSP7kT/7E5Va9YvO+Rf74j/84OfXUU7ufD+r3O0l6Juuf/vSnxmvU8fsdkihwBogzzzwzefWrX51s37492b59e3LccccVyoaXLVuWfPOb38wdm5iYSF70ohcln//85wtr/vKXv0yuuOKK5Mc//nHyxBNPJLfddluyfPny5Pjjj69VuTTnfb/wwgvJhz/84WTbtm3JE088kdx1113J2rVrkz/4gz9IJicnu3M2btyYHH744cmdd96ZPPjgg8kb3/jG2pWJc9739PR08ta3vjU5/PDDk4ceeihXNjo1NZUkST2/32n57PXXX5888sgjySWXXJIcfPDB3WqRj3zkI8n69eu749My8Q996EPJI488klx//fWFMvH/9//+X9JqtZK/+qu/Sh599NHkr/7qr2pbNkx931//+teToaGh5HOf+5yyxP/yyy9P7rjjjuRXv/pVsmPHjuRP/uRPkqGhoZxQrhru+/6bv/mb5NZbb01+8YtfJD/72c+Sj3zkIwmA5JZbbumOGcTvd8q73/3uZPXq1dI1++H7HZIocAaI5557Ljn//POTQw45JDnkkEOS888/v1A6CSD50pe+lDv2xS9+MTnooIOkvU527tyZvO51r0sOPfTQZGRkJHnlK1+ZfPCDHyz0jKkS7vv+93//92TdunXJy172smR4eDh5+ctfnlxwwQXJzp07c3P+4z/+I7nooouSQw89NDnooIOSs88+uzCmSrjv+4knnkgASF933XVXkiT1/X5/7nOfS5YuXZqMjIwkK1euzEWTLrjgguT1r399bvzdd9+dHH/88cnIyEhyxBFHSMX73//93yfLli1LhoeHk+XLl+ceiHWB875f//rXS7+3F1xwQXfMJZdckrz85S9PRkZGkpe97GXJunXrkm3btpX4jmhw3vcnPvGJ5JWvfGUyNjaWvOQlL0n+83/+z8ltt91WWHPQvt9J0ok0H3TQQcm1114rXa9fvt+haCTJAfddJBKJRCKRyIAQ++BEIpFIJBIZOKLAiUQikUgkMnBEgROJRCKRSGTgiAInEolEIpHIwBEFTiQSiUQikYEjCpxIJBKJRCIDRxQ4kUgkEolEBo4ocCKRSCQSiQwcUeBEIpFIJBIZOKLAiUQikUgkMnBEgROJRCKRSGTgiAInEolEIpHIwPH/A9qzxxYLuGB7AAAAAElFTkSuQmCC", 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", "text/plain": [ "
" ] @@ -1425,14 +1479,16 @@ "execution_count": 28, "id": "f896255d", "metadata": { - "collapsed": false, "editable": true, "execution": { - "iopub.execute_input": "2024-02-19T13:47:53.426026Z", - "iopub.status.busy": "2024-02-19T13:47:53.425837Z", - "iopub.status.idle": "2024-02-19T13:47:53.605025Z", - "shell.execute_reply": "2024-02-19T13:47:53.604491Z" - } + "iopub.execute_input": "2024-05-24T12:37:26.586756Z", + "iopub.status.busy": "2024-05-24T12:37:26.585661Z", + "iopub.status.idle": "2024-05-24T12:37:26.695543Z", + "shell.execute_reply": "2024-05-24T12:37:26.693180Z" + }, + "tags": [ + "thebe-init" + ] }, "outputs": [ { @@ -1470,9 +1526,9 @@ ], "metadata": { "kernelspec": { - "display_name": "shenfun24", - "language": "python3", - "name": "shenfun24" + "display_name": "Python 3", + "language": "python", + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -1484,7 +1540,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.0" + "version": "3.12.3" } }, "nbformat": 4, diff --git a/docs/source/mixingbases.ipynb b/docs/source/mixingbases.ipynb index 0ec97322..5599b3ee 100644 --- a/docs/source/mixingbases.ipynb +++ b/docs/source/mixingbases.ipynb @@ -41,7 +41,7 @@ }, "source": [ "\n", - "
\n", + "\n", "\n", "$$\n", "\\begin{equation}\n", @@ -69,7 +69,7 @@ }, "source": [ "\n", - "
\n", + "\n", "\n", "$$\n", "\\begin{equation}\n", @@ -97,7 +97,7 @@ }, "source": [ "\n", - "
\n", + "\n", "\n", "$$\n", "\\begin{equation}\n", @@ -144,7 +144,7 @@ }, "source": [ "\n", - "
\n", + "\n", "\n", "$$\n", "\\label{eq:heinrichs} \\tag{5}\n", @@ -160,7 +160,7 @@ }, "source": [ "\n", - "
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e=t[0],r=t[t.length-1];if(a=e.pmin-e.pos-e.dp+e.size,o=r.pos+r.dp+r.size-e.pmax,a>.01){for(l=t.length-1;l>=0;l--)t[l].dp+=a;i=!1}if(!(o<.01)){if(a<-.01){for(l=t.length-1;l>=0;l--)t[l].dp-=o;i=!1}if(i){var n=0;for(s=0;se.pmax&&n++;for(s=t.length-1;s>=0&&!(n<=0);s--)(u=t[s]).pos>e.pmax-1&&(u.del=!0,n--);for(s=0;s=0;l--)t[l].dp-=o;for(s=t.length-1;s>=0&&!(n<=0);s--)(u=t[s]).pos+u.dp+u.size>e.pmax&&(u.del=!0,n--)}}}for(t.each((function(t){var n=t[f],i=t[h],a=\"x\"===n._id.charAt(0),o=n.range;0===y&&o&&o[0]>o[1]!==a&&(d=-1);var s=0,l=a?r.width:r.height;if(\"x\"===r.hovermode||\"y\"===r.hovermode){var u,c,p=D(t,e),v=t.anchor,A=\"end\"===v?-1:1;if(\"middle\"===v)c=(u=t.crossPos+(a?k(p.y-t.by/2):w(t.bx/2+t.tx2width/2)))+(a?k(t.by):w(t.bx));else if(a)c=(u=t.crossPos+k(M+p.y)-k(t.by/2-M))+k(t.by);else{var S=w(A*M+p.x),E=S+w(A*t.bx);u=t.crossPos+Math.min(S,E),c=t.crossPos+Math.max(S,E)}a?void 0!==b&&void 0!==_&&Math.min(c,_)-Math.max(u,b)>1&&(\"left\"===i.side?(s=i._mainLinePosition,l=r.width):l=i._mainLinePosition):void 0!==m&&void 0!==x&&Math.min(c,x)-Math.max(u,m)>1&&(\"top\"===i.side?(s=i._mainLinePosition,l=r.height):l=i._mainLinePosition)}g[y++]=[{datum:t,traceIndex:t.trace.index,dp:0,pos:t.pos,posref:t.posref,size:t.by*(a?T:1)/2,pmin:s,pmax:l}]})),g.sort((function(t,e){return t[0].posref-e[0].posref||d*(e[0].traceIndex-t[0].traceIndex)}));!i&&p<=v;){for(p++,i=!0,s=0;s.01&&L.pmin===C.pmin&&L.pmax===C.pmax){for(l=E.length-1;l>=0;l--)E[l].dp+=a;for(S.push.apply(S,E),g.splice(s+1,1),c=0,l=S.length-1;l>=0;l--)c+=S[l].dp;for(o=c/S.length,l=S.length-1;l>=0;l--)S[l].dp-=o;i=!1}else s++}g.forEach(A)}for(s=g.length-1;s>=0;s--){var P=g[s];for(l=P.length-1;l>=0;l--){var O=P[l],I=O.datum;I.offset=O.dp,I.del=O.del}}}(Xt,Zt,c,Wt.commonLabelBoundingBox),z(Xt,Zt,c._invScaleX,c._invScaleY)),s&&s.tagName){var Jt=g.getComponentMethod(\"annotations\",\"hasClickToShow\")(t,Ot);f(n.select(s),Jt?\"pointer\":\"\")}s&&!a&&function(t,e,r){if(!r||r.length!==t._hoverdata.length)return!0;for(var n=r.length-1;n>=0;n--){var i=r[n],a=t._hoverdata[n];if(i.curveNumber!==a.curveNumber||String(i.pointNumber)!==String(a.pointNumber)||String(i.pointNumbers)!==String(a.pointNumbers))return!0}return!1}(t,0,Pt)&&(Pt&&t.emit(\"plotly_unhover\",{event:e,points:Pt}),t.emit(\"plotly_hover\",{event:e,points:t._hoverdata,xaxes:_,yaxes:w,xvals:q,yvals:G}))}(t,e,r,a,s)}))},e.loneHover=function(t,e){var r=!0;Array.isArray(t)||(r=!1,t=[t]);var i=e.gd,a=U(i),o=V(i),s=O(t.map((function(t){var r=t._x0||t.x0||t.x||0,n=t._x1||t.x1||t.x||0,s=t._y0||t.y0||t.y||0,l=t._y1||t.y1||t.y||0,u=t.eventData;if(u){var c=Math.min(r,n),f=Math.max(r,n),h=Math.min(s,l),d=Math.max(s,l),v=t.trace;if(g.traceIs(v,\"gl3d\")){var y=i._fullLayout[v.scene]._scene.container,m=y.offsetLeft,x=y.offsetTop;c+=m,f+=m,h+=x,d+=x}u.bbox={x0:c+o,x1:f+o,y0:h+a,y1:d+a},e.inOut_bbox&&e.inOut_bbox.push(u.bbox)}else u=!1;return{color:t.color||p.defaultLine,x0:t.x0||t.x||0,x1:t.x1||t.x||0,y0:t.y0||t.y||0,y1:t.y1||t.y||0,xLabel:t.xLabel,yLabel:t.yLabel,zLabel:t.zLabel,text:t.text,name:t.name,idealAlign:t.idealAlign,borderColor:t.borderColor,fontFamily:t.fontFamily,fontSize:t.fontSize,fontColor:t.fontColor,nameLength:t.nameLength,textAlign:t.textAlign,trace:t.trace||{index:0,hoverinfo:\"\"},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:t.hovertemplate||!1,hovertemplateLabels:t.hovertemplateLabels||!1,eventData:u}})),{gd:i,hovermode:\"closest\",rotateLabels:!1,bgColor:e.bgColor||p.background,container:n.select(e.container),outerContainer:e.outerContainer||e.container}).hoverLabels,l=0,u=0;return s.sort((function(t,e){return t.y0-e.y0})).each((function(t,r){var n=t.y0-t.by/2;t.offset=n-5([\\s\\S]*)<\\/extra>/;function O(t,e){var r=e.gd,i=r._fullLayout,a=e.hovermode,u=e.rotateLabels,f=e.bgColor,d=e.container,v=e.outerContainer,w=e.commonLabelOpts||{};if(0===t.length)return[[]];var T=e.fontFamily||m.HOVERFONT,k=e.fontSize||m.HOVERFONTSIZE,A=t[0],E=A.xa,L=A.ya,P=a.charAt(0),O=P+\"Label\",D=A[O];if(void 0===D&&\"multicategory\"===E.type)for(var z=0;zi.width-b?(g=i.width-b,e.attr(\"d\",\"M\"+(b-M)+\",0L\"+b+\",\"+x+M+\"v\"+x+(2*S+m.height)+\"H-\"+b+\"V\"+x+M+\"H\"+(b-2*M)+\"Z\")):e.attr(\"d\",\"M0,0L\"+M+\",\"+x+M+\"H\"+b+\"v\"+x+(2*S+m.height)+\"H-\"+b+\"V\"+x+M+\"H-\"+M+\"Z\"),Y.minX=g-b,Y.maxX=g+b,\"top\"===E.side?(Y.minY=y-(2*S+m.height),Y.maxY=y-S):(Y.minY=y+S,Y.maxY=y+(2*S+m.height))}else{var _,C,P;\"right\"===L.side?(_=\"start\",C=1,P=\"\",g=E._offset+E._length):(_=\"end\",C=-1,P=\"-\",g=E._offset),y=L._offset+(A.y0+A.y1)/2,l.attr(\"text-anchor\",_),e.attr(\"d\",\"M0,0L\"+P+M+\",\"+M+\"V\"+(S+m.height/2)+\"h\"+P+(2*S+m.width)+\"V-\"+(S+m.height/2)+\"H\"+P+M+\"V-\"+M+\"Z\"),Y.minY=y-(S+m.height/2),Y.maxY=y+(S+m.height/2),\"right\"===L.side?(Y.minX=g+M,Y.maxX=g+M+(2*S+m.width)):(Y.minX=g-M-(2*S+m.width),Y.maxX=g-M);var O,I=m.height/2,z=F-m.top-I,R=\"clip\"+i._uid+\"commonlabel\"+L._id;if(g=0?lt:ut+ht=0?ut:bt+ht=0?ot:st+pt=0?st:_t+pt=0,\"top\"!==t.idealAlign&&G||!Z?G?(O+=R/2,t.anchor=\"start\"):t.anchor=\"middle\":(O-=R/2,t.anchor=\"end\"),t.crossPos=O;else{if(t.pos=O,G=P+z/2+Y<=B,Z=P-z/2-Y>=0,\"left\"!==t.idealAlign&&G||!Z)if(G)P+=z/2,t.anchor=\"start\";else{t.anchor=\"middle\";var W=Y/2,X=P+W-B,J=P-W;X>0&&(P-=X),J<0&&(P+=-J)}else P-=z/2,t.anchor=\"end\";t.crossPos=P}w.attr(\"text-anchor\",t.anchor),E&&A.attr(\"text-anchor\",t.anchor),e.attr(\"transform\",s(P,O)+(u?l(_):\"\"))})),{hoverLabels:wt,commonLabelBoundingBox:Y}}function I(t,e,r,n,i,a){var s=\"\",l=\"\";void 0!==t.nameOverride&&(t.name=t.nameOverride),t.name&&(t.trace._meta&&(t.name=o.templateString(t.name,t.trace._meta)),s=N(t.name,t.nameLength));var u=r.charAt(0),c=\"x\"===u?\"y\":\"x\";void 0!==t.zLabel?(void 0!==t.xLabel&&(l+=\"x: \"+t.xLabel+\"
\"),void 0!==t.yLabel&&(l+=\"y: \"+t.yLabel+\"
\"),\"choropleth\"!==t.trace.type&&\"choroplethmapbox\"!==t.trace.type&&(l+=(l?\"z: \":\"\")+t.zLabel)):e&&t[u+\"Label\"]===i?l=t[c+\"Label\"]||\"\":void 0===t.xLabel?void 0!==t.yLabel&&\"scattercarpet\"!==t.trace.type&&(l=t.yLabel):l=void 0===t.yLabel?t.xLabel:\"(\"+t.xLabel+\", \"+t.yLabel+\")\",!t.text&&0!==t.text||Array.isArray(t.text)||(l+=(l?\"
\":\"\")+t.text),void 0!==t.extraText&&(l+=(l?\"
\":\"\")+t.extraText),a&&\"\"===l&&!t.hovertemplate&&(\"\"===s&&a.remove(),l=s);var f=t.hovertemplate||!1;if(f){var h=t.hovertemplateLabels||t;t[u+\"Label\"]!==i&&(h[u+\"other\"]=h[u+\"Val\"],h[u+\"otherLabel\"]=h[u+\"Label\"]),l=(l=o.hovertemplateString(f,h,n._d3locale,t.eventData[0]||{},t.trace._meta)).replace(P,(function(e,r){return s=N(r,t.nameLength),\"\"}))}return[l,s]}function D(t,e){var r=0,n=t.offset;return e&&(n*=-A,r=t.offset*k),{x:r,y:n}}function z(t,e,r,i){var a=function(t){return t*r},o=function(t){return t*i};t.each((function(t){var r=n.select(this);if(t.del)return r.remove();var i,s,l,u,f=r.select(\"text.nums\"),p=t.anchor,d=\"end\"===p?-1:1,v=(u=(l=(s={start:1,end:-1,middle:0}[(i=t).anchor])*(M+S))+s*(i.txwidth+S),\"middle\"===i.anchor&&(l-=i.tx2width/2,u+=i.txwidth/2+S),{alignShift:s,textShiftX:l,text2ShiftX:u}),g=D(t,e),y=g.x,m=g.y,x=\"middle\"===p;r.select(\"path\").attr(\"d\",x?\"M-\"+a(t.bx/2+t.tx2width/2)+\",\"+o(m-t.by/2)+\"h\"+a(t.bx)+\"v\"+o(t.by)+\"h-\"+a(t.bx)+\"Z\":\"M0,0L\"+a(d*M+y)+\",\"+o(M+m)+\"v\"+o(t.by/2-M)+\"h\"+a(d*t.bx)+\"v-\"+o(t.by)+\"H\"+a(d*M+y)+\"V\"+o(m-M)+\"Z\");var b=y+v.textShiftX,_=m+t.ty0-t.by/2+S,w=t.textAlign||\"auto\";\"auto\"!==w&&(\"left\"===w&&\"start\"!==p?(f.attr(\"text-anchor\",\"start\"),b=x?-t.bx/2-t.tx2width/2+S:-t.bx-S):\"right\"===w&&\"end\"!==p&&(f.attr(\"text-anchor\",\"end\"),b=x?t.bx/2-t.tx2width/2-S:t.bx+S)),f.call(c.positionText,a(b),o(_)),t.tx2width&&(r.select(\"text.name\").call(c.positionText,a(v.text2ShiftX+v.alignShift*S+y),o(m+t.ty0-t.by/2+S)),r.select(\"rect\").call(h.setRect,a(v.text2ShiftX+(v.alignShift-1)*t.tx2width/2+y),o(m-t.by/2-1),a(t.tx2width),o(t.by+2)))}))}function R(t,e){var r=t.index,n=t.trace||{},a=t.cd[0],s=t.cd[r]||{};function l(t){return t||i(t)&&0===t}var u=Array.isArray(r)?function(t,e){var i=o.castOption(a,r,t);return l(i)?i:o.extractOption({},n,\"\",e)}:function(t,e){return o.extractOption(s,n,t,e)};function c(e,r,n){var i=u(r,n);l(i)&&(t[e]=i)}if(c(\"hoverinfo\",\"hi\",\"hoverinfo\"),c(\"bgcolor\",\"hbg\",\"hoverlabel.bgcolor\"),c(\"borderColor\",\"hbc\",\"hoverlabel.bordercolor\"),c(\"fontFamily\",\"htf\",\"hoverlabel.font.family\"),c(\"fontSize\",\"hts\",\"hoverlabel.font.size\"),c(\"fontColor\",\"htc\",\"hoverlabel.font.color\"),c(\"nameLength\",\"hnl\",\"hoverlabel.namelength\"),c(\"textAlign\",\"hta\",\"hoverlabel.align\"),t.posref=\"y\"===e||\"closest\"===e&&\"h\"===n.orientation?t.xa._offset+(t.x0+t.x1)/2:t.ya._offset+(t.y0+t.y1)/2,t.x0=o.constrain(t.x0,0,t.xa._length),t.x1=o.constrain(t.x1,0,t.xa._length),t.y0=o.constrain(t.y0,0,t.ya._length),t.y1=o.constrain(t.y1,0,t.ya._length),void 0!==t.xLabelVal&&(t.xLabel=\"xLabel\"in t?t.xLabel:v.hoverLabelText(t.xa,t.xLabelVal,n.xhoverformat),t.xVal=t.xa.c2d(t.xLabelVal)),void 0!==t.yLabelVal&&(t.yLabel=\"yLabel\"in t?t.yLabel:v.hoverLabelText(t.ya,t.yLabelVal,n.yhoverformat),t.yVal=t.ya.c2d(t.yLabelVal)),void 0!==t.zLabelVal&&void 0===t.zLabel&&(t.zLabel=String(t.zLabelVal)),!(isNaN(t.xerr)||\"log\"===t.xa.type&&t.xerr<=0)){var f=v.tickText(t.xa,t.xa.c2l(t.xerr),\"hover\").text;void 0!==t.xerrneg?t.xLabel+=\" +\"+f+\" / -\"+v.tickText(t.xa,t.xa.c2l(t.xerrneg),\"hover\").text:t.xLabel+=\" ± \"+f,\"x\"===e&&(t.distance+=1)}if(!(isNaN(t.yerr)||\"log\"===t.ya.type&&t.yerr<=0)){var h=v.tickText(t.ya,t.ya.c2l(t.yerr),\"hover\").text;void 0!==t.yerrneg?t.yLabel+=\" +\"+h+\" / -\"+v.tickText(t.ya,t.ya.c2l(t.yerrneg),\"hover\").text:t.yLabel+=\" ± \"+h,\"y\"===e&&(t.distance+=1)}var p=t.hoverinfo||t.trace.hoverinfo;return p&&\"all\"!==p&&(-1===(p=Array.isArray(p)?p:p.split(\"+\")).indexOf(\"x\")&&(t.xLabel=void 0),-1===p.indexOf(\"y\")&&(t.yLabel=void 0),-1===p.indexOf(\"z\")&&(t.zLabel=void 0),-1===p.indexOf(\"text\")&&(t.text=void 0),-1===p.indexOf(\"name\")&&(t.name=void 0)),t}function F(t,e,r){var n,i,o=r.container,s=r.fullLayout,l=s._size,u=r.event,c=!!e.hLinePoint,f=!!e.vLinePoint;if(o.selectAll(\".spikeline\").remove(),f||c){var d=p.combine(s.plot_bgcolor,s.paper_bgcolor);if(c){var g,y,m=e.hLinePoint;n=m&&m.xa,\"cursor\"===(i=m&&m.ya).spikesnap?(g=u.pointerX,y=u.pointerY):(g=n._offset+m.x,y=i._offset+m.y);var x,b,_=a.readability(m.color,d)<1.5?p.contrast(d):m.color,w=i.spikemode,T=i.spikethickness,k=i.spikecolor||_,A=v.getPxPosition(t,i);if(-1!==w.indexOf(\"toaxis\")||-1!==w.indexOf(\"across\")){if(-1!==w.indexOf(\"toaxis\")&&(x=A,b=g),-1!==w.indexOf(\"across\")){var M=i._counterDomainMin,S=i._counterDomainMax;\"free\"===i.anchor&&(M=Math.min(M,i.position),S=Math.max(S,i.position)),x=l.l+M*l.w,b=l.l+S*l.w}o.insert(\"line\",\":first-child\").attr({x1:x,x2:b,y1:y,y2:y,\"stroke-width\":T,stroke:k,\"stroke-dasharray\":h.dashStyle(i.spikedash,T)}).classed(\"spikeline\",!0).classed(\"crisp\",!0),o.insert(\"line\",\":first-child\").attr({x1:x,x2:b,y1:y,y2:y,\"stroke-width\":T+2,stroke:d}).classed(\"spikeline\",!0).classed(\"crisp\",!0)}-1!==w.indexOf(\"marker\")&&o.insert(\"circle\",\":first-child\").attr({cx:A+(\"right\"!==i.side?T:-T),cy:y,r:T,fill:k}).classed(\"spikeline\",!0)}if(f){var E,L,C=e.vLinePoint;n=C&&C.xa,i=C&&C.ya,\"cursor\"===n.spikesnap?(E=u.pointerX,L=u.pointerY):(E=n._offset+C.x,L=i._offset+C.y);var 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e=t._fullLayout.selections.length-1;t._fullLayout._activeSelectionIndex=e,t._fullLayout._deactivateSelection=v,f(t)}}}},53777:function(t,e,r){\"use strict\";var n=r(79952).P,i=r(1426).extendFlat;t.exports={newselection:{mode:{valType:\"enumerated\",values:[\"immediate\",\"gradual\"],dflt:\"immediate\",editType:\"none\"},line:{color:{valType:\"color\",editType:\"none\"},width:{valType:\"number\",min:1,dflt:1,editType:\"none\"},dash:i({},n,{dflt:\"dot\",editType:\"none\"}),editType:\"none\"},editType:\"none\"},activeselection:{fillcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"none\"},opacity:{valType:\"number\",min:0,max:1,dflt:.5,editType:\"none\"},editType:\"none\"}}},90849:function(t){\"use strict\";t.exports=function(t,e,r){r(\"newselection.mode\"),r(\"newselection.line.width\")&&(r(\"newselection.line.color\"),r(\"newselection.line.dash\")),r(\"activeselection.fillcolor\"),r(\"activeselection.opacity\")}},35855:function(t,e,r){\"use strict\";var n=r(64505).selectMode,i=r(51873).clearOutline,a=r(60165),o=a.readPaths,s=a.writePaths,l=a.fixDatesForPaths;t.exports=function(t,e){if(t.length){var r=t[0][0];if(r){var a=r.getAttribute(\"d\"),u=e.gd,c=u._fullLayout.newselection,f=e.plotinfo,h=f.xaxis,p=f.yaxis,d=e.isActiveSelection,v=e.dragmode,g=(u.layout||{}).selections||[];if(!n(v)&&void 0!==d){var y=u._fullLayout._activeSelectionIndex;if(y-1,b=[];if(function(t){return t&&Array.isArray(t)&&!0!==t[0].hoverOnBox}(y)){Z(t,e,a);var _=function(t,e){var r,n,i=t[0],a=-1,o=[];for(n=0;n0?function(t,e){var r,n,i,a=[];for(i=0;i0&&a.push(r);if(1===a.length&&a[0]===e.searchInfo&&(n=e.searchInfo.cd[0].trace).selectedpoints.length===e.pointNumbers.length){for(i=0;i1)return!1;if((n+=e.selectedpoints.length)>1)return!1}return 1===n}(s)&&(h=K(_))){for(o&&o.remove(),g=0;g=0})(i)&&i._fullLayout._deactivateShape(i),function(t){return t._fullLayout._activeSelectionIndex>=0}(i)&&i._fullLayout._deactivateSelection(i);var o=i._fullLayout._zoomlayer,s=p(r),l=v(r);if(s||l){var u,c,f=o.selectAll(\".select-outline-\"+n.id);f&&i._fullLayout._outlining&&(s&&(u=T(f,t)),u&&a.call(\"_guiRelayout\",i,{shapes:u}),l&&!U(t)&&(c=k(f,t)),c&&(i._fullLayout._noEmitSelectedAtStart=!0,a.call(\"_guiRelayout\",i,{selections:c}).then((function(){e&&A(i)}))),i._fullLayout._outlining=!1)}n.selection={},n.selection.selectionDefs=t.selectionDefs=[],n.selection.mergedPolygons=t.mergedPolygons=[]}function W(t){return t._id}function X(t,e,r,n){if(!t.calcdata)return[];var i,a,o,s=[],l=e.map(W),u=r.map(W);for(o=0;o0?n[0]:r;return!!e.selectedpoints&&e.selectedpoints.indexOf(i)>-1}function $(t,e,r){var n,i;for(n=0;n-1&&e;if(!a&&e){var et=ot(t,!0);if(et.length){var nt=et[0].xref,pt=et[0].yref;if(nt&&pt){var dt=ut(et);ct([C(t,nt,\"x\"),C(t,pt,\"y\")])(Q,dt)}}t._fullLayout._noEmitSelectedAtStart?t._fullLayout._noEmitSelectedAtStart=!1:tt&&ft(t,Q),h._reselect=!1}if(!a&&h._deselect){var vt=h._deselect;(function(t,e,r){for(var 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n=r(50215),i=r(41940),a=r(82196).line,o=r(79952).P,s=r(1426).extendFlat,l=r(44467).templatedArray,u=(r(24695),r(9012)),c=r(5386).R,f=r(37281);t.exports=l(\"shape\",{visible:s({},u.visible,{editType:\"calc+arraydraw\"}),showlegend:{valType:\"boolean\",dflt:!1,editType:\"calc+arraydraw\"},legend:s({},u.legend,{editType:\"calc+arraydraw\"}),legendgroup:s({},u.legendgroup,{editType:\"calc+arraydraw\"}),legendgrouptitle:{text:s({},u.legendgrouptitle.text,{editType:\"calc+arraydraw\"}),font:i({editType:\"calc+arraydraw\"}),editType:\"calc+arraydraw\"},legendrank:s({},u.legendrank,{editType:\"calc+arraydraw\"}),legendwidth:s({},u.legendwidth,{editType:\"calc+arraydraw\"}),type:{valType:\"enumerated\",values:[\"circle\",\"rect\",\"path\",\"line\"],editType:\"calc+arraydraw\"},layer:{valType:\"enumerated\",values:[\"below\",\"above\"],dflt:\"above\",editType:\"arraydraw\"},xref:s({},n.xref,{}),xsizemode:{valType:\"enumerated\",values:[\"scaled\",\"pixel\"],dflt:\"scaled\",editType:\"calc+arraydraw\"},xanchor:{valType:\"any\",editType:\"calc+arraydraw\"},x0:{valType:\"any\",editType:\"calc+arraydraw\"},x1:{valType:\"any\",editType:\"calc+arraydraw\"},yref:s({},n.yref,{}),ysizemode:{valType:\"enumerated\",values:[\"scaled\",\"pixel\"],dflt:\"scaled\",editType:\"calc+arraydraw\"},yanchor:{valType:\"any\",editType:\"calc+arraydraw\"},y0:{valType:\"any\",editType:\"calc+arraydraw\"},y1:{valType:\"any\",editType:\"calc+arraydraw\"},path:{valType:\"string\",editType:\"calc+arraydraw\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,editType:\"arraydraw\"},line:{color:s({},a.color,{editType:\"arraydraw\"}),width:s({},a.width,{editType:\"calc+arraydraw\"}),dash:s({},o,{editType:\"arraydraw\"}),editType:\"calc+arraydraw\"},fillcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"arraydraw\"},fillrule:{valType:\"enumerated\",values:[\"evenodd\",\"nonzero\"],dflt:\"evenodd\",editType:\"arraydraw\"},editable:{valType:\"boolean\",dflt:!1,editType:\"calc+arraydraw\"},label:{text:{valType:\"string\",dflt:\"\",editType:\"arraydraw\"},texttemplate:c({},{keys:Object.keys(f)}),font:i({editType:\"calc+arraydraw\",colorEditType:\"arraydraw\"}),textposition:{valType:\"enumerated\",values:[\"top 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n=r(41940),i=r(35025),a=r(1426).extendDeepAll,o=r(30962).overrideAll,s=r(85594),l=r(44467).templatedArray,u=r(98292),c=l(\"step\",{visible:{valType:\"boolean\",dflt:!0},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\"},value:{valType:\"string\"},execute:{valType:\"boolean\",dflt:!0}});t.exports=o(l(\"slider\",{visible:{valType:\"boolean\",dflt:!0},active:{valType:\"number\",min:0,dflt:0},steps:c,lenmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"fraction\"},len:{valType:\"number\",min:0,dflt:1},x:{valType:\"number\",min:-2,max:3,dflt:0},pad:a(i({editType:\"arraydraw\"}),{},{t:{dflt:20}}),xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\"},y:{valType:\"number\",min:-2,max:3,dflt:0},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},transition:{duration:{valType:\"number\",min:0,dflt:150},easing:{valType:\"enumerated\",values:s.transition.easing.values,dflt:\"cubic-in-out\"}},currentvalue:{visible:{valType:\"boolean\",dflt:!0},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\"},offset:{valType:\"number\",dflt:10},prefix:{valType:\"string\"},suffix:{valType:\"string\"},font:n({})},font:n({}),activebgcolor:{valType:\"color\",dflt:u.gripBgActiveColor},bgcolor:{valType:\"color\",dflt:u.railBgColor},bordercolor:{valType:\"color\",dflt:u.railBorderColor},borderwidth:{valType:\"number\",min:0,dflt:u.railBorderWidth},ticklen:{valType:\"number\",min:0,dflt:u.tickLength},tickcolor:{valType:\"color\",dflt:u.tickColor},tickwidth:{valType:\"number\",min:0,dflt:1},minorticklen:{valType:\"number\",min:0,dflt:u.minorTickLength}}),\"arraydraw\",\"from-root\")},98292:function(t){\"use strict\";t.exports={name:\"sliders\",containerClassName:\"slider-container\",groupClassName:\"slider-group\",inputAreaClass:\"slider-input-area\",railRectClass:\"slider-rail-rect\",railTouchRectClass:\"slider-rail-touch-rect\",gripRectClass:\"slider-grip-rect\",tickRectClass:\"slider-tick-rect\",inputProxyClass:\"slider-input-proxy\",labelsClass:\"slider-labels\",labelGroupClass:\"slider-label-group\",labelClass:\"slider-label\",currentValueClass:\"slider-current-value\",railHeight:5,menuIndexAttrName:\"slider-active-index\",autoMarginIdRoot:\"slider-\",minWidth:30,minHeight:30,textPadX:40,arrowOffsetX:4,railRadius:2,railWidth:5,railBorder:4,railBorderWidth:1,railBorderColor:\"#bec8d9\",railBgColor:\"#f8fafc\",railInset:8,stepInset:10,gripRadius:10,gripWidth:20,gripHeight:20,gripBorder:20,gripBorderWidth:1,gripBorderColor:\"#bec8d9\",gripBgColor:\"#f6f8fa\",gripBgActiveColor:\"#dbdde0\",labelPadding:8,labelOffset:0,tickWidth:1,tickColor:\"#333\",tickOffset:25,tickLength:7,minorTickOffset:25,minorTickColor:\"#333\",minorTickLength:4,currentValuePadding:8,currentValueInset:0}},12343:function(t,e,r){\"use strict\";var n=r(71828),i=r(85501),a=r(75067),o=r(98292).name,s=a.steps;function l(t,e,r){function o(r,i){return n.coerce(t,e,a,r,i)}for(var s=i(t,e,{name:\"steps\",handleItemDefaults:u}),l=0,c=0;c0&&(s=s.transition().duration(e.transition.duration).ease(e.transition.easing)),s.attr(\"transform\",l(o-.5*f.gripWidth,e._dims.currentValueTotalHeight))}}function E(t,e){var r=t._dims;return r.inputAreaStart+f.stepInset+(r.inputAreaLength-2*f.stepInset)*Math.min(1,Math.max(0,e))}function L(t,e){var r=t._dims;return Math.min(1,Math.max(0,(e-f.stepInset-r.inputAreaStart)/(r.inputAreaLength-2*f.stepInset-2*r.inputAreaStart)))}function C(t,e,r){var n=r._dims,i=s.ensureSingle(t,\"rect\",f.railTouchRectClass,(function(n){n.call(A,e,t,r).style(\"pointer-events\",\"all\")}));i.attr({width:n.inputAreaLength,height:Math.max(n.inputAreaWidth,f.tickOffset+r.ticklen+n.labelHeight)}).call(a.fill,r.bgcolor).attr(\"opacity\",0),o.setTranslate(i,0,n.currentValueTotalHeight)}function P(t,e){var r=e._dims,n=r.inputAreaLength-2*f.railInset,i=s.ensureSingle(t,\"rect\",f.railRectClass);i.attr({width:n,height:f.railWidth,rx:f.railRadius,ry:f.railRadius,\"shape-rendering\":\"crispEdges\"}).call(a.stroke,e.bordercolor).call(a.fill,e.bgcolor).style(\"stroke-width\",e.borderwidth+\"px\"),o.setTranslate(i,f.railInset,.5*(r.inputAreaWidth-f.railWidth)+r.currentValueTotalHeight)}t.exports=function(t){var e=t._context.staticPlot,r=t._fullLayout,a=function(t,e){for(var r=t[f.name],n=[],i=0;i0?[0]:[]);function l(e){e._commandObserver&&(e._commandObserver.remove(),delete e._commandObserver),i.autoMargin(t,g(e))}if(s.enter().append(\"g\").classed(f.containerClassName,!0).style(\"cursor\",e?null:\"ew-resize\"),s.exit().each((function(){n.select(this).selectAll(\"g.\"+f.groupClassName).each(l)})).remove(),0!==a.length){var u=s.selectAll(\"g.\"+f.groupClassName).data(a,y);u.enter().append(\"g\").classed(f.groupClassName,!0),u.exit().each(l).remove();for(var c=0;c0||_<0){var M={left:[-w,0],right:[w,0],top:[0,-w],bottom:[0,w]}[b.side];r.attr(\"transform\",l(M[0],M[1]))}}}return R.call(F),I&&(E?R.on(\".opacity\",null):(A=0,M=!0,R.text(m).on(\"mouseover.opacity\",(function(){n.select(this).transition().duration(h.SHOW_PLACEHOLDER).style(\"opacity\",1)})).on(\"mouseout.opacity\",(function(){n.select(this).transition().duration(h.HIDE_PLACEHOLDER).style(\"opacity\",0)}))),R.call(f.makeEditable,{gd:t}).on(\"edit\",(function(e){void 0!==x?o.call(\"_guiRestyle\",t,y,e,x):o.call(\"_guiRelayout\",t,y,e)})).on(\"cancel\",(function(){this.text(this.attr(\"data-unformatted\")).call(F)})).on(\"input\",(function(t){this.text(t||\" \").call(f.positionText,_.x,_.y)}))),R.classed(\"js-placeholder\",M),T}}},7163:function(t,e,r){\"use strict\";var n=r(41940),i=r(22399),a=r(1426).extendFlat,o=r(30962).overrideAll,s=r(35025),l=r(44467).templatedArray,u=l(\"button\",{visible:{valType:\"boolean\"},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},args2:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\",dflt:\"\"},execute:{valType:\"boolean\",dflt:!0}});t.exports=o(l(\"updatemenu\",{_arrayAttrRegexps:[/^updatemenus\\[(0|[1-9][0-9]+)\\]\\.buttons/],visible:{valType:\"boolean\"},type:{valType:\"enumerated\",values:[\"dropdown\",\"buttons\"],dflt:\"dropdown\"},direction:{valType:\"enumerated\",values:[\"left\",\"right\",\"up\",\"down\"],dflt:\"down\"},active:{valType:\"integer\",min:-1,dflt:0},showactive:{valType:\"boolean\",dflt:!0},buttons:u,x:{valType:\"number\",min:-2,max:3,dflt:-.05},xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"right\"},y:{valType:\"number\",min:-2,max:3,dflt:1},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},pad:a(s({editType:\"arraydraw\"}),{}),font:n({}),bgcolor:{valType:\"color\"},bordercolor:{valType:\"color\",dflt:i.borderLine},borderwidth:{valType:\"number\",min:0,dflt:1,editType:\"arraydraw\"}}),\"arraydraw\",\"from-root\")},75909:function(t){\"use strict\";t.exports={name:\"updatemenus\",containerClassName:\"updatemenu-container\",headerGroupClassName:\"updatemenu-header-group\",headerClassName:\"updatemenu-header\",headerArrowClassName:\"updatemenu-header-arrow\",dropdownButtonGroupClassName:\"updatemenu-dropdown-button-group\",dropdownButtonClassName:\"updatemenu-dropdown-button\",buttonClassName:\"updatemenu-button\",itemRectClassName:\"updatemenu-item-rect\",itemTextClassName:\"updatemenu-item-text\",menuIndexAttrName:\"updatemenu-active-index\",autoMarginIdRoot:\"updatemenu-\",blankHeaderOpts:{label:\" \"},minWidth:30,minHeight:30,textPadX:24,arrowPadX:16,rx:2,ry:2,textOffsetX:12,textOffsetY:3,arrowOffsetX:4,gapButtonHeader:5,gapButton:2,activeColor:\"#F4FAFF\",hoverColor:\"#F4FAFF\",arrowSymbol:{left:\"◄\",right:\"►\",up:\"▲\",down:\"▼\"}}},64897:function(t,e,r){\"use strict\";var n=r(71828),i=r(85501),a=r(7163),o=r(75909).name,s=a.buttons;function l(t,e,r){function o(r,i){return n.coerce(t,e,a,r,i)}o(\"visible\",i(t,e,{name:\"buttons\",handleItemDefaults:u}).length>0)&&(o(\"active\"),o(\"direction\"),o(\"type\"),o(\"showactive\"),o(\"x\"),o(\"y\"),n.noneOrAll(t,e,[\"x\",\"y\"]),o(\"xanchor\"),o(\"yanchor\"),o(\"pad.t\"),o(\"pad.r\"),o(\"pad.b\"),o(\"pad.l\"),n.coerceFont(o,\"font\",r.font),o(\"bgcolor\",r.paper_bgcolor),o(\"bordercolor\"),o(\"borderwidth\"))}function u(t,e){function r(r,i){return n.coerce(t,e,s,r,i)}r(\"visible\",\"skip\"===t.method||Array.isArray(t.args))&&(r(\"method\"),r(\"args\"),r(\"args2\"),r(\"label\"),r(\"execute\"))}t.exports=function(t,e){i(t,e,{name:o,handleItemDefaults:l})}},13689:function(t,e,r){\"use strict\";var n=r(39898),i=r(74875),a=r(7901),o=r(91424),s=r(71828),l=r(63893),u=r(44467).arrayEditor,c=r(18783).LINE_SPACING,f=r(75909),h=r(25849);function p(t){return t._index}function d(t,e){return+t.attr(f.menuIndexAttrName)===e._index}function v(t,e,r,n,i,a,o,s){e.active=o,u(t.layout,f.name,e).applyUpdate(\"active\",o),\"buttons\"===e.type?y(t,n,null,null,e):\"dropdown\"===e.type&&(i.attr(f.menuIndexAttrName,\"-1\"),g(t,n,i,a,e),s||y(t,n,i,a,e))}function g(t,e,r,n,i){var a=s.ensureSingle(e,\"g\",f.headerClassName,(function(t){t.style(\"pointer-events\",\"all\")})),l=i._dims,u=i.active,c=i.buttons[u]||f.blankHeaderOpts,h={y:i.pad.t,yPad:0,x:i.pad.l,xPad:0,index:0},p={width:l.headerWidth,height:l.headerHeight};a.call(m,i,c,t).call(M,i,h,p),s.ensureSingle(e,\"text\",f.headerArrowClassName,(function(t){t.attr(\"text-anchor\",\"end\").call(o.font,i.font).text(f.arrowSymbol[i.direction])})).attr({x:l.headerWidth-f.arrowOffsetX+i.pad.l,y:l.headerHeight/2+f.textOffsetY+i.pad.t}),a.on(\"click\",(function(){r.call(S,String(d(r,i)?-1:i._index)),y(t,e,r,n,i)})),a.on(\"mouseover\",(function(){a.call(w)})),a.on(\"mouseout\",(function(){a.call(T,i)})),o.setTranslate(e,l.lx,l.ly)}function y(t,e,r,a,o){r||(r=e).attr(\"pointer-events\",\"all\");var l=function(t){return-1==+t.attr(f.menuIndexAttrName)}(r)&&\"buttons\"!==o.type?[]:o.buttons,u=\"dropdown\"===o.type?f.dropdownButtonClassName:f.buttonClassName,c=r.selectAll(\"g.\"+u).data(s.filterVisible(l)),h=c.enter().append(\"g\").classed(u,!0),p=c.exit();\"dropdown\"===o.type?(h.attr(\"opacity\",\"0\").transition().attr(\"opacity\",\"1\"),p.transition().attr(\"opacity\",\"0\").remove()):p.remove();var d=0,g=0,y=o._dims,x=-1!==[\"up\",\"down\"].indexOf(o.direction);\"dropdown\"===o.type&&(x?g=y.headerHeight+f.gapButtonHeader:d=y.headerWidth+f.gapButtonHeader),\"dropdown\"===o.type&&\"up\"===o.direction&&(g=-f.gapButtonHeader+f.gapButton-y.openHeight),\"dropdown\"===o.type&&\"left\"===o.direction&&(d=-f.gapButtonHeader+f.gapButton-y.openWidth);var b={x:y.lx+d+o.pad.l,y:y.ly+g+o.pad.t,yPad:f.gapButton,xPad:f.gapButton,index:0},k={l:b.x+o.borderwidth,t:b.y+o.borderwidth};c.each((function(s,l){var u=n.select(this);u.call(m,o,s,t).call(M,o,b),u.on(\"click\",(function(){n.event.defaultPrevented||(s.execute&&(s.args2&&o.active===l?(v(t,o,0,e,r,a,-1),i.executeAPICommand(t,s.method,s.args2)):(v(t,o,0,e,r,a,l),i.executeAPICommand(t,s.method,s.args))),t.emit(\"plotly_buttonclicked\",{menu:o,button:s,active:o.active}))})),u.on(\"mouseover\",(function(){u.call(w)})),u.on(\"mouseout\",(function(){u.call(T,o),c.call(_,o)}))})),c.call(_,o),x?(k.w=Math.max(y.openWidth,y.headerWidth),k.h=b.y-k.t):(k.w=b.x-k.l,k.h=Math.max(y.openHeight,y.headerHeight)),k.direction=o.direction,a&&(c.size()?function(t,e,r,n,i,a){var o,s,l,u=i.direction,c=\"up\"===u||\"down\"===u,h=i._dims,p=i.active;if(c)for(s=0,l=0;l0?[0]:[]);if(o.enter().append(\"g\").classed(f.containerClassName,!0).style(\"cursor\",\"pointer\"),o.exit().each((function(){n.select(this).selectAll(\"g.\"+f.headerGroupClassName).each(a)})).remove(),0!==r.length){var l=o.selectAll(\"g.\"+f.headerGroupClassName).data(r,p);l.enter().append(\"g\").classed(f.headerGroupClassName,!0);for(var u=s.ensureSingle(o,\"g\",f.dropdownButtonGroupClassName,(function(t){t.style(\"pointer-events\",\"all\")})),c=0;cw,A=s.barLength+2*s.barPad,M=s.barWidth+2*s.barPad,S=d,E=g+y;E+M>u&&(E=u-M);var L=this.container.selectAll(\"rect.scrollbar-horizontal\").data(k?[0]:[]);L.exit().on(\".drag\",null).remove(),L.enter().append(\"rect\").classed(\"scrollbar-horizontal\",!0).call(i.fill,s.barColor),k?(this.hbar=L.attr({rx:s.barRadius,ry:s.barRadius,x:S,y:E,width:A,height:M}),this._hbarXMin=S+A/2,this._hbarTranslateMax=w-A):(delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax);var C=y>T,P=s.barWidth+2*s.barPad,O=s.barLength+2*s.barPad,I=d+v,D=g;I+P>l&&(I=l-P);var z=this.container.selectAll(\"rect.scrollbar-vertical\").data(C?[0]:[]);z.exit().on(\".drag\",null).remove(),z.enter().append(\"rect\").classed(\"scrollbar-vertical\",!0).call(i.fill,s.barColor),C?(this.vbar=z.attr({rx:s.barRadius,ry:s.barRadius,x:I,y:D,width:P,height:O}),this._vbarYMin=D+O/2,this._vbarTranslateMax=T-O):(delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax);var R=this.id,F=c-.5,B=C?f+P+.5:f+.5,N=h-.5,j=k?p+M+.5:p+.5,U=o._topdefs.selectAll(\"#\"+R).data(k||C?[0]:[]);if(U.exit().remove(),U.enter().append(\"clipPath\").attr(\"id\",R).append(\"rect\"),k||C?(this._clipRect=U.select(\"rect\").attr({x:Math.floor(F),y:Math.floor(N),width:Math.ceil(B)-Math.floor(F),height:Math.ceil(j)-Math.floor(N)}),this.container.call(a.setClipUrl,R,this.gd),this.bg.attr({x:d,y:g,width:v,height:y})):(this.bg.attr({width:0,height:0}),this.container.on(\"wheel\",null).on(\".drag\",null).call(a.setClipUrl,null),delete this._clipRect),k||C){var V=n.behavior.drag().on(\"dragstart\",(function(){n.event.sourceEvent.preventDefault()})).on(\"drag\",this._onBoxDrag.bind(this));this.container.on(\"wheel\",null).on(\"wheel\",this._onBoxWheel.bind(this)).on(\".drag\",null).call(V);var H=n.behavior.drag().on(\"dragstart\",(function(){n.event.sourceEvent.preventDefault(),n.event.sourceEvent.stopPropagation()})).on(\"drag\",this._onBarDrag.bind(this));k&&this.hbar.on(\".drag\",null).call(H),C&&this.vbar.on(\".drag\",null).call(H)}this.setTranslate(e,r)},s.prototype.disable=function(){(this.hbar||this.vbar)&&(this.bg.attr({width:0,height:0}),this.container.on(\"wheel\",null).on(\".drag\",null).call(a.setClipUrl,null),delete this._clipRect),this.hbar&&(this.hbar.on(\".drag\",null),this.hbar.remove(),delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax),this.vbar&&(this.vbar.on(\".drag\",null),this.vbar.remove(),delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax)},s.prototype._onBoxDrag=function(){var t=this.translateX,e=this.translateY;this.hbar&&(t-=n.event.dx),this.vbar&&(e-=n.event.dy),this.setTranslate(t,e)},s.prototype._onBoxWheel=function(){var t=this.translateX,e=this.translateY;this.hbar&&(t+=n.event.deltaY),this.vbar&&(e+=n.event.deltaY),this.setTranslate(t,e)},s.prototype._onBarDrag=function(){var t=this.translateX,e=this.translateY;if(this.hbar){var r=t+this._hbarXMin,i=r+this._hbarTranslateMax;t=(o.constrain(n.event.x,r,i)-r)/(i-r)*(this.position.w-this._box.w)}if(this.vbar){var a=e+this._vbarYMin,s=a+this._vbarTranslateMax;e=(o.constrain(n.event.y,a,s)-a)/(s-a)*(this.position.h-this._box.h)}this.setTranslate(t,e)},s.prototype.setTranslate=function(t,e){var r=this.position.w-this._box.w,n=this.position.h-this._box.h;if(t=o.constrain(t||0,0,r),e=o.constrain(e||0,0,n),this.translateX=t,this.translateY=e,this.container.call(a.setTranslate,this._box.l-this.position.l-t,this._box.t-this.position.t-e),this._clipRect&&this._clipRect.attr({x:Math.floor(this.position.l+t-.5),y:Math.floor(this.position.t+e-.5)}),this.hbar){var i=t/r;this.hbar.call(a.setTranslate,t+i*this._hbarTranslateMax,e)}if(this.vbar){var s=e/n;this.vbar.call(a.setTranslate,t,e+s*this._vbarTranslateMax)}}},18783:function(t){\"use strict\";t.exports={FROM_BL:{left:0,center:.5,right:1,bottom:0,middle:.5,top:1},FROM_TL:{left:0,center:.5,right:1,bottom:1,middle:.5,top:0},FROM_BR:{left:1,center:.5,right:0,bottom:0,middle:.5,top:1},LINE_SPACING:1.3,CAP_SHIFT:.7,MID_SHIFT:.35,OPPOSITE_SIDE:{left:\"right\",right:\"left\",top:\"bottom\",bottom:\"top\"}}},24695:function(t){\"use strict\";t.exports={axisRefDescription:function(t,e,r){return[\"If set to a\",t,\"axis id (e.g. *\"+t+\"* 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F=K(c),B=F[0],N=F[1],j=i(R.dtick),U=\"log\"===a&&!(j||\"L\"===R.dtick.charAt(0)),V=q.tickFirst(R,e);if(D){if(t._tmin=V,V=N:Y<=N;Y=q.tickIncrement(Y,W,f,o)){if(D&&H++,R.rangebreaks&&!f){if(Y=p)break}if(C.length>d||Y===Z)break;Z=Y;var X={value:Y};D?(U&&Y!==(0|Y)&&(X.simpleLabel=!0),l>1&&H%l&&(X.skipLabel=!0),C.push(X)):(X.minor=!0,P.push(X))}}else C=[],v=at(t);else D?(C=[],v=ot(t)):(P=[],L=ot(t))}if(I&&!(\"inside\"===t.minor.ticks&&\"outside\"===t.ticks||\"outside\"===t.minor.ticks&&\"inside\"===t.ticks)){for(var J=C.map((function(t){return t.value})),$=[],Q=0;Q0?(a=n-1,o=n):(a=n,o=n);var s,l=t[a].value,u=t[o].value,c=Math.abs(u-l),f=r||c,h=0;f>=m?h=c>=m&&c<=g?c:y:r===b&&f>=_?h=c>=_&&c<=x?c:b:f>=k?h=c>=k&&c<=w?c:T:r===A&&f>=A?h=A:f>=M?h=M:r===S&&f>=S?h=S:r===E&&f>=E&&(h=E),h>=c&&(h=c,s=!0);var p=i+h;if(e.rangebreaks&&h>0){for(var d=0,v=0;v<84;v++){var L=(v+.5)/84;e.maskBreaks(i*(1-L)+L*p)!==O&&d++}(h*=d/84)||(t[n].drop=!0),s&&c>A&&(h=c)}(h>0||0===n)&&(t[n].periodX=i+h/2)}}(C,t,t._definedDelta),t.rangebreaks){var it=\"y\"===t._id.charAt(0),st=1;\"auto\"===t.tickmode&&(st=t.tickfont?t.tickfont.size:12);var lt=NaN;for(r=C.length-1;r>-1;r--)if(C[r].drop)C.splice(r,1);else{C[r].value=zt(C[r].value,t);var ut=t.c2p(C[r].value);(it?lt>ut-st:ltp||ftp&&(ct.periodX=p),ft10||\"01-01\"!==n.substr(5)?t._tickround=\"d\":t._tickround=+e.substr(1)%12==0?\"y\":\"m\";else if(e>=M&&a<=10||e>=15*M)t._tickround=\"d\";else if(e>=L&&a<=16||e>=E)t._tickround=\"M\";else if(e>=C&&a<=19||e>=L)t._tickround=\"S\";else{var o=t.l2r(r+e).replace(/^-/,\"\").length;t._tickround=Math.max(a,o)-20,t._tickround<0&&(t._tickround=4)}}else if(i(e)||\"L\"===e.charAt(0)){var s=t.range.map(t.r2d||Number);i(e)||(e=Number(e.substr(1))),t._tickround=2-Math.floor(Math.log(e)/Math.LN10+.01);var l=Math.max(Math.abs(s[0]),Math.abs(s[1])),u=Math.floor(Math.log(l)/Math.LN10+.01),c=void 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c=s.simpleMap(t.range,t.r2l);if(t._isMinor&&(e*=1.5),e>.7)t.dtick=Math.ceil(e);else if(Math.abs(c[1]-c[0])<1){var f=1.5*Math.abs((c[1]-c[0])/e);e=Math.abs(Math.pow(10,c[1])-Math.pow(10,c[0]))/f,n=a(10),t.dtick=\"L\"+dt(e,n,st)}else t.dtick=e>.3?\"D2\":\"D1\"}else\"category\"===t.type||\"multicategory\"===t.type?(t.tick0=0,t.dtick=Math.ceil(Math.max(e,1))):Dt(t)?(t.tick0=0,n=1,t.dtick=dt(e,n,pt)):(t.tick0=0,n=a(10),t.dtick=dt(e,n,st));if(0===t.dtick&&(t.dtick=1),!i(t.dtick)&&\"string\"!=typeof t.dtick){var h=t.dtick;throw t.dtick=1,\"ax.dtick error: \"+String(h)}},q.tickIncrement=function(t,e,r,a){var o=r?-1:1;if(i(e))return s.increment(t,o*e);var l=e.charAt(0),u=o*Number(e.substr(1));if(\"M\"===l)return s.incrementMonth(t,u,a);if(\"L\"===l)return Math.log(Math.pow(10,t)+u)/Math.LN10;if(\"D\"===l){var c=\"D2\"===e?ht:ft,f=t+.01*o,h=s.roundUp(s.mod(f,1),c,r);return Math.floor(f)+Math.log(n.round(Math.pow(10,h),1))/Math.LN10}throw\"unrecognized dtick 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r=t._categories[Math.round(e.x)];void 0===r&&(r=\"\"),e.text=String(r)}(t,o):\"multicategory\"===c?function(t,e,r){var n=Math.round(e.x),i=t._categories[n]||[],a=void 0===i[1]?\"\":String(i[1]),o=void 0===i[0]?\"\":String(i[0]);r?e.text=o+\" - \"+a:(e.text=a,e.text2=o)}(t,o,r):Dt(t)?function(t,e,r,n,i){if(\"radians\"!==t.thetaunit||r)e.text=bt(e.x,t,i,n);else{var a=e.x/180;if(0===a)e.text=\"0\";else{var o=function(t){function e(t,e){return Math.abs(t-e)<=1e-6}var r=function(t){for(var r=1;!e(Math.round(t*r)/r,t);)r*=10;return r}(t),n=t*r,i=Math.abs(function t(r,n){return e(n,0)?r:t(n,r%n)}(n,r));return[Math.round(n/i),Math.round(r/i)]}(a);if(o[1]>=100)e.text=bt(s.deg2rad(e.x),t,i,n);else{var l=e.x<0;1===o[1]?1===o[0]?e.text=\"π\":e.text=o[0]+\"π\":e.text=[\"\",o[0],\"\",\"⁄\",\"\",o[1],\"\",\"π\"].join(\"\"),l&&(e.text=P+e.text)}}}}(t,o,r,u,v):function(t,e,r,n,i){\"never\"===i?i=\"\":\"all\"===t.showexponent&&Math.abs(e.x/t.dtick)<1e-6&&(i=\"hide\"),e.text=bt(e.x,t,i,n)}(t,o,0,u,v),n||(t.tickprefix&&!d(t.showtickprefix)&&(o.text=t.tickprefix+o.text),t.ticksuffix&&!d(t.showticksuffix)&&(o.text+=t.ticksuffix)),t.labelalias&&t.labelalias.hasOwnProperty(o.text)){var g=t.labelalias[o.text];\"string\"==typeof g&&(o.text=g)}if(\"boundaries\"===t.tickson||t.showdividers){var y=function(e){var r=t.l2p(e);return r>=0&&r<=t._length?e:null};o.xbnd=[y(o.x-.5),y(o.x+t.dtick-.5)]}return o},q.hoverLabelText=function(t,e,r){r&&(t=s.extendFlat({},t,{hoverformat:r}));var n=Array.isArray(e)?e[0]:e,i=Array.isArray(e)?e[1]:void 0;if(void 0!==i&&i!==n)return q.hoverLabelText(t,n,r)+\" - \"+q.hoverLabelText(t,i,r);var a=\"log\"===t.type&&n<=0,o=q.tickText(t,t.c2l(a?-n:n),\"hover\").text;return 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r=[],n={},i=0;i1&&r=i.min&&t=0,a=c(t,e[1])<=0;return(r||i)&&(n||a)}if(t.tickformatstops&&t.tickformatstops.length>0)switch(t.type){case\"date\":case\"linear\":for(e=0;e=o(i)))){r=n;break}break;case\"log\":for(e=0;e=0&&i.unshift(i.splice(n,1).shift())}}));var o={false:{left:0,right:0}};return s.syncOrAsync(i.map((function(e){return function(){if(e){var n=q.getFromId(t,e);r||(r={}),r.axShifts=o,r.overlayingShiftedAx=a;var i=q.drawOne(t,n,r);return n._shiftPusher&&Bt(n,n._fullDepth||0,o,!0),n._r=n.range.slice(),n._rl=s.simpleMap(n._r,n.r2l),i}}})))},q.drawOne=function(t,e,r){var n,i,l,u=(r=r||{}).axShifts||{},p=r.overlayingShiftedAx||[];e.setScale();var d=t._fullLayout,v=e._id,g=v.charAt(0),y=q.counterLetter(v),m=d._plots[e._mainSubplot];if(m){if(e._shiftPusher=e.autoshift||-1!==p.indexOf(e._id)||-1!==p.indexOf(e.overlaying),e._shiftPusher&\"free\"===e.anchor){var x=e.linewidth/2||0;\"inside\"===e.ticks&&(x+=e.ticklen),Bt(e,x,u,!0),Bt(e,e.shift||0,u,!1)}!0===r.skipTitle&&void 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_=r.bottom-(e._offset+e._length);_>0&&(n.yb=0,n.b=_);var w=e._offset-r.top;w>0&&(n.yt=1,n.t=w)}n[y]=\"free\"===e.anchor?e.position:e._anchorAxis.domain[v[0]],e.title.text!==d._dfltTitle[g]&&(n[l]+=At(e)+(e.title.standoff||0)),e.mirror&&\"free\"!==e.anchor&&((i={x:0,y:0,r:0,l:0,t:0,b:0})[u]=e.linewidth,e.mirror&&!0!==e.mirror&&(i[u]+=f),!0===e.mirror||\"ticks\"===e.mirror?i[y]=e._anchorAxis.domain[v[1]]:\"all\"!==e.mirror&&\"allticks\"!==e.mirror||(i[y]=[e._counterDomainMin,e._counterDomainMax][v[1]]))}lt&&(s=o.getComponentMethod(\"rangeslider\",\"autoMarginOpts\")(t,e)),\"string\"==typeof e.automargin&&(_t(n,e.automargin),_t(i,e.automargin)),a.autoMargin(t,Et(e),n),a.autoMargin(t,Lt(e),i),a.autoMargin(t,Ct(e),s)})),s.syncOrAsync(ot)}}function ut(t){var r=v+(t||\"tick\");return M[r]||(M[r]=function(t,e){var r,n,i,a;return t._selections[e].size()?(r=1/0,n=-1/0,i=1/0,a=-1/0,t._selections[e].each((function(){var t=St(this),e=h.bBox(t.node().parentNode);r=Math.min(r,e.top),n=Math.max(n,e.bottom),i=Math.min(i,e.left),a=Math.max(a,e.right)}))):(r=0,n=0,i=0,a=0),{top:r,bottom:n,left:i,right:a,height:n-r,width:a-i}}(e,r)),M[r]}},q.getTickSigns=function(t,e){var r=t._id.charAt(0),n={x:\"top\",y:\"right\"}[r],i=t.side===n?1:-1,a=[-1,1,i,-i];return\"inside\"!==(e?(t.minor||{}).ticks:t.ticks)==(\"x\"===r)&&(a=a.map((function(t){return-t}))),t.side&&a.push({l:-1,t:-1,r:1,b:1}[t.side.charAt(0)]),a},q.makeTransTickFn=function(t){return\"x\"===t._id.charAt(0)?function(e){return l(t._offset+t.l2p(e.x),0)}:function(e){return l(0,t._offset+t.l2p(e.x))}},q.makeTransTickLabelFn=function(t){var e=function(t){var e=t.ticklabelposition||\"\",r=function(t){return-1!==e.indexOf(t)},n=r(\"top\"),i=r(\"left\"),a=r(\"right\"),o=r(\"bottom\"),s=r(\"inside\"),l=o||i||n||a;if(!l&&!s)return[0,0];var 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r?[r[0]-t.xaxis._offset,r[1]-t.yaxis._offset]:[null,null]},t.xaxis={_id:\"x\",c2p:function(e){return t.project(e)[0]}},t.yaxis={_id:\"y\",c2p:function(e){return t.project(e)[1]}},t.mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},v.setConvert(t.mockAxis,r)},S.saveViewInitial=function(t){var e,r=t.center||{},n=t.projection,i=n.rotation||{};this.viewInitial={fitbounds:t.fitbounds,\"projection.scale\":n.scale},e=t._isScoped?{\"center.lon\":r.lon,\"center.lat\":r.lat}:t._isClipped?{\"projection.rotation.lon\":i.lon,\"projection.rotation.lat\":i.lat}:{\"center.lon\":r.lon,\"center.lat\":r.lat,\"projection.rotation.lon\":i.lon},u.extendFlat(this.viewInitial,e)},S.render=function(t){this._hasMarkerAngles&&t?this.plot(this._geoCalcData,this._fullLayout,[],!0):this._render()},S._render=function(){var t,e=this.projection,r=e.getPath();function n(t){var r=e(t.lonlat);return r?c(r[0],r[1]):null}function i(t){return e.isLonLatOverEdges(t.lonlat)?\"none\":null}for(t in 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r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},t.exports=function(t){var e=new a;return e.merge(t),e}},96085:function(t,e,r){\"use strict\";t.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],u=0;u<3;++u){var c=s[a[u]];if(c._length=(r[u].hi-r[u].lo)*r[u].pixelsPerDataUnit/t.dataScale[u],Math.abs(c._length)===1/0||isNaN(c._length))l[u]=[];else{c._input_range=c.range.slice(),c.range[0]=r[u].lo/t.dataScale[u],c.range[1]=r[u].hi/t.dataScale[u],c._m=1/(t.dataScale[u]*r[u].pixelsPerDataUnit),c.range[0]===c.range[1]&&(c.range[0]-=1,c.range[1]+=1);var f=c.tickmode;if(\"auto\"===c.tickmode){c.tickmode=\"linear\";var h=c.nticks||i.constrain(c._length/40,4,9);n.autoTicks(c,Math.abs(c.range[1]-c.range[0])/h)}for(var p=n.calcTicks(c,{msUTC:!0}),d=0;d/g,\" 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Context lost.\")};requestAnimationFrame(e)};var M=[\"xaxis\",\"yaxis\",\"zaxis\"];function S(t,e,r){for(var n=t.fullSceneLayout,i=0;i<3;i++){var a=M[i],o=a.charAt(0),s=n[a],l=e[o],u=e[o+\"calendar\"],c=e[\"_\"+o+\"length\"];if(f.isArrayOrTypedArray(l))for(var h,p=0;p<(c||l.length);p++)if(f.isArrayOrTypedArray(l[p]))for(var d=0;dy[1][o])y[0][o]=-1,y[1][o]=1;else{var O=y[1][o]-y[0][o];y[0][o]-=O/32,y[1][o]+=O/32}if(b=[y[0][o],y[1][o]],b=_(b,l),y[0][o]=b[0],y[1][o]=b[1],l.isReversed()){var I=y[0][o];y[0][o]=y[1][o],y[1][o]=I}}else b=l.range,y[0][o]=l.r2l(b[0]),y[1][o]=l.r2l(b[1]);y[0][o]===y[1][o]&&(y[0][o]-=1,y[1][o]+=1),m[o]=y[1][o]-y[0][o],l.range=[y[0][o],y[1][o]],l.limitRange(),n.glplot.setBounds(o,{min:l.range[0]*p[o],max:l.range[1]*p[o]})}var D=c.aspectmode;if(\"cube\"===D)g=[1,1,1];else if(\"manual\"===D){var z=c.aspectratio;g=[z.x,z.y,z.z]}else{if(\"auto\"!==D&&\"data\"!==D)throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");var R=[1,1,1];for(o=0;o<3;++o){var F=x[u=(l=c[M[o]]).type];R[o]=Math.pow(F.acc,1/F.count)/p[o]}g=\"data\"===D||Math.max.apply(null,R)/Math.min.apply(null,R)<=4?R:[1,1,1]}c.aspectratio.x=f.aspectratio.x=g[0],c.aspectratio.y=f.aspectratio.y=g[1],c.aspectratio.z=f.aspectratio.z=g[2],n.glplot.setAspectratio(c.aspectratio),n.viewInitial.aspectratio||(n.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z}),n.viewInitial.aspectmode||(n.viewInitial.aspectmode=c.aspectmode);var B=c.domain||null,N=e._size||null;if(B&&N){var j=n.container.style;j.position=\"absolute\",j.left=N.l+B.x[0]*N.w+\"px\",j.top=N.t+(1-B.y[1])*N.h+\"px\",j.width=N.w*(B.x[1]-B.x[0])+\"px\",j.height=N.h*(B.y[1]-B.y[0])+\"px\"}n.glplot.redraw()}},k.destroy=function(){var t=this;t.glplot&&(t.camera.mouseListener.enabled=!1,t.container.removeEventListener(\"wheel\",t.camera.wheelListener),t.camera=null,t.glplot.dispose(),t.container.parentNode.removeChild(t.container),t.glplot=null)},k.getCamera=function(){var t,e=this;return e.camera.view.recalcMatrix(e.camera.view.lastT()),{up:{x:(t=e.camera).up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?\"orthographic\":\"perspective\"}}},k.setViewport=function(t){var e,r=this,n=t.camera;r.camera.lookAt.apply(this,[[(e=n).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),r.glplot.setAspectratio(t.aspectratio),\"orthographic\"===n.projection.type!==r.camera._ortho&&(r.glplot.redraw(),r.glplot.clearRGBA(),r.glplot.dispose(),r.initializeGLPlot())},k.isCameraChanged=function(t){var e=this.getCamera(),r=f.nestedProperty(t,this.id+\".camera\").get();function n(t,e,r,n){var i=[\"up\",\"center\",\"eye\"],a=[\"x\",\"y\",\"z\"];return e[i[r]]&&t[i[r]][a[n]]===e[i[r]][a[n]]}var i=!1;if(void 0===r)i=!0;else{for(var a=0;a<3;a++)for(var o=0;o<3;o++)if(!n(e,r,a,o)){i=!0;break}(!r.projection||e.projection&&e.projection.type!==r.projection.type)&&(i=!0)}return i},k.isAspectChanged=function(t){var e=this.glplot.getAspectratio(),r=f.nestedProperty(t,this.id+\".aspectratio\").get();return void 0===r||r.x!==e.x||r.y!==e.y||r.z!==e.z},k.saveLayout=function(t){var e,r,n,i,a,o,s=this,l=s.fullLayout,u=s.isCameraChanged(t),h=s.isAspectChanged(t),p=u||h;if(p){var d={};u&&(e=s.getCamera(),n=(r=f.nestedProperty(t,s.id+\".camera\")).get(),d[s.id+\".camera\"]=n),h&&(i=s.glplot.getAspectratio(),o=(a=f.nestedProperty(t,s.id+\".aspectratio\")).get(),d[s.id+\".aspectratio\"]=o),c.call(\"_storeDirectGUIEdit\",t,l._preGUI,d),u&&(r.set(e),f.nestedProperty(l,s.id+\".camera\").set(e)),h&&(a.set(i),f.nestedProperty(l,s.id+\".aspectratio\").set(i),s.glplot.redraw())}return 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l,u=s.getContext(\"2d\",{willReadFrequently:!0}),c=u.createImageData(i,a);switch(c.data.set(o),u.putImageData(c,0,0),t){case\"jpeg\":l=s.toDataURL(\"image/jpeg\");break;case\"webp\":l=s.toDataURL(\"image/webp\");break;default:l=s.toDataURL(\"image/png\")}return e.staticMode&&e.container.removeChild(n),l},k.setConvert=function(){for(var t=0;t<3;t++){var e=this.fullSceneLayout[M[t]];p.setConvert(e,this.fullLayout),e.setScale=f.noop}},k.make4thDimension=function(){var t=this,e=t.graphDiv._fullLayout;t._mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},p.setConvert(t._mockAxis,e)},t.exports=T},90060:function(t){\"use strict\";t.exports=function(t,e,r,n){n=n||t.length;for(var i=new Array(n),a=0;aOpenStreetMap contributors',o=['© Carto',a].join(\" \"),s=['Map tiles by Stamen Design','under CC BY 3.0',\"|\",'Data by OpenStreetMap contributors','under ODbL'].join(\" 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T=m.split(\"|\").join(\"
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title\"),attributes:{x:b,y:_,\"text-anchor\":\"middle\"},transform:{rotate:-v}})}},N.updateAngularAxis=function(t,e){var r=this,n=r.gd,i=r.layers,a=r.radius,c=r.innerRadius,f=r.cx,p=r.cy,d=r.getAngular(e),v=r.angularAxis,g=r.isSmith;g||(r.fillViewInitialKey(\"angularaxis.rotation\",d.rotation),v.setGeometry(),v.setScale());var y=g?function(t){var e=I(r,C([0,t.x]));return Math.atan2(e[0]-f,e[1]-p)-Math.PI/2}:function(t){return v.t2g(t.x)};\"linear\"===v.type&&\"radians\"===v.thetaunit&&(v.tick0=F(v.tick0),v.dtick=F(v.dtick));var m=function(t){return l(f+a*Math.cos(t),p-a*Math.sin(t))},x=g?function(t){var e=I(r,C([0,t.x]));return l(e[0],e[1])}:function(t){return m(y(t))},b=g?function(t){var e=I(r,C([0,t.x])),n=Math.atan2(e[0]-f,e[1]-p)-Math.PI/2;return l(e[0],e[1])+s(-F(n))}:function(t){var e=y(t);return m(e)+s(-F(e))},_=g?function(t){return P(r,t.x,0,1/0)}:function(t){var e=y(t),r=Math.cos(e),n=Math.sin(e);return\"M\"+[f+c*r,p-c*n]+\"L\"+[f+a*r,p-a*n]},w=h.makeLabelFns(v,0).labelStandoff,T={xFn:function(t){var e=y(t);return Math.cos(e)*w},yFn:function(t){var e=y(t),r=Math.sin(e)>0?.2:1;return-Math.sin(e)*(w+t.fontSize*r)+Math.abs(Math.cos(e))*(t.fontSize*M)},anchorFn:function(t){var e=y(t),r=Math.cos(e);return Math.abs(r)<.1?\"middle\":r>0?\"start\":\"end\"},heightFn:function(t,e,r){var n=y(t);return-.5*(1+Math.sin(n))*r}},k=j(d);r.angularTickLayout!==k&&(i[\"angular-axis\"].selectAll(\".\"+v._id+\"tick\").remove(),r.angularTickLayout=k);var A,S=g?[1/0].concat(v.tickvals||[]).map((function(t){return h.tickText(v,t,!0,!1)})):h.calcTicks(v);if(g&&(S[0].text=\"∞\",S[0].fontSize*=1.75),\"linear\"===e.gridshape?(A=S.map(y),o.angleDelta(A[0],A[1])<0&&(A=A.slice().reverse())):A=null,r.vangles=A,\"category\"===v.type&&(S=S.filter((function(t){return o.isAngleInsideSector(y(t),r.sectorInRad)}))),v.visible){var E=\"inside\"===v.ticks?-1:1,L=(v.linewidth||1)/2;h.drawTicks(n,v,{vals:S,layer:i[\"angular-axis\"],path:\"M\"+E*L+\",0h\"+E*v.ticklen,transFn:b,crisp:!1}),h.drawGrid(n,v,{vals:S,layer:i[\"angular-grid\"],path:_,transFn:o.noop,crisp:!1}),h.drawLabels(n,v,{vals:S,layer:i[\"angular-axis\"],repositionOnUpdate:!0,transFn:x,labelFns:T})}V(i[\"angular-line\"].select(\"path\"),d.showline,{d:r.pathSubplot(),transform:l(f,p)}).attr(\"stroke-width\",d.linewidth).call(u.stroke,d.linecolor)},N.updateFx=function(t,e){this.gd._context.staticPlot||(!this.isSmith&&(this.updateAngularDrag(t),this.updateRadialDrag(t,e,0),this.updateRadialDrag(t,e,1)),this.updateHoverAndMainDrag(t))},N.updateHoverAndMainDrag=function(t){var e,r,s=this,u=s.isSmith,c=s.gd,f=s.layers,h=t._zoomlayer,p=S.MINZOOM,d=S.OFFEDGE,v=s.radius,x=s.innerRadius,T=s.cx,k=s.cy,A=s.cxx,M=s.cyy,L=s.sectorInRad,C=s.vangles,P=s.radialAxis,O=E.clampTiny,I=E.findXYatLength,D=E.findEnclosingVertexAngles,z=S.cornerHalfWidth,R=S.cornerLen/2,F=g.makeDragger(f,\"path\",\"maindrag\",!1===t.dragmode?\"none\":\"crosshair\");n.select(F).attr(\"d\",s.pathSubplot()).attr(\"transform\",l(T,k)),F.onmousemove=function(t){m.hover(c,t,s.id),c._fullLayout._lasthover=F,c._fullLayout._hoversubplot=s.id},F.onmouseout=function(t){c._dragging||y.unhover(c,t)};var B,N,j,U,V,H,q,G,Z,Y={element:F,gd:c,subplot:s.id,plotinfo:{id:s.id,xaxis:s.xaxis,yaxis:s.yaxis},xaxes:[s.xaxis],yaxes:[s.yaxis]};function W(t,e){return Math.sqrt(t*t+e*e)}function X(t,e){return W(t-A,e-M)}function J(t,e){return Math.atan2(M-e,t-A)}function K(t,e){return[t*Math.cos(e),t*Math.sin(-e)]}function $(t,e){if(0===t)return s.pathSector(2*z);var r=R/t,n=e-r,i=e+r,a=Math.max(0,Math.min(t,v)),o=a-z,l=a+z;return\"M\"+K(o,n)+\"A\"+[o,o]+\" 0,0,0 \"+K(o,i)+\"L\"+K(l,i)+\"A\"+[l,l]+\" 0,0,1 \"+K(l,n)+\"Z\"}function Q(t,e,r){if(0===t)return s.pathSector(2*z);var n,i,a=K(t,e),o=K(t,r),l=O((a[0]+o[0])/2),u=O((a[1]+o[1])/2);if(l&&u){var c=u/l,f=-1/c,h=I(z,c,l,u);n=I(R,f,h[0][0],h[0][1]),i=I(R,f,h[1][0],h[1][1])}else{var p,d;u?(p=R,d=z):(p=z,d=R),n=[[l-p,u-d],[l+p,u-d]],i=[[l-p,u+d],[l+p,u+d]]}return\"M\"+n.join(\"L\")+\"L\"+i.reverse().join(\"L\")+\"Z\"}function tt(t,e){return e=Math.max(Math.min(e,v),x),tp?(t-1&&1===t&&_(e,c,[s.xaxis],[s.yaxis],s.id,Y),r.indexOf(\"event\")>-1&&m.click(c,e,s.id)}Y.prepFn=function(t,n,a){var l=c._fullLayout.dragmode,f=F.getBoundingClientRect();c._fullLayout._calcInverseTransform(c);var p=c._fullLayout._invTransform;e=c._fullLayout._invScaleX,r=c._fullLayout._invScaleY;var d=o.apply3DTransform(p)(n-f.left,a-f.top);if(B=d[0],N=d[1],C){var y=E.findPolygonOffset(v,L[0],L[1],C);B+=A+y[0],N+=M+y[1]}switch(l){case\"zoom\":Y.clickFn=st,u||(Y.moveFn=C?it:rt,Y.doneFn=at,function(){j=null,U=null,V=s.pathSubplot(),H=!1;var t=c._fullLayout[s.id];q=i(t.bgcolor).getLuminance(),(G=g.makeZoombox(h,q,T,k,V)).attr(\"fill-rule\",\"evenodd\"),Z=g.makeCorners(h,T,k),w(c)}());break;case\"select\":case\"lasso\":b(t,n,a,Y,l)}},y.init(Y)},N.updateRadialDrag=function(t,e,r){var i=this,u=i.gd,c=i.layers,f=i.radius,h=i.innerRadius,p=i.cx,d=i.cy,v=i.radialAxis,m=S.radialDragBoxSize,x=m/2;if(v.visible){var b,_,T,M=R(i.radialAxisAngle),E=v._rl,L=E[0],C=E[1],P=E[r],O=.75*(E[1]-E[0])/(1-i.getHole(e))/f;r?(b=p+(f+x)*Math.cos(M),_=d-(f+x)*Math.sin(M),T=\"radialdrag\"):(b=p+(h-x)*Math.cos(M),_=d-(h-x)*Math.sin(M),T=\"radialdrag-inner\");var I,D,z,B=g.makeRectDragger(c,T,\"crosshair\",-x,-x,m,m),N={element:B,gd:u};!1===t.dragmode&&(N.dragmode=!1),V(n.select(B),v.visible&&h0==(r?z>L:zn?function(t){return t<=0}:function(t){return t>=0};t.c2g=function(r){var n=t.c2l(r)-e;return(s(n)?n:0)+o},t.g2c=function(r){return t.l2c(r+e-o)},t.g2p=function(t){return t*a},t.c2p=function(e){return t.g2p(t.c2g(e))}}}(t,e);break;case\"angularaxis\":!function(t,e){var r=t.type;if(\"linear\"===r){var i=t.d2c,s=t.c2d;t.d2c=function(t,e){return function(t,e){return\"degrees\"===e?a(t):t}(i(t),e)},t.c2d=function(t,e){return s(function(t,e){return\"degrees\"===e?o(t):t}(t,e))}}t.makeCalcdata=function(e,i){var a,o,s=e[i],l=e._length,u=function(r){return t.d2c(r,e.thetaunit)};if(s){if(n.isTypedArray(s)&&\"linear\"===r){if(l===s.length)return s;if(s.subarray)return s.subarray(0,l)}for(a=new Array(l),o=0;o0?1:0}function r(t){var e=t[0],r=t[1];if(!isFinite(e)||!isFinite(r))return[1,0];var n=(e+1)*(e+1)+r*r;return[(e*e+r*r-1)/n,2*r/n]}function n(t,e){var r=e[0],n=e[1];return[r*t.radius+t.cx,-n*t.radius+t.cy]}function i(t,e){return e*t.radius}t.exports={smith:r,reactanceArc:function(t,e,a,o){var s=n(t,r([a,e])),l=s[0],u=s[1],c=n(t,r([o,e])),f=c[0],h=c[1];if(0===e)return[\"M\"+l+\",\"+u,\"L\"+f+\",\"+h].join(\" \");var p=i(t,1/Math.abs(e));return[\"M\"+l+\",\"+u,\"A\"+p+\",\"+p+\" 0 0,\"+(e<0?1:0)+\" \"+f+\",\"+h].join(\" \")},resistanceArc:function(t,a,o,s){var l=i(t,1/(a+1)),u=n(t,r([a,o])),c=u[0],f=u[1],h=n(t,r([a,s])),p=h[0],d=h[1];if(e(o)!==e(s)){var v=n(t,r([a,0]));return[\"M\"+c+\",\"+f,\"A\"+l+\",\"+l+\" 0 0,\"+(00){for(var n=[],i=0;i=c&&(h.min=0,d.min=0,g.min=0,t.aaxis&&delete t.aaxis.min,t.baxis&&delete t.baxis.min,t.caxis&&delete t.caxis.min)}function v(t,e,r,n){var i=h[e._name];function o(r,n){return a.coerce(t,e,i,r,n)}o(\"uirevision\",n.uirevision),e.type=\"linear\";var p=o(\"color\"),d=p!==i.color.dflt?p:r.font.color,v=e._name.charAt(0).toUpperCase(),g=\"Component 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n=r(39898),i=r(84267),a=r(73972),o=r(71828),s=o.strTranslate,l=o._,u=r(7901),c=r(91424),f=r(21994),h=r(1426).extendFlat,p=r(74875),d=r(89298),v=r(28569),g=r(30211),y=r(64505),m=y.freeMode,x=y.rectMode,b=r(92998),_=r(47322).prepSelect,w=r(47322).selectOnClick,T=r(47322).clearOutline,k=r(47322).clearSelectionsCache,A=r(85555);function M(t,e){this.id=t.id,this.graphDiv=t.graphDiv,this.init(e),this.makeFramework(e),this.aTickLayout=null,this.bTickLayout=null,this.cTickLayout=null}t.exports=M;var S=M.prototype;S.init=function(t){this.container=t._ternarylayer,this.defs=t._defs,this.layoutId=t._uid,this.traceHash={},this.layers={}},S.plot=function(t,e){var r=this,n=e[r.id],i=e._size;r._hasClipOnAxisFalse=!1;for(var a=0;aE*b?i=(a=b)*E:a=(i=x)/E,o=y*i/x,l=m*a/b,r=e.l+e.w*v-i/2,n=e.t+e.h*(1-g)-a/2,p.x0=r,p.y0=n,p.w=i,p.h=a,p.sum=_,p.xaxis={type:\"linear\",range:[w+2*k-_,_-w-2*T],domain:[v-o/2,v+o/2],_id:\"x\"},f(p.xaxis,p.graphDiv._fullLayout),p.xaxis.setScale(),p.xaxis.isPtWithinRange=function(t){return t.a>=p.aaxis.range[0]&&t.a<=p.aaxis.range[1]&&t.b>=p.baxis.range[1]&&t.b<=p.baxis.range[0]&&t.c>=p.caxis.range[1]&&t.c<=p.caxis.range[0]},p.yaxis={type:\"linear\",range:[w,_-T-k],domain:[g-l/2,g+l/2],_id:\"y\"},f(p.yaxis,p.graphDiv._fullLayout),p.yaxis.setScale(),p.yaxis.isPtWithinRange=function(){return!0};var A=p.yaxis.domain[0],M=p.aaxis=h({},t.aaxis,{range:[w,_-T-k],side:\"left\",tickangle:(+t.aaxis.tickangle||0)-30,domain:[A,A+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(M,p.graphDiv._fullLayout),M.setScale();var S=p.baxis=h({},t.baxis,{range:[_-w-k,T],side:\"bottom\",domain:p.xaxis.domain,anchor:\"free\",position:0,_id:\"x\",_length:i});f(S,p.graphDiv._fullLayout),S.setScale();var L=p.caxis=h({},t.caxis,{range:[_-w-T,k],side:\"right\",tickangle:(+t.caxis.tickangle||0)+30,domain:[A,A+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(L,p.graphDiv._fullLayout),L.setScale();var C=\"M\"+r+\",\"+(n+a)+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDef.select(\"path\").attr(\"d\",C),p.layers.plotbg.select(\"path\").attr(\"d\",C);var P=\"M0,\"+a+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDefRelative.select(\"path\").attr(\"d\",P);var O=s(r,n);p.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",O),p.clipDefRelative.select(\"path\").attr(\"transform\",null);var I=s(r-S._offset,n+a);p.layers.baxis.attr(\"transform\",I),p.layers.bgrid.attr(\"transform\",I);var D=s(r+i/2,n)+\"rotate(30)\"+s(0,-M._offset);p.layers.aaxis.attr(\"transform\",D),p.layers.agrid.attr(\"transform\",D);var z=s(r+i/2,n)+\"rotate(-30)\"+s(0,-L._offset);p.layers.caxis.attr(\"transform\",z),p.layers.cgrid.attr(\"transform\",z),p.drawAxes(!0),p.layers.aline.select(\"path\").attr(\"d\",M.showline?\"M\"+r+\",\"+(n+a)+\"l\"+i/2+\",-\"+a:\"M0,0\").call(u.stroke,M.linecolor||\"#000\").style(\"stroke-width\",(M.linewidth||0)+\"px\"),p.layers.bline.select(\"path\").attr(\"d\",S.showline?\"M\"+r+\",\"+(n+a)+\"h\"+i:\"M0,0\").call(u.stroke,S.linecolor||\"#000\").style(\"stroke-width\",(S.linewidth||0)+\"px\"),p.layers.cline.select(\"path\").attr(\"d\",L.showline?\"M\"+(r+i/2)+\",\"+n+\"l\"+i/2+\",\"+a:\"M0,0\").call(u.stroke,L.linecolor||\"#000\").style(\"stroke-width\",(L.linewidth||0)+\"px\"),p.graphDiv._context.staticPlot||p.initInteractions(),c.setClipUrl(p.layers.frontplot,p._hasClipOnAxisFalse?null:p.clipId,p.graphDiv)},S.drawAxes=function(t){var e=this,r=e.graphDiv,n=e.id.substr(7)+\"title\",i=e.layers,a=e.aaxis,o=e.baxis,s=e.caxis;if(e.drawAx(a),e.drawAx(o),e.drawAx(s),t){var u=Math.max(a.showticklabels?a.tickfont.size/2:0,(s.showticklabels?.75*s.tickfont.size:0)+(\"outside\"===s.ticks?.87*s.ticklen:0)),c=(o.showticklabels?o.tickfont.size:0)+(\"outside\"===o.ticks?o.ticklen:0)+3;i[\"a-title\"]=b.draw(r,\"a\"+n,{propContainer:a,propName:e.id+\".aaxis.title\",placeholder:l(r,\"Click to enter Component A title\"),attributes:{x:e.x0+e.w/2,y:e.y0-a.title.font.size/3-u,\"text-anchor\":\"middle\"}}),i[\"b-title\"]=b.draw(r,\"b\"+n,{propContainer:o,propName:e.id+\".baxis.title\",placeholder:l(r,\"Click to enter Component B title\"),attributes:{x:e.x0-c,y:e.y0+e.h+.83*o.title.font.size+c,\"text-anchor\":\"middle\"}}),i[\"c-title\"]=b.draw(r,\"c\"+n,{propContainer:s,propName:e.id+\".caxis.title\",placeholder:l(r,\"Click to enter Component C title\"),attributes:{x:e.x0+e.w+c,y:e.y0+e.h+.83*s.title.font.size+c,\"text-anchor\":\"middle\"}})}},S.drawAx=function(t){var 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n=r(50693),i=r(12663).axisHoverFormat,a=r(5386).fF,o=r(54532),s=r(9012),l=r(1426).extendFlat;t.exports=l({x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},i:{valType:\"data_array\",editType:\"calc\"},j:{valType:\"data_array\",editType:\"calc\"},k:{valType:\"data_array\",editType:\"calc\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:a({editType:\"calc\"}),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),delaunayaxis:{valType:\"enumerated\",values:[\"x\",\"y\",\"z\"],dflt:\"z\",editType:\"calc\"},alphahull:{valType:\"number\",dflt:-1,editType:\"calc\"},intensity:{valType:\"data_array\",editType:\"calc\"},intensitymode:{valType:\"enumerated\",values:[\"vertex\",\"cell\"],dflt:\"vertex\",editType:\"calc\"},color:{valType:\"color\",editType:\"calc\"},vertexcolor:{valType:\"data_array\",editType:\"calc\"},facecolor:{valType:\"data_array\",editType:\"calc\"},transforms:void 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n=r(9012),i=r(27670).Y,a=r(41940),o=r(22399),s=r(5386).fF,l=r(5386).si,u=r(1426).extendFlat,c=r(79952).u,f=a({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});t.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:o.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},pattern:c,editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:u({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:s({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),texttemplate:l({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:u({},f,{}),insidetextorientation:{valType:\"enumerated\",values:[\"horizontal\",\"radial\",\"tangential\",\"auto\"],dflt:\"auto\",editType:\"plot\"},insidetextfont:u({},f,{}),outsidetextfont:u({},f,{}),automargin:{valType:\"boolean\",dflt:!1,editType:\"plot\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:u({},f,{}),position:{valType:\"enumerated\",values:[\"top 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n=r(74875);e.name=\"pie\",e.plot=function(t,r,i,a){n.plotBasePlot(e.name,t,r,i,a)},e.clean=function(t,r,i,a){n.cleanBasePlot(e.name,t,r,i,a)}},32354:function(t,e,r){\"use strict\";var n=r(92770),i=r(84267),a=r(7901),o={};function s(t){return function(e,r){return!!e&&!!(e=i(e)).isValid()&&(e=a.addOpacity(e,e.getAlpha()),t[r]||(t[r]=e),e)}}function l(t,e){var r,n=JSON.stringify(t),a=e[n];if(!a){for(a=t.slice(),r=0;r=0})),(\"funnelarea\"===e.type?y:e.sort)&&a.sort((function(t,e){return e.v-t.v})),a[0]&&(a[0].vTotal=g),a},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r=\"pie\");var n=t._fullLayout,i=t.calcdata,a=n[r+\"colorway\"],s=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(a=l(a,o));for(var u=0,c=0;c0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:a,len:o}}function c(t,e,r,n,i){n(\"marker.line.width\")&&n(\"marker.line.color\",i?void 0:r.paper_bgcolor);var a=n(\"marker.colors\");l(n,\"marker.pattern\",a),t.marker&&!e.marker.pattern.fgcolor&&(e.marker.pattern.fgcolor=t.marker.colors),e.marker.pattern.bgcolor||(e.marker.pattern.bgcolor=r.paper_bgcolor)}t.exports={handleLabelsAndValues:u,handleMarkerDefaults:c,supplyDefaults:function(t,e,r,n){function l(r,n){return i.coerce(t,e,a,r,n)}var f=u(l(\"labels\"),l(\"values\")),h=f.len;if(e._hasLabels=f.hasLabels,e._hasValues=f.hasValues,!e._hasLabels&&e._hasValues&&(l(\"label0\"),l(\"dlabel\")),h){e._length=h,c(t,e,n,l,!0),l(\"scalegroup\");var p,d=l(\"text\"),v=l(\"texttemplate\");if(v||(p=l(\"textinfo\",Array.isArray(d)?\"text+percent\":\"percent\")),l(\"hovertext\"),l(\"hovertemplate\"),v||p&&\"none\"!==p){var g=l(\"textposition\");s(t,e,n,l,g,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(g)||\"auto\"===g||\"outside\"===g)&&l(\"automargin\"),(\"inside\"===g||\"auto\"===g||Array.isArray(g))&&l(\"insidetextorientation\")}o(e,n,l);var y=l(\"hole\");if(l(\"title.text\")){var m=l(\"title.position\",y?\"middle center\":\"top center\");y||\"middle center\"!==m||(e.title.position=\"top center\"),i.coerceFont(l,\"title.font\",n.font)}l(\"sort\"),l(\"direction\"),l(\"rotation\"),l(\"pull\")}else e.visible=!1}}},20007:function(t,e,r){\"use strict\";var n=r(23469).appendArrayMultiPointValues;t.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,bbox:t.bbox,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),\"funnelarea\"===e.type&&(delete r.v,delete r.i),r}},22209:function(t,e,r){\"use strict\";var n=r(91424),i=r(7901);t.exports=function(t,e,r,a){var o=r.marker.pattern;o&&o.shape?n.pointStyle(t,r,a,e):i.fill(t,e.color)}},53581:function(t,e,r){\"use strict\";var n=r(71828);function i(t){return-1!==t.indexOf(\"e\")?t.replace(/[.]?0+e/,\"e\"):-1!==t.indexOf(\".\")?t.replace(/[.]?0+$/,\"\"):t}e.formatPiePercent=function(t,e){var r=i((100*t).toPrecision(3));return n.numSeparate(r,e)+\"%\"},e.formatPieValue=function(t,e){var r=i(t.toPrecision(10));return n.numSeparate(r,e)},e.getFirstFilled=function(t,e){if(Array.isArray(t))for(var r=0;r\"),name:f.hovertemplate||-1!==h.indexOf(\"name\")?f.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:g.castOption(_.bgcolor,t.pts)||t.color,borderColor:g.castOption(_.bordercolor,t.pts),fontFamily:g.castOption(w.family,t.pts),fontSize:g.castOption(w.size,t.pts),fontColor:g.castOption(w.color,t.pts),nameLength:g.castOption(_.namelength,t.pts),textAlign:g.castOption(_.align,t.pts),hovertemplate:g.castOption(f.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[y(t,f)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e,inOut_bbox:T}),t.bbox=T[0],u._hasHoverLabel=!0}u._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[y(t,f)],event:n.event})}})),t.on(\"mouseout\",(function(t){var r=e._fullLayout,i=e._fullData[u.index],o=n.select(this).datum();u._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[y(o,i)],event:n.event}),u._hasHoverEvent=!1),u._hasHoverLabel&&(a.loneUnhover(r._hoverlayer.node()),u._hasHoverLabel=!1)})),t.on(\"click\",(function(t){var r=e._fullLayout,i=e._fullData[u.index];e._dragging||!1===r.hovermode||(e._hoverdata=[y(t,i)],a.click(e,n.event))}))}function b(t,e,r){var n=g.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=g.castOption(t._input.textfont.color,e.pts));var i=g.castOption(t.insidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,a=g.castOption(t.insidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size;return{color:n||o.contrast(e.color),family:i,size:a}}function _(t,e){for(var r,n,i=0;ie&&e>n||r=-4;g-=2)y(Math.PI*g,\"tan\");for(g=4;g>=-4;g-=2)y(Math.PI*(g+1),\"tan\")}if(f||p){for(g=4;g>=-4;g-=2)y(Math.PI*(g+1.5),\"rad\");for(g=4;g>=-4;g-=2)y(Math.PI*(g+.5),\"rad\")}}if(s||d||f){var m=Math.sqrt(t.width*t.width+t.height*t.height);if((a={scale:i*n*2/m,rCenter:1-i,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,a.scale>=1)return a;v.push(a)}(d||p)&&((a=T(t,n,o,l,u)).textPosAngle=(e.startangle+e.stopangle)/2,v.push(a)),(d||h)&&((a=k(t,n,o,l,u)).textPosAngle=(e.startangle+e.stopangle)/2,v.push(a));for(var x=0,b=0,_=0;_=1)break}return v[x]}function T(t,e,r,n,i){e=Math.max(0,e-2*v);var a=t.width/t.height,o=S(a,n,e,r);return{scale:2*o/t.height,rCenter:A(a,o/e),rotate:M(i)}}function k(t,e,r,n,i){e=Math.max(0,e-2*v);var a=t.height/t.width,o=S(a,n,e,r);return{scale:2*o/t.width,rCenter:A(a,o/e),rotate:M(i+Math.PI/2)}}function A(t,e){return Math.cos(e)-t*e}function M(t){return(180/Math.PI*t+720)%180-90}function S(t,e,r,n){var i=t+1/(2*Math.tan(e));return r*Math.min(1/(Math.sqrt(i*i+.5)+i),n/(Math.sqrt(t*t+n/2)+t))}function E(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function L(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return r<0&&(i*=-1),n<0&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function C(t,e){var r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=O(a),-1!==a.title.position.indexOf(\"top\")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf(\"bottom\")&&(o.y+=(1+i)*t.r);var l,u=t.r/(void 0===(l=t.trace.aspectratio)?1:l),c=e.w*(a.domain.x[1]-a.domain.x[0])/2;return-1!==a.title.position.indexOf(\"left\")?(c+=u,o.x-=(1+i)*u,s.tx+=t.titleBox.width/2):-1!==a.title.position.indexOf(\"center\")?c*=2:-1!==a.title.position.indexOf(\"right\")&&(c+=u,o.x+=(1+i)*u,s.tx-=t.titleBox.width/2),r=c/t.titleBox.width,n=P(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function P(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function O(t){var e,r=t.pull;if(!r)return 0;if(Array.isArray(r))for(r=0,e=0;er&&(r=t.pull[e]);return r}function I(t,e){for(var r=[],n=0;n1?c=(u=r.r)/i.aspectratio:u=(c=r.r)*i.aspectratio,l=(u*=(1+i.baseratio)/2)*c}o=Math.min(o,l/r.vTotal)}for(n=0;n\")}if(a){var x=l.castOption(i,e.i,\"texttemplate\");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:g.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:g.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(i,t.i,\"customdata\")}}(e),_=g.getFirstFilled(i.text,e.pts);(m(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,i._meta||{})}else e.text=\"\"}}function R(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}t.exports={plot:function(t,e){var r=t._context.staticPlot,a=t._fullLayout,h=a._size;d(\"pie\",a),_(e,t),I(e,h);var v=l.makeTraceGroups(a._pielayer,e,\"trace\").each((function(e){var d=n.select(this),v=e[0],y=v.trace;!function(t){var e,r,n,i=t[0],a=i.r,o=i.trace,s=g.getRotationAngle(o.rotation),l=2*Math.PI/i.vTotal,u=\"px0\",c=\"px1\";if(\"counterclockwise\"===o.direction){for(e=0;ei.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/i.vTotal,.5),r.ring=1-o.hole,r.rInscribed=E(r,i))}(e),d.attr(\"stroke-linejoin\",\"round\"),d.each((function(){var m=n.select(this).selectAll(\"g.slice\").data(e);m.enter().append(\"g\").classed(\"slice\",!0),m.exit().remove();var _=[[[],[]],[[],[]]],T=!1;m.each((function(i,o){if(i.hidden)n.select(this).selectAll(\"path,g\").remove();else{i.pointNumber=i.i,i.curveNumber=y.index,_[i.pxmid[1]<0?0:1][i.pxmid[0]<0?0:1].push(i);var u=v.cx,c=v.cy,h=n.select(this),d=h.selectAll(\"path.surface\").data([i]);if(d.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":r?\"none\":\"all\"}),h.call(x,t,e),y.pull){var m=+g.castOption(y.pull,i.pts)||0;m>0&&(u+=m*i.pxmid[0],c+=m*i.pxmid[1])}i.cxFinal=u,i.cyFinal=c;var k=y.hole;if(i.v===v.vTotal){var A=\"M\"+(u+i.px0[0])+\",\"+(c+i.px0[1])+P(i.px0,i.pxmid,!0,1)+P(i.pxmid,i.px0,!0,1)+\"Z\";k?d.attr(\"d\",\"M\"+(u+k*i.px0[0])+\",\"+(c+k*i.px0[1])+P(i.px0,i.pxmid,!1,k)+P(i.pxmid,i.px0,!1,k)+\"Z\"+A):d.attr(\"d\",A)}else{var M=P(i.px0,i.px1,!0,1);if(k){var S=1-k;d.attr(\"d\",\"M\"+(u+k*i.px1[0])+\",\"+(c+k*i.px1[1])+P(i.px1,i.px0,!1,k)+\"l\"+S*i.px0[0]+\",\"+S*i.px0[1]+M+\"Z\")}else d.attr(\"d\",\"M\"+u+\",\"+c+\"l\"+i.px0[0]+\",\"+i.px0[1]+M+\"Z\")}z(t,i,v);var E=g.castOption(y.textposition,i.pts),C=h.selectAll(\"g.slicetext\").data(i.text&&\"none\"!==E?[0]:[]);C.enter().append(\"g\").classed(\"slicetext\",!0),C.exit().remove(),C.each((function(){var r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),h=l.ensureUniformFontSize(t,\"outside\"===E?function(t,e,r){return{color:g.castOption(t.outsidetextfont.color,e.pts)||g.castOption(t.textfont.color,e.pts)||r.color,family:g.castOption(t.outsidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,size:g.castOption(t.outsidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size}}(y,i,a.font):b(y,i,a.font));r.text(i.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,h).call(f.convertToTspans,t);var d,m=s.bBox(r.node());if(\"outside\"===E)d=L(m,i);else if(d=w(m,i,v),\"auto\"===E&&d.scale<1){var x=l.ensureUniformFontSize(t,y.outsidetextfont);r.call(s.font,x),d=L(m=s.bBox(r.node()),i)}var _=d.textPosAngle,k=void 0===_?i.pxmid:D(v.r,_);if(d.targetX=u+k[0]*d.rCenter+(d.x||0),d.targetY=c+k[1]*d.rCenter+(d.y||0),R(d,m),d.outside){var A=d.targetY;i.yLabelMin=A-m.height/2,i.yLabelMid=A,i.yLabelMax=A+m.height/2,i.labelExtraX=0,i.labelExtraY=0,T=!0}d.fontSize=h.size,p(y.type,d,a),e[o].transform=d,l.setTransormAndDisplay(r,d)}))}function P(t,e,r,n){var a=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return\"a\"+n*v.r+\",\"+n*v.r+\" 0 \"+i.largeArc+(r?\" 1 \":\" 0 \")+a+\",\"+o}}));var k=n.select(this).selectAll(\"g.titletext\").data(y.title.text?[0]:[]);if(k.enter().append(\"g\").classed(\"titletext\",!0),k.exit().remove(),k.each((function(){var e,r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),i=y.title.text;y._meta&&(i=l.templateString(i,y._meta)),r.text(i).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,y.title.font).call(f.convertToTspans,t),e=\"middle center\"===y.title.position?function(t){var e=Math.sqrt(t.titleBox.width*t.titleBox.width+t.titleBox.height*t.titleBox.height);return{x:t.cx,y:t.cy,scale:t.trace.hole*t.r*2/e,tx:0,ty:-t.titleBox.height/2+t.trace.title.font.size}}(v):C(v,h),r.attr(\"transform\",c(e.x,e.y)+u(Math.min(1,e.scale))+c(e.tx,e.ty))})),T&&function(t,e){var r,n,i,a,o,s,l,u,c,f,h,p,d;function v(t,e){return t.pxmid[1]-e.pxmid[1]}function y(t,e){return e.pxmid[1]-t.pxmid[1]}function m(t,r){r||(r={});var i,u,c,h,p=r.labelExtraY+(n?r.yLabelMax:r.yLabelMin),d=n?t.yLabelMin:t.yLabelMax,v=n?t.yLabelMax:t.yLabelMin,y=t.cyFinal+o(t.px0[1],t.px1[1]),m=p-d;if(m*l>0&&(t.labelExtraY=m),Array.isArray(e.pull))for(u=0;u=(g.castOption(e.pull,c.pts)||0)||((t.pxmid[1]-c.pxmid[1])*l>0?(m=c.cyFinal+o(c.px0[1],c.px1[1])-d-t.labelExtraY)*l>0&&(t.labelExtraY+=m):(v+t.labelExtraY-y)*l>0&&(i=3*s*Math.abs(u-f.indexOf(t)),(h=c.cxFinal+a(c.px0[0],c.px1[0])+i-(t.cxFinal+t.pxmid[0])-t.labelExtraX)*s>0&&(t.labelExtraX+=h)))}for(n=0;n<2;n++)for(i=n?v:y,o=n?Math.max:Math.min,l=n?1:-1,r=0;r<2;r++){for(a=r?Math.max:Math.min,s=r?1:-1,(u=t[n][r]).sort(i),c=t[1-n][r],f=c.concat(u),p=[],h=0;hMath.abs(f)?s+=\"l\"+f*t.pxmid[0]/t.pxmid[1]+\",\"+f+\"H\"+(a+t.labelExtraX+u):s+=\"l\"+t.labelExtraX+\",\"+c+\"v\"+(f-c)+\"h\"+u}else 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n=r(39898),i=r(63463),a=r(72597).resizeText;t.exports=function(t){var e=t._fullLayout._pielayer.selectAll(\".trace\");a(t,e,\"pie\"),e.each((function(e){var r=e[0].trace,a=n.select(this);a.style({opacity:r.opacity}),a.selectAll(\"path.surface\").each((function(e){n.select(this).call(i,e,r,t)}))}))}},63463:function(t,e,r){\"use strict\";var n=r(7901),i=r(53581).castOption,a=r(22209);t.exports=function(t,e,r,o){var s=r.marker.line,l=i(s.color,e.pts)||n.defaultLine,u=i(s.width,e.pts)||0;t.call(a,e,r,o).style(\"stroke-width\",u).call(n.stroke,l)}},10959:function(t,e,r){\"use strict\";var 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n=r(39898),i=r(674),a=r(81684).sX,o=r(91424),s=r(71828),l=r(63893),u=r(72597),c=u.recordMinTextSize,f=u.clearMinTextSize,h=r(14575),p=r(53581).getRotationAngle,d=h.computeTransform,v=h.transformInsideText,g=r(29969).styleOne,y=r(16688).resizeText,m=r(83523),x=r(7055),b=r(2791);function _(t,r,u,f){var h=t._context.staticPlot,y=t._fullLayout,_=!y.uniformtext.mode&&b.hasTransition(f),T=n.select(u).selectAll(\"g.slice\"),k=r[0],A=k.trace,M=k.hierarchy,S=b.findEntryWithLevel(M,A.level),E=b.getMaxDepth(A),L=y._size,C=A.domain,P=L.w*(C.x[1]-C.x[0]),O=L.h*(C.y[1]-C.y[0]),I=.5*Math.min(P,O),D=k.cx=L.l+L.w*(C.x[1]+C.x[0])/2,z=k.cy=L.t+L.h*(1-C.y[0])-O/2;if(!S)return T.remove();var R=null,F={};_&&T.each((function(t){F[b.getPtId(t)]={rpx0:t.rpx0,rpx1:t.rpx1,x0:t.x0,x1:t.x1,transform:t.transform},!R&&b.isEntry(t)&&(R=t)}));var B=function(t){return i.partition().size([2*Math.PI,t.height+1])(t)}(S).descendants(),N=S.height+1,j=0,U=E;k.hasMultipleRoots&&b.isHierarchyRoot(S)&&(B=B.slice(1),N-=1,j=1,U+=1),B=B.filter((function(t){return t.y1<=U}));var V=p(A.rotation);V&&B.forEach((function(t){t.x0+=V,t.x1+=V}));var H=Math.min(N,E),q=function(t){return(t-j)/H*I},G=function(t,e){return[t*Math.cos(e),-t*Math.sin(e)]},Z=function(t){return s.pathAnnulus(t.rpx0,t.rpx1,t.x0,t.x1,D,z)},Y=function(t){return D+w(t)[0]*(t.transform.rCenter||0)+(t.transform.x||0)},W=function(t){return z+w(t)[1]*(t.transform.rCenter||0)+(t.transform.y||0)};(T=T.data(B,b.getPtId)).enter().append(\"g\").classed(\"slice\",!0),_?T.exit().transition().each((function(){var t=n.select(this);t.select(\"path.surface\").transition().attrTween(\"d\",(function(t){var e=function(t){var e,r=b.getPtId(t),n=F[r],i=F[b.getPtId(S)];if(i){var o=(t.x1>i.x1?2*Math.PI:0)+V;e=t.rpx1X?2*Math.PI:0)+V;e={x0:i,x1:i}}else e={rpx0:I,rpx1:I},s.extendFlat(e,$(t));else e={rpx0:0,rpx1:0};else e={x0:V,x1:V};return a(e,n)}(t);return function(t){return Z(e(t))}})):f.attr(\"d\",Z),u.call(m,S,t,r,{eventDataKeys:x.eventDataKeys,transitionTime:x.CLICK_TRANSITION_TIME,transitionEasing:x.CLICK_TRANSITION_EASING}).call(b.setSliceCursor,t,{hideOnRoot:!0,hideOnLeaves:!0,isTransitioning:t._transitioning}),f.call(g,i,A,t);var p=s.ensureSingle(u,\"g\",\"slicetext\"),w=s.ensureSingle(p,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),T=s.ensureUniformFontSize(t,b.determineTextFont(A,i,y.font));w.text(e.formatSliceLabel(i,S,A,r,y)).classed(\"slicetext\",!0).attr(\"text-anchor\",\"middle\").call(o.font,T).call(l.convertToTspans,t);var M=o.bBox(w.node());i.transform=v(M,i,k),i.transform.targetX=Y(i),i.transform.targetY=W(i);var E=function(t,e){var r=t.transform;return d(r,e),r.fontSize=T.size,c(A.type,r,y),s.getTextTransform(r)};_?w.transition().attrTween(\"transform\",(function(t){var e=function(t){var e,r=F[b.getPtId(t)],n=t.transform;if(r)e=r;else if(e={rpx1:t.rpx1,transform:{textPosAngle:n.textPosAngle,scale:0,rotate:n.rotate,rCenter:n.rCenter,x:n.x,y:n.y}},R)if(t.parent)if(X){var i=t.x1>X?2*Math.PI:0;e.x0=e.x1=i}else s.extendFlat(e,$(t));else e.x0=e.x1=V;else e.x0=e.x1=V;var o=a(e.transform.textPosAngle,t.transform.textPosAngle),l=a(e.rpx1,t.rpx1),u=a(e.x0,t.x0),f=a(e.x1,t.x1),h=a(e.transform.scale,n.scale),p=a(e.transform.rotate,n.rotate),d=0===n.rCenter?3:0===e.transform.rCenter?1/3:1,v=a(e.transform.rCenter,n.rCenter);return function(t){var e=l(t),r=u(t),i=f(t),a=function(t){return v(Math.pow(t,d))}(t),s={pxmid:G(e,(r+i)/2),rpx1:e,transform:{textPosAngle:o(t),rCenter:a,x:n.x,y:n.y}};return c(A.type,n,y),{transform:{targetX:Y(s),targetY:W(s),scale:h(t),rotate:p(t),rCenter:a}}}}(t);return function(t){return E(e(t),M)}})):w.attr(\"transform\",E(i,M))}))}function w(t){return e=t.rpx1,r=t.transform.textPosAngle,[e*Math.sin(r),-e*Math.cos(r)];var e,r}e.plot=function(t,e,r,i){var a,o,s=t._fullLayout,l=s._sunburstlayer,u=!r,c=!s.uniformtext.mode&&b.hasTransition(r);f(\"sunburst\",s),(a=l.selectAll(\"g.trace.sunburst\").data(e,(function(t){return t[0].trace.uid}))).enter().append(\"g\").classed(\"trace\",!0).classed(\"sunburst\",!0).attr(\"stroke-linejoin\",\"round\"),a.order(),c?(i&&(o=i()),n.transition().duration(r.duration).ease(r.easing).each(\"end\",(function(){o&&o()})).each(\"interrupt\",(function(){o&&o()})).each((function(){l.selectAll(\"g.trace\").each((function(e){_(t,e,this,r)}))}))):(a.each((function(e){_(t,e,this,r)})),s.uniformtext.mode&&y(t,s._sunburstlayer.selectAll(\".trace\"),\"sunburst\")),u&&a.exit().remove()},e.formatSliceLabel=function(t,e,r,n,i){var a=r.texttemplate,o=r.textinfo;if(!(a||o&&\"none\"!==o))return\"\";var l=i.separators,u=n[0],c=t.data.data,f=u.hierarchy,h=b.isHierarchyRoot(t),p=b.getParent(f,t),d=b.getValue(t);if(!a){var v,g=o.split(\"+\"),y=function(t){return-1!==g.indexOf(t)},m=[];if(y(\"label\")&&c.label&&m.push(c.label),c.hasOwnProperty(\"v\")&&y(\"value\")&&m.push(b.formatValue(c.v,l)),!h){y(\"current path\")&&m.push(b.getPath(t.data));var x=0;y(\"percent parent\")&&x++,y(\"percent entry\")&&x++,y(\"percent root\")&&x++;var _=x>1;if(x){var w,T=function(t){v=b.formatPercent(w,l),_&&(v+=\" of \"+t),m.push(v)};y(\"percent parent\")&&!h&&(w=d/b.getValue(p),T(\"parent\")),y(\"percent entry\")&&(w=d/b.getValue(e),T(\"entry\")),y(\"percent root\")&&(w=d/b.getValue(f),T(\"root\"))}}return y(\"text\")&&(v=s.castOption(r,c.i,\"text\"),s.isValidTextValue(v)&&m.push(v)),m.join(\"
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f=t.exports=u(l({z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:o(),xhoverformat:a(\"x\"),yhoverformat:a(\"y\"),zhoverformat:a(\"z\"),connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},surfacecolor:{valType:\"data_array\"}},i(\"\",{colorAttr:\"z or 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n=r(78803);t.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},43768:function(t,e,r){\"use strict\";var n=r(9330).gl_surface3d,i=r(9330).ndarray,a=r(9330).ndarray_linear_interpolate.d2,o=r(824),s=r(43907),l=r(71828).isArrayOrTypedArray,u=r(81697).parseColorScale,c=r(78614),f=r(21081).extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?i:n.d2l(i,0,r)},p.getZat=function(t,e,r,n){var i=this.data.z[e][t];return null===i&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[e][t]),void 0===r?i:n.d2l(i,0,r)},p.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,i],t.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],t.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){null!=t.dataCoordinate[a]&&(t.dataCoordinate[a]*=this.scene.dataScale[a])}var o=this.data.hovertext||this.data.text;return Array.isArray(o)&&o[i]&&void 0!==o[i][n]?t.textLabel=o[i][n]:t.textLabel=o||\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var 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v(t,e){if(t0){r=d[n];break}return r}function m(t,e){if(!(t<1||e<1)){for(var r=g(t),n=g(e),i=1,a=0;a_;)r--,r/=y(r),++r1?n:1},p.refineCoords=function(t){for(var e=this.dataScaleX,r=this.dataScaleY,n=t[0].shape[0],a=t[0].shape[1],o=0|Math.floor(t[0].shape[0]*e+1),s=0|Math.floor(t[0].shape[1]*r+1),l=1+n+1,u=1+a+1,c=i(new Float32Array(l*u),[l,u]),f=[1/e,0,0,0,1/r,0,0,0,1],h=0;h0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(i[t]=!0,e=this.contourStart[t];ea&&(this.minValues[e]=a),this.maxValues[e]\",maxDimensionCount:60,overdrag:45,releaseTransitionDuration:120,releaseTransitionEase:\"cubic-out\",scrollbarCaptureWidth:18,scrollbarHideDelay:1e3,scrollbarHideDuration:1e3,scrollbarOffset:5,scrollbarWidth:8,transitionDuration:100,transitionEase:\"cubic-out\",uplift:5,wrapSpacer:\" \",wrapSplitCharacter:\" \",cn:{table:\"table\",tableControlView:\"table-control-view\",scrollBackground:\"scroll-background\",yColumn:\"y-column\",columnBlock:\"column-block\",scrollAreaClip:\"scroll-area-clip\",scrollAreaClipRect:\"scroll-area-clip-rect\",columnBoundary:\"column-boundary\",columnBoundaryClippath:\"column-boundary-clippath\",columnBoundaryRect:\"column-boundary-rect\",columnCells:\"column-cells\",columnCell:\"column-cell\",cellRect:\"cell-rect\",cellText:\"cell-text\",cellTextHolder:\"cell-text-holder\",scrollbarKit:\"scrollbar-kit\",scrollbar:\"scrollbar\",scrollbarSlider:\"scrollbar-slider\",scrollbarGlyph:\"scrollbar-glyph\",scrollbarCaptureZone:\"scrollbar-capture-zone\"}}},51018:function(t,e,r){\"use strict\";var n=r(49850),i=r(1426).extendFlat,a=r(92770);function o(t){if(Array.isArray(t)){for(var e=0,r=0;r=e||u===t.length-1)&&(n[i]=o,o.key=l++,o.firstRowIndex=s,o.lastRowIndex=u,o={firstRowIndex:null,lastRowIndex:null,rows:[]},i+=a,s=u+1,a=0);return n}t.exports=function(t,e){var r=l(e.cells.values),p=function(t){return t.slice(e.header.values.length,t.length)},d=l(e.header.values);d.length&&!d[0].length&&(d[0]=[\"\"],d=l(d));var v=d.concat(p(r).map((function(){return u((d[0]||[\"\"]).length)}))),g=e.domain,y=Math.floor(t._fullLayout._size.w*(g.x[1]-g.x[0])),m=Math.floor(t._fullLayout._size.h*(g.y[1]-g.y[0])),x=e.header.values.length?v[0].map((function(){return e.header.height})):[n.emptyHeaderHeight],b=r.length?r[0].map((function(){return e.cells.height})):[],_=x.reduce(s,0),w=h(b,m-_+n.uplift),T=f(h(x,_),[]),k=f(w,T),A={},M=e._fullInput.columnorder.concat(p(r.map((function(t,e){return e})))),S=v.map((function(t,r){var n=Array.isArray(e.columnwidth)?e.columnwidth[Math.min(r,e.columnwidth.length-1)]:e.columnwidth;return a(n)?Number(n):1})),E=S.reduce(s,0);S=S.map((function(t){return t/E*y}));var L=Math.max(o(e.header.line.width),o(e.cells.line.width)),C={key:e.uid+t._context.staticPlot,translateX:g.x[0]*t._fullLayout._size.w,translateY:t._fullLayout._size.h*(1-g.y[1]),size:t._fullLayout._size,width:y,maxLineWidth:L,height:m,columnOrder:M,groupHeight:m,rowBlocks:k,headerRowBlocks:T,scrollY:0,cells:i({},e.cells,{values:r}),headerCells:i({},e.header,{values:v}),gdColumns:v.map((function(t){return t[0]})),gdColumnsOriginalOrder:v.map((function(t){return t[0]})),prevPages:[0,0],scrollbarState:{scrollbarScrollInProgress:!1},columns:v.map((function(t,e){var r=A[t];return A[t]=(r||0)+1,{key:t+\"__\"+A[t],label:t,specIndex:e,xIndex:M[e],xScale:c,x:void 0,calcdata:void 0,columnWidth:S[e]}}))};return C.columns.forEach((function(t){t.calcdata=C,t.x=c(t)})),C}},56269:function(t,e,r){\"use strict\";var n=r(1426).extendFlat;e.splitToPanels=function(t){var 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a=0,o=0;o>26,this.words[o]=67108863&e;for(;0!==a&&o>26,this.words[o]=67108863&e;if(0===a&&o>>13,p=0|o[1],d=8191&p,v=p>>>13,g=0|o[2],y=8191&g,m=g>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],L=8191&E,C=E>>>13,P=0|o[7],O=8191&P,I=P>>>13,D=0|o[8],z=8191&D,R=D>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],U=8191&j,V=j>>>13,H=0|s[1],q=8191&H,G=H>>>13,Z=0|s[2],Y=8191&Z,W=Z>>>13,X=0|s[3],J=8191&X,K=X>>>13,$=0|s[4],Q=8191&$,tt=$>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ut=st>>>13,ct=0|s[8],ft=8191&ct,ht=ct>>>13,pt=0|s[9],dt=8191&pt,vt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var gt=(u+(n=Math.imul(f,U))|0)+((8191&(i=(i=Math.imul(f,V))+Math.imul(h,U)|0))<<13)|0;u=((a=Math.imul(h,V))+(i>>>13)|0)+(gt>>>26)|0,gt&=67108863,n=Math.imul(d,U),i=(i=Math.imul(d,V))+Math.imul(v,U)|0,a=Math.imul(v,V);var yt=(u+(n=n+Math.imul(f,q)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,q)|0))<<13)|0;u=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(y,U),i=(i=Math.imul(y,V))+Math.imul(m,U)|0,a=Math.imul(m,V),n=n+Math.imul(d,q)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(v,q)|0,a=a+Math.imul(v,G)|0;var mt=(u+(n=n+Math.imul(f,Y)|0)|0)+((8191&(i=(i=i+Math.imul(f,W)|0)+Math.imul(h,Y)|0))<<13)|0;u=((a=a+Math.imul(h,W)|0)+(i>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(b,U),i=(i=Math.imul(b,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(y,q)|0,i=(i=i+Math.imul(y,G)|0)+Math.imul(m,q)|0,a=a+Math.imul(m,G)|0,n=n+Math.imul(d,Y)|0,i=(i=i+Math.imul(d,W)|0)+Math.imul(v,Y)|0,a=a+Math.imul(v,W)|0;var xt=(u+(n=n+Math.imul(f,J)|0)|0)+((8191&(i=(i=i+Math.imul(f,K)|0)+Math.imul(h,J)|0))<<13)|0;u=((a=a+Math.imul(h,K)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,q)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,q)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(y,Y)|0,i=(i=i+Math.imul(y,W)|0)+Math.imul(m,Y)|0,a=a+Math.imul(m,W)|0,n=n+Math.imul(d,J)|0,i=(i=i+Math.imul(d,K)|0)+Math.imul(v,J)|0,a=a+Math.imul(v,K)|0;var bt=(u+(n=n+Math.imul(f,Q)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,Q)|0))<<13)|0;u=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,U),i=(i=Math.imul(M,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,q)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,q)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,Y)|0,i=(i=i+Math.imul(b,W)|0)+Math.imul(_,Y)|0,a=a+Math.imul(_,W)|0,n=n+Math.imul(y,J)|0,i=(i=i+Math.imul(y,K)|0)+Math.imul(m,J)|0,a=a+Math.imul(m,K)|0,n=n+Math.imul(d,Q)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(v,Q)|0,a=a+Math.imul(v,tt)|0;var _t=(u+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;u=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,U),i=(i=Math.imul(L,V))+Math.imul(C,U)|0,a=Math.imul(C,V),n=n+Math.imul(M,q)|0,i=(i=i+Math.imul(M,G)|0)+Math.imul(S,q)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,Y)|0,i=(i=i+Math.imul(T,W)|0)+Math.imul(k,Y)|0,a=a+Math.imul(k,W)|0,n=n+Math.imul(b,J)|0,i=(i=i+Math.imul(b,K)|0)+Math.imul(_,J)|0,a=a+Math.imul(_,K)|0,n=n+Math.imul(y,Q)|0,i=(i=i+Math.imul(y,tt)|0)+Math.imul(m,Q)|0,a=a+Math.imul(m,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(v,rt)|0,a=a+Math.imul(v,nt)|0;var wt=(u+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;u=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(O,U),i=(i=Math.imul(O,V))+Math.imul(I,U)|0,a=Math.imul(I,V),n=n+Math.imul(L,q)|0,i=(i=i+Math.imul(L,G)|0)+Math.imul(C,q)|0,a=a+Math.imul(C,G)|0,n=n+Math.imul(M,Y)|0,i=(i=i+Math.imul(M,W)|0)+Math.imul(S,Y)|0,a=a+Math.imul(S,W)|0,n=n+Math.imul(T,J)|0,i=(i=i+Math.imul(T,K)|0)+Math.imul(k,J)|0,a=a+Math.imul(k,K)|0,n=n+Math.imul(b,Q)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,Q)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(y,rt)|0,i=(i=i+Math.imul(y,nt)|0)+Math.imul(m,rt)|0,a=a+Math.imul(m,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(v,at)|0,a=a+Math.imul(v,ot)|0;var Tt=(u+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ut)|0)+Math.imul(h,lt)|0))<<13)|0;u=((a=a+Math.imul(h,ut)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(z,U),i=(i=Math.imul(z,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(O,q)|0,i=(i=i+Math.imul(O,G)|0)+Math.imul(I,q)|0,a=a+Math.imul(I,G)|0,n=n+Math.imul(L,Y)|0,i=(i=i+Math.imul(L,W)|0)+Math.imul(C,Y)|0,a=a+Math.imul(C,W)|0,n=n+Math.imul(M,J)|0,i=(i=i+Math.imul(M,K)|0)+Math.imul(S,J)|0,a=a+Math.imul(S,K)|0,n=n+Math.imul(T,Q)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,Q)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(y,at)|0,i=(i=i+Math.imul(y,ot)|0)+Math.imul(m,at)|0,a=a+Math.imul(m,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ut)|0)+Math.imul(v,lt)|0,a=a+Math.imul(v,ut)|0;var kt=(u+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;u=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(z,q)|0,i=(i=i+Math.imul(z,G)|0)+Math.imul(R,q)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(O,Y)|0,i=(i=i+Math.imul(O,W)|0)+Math.imul(I,Y)|0,a=a+Math.imul(I,W)|0,n=n+Math.imul(L,J)|0,i=(i=i+Math.imul(L,K)|0)+Math.imul(C,J)|0,a=a+Math.imul(C,K)|0,n=n+Math.imul(M,Q)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(S,Q)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(y,lt)|0,i=(i=i+Math.imul(y,ut)|0)+Math.imul(m,lt)|0,a=a+Math.imul(m,ut)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(v,ft)|0,a=a+Math.imul(v,ht)|0;var At=(u+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,vt)|0)+Math.imul(h,dt)|0))<<13)|0;u=((a=a+Math.imul(h,vt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,q),i=(i=Math.imul(B,G))+Math.imul(N,q)|0,a=Math.imul(N,G),n=n+Math.imul(z,Y)|0,i=(i=i+Math.imul(z,W)|0)+Math.imul(R,Y)|0,a=a+Math.imul(R,W)|0,n=n+Math.imul(O,J)|0,i=(i=i+Math.imul(O,K)|0)+Math.imul(I,J)|0,a=a+Math.imul(I,K)|0,n=n+Math.imul(L,Q)|0,i=(i=i+Math.imul(L,tt)|0)+Math.imul(C,Q)|0,a=a+Math.imul(C,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ut)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ut)|0,n=n+Math.imul(y,ft)|0,i=(i=i+Math.imul(y,ht)|0)+Math.imul(m,ft)|0,a=a+Math.imul(m,ht)|0;var Mt=(u+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,vt)|0)+Math.imul(v,dt)|0))<<13)|0;u=((a=a+Math.imul(v,vt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,Y),i=(i=Math.imul(B,W))+Math.imul(N,Y)|0,a=Math.imul(N,W),n=n+Math.imul(z,J)|0,i=(i=i+Math.imul(z,K)|0)+Math.imul(R,J)|0,a=a+Math.imul(R,K)|0,n=n+Math.imul(O,Q)|0,i=(i=i+Math.imul(O,tt)|0)+Math.imul(I,Q)|0,a=a+Math.imul(I,tt)|0,n=n+Math.imul(L,rt)|0,i=(i=i+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,a=a+Math.imul(C,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ut)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ut)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(u+(n=n+Math.imul(y,dt)|0)|0)+((8191&(i=(i=i+Math.imul(y,vt)|0)+Math.imul(m,dt)|0))<<13)|0;u=((a=a+Math.imul(m,vt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),i=(i=Math.imul(B,K))+Math.imul(N,J)|0,a=Math.imul(N,K),n=n+Math.imul(z,Q)|0,i=(i=i+Math.imul(z,tt)|0)+Math.imul(R,Q)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(O,rt)|0,i=(i=i+Math.imul(O,nt)|0)+Math.imul(I,rt)|0,a=a+Math.imul(I,nt)|0,n=n+Math.imul(L,at)|0,i=(i=i+Math.imul(L,ot)|0)+Math.imul(C,at)|0,a=a+Math.imul(C,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ut)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ut)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(u+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,vt)|0)+Math.imul(_,dt)|0))<<13)|0;u=((a=a+Math.imul(_,vt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,Q),i=(i=Math.imul(B,tt))+Math.imul(N,Q)|0,a=Math.imul(N,tt),n=n+Math.imul(z,rt)|0,i=(i=i+Math.imul(z,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(O,at)|0,i=(i=i+Math.imul(O,ot)|0)+Math.imul(I,at)|0,a=a+Math.imul(I,ot)|0,n=n+Math.imul(L,lt)|0,i=(i=i+Math.imul(L,ut)|0)+Math.imul(C,lt)|0,a=a+Math.imul(C,ut)|0,n=n+Math.imul(M,ft)|0,i=(i=i+Math.imul(M,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Lt=(u+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,vt)|0)+Math.imul(k,dt)|0))<<13)|0;u=((a=a+Math.imul(k,vt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(z,at)|0,i=(i=i+Math.imul(z,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(O,lt)|0,i=(i=i+Math.imul(O,ut)|0)+Math.imul(I,lt)|0,a=a+Math.imul(I,ut)|0,n=n+Math.imul(L,ft)|0,i=(i=i+Math.imul(L,ht)|0)+Math.imul(C,ft)|0,a=a+Math.imul(C,ht)|0;var Ct=(u+(n=n+Math.imul(M,dt)|0)|0)+((8191&(i=(i=i+Math.imul(M,vt)|0)+Math.imul(S,dt)|0))<<13)|0;u=((a=a+Math.imul(S,vt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(z,lt)|0,i=(i=i+Math.imul(z,ut)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ut)|0,n=n+Math.imul(O,ft)|0,i=(i=i+Math.imul(O,ht)|0)+Math.imul(I,ft)|0,a=a+Math.imul(I,ht)|0;var Pt=(u+(n=n+Math.imul(L,dt)|0)|0)+((8191&(i=(i=i+Math.imul(L,vt)|0)+Math.imul(C,dt)|0))<<13)|0;u=((a=a+Math.imul(C,vt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ut))+Math.imul(N,lt)|0,a=Math.imul(N,ut),n=n+Math.imul(z,ft)|0,i=(i=i+Math.imul(z,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var Ot=(u+(n=n+Math.imul(O,dt)|0)|0)+((8191&(i=(i=i+Math.imul(O,vt)|0)+Math.imul(I,dt)|0))<<13)|0;u=((a=a+Math.imul(I,vt)|0)+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var It=(u+(n=n+Math.imul(z,dt)|0)|0)+((8191&(i=(i=i+Math.imul(z,vt)|0)+Math.imul(R,dt)|0))<<13)|0;u=((a=a+Math.imul(R,vt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863;var Dt=(u+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,vt))+Math.imul(N,dt)|0))<<13)|0;return u=((a=Math.imul(N,vt))+(i>>>13)|0)+(Dt>>>26)|0,Dt&=67108863,l[0]=gt,l[1]=yt,l[2]=mt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=Pt,l[16]=Ot,l[17]=It,l[18]=Dt,0!==u&&(l[19]=u,r.length++),r};function v(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(d=p),a.prototype.mulTo=function(t,e){var r,n=this.length+t.length;return r=10===this.length&&10===t.length?d(this,t,e):n<63?p(this,t,e):n<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):v(this,t,e),r},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o>>=1)i++;return 1<>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<o)for(this.length-=o,u=0;u=0&&(0!==c||u>=i);u--){var f=0|this.words[u];this.words[u]=c<<26-a|f>>>a,c=f&s}return l&&0!==c&&(l.words[l.length++]=c),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!=(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var u=0;u=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),u=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++u;for(var c=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(c),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,v=1;0==(r.words[0]&v)&&d<26;++d,v<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(c),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(u)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var u=0,c=1;0==(e.words[0]&c)&&u<26;++u,c<<=1);if(u>0)for(e.iushrn(u);u-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,i=1<>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];e=i===t?0:it.length)return 1;if(this.length=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){ni&&(e=1);break}}return e},a.prototype.gtn=function(t){return 1===this.cmpn(t)},a.prototype.gt=function(t){return 1===this.cmp(t)},a.prototype.gten=function(t){return this.cmpn(t)>=0},a.prototype.gte=function(t){return this.cmp(t)>=0},a.prototype.ltn=function(t){return-1===this.cmpn(t)},a.prototype.lt=function(t){return-1===this.cmp(t)},a.prototype.lten=function(t){return this.cmpn(t)<=0},a.prototype.lte=function(t){return this.cmp(t)<=0},a.prototype.eqn=function(t){return 0===this.cmpn(t)},a.prototype.eq=function(t){return 0===this.cmp(t)},a.red=function(t){return new T(t)},a.prototype.toRed=function(t){return n(!this.red,\"Already a number in reduction context\"),n(0===this.negative,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},a.prototype.fromRed=function(){return n(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},a.prototype._forceRed=function(t){return this.red=t,this},a.prototype.forceRed=function(t){return n(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},a.prototype.redAdd=function(t){return n(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},a.prototype.redIAdd=function(t){return n(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},a.prototype.redSub=function(t){return n(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},a.prototype.redISub=function(t){return n(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},a.prototype.redShl=function(t){return n(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},a.prototype.redMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},a.prototype.redIMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},a.prototype.redSqr=function(){return n(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var y={k256:null,p224:null,p192:null,p25519:null};function m(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function x(){m.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}function b(){m.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}function _(){m.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}function w(){m.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}function T(t){if(\"string\"==typeof t){var e=a._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),\"modulus must be greater than 1\"),this.m=t,this.prime=null}function k(t){T.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new a(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}m.prototype._tmp=function(){var t=new a(null);return t.words=new Array(Math.ceil(this.n/13)),t},m.prototype.ireduce=function(t){var e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e0?r.isub(this.p):void 0!==r.strip?r.strip():r._strip(),r},m.prototype.split=function(t,e){t.iushrn(this.n,0,e)},m.prototype.imulK=function(t){return t.imul(this.k)},i(x,m),x.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;i>>22,a=o}a>>>=22,t.words[i-10]=a,0===a&&t.length>10?t.length-=10:t.length-=9},x.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(y[t])return y[t];var e;if(\"k256\"===t)e=new x;else if(\"p224\"===t)e=new b;else if(\"p192\"===t)e=new _;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new w}return y[t]=e,e},T.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red numbers\")},T.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),\"red works only with positives\"),n(t.red&&t.red===e.red,\"red works only with red numbers\")},T.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},T.prototype.neg=function(t){return t.isZero()?t.clone():this.m.sub(t)._forceRed(this)},T.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},T.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},T.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},T.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},T.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.ushln(e))},T.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},T.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},T.prototype.isqr=function(t){return this.imul(t,t.clone())},T.prototype.sqr=function(t){return this.mul(t,t)},T.prototype.sqrt=function(t){if(t.isZero())return t.clone();var e=this.m.andln(3);if(n(e%2==1),3===e){var r=this.m.add(new a(1)).iushrn(2);return this.pow(t,r)}for(var i=this.m.subn(1),o=0;!i.isZero()&&0===i.andln(1);)o++,i.iushrn(1);n(!i.isZero());var s=new a(1).toRed(this),l=s.redNeg(),u=this.m.subn(1).iushrn(1),c=this.m.bitLength();for(c=new a(2*c*c).toRed(this);0!==this.pow(c,u).cmp(l);)c.redIAdd(l);for(var f=this.pow(c,i),h=this.pow(t,i.addn(1).iushrn(1)),p=this.pow(t,i),d=o;0!==p.cmp(s);){for(var v=p,g=0;0!==v.cmp(s);g++)v=v.redSqr();n(g=0;n--){for(var u=e.words[n],c=l-1;c>=0;c--){var f=u>>c&1;i!==r[0]&&(i=this.sqr(i)),0!==f||0!==o?(o<<=1,o|=f,(4==++s||0===n&&0===c)&&(i=this.mul(i,r[o]),s=0,o=0)):s=0}l=26}return i},T.prototype.convertTo=function(t){var 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e(t._color,t.key,t.value,t.left,t.right,t._count)}function n(t,r){return new e(t,r.key,r.value,r.left,r.right,r._count)}function i(t){t._count=1+(t.left?t.left._count:0)+(t.right?t.right._count:0)}function a(t,e){this._compare=t,this.root=e}t.exports=function(t){return new a(t||p,null)};var o=a.prototype;function s(t,e){var r;return e.left&&(r=s(t,e.left))?r:(r=t(e.key,e.value))||(e.right?s(t,e.right):void 0)}function l(t,e,r,n){if(e(t,n.key)<=0){var i;if(n.left&&(i=l(t,e,r,n.left)))return i;if(i=r(n.key,n.value))return i}if(n.right)return l(t,e,r,n.right)}function u(t,e,r,n,i){var a,o=r(t,i.key),s=r(e,i.key);if(o<=0){if(i.left&&(a=u(t,e,r,n,i.left)))return a;if(s>0&&(a=n(i.key,i.value)))return a}if(s>0&&i.right)return u(t,e,r,n,i.right)}function c(t,e){this.tree=t,this._stack=e}Object.defineProperty(o,\"keys\",{get:function(){var t=[];return this.forEach((function(e,r){t.push(e)})),t}}),Object.defineProperty(o,\"values\",{get:function(){var t=[];return this.forEach((function(e,r){t.push(r)})),t}}),Object.defineProperty(o,\"length\",{get:function(){return this.root?this.root._count:0}}),o.insert=function(t,r){for(var o=this._compare,s=this.root,l=[],u=[];s;){var c=o(t,s.key);l.push(s),u.push(c),s=c<=0?s.left:s.right}l.push(new e(0,t,r,null,null,1));for(var f=l.length-2;f>=0;--f)s=l[f],u[f]<=0?l[f]=new e(s._color,s.key,s.value,l[f+1],s.right,s._count+1):l[f]=new e(s._color,s.key,s.value,s.left,l[f+1],s._count+1);for(f=l.length-1;f>1;--f){var h=l[f-1];if(s=l[f],1===h._color||1===s._color)break;var p=l[f-2];if(p.left===h)if(h.left===s){if(!(d=p.right)||0!==d._color){p._color=0,p.left=h.right,h._color=1,h.right=p,l[f-2]=h,l[f-1]=s,i(p),i(h),f>=3&&((v=l[f-3]).left===p?v.left=h:v.right=h);break}h._color=1,p.right=n(1,d),p._color=0,f-=1}else{if(!(d=p.right)||0!==d._color){h.right=s.left,p._color=0,p.left=s.right,s._color=1,s.left=h,s.right=p,l[f-2]=s,l[f-1]=h,i(p),i(h),i(s),f>=3&&((v=l[f-3]).left===p?v.left=s:v.right=s);break}h._color=1,p.right=n(1,d),p._color=0,f-=1}else if(h.right===s){if(!(d=p.left)||0!==d._color){p._color=0,p.right=h.left,h._color=1,h.left=p,l[f-2]=h,l[f-1]=s,i(p),i(h),f>=3&&((v=l[f-3]).right===p?v.right=h:v.left=h);break}h._color=1,p.left=n(1,d),p._color=0,f-=1}else{var d;if(!(d=p.left)||0!==d._color){var v;h.left=s.right,p._color=0,p.right=s.left,s._color=1,s.right=h,s.left=p,l[f-2]=s,l[f-1]=h,i(p),i(h),i(s),f>=3&&((v=l[f-3]).right===p?v.right=s:v.left=s);break}h._color=1,p.left=n(1,d),p._color=0,f-=1}}return l[0]._color=1,new a(o,l[0])},o.forEach=function(t,e,r){if(this.root)switch(arguments.length){case 1:return s(t,this.root);case 2:return l(e,this._compare,t,this.root);case 3:if(this._compare(e,r)>=0)return;return u(e,r,this._compare,t,this.root)}},Object.defineProperty(o,\"begin\",{get:function(){for(var t=[],e=this.root;e;)t.push(e),e=e.left;return new c(this,t)}}),Object.defineProperty(o,\"end\",{get:function(){for(var t=[],e=this.root;e;)t.push(e),e=e.right;return new c(this,t)}}),o.at=function(t){if(t<0)return new c(this,[]);for(var e=this.root,r=[];;){if(r.push(e),e.left){if(t=e.right._count)break;e=e.right}return new c(this,[])},o.ge=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a<=0&&(i=n.length),r=a<=0?r.left:r.right}return n.length=i,new c(this,n)},o.gt=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a<0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new c(this,n)},o.lt=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>0&&(i=n.length),r=a<=0?r.left:r.right}return n.length=i,new c(this,n)},o.le=function(t){for(var e=this._compare,r=this.root,n=[],i=0;r;){var a=e(t,r.key);n.push(r),a>=0&&(i=n.length),r=a<0?r.left:r.right}return n.length=i,new c(this,n)},o.find=function(t){for(var e=this._compare,r=this.root,n=[];r;){var i=e(t,r.key);if(n.push(r),0===i)return new c(this,n);r=i<=0?r.left:r.right}return new c(this,[])},o.remove=function(t){var e=this.find(t);return e?e.remove():this},o.get=function(t){for(var e=this._compare,r=this.root;r;){var n=e(t,r.key);if(0===n)return r.value;r=n<=0?r.left:r.right}};var f=c.prototype;function h(t,e){t.key=e.key,t.value=e.value,t.left=e.left,t.right=e.right,t._color=e._color,t._count=e._count}function p(t,e){return te?1:0}Object.defineProperty(f,\"valid\",{get:function(){return this._stack.length>0}}),Object.defineProperty(f,\"node\",{get:function(){return this._stack.length>0?this._stack[this._stack.length-1]:null},enumerable:!0}),f.clone=function(){return new c(this.tree,this._stack.slice())},f.remove=function(){var t=this._stack;if(0===t.length)return this.tree;var o=new Array(t.length),s=t[t.length-1];o[o.length-1]=new e(s._color,s.key,s.value,s.left,s.right,s._count);for(var l=t.length-2;l>=0;--l)(s=t[l]).left===t[l+1]?o[l]=new e(s._color,s.key,s.value,o[l+1],s.right,s._count):o[l]=new e(s._color,s.key,s.value,s.left,o[l+1],s._count);if((s=o[o.length-1]).left&&s.right){var u=o.length;for(s=s.left;s.right;)o.push(s),s=s.right;var c=o[u-1];for(o.push(new e(s._color,c.key,c.value,s.left,s.right,s._count)),o[u-1].key=s.key,o[u-1].value=s.value,l=o.length-2;l>=u;--l)s=o[l],o[l]=new e(s._color,s.key,s.value,s.left,o[l+1],s._count);o[u-1].left=o[u]}if(0===(s=o[o.length-1])._color){var f=o[o.length-2];for(f.left===s?f.left=null:f.right===s&&(f.right=null),o.pop(),l=0;l=0;--l){if(e=t[l],0===l)return void(e._color=1);if((a=t[l-1]).left===e){if((o=a.right).right&&0===o.right._color)return s=(o=a.right=r(o)).right=r(o.right),a.right=o.left,o.left=a,o.right=s,o._color=a._color,e._color=1,a._color=1,s._color=1,i(a),i(o),l>1&&((u=t[l-2]).left===a?u.left=o:u.right=o),void(t[l-1]=o);if(o.left&&0===o.left._color)return s=(o=a.right=r(o)).left=r(o.left),a.right=s.left,o.left=s.right,s.left=a,s.right=o,s._color=a._color,a._color=1,o._color=1,e._color=1,i(a),i(o),i(s),l>1&&((u=t[l-2]).left===a?u.left=s:u.right=s),void(t[l-1]=s);if(1===o._color){if(0===a._color)return a._color=1,void(a.right=n(0,o));a.right=n(0,o);continue}o=r(o),a.right=o.left,o.left=a,o._color=a._color,a._color=0,i(a),i(o),l>1&&((u=t[l-2]).left===a?u.left=o:u.right=o),t[l-1]=o,t[l]=a,l+11&&((u=t[l-2]).right===a?u.right=o:u.left=o),void(t[l-1]=o);if(o.right&&0===o.right._color)return s=(o=a.left=r(o)).right=r(o.right),a.left=s.right,o.right=s.left,s.right=a,s.left=o,s._color=a._color,a._color=1,o._color=1,e._color=1,i(a),i(o),i(s),l>1&&((u=t[l-2]).right===a?u.right=s:u.left=s),void(t[l-1]=s);if(1===o._color){if(0===a._color)return a._color=1,void(a.left=n(0,o));a.left=n(0,o);continue}var u;o=r(o),a.left=o.right,o.right=a,o._color=a._color,a._color=0,i(a),i(o),l>1&&((u=t[l-2]).right===a?u.right=o:u.left=o),t[l-1]=o,t[l]=a,l+10)return this._stack[this._stack.length-1].key},enumerable:!0}),Object.defineProperty(f,\"value\",{get:function(){if(this._stack.length>0)return this._stack[this._stack.length-1].value},enumerable:!0}),Object.defineProperty(f,\"index\",{get:function(){var t=0,e=this._stack;if(0===e.length){var r=this.tree.root;return r?r._count:0}e[e.length-1].left&&(t=e[e.length-1].left._count);for(var n=e.length-2;n>=0;--n)e[n+1]===e[n].right&&(++t,e[n].left&&(t+=e[n].left._count));return t},enumerable:!0}),f.next=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.right)for(e=e.right;e;)t.push(e),e=e.left;else for(t.pop();t.length>0&&t[t.length-1].right===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(f,\"hasNext\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].right)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].left===t[e])return!0;return!1}}),f.update=function(t){var r=this._stack;if(0===r.length)throw new Error(\"Can't update empty node!\");var n=new Array(r.length),i=r[r.length-1];n[n.length-1]=new e(i._color,i.key,t,i.left,i.right,i._count);for(var o=r.length-2;o>=0;--o)(i=r[o]).left===r[o+1]?n[o]=new e(i._color,i.key,i.value,n[o+1],i.right,i._count):n[o]=new e(i._color,i.key,i.value,i.left,n[o+1],i._count);return new a(this.tree._compare,n[0])},f.prev=function(){var t=this._stack;if(0!==t.length){var e=t[t.length-1];if(e.left)for(e=e.left;e;)t.push(e),e=e.right;else for(t.pop();t.length>0&&t[t.length-1].left===e;)e=t[t.length-1],t.pop()}},Object.defineProperty(f,\"hasPrev\",{get:function(){var t=this._stack;if(0===t.length)return!1;if(t[t.length-1].left)return!0;for(var e=t.length-1;e>0;--e)if(t[e-1].right===t[e])return!0;return!1}})},7453:function(t,e,r){\"use strict\";t.exports=function(t,e){var r=new c(t);return r.update(e),r};var n=r(9557),i=r(1681),a=r(1011),o=r(2864),s=r(8468),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function u(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function c(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=\"sans-serif\",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=a(t)}var f=c.prototype;function h(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}f.update=function(t){function e(e,r,n){if(n in t){var i,a=t[n],o=this[n];(e?Array.isArray(a)&&Array.isArray(a[0]):Array.isArray(a))?this[n]=i=[r(a[0]),r(a[1]),r(a[2])]:this[n]=i=[r(a),r(a),r(a)];for(var s=0;s<3;++s)if(i[s]!==o[s])return!0}return!1}t=t||{};var r,a=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),u=e.bind(this,!0,(function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]})),c=!1,f=!1;if(\"bounds\"in t)for(var h=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)h[p][d]!==this.bounds[p][d]&&(f=!0),this.bounds[p][d]=h[p][d];if(\"ticks\"in t)for(r=t.ticks,c=!0,this.autoTicks=!1,p=0;p<3;++p)this.tickSpacing[p]=0;else a(\"tickSpacing\")&&(this.autoTicks=!0,f=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in 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v=l(\"labels\");l(\"labelFont\")&&(v=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),u(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),u(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),u(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),u(\"gridColor\"),o(\"zeroEnable\"),u(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),u(\"backgroundColor\"),this._text?this._text&&(v||c)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&c&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,u=n[e],c=0;c<3;++c)if(e!==c){var f=a,h=s,p=o,d=l;u&1<0?(p[c]=-1,d[c]=0):(p[c]=0,d[c]=1)}}var v=[0,0,0],g={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var y=[0,0,0],m=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||g;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,c=o(r,n,i,a,s),f=c.cubeEdges,h=c.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=f[A],this.lastCubeProps.axis[A]=h[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,f,h);e=this.gl;var S,E,L,C=v;for(A=0;A<3;++A)this.backgroundEnable[A]?C[A]=h[A]:C[A]=0;for(this._background.draw(r,n,i,a,C,this.backgroundColor),this._lines.bind(r,n,i,this),A=0;A<3;++A){var P=[0,0,0];h[A]>0?P[A]=a[1][A]:P[A]=a[0][A];for(var O=0;O<2;++O){var I=(A+1+O)%3,D=(A+1+(1^O))%3;this.gridEnable[I]&&this._lines.drawGrid(I,D,this.bounds,P,this.gridColor[I],this.gridWidth[I]*this.pixelRatio)}for(O=0;O<2;++O)I=(A+1+O)%3,D=(A+1+(1^O))%3,this.zeroEnable[D]&&Math.min(a[0][D],a[1][D])<=0&&Math.max(a[0][D],a[1][D])>=0&&this._lines.drawZero(I,D,this.bounds,P,this.zeroLineColor[D],this.zeroLineWidth[D]*this.pixelRatio)}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var z=u(y,M[A].primalMinor),R=u(m,M[A].mirrorMinor),F=this.lineTickLength;for(O=0;O<3;++O){var B=k/r[5*O];z[O]*=F[O]*B,R[O]*=F[O]*B}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,z,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,R,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}function N(t){(L=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio),A=0;A<3;++A){var U=M[A].primalMinor,V=M[A].mirrorMinor,H=u(x,M[A].primalOffset);for(O=0;O<3;++O)this.lineTickEnable[A]&&(H[O]+=k*U[O]*Math.max(this.lineTickLength[O],0)/r[5*O]);var q=[0,0,0];if(q[A]=1,this.tickEnable[A]){for(-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]=\"auto\"):this.tickAlign[A]=-1,E=1,\"auto\"===(S=[this.tickAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),L=[0,0,0],j(A,U,V),O=0;O<3;++O)H[O]+=k*U[O]*this.tickPad[O]/r[5*O];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],H,this.tickColor[A],q,L,S)}if(this.labelEnable[A]){for(E=0,L=[0,0,0],this.labels[A].length>4&&(N(A),E=1),\"auto\"===(S=[this.labelAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),O=0;O<3;++O)H[O]+=k*U[O]*this.labelPad[O]/r[5*O];H[A]+=.5*(a[0][A]+a[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],H,this.labelColor[A],[0,0,0],L,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},1011:function(t,e,r){\"use strict\";t.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var u=(l+1)%3,c=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[u]=d;for(var v=-1;v<=1;v+=2)f[c]=v,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var g=u;u=c,c=g}var y=n(t,new Float32Array(e)),m=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:y,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:y,type:t.FLOAT,size:3,offset:12,stride:24}],m),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,y,x,b)};var n=r(5827),i=r(2944),a=r(1943).bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},2864:function(t,e,r){\"use strict\";t.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var m=0,x=0;x<2;++x){c[2]=a[x][2];for(var b=0;b<2;++b){c[1]=a[b][1];for(var _=0;_<2;++_)c[0]=a[_][0],h(l[m],c,s),m+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)u[x][k]=l[x][k]/T;p&&(u[x][2]*=-1),T<0&&(w<0||u[x][2]E&&(w|=1<E&&(w|=1<u[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x)(N=R^1<u[B][0]&&(B=N))}var j=v;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===z?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=g,H=w;for(A=0;A<3;++A)V[A]=H&1< HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n b - PI :\\n b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n // if ratio is set to 0.5 then it is 50%, 50%.\\n // when using a higher ratio e.g. 0.75 the result would\\n // likely be more horizontal than vertical.\\n\\n float b = positive_angle(a);\\n\\n return\\n (b < ( ratio) * HALF_PI) ? 0.0 :\\n (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n 0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n float b = positive_angle(a);\\n float div = TWO_PI / float(n);\\n float c = roundTo(b, div);\\n return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n return\\n (option > 2) ? look_round_n_directions(rawAngle + delta, option) : // option 3-n: round to n directions\\n (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n (option == 1) ? rawAngle + delta : // use free angle, and flip to align with one direction of the axis\\n (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n (option ==-1) ? 0.0 : // useful for backward compatibility, all texts remains horizontal\\n rawAngle; // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n (axis.y == 0.0) &&\\n (axis.z == 0.0);\\n\\nvoid main() {\\n //Compute world offset\\n float axisDistance = position.z;\\n vec3 dataPosition = axisDistance * axis + offset;\\n\\n float beta = angle; // i.e. user defined attributes for each tick\\n\\n float axisAngle;\\n float clipAngle;\\n float flip;\\n\\n if (enableAlign) {\\n axisAngle = (isAxisTitle) ? HALF_PI :\\n computeViewAngle(dataPosition, dataPosition + axis);\\n clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n beta += applyAlignOption(clipAngle, flip * PI);\\n }\\n\\n //Compute plane offset\\n vec2 planeCoord = position.xy * pixelScale;\\n\\n mat2 planeXform = scale * mat2(\\n cos(beta), sin(beta),\\n -sin(beta), cos(beta)\\n );\\n\\n vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n //Compute clip position\\n vec3 clipPosition = project(dataPosition);\\n\\n //Apply text offset in clip coordinates\\n clipPosition += vec3(viewOffset, 0.0);\\n\\n //Done\\n gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n gl_FragColor = color;\\n}\"]);e.f=function(t){return i(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n vec3 realNormal = signAxis * normal;\\n\\n if(dot(realNormal, enable) > 0.0) {\\n vec3 minRange = min(bounds[0], bounds[1]);\\n vec3 maxRange = max(bounds[0], bounds[1]);\\n vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n } else {\\n gl_Position = vec4(0,0,0,0);\\n }\\n\\n colorChannel = abs(realNormal);\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n gl_FragColor = colorChannel.x * colors[0] +\\n colorChannel.y * colors[1] +\\n colorChannel.z * colors[2];\\n}\"]);e.bg=function(t){return i(t,u,c,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},9557:function(t,e,r){\"use strict\";t.exports=function(t,e,r,i,o,l){var u=n(t),f=a(t,[{buffer:u,size:3}]),h=s(t);h.attributes.position.location=0;var p=new c(t,h,u,f);return p.update(e,r,i,o,l),p};var n=r(5827),a=r(2944),o=r(875),s=r(1943).f,l=window||i.global||{},u=l.__TEXT_CACHE||{};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}l.__TEXT_CACHE={};var f=c.prototype,h=[0,0];f.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,h[0]=this.gl.drawingBufferWidth,h[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=h},f.unbind=function(){this.vao.unbind()},f.update=function(t,e,r,n,i){var a=[];function s(t,e,r,n,i,s){var l=u[r];l||(l=u[r]={});var c=l[e];c||(c=l[e]=function(t,e){try{return o(t,e)}catch(e){return console.warn('error vectorizing text:\"'+t+'\" error:',e),{cells:[],positions:[]}}}(e,{triangles:!0,font:r,textAlign:\"center\",textBaseline:\"middle\",lineSpacing:i,styletags:s}));for(var f=(n||12)/12,h=c.positions,p=c.cells,d=0,v=p.length;d=0;--y){var m=h[g[y]];a.push(f*m[0],-f*m[1],t)}}for(var l=[0,0,0],c=[0,0,0],f=[0,0,0],h=[0,0,0],p={breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},d=0;d<3;++d){f[d]=a.length/3|0,s(.5*(t[0][d]+t[1][d]),e[d],r[d],12,1.25,p),h[d]=(a.length/3|0)-f[d],l[d]=a.length/3|0;for(var v=0;v=0&&(i=r.length-n-1);var a=Math.pow(10,i),o=Math.round(t*e*a),s=o+\"\";if(s.indexOf(\"e\")>=0)return s;var l=o/a,u=o%a;o<0?(l=0|-Math.ceil(l),u=0|-u):(l=0|Math.floor(l),u|=0);var c=\"\"+l;if(o<0&&(c=\"-\"+c),i){for(var f=\"\"+u;f.length=t[0][i];--o)a.push({x:o*e[i],text:r(e[i],o)});n.push(a)}return n},e.equal=function(t,e){for(var r=0;r<3;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;nr)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function c(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=u(this.gl,this.type,this.length,this.usage,t.data,e):this.length=u(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=u(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?c(t,\"uint16\"):c(t,\"float32\"),this.length=u(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=u(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},t.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var i=t.createBuffer(),a=new s(t,r,i,0,n);return a.update(e),a}},1140:function(t,e,r){\"use strict\";var n=r(2858);t.exports=function(t,e){var r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,u=1/0,c=-1/0,f=1/0,h=-1/0,p=null,d=null,v=[],g=1/0,y=!1,m=0;mo&&(o=n.length(b)),m){var _=2*n.distance(p,x)/(n.length(d)+n.length(b));_?(g=Math.min(g,_),y=!1):y=!0}y||(p=x,d=b),v.push(b)}var w=[s,u,f],T=[l,c,h];e&&(e[0]=w,e[1]=T),0===o&&(o=1);var k=1/o;isFinite(g)||(g=1),a.vectorScale=g;var A=t.coneSize||.5;t.absoluteConeSize&&(A=t.absoluteConeSize*k),a.coneScale=A,m=0;for(var M=0;m=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=c({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return u(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,v=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],v=+t.vertexIntensityBounds[1];else for(var g=0;g0){var v=this.triShader;v.bind(),v.uniforms=u,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?i.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},t.exports=function(t,e,r){var s=r.shaders;1===arguments.length&&(t=(e=t).gl);var l=function(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}(t,s),c=function(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}(t,s),f=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));f.generateMipmap(),f.minFilter=t.LINEAR_MIPMAP_LINEAR,f.magFilter=t.LINEAR;var p=i(t),d=i(t),v=i(t),g=i(t),y=i(t),m=new h(t,f,l,c,p,d,y,v,g,a(t,[{buffer:p,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:v,type:t.FLOAT,size:4},{buffer:g,type:t.FLOAT,size:2},{buffer:d,type:t.FLOAT,size:4}]),r.traceType||\"cone\");return m.update(e),m}},7234:function(t,e,r){var n=r(6832),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n// segment + 0 top vertex\\n// segment + 1 perimeter vertex a+1\\n// segment + 2 perimeter vertex a\\n// segment + 3 center base vertex\\n// segment + 4 perimeter vertex a\\n// segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n const float segmentCount = 8.0;\\n\\n float index = rawIndex - floor(rawIndex /\\n (segmentCount * 6.0)) *\\n (segmentCount * 6.0);\\n\\n float segment = floor(0.001 + index/6.0);\\n float segmentIndex = index - (segment*6.0);\\n\\n normal = -normalize(d);\\n\\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n return mix(vec3(0.0), -d, coneOffset);\\n }\\n\\n float nextAngle = (\\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\\n (segmentIndex > 4.99 && segmentIndex < 5.01)\\n ) ? 1.0 : 0.0;\\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n vec3 v2 = v1 - d;\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d)*0.25;\\n vec3 y = v * sin(angle) * length(d)*0.25;\\n vec3 v3 = v2 + x + y;\\n if (segmentIndex < 3.0) {\\n vec3 tx = u * sin(angle);\\n vec3 ty = v * -cos(angle);\\n vec3 tangent = tx + ty;\\n normal = normalize(cross(v3 - v1, tangent));\\n }\\n\\n if (segmentIndex == 0.0) {\\n return mix(d, vec3(0.0), coneOffset);\\n }\\n return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n // Scale the vector magnitude to stay constant with\\n // model & view changes.\\n vec3 normal;\\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * conePosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n // vec4 m_position = model * vec4(conePosition, 1.0);\\n vec4 t_position = view * conePosition;\\n gl_Position = projection * t_position;\\n\\n f_color = color;\\n f_data = conePosition.xyz;\\n f_position = position.xyz;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n// segment + 0 top vertex\\n// segment + 1 perimeter vertex a+1\\n// segment + 2 perimeter vertex a\\n// segment + 3 center base vertex\\n// segment + 4 perimeter vertex a\\n// segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n const float segmentCount = 8.0;\\n\\n float index = rawIndex - floor(rawIndex /\\n (segmentCount * 6.0)) *\\n (segmentCount * 6.0);\\n\\n float segment = floor(0.001 + index/6.0);\\n float segmentIndex = index - (segment*6.0);\\n\\n normal = -normalize(d);\\n\\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n return mix(vec3(0.0), -d, coneOffset);\\n }\\n\\n float nextAngle = (\\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\\n (segmentIndex > 4.99 && segmentIndex < 5.01)\\n ) ? 1.0 : 0.0;\\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n vec3 v2 = v1 - d;\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d)*0.25;\\n vec3 y = v * sin(angle) * length(d)*0.25;\\n vec3 v3 = v2 + x + y;\\n if (segmentIndex < 3.0) {\\n vec3 tx = u * sin(angle);\\n vec3 ty = v * -cos(angle);\\n vec3 tangent = tx + ty;\\n normal = normalize(cross(v3 - v1, tangent));\\n }\\n\\n if (segmentIndex == 0.0) {\\n return mix(d, vec3(0.0), coneOffset);\\n }\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n vec3 normal;\\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n gl_Position = projection * view * conePosition;\\n f_id = id;\\n f_position = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec3\"}]},e.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec3\"}]}},1950:function(t){t.exports={0:\"NONE\",1:\"ONE\",2:\"LINE_LOOP\",3:\"LINE_STRIP\",4:\"TRIANGLES\",5:\"TRIANGLE_STRIP\",6:\"TRIANGLE_FAN\",256:\"DEPTH_BUFFER_BIT\",512:\"NEVER\",513:\"LESS\",514:\"EQUAL\",515:\"LEQUAL\",516:\"GREATER\",517:\"NOTEQUAL\",518:\"GEQUAL\",519:\"ALWAYS\",768:\"SRC_COLOR\",769:\"ONE_MINUS_SRC_COLOR\",770:\"SRC_ALPHA\",771:\"ONE_MINUS_SRC_ALPHA\",772:\"DST_ALPHA\",773:\"ONE_MINUS_DST_ALPHA\",774:\"DST_COLOR\",775:\"ONE_MINUS_DST_COLOR\",776:\"SRC_ALPHA_SATURATE\",1024:\"STENCIL_BUFFER_BIT\",1028:\"FRONT\",1029:\"BACK\",1032:\"FRONT_AND_BACK\",1280:\"INVALID_ENUM\",1281:\"INVALID_VALUE\",1282:\"INVALID_OPERATION\",1285:\"OUT_OF_MEMORY\",1286:\"INVALID_FRAMEBUFFER_OPERATION\",2304:\"CW\",2305:\"CCW\",2849:\"LINE_WIDTH\",2884:\"CULL_FACE\",2885:\"CULL_FACE_MODE\",2886:\"FRONT_FACE\",2928:\"DEPTH_RANGE\",2929:\"DEPTH_TEST\",2930:\"DEPTH_WRITEMASK\",2931:\"DEPTH_CLEAR_VALUE\",2932:\"DEPTH_FUNC\",2960:\"STENCIL_TEST\",2961:\"STENCIL_CLEAR_VALUE\",2962:\"STENCIL_FUNC\",2963:\"STENCIL_VALUE_MASK\",2964:\"STENCIL_FAIL\",2965:\"STENCIL_PASS_DEPTH_FAIL\",2966:\"STENCIL_PASS_DEPTH_PASS\",2967:\"STENCIL_REF\",2968:\"STENCIL_WRITEMASK\",2978:\"VIEWPORT\",3024:\"DITHER\",3042:\"BLEND\",3088:\"SCISSOR_BOX\",3089:\"SCISSOR_TEST\",3106:\"COLOR_CLEAR_VALUE\",3107:\"COLOR_WRITEMASK\",3317:\"UNPACK_ALIGNMENT\",3333:\"PACK_ALIGNMENT\",3379:\"MAX_TEXTURE_SIZE\",3386:\"MAX_VIEWPORT_DIMS\",3408:\"SUBPIXEL_BITS\",3410:\"RED_BITS\",3411:\"GREEN_BITS\",3412:\"BLUE_BITS\",3413:\"ALPHA_BITS\",3414:\"DEPTH_BITS\",3415:\"STENCIL_BITS\",3553:\"TEXTURE_2D\",4352:\"DONT_CARE\",4353:\"FASTEST\",4354:\"NICEST\",5120:\"BYTE\",5121:\"UNSIGNED_BYTE\",5122:\"SHORT\",5123:\"UNSIGNED_SHORT\",5124:\"INT\",5125:\"UNSIGNED_INT\",5126:\"FLOAT\",5386:\"INVERT\",5890:\"TEXTURE\",6401:\"STENCIL_INDEX\",6402:\"DEPTH_COMPONENT\",6406:\"ALPHA\",6407:\"RGB\",6408:\"RGBA\",6409:\"LUMINANCE\",6410:\"LUMINANCE_ALPHA\",7680:\"KEEP\",7681:\"REPLACE\",7682:\"INCR\",7683:\"DECR\",7936:\"VENDOR\",7937:\"RENDERER\",7938:\"VERSION\",9728:\"NEAREST\",9729:\"LINEAR\",9984:\"NEAREST_MIPMAP_NEAREST\",9985:\"LINEAR_MIPMAP_NEAREST\",9986:\"NEAREST_MIPMAP_LINEAR\",9987:\"LINEAR_MIPMAP_LINEAR\",10240:\"TEXTURE_MAG_FILTER\",10241:\"TEXTURE_MIN_FILTER\",10242:\"TEXTURE_WRAP_S\",10243:\"TEXTURE_WRAP_T\",10497:\"REPEAT\",10752:\"POLYGON_OFFSET_UNITS\",16384:\"COLOR_BUFFER_BIT\",32769:\"CONSTANT_COLOR\",32770:\"ONE_MINUS_CONSTANT_COLOR\",32771:\"CONSTANT_ALPHA\",32772:\"ONE_MINUS_CONSTANT_ALPHA\",32773:\"BLEND_COLOR\",32774:\"FUNC_ADD\",32777:\"BLEND_EQUATION_RGB\",32778:\"FUNC_SUBTRACT\",32779:\"FUNC_REVERSE_SUBTRACT\",32819:\"UNSIGNED_SHORT_4_4_4_4\",32820:\"UNSIGNED_SHORT_5_5_5_1\",32823:\"POLYGON_OFFSET_FILL\",32824:\"POLYGON_OFFSET_FACTOR\",32854:\"RGBA4\",32855:\"RGB5_A1\",32873:\"TEXTURE_BINDING_2D\",32926:\"SAMPLE_ALPHA_TO_COVERAGE\",32928:\"SAMPLE_COVERAGE\",32936:\"SAMPLE_BUFFERS\",32937:\"SAMPLES\",32938:\"SAMPLE_COVERAGE_VALUE\",32939:\"SAMPLE_COVERAGE_INVERT\",32968:\"BLEND_DST_RGB\",32969:\"BLEND_SRC_RGB\",32970:\"BLEND_DST_ALPHA\",32971:\"BLEND_SRC_ALPHA\",33071:\"CLAMP_TO_EDGE\",33170:\"GENERATE_MIPMAP_HINT\",33189:\"DEPTH_COMPONENT16\",33306:\"DEPTH_STENCIL_ATTACHMENT\",33635:\"UNSIGNED_SHORT_5_6_5\",33648:\"MIRRORED_REPEAT\",33901:\"ALIASED_POINT_SIZE_RANGE\",33902:\"ALIASED_LINE_WIDTH_RANGE\",33984:\"TEXTURE0\",33985:\"TEXTURE1\",33986:\"TEXTURE2\",33987:\"TEXTURE3\",33988:\"TEXTURE4\",33989:\"TEXTURE5\",33990:\"TEXTURE6\",33991:\"TEXTURE7\",33992:\"TEXTURE8\",33993:\"TEXTURE9\",33994:\"TEXTURE10\",33995:\"TEXTURE11\",33996:\"TEXTURE12\",33997:\"TEXTURE13\",33998:\"TEXTURE14\",33999:\"TEXTURE15\",34e3:\"TEXTURE16\",34001:\"TEXTURE17\",34002:\"TEXTURE18\",34003:\"TEXTURE19\",34004:\"TEXTURE20\",34005:\"TEXTURE21\",34006:\"TEXTURE22\",34007:\"TEXTURE23\",34008:\"TEXTURE24\",34009:\"TEXTURE25\",34010:\"TEXTURE26\",34011:\"TEXTURE27\",34012:\"TEXTURE28\",34013:\"TEXTURE29\",34014:\"TEXTURE30\",34015:\"TEXTURE31\",34016:\"ACTIVE_TEXTURE\",34024:\"MAX_RENDERBUFFER_SIZE\",34041:\"DEPTH_STENCIL\",34055:\"INCR_WRAP\",34056:\"DECR_WRAP\",34067:\"TEXTURE_CUBE_MAP\",34068:\"TEXTURE_BINDING_CUBE_MAP\",34069:\"TEXTURE_CUBE_MAP_POSITIVE_X\",34070:\"TEXTURE_CUBE_MAP_NEGATIVE_X\",34071:\"TEXTURE_CUBE_MAP_POSITIVE_Y\",34072:\"TEXTURE_CUBE_MAP_NEGATIVE_Y\",34073:\"TEXTURE_CUBE_MAP_POSITIVE_Z\",34074:\"TEXTURE_CUBE_MAP_NEGATIVE_Z\",34076:\"MAX_CUBE_MAP_TEXTURE_SIZE\",34338:\"VERTEX_ATTRIB_ARRAY_ENABLED\",34339:\"VERTEX_ATTRIB_ARRAY_SIZE\",34340:\"VERTEX_ATTRIB_ARRAY_STRIDE\",34341:\"VERTEX_ATTRIB_ARRAY_TYPE\",34342:\"CURRENT_VERTEX_ATTRIB\",34373:\"VERTEX_ATTRIB_ARRAY_POINTER\",34466:\"NUM_COMPRESSED_TEXTURE_FORMATS\",34467:\"COMPRESSED_TEXTURE_FORMATS\",34660:\"BUFFER_SIZE\",34661:\"BUFFER_USAGE\",34816:\"STENCIL_BACK_FUNC\",34817:\"STENCIL_BACK_FAIL\",34818:\"STENCIL_BACK_PASS_DEPTH_FAIL\",34819:\"STENCIL_BACK_PASS_DEPTH_PASS\",34877:\"BLEND_EQUATION_ALPHA\",34921:\"MAX_VERTEX_ATTRIBS\",34922:\"VERTEX_ATTRIB_ARRAY_NORMALIZED\",34930:\"MAX_TEXTURE_IMAGE_UNITS\",34962:\"ARRAY_BUFFER\",34963:\"ELEMENT_ARRAY_BUFFER\",34964:\"ARRAY_BUFFER_BINDING\",34965:\"ELEMENT_ARRAY_BUFFER_BINDING\",34975:\"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING\",35040:\"STREAM_DRAW\",35044:\"STATIC_DRAW\",35048:\"DYNAMIC_DRAW\",35632:\"FRAGMENT_SHADER\",35633:\"VERTEX_SHADER\",35660:\"MAX_VERTEX_TEXTURE_IMAGE_UNITS\",35661:\"MAX_COMBINED_TEXTURE_IMAGE_UNITS\",35663:\"SHADER_TYPE\",35664:\"FLOAT_VEC2\",35665:\"FLOAT_VEC3\",35666:\"FLOAT_VEC4\",35667:\"INT_VEC2\",35668:\"INT_VEC3\",35669:\"INT_VEC4\",35670:\"BOOL\",35671:\"BOOL_VEC2\",35672:\"BOOL_VEC3\",35673:\"BOOL_VEC4\",35674:\"FLOAT_MAT2\",35675:\"FLOAT_MAT3\",35676:\"FLOAT_MAT4\",35678:\"SAMPLER_2D\",35680:\"SAMPLER_CUBE\",35712:\"DELETE_STATUS\",35713:\"COMPILE_STATUS\",35714:\"LINK_STATUS\",35715:\"VALIDATE_STATUS\",35716:\"INFO_LOG_LENGTH\",35717:\"ATTACHED_SHADERS\",35718:\"ACTIVE_UNIFORMS\",35719:\"ACTIVE_UNIFORM_MAX_LENGTH\",35720:\"SHADER_SOURCE_LENGTH\",35721:\"ACTIVE_ATTRIBUTES\",35722:\"ACTIVE_ATTRIBUTE_MAX_LENGTH\",35724:\"SHADING_LANGUAGE_VERSION\",35725:\"CURRENT_PROGRAM\",36003:\"STENCIL_BACK_REF\",36004:\"STENCIL_BACK_VALUE_MASK\",36005:\"STENCIL_BACK_WRITEMASK\",36006:\"FRAMEBUFFER_BINDING\",36007:\"RENDERBUFFER_BINDING\",36048:\"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE\",36049:\"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME\",36050:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL\",36051:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE\",36053:\"FRAMEBUFFER_COMPLETE\",36054:\"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\",36055:\"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\",36057:\"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\",36061:\"FRAMEBUFFER_UNSUPPORTED\",36064:\"COLOR_ATTACHMENT0\",36096:\"DEPTH_ATTACHMENT\",36128:\"STENCIL_ATTACHMENT\",36160:\"FRAMEBUFFER\",36161:\"RENDERBUFFER\",36162:\"RENDERBUFFER_WIDTH\",36163:\"RENDERBUFFER_HEIGHT\",36164:\"RENDERBUFFER_INTERNAL_FORMAT\",36168:\"STENCIL_INDEX8\",36176:\"RENDERBUFFER_RED_SIZE\",36177:\"RENDERBUFFER_GREEN_SIZE\",36178:\"RENDERBUFFER_BLUE_SIZE\",36179:\"RENDERBUFFER_ALPHA_SIZE\",36180:\"RENDERBUFFER_DEPTH_SIZE\",36181:\"RENDERBUFFER_STENCIL_SIZE\",36194:\"RGB565\",36336:\"LOW_FLOAT\",36337:\"MEDIUM_FLOAT\",36338:\"HIGH_FLOAT\",36339:\"LOW_INT\",36340:\"MEDIUM_INT\",36341:\"HIGH_INT\",36346:\"SHADER_COMPILER\",36347:\"MAX_VERTEX_UNIFORM_VECTORS\",36348:\"MAX_VARYING_VECTORS\",36349:\"MAX_FRAGMENT_UNIFORM_VECTORS\",37440:\"UNPACK_FLIP_Y_WEBGL\",37441:\"UNPACK_PREMULTIPLY_ALPHA_WEBGL\",37442:\"CONTEXT_LOST_WEBGL\",37443:\"UNPACK_COLORSPACE_CONVERSION_WEBGL\",37444:\"BROWSER_DEFAULT_WEBGL\"}},6603:function(t,e,r){var 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n=r(8931);t.exports=function(t,e,r,n){i||(i=t.FRAMEBUFFER_UNSUPPORTED,a=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,o=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,s=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var u=t.getExtension(\"WEBGL_draw_buffers\");if(!l&&u&&function(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);l=new Array(r+1);for(var n=0;n<=r;++n){for(var i=new Array(r),a=0;ac||r<0||r>c)throw new Error(\"gl-fbo: Parameters are too large for FBO\");var f=1;if(\"color\"in(n=n||{})){if((f=Math.max(0|n.color,0))<0)throw new Error(\"gl-fbo: Must specify a nonnegative number of colors\");if(f>1){if(!u)throw new Error(\"gl-fbo: Multiple draw buffer extension not supported\");if(f>t.getParameter(u.MAX_COLOR_ATTACHMENTS_WEBGL))throw new Error(\"gl-fbo: Context does not support \"+f+\" draw buffers\")}}var h=t.UNSIGNED_BYTE,p=t.getExtension(\"OES_texture_float\");if(n.float&&f>0){if(!p)throw new Error(\"gl-fbo: Context does not support floating point textures\");h=t.FLOAT}else 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x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){for(t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null),y=0;yi||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=u(n),o=0;o>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var v=i.attributes;return this.positionBuffer.bind(),v.position.pointer(),this.weightBuffer.bind(),v.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),v.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var u,c,f,p,d=t.colorLevels||[0],v=t.colorValues||[0,0,0,1],g=d.length,y=this.bounds;l?(u=y[0]=r[0],c=y[1]=o[0],f=y[2]=r[r.length-1],p=y[3]=o[o.length-1]):(u=y[0]=r[0]+(r[1]-r[0])/2,c=y[1]=o[0]+(o[1]-o[0])/2,f=y[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=y[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var m=1/(f-u),x=1/(p-c),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),A=a.mallocUint8(2*w),M=a.mallocUint32(w),S=0,E=l?b-1:b,L=l?_-1:_,C=0;C max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float dashScale;\\nuniform float opacity;\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n if (\\n outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n fragColor.a * opacity == 0.\\n ) discard;\\n\\n float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n if(dashWeight < 0.5) {\\n discard;\\n }\\n gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX 1.70141184e38\\n#define FLOAT_MIN 1.17549435e-38\\n\\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\\nvec4 packFloat(float v) {\\n float av = abs(v);\\n\\n //Handle special cases\\n if(av < FLOAT_MIN) {\\n return vec4(0.0, 0.0, 0.0, 0.0);\\n } else if(v > FLOAT_MAX) {\\n return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n } else if(v < -FLOAT_MAX) {\\n return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n }\\n\\n vec4 c = vec4(0,0,0,0);\\n\\n //Compute exponent and mantissa\\n float e = floor(log2(av));\\n float m = av * pow(2.0, -e) - 1.0;\\n\\n //Unpack mantissa\\n c[1] = floor(128.0 * m);\\n m -= c[1] / 128.0;\\n c[2] = floor(32768.0 * m);\\n m -= c[2] / 32768.0;\\n c[3] = floor(8388608.0 * m);\\n\\n //Unpack exponent\\n float ebias = e + 127.0;\\n c[0] = floor(ebias / 2.0);\\n ebias -= c[0] * 2.0;\\n c[1] += floor(ebias) * 128.0;\\n\\n //Unpack sign bit\\n c[0] += 128.0 * step(0.0, -v);\\n\\n //Scale back to range\\n return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];e.createShader=function(t){return i(t,a,o,null,l)},e.createPickShader=function(t){return i(t,a,s,null,l)}},6086:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),c=u(new Array(1024),[256,1,4]),p=0;p<1024;++p)c.data[p]=255;var d=a(e,c);d.wrap=e.REPEAT;var v=new y(e,r,o,s,l,d);return v.update(t),v};var n=r(5827),i=r(2944),a=r(8931),o=new Uint8Array(4),s=new Float32Array(o.buffer),l=r(5070),u=r(5050),c=r(248),f=c.createShader,h=c.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function v(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function g(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function y(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var m=y.prototype;m.isTransparent=function(){return this.hasAlpha},m.isOpaque=function(){return!this.hasAlpha},m.pickSlots=1,m.setPickBase=function(t){this.pickId=t},m.drawTransparent=m.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:v(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:v(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var i=[],a=[],o=[],s=0,c=0,f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],h=t.position||t.positions;if(h){var p=t.color||t.colors||[0,0,0,1],v=t.lineWidth||1,g=!1;t:for(e=1;e0){for(var w=0;w<24;++w)i.push(i[i.length-12]);c+=2,g=!0}continue t}f[0][r]=Math.min(f[0][r],b[r],_[r]),f[1][r]=Math.max(f[1][r],b[r],_[r])}Array.isArray(p[0])?(y=p.length>e-1?p[e-1]:p.length>0?p[p.length-1]:[0,0,0,1],m=p.length>e?p[e]:p.length>0?p[p.length-1]:[0,0,0,1]):y=m=p,3===y.length&&(y=[y[0],y[1],y[2],1]),3===m.length&&(m=[m[0],m[1],m[2],1]),!this.hasAlpha&&y[3]<1&&(this.hasAlpha=!0),x=Array.isArray(v)?v.length>e-1?v[e-1]:v.length>0?v[v.length-1]:[0,0,0,1]:v;var T=s;if(s+=d(b,_),g){for(r=0;r<2;++r)i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,y[0],y[1],y[2],y[3]);c+=2,g=!1}i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,y[0],y[1],y[2],y[3],b[0],b[1],b[2],_[0],_[1],_[2],T,-x,y[0],y[1],y[2],y[3],_[0],_[1],_[2],b[0],b[1],b[2],s,-x,m[0],m[1],m[2],m[3],_[0],_[1],_[2],b[0],b[1],b[2],s,x,m[0],m[1],m[2],m[3]),c+=4}}if(this.buffer.update(i),a.push(s),o.push(h[h.length-1].slice()),this.bounds=f,this.vertexCount=c,this.points=o,this.arcLength=a,\"dashes\"in t){var k=t.dashes.slice();for(k.unshift(0),e=1;e1.0001)return null;y+=g[f]}return Math.abs(y-1)>.001?null:[h,s(t,g),g]}},2056:function(t,e,r){var n=r(6832),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n , view\\n , projection\\n , inverseModel;\\nuniform vec3 eyePosition\\n , lightPosition;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n gl_Position = project(position);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * vec4(position , 1.0);\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n f_color = color;\\n f_data = position;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n , fresnel\\n , kambient\\n , kdiffuse\\n , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (f_color.a == 0.0 ||\\n outOfRange(clipBounds[0], clipBounds[1], f_data)\\n ) discard;\\n\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n f_color = color;\\n f_data = position;\\n f_uv = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n } else {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n }\\n gl_PointSize = pointSize;\\n f_color = color;\\n f_uv = uv;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n if(dot(pointR, pointR) > 0.25) {\\n discard;\\n }\\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n f_id = id;\\n f_position = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute float pointSize;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n } else {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n gl_PointSize = pointSize;\\n }\\n f_id = id;\\n f_position = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},e.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},e.pointShader={vertex:l,fragment:u,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},e.pickShader={vertex:c,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},e.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},e.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},8116:function(t,e,r){\"use strict\";var n=r(5158),i=r(5827),a=r(2944),o=r(8931),s=r(115),l=r(104),u=r(7437),c=r(5050),f=r(9156),h=r(7212),p=r(5306),d=r(2056),v=r(4340),g=d.meshShader,y=d.wireShader,m=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,T,k,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=c,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=u,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=g,this.edgeUVs=y,this.edgeIds=v,this.edgeVAO=m,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function A(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;rt&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function M(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function S(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function E(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function L(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()),this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};(s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;ai[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t],r.uniforms.angle=y[t],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t]&&T&&(c[1^t]-=M*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),c[1^t]=M*s[2+(1^t)]-1,d[t+2]&&(c[1^t]+=M*p*v[t+2],ki[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t+2],r.uniforms.angle=y[t+2],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t+2]&&T&&(c[1^t]+=M*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),v.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,u=r.pixelRatio;if(this.titleCount){for(var c=0;c<2;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),v.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,u=.5*(n[o+2]+n[o]),c=n[o+2]-n[o],f=a[o],v=a[o+2]-f,g=i[o],y=i[o+2]-g;p[o]=2*l/c*v/y,h[o]=2*(s-u)/c*v/y}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),v.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,u=t.bounds;for(o=0;o<2;++o){var c=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e=0){var v=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(v,e[1],v,e[3],p[d],h[d]):o.drawLine(e[0],v,e[2],v,p[d],h[d])}}for(d=0;d=0;--t)this.objects[t].dispose();for(this.objects.length=0,t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},u.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},u.removeObject=function(t){for(var e=this.objects,r=0;rMath.abs(e))u.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-u.lastT())/20;u.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=r(8161),i=r(1152),a=r(6145),o=r(6475),s=r(2565),l=r(5233)},8245:function(t,e,r){var n=r(6832),i=r(5158),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n uv = position;\\n gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);t.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},1059:function(t,e,r){\"use strict\";var n=r(4296),i=r(7453),a=r(2771),o=r(6496),s=r(2611),l=r(4234),u=r(8126),c=r(6145),f=r(1120),h=r(5268),p=r(8245),d=r(2321)({tablet:!0,featureDetect:!0});function v(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function g(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}return e>0?(r=Math.round(Math.pow(10,e)),Math.ceil(t/r)*r):Math.ceil(t)}function y(t){return\"boolean\"!=typeof t||t}t.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;e||(e=document.createElement(\"canvas\"),t.container?t.container.appendChild(e):document.body.appendChild(e));var r=t.gl;if(r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d})),!r)throw new Error(\"webgl not supported\");var m=t.bounds||[[-10,-10,-10],[10,10,10]],x=new v,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:w},k=t.axes||{},A=i(r,k);A.enable=!k.disable;var M=t.spikes||{},S=o(r,M),E=[],L=[],C=[],P=[],O=!0,I=!0,D={view:null,projection:new Array(16),model:new Array(16),_ortho:!1},z=(I=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),R=t.cameraObject||n(e,T),F={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:R,axes:A,axesPixels:null,spikes:S,bounds:m,objects:E,shape:z,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:y(t.autoResize),autoBounds:y(t.autoBounds),autoScale:!!t.autoScale,autoCenter:y(t.autoCenter),clipToBounds:y(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:D,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,I=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},B=[r.drawingBufferWidth/F.pixelRatio|0,r.drawingBufferHeight/F.pixelRatio|0];function N(){if(!F._stopped&&F.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*F.pixelRatio),a=0|Math.ceil(n*F.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",O=!0}}}function j(){for(var t=E.length,e=P.length,n=0;n0&&0===C[e-1];)C.pop(),P.pop().dispose()}function U(){if(F.contextLost)return!0;r.isContextLost()&&(F.contextLost=!0,F.mouseListener.enabled=!1,F.selection.object=null,F.oncontextloss&&F.oncontextloss())}F.autoResize&&N(),window.addEventListener(\"resize\",N),F.update=function(t){F._stopped||(t=t||{},O=!0,I=!0)},F.add=function(t){F._stopped||(t.axes=A,E.push(t),L.push(-1),O=!0,I=!0,j())},F.remove=function(t){if(!F._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),L.pop(),O=!0,I=!0,j())}},F.dispose=function(){if(!F._stopped&&(F._stopped=!0,window.removeEventListener(\"resize\",N),e.removeEventListener(\"webglcontextlost\",U),F.mouseListener.enabled=!1,!F.contextLost)){A.dispose(),S.dispose();for(var t=0;tx.distance)continue;for(var u=0;u 1.0) {\\n discard;\\n }\\n baseColor = mix(borderColor, color, step(radius, centerFraction));\\n gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n }\\n}\\n\"]),e.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n vec3 hgPosition = matrix * vec3(position, 1);\\n gl_Position = vec4(hgPosition.xy, 0, hgPosition.z);\\n gl_PointSize = pointSize;\\n\\n vec4 id = pickId + pickOffset;\\n id.y += floor(id.x / 256.0);\\n id.x -= floor(id.x / 256.0) * 256.0;\\n\\n id.z += floor(id.y / 256.0);\\n id.y -= floor(id.y / 256.0) * 256.0;\\n\\n id.w += floor(id.z / 256.0);\\n id.z -= floor(id.z / 256.0) * 256.0;\\n\\n fragId = id;\\n}\\n\"]),e.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n if(radius > 1.0) {\\n discard;\\n }\\n gl_FragColor = fragId / 255.0;\\n}\\n\"])},8271:function(t,e,r){\"use strict\";var n=r(5158),i=r(5827),a=r(5306),o=r(8023);function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}t.exports=function(t,e){var r=t.gl,a=new s(t,i(r),i(r),n(r,o.pointVertex,o.pointFragment),n(r,o.pickVertex,o.pickFragment));return a.update(e),t.addObject(a),a};var l,u,c=s.prototype;c.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},c.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),u=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e>>1;for(r=0;r=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),c=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=c<5,r.uniforms.pointSize=c,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(u[0]=255&t,u[1]=t>>8&255,u[2]=t>>16&255,u[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=u,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),c.draw=c.unifiedDraw,c.drawPick=c.unifiedDraw,c.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},6093:function(t){t.exports=function(t,e,r,n){var i,a,o,s,l,u=e[0],c=e[1],f=e[2],h=e[3],p=r[0],d=r[1],v=r[2],g=r[3];return(a=u*p+c*d+f*v+h*g)<0&&(a=-a,p=-p,d=-d,v=-v,g=-g),1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n),t[0]=s*u+l*p,t[1]=s*c+l*d,t[2]=s*f+l*v,t[3]=s*h+l*g,t}},8240:function(t){\"use strict\";t.exports=function(t){return t||0===t?t.toString():\"\"}},4123:function(t,e,r){\"use strict\";var n=r(875);t.exports=function(t,e,r){var a=i[e];if(a||(a=i[e]={}),t in a)return a[t];var o={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,u,c=n(t,o);if(r&&1!==r){for(l=0;l max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float scale = 1.0;\\n if(distance(highlightId, id) < 0.0001) {\\n scale = highlightScale;\\n }\\n\\n vec4 worldPosition = model * vec4(position, 1);\\n vec4 viewPosition = view * worldPosition;\\n viewPosition = viewPosition / viewPosition.w;\\n vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n gl_Position = clipPosition;\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = position;\\n }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float scale = pixelRatio;\\n if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n scale *= highlightScale;\\n }\\n\\n vec4 worldPosition = model * vec4(position, 1.0);\\n vec4 viewPosition = view * worldPosition;\\n vec4 clipPosition = projection * viewPosition;\\n clipPosition /= clipPosition.w;\\n\\n gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = position;\\n }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float lscale = pixelRatio * scale;\\n if(distance(highlightId, id) < 0.0001) {\\n lscale *= highlightScale;\\n }\\n\\n vec4 clipCenter = projection * view * model * vec4(position, 1);\\n vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n gl_Position = clipPosition;\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = dataPosition;\\n }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (\\n outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n interpColor.a * opacity == 0.\\n ) discard;\\n gl_FragColor = interpColor * opacity;\\n}\\n\"]),u=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:c},h={vertex:o,fragment:l,attributes:c},p={vertex:s,fragment:l,attributes:c},d={vertex:a,fragment:u,attributes:c},v={vertex:o,fragment:u,attributes:c},g={vertex:s,fragment:u,attributes:c};function y(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}e.createPerspective=function(t){return y(t,f)},e.createOrtho=function(t){return y(t,h)},e.createProject=function(t){return y(t,p)},e.createPickPerspective=function(t){return y(t,d)},e.createPickOrtho=function(t){return y(t,v)},e.createPickProject=function(t){return y(t,g)}},2182:function(t,e,r){\"use strict\";var n=r(3596),i=r(5827),a=r(2944),o=r(5306),s=r(104),l=r(9282),u=r(4123),c=r(8240),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function v(t){return!0===t||t>1?1:t}function g(t,e,r,n,i,a,o,s,l,u,c,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=u,this.pickOrthoShader=c,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}t.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),u=l.createPickOrtho(e),c=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),v=new g(e,r,n,o,f,h,p,d,a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),s,u,c);return v.update(t),v};var y=g.prototype;y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},y.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var m=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],A=[[0,0,0],[0,0,0]];function M(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}var L=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function C(t,e,r,n,i,a,o){var l=r.gl;if((a===r.projectHasAlpha||o)&&function(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,u=r.model||f,c=r.view||f,h=r.projection||f,d=e.axesBounds,v=function(t){for(var e=A,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],m[0]=2/o.drawingBufferWidth,m[1]=2/o.drawingBufferHeight,t.bind(),l.view=c,l.projection=h,l.screenSize=m,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=v,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var g=0;g<3;++g)if(a[g]){l.scale=e.projectScale[g],l.opacity=e.projectOpacity[g];for(var y=T,L=0;L<16;++L)y[L]=0;for(L=0;L<4;++L)y[5*L]=1;y[5*g]=0,i[g]<0?y[12+g]=d[0][g]:y[12+g]=d[1][g],s(y,u,y),l.model=y;var C=(g+1)%3,P=(g+2)%3,O=M(x),I=M(b);O[C]=1,I[P]=1;var D=p(0,0,0,S(_,O)),z=p(0,0,0,S(w,I));if(Math.abs(D[1])>Math.abs(z[1])){var R=D;D=z,z=R,R=O,O=I,I=R;var F=C;C=P,P=F}D[0]<0&&(O[C]=-1),z[1]>0&&(I[P]=-1);var B=0,N=0;for(L=0;L<4;++L)B+=Math.pow(u[4*C+L],2),N+=Math.pow(u[4*P+L],2);O[C]/=Math.sqrt(B),I[P]/=Math.sqrt(N),l.axes[0]=O,l.axes[1]=I,l.fragClipBounds[0]=E(k,v[0],g,-1e8),l.fragClipBounds[1]=E(k,v[1],g,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}(e,r,n,i),a===r.hasAlpha||o){t.bind();var u=t.uniforms;u.model=n.model||f,u.view=n.view||f,u.projection=n.projection||f,m[0]=2/l.drawingBufferWidth,m[1]=2/l.drawingBufferHeight,u.screenSize=m,u.highlightId=r.highlightId,u.highlightScale=r.highlightScale,u.fragClipBounds=L,u.clipBounds=r.axes.bounds,u.opacity=r.opacity,u.pickGroup=r.pickId/255,u.pixelRatio=i,r.vao.bind(),r.vao.draw(l.TRIANGLES,r.vertexCount),r.lineWidth>0&&(l.lineWidth(r.lineWidth*i),r.vao.draw(l.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function P(t,e,r,i){var a;a=Array.isArray(t)?e=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},y.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},y.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,\"projectOpacity\"in t){Array.isArray(t.projectOpacity)?this.projectOpacity=t.projectOpacity.slice():(r=+t.projectOpacity,this.projectOpacity=[r,r,r]);for(var n=0;n<3;++n)this.projectOpacity[n]=v(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=v(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var i,a,s=t.position,l=t.font||\"normal\",u=t.alignment||[0,0];if(2===u.length)i=u[0],a=u[1];else for(i=[],a=[],n=0;n0){var I=0,D=x,z=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(y)&&Array.isArray(y[0]);t:for(n=0;n<_;++n){for(m+=1,w=s[n],T=0;T<3;++T){if(isNaN(w[T])||!isFinite(w[T]))continue t;f[T]=Math.max(f[T],w[T]),c[T]=Math.min(c[T],w[T])}k=(N=P(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(U=F?n0?1-M[0][0]:Z<0?1+M[1][0]:1,Y*=Y>0?1-M[0][1]:Y<0?1+M[1][1]:1],X=k.cells||[],J=k.positions||[];for(T=0;T0){var y=r*c;o.drawBox(f-y,h-y,p+y,h+y,a),o.drawBox(f-y,d-y,p+y,d+y,a),o.drawBox(f-y,h-y,f+y,d+y,a),o.drawBox(p-y,h-y,p+y,d+y,a)}}}},s.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},s.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},2611:function(t,e,r){\"use strict\";t.exports=function(t,e){var r=e[0],a=e[1];return new l(t,n(t,r,a,{}),i.mallocUint8(r*a*4))};var n=r(4234),i=r(5306),a=r(5050),o=r(2288).nextPow2;function s(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function l(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}var u=l.prototype;Object.defineProperty(u,\"shape\",{get:function(){return this.gl?this.fbo.shape.slice():[0,0]},set:function(t){if(this.gl){this.fbo.shape=t;var e=this.fbo.shape[0],r=this.fbo.shape[1];if(r*e*4>this.buffer.length){i.free(this.buffer);for(var n=this.buffer=i.mallocUint8(o(r*e*4)),a=0;ar)for(t=r;te)for(t=e;t=0){for(var T=0|w.type.charAt(w.type.length-1),k=new Array(T),A=0;A=0;)M+=1;_[m]=M}var S=new Array(r.length);function E(){h.program=o.program(p,h._vref,h._fref,b,_);for(var t=0;t=0){if((d=h.charCodeAt(h.length-1)-48)<2||d>4)throw new n(\"\",\"Invalid data type for attribute \"+f+\": \"+h);s(t,e,p[0],i,d,a,f)}else{if(!(h.indexOf(\"mat\")>=0))throw new n(\"\",\"Unknown data type for attribute \"+f+\": \"+h);var d;if((d=h.charCodeAt(h.length-1)-48)<2||d>4)throw new n(\"\",\"Invalid data type for attribute \"+f+\": \"+h);l(t,e,p,i,d,a,f)}}}return a};var n=r(9068);function i(t,e,r,n,i,a){this._gl=t,this._wrapper=e,this._index=r,this._locations=n,this._dimension=i,this._constFunc=a}var a=i.prototype;a.pointer=function(t,e,r,n){var i=this,a=i._gl,o=i._locations[i._index];a.vertexAttribPointer(o,i._dimension,t||a.FLOAT,!!e,r||0,n||0),a.enableVertexAttribArray(o)},a.set=function(t,e,r,n){return this._constFunc(this._locations[this._index],t,e,r,n)},Object.defineProperty(a,\"location\",{get:function(){return this._locations[this._index]},set:function(t){return t!==this._locations[this._index]&&(this._locations[this._index]=0|t,this._wrapper.program=null),0|t}});var o=[function(t,e,r){return void 0===r.length?t.vertexAttrib1f(e,r):t.vertexAttrib1fv(e,r)},function(t,e,r,n){return void 0===r.length?t.vertexAttrib2f(e,r,n):t.vertexAttrib2fv(e,r)},function(t,e,r,n,i){return void 0===r.length?t.vertexAttrib3f(e,r,n,i):t.vertexAttrib3fv(e,r)},function(t,e,r,n,i,a){return void 0===r.length?t.vertexAttrib4f(e,r,n,i,a):t.vertexAttrib4fv(e,r)}];function s(t,e,r,n,a,s,l){var u=o[a],c=new i(t,e,r,n,a,u);Object.defineProperty(s,l,{set:function(e){return t.disableVertexAttribArray(n[r]),u(t,n[r],e),e},get:function(){return c},enumerable:!0})}function l(t,e,r,n,i,a,o){for(var l=new Array(i),u=new Array(i),c=0;c4)throw new i(\"\",\"Invalid uniform dimension type for matrix \"+name+\": \"+m);t[\"uniformMatrix\"+y+\"fv\"](s[f],!1,h);break}throw new i(\"\",\"Unknown uniform data type for \"+name+\": \"+m)}if((y=m.charCodeAt(m.length-1)-48)<2||y>4)throw new i(\"\",\"Invalid data type\");switch(m.charAt(0)){case\"b\":case\"i\":t[\"uniform\"+y+\"iv\"](s[f],h);break;case\"v\":t[\"uniform\"+y+\"fv\"](s[f],h);break;default:throw new i(\"\",\"Unrecognized data type for vector \"+name+\": \"+m)}}}}}}function u(t,e){if(\"object\"!=typeof e)return[[t,e]];var r=[];for(var n in e){var i=e[n],a=t;parseInt(n)+\"\"===n?a+=\"[\"+n+\"]\":a+=\".\"+n,\"object\"==typeof 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a||(a[s[0]]=[]),a=a[s[0]];for(var l=1;l1)for(var l=0;l 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n float segmentCount = 8.0;\\n\\n float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d);\\n vec3 y = v * sin(angle) * length(d);\\n vec3 v3 = x + y;\\n\\n normal = normalize(v3);\\n\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n // Scale the vector magnitude to stay constant with\\n // model & view changes.\\n vec3 normal;\\n vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * tubePosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n // vec4 m_position = model * vec4(tubePosition, 1.0);\\n vec4 t_position = view * tubePosition;\\n gl_Position = projection * t_position;\\n\\n f_color = color;\\n f_data = tubePosition.xyz;\\n f_position = position.xyz;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 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p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) 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f_id.xyz);\\n}\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec4\"}]},e.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec4\"}]}},7307:function(t,e,r){\"use strict\";var n=r(2858),i=r(4020),a=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"],o=function(t,e){var r,n=t.length;for(r=0;re)return r-1}return r},s=function(t,e,r){return tr?r:t},l=function(t){var e=1/0;t.sort((function(t,e){return t-e}));for(var r=t.length,n=1;nf-1||m>h-1||x>p-1)return n.create();var b,_,w,T,k,A,M=a[0][d],S=a[0][y],E=a[1][v],L=a[1][m],C=a[2][g],P=(l-M)/(S-M),O=(u-E)/(L-E),I=(c-C)/(a[2][x]-C);switch(isFinite(P)||(P=.5),isFinite(O)||(O=.5),isFinite(I)||(I=.5),r.reversedX&&(d=f-1-d,y=f-1-y),r.reversedY&&(v=h-1-v,m=h-1-m),r.reversedZ&&(g=p-1-g,x=p-1-x),r.filled){case 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e=t[0],r=t[1],n=t[2];return!(eb||r_||nw)},k=10*n.distance(e[0],e[1])/u,A=k*k,M=1,S=0,E=r.length;E>1&&(M=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=t.length,u=0;uS&&(S=F),z.push(F),g.push({points:P,velocities:O,divergences:z});for(var B=0;B<100*u&&P.lengthA&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,C),I=d(N),n.squaredDistance(D,N)-A>-1e-4*A&&(P.push(N),D=N,O.push(I),R=v(N,I),F=n.length(R),isFinite(F)&&F>S&&(S=F),z.push(F)),C=N}}var U=function(t,e,r,a){for(var o=0,s=0;s0)for(T=0;T<8;T++){var k=(T+1)%8;u.push(h[T],p[T],p[k],p[k],h[k],h[T]),f.push(m,y,y,y,m,m),d.push(v,g,g,g,v,v);var A=u.length;c.push([A-6,A-5,A-4],[A-3,A-2,A-1])}var M=h;h=p,p=M;var S=m;m=y,y=S;var E=v;v=g,g=E}return{positions:u,cells:c,vectors:f,vertexIntensity:d}}(t,r,a,o)})),f=[],h=[],p=[],d=[];for(s=0;s max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n if (\\n kill > 0.0 ||\\n vColor.a == 0.0 ||\\n outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\\n ) discard;\\n\\n vec3 N = normalize(surfaceNormal);\\n vec3 V = normalize(eyeDirection);\\n vec3 L = normalize(lightDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\\n float diffuse = 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e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},e.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},e.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},3754:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl,r=m(e),n=b(e),s=x(e),l=_(e),u=i(e),c=a(e,[{buffer:u,size:4,stride:w,offset:0},{buffer:u,size:3,stride:w,offset:16},{buffer:u,size:3,stride:w,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),v=o(e,1,S,e.RGBA,e.UNSIGNED_BYTE);v.minFilter=e.LINEAR,v.magFilter=e.LINEAR;var g=new E(e,[0,0],[[0,0,0],[0,0,0]],r,n,u,c,v,s,l,f,h,p,d,[0,0,0]),y={levels:[[],[],[]]};for(var T in t)y[T]=t[T];return y.colormap=y.colormap||\"jet\",g.update(y),g};var n=r(2288),i=r(5827),a=r(2944),o=r(8931),s=r(5306),l=r(9156),u=r(7498),c=r(7382),f=r(5050),h=r(4162),p=r(104),d=r(7437),v=r(5070),g=r(9144),y=r(9054),m=y.createShader,x=y.createContourShader,b=y.createPickShader,_=y.createPickContourShader,w=40,T=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],k=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],A=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function M(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=A[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();var S=256;function E(t,e,r,n,i,a,o,l,u,c,h,p,d,v,g){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=g,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new M([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=v,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var L=E.prototype;L.genColormap=function(t,e){var r=!1,n=c([l({colormap:t,nshades:S,format:\"rgba\"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;rt&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return u.divseq(n,255),this.hasAlphaScale=r,n},L.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},L.isOpaque=function(){return!this.isTransparent()},L.pickSlots=1,L.setPickBase=function(t){this.pickId=t};var C=[0,0,0],P={showSurface:!1,showContour:!1,projections:[T.slice(),T.slice(),T.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function O(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||C,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=P.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var u=P.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)u[i][n]=t.clipBounds[i][n];u[0][r]=-1e8,u[1][r]=1e8}return P.showSurface=o,P.showContour=s,P}var I={model:T,view:T,projection:T,inverseModel:T.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},D=T.slice(),z=[1,0,0,0,1,0,0,0,1];function R(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=I;n.model=t.model||T,n.view=t.view||T,n.projection=t.projection||T,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=z,n.vertexColor=this.vertexColor;var s=D;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var u=s[12+i];for(o=0;o<3;++o)u+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=u/l}var c=O(n,this);if(c.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=c.projections[i],this._shader.uniforms.clipBounds=c.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(c.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=A[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;c<2;++c)for(var f=c?a:1-a,h=0;h<2;++h)for(var p=i+c,d=s+h,g=f*(h?l:1-l),y=0;y<3;++y)u[y]+=this._field[y].get(p,d)*g;for(var m=this._pickResult.level,x=0;x<3;++x)if(m[x]=v.le(this.contourLevels[x],u[x]),m[x]<0)this.contourLevels[x].length>0&&(m[x]=0);else if(m[x]Math.abs(_-u[x])&&(m[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],y=0;y<3;++y)r.dataCoordinate[y]=this._field[y].get(r.index[0],r.index[1]);return r},L.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();u.assign(t.lo(1,1).hi(r[0],r[1]),e),u.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),u.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),u.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),u.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},L.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=B(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=B(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=B(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=j(t.contourColor)),\"contourProject\"in t&&(this.contourProject=B(t.contourProject,(function(t){return B(t,Boolean)}))),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=j(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=B(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=B(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0),\"colormap\"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var u=l[o];for(y=0;y<2;++y)if(u.shape[y]!==a[y])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],u)}}else if(t.ticks){var c=t.ticks;if(!Array.isArray(c)||2!==c.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=c[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var v=[0,0];v[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],v,0)}this._field[0].set(0,0,0);for(var y=0;y0){for(var xt=0;xt<5;++xt)$.pop();U-=1}continue t}$.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[Q]=et,this._contourCounts[Q]=rt}var bt=s.mallocFloat($.length);for(o=0;o<$.length;++o)bt[o]=$[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},L.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},L.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,u=(o+2)%3,c=this._field[o],f=this._field[l],p=this._field[u],d=h(c,r[o]),v=d.cells,g=d.positions;for(this._dynamicOffsets[o]=n,e=0;es||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=d(o,e.stride.slice()),u=0;\"float32\"===r?u=t.FLOAT:\"float64\"===r?(u=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?u=t.UNSIGNED_BYTE:(u=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var f,p,g=0;if(2===o.length)g=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])g=t.ALPHA;else if(2===o[2])g=t.LUMINANCE_ALPHA;else if(3===o[2])g=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");g=t.RGBA}}u!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(u=t.UNSIGNED_BYTE,l=!1);var y=e.size;if(l)f=0===e.offset&&e.data.length===y?e.data:e.data.subarray(e.offset,e.offset+y);else{var m=[o[2],o[2]*o[0],1];p=a.malloc(y,r);var x=n(p,o,m,0);\"float32\"!==r&&\"float64\"!==r||u!==t.UNSIGNED_BYTE?i.assign(x,e):c(x,e),f=p.subarray(0,y)}var b=v(t);return t.texImage2D(t.TEXTURE_2D,0,g,o[0],o[1],0,g,u,f),l||a.free(p),new h(t,b,o[0],o[1],g,u)}(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function u(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var c=function(t,e){i.muls(t,e,255)};function f(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function h(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var p=h.prototype;function d(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function v(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function g(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=v(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new h(t,o,e,r,n,i)}Object.defineProperties(p,{minFilter:{get:function(){return this._minFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,t),this._minFilter=t}},magFilter:{get:function(){return this._magFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,t),this._magFilter=t}},mipSamples:{get:function(){return this._anisoSamples},set:function(t){var e=this._anisoSamples;if(this._anisoSamples=0|Math.max(t,1),e!==this._anisoSamples){var r=this.gl.getExtension(\"EXT_texture_filter_anisotropic\");r&&this.gl.texParameterf(this.gl.TEXTURE_2D,r.TEXTURE_MAX_ANISOTROPY_EXT,this._anisoSamples)}return this._anisoSamples}},wrapS:{get:function(){return this._wrapS},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,t),this._wrapS=t}},wrapT:{get:function(){return this._wrapT},set:function(t){if(this.bind(),l.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,t),this._wrapT=t}},wrap:{get:function(){return this._wrapVector},set:function(t){if(Array.isArray(t)||(t=[t,t]),2!==t.length)throw new Error(\"gl-texture2d: Must specify wrap mode for rows and columns\");for(var e=0;e<2;++e)if(l.indexOf(t[e])<0)throw new Error(\"gl-texture2d: Unknown wrap mode \"+t);this._wrapS=t[0],this._wrapT=t[1];var r=this.gl;return this.bind(),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_S,this._wrapS),r.texParameteri(r.TEXTURE_2D,r.TEXTURE_WRAP_T,this._wrapT),t}},shape:{get:function(){return this._shapeVector},set:function(t){if(Array.isArray(t)){if(2!==t.length)throw new Error(\"gl-texture2d: Invalid texture shape\")}else t=[0|t,0|t];return 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e>t==t>0?o===a?(r+=1,o=0):o+=1:0===o?(o=a,r-=1):o-=1,n.pack(o,r)}},115:function(t,e){e.vertexNormals=function(t,e,r){for(var n=e.length,i=new Array(n),a=void 0===r?1e-6:r,o=0;oa){var b=i[u],_=1/Math.sqrt(g*m);for(x=0;x<3;++x){var w=(x+1)%3,T=(x+2)%3;b[x]+=_*(y[w]*v[T]-y[T]*v[w])}}}for(o=0;oa)for(_=1/Math.sqrt(k),x=0;x<3;++x)b[x]*=_;else for(x=0;x<3;++x)b[x]=0}return i},e.faceNormals=function(t,e,r){for(var n=t.length,i=new Array(n),a=void 0===r?1e-6:r,o=0;oa?1/Math.sqrt(p):0,u=0;u<3;++u)h[u]*=p;i[o]=h}return i}},567:function(t){\"use strict\";t.exports=function(t,e,r,n,i,a,o,s,l,u){var c=e+a+u;if(f>0){var f=Math.sqrt(c+1);t[0]=.5*(o-l)/f,t[1]=.5*(s-n)/f,t[2]=.5*(r-a)/f,t[3]=.5*f}else{var h=Math.max(e,a,u);f=Math.sqrt(2*h-c+1),e>=h?(t[0]=.5*f,t[1]=.5*(i+r)/f,t[2]=.5*(s+n)/f,t[3]=.5*(o-l)/f):a>=h?(t[0]=.5*(r+i)/f,t[1]=.5*f,t[2]=.5*(l+o)/f,t[3]=.5*(s-n)/f):(t[0]=.5*(n+s)/f,t[1]=.5*(o+l)/f,t[2]=.5*f,t[3]=.5*(r-i)/f)}return t}},7774:function(t,e,r){\"use strict\";t.exports=function(t){var e=(t=t||{}).center||[0,0,0],r=t.rotation||[0,0,0,1],n=t.radius||1;e=[].slice.call(e,0,3),c(r=[].slice.call(r,0,4),r);var i=new f(r,e,Math.log(n));return i.setDistanceLimits(t.zoomMin,t.zoomMax),(\"eye\"in t||\"up\"in t)&&i.lookAt(0,t.eye,t.center,t.up),i};var n=r(8444),i=r(3012),a=r(5950),o=r(7437),s=r(567);function l(t,e,r){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2))}function u(t,e,r,n){return Math.sqrt(Math.pow(t,2)+Math.pow(e,2)+Math.pow(r,2)+Math.pow(n,2))}function c(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=u(r,n,i,a);o>1e-6?(t[0]=r/o,t[1]=n/o,t[2]=i/o,t[3]=a/o):(t[0]=t[1]=t[2]=0,t[3]=1)}function f(t,e,r){this.radius=n([r]),this.center=n(e),this.rotation=n(t),this.computedRadius=this.radius.curve(0),this.computedCenter=this.center.curve(0),this.computedRotation=this.rotation.curve(0),this.computedUp=[.1,0,0],this.computedEye=[.1,0,0],this.computedMatrix=[.1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],this.recalcMatrix(0)}var h=f.prototype;h.lastT=function(){return Math.max(this.radius.lastT(),this.center.lastT(),this.rotation.lastT())},h.recalcMatrix=function(t){this.radius.curve(t),this.center.curve(t),this.rotation.curve(t);var e=this.computedRotation;c(e,e);var r=this.computedMatrix;a(r,e);var n=this.computedCenter,i=this.computedEye,o=this.computedUp,s=Math.exp(this.computedRadius[0]);i[0]=n[0]+s*r[2],i[1]=n[1]+s*r[6],i[2]=n[2]+s*r[10],o[0]=r[1],o[1]=r[5],o[2]=r[9];for(var l=0;l<3;++l){for(var u=0,f=0;f<3;++f)u+=r[l+4*f]*i[f];r[12+l]=-u}},h.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;n<16;++n)e[n]=r[n];return e}return r},h.idle=function(t){this.center.idle(t),this.radius.idle(t),this.rotation.idle(t)},h.flush=function(t){this.center.flush(t),this.radius.flush(t),this.rotation.flush(t)},h.pan=function(t,e,r,n){e=e||0,r=r||0,n=n||0,this.recalcMatrix(t);var i=this.computedMatrix,a=i[1],o=i[5],s=i[9],u=l(a,o,s);a/=u,o/=u,s/=u;var 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r,n,o,s,l,u,c,f,h,p=1,d=t.length,v=\"\";for(n=0;n=0),s.type){case\"b\":r=parseInt(r,10).toString(2);break;case\"c\":r=String.fromCharCode(parseInt(r,10));break;case\"d\":case\"i\":r=parseInt(r,10);break;case\"j\":r=JSON.stringify(r,null,s.width?parseInt(s.width):0);break;case\"e\":r=s.precision?parseFloat(r).toExponential(s.precision):parseFloat(r).toExponential();break;case\"f\":r=s.precision?parseFloat(r).toFixed(s.precision):parseFloat(r);break;case\"g\":r=s.precision?String(Number(r.toPrecision(s.precision))):parseFloat(r);break;case\"o\":r=(parseInt(r,10)>>>0).toString(8);break;case\"s\":r=String(r),r=s.precision?r.substring(0,s.precision):r;break;case\"t\":r=String(!!r),r=s.precision?r.substring(0,s.precision):r;break;case\"T\":r=Object.prototype.toString.call(r).slice(8,-1).toLowerCase(),r=s.precision?r.substring(0,s.precision):r;break;case\"u\":r=parseInt(r,10)>>>0;break;case\"v\":r=r.valueOf(),r=s.precision?r.substring(0,s.precision):r;break;case\"x\":r=(parseInt(r,10)>>>0).toString(16);break;case\"X\":r=(parseInt(r,10)>>>0).toString(16).toUpperCase()}i.json.test(s.type)?v+=r:(!i.number.test(s.type)||f&&!s.sign?h=\"\":(h=f?\"+\":\"-\",r=r.toString().replace(i.sign,\"\")),u=s.pad_char?\"0\"===s.pad_char?\"0\":s.pad_char.charAt(1):\" 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s[t]=n}(t),arguments)}function o(t,e){return a.apply(null,[t].concat(e||[]))}var s=Object.create(null);e.sprintf=a,e.vsprintf=o,\"undefined\"!=typeof window&&(window.sprintf=a,window.vsprintf=o,void 0===(n=function(){return{sprintf:a,vsprintf:o}}.call(e,r,e,t))||(t.exports=n))}()},4162:function(t,e,r){\"use strict\";t.exports=function(t,e){if(t.dimension<=0)return{positions:[],cells:[]};if(1===t.dimension)return function(t,e){for(var r=i(t,e),n=r.length,a=new Array(n),o=new Array(n),s=0;sn|0},vertex:function(t,e,r,n,i,a,o,s,l,u,c,f,h){var p=(o<<0)+(s<<1)+(l<<2)+(u<<3)|0;if(0!==p&&15!==p)switch(p){case 0:case 15:c.push([t-.5,e-.5]);break;case 1:c.push([t-.25-.25*(n+r-2*h)/(r-n),e-.25-.25*(i+r-2*h)/(r-i)]);break;case 2:c.push([t-.75-.25*(-n-r+2*h)/(n-r),e-.25-.25*(a+n-2*h)/(n-a)]);break;case 3:c.push([t-.5,e-.5-.5*(i+r+a+n-4*h)/(r-i+n-a)]);break;case 4:c.push([t-.25-.25*(a+i-2*h)/(i-a),e-.75-.25*(-i-r+2*h)/(i-r)]);break;case 5:c.push([t-.5-.5*(n+r+a+i-4*h)/(r-n+i-a),e-.5]);break;case 6:c.push([t-.5-.25*(-n-r+a+i)/(n-r+i-a),e-.5-.25*(-i-r+a+n)/(i-r+n-a)]);break;case 7:c.push([t-.75-.25*(a+i-2*h)/(i-a),e-.75-.25*(a+n-2*h)/(n-a)]);break;case 8:c.push([t-.75-.25*(-a-i+2*h)/(a-i),e-.75-.25*(-a-n+2*h)/(a-n)]);break;case 9:c.push([t-.5-.25*(n+r+-a-i)/(r-n+a-i),e-.5-.25*(i+r+-a-n)/(r-i+a-n)]);break;case 10:c.push([t-.5-.5*(-n-r-a-i+4*h)/(n-r+a-i),e-.5]);break;case 11:c.push([t-.25-.25*(-a-i+2*h)/(a-i),e-.75-.25*(i+r-2*h)/(r-i)]);break;case 12:c.push([t-.5,e-.5-.5*(-i-r-a-n+4*h)/(i-r+a-n)]);break;case 13:c.push([t-.75-.25*(n+r-2*h)/(r-n),e-.25-.25*(-a-n+2*h)/(a-n)]);break;case 14:c.push([t-.25-.25*(-n-r+2*h)/(n-r),e-.25-.25*(-i-r+2*h)/(i-r)])}},cell:function(t,e,r,n,i,a,o,s,l){i?s.push([t,e]):s.push([e,t])}});return function(t,e){var r=[],i=[];return n(t,r,i,e),{positions:r,cells:i}}}},o={}},6946:function(t,e,r){\"use strict\";t.exports=function t(e,r,i){i=i||{};var a=o[e];a||(a=o[e]={\" \":{data:new Float32Array(0),shape:.2}});var s=a[r];if(!s)if(r.length<=1||!/\\d/.test(r))s=a[r]=function(t){for(var e=t.cells,r=t.positions,n=new Float32Array(6*e.length),i=0,a=0,o=0;o0&&(f+=.02);var p=new Float32Array(c),d=0,v=-.5*f;for(h=0;hMath.max(r,n)?i[2]=1:r>Math.max(e,n)?i[0]=1:i[1]=1;for(var a=0,o=0,l=0;l<3;++l)a+=t[l]*t[l],o+=i[l]*t[l];for(l=0;l<3;++l)i[l]-=o/a*t[l];return s(i,i),i}function h(t,e,r,i,a,o,s,l){this.center=n(r),this.up=n(i),this.right=n(a),this.radius=n([o]),this.angle=n([s,l]),this.angle.bounds=[[-1/0,-Math.PI/2],[1/0,Math.PI/2]],this.setDistanceLimits(t,e),this.computedCenter=this.center.curve(0),this.computedUp=this.up.curve(0),this.computedRight=this.right.curve(0),this.computedRadius=this.radius.curve(0),this.computedAngle=this.angle.curve(0),this.computedToward=[0,0,0],this.computedEye=[0,0,0],this.computedMatrix=new Array(16);for(var u=0;u<16;++u)this.computedMatrix[u]=.5;this.recalcMatrix(0)}var p=h.prototype;p.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-1/0,e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},p.getDistanceLimits=function(t){var e=this.radius.bounds[0];return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},p.recalcMatrix=function(t){this.center.curve(t),this.up.curve(t),this.right.curve(t),this.radius.curve(t),this.angle.curve(t);for(var e=this.computedUp,r=this.computedRight,n=0,i=0,a=0;a<3;++a)i+=e[a]*r[a],n+=e[a]*e[a];var l=Math.sqrt(n),c=0;for(a=0;a<3;++a)r[a]-=e[a]*i/n,c+=r[a]*r[a],e[a]/=l;var f=Math.sqrt(c);for(a=0;a<3;++a)r[a]/=f;var h=this.computedToward;o(h,e,r),s(h,h);var p=Math.exp(this.computedRadius[0]),d=this.computedAngle[0],v=this.computedAngle[1],g=Math.cos(d),y=Math.sin(d),m=Math.cos(v),x=Math.sin(v),b=this.computedCenter,_=g*m,w=y*m,T=x,k=-g*x,A=-y*x,M=m,S=this.computedEye,E=this.computedMatrix;for(a=0;a<3;++a){var L=_*r[a]+w*h[a]+T*e[a];E[4*a+1]=k*r[a]+A*h[a]+M*e[a],E[4*a+2]=L,E[4*a+3]=0}var C=E[1],P=E[5],O=E[9],I=E[2],D=E[6],z=E[10],R=P*z-O*D,F=O*I-C*z,B=C*D-P*I,N=u(R,F,B);for(R/=N,F/=N,B/=N,E[0]=R,E[4]=F,E[8]=B,a=0;a<3;++a)S[a]=b[a]+E[2+4*a]*p;for(a=0;a<3;++a){c=0;for(var j=0;j<3;++j)c+=E[a+4*j]*S[j];E[12+a]=-c}E[15]=1},p.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;n<16;++n)e[n]=r[n];return e}return r};var d=[0,0,0];p.rotate=function(t,e,r,n){if(this.angle.move(t,e,r),n){this.recalcMatrix(t);var i=this.computedMatrix;d[0]=i[2],d[1]=i[6],d[2]=i[10];for(var o=this.computedUp,s=this.computedRight,l=this.computedToward,u=0;u<3;++u)i[4*u]=o[u],i[4*u+1]=s[u],i[4*u+2]=l[u];for(a(i,i,n,d),u=0;u<3;++u)o[u]=i[4*u],s[u]=i[4*u+1];this.up.set(t,o[0],o[1],o[2]),this.right.set(t,s[0],s[1],s[2])}},p.pan=function(t,e,r,n){e=e||0,r=r||0,n=n||0,this.recalcMatrix(t);var i=this.computedMatrix,a=(Math.exp(this.computedRadius[0]),i[1]),o=i[5],s=i[9],l=u(a,o,s);a/=l,o/=l,s/=l;var c=i[0],f=i[4],h=i[8],p=c*a+f*o+h*s,d=u(c-=a*p,f-=o*p,h-=s*p),v=(c/=d)*e+a*r,g=(f/=d)*e+o*r,y=(h/=d)*e+s*r;this.center.move(t,v,g,y);var m=Math.exp(this.computedRadius[0]);m=Math.max(1e-4,m+n),this.radius.set(t,Math.log(m))},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e,r,n){var a=1;\"number\"==typeof r&&(a=0|r),(a<0||a>3)&&(a=1);var o=(a+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var s=e[a],l=e[a+4],f=e[a+8];if(n){var h=Math.abs(s),p=Math.abs(l),d=Math.abs(f),v=Math.max(h,p,d);h===v?(s=s<0?-1:1,l=f=0):d===v?(f=f<0?-1:1,s=l=0):(l=l<0?-1:1,s=f=0)}else{var g=u(s,l,f);s/=g,l/=g,f/=g}var y,m,x=e[o],b=e[o+4],_=e[o+8],w=x*s+b*l+_*f,T=u(x-=s*w,b-=l*w,_-=f*w),k=l*(_/=T)-f*(b/=T),A=f*(x/=T)-s*_,M=s*b-l*x,S=u(k,A,M);if(k/=S,A/=S,M/=S,this.center.jump(t,q,G,Z),this.radius.idle(t),this.up.jump(t,s,l,f),this.right.jump(t,x,b,_),2===a){var E=e[1],L=e[5],C=e[9],P=E*x+L*b+C*_,O=E*k+L*A+C*M;y=R<0?-Math.PI/2:Math.PI/2,m=Math.atan2(O,P)}else{var I=e[2],D=e[6],z=e[10],R=I*s+D*l+z*f,F=I*x+D*b+z*_,B=I*k+D*A+z*M;y=Math.asin(c(R)),m=Math.atan2(B,F)}this.angle.jump(t,m,y),this.recalcMatrix(t);var N=e[2],j=e[6],U=e[10],V=this.computedMatrix;i(V,e);var H=V[15],q=V[12]/H,G=V[13]/H,Z=V[14]/H,Y=Math.exp(this.computedRadius[0]);this.center.jump(t,q-N*Y,G-j*Y,Z-U*Y)},p.lastT=function(){return Math.max(this.center.lastT(),this.up.lastT(),this.right.lastT(),this.radius.lastT(),this.angle.lastT())},p.idle=function(t){this.center.idle(t),this.up.idle(t),this.right.idle(t),this.radius.idle(t),this.angle.idle(t)},p.flush=function(t){this.center.flush(t),this.up.flush(t),this.right.flush(t),this.radius.flush(t),this.angle.flush(t)},p.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},p.lookAt=function(t,e,r,n){this.recalcMatrix(t),e=e||this.computedEye,r=r||this.computedCenter;var i=(n=n||this.computedUp)[0],a=n[1],o=n[2],s=u(i,a,o);if(!(s<1e-6)){i/=s,a/=s,o/=s;var l=e[0]-r[0],f=e[1]-r[1],h=e[2]-r[2],p=u(l,f,h);if(!(p<1e-6)){l/=p,f/=p,h/=p;var d=this.computedRight,v=d[0],g=d[1],y=d[2],m=i*v+a*g+o*y,x=u(v-=m*i,g-=m*a,y-=m*o);if(!(x<.01&&(x=u(v=a*h-o*f,g=o*l-i*h,y=i*f-a*l))<1e-6)){v/=x,g/=x,y/=x,this.up.set(t,i,a,o),this.right.set(t,v,g,y),this.center.set(t,r[0],r[1],r[2]),this.radius.set(t,Math.log(p));var b=a*y-o*g,_=o*v-i*y,w=i*g-a*v,T=u(b,_,w),k=i*l+a*f+o*h,A=v*l+g*f+y*h,M=(b/=T)*l+(_/=T)*f+(w/=T)*h,S=Math.asin(c(k)),E=Math.atan2(M,A),L=this.angle._state,C=L[L.length-1],P=L[L.length-2];C%=2*Math.PI;var O=Math.abs(C+2*Math.PI-E),I=Math.abs(C-E),D=Math.abs(C-2*Math.PI-E);O0?r.pop():new ArrayBuffer(t)}function d(t){return new Uint8Array(p(t),0,t)}function v(t){return new Uint16Array(p(2*t),0,t)}function g(t){return new Uint32Array(p(4*t),0,t)}function y(t){return new Int8Array(p(t),0,t)}function m(t){return new Int16Array(p(2*t),0,t)}function x(t){return new 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n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[8],c=e[9],f=e[10],h=e[11];return e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=a*i-u*n,t[1]=o*i-c*n,t[2]=s*i-f*n,t[3]=l*i-h*n,t[8]=a*n+u*i,t[9]=o*n+c*i,t[10]=s*n+f*i,t[11]=l*n+h*i,t}},15692:function(t){t.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],u=e[4],c=e[5],f=e[6],h=e[7];return e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]),t[0]=a*i+u*n,t[1]=o*i+c*n,t[2]=s*i+f*n,t[3]=l*i+h*n,t[4]=u*i-a*n,t[5]=c*i-o*n,t[6]=f*i-s*n,t[7]=h*i-l*n,t}},10789:function(t){t.exports=function(t,e,r){var n=r[0],i=r[1],a=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*i,t[5]=e[5]*i,t[6]=e[6]*i,t[7]=e[7]*i,t[8]=e[8]*a,t[9]=e[9]*a,t[10]=e[10]*a,t[11]=e[11]*a,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t}},6726:function(t){t.exports=function(t){return\"mat4(\"+t[0]+\", \"+t[1]+\", 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t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},42505:function(t,e,r){\"use strict\";var n=r(72791),i=r(71299),a=r(98580),o=r(12018),s=r(83522),l=r(25075),u=r(68016),c=r(58404),f=r(18863),h=r(10973),p=r(25677),d=r(75686),v=r(53545),g=r(56131),y=r(32879),m=r(30120),x=r(13547).nextPow2,b=new s,_=!1;if(document.body){var w=document.body.appendChild(document.createElement(\"div\"));w.style.font=\"italic small-caps bold condensed 16px/2 cursive\",getComputedStyle(w).fontStretch&&(_=!0),document.body.removeChild(w)}var T=function(t){!function(t){return\"function\"==typeof t&&t._gl&&t.prop&&t.texture&&t.buffer}(t)?this.gl=o(t):(t={regl:t},this.gl=t.regl._gl),this.shader=b.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||a({gl:this.gl}),this.charBuffer=this.regl.buffer({type:\"uint8\",usage:\"stream\"}),this.sizeBuffer=this.regl.buffer({type:\"float\",usage:\"stream\"}),this.shader||(this.shader=this.createShader(),b.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(h(t)?t:{})};T.prototype.createShader=function(){var t=this.regl,e=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst 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return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},T.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=i(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign 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t.offset&&(t.offset=[t.offset,0]),this.positionOffset=m(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=T.baseFontSize+\"px sans-serif\");var r,a=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach((function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(T.baseFontSize+\"px \"+t)}else t=n.parse(n.stringify(t));var i=n.stringify({size:T.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&i==e.font[r].baseString||(a=!0,e.font[r]=T.fonts[i],e.font[r]))){var u=t.family.join(\", \"),c=[t.style];t.style!=t.variant&&c.push(t.variant),t.variant!=t.weight&&c.push(t.weight),_&&t.weight!=t.stretch&&c.push(t.stretch),e.font[r]={baseString:i,family:u,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:y(u,{origin:\"top\",fontSize:T.baseFontSize,fontStyle:c.join(\" \")})},T.fonts[i]=e.font[r]}})),(a||o)&&this.font.forEach((function(r,i){var a=n.stringify({size:e.fontSize[i],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[i]=e.shader.atlas[a],!e.fontAtlas[i]){var o=r.metrics;e.shader.atlas[a]=e.fontAtlas[i]={fontString:a,step:2*Math.ceil(e.fontSize[i]*o.bottom*.5),em:e.fontSize[i],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)})),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),h=0;h2){for(var w=!t.position[0].length,k=c.mallocFloat(2*this.count),A=0,M=0;A1?e.align[r]:e.align[0]:e.align;if(\"number\"==typeof n)return n;switch(n){case\"right\":case\"end\":return-t;case\"center\":case\"centre\":case\"middle\":return.5*-t}return 0}))),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map((function(t,r){var n=(e.font[r]||e.font[0]).metrics,i=0;return i+=.5*n.bottom,-1*(i+=\"number\"==typeof t?t-n.baseline:-n[t])}))),null!=t.color)if(t.color||(t.color=\"transparent\"),\"string\"!=typeof t.color&&isNaN(t.color)){var q;if(\"number\"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;q=c.mallocUint8(G);for(var Z=(t.color.subarray||t.color.slice).bind(t.color),Y=0;Y4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var J=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array(J);for(var K=0;K1?this.counts[K]:this.counts[0],offset:this.textOffsets.length>1?this.textOffsets[K]:this.textOffsets[0],color:this.color?this.color.length<=4?this.color:this.color.subarray(4*K,4*K+4):[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[K]:this.opacity,baseline:null!=this.baselineOffset[K]?this.baselineOffset[K]:this.baselineOffset[0],align:this.align?null!=this.alignOffset[K]?this.alignOffset[K]:this.alignOffset[0]:0,atlas:this.fontAtlas[K]||this.fontAtlas[0],positionOffset:this.positionOffset.length>2?this.positionOffset.subarray(2*K,2*K+2):this.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},T.prototype.destroy=function(){},T.prototype.kerning=!0,T.prototype.position={constant:new Float32Array(2)},T.prototype.translate=null,T.prototype.scale=null,T.prototype.font=null,T.prototype.text=\"\",T.prototype.positionOffset=[0,0],T.prototype.opacity=1,T.prototype.color=new Uint8Array([0,0,0,255]),T.prototype.alignOffset=[0,0],T.maxAtlasSize=1024,T.atlasCanvas=document.createElement(\"canvas\"),T.atlasContext=T.atlasCanvas.getContext(\"2d\",{alpha:!1}),T.baseFontSize=64,T.fonts={},t.exports=T},12018:function(t,e,r){\"use strict\";var n=r(71299);function i(t){if(t.container)if(t.container==document.body)document.body.style.width||(t.canvas.width=t.width||t.pixelRatio*r.g.innerWidth),document.body.style.height||(t.canvas.height=t.height||t.pixelRatio*r.g.innerHeight);else{var e=t.container.getBoundingClientRect();t.canvas.width=t.width||e.right-e.left,t.canvas.height=t.height||e.bottom-e.top}}function a(t){return\"function\"==typeof t.getContext&&\"width\"in t&&\"height\"in t}function o(){var t=document.createElement(\"canvas\");return t.style.position=\"absolute\",t.style.top=0,t.style.left=0,t}t.exports=function(t){var e;if(t?\"string\"==typeof t&&(t={container:t}):t={},(t=a(t)||\"string\"==typeof(e=t).nodeName&&\"function\"==typeof e.appendChild&&\"function\"==typeof e.getBoundingClientRect?{container:t}:function(t){return\"function\"==typeof t.drawArrays||\"function\"==typeof t.drawElements}(t)?{gl:t}:n(t,{container:\"container target element el canvas holder parent parentNode wrapper use ref root node\",gl:\"gl context webgl 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Intl.NumberFormat(this.locale?this.locale.evaluate(t):[],{style:this.currency?\"currency\":\"decimal\",currency:this.currency?this.currency.evaluate(t):void 0,minimumFractionDigits:this.minFractionDigits?this.minFractionDigits.evaluate(t):void 0,maximumFractionDigits:this.maxFractionDigits?this.maxFractionDigits.evaluate(t):void 0}).format(this.number.evaluate(t))},Br.prototype.eachChild=function(t){t(this.number),this.locale&&t(this.locale),this.currency&&t(this.currency),this.minFractionDigits&&t(this.minFractionDigits),this.maxFractionDigits&&t(this.maxFractionDigits)},Br.prototype.outputDefined=function(){return!1},Br.prototype.serialize=function(){var t={};return this.locale&&(t.locale=this.locale.serialize()),this.currency&&(t.currency=this.currency.serialize()),this.minFractionDigits&&(t[\"min-fraction-digits\"]=this.minFractionDigits.serialize()),this.maxFractionDigits&&(t[\"max-fraction-digits\"]=this.maxFractionDigits.serialize()),[\"number-format\",this.number.serialize(),t]};var Nr=function(t){this.type=Ht,this.input=t};Nr.parse=function(t,e){if(2!==t.length)return e.error(\"Expected 1 argument, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1);return r?\"array\"!==r.type.kind&&\"string\"!==r.type.kind&&\"value\"!==r.type.kind?e.error(\"Expected argument of type string or array, but found \"+Qt(r.type)+\" instead.\"):new Nr(r):null},Nr.prototype.evaluate=function(t){var e=this.input.evaluate(t);if(\"string\"==typeof e)return e.length;if(Array.isArray(e))return e.length;throw new ge(\"Expected value to be of type string or array, but found \"+Qt(pe(e))+\" 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e[0].value.indexOf(t.geometryType())>=0}],\"filter-id-in\":[Gt,[$t(Wt)],function(t,e){return e[0].value.indexOf(t.id())>=0}],\"filter-in-small\":[Gt,[qt,$t(Wt)],function(t,e){var r=e[0];return e[1].value.indexOf(t.properties()[r.value])>=0}],\"filter-in-large\":[Gt,[qt,$t(Wt)],function(t,e){var r=e[0],n=e[1];return function(t,e,r,n){for(;r<=n;){var i=r+n>>1;if(e[i]===t)return!0;e[i]>t?n=i-1:r=i+1}return!1}(t.properties()[r.value],n.value,0,n.value.length-1)}],all:{type:Gt,overloads:[[[Gt,Gt],function(t,e){var r=e[0],n=e[1];return r.evaluate(t)&&n.evaluate(t)}],[qr(Gt),function(t,e){for(var r=0,n=e;r0&&\"string\"==typeof t[0]&&t[0]in jr}function ln(t,e){var r=new We(jr,[],e?function(t){var e={color:Zt,string:qt,number:Ht,enum:qt,boolean:Gt,formatted:Jt,resolvedImage:Kt};return\"array\"===t.type?$t(e[t.value]||Wt,t.length):e[t.type]}(e):void 0),n=r.parse(t,void 0,void 0,void 0,e&&\"string\"===e.type?{typeAnnotation:\"coerce\"}:void 0);return n?Gr(new on(n,e)):Zr(r.errors)}on.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._evaluator.globals=t,this._evaluator.feature=e,this._evaluator.featureState=r,this._evaluator.canonical=n,this._evaluator.availableImages=i||null,this._evaluator.formattedSection=a,this.expression.evaluate(this._evaluator)},on.prototype.evaluate=function(t,e,r,n,i,a){this._evaluator.globals=t,this._evaluator.feature=e||null,this._evaluator.featureState=r||null,this._evaluator.canonical=n,this._evaluator.availableImages=i||null,this._evaluator.formattedSection=a||null;try{var o=this.expression.evaluate(this._evaluator);if(null==o||\"number\"==typeof o&&o!=o)return this._defaultValue;if(this._enumValues&&!(o in this._enumValues))throw new ge(\"Expected value to be one of \"+Object.keys(this._enumValues).map((function(t){return JSON.stringify(t)})).join(\", \")+\", but found \"+JSON.stringify(o)+\" instead.\");return o}catch(t){return this._warningHistory[t.message]||(this._warningHistory[t.message]=!0,\"undefined\"!=typeof console&&console.warn(t.message)),this._defaultValue}};var un=function(t,e){this.kind=t,this._styleExpression=e,this.isStateDependent=\"constant\"!==t&&!Ge(e.expression)};un.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)},un.prototype.evaluate=function(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)};var cn=function(t,e,r,n){this.kind=t,this.zoomStops=r,this._styleExpression=e,this.isStateDependent=\"camera\"!==t&&!Ge(e.expression),this.interpolationType=n};function fn(t,e){if(\"error\"===(t=ln(t,e)).result)return t;var r=t.value.expression,n=qe(r);if(!n&&!Yr(e))return Zr([new jt(\"\",\"data expressions not supported\")]);var i=Ze(r,[\"zoom\"]);if(!i&&!Wr(e))return Zr([new jt(\"\",\"zoom expressions not supported\")]);var a=pn(r);if(!a&&!i)return Zr([new jt(\"\",'\"zoom\" expression may only be 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e=1;e\"===r||\"<=\"===r||\">=\"===r?Mn(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(An))):\"all\"===r?[\"all\"].concat(t.slice(1).map(An)):\"none\"===r?[\"all\"].concat(t.slice(1).map(An).map(Ln)):\"in\"===r?Sn(t[1],t.slice(2)):\"!in\"===r?Ln(Sn(t[1],t.slice(2))):\"has\"===r?En(t[1]):\"!has\"===r?Ln(En(t[1])):\"within\"!==r||t}function Mn(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function Sn(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some((function(t){return typeof t!=typeof e[0]}))?[\"filter-in-large\",t,[\"literal\",e.sort(Tn)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function En(t){switch(t){case\"$type\":return!0;case\"$id\":return[\"filter-has-id\"];default:return[\"filter-has\",t]}}function Ln(t){return[\"!\",t]}function Cn(t){return bn(Nt(t.value))?mn(Ft({},t,{expressionContext:\"filter\",valueSpec:{value:\"boolean\"}})):Pn(t)}function Pn(t){var e=t.value,r=t.key;if(\"array\"!==Jr(e))return[new zt(r,e,\"array expected, \"+Jr(e)+\" found\")];var n,i=t.styleSpec,a=[];if(e.length<1)return[new zt(r,e,\"filter array must have at least 1 element\")];switch(a=a.concat(xn({key:r+\"[0]\",value:e[0],valueSpec:i.filter_operator,style:t.style,styleSpec:t.styleSpec})),Bt(e[0])){case\"<\":case\"<=\":case\">\":case\">=\":e.length>=2&&\"$type\"===Bt(e[1])&&a.push(new zt(r,e,'\"$type\" cannot be use with operator \"'+e[0]+'\"'));case\"==\":case\"!=\":3!==e.length&&a.push(new zt(r,e,'filter array for operator \"'+e[0]+'\" must have 3 elements'));case\"in\":case\"!in\":e.length>=2&&\"string\"!==(n=Jr(e[1]))&&a.push(new zt(r+\"[1]\",e[1],\"string expected, \"+n+\" found\"));for(var o=2;o=c[p+0]&&n>=c[p+1])?(o[h]=!0,a.push(u[h])):o[h]=!1}}},Qn.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToCellCoord(t),u=this._convertToCellCoord(e),c=this._convertToCellCoord(r),f=this._convertToCellCoord(n),h=l;h<=c;h++)for(var p=u;p<=f;p++){var d=this.d*p+h;if((!s||s(this._convertFromCellCoord(h),this._convertFromCellCoord(p),this._convertFromCellCoord(h+1),this._convertFromCellCoord(p+1)))&&i.call(this,t,e,r,n,d,a,o,s))return}},Qn.prototype._convertFromCellCoord=function(t){return(t-this.padding)/this.scale},Qn.prototype._convertToCellCoord=function(t){return Math.max(0,Math.min(this.d-1,Math.floor(t*this.scale)+this.padding))},Qn.prototype.toArrayBuffer=function(){if(this.arrayBuffer)return this.arrayBuffer;for(var t=this.cells,e=$n+this.cells.length+1+1,r=0,n=0;n=0)){var f=t[c];u[c]=ri[l].shallow.indexOf(c)>=0?f:si(f,e)}t instanceof Error&&(u.message=t.message)}if(u.$name)throw new Error(\"$name property is reserved for worker serialization logic.\");return\"Object\"!==l&&(u.$name=l),u}throw new Error(\"can't serialize object of type \"+typeof t)}function li(t){if(null==t||\"boolean\"==typeof t||\"number\"==typeof t||\"string\"==typeof t||t instanceof Boolean||t instanceof Number||t instanceof String||t instanceof Date||t instanceof RegExp||ai(t)||oi(t)||ArrayBuffer.isView(t)||t instanceof ti)return t;if(Array.isArray(t))return t.map(li);if(\"object\"==typeof t){var e=t.$name||\"Object\",r=ri[e].klass;if(!r)throw new Error(\"can't deserialize unregistered class \"+e);if(r.deserialize)return r.deserialize(t);for(var n=Object.create(r.prototype),i=0,a=Object.keys(t);i=0?s:li(s)}}return n}throw new Error(\"can't deserialize object of type \"+typeof t)}var ui=function(){this.first=!0};ui.prototype.update=function(t,e){var r=Math.floor(t);return this.first?(this.first=!1,this.lastIntegerZoom=r,this.lastIntegerZoomTime=0,this.lastZoom=t,this.lastFloorZoom=r,!0):(this.lastFloorZoom>r?(this.lastIntegerZoom=r+1,this.lastIntegerZoomTime=e):this.lastFloorZoom=128&&t<=255},Arabic:function(t){return t>=1536&&t<=1791},\"Arabic 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t>=11008&&t<=11263},\"CJK Radicals Supplement\":function(t){return t>=11904&&t<=12031},\"Kangxi Radicals\":function(t){return t>=12032&&t<=12255},\"Ideographic Description Characters\":function(t){return t>=12272&&t<=12287},\"CJK Symbols and Punctuation\":function(t){return t>=12288&&t<=12351},Hiragana:function(t){return t>=12352&&t<=12447},Katakana:function(t){return t>=12448&&t<=12543},Bopomofo:function(t){return t>=12544&&t<=12591},\"Hangul Compatibility Jamo\":function(t){return t>=12592&&t<=12687},Kanbun:function(t){return t>=12688&&t<=12703},\"Bopomofo Extended\":function(t){return t>=12704&&t<=12735},\"CJK Strokes\":function(t){return t>=12736&&t<=12783},\"Katakana Phonetic Extensions\":function(t){return t>=12784&&t<=12799},\"Enclosed CJK Letters and Months\":function(t){return t>=12800&&t<=13055},\"CJK Compatibility\":function(t){return t>=13056&&t<=13311},\"CJK Unified Ideographs Extension A\":function(t){return t>=13312&&t<=19903},\"Yijing Hexagram 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e=0,r=t;e=65097&&t<=65103)||ci[\"CJK Compatibility Ideographs\"](t)||ci[\"CJK Compatibility\"](t)||ci[\"CJK Radicals Supplement\"](t)||ci[\"CJK Strokes\"](t)||!(!ci[\"CJK Symbols and Punctuation\"](t)||t>=12296&&t<=12305||t>=12308&&t<=12319||12336===t)||ci[\"CJK Unified Ideographs Extension A\"](t)||ci[\"CJK Unified Ideographs\"](t)||ci[\"Enclosed CJK Letters and Months\"](t)||ci[\"Hangul Compatibility Jamo\"](t)||ci[\"Hangul Jamo Extended-A\"](t)||ci[\"Hangul Jamo Extended-B\"](t)||ci[\"Hangul Jamo\"](t)||ci[\"Hangul Syllables\"](t)||ci.Hiragana(t)||ci[\"Ideographic Description Characters\"](t)||ci.Kanbun(t)||ci[\"Kangxi Radicals\"](t)||ci[\"Katakana Phonetic Extensions\"](t)||ci.Katakana(t)&&12540!==t||!(!ci[\"Halfwidth and Fullwidth Forms\"](t)||65288===t||65289===t||65293===t||t>=65306&&t<=65310||65339===t||65341===t||65343===t||t>=65371&&t<=65503||65507===t||t>=65512&&t<=65519)||!(!ci[\"Small Form Variants\"](t)||t>=65112&&t<=65118||t>=65123&&t<=65126)||ci[\"Unified Canadian 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Ri=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};Ri.prototype.possiblyEvaluate=function(t,e,r){for(var n=new Ni(this._properties),i=0,a=Object.keys(this._values);in.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(Ui),Hi=function(t){this.specification=t};Hi.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n);return this._calculate(i,i,i,e)}return this._calculate(t.expression.evaluate(new Pi(Math.floor(e.zoom-1),e)),t.expression.evaluate(new Pi(Math.floor(e.zoom),e)),t.expression.evaluate(new Pi(Math.floor(e.zoom+1),e)),e)}},Hi.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},Hi.prototype.interpolate=function(t){return t};var qi=function(t){this.specification=t};qi.prototype.possiblyEvaluate=function(t,e,r,n){return!!t.expression.evaluate(e,null,{},r,n)},qi.prototype.interpolate=function(){return!1};var Gi=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[],t){var r=t[e];r.specification.overridable&&this.overridableProperties.push(e);var n=this.defaultPropertyValues[e]=new Oi(r,void 0),i=this.defaultTransitionablePropertyValues[e]=new Ii(r);this.defaultTransitioningPropertyValues[e]=i.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};ni(\"DataDrivenProperty\",Ui),ni(\"DataConstantProperty\",ji),ni(\"CrossFadedDataDrivenProperty\",Vi),ni(\"CrossFadedProperty\",Hi),ni(\"ColorRampProperty\",qi);var Zi=\"-transition\",Yi=function(t){function 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this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Ji);la.prototype.bytesPerElement=12,ni(\"StructArrayLayout2i2i2i12\",la);var ua=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n,i)},e.prototype.emplace=function(t,e,r,n,i,a){var o=4*t,s=8*t;return this.float32[o+0]=e,this.float32[o+1]=r,this.float32[o+2]=n,this.int16[s+6]=i,this.int16[s+7]=a,t},e}(Ji);ua.prototype.bytesPerElement=16,ni(\"StructArrayLayout2f1f2i16\",ua);var ca=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=12*t,o=3*t;return this.uint8[a+0]=e,this.uint8[a+1]=r,this.float32[o+1]=n,this.float32[o+2]=i,t},e}(Ji);ca.prototype.bytesPerElement=12,ni(\"StructArrayLayout2ub2f12\",ca);var fa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return 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this.int16[m+0]=e,this.int16[m+1]=r,this.uint16[m+2]=n,this.uint16[m+3]=i,this.uint32[x+2]=a,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[m+10]=l,this.uint16[m+11]=u,this.uint16[m+12]=c,this.float32[x+7]=f,this.float32[x+8]=h,this.uint8[b+36]=p,this.uint8[b+37]=d,this.uint8[b+38]=v,this.uint32[x+10]=g,this.int16[m+22]=y,t},e}(Ji);ha.prototype.bytesPerElement=48,ni(\"StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48\",ha);var pa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,k,A,M,S){var E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,k,A,M,S)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,k,A,M,S,E){var L=34*t,C=17*t;return this.int16[L+0]=e,this.int16[L+1]=r,this.int16[L+2]=n,this.int16[L+3]=i,this.int16[L+4]=a,this.int16[L+5]=o,this.int16[L+6]=s,this.int16[L+7]=l,this.uint16[L+8]=u,this.uint16[L+9]=c,this.uint16[L+10]=f,this.uint16[L+11]=h,this.uint16[L+12]=p,this.uint16[L+13]=d,this.uint16[L+14]=v,this.uint16[L+15]=g,this.uint16[L+16]=y,this.uint16[L+17]=m,this.uint16[L+18]=x,this.uint16[L+19]=b,this.uint16[L+20]=_,this.uint16[L+21]=w,this.uint16[L+22]=T,this.uint32[C+12]=k,this.float32[C+13]=A,this.float32[C+14]=M,this.float32[C+15]=S,this.float32[C+16]=E,t},e}(Ji);pa.prototype.bytesPerElement=68,ni(\"StructArrayLayout8i15ui1ul4f68\",pa);var da=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.float32[r+0]=e,t},e}(Ji);da.prototype.bytesPerElement=4,ni(\"StructArrayLayout1f4\",da);var va=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,t},e}(Ji);va.prototype.bytesPerElement=6,ni(\"StructArrayLayout3i6\",va);var ga=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=2*t,a=4*t;return this.uint32[i+0]=e,this.uint16[a+2]=r,this.uint16[a+3]=n,t},e}(Ji);ga.prototype.bytesPerElement=8,ni(\"StructArrayLayout1ul2ui8\",ga);var ya=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new 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t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.float32[n+0]=e,this.float32[n+1]=r,t},e}(Ji);xa.prototype.bytesPerElement=8,ni(\"StructArrayLayout2f8\",xa);var ba=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.float32[a+0]=e,this.float32[a+1]=r,this.float32[a+2]=n,this.float32[a+3]=i,t},e}(Ji);ba.prototype.bytesPerElement=16,ni(\"StructArrayLayout4f16\",ba);var _a=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},anchorPoint:{configurable:!0}};return r.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},r.x1.get=function(){return this._structArray.int16[this._pos2+2]},r.y1.get=function(){return this._structArray.int16[this._pos2+3]},r.x2.get=function(){return this._structArray.int16[this._pos2+4]},r.y2.get=function(){return this._structArray.int16[this._pos2+5]},r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.anchorPoint.get=function(){return new a(this.anchorPointX,this.anchorPointY)},Object.defineProperties(e.prototype,r),e}(Xi);_a.prototype.size=20;var wa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new _a(this,t)},e}(sa);ni(\"CollisionBoxArray\",wa);var Ta=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var 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S=o.content;x=zu(h,0,S[0]),_=zu(p,0,S[1]),b=zu(h,S[0],S[2]),w=zu(p,S[1],S[3]),T=S[0]-x,A=S[1]-_,k=S[2]-S[0]-b,M=S[3]-S[1]-w}var E=function(n,i,l,u){var h=Fu(n.stretch-x,b,c,t.left),p=Bu(n.fixed-T,k,n.stretch,v),d=Fu(i.stretch-_,w,f,t.top),y=Bu(i.fixed-A,M,i.stretch,g),m=Fu(l.stretch-x,b,c,t.left),S=Bu(l.fixed-T,k,l.stretch,v),E=Fu(u.stretch-_,w,f,t.top),L=Bu(u.fixed-A,M,u.stretch,g),C=new a(h,d),P=new a(m,d),O=new a(m,E),I=new a(h,E),D=new a(p/s,y/s),z=new a(S/s,L/s),R=e*Math.PI/180;if(R){var F=Math.sin(R),B=Math.cos(R),N=[B,-F,F,B];C._matMult(N),P._matMult(N),I._matMult(N),O._matMult(N)}var j=n.stretch+n.fixed,U=l.stretch+l.fixed,V=i.stretch+i.fixed,H=u.stretch+u.fixed;return{tl:C,tr:P,bl:I,br:O,tex:{x:o.paddedRect.x+Iu+j,y:o.paddedRect.y+Iu+V,w:U-j,h:H-V},writingMode:void 0,glyphOffset:[0,0],sectionIndex:0,pixelOffsetTL:D,pixelOffsetBR:z,minFontScaleX:k/s/c,minFontScaleY:M/s/f,isSDF:r}};if(n&&(o.stretchX||o.stretchY))for(var L=Ru(h,y,v),C=Ru(p,m,g),P=0;P0&&(d=Math.max(10,d),this.circleDiameter=d)}else{var v=o.top*s-l,g=o.bottom*s+l,y=o.left*s-l,m=o.right*s+l,x=o.collisionPadding;if(x&&(y-=x[0]*s,v-=x[1]*s,m+=x[2]*s,g+=x[3]*s),c){var b=new a(y,v),_=new a(m,v),w=new a(y,g),T=new a(m,g),k=c*Math.PI/180;b._rotate(k),_._rotate(k),w._rotate(k),T._rotate(k),y=Math.min(b.x,_.x,w.x,T.x),m=Math.max(b.x,_.x,w.x,T.x),v=Math.min(b.y,_.y,w.y,T.y),g=Math.max(b.y,_.y,w.y,T.y)}t.emplaceBack(e.x,e.y,y,v,m,g,r,n,i)}this.boxEndIndex=t.length},ju=function(t,e){if(void 0===t&&(t=[]),void 0===e&&(e=Uu),this.data=t,this.length=this.data.length,this.compare=e,this.length>0)for(var r=(this.length>>1)-1;r>=0;r--)this._down(r)};function Uu(t,e){return te?1:0}function Vu(t,e,r){void 0===e&&(e=1),void 0===r&&(r=!1);for(var n=1/0,i=1/0,o=-1/0,s=-1/0,l=t[0],u=0;uo)&&(o=c.x),(!u||c.y>s)&&(s=c.y)}var f=o-n,h=s-i,p=Math.min(f,h),d=p/2,v=new ju([],Hu);if(0===p)return new a(n,i);for(var g=n;gm.d||!m.d)&&(m=b,r&&console.log(\"found best %d after %d probes\",Math.round(1e4*b.d)/1e4,x)),b.max-m.d<=e||(d=b.h/2,v.push(new qu(b.p.x-d,b.p.y-d,d,t)),v.push(new qu(b.p.x+d,b.p.y-d,d,t)),v.push(new qu(b.p.x-d,b.p.y+d,d,t)),v.push(new qu(b.p.x+d,b.p.y+d,d,t)),x+=4)}return r&&(console.log(\"num probes: \"+x),console.log(\"best distance: \"+m.d)),m.p}function Hu(t,e){return e.max-t.max}function qu(t,e,r,n){this.p=new a(t,e),this.h=r,this.d=function(t,e){for(var r=!1,n=1/0,i=0;it.y!=c.y>t.y&&t.x<(c.x-u.x)*(t.y-u.y)/(c.y-u.y)+u.x&&(r=!r),n=Math.min(n,ko(t,u,c))}return(r?1:-1)*Math.sqrt(n)}(this.p,n),this.max=this.d+this.h*Math.SQRT2}ju.prototype.push=function(t){this.data.push(t),this.length++,this._up(this.length-1)},ju.prototype.pop=function(){if(0!==this.length){var t=this.data[0],e=this.data.pop();return this.length--,this.length>0&&(this.data[0]=e,this._down(0)),t}},ju.prototype.peek=function(){return this.data[0]},ju.prototype._up=function(t){for(var e=this.data,r=this.compare,n=e[t];t>0;){var i=t-1>>1,a=e[i];if(r(n,a)>=0)break;e[t]=a,t=i}e[t]=n},ju.prototype._down=function(t){for(var e=this.data,r=this.compare,n=this.length>>1,i=e[t];t=0)break;e[t]=o,t=a}e[t]=i};var Gu=7,Zu=Number.POSITIVE_INFINITY;function Yu(t,e){return e[1]!==Zu?function(t,e,r){var n=0,i=0;switch(e=Math.abs(e),r=Math.abs(r),t){case\"top-right\":case\"top-left\":case\"top\":i=r-Gu;break;case\"bottom-right\":case\"bottom-left\":case\"bottom\":i=-r+Gu}switch(t){case\"top-right\":case\"bottom-right\":case\"right\":n=-e;break;case\"top-left\":case\"bottom-left\":case\"left\":n=e}return[n,i]}(t,e[0],e[1]):function(t,e){var r=0,n=0;e<0&&(e=0);var i=e/Math.sqrt(2);switch(t){case\"top-right\":case\"top-left\":n=i-Gu;break;case\"bottom-right\":case\"bottom-left\":n=-i+Gu;break;case\"bottom\":n=-e+Gu;break;case\"top\":n=e-Gu}switch(t){case\"top-right\":case\"bottom-right\":r=-i;break;case\"top-left\":case\"bottom-left\":r=i;break;case\"left\":r=e;break;case\"right\":r=-e}return[r,n]}(t,e[0])}function Wu(t){switch(t){case\"right\":case\"top-right\":case\"bottom-right\":return\"right\";case\"left\":case\"top-left\":case\"bottom-left\":return\"left\"}return\"center\"}var Xu=255,Ju=Xu*bu;function Ku(t,e,r,n,i,o,s,l,u,c,f,h,p,d,v){var g=function(t,e,r,n,i,o,s,l){for(var u=n.layout.get(\"text-rotate\").evaluate(o,{})*Math.PI/180,c=[],f=0,h=e.positionedLines;fJu&&w(t.layerIds[0]+': Value for \"text-size\" is >= '+Xu+'. Reduce your \"text-size\".'):\"composite\"===y.kind&&((m=[bu*d.compositeTextSizes[0].evaluate(s,{},v),bu*d.compositeTextSizes[1].evaluate(s,{},v)])[0]>Ju||m[1]>Ju)&&w(t.layerIds[0]+': Value for \"text-size\" is >= '+Xu+'. Reduce your \"text-size\".'),t.addSymbols(t.text,g,m,l,o,s,c,e,u.lineStartIndex,u.lineLength,p,v);for(var x=0,b=f;x=0;o--)if(n.dist(a[o])0)&&(\"constant\"!==a.value.kind||a.value.value.length>0),u=\"constant\"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,c=i.get(\"symbol-sort-key\");if(this.features=[],l||u){for(var f=e.iconDependencies,h=e.glyphDependencies,p=e.availableImages,d=new Pi(this.zoom),v=0,g=t;v=0;for(var I=0,D=k.sections;I=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l0},sc.prototype.hasIconData=function(){return this.icon.segments.get().length>0},sc.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},sc.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},sc.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},sc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},ni(\"SymbolBucket\",sc,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),sc.MAX_GLYPHS=65535,sc.addDynamicAttributes=nc;var lc=new Gi({\"symbol-placement\":new ji(Dt.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new ji(Dt.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new ji(Dt.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new Ui(Dt.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new ji(Dt.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new ji(Dt.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new ji(Dt.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new ji(Dt.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new ji(Dt.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new Ui(Dt.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new ji(Dt.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new ji(Dt.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new Ui(Dt.layout_symbol[\"icon-image\"]),\"icon-rotate\":new Ui(Dt.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new ji(Dt.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new ji(Dt.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new Ui(Dt.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new Ui(Dt.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new ji(Dt.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new ji(Dt.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new ji(Dt.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new Ui(Dt.layout_symbol[\"text-field\"]),\"text-font\":new Ui(Dt.layout_symbol[\"text-font\"]),\"text-size\":new Ui(Dt.layout_symbol[\"text-size\"]),\"text-max-width\":new Ui(Dt.layout_symbol[\"text-max-width\"]),\"text-line-height\":new ji(Dt.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new Ui(Dt.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new Ui(Dt.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new Ui(Dt.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new ji(Dt.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new Ui(Dt.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new ji(Dt.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new ji(Dt.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new Ui(Dt.layout_symbol[\"text-rotate\"]),\"text-padding\":new ji(Dt.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new ji(Dt.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new Ui(Dt.layout_symbol[\"text-transform\"]),\"text-offset\":new Ui(Dt.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new ji(Dt.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new ji(Dt.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new ji(Dt.layout_symbol[\"text-optional\"])}),uc={paint:new Gi({\"icon-opacity\":new Ui(Dt.paint_symbol[\"icon-opacity\"]),\"icon-color\":new Ui(Dt.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new Ui(Dt.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new Ui(Dt.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new Ui(Dt.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new ji(Dt.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new ji(Dt.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new Ui(Dt.paint_symbol[\"text-opacity\"]),\"text-color\":new Ui(Dt.paint_symbol[\"text-color\"],{runtimeType:Zt,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new Ui(Dt.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new Ui(Dt.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new Ui(Dt.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new ji(Dt.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new ji(Dt.paint_symbol[\"text-translate-anchor\"])}),layout:lc},cc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Vt,this.defaultValue=t};cc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},cc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},cc.prototype.outputDefined=function(){return!1},cc.prototype.serialize=function(){return null},ni(\"FormatSectionOverride\",cc,{omit:[\"defaultValue\"]});var fc=function(t){function e(e){t.call(this,e,uc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var n=this.layout.get(\"text-writing-mode\");if(n){for(var i=[],a=0,o=n;a\",targetMapId:n,sourceMapId:a.mapId})}}},Ac.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else A()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Ac.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Ac.prototype.processTask=function(t,e){var r=this;if(\"\"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(li(e.error)):n(null,li(e.data)))}else{var i=!1,a=E(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:\"\",sourceMapId:r.mapId,error:e?si(e):null,data:si(n,a)},a)}:function(t){i=!0},s=null,l=li(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var u=e.type.split(\".\");s=this.parent.getWorkerSource(e.sourceMapId,u[0],l.source)[u[1]](l,o)}else o(new Error(\"Could not find function \"+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Ac.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};var Sc=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Sc.prototype.setNorthEast=function(t){return this._ne=t instanceof Lc?new Lc(t.lng,t.lat):Lc.convert(t),this},Sc.prototype.setSouthWest=function(t){return this._sw=t instanceof Lc?new Lc(t.lng,t.lat):Lc.convert(t),this},Sc.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof Lc)e=t,r=t;else{if(!(t instanceof Sc)){if(Array.isArray(t)){if(4===t.length||t.every(Array.isArray)){var a=t;return this.extend(Sc.convert(a))}var o=t;return this.extend(Lc.convert(o))}return this}if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new Lc(e.lng,e.lat),this._ne=new Lc(r.lng,r.lat)),this},Sc.prototype.getCenter=function(){return new Lc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Sc.prototype.getSouthWest=function(){return this._sw},Sc.prototype.getNorthEast=function(){return this._ne},Sc.prototype.getNorthWest=function(){return new Lc(this.getWest(),this.getNorth())},Sc.prototype.getSouthEast=function(){return new Lc(this.getEast(),this.getSouth())},Sc.prototype.getWest=function(){return this._sw.lng},Sc.prototype.getSouth=function(){return this._sw.lat},Sc.prototype.getEast=function(){return this._ne.lng},Sc.prototype.getNorth=function(){return this._ne.lat},Sc.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Sc.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Sc.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Sc.prototype.contains=function(t){var e=Lc.convert(t),r=e.lng,n=e.lat,i=this._sw.lat<=n&&n<=this._ne.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),i&&a},Sc.convert=function(t){return!t||t instanceof Sc?t:new Sc(t)};var Ec=6371008.8,Lc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};Lc.prototype.wrap=function(){return new Lc(c(this.lng,-180,180),this.lat)},Lc.prototype.toArray=function(){return[this.lng,this.lat]},Lc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},Lc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return Ec*Math.acos(Math.min(i,1))},Lc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Sc(new Lc(this.lng-r,this.lat-e),new Lc(this.lng+r,this.lat+e))},Lc.convert=function(t){if(t instanceof Lc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Lc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new Lc(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: , lat: }, an object {lon: , lat: }, or an array of [, ]\")};var Cc=2*Math.PI*Ec;function Pc(t){return Cc*Math.cos(t*Math.PI/180)}function Oc(t){return(180+t)/360}function Ic(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Dc(t,e){return t/Pc(e)}function zc(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var Rc=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};Rc.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Lc.convert(t);return new Rc(Oc(r.lng),Ic(r.lat),Dc(e,r.lat))},Rc.prototype.toLngLat=function(){return new Lc(360*this.x-180,zc(this.y))},Rc.prototype.toAltitude=function(){return t=this.z,e=this.y,t*Pc(zc(e));var t,e},Rc.prototype.meterInMercatorCoordinateUnits=function(){return 1/Cc*(t=zc(this.y),1/Math.cos(t*Math.PI/180));var t};var Fc=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=jc(0,t,t,e,r)};Fc.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},Fc.prototype.url=function(t,e){var r,n,i,a,o,s=(r=this.x,n=this.y,i=this.z,a=Mc(256*r,256*(n=Math.pow(2,i)-n-1),i),o=Mc(256*(r+1),256*(n+1),i),a[0]+\",\"+a[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<this.canonical.z?new Nc(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Nc(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},Nc.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?jc(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):jc(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},Nc.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ>e&&t.canonical.y===this.canonical.y>>e},Nc.prototype.children=function(t){if(this.overscaledZ>=t)return[new Nc(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new Nc(e,this.wrap,e,r,n),new Nc(e,this.wrap,e,r+1,n),new Nc(e,this.wrap,e,r,n+1),new Nc(e,this.wrap,e,r+1,n+1)]},Nc.prototype.isLessThan=function(t){return this.wrapt.wrap)&&(this.overscaledZt.overscaledZ)&&(this.canonical.xt.canonical.x)&&this.canonical.y=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},Uc.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},Uc.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},Uc.prototype.getPixels=function(){return new Wo({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},Uc.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,u=a;u=0&&c[3]>=0&&s.insert(o,c[0],c[1],c[2],c[3])}},Zc.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new Js.VectorTile(new Sl(this.rawTileData)).layers,this.sourceLayerCoder=new Vc(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},Zc.prototype.query=function(t,e,r,n){var i=this;this.loadVTLayers();for(var o=t.params||{},s=co/t.tileSize/t.scale,l=wn(o.filter),u=t.queryGeometry,c=t.queryPadding*s,f=Wc(u),h=this.grid.query(f.minX-c,f.minY-c,f.maxX+c,f.maxY+c),p=Wc(t.cameraQueryGeometry),d=0,v=this.grid3D.query(p.minX-c,p.minY-c,p.maxX+c,p.maxY+c,(function(e,r,n,i){return function(t,e,r,n,i){for(var o=0,s=t;o=l.x&&i>=l.y)return!0}var u=[new a(e,r),new a(e,i),new a(n,i),new a(n,r)];if(t.length>2)for(var c=0,f=u;c=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),p=this.vtLayers[h].feature(n);if(i.filter(new Pi(this.tileID.overscaledZ),p))for(var d=this.getId(p,h),v=0;vn)i=!1;else if(e)if(this.expirationTimect&&(t.getActor().send(\"enforceCacheSizeLimit\",ut),yt=0)},t.clamp=u,t.clearTileCache=function(t){var e=self.caches.delete(lt);t&&e.catch(t).then((function(){return t()}))},t.clipLine=Ou,t.clone=function(t){var e=new Io(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},t.clone$1=b,t.clone$2=function(t){var e=new Io(3);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e},t.collisionCircleLayout=_l,t.config=B,t.create=function(){var t=new Io(16);return Io!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0),t[0]=1,t[5]=1,t[10]=1,t[15]=1,t},t.create$1=function(){var t=new Io(9);return Io!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[5]=0,t[6]=0,t[7]=0),t[0]=1,t[4]=1,t[8]=1,t},t.create$2=function(){var t=new Io(4);return Io!=Float32Array&&(t[1]=0,t[2]=0),t[0]=1,t[3]=1,t},t.createCommonjsModule=e,t.createExpression=ln,t.createLayout=Ki,t.createStyleLayer=function(t){return\"custom\"===t.type?new gc(t):new yc[t.type](t)},t.cross=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=r[0],s=r[1],l=r[2];return t[0]=i*l-a*s,t[1]=a*o-n*l,t[2]=n*s-i*o,t},t.deepEqual=function t(e,r){if(Array.isArray(e)){if(!Array.isArray(r)||e.length!==r.length)return!1;for(var n=0;n0&&(a=1/Math.sqrt(a)),t[0]=e[0]*a,t[1]=e[1]*a,t[2]=e[2]*a,t},t.number=$e,t.offscreenCanvasSupported=mt,t.ortho=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),u=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*u,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*u,t[15]=1,t},t.parseGlyphPBF=function(t){return new Sl(t).readFields(Wl,[])},t.pbf=Sl,t.performSymbolLayout=function(t,e,r,n,i,a,o){t.createArrays();var s=512*t.overscaling;t.tilePixelRatio=co/s,t.compareText={},t.iconsNeedLinear=!1;var l=t.layers[0].layout,u=t.layers[0]._unevaluatedLayout._values,c={};if(\"composite\"===t.textSizeData.kind){var f=t.textSizeData,h=f.minZoom,p=f.maxZoom;c.compositeTextSizes=[u[\"text-size\"].possiblyEvaluate(new Pi(h),o),u[\"text-size\"].possiblyEvaluate(new Pi(p),o)]}if(\"composite\"===t.iconSizeData.kind){var d=t.iconSizeData,v=d.minZoom,g=d.maxZoom;c.compositeIconSizes=[u[\"icon-size\"].possiblyEvaluate(new Pi(v),o),u[\"icon-size\"].possiblyEvaluate(new Pi(g),o)]}c.layoutTextSize=u[\"text-size\"].possiblyEvaluate(new Pi(t.zoom+1),o),c.layoutIconSize=u[\"icon-size\"].possiblyEvaluate(new Pi(t.zoom+1),o),c.textMaxSize=u[\"text-size\"].possiblyEvaluate(new Pi(18));for(var y=l.get(\"text-line-height\")*kl,m=\"map\"===l.get(\"text-rotation-alignment\")&&\"point\"!==l.get(\"symbol-placement\"),x=l.get(\"text-keep-upright\"),b=l.get(\"text-size\"),_=function(){var a=k[T],s=l.get(\"text-font\").evaluate(a,{},o).join(\",\"),u=b.evaluate(a,{},o),f=c.layoutTextSize.evaluate(a,{},o),h=c.layoutIconSize.evaluate(a,{},o),p={horizontal:{},vertical:void 0},d=a.text,v=[0,0];if(d){var g=d.toString(),_=l.get(\"text-letter-spacing\").evaluate(a,{},o)*kl,A=function(t){for(var e=0,r=t;e=co||f.y<0||f.y>=co||function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,T,k,A){var M,S,E,L,C,P=t.addToLineVertexArray(e,r),O=0,I=0,D=0,z=0,R=-1,F=-1,B={},N=Fa(\"\"),j=0,U=0;if(void 0===s._unevaluatedLayout.getValue(\"text-radial-offset\")?(j=(M=s.layout.get(\"text-offset\").evaluate(b,{},k).map((function(t){return t*kl})))[0],U=M[1]):(j=s.layout.get(\"text-radial-offset\").evaluate(b,{},k)*kl,U=Zu),t.allowVerticalPlacement&&n.vertical){var V=s.layout.get(\"text-rotate\").evaluate(b,{},k)+90,H=n.vertical;L=new Nu(l,e,u,c,f,H,h,p,d,V),o&&(C=new Nu(l,e,u,c,f,o,g,y,d,V))}if(i){var q=s.layout.get(\"icon-rotate\").evaluate(b,{}),G=\"none\"!==s.layout.get(\"icon-text-fit\"),Z=Du(i,q,T,G),Y=o?Du(o,q,T,G):void 0;E=new Nu(l,e,u,c,f,i,g,y,!1,q),O=4*Z.length;var W=t.iconSizeData,X=null;\"source\"===W.kind?(X=[bu*s.layout.get(\"icon-size\").evaluate(b,{})])[0]>Ju&&w(t.layerIds[0]+': Value for \"icon-size\" is >= '+Xu+'. Reduce your \"icon-size\".'):\"composite\"===W.kind&&((X=[bu*_.compositeIconSizes[0].evaluate(b,{},k),bu*_.compositeIconSizes[1].evaluate(b,{},k)])[0]>Ju||X[1]>Ju)&&w(t.layerIds[0]+': Value for \"icon-size\" is >= '+Xu+'. Reduce your \"icon-size\".'),t.addSymbols(t.icon,Z,X,x,m,b,!1,e,P.lineStartIndex,P.lineLength,-1,k),R=t.icon.placedSymbolArray.length-1,Y&&(I=4*Y.length,t.addSymbols(t.icon,Y,X,x,m,b,nu.vertical,e,P.lineStartIndex,P.lineLength,-1,k),F=t.icon.placedSymbolArray.length-1)}for(var J in n.horizontal){var K=n.horizontal[J];if(!S){N=Fa(K.text);var $=s.layout.get(\"text-rotate\").evaluate(b,{},k);S=new Nu(l,e,u,c,f,K,h,p,d,$)}var Q=1===K.positionedLines.length;if(D+=Ku(t,e,K,a,s,d,b,v,P,n.vertical?nu.horizontal:nu.horizontalOnly,Q?Object.keys(n.horizontal):[J],B,R,_,k),Q)break}n.vertical&&(z+=Ku(t,e,n.vertical,a,s,d,b,v,P,nu.vertical,[\"vertical\"],B,F,_,k));var tt=S?S.boxStartIndex:t.collisionBoxArray.length,et=S?S.boxEndIndex:t.collisionBoxArray.length,rt=L?L.boxStartIndex:t.collisionBoxArray.length,nt=L?L.boxEndIndex:t.collisionBoxArray.length,it=E?E.boxStartIndex:t.collisionBoxArray.length,at=E?E.boxEndIndex:t.collisionBoxArray.length,ot=C?C.boxStartIndex:t.collisionBoxArray.length,st=C?C.boxEndIndex:t.collisionBoxArray.length,lt=-1,ut=function(t,e){return t&&t.circleDiameter?Math.max(t.circleDiameter,e):e};lt=ut(S,lt),lt=ut(L,lt),lt=ut(E,lt);var ct=(lt=ut(C,lt))>-1?1:0;ct&&(lt*=A/kl),t.glyphOffsetArray.length>=sc.MAX_GLYPHS&&w(\"Too many glyphs being rendered in a tile. See https://github.com/mapbox/mapbox-gl-js/issues/2907\"),void 0!==b.sortKey&&t.addToSortKeyRanges(t.symbolInstances.length,b.sortKey),t.symbolInstances.emplaceBack(e.x,e.y,B.right>=0?B.right:-1,B.center>=0?B.center:-1,B.left>=0?B.left:-1,B.vertical||-1,R,F,N,tt,et,rt,nt,it,at,ot,st,u,D,z,O,I,ct,0,h,j,U,lt)}(t,f,s,r,n,i,h,t.layers[0],t.collisionBoxArray,e.index,e.sourceLayerIndex,t.index,m,T,M,l,b,k,S,d,e,a,u,c,o)};if(\"line\"===E)for(var O=0,I=Ou(e.geometry,0,0,co,co);O1){var U=Lu(j,A,r.vertical||v,n,g,x);U&&P(j,U)}}else if(\"Polygon\"===e.type)for(var V=0,H=Is(e.geometry,0);V=E.maxzoom||\"none\"!==E.visibility&&(o(S,this.zoom,n),(v[E.id]=E.createBucket({index:c.bucketLayerIDs.length,layers:S,zoom:this.zoom,pixelRatio:this.pixelRatio,overscaling:this.overscaling,collisionBoxArray:this.collisionBoxArray,sourceLayerIndex:b,sourceID:this.source})).populate(_,g,this.tileID.canonical),c.bucketLayerIDs.push(S.map((function(t){return t.id}))))}}}var L=t.mapObject(g.glyphDependencies,(function(t){return Object.keys(t).map(Number)}));Object.keys(L).length?a.send(\"getGlyphs\",{uid:this.uid,stacks:L},(function(t,e){f||(f=t,h=e,O.call(l))})):h={};var C=Object.keys(g.iconDependencies);C.length?a.send(\"getImages\",{icons:C,source:this.source,tileID:this.tileID,type:\"icons\"},(function(t,e){f||(f=t,p=e,O.call(l))})):p={};var P=Object.keys(g.patternDependencies);function O(){if(f)return s(f);if(h&&p&&d){var e=new i(h),r=new t.ImageAtlas(p,d);for(var a in v){var l=v[a];l instanceof t.SymbolBucket?(o(l.layers,this.zoom,n),t.performSymbolLayout(l,h,e.positions,p,r.iconPositions,this.showCollisionBoxes,this.tileID.canonical)):l.hasPattern&&(l instanceof t.LineBucket||l instanceof t.FillBucket||l instanceof t.FillExtrusionBucket)&&(o(l.layers,this.zoom,n),l.addFeatures(g,this.tileID.canonical,r.patternPositions))}this.status=\"done\",s(null,{buckets:t.values(v).filter((function(t){return!t.isEmpty()})),featureIndex:c,collisionBoxArray:this.collisionBoxArray,glyphAtlasImage:e.image,imageAtlas:r,glyphMap:this.returnDependencies?h:null,iconMap:this.returnDependencies?p:null,glyphPositions:this.returnDependencies?e.positions:null})}}P.length?a.send(\"getImages\",{icons:P,source:this.source,tileID:this.tileID,type:\"patterns\"},(function(t,e){f||(f=t,d=e,O.call(l))})):d={},O.call(this)};var l=function(t,e,r,n){this.actor=t,this.layerIndex=e,this.availableImages=r,this.loadVectorData=n||s,this.loading={},this.loaded={}};l.prototype.loadTile=function(e,r){var n=this,i=e.uid;this.loading||(this.loading={});var o=!!(e&&e.request&&e.request.collectResourceTiming)&&new t.RequestPerformance(e.request),s=this.loading[i]=new a(e);s.abort=this.loadVectorData(e,(function(e,a){if(delete n.loading[i],e||!a)return s.status=\"done\",n.loaded[i]=s,r(e);var l=a.rawData,u={};a.expires&&(u.expires=a.expires),a.cacheControl&&(u.cacheControl=a.cacheControl);var c={};if(o){var f=o.finish();f&&(c.resourceTiming=JSON.parse(JSON.stringify(f)))}s.vectorTile=a.vectorTile,s.parse(a.vectorTile,n.layerIndex,n.availableImages,n.actor,(function(e,n){if(e||!n)return r(e);r(null,t.extend({rawTileData:l.slice(0)},n,u,c))})),n.loaded=n.loaded||{},n.loaded[i]=s}))},l.prototype.reloadTile=function(t,e){var r=this,n=this.loaded,i=t.uid,a=this;if(n&&n[i]){var o=n[i];o.showCollisionBoxes=t.showCollisionBoxes;var s=function(t,n){var i=o.reloadCallback;i&&(delete o.reloadCallback,o.parse(o.vectorTile,a.layerIndex,r.availableImages,a.actor,i)),e(t,n)};\"parsing\"===o.status?o.reloadCallback=s:\"done\"===o.status&&(o.vectorTile?o.parse(o.vectorTile,this.layerIndex,this.availableImages,this.actor,s):s())}},l.prototype.abortTile=function(t,e){var r=this.loading,n=t.uid;r&&r[n]&&r[n].abort&&(r[n].abort(),delete r[n]),e()},l.prototype.removeTile=function(t,e){var r=this.loaded,n=t.uid;r&&r[n]&&delete r[n],e()};var u=t.window.ImageBitmap,c=function(){this.loaded={}};c.prototype.loadTile=function(e,r){var n=e.uid,i=e.encoding,a=e.rawImageData,o=u&&a instanceof u?this.getImageData(a):a,s=new t.DEMData(n,o,i);this.loaded=this.loaded||{},this.loaded[n]=s,r(null,s)},c.prototype.getImageData=function(e){this.offscreenCanvas&&this.offscreenCanvasContext||(this.offscreenCanvas=new OffscreenCanvas(e.width,e.height),this.offscreenCanvasContext=this.offscreenCanvas.getContext(\"2d\")),this.offscreenCanvas.width=e.width,this.offscreenCanvas.height=e.height,this.offscreenCanvasContext.drawImage(e,0,0,e.width,e.height);var r=this.offscreenCanvasContext.getImageData(-1,-1,e.width+2,e.height+2);return this.offscreenCanvasContext.clearRect(0,0,this.offscreenCanvas.width,this.offscreenCanvas.height),new t.RGBAImage({width:r.width,height:r.height},r.data)},c.prototype.removeTile=function(t){var e=this.loaded,r=t.uid;e&&e[r]&&delete e[r]};var f=function t(e,r){var n,i=e&&e.type;if(\"FeatureCollection\"===i)for(n=0;n=0!=!!e&&t.reverse()}var d=t.vectorTile.VectorTileFeature.prototype.toGeoJSON,v=function(e){this._feature=e,this.extent=t.EXTENT,this.type=e.type,this.properties=e.tags,\"id\"in e&&!isNaN(e.id)&&(this.id=parseInt(e.id,10))};v.prototype.loadGeometry=function(){if(1===this._feature.type){for(var e=[],r=0,n=this._feature.geometry;r>31}function P(t,e){for(var r=t.loadGeometry(),n=t.type,i=0,a=0,o=r.length,s=0;s>1;D(t,e,o,n,i,a%2),I(t,e,r,n,o-1,a+1),I(t,e,r,o+1,i,a+1)}}function D(t,e,r,n,i,a){for(;i>n;){if(i-n>600){var o=i-n+1,s=r-n+1,l=Math.log(o),u=.5*Math.exp(2*l/3),c=.5*Math.sqrt(l*u*(o-u)/o)*(s-o/2<0?-1:1);D(t,e,r,Math.max(n,Math.floor(r-s*u/o+c)),Math.min(i,Math.floor(r+(o-s)*u/o+c)),a)}var f=e[2*r+a],h=n,p=i;for(z(t,e,n,r),e[2*i+a]>f&&z(t,e,n,i);hf;)p--}e[2*n+a]===f?z(t,e,n,p):z(t,e,++p,i),p<=r&&(n=p+1),r<=p&&(i=p-1)}}function z(t,e,r,n){R(t,r,n),R(e,2*r,2*n),R(e,2*r+1,2*n+1)}function R(t,e,r){var n=t[e];t[e]=t[r],t[r]=n}function F(t,e,r,n){var i=t-r,a=e-n;return i*i+a*a}_.fromVectorTileJs=w,_.fromGeojsonVt=T,_.GeoJSONWrapper=k;var B=function(t){return t[0]},N=function(t){return t[1]},j=function(t,e,r,n,i){void 0===e&&(e=B),void 0===r&&(r=N),void 0===n&&(n=64),void 0===i&&(i=Float64Array),this.nodeSize=n,this.points=t;for(var a=t.length<65536?Uint16Array:Uint32Array,o=this.ids=new a(t.length),s=this.coords=new i(2*t.length),l=0;l=r&&s<=i&&l>=n&&l<=a&&c.push(t[d]);else{var v=Math.floor((p+h)/2);s=e[2*v],l=e[2*v+1],s>=r&&s<=i&&l>=n&&l<=a&&c.push(t[v]);var g=(f+1)%2;(0===f?r<=s:n<=l)&&(u.push(p),u.push(v-1),u.push(g)),(0===f?i>=s:a>=l)&&(u.push(v+1),u.push(h),u.push(g))}}return c}(this.ids,this.coords,t,e,r,n,this.nodeSize)},j.prototype.within=function(t,e,r){return function(t,e,r,n,i,a){for(var o=[0,t.length-1,0],s=[],l=i*i;o.length;){var u=o.pop(),c=o.pop(),f=o.pop();if(c-f<=a)for(var h=f;h<=c;h++)F(e[2*h],e[2*h+1],r,n)<=l&&s.push(t[h]);else{var p=Math.floor((f+c)/2),d=e[2*p],v=e[2*p+1];F(d,v,r,n)<=l&&s.push(t[p]);var g=(u+1)%2;(0===u?r-i<=d:n-i<=v)&&(o.push(f),o.push(p-1),o.push(g)),(0===u?r+i>=d:n+i>=v)&&(o.push(p+1),o.push(c),o.push(g))}}return s}(this.ids,this.coords,t,e,r,this.nodeSize)};var U={minZoom:0,maxZoom:16,radius:40,extent:512,nodeSize:64,log:!1,generateId:!1,reduce:null,map:function(t){return t}},V=function(t){this.options=X(Object.create(U),t),this.trees=new Array(this.options.maxZoom+1)};function H(t,e,r,n,i){return{x:t,y:e,zoom:1/0,id:r,parentId:-1,numPoints:n,properties:i}}function q(t,e){var r=t.geometry.coordinates,n=r[0],i=r[1];return{x:Y(n),y:W(i),zoom:1/0,index:e,parentId:-1}}function G(t){return{type:\"Feature\",id:t.id,properties:Z(t),geometry:{type:\"Point\",coordinates:[(n=t.x,360*(n-.5)),(e=t.y,r=(180-360*e)*Math.PI/180,360*Math.atan(Math.exp(r))/Math.PI-90)]}};var e,r,n}function Z(t){var e=t.numPoints,r=e>=1e4?Math.round(e/1e3)+\"k\":e>=1e3?Math.round(e/100)/10+\"k\":e;return X(X({},t.properties),{cluster:!0,cluster_id:t.id,point_count:e,point_count_abbreviated:r})}function Y(t){return t/360+.5}function W(t){var e=Math.sin(t*Math.PI/180),r=.5-.25*Math.log((1+e)/(1-e))/Math.PI;return r<0?0:r>1?1:r}function X(t,e){for(var r in e)t[r]=e[r];return t}function J(t){return t.x}function K(t){return t.y}function $(t,e,r,n){for(var i,a=n,o=r-e>>1,s=r-e,l=t[e],u=t[e+1],c=t[r],f=t[r+1],h=e+3;ha)i=h,a=p;else if(p===a){var d=Math.abs(h-o);dn&&(i-e>3&&$(t,e,i,n),t[i+2]=a,r-i>3&&$(t,i,r,n))}function Q(t,e,r,n,i,a){var o=i-r,s=a-n;if(0!==o||0!==s){var l=((t-r)*o+(e-n)*s)/(o*o+s*s);l>1?(r=i,n=a):l>0&&(r+=o*l,n+=s*l)}return(o=t-r)*o+(s=e-n)*s}function tt(t,e,r,n){var i={id:void 0===t?null:t,type:e,geometry:r,tags:n,minX:1/0,minY:1/0,maxX:-1/0,maxY:-1/0};return function(t){var e=t.geometry,r=t.type;if(\"Point\"===r||\"MultiPoint\"===r||\"LineString\"===r)et(t,e);else if(\"Polygon\"===r||\"MultiLineString\"===r)for(var n=0;n0&&(o+=n?(i*u-l*a)/2:Math.sqrt(Math.pow(l-i,2)+Math.pow(u-a,2))),i=l,a=u}var c=e.length-3;e[2]=1,$(e,0,c,r),e[c+2]=1,e.size=Math.abs(o),e.start=0,e.end=e.size}function at(t,e,r,n){for(var i=0;i1?1:r}function lt(t,e,r,n,i,a,o,s){if(n/=e,a>=(r/=e)&&o=n)return null;for(var l=[],u=0;u=r&&d=n)){var v=[];if(\"Point\"===h||\"MultiPoint\"===h)ut(f,v,r,n,i);else if(\"LineString\"===h)ct(f,v,r,n,i,!1,s.lineMetrics);else if(\"MultiLineString\"===h)ht(f,v,r,n,i,!1);else if(\"Polygon\"===h)ht(f,v,r,n,i,!0);else if(\"MultiPolygon\"===h)for(var g=0;g=r&&o<=n&&(e.push(t[a]),e.push(t[a+1]),e.push(t[a+2]))}}function ct(t,e,r,n,i,a,o){for(var s,l,u=ft(t),c=0===i?dt:vt,f=t.start,h=0;hr&&(l=c(u,p,d,g,y,r),o&&(u.start=f+s*l)):m>n?x=r&&(l=c(u,p,d,g,y,r),b=!0),x>n&&m<=n&&(l=c(u,p,d,g,y,n),b=!0),!a&&b&&(o&&(u.end=f+s*l),e.push(u),u=ft(t)),o&&(f+=s)}var _=t.length-3;p=t[_],d=t[_+1],v=t[_+2],(m=0===i?p:d)>=r&&m<=n&&pt(u,p,d,v),_=u.length-3,a&&_>=3&&(u[_]!==u[0]||u[_+1]!==u[1])&&pt(u,u[0],u[1],u[2]),u.length&&e.push(u)}function ft(t){var e=[];return e.size=t.size,e.start=t.start,e.end=t.end,e}function ht(t,e,r,n,i,a){for(var o=0;oo.maxX&&(o.maxX=c),f>o.maxY&&(o.maxY=f)}return o}function _t(t,e,r,n){var i=e.geometry,a=e.type,o=[];if(\"Point\"===a||\"MultiPoint\"===a)for(var s=0;s0&&e.size<(i?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;lo)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;i&&function(t,e){for(var r=0,n=0,i=t.length,a=i-2;n0===e)for(n=0,i=t.length;n24)throw new Error(\"maxZoom should be in the 0-24 range\");if(e.promoteId&&e.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n=n;u--){var c=+Date.now();s=this._cluster(s,u),this.trees[u]=new j(s,J,K,a,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",u,s.length,+Date.now()-c)}return r&&console.timeEnd(\"total time\"),this},V.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],u=[],c=0,f=l.range(Y(r),W(a),Y(i),W(n));c1?this._map(u,!0):null,g=(l<<5)+(e+1)+this.points.length,y=0,m=f;y>5},V.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},V.prototype._map=function(t,e){if(t.numPoints)return e?X({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?X({},n):n},Tt.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},Tt.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,u=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var c=1<1&&console.time(\"creation\"),h=this.tiles[f]=bt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),u)){u>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<1&&console.time(\"clipping\");var v,g,y,m,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;v=g=y=m=null,x=lt(t,c,r-_,r+T,0,h.minX,h.maxX,l),b=lt(t,c,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(v=lt(x,c,n-_,n+T,1,h.minY,h.maxY,l),g=lt(x,c,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(y=lt(b,c,n-_,n+T,1,h.minY,h.maxY,l),m=lt(b,c,n+w,n+k,1,h.minY,h.maxY,l),b=null),u>1&&console.timeEnd(\"clipping\"),s.push(v||[],e+1,2*r,2*n),s.push(g||[],e+1,2*r,2*n+1),s.push(y||[],e+1,2*r+1,2*n),s.push(m||[],e+1,2*r+1,2*n+1)}}},Tt.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,u=t,c=e,f=r;!l&&u>0;)u--,c=Math.floor(c/2),f=Math.floor(f/2),l=this.tiles[kt(u,c,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",u,c,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,u,c,f,t,e,r),a>1&&console.timeEnd(\"drilling down\"),this.tiles[s]?mt(this.tiles[s],i):null):null};var Mt=function(e){function r(t,r,n,i){e.call(this,t,r,n,At),i&&(this.loadGeoJSON=i)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&\"Idle\"!==this._state?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var i=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(a,o){if(a||!o)return r(a);if(\"object\"!=typeof o)return r(new Error(\"Input data given to '\"+n.source+\"' is not a valid GeoJSON object.\"));f(o,!0);try{e._geoJSONIndex=n.cluster?new V(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var i={},a={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),u=0,c=l;u=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var h=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e=0?1.2:1))}function y(t,e,r,n,i,a,o){for(var s=0;s65535)e(new Error(\"glyphs > 65535 not supported\"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=void 0,d=i/r*(n+1);if(l.isDash){var v=n-Math.abs(d);p=Math.sqrt(h*h+v*v)}else p=n-Math.sqrt(h*h+d*d);this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],u=0;u1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=l.isDash?h:-h;this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o=n&&e.x=i&&e.y0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+10&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;\"string\"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+\".loadData\",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor;var a={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};e.request=this.actor.send(i,a,(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,\"reloadTile\"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),O=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),I=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;or.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(I),z=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return\"number\"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];tthis.max){var o=this._getAndRemoveByKey(this.order[0]);o&&this.onRemove(o)}return this},j.prototype.has=function(t){return t.wrapped().key in this.data},j.prototype.getAndRemove=function(t){return this.has(t)?this._getAndRemoveByKey(t.wrapped().key):null},j.prototype._getAndRemoveByKey=function(t){var e=this.data[t].shift();return e.timeout&&clearTimeout(e.timeout),0===this.data[t].length&&delete this.data[t],this.order.splice(this.order.indexOf(t),1),e.value},j.prototype.getByKey=function(t){var e=this.data[t];return e?e[0].value:null},j.prototype.get=function(t){return this.has(t)?this.data[t.wrapped().key][0].value:null},j.prototype.remove=function(t,e){if(!this.has(t))return this;var r=t.wrapped().key,n=void 0===e?0:this.data[r].indexOf(e),i=this.data[r][n];return this.data[r].splice(n,1),i.timeout&&clearTimeout(i.timeout),0===this.data[r].length&&delete this.data[r],this.onRemove(i.value),this.order.splice(this.order.indexOf(r),1),this},j.prototype.setMaxSize=function(t){for(this.max=t;this.order.length>this.max;){var e=this._getAndRemoveByKey(this.order[0]);e&&this.onRemove(e)}return this},j.prototype.filter=function(t){var e=[];for(var r in this.data)for(var n=0,i=this.data[r];n1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(Dt(this._source.type)){for(var u={},c={},f=0,h=Object.keys(l);fthis._source.maxzoom){var g=d.children(this._source.maxzoom)[0],y=this.getTile(g);if(y&&y.hasData()){n[g.key]=g;continue}}else{var m=d.children(this._source.maxzoom);if(n[m[0].key]&&n[m[1].key]&&n[m[2].key]&&n[m[3].key])continue}for(var x=v.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(v=this.getTile(_))&&x&&(v=this._addTile(_)),v&&(n[_.key]=_,x=v.wasRequested(),v.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),u=s.map((function(t){return o.pointCoordinate(t)})),c=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,v=0,g=u;v=0&&y[1].y+g>=0){var m=l.map((function(t){return s.getTilePoint(t)})),x=u.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:m,cameraQueryGeometry:x,scale:v})}}},x=0;x=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||\"_geojsonTileLayer\",this._state.getState(t,e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles)this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,\"reloading\");this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function It(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function Dt(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function zt(){return new t.window.Worker(na.workerUrl)}Ot.maxOverzooming=10,Ot.maxUnderzooming=3;var Rt=\"mapboxgl_preloaded_worker_pool\",Ft=function(){this.active={}};Ft.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Qt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ae(e,r,n,i,a,o,s,l){var u=i?e.textSizeData:e.iconSizeData,c=t.evaluateSizeForZoom(u,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,v=n.transform.width/n.transform.height,g=!1,y=0;yMath.abs(n.x-r.x)*i?{useVertical:!0}:(e===t.WritingMode.vertical?r.yn.x)?{needsFlipping:!0}:null}function le(e,r,n,i,a,o,s,l,u,c,f,h,p,d){var v,g=r/24,y=e.lineOffsetX*g,m=e.lineOffsetY*g;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=oe(g,l,y,m,n,f,h,e,u,o,p);if(!w)return{notEnoughRoom:!0};var T=re(w.first.point,s).point,k=re(w.last.point,s).point;if(i&&!n){var A=se(e.writingMode,T,k,d);if(A)return A}v=[w.first];for(var M=e.glyphStartIndex+1;M0?C.point:ue(h,L,S,1,a),O=se(e.writingMode,S,P,d);if(O)return O}var I=ce(g*l.getoffsetX(e.glyphStartIndex),y,m,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,u,o,p);if(!I)return{notEnoughRoom:!0};v=[I]}for(var D=0,z=v;D0?1:-1,v=0;i&&(d*=-1,v=Math.PI),d<0&&(v+=Math.PI);for(var g=d>0?l+s:l+s+1,y=a,m=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((g+=d)=u)return null;if(m=y,w.push(y),void 0===(y=h[g])){var T=new t.Point(c.getx(g),c.gety(g)),k=re(T,f);if(k.signedDistanceFromCamera>0)y=h[g]=k.point;else{var A=g-d;y=ue(0===x?o:new t.Point(c.getx(A),c.gety(A)),T,m,_-x+1,f)}}x+=b,b=m.dist(y)}var M=(_-x)/b,S=y.sub(m),E=S.mult(M)._add(m);E._add(S._unit()._perp()._mult(n*d));var L=v+Math.atan2(y.y-m.y,y.x-m.x);return w.push(E),{point:E,angle:L,path:w}}Qt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Qt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Qt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Qt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Qt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Qt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s0:o},Qt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var u=[],c={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(a,s,o,l,this._queryCellCircle,u,c,i),n?u.length>0:u},Qt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Qt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Qt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Qt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,u=this.boxCells[i];if(null!==u)for(var c=this.bboxes,f=0,h=u;f=c[d+0]&&n>=c[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:c[d],y1:c[d+1],x2:c[d+2],y2:c[d+3]})}}}var v=this.circleCells[i];if(null!==v)for(var g=this.circles,y=0,m=v;yo*o+s*s},Qt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var u=(o-i)/2,c=Math.abs(e-(i+u));if(c>u+r)return!1;if(l<=s||c<=u)return!0;var f=l-s,h=c-u;return f*f+h*h<=r*r};var fe=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function he(t,e){for(var r=0;r=1;P--)C.push(E.path[P]);for(var O=1;O0){for(var R=C[0].clone(),F=C[0].clone(),B=1;B=A.x&&F.x<=M.x&&R.y>=A.y&&F.y<=M.y?[C]:F.xM.x||F.yM.y?[]:t.clipLine([C],A.x,A.y,M.x,M.y)}for(var N=0,j=z;N=this.screenRightBoundary||nthis.screenBottomBoundary},ve.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t=0&&e0?(this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(v=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:g,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:v},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:y,placedGlyphBoxes:m}):void 0},Ae.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,u=a.textLabelPlaneMatrix,c=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,v=a.collisionGroup,g=s.get(\"text-optional\"),y=s.get(\"icon-optional\"),m=s.get(\"text-allow-overlap\"),x=s.get(\"icon-allow-overlap\"),b=\"map\"===s.get(\"text-rotation-alignment\"),_=\"map\"===s.get(\"text-pitch-alignment\"),w=\"none\"!==s.get(\"icon-text-fit\"),T=\"viewport-y\"===s.get(\"symbol-z-order\"),k=m&&(x||!o.hasIconData()||y),A=x&&(m||!o.hasTextData()||g);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var M=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new xe(!1,!1,!1);else{var p,T=!1,M=!1,S=!0,E=null,L={box:null,offscreen:null},C={box:null,offscreen:null},P=null,O=null,I=0,D=0,z=0;a.textFeatureIndex?I=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(I=e.featureIndex),a.verticalTextFeatureIndex&&(D=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,n=a,i.markUsedOrientation(o,n,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,u=e.textBoxScale,c=w&&!x?r:null,h={box:[],offscreen:!1},p=m?2*N.length:N.length,d=0;d=N.length,k=i.attemptAnchorPlacement(g,t,a,s,u,b,_,f,l,v,y,e,o,n,c);if(k&&(h=k.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=k.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox,n=L&&L.box&&L.box.length;return o.allowVerticalPlacement&&!n&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),L&&(T=L.box,S=L.offscreen);var V=F(L&&L.box);if(!T&&i.prevPlacement){var H=i.prevPlacement.variableOffsets[e.crossTileID];H&&(i.variableOffsets[e.crossTileID]=H,i.markUsedJustification(o,H.anchor,e,V))}}else{var q=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,m,f,l,v.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return q(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?q(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(L&&L.box&&L.box.length)}}if(T=(p=L)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),Z=t.evaluateSizeForFeature(o.textSizeData,d,G),Y=s.get(\"text-padding\"),W=e.collisionCircleDiameter;P=i.collisionIndex.placeCollisionCircles(m,G,o.lineVertexArray,o.glyphOffsetArray,Z,l,u,c,n,_,v.predicate,W,Y),T=m||P.circles.length>0&&!P.collisionDetected,S=S&&P.offscreen}if(a.iconFeatureIndex&&(z=a.iconFeatureIndex),a.iconBox){var X=function(t){var e=w&&E?ke(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,v.predicate)};M=C&&C.box&&C.box.length&&a.verticalIconBox?(O=X(a.verticalIconBox)).box.length>0:(O=X(a.iconBox)).box.length>0,S=S&&O.offscreen}var J=g||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,K=y||0===e.numIconVertices;if(J||K?K?J||(M=M&&T):T=M&&T:M=T=M&&T,T&&p&&p.box&&(C&&C.box&&D?i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,D,v.ID):i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,I,v.ID)),M&&O&&i.collisionIndex.insertCollisionBox(O.box,s.get(\"icon-ignore-placement\"),o.bucketInstanceId,z,v.ID),P&&(T&&i.collisionIndex.insertCollisionCircles(P.circles,s.get(\"text-ignore-placement\"),o.bucketInstanceId,I,v.ID),n)){var $=o.bucketInstanceId,Q=i.collisionCircleArrays[$];void 0===Q&&(Q=i.collisionCircleArrays[$]=new be);for(var tt=0;tt=0;--E){var L=S[E];M(o.symbolInstances.get(L),o.collisionArrays[L])}else for(var C=e.symbolInstanceStart;C=0&&(e.text.placedSymbolArray.get(u).crossTileID=a>=0&&u!==a?0:n.crossTileID)}},Ae.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o0||l>0,x=a.numIconVertices>0,b=i.placedOrientations[a.crossTileID],_=b===t.WritingMode.vertical,w=b===t.WritingMode.horizontal||b===t.WritingMode.horizontalOnly;if(m){var T=De(y.text),k=_?ze:T;d(e.text,s,k);var A=w?ze:T;d(e.text,l,A);var M=y.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=M||_?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=M||w?1:0);var S=i.variableOffsets[a.crossTileID];S&&i.markUsedJustification(e,S.anchor,a,b);var E=i.placedOrientations[a.crossTileID];E&&(i.markUsedJustification(e,\"left\",a,E),i.markUsedOrientation(e,E,a))}if(x){var L=De(y.icon),C=!(h&&a.verticalPlacedIconSymbolIndex&&_);if(a.placedIconSymbolIndex>=0){var P=C?L:ze;d(e.icon,a.numIconVertices,P),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=y.icon.isHidden()}if(a.verticalPlacedIconSymbolIndex>=0){var O=C?ze:L;d(e.icon,a.numVerticalIconVertices,O),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=y.icon.isHidden()}}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var I=e.collisionArrays[n];if(I){var D=new t.Point(0,0);if(I.textBox||I.verticalTextBox){var z=!0;if(u){var R=i.variableOffsets[v];R?(D=Te(R.anchor,R.width,R.height,R.textOffset,R.textBoxScale),c&&D._rotate(f?i.transform.angle:-i.transform.angle)):z=!1}I.textBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!z||_,D.x,D.y),I.verticalTextBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!z||w,D.x,D.y)}var F=Boolean(!w&&I.verticalIconBox);I.iconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,F,h?D.x:0,h?D.y:0),I.verticalIconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,!F,h?D.x:0,h?D.y:0)}}},g=0;gt},Ae.prototype.setStale=function(){this.stale=!0};var Se=Math.pow(2,25),Ee=Math.pow(2,24),Le=Math.pow(2,17),Ce=Math.pow(2,16),Pe=Math.pow(2,9),Oe=Math.pow(2,8),Ie=Math.pow(2,1);function De(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*Se+e*Ee+r*Le+e*Ce+r*Pe+e*Oe+r*Ie+e}var ze=0,Re=function(t){this._sortAcrossTiles=\"viewport-y\"!==t.layout.get(\"symbol-z-order\")&&void 0!==t.layout.get(\"symbol-sort-key\").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Re.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Re(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},Fe.prototype.commit=function(t){return this.placement.commit(t),this.placement};var Be=512/t.EXTENT/2,Ne=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;nt.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var u=o[t.scaledTo(Number(a)).key];u&&u.findMatches(e.symbolInstances,t,i)}}for(var c=0;c1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,c())})),u=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),(function(t,e){u=null,o||(o=t,a=e,c())}));function c(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],u=l.width,c=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,v=l.stretchX,g=l.stretchY,y=l.content,m=new t.RGBAImage({width:u,height:c});t.RGBAImage.copy(e,m,{x:f,y:h},{x:0,y:0},{width:u,height:c}),r[s]={data:m,pixelRatio:d,sdf:p,stretchX:v,stretchY:g,content:y}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),u&&(u.cancel(),u=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast(\"setImages\",r._availableImages),r.fire(new t.Event(\"data\",{dataType:\"style\"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r0)throw new Error(\"Unimplemented: \"+i.map((function(t){return t.command})).join(\", \")+\".\");return n.forEach((function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0&&this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n))){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Ot(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else{var a;if(\"custom\"===e.type){if(He(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&\"custom\"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,\"layers.\"+i.id+\".filter\",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;\"geojson\"===o&&i?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o=\"vector\"===a?e.sourceLayer:void 0;\"vector\"!==a||o?r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is requred to remove its specific state property.\"))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if(\"vector\"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&\"raster\"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s=0;d--){var v=this._order[d];if(r(v))for(var g=i.length-1;g>=0;g--){var y=i[g].feature;if(n[y.layer.id] 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),nr=_r(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),ir=_r(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\"),ar=_r(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),or=_r(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),sr=_r(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),lr=_r(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),ur=_r(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),cr=_r(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),fr=_r(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform float u_maxzoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggeration=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/ pow(2.0,(u_zoom-u_maxzoom)*exaggeration+19.2562-u_zoom);gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),hr=_r(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),pr=_r(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),dr=_r(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,vec2(v_lineprogress,0.5));gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define MAX_LINE_DISTANCE 32767.0\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_lineprogress=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0/MAX_LINE_DISTANCE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),vr=_r(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}\"),gr=_r(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),yr=_r(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),mr=_r(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),xr=_r(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\"),br=_r(\"#define SDF_PX 8.0\\n#define SDF 1.0\\n#define ICON 0.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}\");function _r(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n={};return{fragmentSource:t=t.replace(r,(function(t,e,r,i,a){return n[a]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+a+\"\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"})),vertexSource:e=e.replace(r,(function(t,e,r,i,a){var o=\"float\"===i?\"vec2\":\"vec4\",s=a.match(/color/)?\"color\":o;return n[a]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+a+\" = a_\"+a+\";\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+r+\" \"+i+\" \"+a+\" = a_\"+a+\";\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n \"+r+\" \"+i+\" \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"}))}}var wr=Object.freeze({__proto__:null,prelude:Xe,background:Je,backgroundPattern:Ke,circle:$e,clippingMask:Qe,heatmap:tr,heatmapTexture:er,collisionBox:rr,collisionCircle:nr,debug:ir,fill:ar,fillOutline:or,fillOutlinePattern:sr,fillPattern:lr,fillExtrusion:ur,fillExtrusionPattern:cr,hillshadePrepare:fr,hillshade:hr,line:pr,lineGradient:dr,linePattern:vr,lineSDF:gr,raster:yr,symbolIcon:mr,symbolSDF:xr,symbolTextAndIcon:br}),Tr=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};Tr.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,u=0;!l&&u>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}kr.prototype.draw=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v){var g,y=t.gl;if(!this.failedToCreate){for(var m in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[m].set(o[m]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(g={},g[y.LINES]=2,g[y.TRIANGLES]=3,g[y.LINE_STRIP]=1,g)[e],b=0,_=c.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new Tr)).bind(t,this,l,p?p.getPaintVertexBuffers():[],u,w.vertexOffset,d,v),y.drawElements(e,w.primitiveLength*x,y.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var Mr=function(e,r,n,i){var a=r.style.light,o=a.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===a.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var u=a.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get(\"intensity\"),u_lightcolor:[u.r,u.g,u.b],u_vertical_gradient:+n,u_opacity:i}},Sr=function(e,r,n,i,a,o,s){return t.extend(Mr(e,r,n,i),Ar(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},Er=function(t){return{u_matrix:t}},Lr=function(e,r,n,i){return t.extend(Er(e),Ar(n,r,i))},Cr=function(t,e){return{u_matrix:t,u_world:e}},Pr=function(e,r,n,i,a){return t.extend(Lr(e,r,n,i),{u_world:a})},Or=function(e,r,n,i){var a,o,s=e.transform;if(\"map\"===i.paint.get(\"circle-pitch-alignment\")){var l=ge(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===i.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get(\"circle-translate\"),i.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},Ir=function(t,e,r){var n=ge(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},Dr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},zr=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Rr=function(t){return{u_matrix:t}},Fr=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:ge(e,1,r),u_intensity:n}},Br=function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:n,u_color_ramp:i,u_opacity:r.paint.get(\"heatmap-opacity\")}},Nr=function(e,r,n){var i=n.paint.get(\"hillshade-shadow-color\"),a=n.paint.get(\"hillshade-highlight-color\"),o=n.paint.get(\"hillshade-accent-color\"),s=n.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===n.paint.get(\"hillshade-illumination-anchor\")&&(s-=e.transform.angle);var l,u,c,f=!e.options.moving;return{u_matrix:e.transform.calculatePosMatrix(r.tileID.toUnwrapped(),f),u_image:0,u_latrange:(l=r.tileID,u=Math.pow(2,l.canonical.z),c=l.canonical.y,[new t.MercatorCoordinate(0,c/u).toLngLat().lat,new t.MercatorCoordinate(0,(c+1)/u).toLngLat().lat]),u_light:[n.paint.get(\"hillshade-exaggeration\"),s],u_shadow:i,u_highlight:a,u_accent:o}},jr=function(e,r,n){var i=r.stride,a=t.create();return t.ortho(a,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(a,a,[0,-t.EXTENT,0]),{u_matrix:a,u_image:1,u_dimension:[i,i],u_zoom:e.overscaledZ,u_maxzoom:n,u_unpack:r.getUnpackVector()}};var Ur=function(e,r,n){var i=e.transform;return{u_matrix:Zr(e,r,n),u_ratio:1/ge(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},Vr=function(e,r,n){return t.extend(Ur(e,r,n),{u_image:0})},Hr=function(e,r,n,i){var a=e.transform,o=Gr(r,a);return{u_matrix:Zr(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/ge(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},qr=function(e,r,n,i,a){var o=e.transform,s=e.lineAtlas,l=Gr(r,o),u=\"round\"===n.layout.get(\"line-cap\"),c=s.getDash(i.from,u),f=s.getDash(i.to,u),h=c.width*a.fromScale,p=f.width*a.toScale;return t.extend(Ur(e,r,n),{u_patternscale_a:[l/h,-c.height/2],u_patternscale_b:[l/p,-f.height/2],u_sdfgamma:s.width/(256*Math.min(h,p)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:c.y,u_tex_y_b:f.y,u_mix:a.t})};function Gr(t,e){return 1/ge(t,1,e.tileZoom)}function Zr(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var Yr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get(\"raster-brightness-min\"),u_brightness_high:i.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=i.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get(\"raster-contrast\"),a>0?1/(1-a):1+a),u_spin_weights:Wr(i.paint.get(\"raster-hue-rotate\"))};var a,o};function Wr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Xr,Jr=function(t,e,r,n,i,a,o,s,l,u){var c=i.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:c.cameraToCenterDistance,u_pitch:c.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:c.width/c.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:u,u_texture:0}},Kr=function(e,r,n,i,a,o,s,l,u,c,f){var h=a.transform;return t.extend(Jr(e,r,n,i,a,o,s,l,u,c),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},$r=function(e,r,n,i,a,o,s,l,u,c){return t.extend(Kr(e,r,n,i,a,o,s,l,!0,u,!0),{u_texsize_icon:c,u_texture_icon:1})},Qr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},tn=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,u=Math.pow(2,n.tileID.overscaledZ),c=n.tileSize*Math.pow(2,r.transform.tileZoom)/u,f=c*(n.tileID.canonical.x+n.tileID.wrap*u),h=c*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/ge(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},en={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_maxzoom:new t.Uniform1f(e,r.u_maxzoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function rn(e,r,n,i,a,o,s){for(var l=e.context,u=l.gl,c=e.useProgram(\"collisionBox\"),f=[],h=0,p=0,d=0;d0){var _=t.create(),w=m;t.mul(_,y.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,y.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&c.draw(l,u.LINES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,Ir(m,e.transform,g),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram(\"collisionCircle\"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var A=0,M=0,S=f;M=0&&(v[y.associatedIconIndex]={shiftedAnchor:S,angle:E})}else he(y.numGlyphs,p)}if(f){d.clear();for(var C=e.icon.placedSymbolArray,P=0;P0){var s=t.browser.now(),l=(s-e.timeAdded)/o,u=r?(s-r.timeAdded)/o:-1,c=n.getSource(),f=a.coveringZoomLevel({tileSize:c.tileSize,roundZoom:c.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-u,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var vn=new t.Color(1,0,0,1),gn=new t.Color(0,1,0,1),yn=new t.Color(0,0,1,1),mn=new t.Color(1,0,1,1),xn=new t.Color(0,1,1,1);function bn(t){var e=t.transform.padding;_n(t,t.transform.height-(e.top||0),3,vn),_n(t,e.bottom||0,3,gn),wn(t,e.left||0,3,yn),wn(t,t.transform.width-(e.right||0),3,mn);var r=t.transform.centerPoint;!function(t,e,r,n){var i=20,a=2;Tn(t,e-a/2,r-i/2,a,i,n),Tn(t,e-i/2,r-a/2,i,a,n)}(t,r.x,t.transform.height-r.y,xn)}function _n(t,e,r,n){Tn(t,0,e+r/2,t.transform.width,r,n)}function wn(t,e,r,n){Tn(t,e-r/2,0,r,t.transform.height,n)}function Tn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function kn(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=Mt.disabled,u=Et.disabled,c=e.colorModeForRenderPass(),f=\"$debug\";i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,u,c,Ct.disabled,zr(o,t.Color.red),f,e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var h=r.getTileByID(n.key).latestRawTileData,p=h&&h.byteLength||0,d=Math.floor(p/1024),v=r.getTile(n).tileSize,g=512/Math.min(v,512)*(n.overscaledZ/e.transform.zoom)*.5,y=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(y+=\" => \"+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext(\"2d\");i.clearRect(0,0,r.width,r.height),i.shadowColor=\"white\",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle=\"white\",i.textBaseline=\"top\",i.font=\"bold 36px Open Sans, sans-serif\",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,y+\" \"+d+\"kb\"),s.draw(i,a.TRIANGLES,l,u,Lt.alphaBlended,Ct.disabled,zr(o,t.Color.transparent,g),f,e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var An={symbol:function(e,r,n,i,a){if(\"translucent\"===e.renderPass){var o=Et.disabled,s=e.colorModeForRenderPass();n.layout.get(\"text-variable-anchor\")&&function(e,r,n,i,a,o,s){for(var l=r.transform,u=\"map\"===a,c=\"map\"===o,f=0,h=e;f256&&this.clearStencil(),r.setColorMode(Lt.disabled),r.setDepthMode(Mt.disabled);var i=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var a=0,o=e;a256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new Et({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},Mn.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new Et({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},Mn.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s=0;this.currentLayer--){var w=this.style._layers[i[this.currentLayer]],T=a[w.source],k=c[w.source];this._renderTileClippingMasks(w,k),this.renderLayer(this,T,w,k)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer0?e.pop():null},Mn.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},Mn.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e?e.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new kr(this.context,wr[t],e,en[t],this._showOverdrawInspector)),this.cache[r]},Mn.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},Mn.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},Mn.prototype.initDebugOverlayCanvas=function(){if(null==this.debugOverlayCanvas){this.debugOverlayCanvas=t.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var e=this.context.gl;this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,e.RGBA)}},Mn.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var Sn=function(t,e){this.points=t,this.planes=e};Sn.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new Sn(a,o)};var En=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};En.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var u=Number.MAX_VALUE,c=-Number.MAX_VALUE,f=0;fthis.max[l]-this.min[l])return 0}return 1};var Ln=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=t,this.bottom=e,this.left=r,this.right=n};Ln.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},Ln.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},Ln.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},Ln.prototype.clone=function(){return new Ln(this.top,this.bottom,this.left,this.right)},Ln.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var Cn=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new Ln,this._posMatrixCache={},this._alignedPosMatrixCache={}},Pn={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};Cn.prototype.clone=function(){var t=new Cn(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},Pn.minZoom.get=function(){return this._minZoom},Pn.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},Pn.maxZoom.get=function(){return this._maxZoom},Pn.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},Pn.minPitch.get=function(){return this._minPitch},Pn.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},Pn.maxPitch.get=function(){return this._maxPitch},Pn.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},Pn.renderWorldCopies.get=function(){return this._renderWorldCopies},Pn.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},Pn.worldSize.get=function(){return this.tileSize*this.scale},Pn.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},Pn.size.get=function(){return new t.Point(this.width,this.height)},Pn.bearing.get=function(){return-this.angle/Math.PI*180},Pn.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},Pn.pitch.get=function(){return this._pitch/Math.PI*180},Pn.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},Pn.fov.get=function(){return this._fov/Math.PI*180},Pn.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},Pn.zoom.get=function(){return this._zoom},Pn.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},Pn.center.get=function(){return this._center},Pn.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},Pn.padding.get=function(){return this._edgeInsets.toJSON()},Pn.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},Pn.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},Cn.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},Cn.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},Cn.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},Cn.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),u=s-1;u<=l+1;u++)0!==u&&r.push(new t.UnwrappedTileID(u,e));return r},Cn.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&re.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=Sn.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var u=function(t){return{aabb:new En([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},c=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)c.push(u(-d)),c.push(u(d));for(c.push(u(0));c.length>0;){var v=c.pop(),g=v.x,y=v.y,m=v.fullyVisible;if(!m){var x=v.aabb.intersects(s);if(0===x)continue;m=2===x}var b=v.aabb.distanceX(o),_=v.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_)),T=3+(1<T&&v.zoom>=l)f.push({tileID:new t.OverscaledTileID(v.zoom===h?p:v.zoom,v.wrap,v.zoom,g,y),distanceSq:t.sqrLen([o[0]-.5-g,o[1]-.5-y])});else for(var k=0;k<4;k++){var A=(g<<1)+k%2,M=(y<<1)+(k>>1);c.push({aabb:v.aabb.quadrant(k),zoom:v.zoom+1,x:A,y:M,wrap:v.wrap,fullyVisible:m})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},Cn.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},Pn.unmodified.get=function(){return this._unmodified},Cn.prototype.zoomScale=function(t){return Math.pow(2,t)},Cn.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},Cn.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},Cn.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},Pn.point.get=function(){return this.project(this.center)},Cn.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},Cn.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},Cn.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},Cn.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},Cn.prototype.coordinateLocation=function(t){return t.toLngLat()},Cn.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[0]/i,s=n[0]/a,l=r[1]/i,u=n[1]/a,c=r[2]/i,f=n[2]/a,h=c===f?0:(0-c)/(f-c);return new t.MercatorCoordinate(t.number(o,s,h)/this.worldSize,t.number(l,u,h)/this.worldSize)},Cn.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},Cn.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},Cn.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},Cn.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},Cn.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},Cn.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},Cn.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,u=this.size,c=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-ao&&(i=o-g)}if(this.lngRange){var y=p.x,m=u.x/2;y-ml&&(n=l-m)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=c,this._constraining=!1}},Cn.prototype._calcMatrices=function(){if(this.height){var e=this._fov/2,r=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(e)*this.height;var n=Math.PI/2+this._pitch,i=this._fov*(.5+r.y/this.height),a=Math.sin(i)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-n-i,.01,Math.PI-.01)),o=this.point,s=o.x,l=o.y,u=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),c=this.height/50,f=new Float64Array(16);t.perspective(f,this._fov,this.width/this.height,c,u),f[8]=2*-r.x/this.width,f[9]=2*r.y/this.height,t.scale(f,f,[1,-1,1]),t.translate(f,f,[0,0,-this.cameraToCenterDistance]),t.rotateX(f,f,this._pitch),t.rotateZ(f,f,this.angle),t.translate(f,f,[-s,-l,0]),this.mercatorMatrix=t.scale([],f,[this.worldSize,this.worldSize,this.worldSize]),t.scale(f,f,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=f,this.invProjMatrix=t.invert([],this.projMatrix);var h=this.width%2/2,p=this.height%2/2,d=Math.cos(this.angle),v=Math.sin(this.angle),g=s-Math.round(s)+d*h+v*p,y=l-Math.round(l)+d*p+v*h,m=new Float64Array(f);if(t.translate(m,m,[g>.5?g-1:g,y>.5?y-1:y,0]),this.alignedProjMatrix=m,f=t.create(),t.scale(f,f,[this.width/2,-this.height/2,1]),t.translate(f,f,[1,-1,0]),this.labelPlaneMatrix=f,f=t.create(),t.scale(f,f,[1,-1,1]),t.translate(f,f,[-1,-1,0]),t.scale(f,f,[2/this.width,2/this.height,1]),this.glCoordMatrix=f,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(f=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=f,this._posMatrixCache={},this._alignedPosMatrixCache={}}},Cn.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},Cn.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},Cn.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},On.prototype._updateHashUnthrottled=function(){var e=this.getHashString();try{t.window.history.replaceState(t.window.history.state,\"\",e)}catch(t){}};var In={linearity:.3,easing:t.bezier(0,0,.3,1)},Dn=t.extend({deceleration:2500,maxSpeed:1400},In),zn=t.extend({deceleration:20,maxSpeed:1400},In),Rn=t.extend({deceleration:1e3,maxSpeed:360},In),Fn=t.extend({deceleration:1e3,maxSpeed:90},In),Bn=function(t){this._map=t,this.clear()};function Nn(t,e){(!t.duration||t.duration0&&r-e[0].time>160;)e.shift()},Bn.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n=this._clickTolerance||this._map.fire(new Un(t.type,this._map,t))},qn.prototype.dblclick=function(t){return this._firePreventable(new Un(t.type,this._map,t))},qn.prototype.mouseover=function(t){this._map.fire(new Un(t.type,this._map,t))},qn.prototype.mouseout=function(t){this._map.fire(new Un(t.type,this._map,t))},qn.prototype.touchstart=function(t){return this._firePreventable(new Vn(t.type,this._map,t))},qn.prototype.touchmove=function(t){this._map.fire(new Vn(t.type,this._map,t))},qn.prototype.touchend=function(t){this._map.fire(new Vn(t.type,this._map,t))},qn.prototype.touchcancel=function(t){this._map.fire(new Vn(t.type,this._map,t))},qn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},qn.prototype.isEnabled=function(){return!0},qn.prototype.isActive=function(){return!1},qn.prototype.enable=function(){},qn.prototype.disable=function(){};var Gn=function(t){this._map=t};Gn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},Gn.prototype.mousemove=function(t){this._map.fire(new Un(t.type,this._map,t))},Gn.prototype.mousedown=function(){this._delayContextMenu=!0},Gn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new Un(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},Gn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new Un(t.type,this._map,t)),this._map.listens(\"contextmenu\")&&t.preventDefault()},Gn.prototype.isEnabled=function(){return!0},Gn.prototype.isActive=function(){return!1},Gn.prototype.enable=function(){},Gn.prototype.disable=function(){};var Zn=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Yn(t,e){for(var r={},n=0;nthis.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n30)&&(this.aborted=!0)}}},Wn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Xn=function(t){this.singleTap=new Wn(t),this.numTaps=t.numTaps,this.reset()};Xn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Xn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Xn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Xn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Jn=function(){this._zoomIn=new Xn({numTouches:1,numTaps:2}),this._zoomOut=new Xn({numTouches:2,numTaps:1}),this.reset()};Jn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Jn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Jn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Jn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Jn.prototype.touchcancel=function(){this.reset()},Jn.prototype.enable=function(){this._enabled=!0},Jn.prototype.disable=function(){this._enabled=!1,this.reset()},Jn.prototype.isEnabled=function(){return this._enabled},Jn.prototype.isActive=function(){return this._active};var Kn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};Kn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},Kn.prototype._correctButton=function(t,e){return!1},Kn.prototype._move=function(t,e){return{}},Kn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},Kn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r&&(t.preventDefault(),this._moved||!(e.dist(r)0&&(this._active=!0);var i=Yn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var u=i[l],c=this._touches[l];c&&(a._add(u),o._add(u.sub(c)),s++,i[l]=u)}if(this._touches=i,!(sMath.abs(t.x)}var ui=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,li(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid)return this._lastPoints=t,this._active=!0,{pitchDelta:(n.y+i.y)/2*-.5}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return li(t)&&li(e)&&a}},e}(ri),ci={panStep:100,bearingStep:15,pitchStep:10},fi=function(){var t=ci;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep};function hi(t){return t*(2-t)}fi.prototype.reset=function(){this._active=!1},fi.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:\"keyboardHandler\",easing:hi,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},fi.prototype.enable=function(){this._enabled=!0},fi.prototype.disable=function(){this._enabled=!1,this.reset()},fi.prototype.isEnabled=function(){return this._enabled},fi.prototype.isActive=function(){return this._active};var pi=4.000244140625,di=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=.0022222222222222222,t.bindAll([\"_onWheel\",\"_onTimeout\",\"_onScrollFrame\",\"_onScrollFinished\"],this)};di.prototype.setZoomRate=function(t){this._defaultZoomRate=t},di.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},di.prototype.isEnabled=function(){return!!this._enabled},di.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},di.prototype.isZooming=function(){return!!this._zooming},di.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},di.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},di.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%pi==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},di.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(t)},di.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},di.prototype.renderFrame=function(){return this._onScrollFrame()},di.prototype._onScrollFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>pi?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,u=this._easing,c=!1;if(\"wheel\"===this._type&&l&&u){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=u(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):c=!0}else o=s,c=!0;return this._active=!0,c&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!c,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},di.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},di.prototype.reset=function(){this._active=!1};var vi=function(t,e){this._clickZoom=t,this._tapZoom=e};vi.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},vi.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},vi.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},vi.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var gi=function(){this.reset()};gi.prototype.reset=function(){this._active=!1},gi.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},gi.prototype.enable=function(){this._enabled=!0},gi.prototype.disable=function(){this._enabled=!1,this.reset()},gi.prototype.isEnabled=function(){return this._enabled},gi.prototype.isActive=function(){return this._active};var yi=function(){this._tap=new Xn({numTouches:1,numTaps:1}),this.reset()};yi.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},yi.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},yi.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},yi.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},yi.prototype.touchcancel=function(){this.reset()},yi.prototype.enable=function(){this._enabled=!0},yi.prototype.disable=function(){this._enabled=!1,this.reset()},yi.prototype.isEnabled=function(){return this._enabled},yi.prototype.isActive=function(){return this._active};var mi=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};mi.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},mi.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},mi.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},mi.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var xi=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};xi.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},xi.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},xi.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},xi.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var bi=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};bi.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},bi.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},bi.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},bi.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},bi.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},bi.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var _i=function(t){return t.zoom||t.drag||t.pitch||t.rotate},wi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(t.Event);function Ti(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var ki=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Bn(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var i=this._el;this._listeners=[[i,\"touchstart\",{passive:!1}],[i,\"touchmove\",{passive:!1}],[i,\"touchend\",void 0],[i,\"touchcancel\",void 0],[i,\"mousedown\",void 0],[i,\"mousemove\",void 0],[i,\"mouseup\",void 0],[t.window.document,\"mousemove\",{capture:!0}],[t.window.document,\"mouseup\",void 0],[i,\"mouseover\",void 0],[i,\"mouseout\",void 0],[i,\"dblclick\",void 0],[i,\"click\",void 0],[i,\"keydown\",{capture:!1}],[i,\"keyup\",void 0],[i,\"wheel\",{passive:!1}],[i,\"contextmenu\",void 0],[t.window,\"blur\",void 0]];for(var a=0,o=this._listeners;aa?Math.min(2,_):Math.max(.5,_),w=Math.pow(g,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(v));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event(\"movestart\",e)),this._zooming&&!n.zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&!n.rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&!n.pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event(\"zoomend\",e)),i&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),u=this.getPadding(),c=\"zoom\"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,p=\"padding\"in e?e.padding:a.padding,d=a.zoomScale(c-o),v=t.Point.convert(e.offset),g=a.centerPoint.add(v),y=a.pointLocation(g),m=t.LngLat.convert(e.center||y);this._normalizeCenter(m);var x=a.project(y),b=a.project(m).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if(\"minZoom\"in e){var A=t.clamp(Math.min(e.minZoom,o,c),a.minZoom,a.maxZoom),M=w/a.zoomScale(A-o);_=Math.sqrt(M/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function L(t){return(Math.exp(t)-Math.exp(-t))/2}function C(t){return(Math.exp(t)+Math.exp(-t))/2}var P=E(0),O=function(t){return C(P)/C(P+_*t)},I=function(t){return w*((C(P)*(L(e=P+_*t)/C(e))-L(P))/S)/k;var e},D=(E(1)-P)/_;if(Math.abs(k)<1e-6||!isFinite(D)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var z=Te.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*D,d=1/O(i);a.zoom=1===e?c:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(u,p,e),g=a.centerPoint.add(v));var y=1===e?m:a.unproject(x.add(b.mult(I(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?y.wrap():y,g),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop()}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)180?-360:r<-180?360:0}},r}(t.Evented),Mi=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};Mi.prototype.getDefaultPosition=function(){return\"bottom-right\"},Mi.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},Mi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},Mi.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n=0)return!1;return!0}))).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},Mi.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\")};var Si=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};Si.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},Si.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},Si.prototype.getDefaultPosition=function(){return\"bottom-left\"},Si.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},Si.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t)if(t[e].getSource().mapbox_logo)return!0;return!1}},Si.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var Ei=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};Ei.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},Ei.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;re.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(null!=e.minPitch&&e.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(null!=e.maxPitch&&e.maxPitch>Ii)throw new Error(\"maxPitch must be less than or equal to 60\");var i=new Cn(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new Ei,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},Li,e.locale),this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof Pi))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",(function(){return r._update(!1)})),this.on(\"moveend\",(function(){return r._update(!1)})),this.on(\"zoom\",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1)),this.handlers=new ki(this,e);var a=\"string\"==typeof e.hash&&e.hash||void 0;this._hash=e.hash&&new On(a).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new Mi({customAttribution:e.customAttribution})),this.addControl(new Si,e.logoPosition),this.on(\"style.load\",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on(\"data\",(function(e){r._update(\"style\"===e.dataType),r.fire(new t.Event(e.dataType+\"data\",e))})),this.on(\"dataloading\",(function(e){r.fire(new t.Event(e.dataType+\"dataloading\",e))}))}n&&(i.__proto__=n),i.prototype=Object.create(n&&n.prototype),i.prototype.constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&e.getDefaultPosition&&(r=e.getDefaultPosition()),void 0===r&&(r=\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e))),this.fire(new t.Event(\"resize\",e)),a&&this.fire(new t.Event(\"moveend\",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()Ii)throw new Error(\"maxPitch must be less than or equal to 60\");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if(\"mouseenter\"===t||\"mouseover\"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new Un(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new Un(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new Un(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;if(void 0===r)return n.prototype.off.call(this,t,e);return this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ni.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ni.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ni.prototype.off=function(){var t=this.element;r.removeEventListener(t,\"mousedown\",this.mousedown),r.removeEventListener(t,\"touchstart\",this.touchstart,{passive:!1}),r.removeEventListener(t,\"touchmove\",this.touchmove),r.removeEventListener(t,\"touchend\",this.touchend),r.removeEventListener(t,\"touchcancel\",this.reset),this.offTemp()},Ni.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,\"mousemove\",this.mousemove),r.removeEventListener(t.window,\"mouseup\",this.mouseup)},Ni.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,\"mousemove\",this.mousemove),r.addEventListener(t.window,\"mouseup\",this.mouseup)},Ni.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ni.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ni.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ni.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ni.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)e.getEast()||r.latitudee.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event(\"outofmaxbounds\",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+\"px\",this._circleElement.style.height=i+\"px\"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var r=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=r,this._geolocateButton.setAttribute(\"aria-label\",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&Yi)return;this._setErrorState()}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",!1===e){t.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var i=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute(\"aria-label\",i)}else{var a=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=a,this._geolocateButton.setAttribute(\"aria-label\",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new qi(this._dotElement),this._circleElement=r.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new qi({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",(function(e){var r=e.originalEvent&&\"resize\"===e.originalEvent.type;e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||r||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":Zi--,Yi=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}if(\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),++Zi>1?(e={maximumAge:6e5,timeout:0},Yi=!0):(e=this.options.positionOptions,Yi=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Xi={maxWidth:100,unit:\"metric\"},Ji=function(e){this.options=t.extend({},Xi,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function Ki(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&\"imperial\"===r.unit){var l=3.2808*s;l>5280?$i(e,n,l/5280,t._getUIString(\"ScaleControl.Miles\")):$i(e,n,l,t._getUIString(\"ScaleControl.Feet\"))}else r&&\"nautical\"===r.unit?$i(e,n,s/1852,t._getUIString(\"ScaleControl.NauticalMiles\")):s>=1e3?$i(e,n,s/1e3,t._getUIString(\"ScaleControl.Kilometers\")):$i(e,n,s,t._getUIString(\"ScaleControl.Meters\"))}function $i(t,e,r,n){var i,a,o,s=(i=r,(a=Math.pow(10,(\"\"+Math.floor(i)).length-1))*((o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o))),l=s/r;t.style.width=e*l+\"px\",t.innerHTML=s+\" \"+n}Ji.prototype.getDefaultPosition=function(){return\"bottom-left\"},Ji.prototype._onMove=function(){Ki(this._map,this._container,this.options)},Ji.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl 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this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},Qi.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},Qi.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},Qi.prototype._setupUI=function(){var e=this._fullscreenButton=r.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);r.create(\"span\",\"mapboxgl-ctrl-icon\",e).setAttribute(\"aria-hidden\",!0),e.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},Qi.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},Qi.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},Qi.prototype._isFullscreen=function(){return this._fullscreen},Qi.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},Qi.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var ta={closeButton:!0,closeOnClick:!0,className:\"\",maxWidth:\"240px\"},ea=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(ta),r),t.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createContent=function(){this._content&&r.remove(this._content),this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"×\",this._closeButton.addEventListener(\"click\",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(t){var e=this,n=this._lngLat||this._trackPointer;if(this._map&&n&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach((function(t){return e._container.classList.add(t)})),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=ji(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||t)){var i=this._pos=this._trackPointer&&t?t:this._map.project(this._lngLat),a=this.options.anchor,o=ra(this.options.offset);if(!a){var s,l=this._container.offsetWidth,u=this._container.offsetHeight;s=i.y+o.bottom.ythis._map.transform.height-u?[\"bottom\"]:[],i.xthis._map.transform.width-l/2&&s.push(\"right\"),a=0===s.length?\"bottom\":s.join(\"-\")}var c=i.add(o[a]).round();r.setTransform(this._container,Ui[a]+\" translate(\"+c.x+\"px,\"+c.y+\"px)\"),Vi(this._container,a,\"popup\")}},n.prototype._onClose=function(){this.remove()},n}(t.Evented);function ra(e){if(e){if(\"number\"==typeof e){var r=Math.round(Math.sqrt(.5*Math.pow(e,2)));return{center:new t.Point(0,0),top:new t.Point(0,e),\"top-left\":new t.Point(r,r),\"top-right\":new t.Point(-r,r),bottom:new t.Point(0,-e),\"bottom-left\":new t.Point(r,-r),\"bottom-right\":new t.Point(-r,-r),left:new t.Point(e,0),right:new t.Point(-e,0)}}if(e instanceof t.Point||Array.isArray(e)){var n=t.Point.convert(e);return{center:n,top:n,\"top-left\":n,\"top-right\":n,bottom:n,\"bottom-left\":n,\"bottom-right\":n,left:n,right:n}}return{center:t.Point.convert(e.center||[0,0]),top:t.Point.convert(e.top||[0,0]),\"top-left\":t.Point.convert(e[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(e[\"top-right\"]||[0,0]),bottom:t.Point.convert(e.bottom||[0,0]),\"bottom-left\":t.Point.convert(e[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(e[\"bottom-right\"]||[0,0]),left:t.Point.convert(e.left||[0,0]),right:t.Point.convert(e.right||[0,0])}}return ra(new t.Point(0,0))}var na={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:zi,NavigationControl:Bi,GeolocateControl:Wi,AttributionControl:Mi,ScaleControl:Ji,FullscreenControl:Qi,Popup:ea,Marker:qi,Style:Ye,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){jt().acquire(Rt)},clearPrewarmedResources:function(){var t=Bt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(Rt),Bt=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. 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this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),!0},extraInfo:function(t,e,r){var 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n.baseCalendar,i(a.prototype,{name:\"UmmAlQura\",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Umm al-Qura\",epochs:[\"BH\",\"AH\"],monthNames:[\"Al-Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' Al-Thani\",\"Jumada Al-Awwal\",\"Jumada Al-Thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-Ahad\",\"Yawm al-Ithnain\",\"Yawm al-Thalāthā’\",\"Yawm al-Arba‘ā’\",\"Yawm al-Khamīs\",\"Yawm al-Jum‘a\",\"Yawm al-Sabt\"],dayNamesMin:[\"Ah\",\"Ith\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!0}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 355===this.daysInYear(e.year())},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){for(var e=0,r=1;r<=12;r++)e+=this.daysInMonth(t,r);return e},daysInMonth:function(t,e){for(var r=this._validate(t,e,this.minDay,n.local.invalidMonth).toJD()-24e5+.5,i=0,a=0;ar)return o[i]-o[i-1];i++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate),a=12*(i.year()-1)+i.month()-15292;return i.day()+o[a-1]-1+24e5-.5},fromJD:function(t){for(var e=t-24e5+.5,r=0,n=0;ne);n++)r++;var i=r+15292,a=Math.floor((i-1)/12),s=a+1,l=i-12*a,u=e-o[r-1]+1;return this.newDate(s,l,u)},isValid:function(t,e,r){var i=n.baseCalendar.prototype.isValid.apply(this,arguments);return i&&(i=(t=null!=t.year?t.year:t)>=1276&&t<=1500),i},_validate:function(t,e,r,i){var a=n.baseCalendar.prototype._validate.apply(this,arguments);if(a.year<1276||a.year>1500)throw i.replace(/\\{0\\}/,this.local.name);return a}}),n.calendars.ummalqura=a;var 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n=r(56131);function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(u.local.invalidDate||u.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(u.local.invalidDate||u.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(u.local.differentCalendars||u.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,u.local.invalidMonth||u.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var 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e=t[0].trace,r=e.error_y||{},a=e.error_x||{},o=n.select(this);o.selectAll(\"path.yerror\").style(\"stroke-width\",r.thickness+\"px\").call(i.stroke,r.color),a.copy_ystyle&&(a=r),o.selectAll(\"path.xerror\").style(\"stroke-width\",a.thickness+\"px\").call(i.stroke,a.color)}))}},55756:function(t,e,r){\"use strict\";var n=r(25376),i=r(65460).hoverlabel,a=r(92880).extendFlat;t.exports={hoverlabel:{bgcolor:a({},i.bgcolor,{arrayOk:!0}),bordercolor:a({},i.bordercolor,{arrayOk:!0}),font:n({arrayOk:!0,editType:\"none\"}),align:a({},i.align,{arrayOk:!0}),namelength:a({},i.namelength,{arrayOk:!0}),editType:\"none\"}}},55056:function(t,e,r){\"use strict\";var n=r(3400),i=r(24040);function a(t,e,r,i){i=i||n.identity,Array.isArray(t)&&(e[0][r]=i(t))}t.exports=function(t){var e=t.calcdata,r=t._fullLayout;function o(t){return function(e){return n.coerceHoverinfo({hoverinfo:e},{_module:t._module},r)}}for(var s=0;s=0&&r.indexZ[0]._length||bt<0||bt>K[0]._length)return v.unhoverRaw(t,e)}else xt=\"xpx\"in e?e.xpx:Z[0]._length/2,bt=\"ypx\"in e?e.ypx:K[0]._length/2;if(e.pointerX=xt+Z[0]._offset,e.pointerY=bt+K[0]._offset,rt=\"xval\"in e?m.flat(x,e.xval):m.p2c(Z,xt),nt=\"yval\"in e?m.flat(x,e.yval):m.p2c(K,bt),!i(rt[0])||!i(nt[0]))return o.warn(\"Fx.hover failed\",e,t),v.unhoverRaw(t,e)}var kt=1/0;function At(r,n){for(at=0;atdt&&(vt.splice(0,dt),kt=vt[0].distance),A&&0!==et&&0===vt.length){pt.distance=et,pt.index=!1;var c=st._module.hoverPoints(pt,ft,ht,\"closest\",{hoverLayer:b._hoverlayer});if(c&&(c=c.filter((function(t){return t.spikeDistance<=et}))),c&&c.length){var f,h=c.filter((function(t){return t.xa.showspikes&&\"hovered data\"!==t.xa.spikesnap}));if(h.length){var p=h[0];i(p.x0)&&i(p.y0)&&(f=St(p),(!yt.vLinePoint||yt.vLinePoint.spikeDistance>f.spikeDistance)&&(yt.vLinePoint=f))}var v=c.filter((function(t){return t.ya.showspikes&&\"hovered data\"!==t.ya.spikesnap}));if(v.length){var g=v[0];i(g.x0)&&i(g.y0)&&(f=St(g),(!yt.hLinePoint||yt.hLinePoint.spikeDistance>f.spikeDistance)&&(yt.hLinePoint=f))}}}}}function Mt(t,e,r){for(var n,i=null,a=1/0,o=0;o0&&Math.abs(t.distance)Bt-1;Nt--)qt(vt[Nt]);vt=jt,Pt()}var Ht=t._hoverdata,Gt=[],Wt=q(t),Yt=H(t);for(it=0;it1||vt.length>1)||\"closest\"===M&&mt&&vt.length>1,oe=d.combine(b.plot_bgcolor||d.background,b.paper_bgcolor),se=z(vt,{gd:t,hovermode:M,rotateLabels:ae,bgColor:oe,container:b._hoverlayer,outerContainer:b._paper.node(),commonLabelOpts:b.hoverlabel,hoverdistance:b.hoverdistance}),le=se.hoverLabels;if(m.isUnifiedHover(M)||(function(t,e,r,n){var i,a,o,s,l,u,c,f=e?\"xa\":\"ya\",h=e?\"ya\":\"xa\",p=0,d=1,v=t.size(),g=new Array(v),y=0,m=n.minX,x=n.maxX,b=n.minY,_=n.maxY,w=function(t){return t*r._invScaleX},T=function(t){return t*r._invScaleY};function A(t){var e=t[0],r=t[t.length-1];if(a=e.pmin-e.pos-e.dp+e.size,o=r.pos+r.dp+r.size-e.pmax,a>.01){for(l=t.length-1;l>=0;l--)t[l].dp+=a;i=!1}if(!(o<.01)){if(a<-.01){for(l=t.length-1;l>=0;l--)t[l].dp-=o;i=!1}if(i){var n=0;for(s=0;se.pmax&&n++;for(s=t.length-1;s>=0&&!(n<=0);s--)(u=t[s]).pos>e.pmax-1&&(u.del=!0,n--);for(s=0;s=0;l--)t[l].dp-=o;for(s=t.length-1;s>=0&&!(n<=0);s--)(u=t[s]).pos+u.dp+u.size>e.pmax&&(u.del=!0,n--)}}}for(t.each((function(t){var n=t[f],i=t[h],a=\"x\"===n._id.charAt(0),o=n.range;0===y&&o&&o[0]>o[1]!==a&&(d=-1);var s=0,l=a?r.width:r.height;if(\"x\"===r.hovermode||\"y\"===r.hovermode){var u,c,p=R(t,e),v=t.anchor,A=\"end\"===v?-1:1;if(\"middle\"===v)c=(u=t.crossPos+(a?T(p.y-t.by/2):w(t.bx/2+t.tx2width/2)))+(a?T(t.by):w(t.bx));else if(a)c=(u=t.crossPos+T(S+p.y)-T(t.by/2-S))+T(t.by);else{var M=w(A*S+p.x),E=M+w(A*t.bx);u=t.crossPos+Math.min(M,E),c=t.crossPos+Math.max(M,E)}a?void 0!==b&&void 0!==_&&Math.min(c,_)-Math.max(u,b)>1&&(\"left\"===i.side?(s=i._mainLinePosition,l=r.width):l=i._mainLinePosition):void 0!==m&&void 0!==x&&Math.min(c,x)-Math.max(u,m)>1&&(\"top\"===i.side?(s=i._mainLinePosition,l=r.height):l=i._mainLinePosition)}g[y++]=[{datum:t,traceIndex:t.trace.index,dp:0,pos:t.pos,posref:t.posref,size:t.by*(a?k:1)/2,pmin:s,pmax:l}]})),g.sort((function(t,e){return t[0].posref-e[0].posref||d*(e[0].traceIndex-t[0].traceIndex)}));!i&&p<=v;){for(p++,i=!0,s=0;s.01&&L.pmin===C.pmin&&L.pmax===C.pmax){for(l=E.length-1;l>=0;l--)E[l].dp+=a;for(M.push.apply(M,E),g.splice(s+1,1),c=0,l=M.length-1;l>=0;l--)c+=M[l].dp;for(o=c/M.length,l=M.length-1;l>=0;l--)M[l].dp-=o;i=!1}else s++}g.forEach(A)}for(s=g.length-1;s>=0;s--){var P=g[s];for(l=P.length-1;l>=0;l--){var O=P[l],I=O.datum;I.offset=O.dp,I.del=O.del}}}(le,ae,b,se.commonLabelBoundingBox),F(le,ae,b._invScaleX,b._invScaleY)),l&&l.tagName){var ue=y.getComponentMethod(\"annotations\",\"hasClickToShow\")(t,Gt);h(n.select(l),ue?\"pointer\":\"\")}l&&!a&&function(t,e,r){if(!r||r.length!==t._hoverdata.length)return!0;for(var n=r.length-1;n>=0;n--){var i=r[n],a=t._hoverdata[n];if(i.curveNumber!==a.curveNumber||String(i.pointNumber)!==String(a.pointNumber)||String(i.pointNumbers)!==String(a.pointNumbers))return!0}return!1}(t,0,Ht)&&(Ht&&t.emit(\"plotly_unhover\",{event:e,points:Ht}),t.emit(\"plotly_hover\",{event:e,points:t._hoverdata,xaxes:Z,yaxes:K,xvals:rt,yvals:nt}))}(t,e,r,a,l)}))},e.loneHover=function(t,e){var r=!0;Array.isArray(t)||(r=!1,t=[t]);var i=e.gd,a=q(i),o=H(i),s=z(t.map((function(t){var r=t._x0||t.x0||t.x||0,n=t._x1||t.x1||t.x||0,s=t._y0||t.y0||t.y||0,l=t._y1||t.y1||t.y||0,u=t.eventData;if(u){var c=Math.min(r,n),f=Math.max(r,n),h=Math.min(s,l),p=Math.max(s,l),v=t.trace;if(y.traceIs(v,\"gl3d\")){var g=i._fullLayout[v.scene]._scene.container,m=g.offsetLeft,x=g.offsetTop;c+=m,f+=m,h+=x,p+=x}u.bbox={x0:c+o,x1:f+o,y0:h+a,y1:p+a},e.inOut_bbox&&e.inOut_bbox.push(u.bbox)}else u=!1;return{color:t.color||d.defaultLine,x0:t.x0||t.x||0,x1:t.x1||t.x||0,y0:t.y0||t.y||0,y1:t.y1||t.y||0,xLabel:t.xLabel,yLabel:t.yLabel,zLabel:t.zLabel,text:t.text,name:t.name,idealAlign:t.idealAlign,borderColor:t.borderColor,fontFamily:t.fontFamily,fontSize:t.fontSize,fontColor:t.fontColor,fontWeight:t.fontWeight,fontStyle:t.fontStyle,fontVariant:t.fontVariant,nameLength:t.nameLength,textAlign:t.textAlign,trace:t.trace||{index:0,hoverinfo:\"\"},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:t.hovertemplate||!1,hovertemplateLabels:t.hovertemplateLabels||!1,eventData:u}})),{gd:i,hovermode:\"closest\",rotateLabels:!1,bgColor:e.bgColor||d.background,container:n.select(e.container),outerContainer:e.outerContainer||e.container}).hoverLabels,l=0,u=0;return s.sort((function(t,e){return t.y0-e.y0})).each((function(t,r){var n=t.y0-t.by/2;t.offset=n-5([\\s\\S]*)<\\/extra>/;function z(t,e){var r=e.gd,i=r._fullLayout,a=e.hovermode,s=e.rotateLabels,c=e.bgColor,h=e.container,v=e.outerContainer,g=e.commonLabelOpts||{};if(0===t.length)return[[]];var T=e.fontFamily||x.HOVERFONT,k=e.fontSize||x.HOVERFONTSIZE,A=e.fontWeight||i.font.weight,M=e.fontStyle||i.font.style,L=e.fontVariant||i.font.variant,C=t[0],P=C.xa,I=C.ya,z=a.charAt(0),R=z+\"Label\",F=C[R];if(void 0===F&&\"multicategory\"===P.type)for(var B=0;Bi.width-_&&(w=i.width-_),e.attr(\"d\",\"M\"+(y-w)+\",0L\"+(y-w+S)+\",\"+b+S+\"H\"+_+\"v\"+b+(2*E+x.height)+\"H\"+-_+\"V\"+b+S+\"H\"+(y-w-S)+\"Z\"),y=w,K.minX=y-_,K.maxX=y+_,\"top\"===P.side?(K.minY=m-(2*E+x.height),K.maxY=m-E):(K.minY=m+E,K.maxY=m+(2*E+x.height))}else{var O,z,D;\"right\"===I.side?(O=\"start\",z=1,D=\"\",y=P._offset+P._length):(O=\"end\",z=-1,D=\"-\",y=P._offset),m=I._offset+(C.y0+C.y1)/2,s.attr(\"text-anchor\",O),e.attr(\"d\",\"M0,0L\"+D+S+\",\"+S+\"V\"+(E+x.height/2)+\"h\"+D+(2*E+x.width)+\"V-\"+(E+x.height/2)+\"H\"+D+S+\"V-\"+S+\"Z\"),K.minY=m-(E+x.height/2),K.maxY=m+(E+x.height/2),\"right\"===I.side?(K.minX=y+S,K.maxX=y+S+(2*E+x.width)):(K.minX=y-S-(2*E+x.width),K.maxX=y-S);var R,B=x.height/2,N=j-x.top-B,U=\"clip\"+i._uid+\"commonlabel\"+I._id;if(y=0?ft:ht+vt=0?ht:Tt+vt=0?ut:ct+gt=0?ct:kt+gt=0,\"top\"!==t.idealAlign&&X||!Z?X?(R+=N/2,t.anchor=\"start\"):t.anchor=\"middle\":(R-=N/2,t.anchor=\"end\"),t.crossPos=R;else{if(t.pos=R,X=z+B/2+K<=U,Z=z-B/2-K>=0,\"left\"!==t.idealAlign&&X||!Z)if(X)z+=B/2,t.anchor=\"start\";else{t.anchor=\"middle\";var J=K/2,$=z+J-U,Q=z-J;$>0&&(z-=$),Q<0&&(z+=-Q)}else z-=B/2,t.anchor=\"end\";t.crossPos=z}_.attr(\"text-anchor\",t.anchor),P&&C.attr(\"text-anchor\",t.anchor),e.attr(\"transform\",l(z,R)+(s?u(w):\"\"))})),{hoverLabels:At,commonLabelBoundingBox:K}}function D(t,e,r,n,i,a){var s=\"\",l=\"\";void 0!==t.nameOverride&&(t.name=t.nameOverride),t.name&&(t.trace._meta&&(t.name=o.templateString(t.name,t.trace._meta)),s=U(t.name,t.nameLength));var u=r.charAt(0),c=\"x\"===u?\"y\":\"x\";void 0!==t.zLabel?(void 0!==t.xLabel&&(l+=\"x: \"+t.xLabel+\"
\"),void 0!==t.yLabel&&(l+=\"y: \"+t.yLabel+\"
\"),\"choropleth\"!==t.trace.type&&\"choroplethmapbox\"!==t.trace.type&&(l+=(l?\"z: \":\"\")+t.zLabel)):e&&t[u+\"Label\"]===i?l=t[c+\"Label\"]||\"\":void 0===t.xLabel?void 0!==t.yLabel&&\"scattercarpet\"!==t.trace.type&&(l=t.yLabel):l=void 0===t.yLabel?t.xLabel:\"(\"+t.xLabel+\", \"+t.yLabel+\")\",!t.text&&0!==t.text||Array.isArray(t.text)||(l+=(l?\"
\":\"\")+t.text),void 0!==t.extraText&&(l+=(l?\"
\":\"\")+t.extraText),a&&\"\"===l&&!t.hovertemplate&&(\"\"===s&&a.remove(),l=s);var f=t.hovertemplate||!1;if(f){var h=t.hovertemplateLabels||t;t[u+\"Label\"]!==i&&(h[u+\"other\"]=h[u+\"Val\"],h[u+\"otherLabel\"]=h[u+\"Label\"]),l=(l=o.hovertemplateString(f,h,n._d3locale,t.eventData[0]||{},t.trace._meta)).replace(I,(function(e,r){return s=U(r,t.nameLength),\"\"}))}return[l,s]}function R(t,e){var r=0,n=t.offset;return e&&(n*=-M,r=t.offset*A),{x:r,y:n}}function F(t,e,r,i){var a=function(t){return t*r},o=function(t){return t*i};t.each((function(t){var r=n.select(this);if(t.del)return r.remove();var i,s,l,u,c=r.select(\"text.nums\"),h=t.anchor,d=\"end\"===h?-1:1,v=(u=(l=(s={start:1,end:-1,middle:0}[(i=t).anchor])*(S+E))+s*(i.txwidth+E),\"middle\"===i.anchor&&(l-=i.tx2width/2,u+=i.txwidth/2+E),{alignShift:s,textShiftX:l,text2ShiftX:u}),g=R(t,e),y=g.x,m=g.y,x=\"middle\"===h;r.select(\"path\").attr(\"d\",x?\"M-\"+a(t.bx/2+t.tx2width/2)+\",\"+o(m-t.by/2)+\"h\"+a(t.bx)+\"v\"+o(t.by)+\"h-\"+a(t.bx)+\"Z\":\"M0,0L\"+a(d*S+y)+\",\"+o(S+m)+\"v\"+o(t.by/2-S)+\"h\"+a(d*t.bx)+\"v-\"+o(t.by)+\"H\"+a(d*S+y)+\"V\"+o(m-S)+\"Z\");var b=y+v.textShiftX,_=m+t.ty0-t.by/2+E,w=t.textAlign||\"auto\";\"auto\"!==w&&(\"left\"===w&&\"start\"!==h?(c.attr(\"text-anchor\",\"start\"),b=x?-t.bx/2-t.tx2width/2+E:-t.bx-E):\"right\"===w&&\"end\"!==h&&(c.attr(\"text-anchor\",\"end\"),b=x?t.bx/2-t.tx2width/2-E:t.bx+E)),c.call(f.positionText,a(b),o(_)),t.tx2width&&(r.select(\"text.name\").call(f.positionText,a(v.text2ShiftX+v.alignShift*E+y),o(m+t.ty0-t.by/2+E)),r.select(\"rect\").call(p.setRect,a(v.text2ShiftX+(v.alignShift-1)*t.tx2width/2+y),o(m-t.by/2-1),a(t.tx2width),o(t.by+2)))}))}function B(t,e){var r=t.index,n=t.trace||{},a=t.cd[0],s=t.cd[r]||{};function l(t){return t||i(t)&&0===t}var u=Array.isArray(r)?function(t,e){var i=o.castOption(a,r,t);return l(i)?i:o.extractOption({},n,\"\",e)}:function(t,e){return o.extractOption(s,n,t,e)};function c(e,r,n){var i=u(r,n);l(i)&&(t[e]=i)}if(c(\"hoverinfo\",\"hi\",\"hoverinfo\"),c(\"bgcolor\",\"hbg\",\"hoverlabel.bgcolor\"),c(\"borderColor\",\"hbc\",\"hoverlabel.bordercolor\"),c(\"fontFamily\",\"htf\",\"hoverlabel.font.family\"),c(\"fontSize\",\"hts\",\"hoverlabel.font.size\"),c(\"fontColor\",\"htc\",\"hoverlabel.font.color\"),c(\"fontWeight\",\"htw\",\"hoverlabel.font.weight\"),c(\"fontStyle\",\"hty\",\"hoverlabel.font.style\"),c(\"fontVariant\",\"htv\",\"hoverlabel.font.variant\"),c(\"nameLength\",\"hnl\",\"hoverlabel.namelength\"),c(\"textAlign\",\"hta\",\"hoverlabel.align\"),t.posref=\"y\"===e||\"closest\"===e&&\"h\"===n.orientation?t.xa._offset+(t.x0+t.x1)/2:t.ya._offset+(t.y0+t.y1)/2,t.x0=o.constrain(t.x0,0,t.xa._length),t.x1=o.constrain(t.x1,0,t.xa._length),t.y0=o.constrain(t.y0,0,t.ya._length),t.y1=o.constrain(t.y1,0,t.ya._length),void 0!==t.xLabelVal&&(t.xLabel=\"xLabel\"in t?t.xLabel:g.hoverLabelText(t.xa,t.xLabelVal,n.xhoverformat),t.xVal=t.xa.c2d(t.xLabelVal)),void 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0),-1===p.indexOf(\"name\")&&(t.name=void 0)),t}function N(t,e,r){var n,i,o=r.container,s=r.fullLayout,l=s._size,u=r.event,c=!!e.hLinePoint,f=!!e.vLinePoint;if(o.selectAll(\".spikeline\").remove(),f||c){var h=d.combine(s.plot_bgcolor,s.paper_bgcolor);if(c){var v,y,m=e.hLinePoint;n=m&&m.xa,\"cursor\"===(i=m&&m.ya).spikesnap?(v=u.pointerX,y=u.pointerY):(v=n._offset+m.x,y=i._offset+m.y);var x,b,_=a.readability(m.color,h)<1.5?d.contrast(h):m.color,w=i.spikemode,T=i.spikethickness,k=i.spikecolor||_,A=g.getPxPosition(t,i);if(-1!==w.indexOf(\"toaxis\")||-1!==w.indexOf(\"across\")){if(-1!==w.indexOf(\"toaxis\")&&(x=A,b=v),-1!==w.indexOf(\"across\")){var 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n,i,a,o=e[t],s=w.scopeDefaults[e.scope];\"lonaxis\"===t?(n=s.lonaxisRange,i=s.lataxisRange,a=function(t,e){return[t,e]}):\"lataxis\"===t&&(n=s.lataxisRange,i=s.lonaxisRange,a=function(t,e){return[e,t]});var l={type:\"linear\",range:[n[0],n[1]-1e-6],tick0:o.tick0,dtick:o.dtick};v.setConvert(l,r);var u=v.calcTicks(l);e.isScoped||\"lonaxis\"!==t||u.pop();for(var c=u.length,f=new Array(c),h=0;h-1&&b(n.event,i,[r.xaxis],[r.yaxis],r.id,c),s.indexOf(\"event\")>-1&&p.click(i,n.event))}))}function f(t){return r.projection.invert([t[0]+r.xaxis._offset,t[1]+r.yaxis._offset])}},S.makeFramework=function(){var t=this,e=t.graphDiv,r=e._fullLayout,i=\"clip\"+r._uid+t.id;t.clipDef=r._clips.append(\"clipPath\").attr(\"id\",i),t.clipRect=t.clipDef.append(\"rect\"),t.framework=n.select(t.container).append(\"g\").attr(\"class\",\"geo \"+t.id).call(h.setClipUrl,i,e),t.project=function(e){var r=t.projection(e);return r?[r[0]-t.xaxis._offset,r[1]-t.yaxis._offset]:[null,null]},t.xaxis={_id:\"x\",c2p:function(e){return t.project(e)[0]}},t.yaxis={_id:\"y\",c2p:function(e){return t.project(e)[1]}},t.mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},v.setConvert(t.mockAxis,r)},S.saveViewInitial=function(t){var e,r=t.center||{},n=t.projection,i=n.rotation||{};this.viewInitial={fitbounds:t.fitbounds,\"projection.scale\":n.scale},e=t._isScoped?{\"center.lon\":r.lon,\"center.lat\":r.lat}:t._isClipped?{\"projection.rotation.lon\":i.lon,\"projection.rotation.lat\":i.lat}:{\"center.lon\":r.lon,\"center.lat\":r.lat,\"projection.rotation.lon\":i.lon},u.extendFlat(this.viewInitial,e)},S.render=function(t){this._hasMarkerAngles&&t?this.plot(this._geoCalcData,this._fullLayout,[],!0):this._render()},S._render=function(){var t,e=this.projection,r=e.getPath();function n(t){var r=e(t.lonlat);return r?c(r[0],r[1]):null}function i(t){return e.isLonLatOverEdges(t.lonlat)?\"none\":null}for(t in 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r=0,n=0,i=t.length;nMath.abs(s)?(u.boxEnd[1]=u.boxStart[1]+Math.abs(a)*_*(s>=0?1:-1),u.boxEnd[1]l[3]&&(u.boxEnd[1]=l[3],u.boxEnd[0]=u.boxStart[0]+(l[3]-u.boxStart[1])/Math.abs(_))):(u.boxEnd[0]=u.boxStart[0]+Math.abs(s)/_*(a>=0?1:-1),u.boxEnd[0]l[2]&&(u.boxEnd[0]=l[2],u.boxEnd[1]=u.boxStart[1]+(l[2]-u.boxStart[0])*Math.abs(_)))}}else u.boxEnabled?(a=u.boxStart[0]!==u.boxEnd[0],s=u.boxStart[1]!==u.boxEnd[1],a||s?(a&&(g(0,u.boxStart[0],u.boxEnd[0]),t.xaxis.autorange=!1),s&&(g(1,u.boxStart[1],u.boxEnd[1]),t.yaxis.autorange=!1),t.relayoutCallback()):t.glplot.setDirty(),u.boxEnabled=!1,u.boxInited=!1):u.boxInited&&(u.boxInited=!1);break;case\"pan\":u.boxEnabled=!1,u.boxInited=!1,e?(u.panning||(u.dragStart[0]=n,u.dragStart[1]=i),Math.abs(u.dragStart[0]-n).999&&(g=\"turntable\"):g=\"turntable\")}else g=\"turntable\";r(\"dragmode\",g),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}t.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:c,attributes:l,handleDefaults:f,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},autotypenumbersDflt:e.autotypenumbers,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},346:function(t,e,r){\"use strict\";var n=r(86140),i=r(86968).u,a=r(92880).extendFlat,o=r(3400).counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}t.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:i({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\",_deprecated:{cameraposition:{valType:\"info_array\",editType:\"camera\"}}}},9020:function(t,e,r){\"use strict\";var n=r(43080),i=[\"xaxis\",\"yaxis\",\"zaxis\"];function a(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}a.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},t.exports=function(t){var e=new a;return e.merge(t),e}},87152:function(t,e,r){\"use strict\";t.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],u=0;u<3;++u){var c=s[a[u]];if(c._length=(r[u].hi-r[u].lo)*r[u].pixelsPerDataUnit/t.dataScale[u],Math.abs(c._length)===1/0||isNaN(c._length))l[u]=[];else{c._input_range=c.range.slice(),c.range[0]=r[u].lo/t.dataScale[u],c.range[1]=r[u].hi/t.dataScale[u],c._m=1/(t.dataScale[u]*r[u].pixelsPerDataUnit),c.range[0]===c.range[1]&&(c.range[0]-=1,c.range[1]+=1);var f=c.tickmode;if(\"auto\"===c.tickmode){c.tickmode=\"linear\";var h=c.nticks||i.constrain(c._length/40,4,9);n.autoTicks(c,Math.abs(c.range[1]-c.range[0])/h)}for(var p=n.calcTicks(c,{msUTC:!0}),d=0;d/g,\" 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a=r._fullLayout._invScaleX,o=r._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+s+\" \"+l),n.setAttributeNS(null,\"width\",s),n.setAttributeNS(null,\"height\",l),b(e),e.glplot.axes.update(e.axesOptions);for(var u=Object.keys(e.traces),c=null,h=e.glplot.selection,v=0;v\")):\"isosurface\"===t.type||\"volume\"===t.type?(k.valueLabel=p.hoverLabelText(e._mockAxis,e._mockAxis.d2l(h.traceCoordinate[3]),t.valuehoverformat),E.push(\"value: \"+k.valueLabel),h.textLabel&&E.push(h.textLabel),x=E.join(\"
\")):x=h.textLabel;var L={x:h.traceCoordinate[0],y:h.traceCoordinate[1],z:h.traceCoordinate[2],data:_._input,fullData:_,curveNumber:_.index,pointNumber:T};d.appendArrayPointValue(L,_,T),t._module.eventData&&(L=_._module.eventData(L,h,_,{},T));var C={points:[L]};if(e.fullSceneLayout.hovermode){var P=[];d.loneHover({trace:_,x:(.5+.5*m[0]/m[3])*s,y:(.5-.5*m[1]/m[3])*l,xLabel:k.xLabel,yLabel:k.yLabel,zLabel:k.zLabel,text:x,name:c.name,color:d.castHoverOption(_,T,\"bgcolor\")||c.color,borderColor:d.castHoverOption(_,T,\"bordercolor\"),fontFamily:d.castHoverOption(_,T,\"font.family\"),fontSize:d.castHoverOption(_,T,\"font.size\"),fontColor:d.castHoverOption(_,T,\"font.color\"),nameLength:d.castHoverOption(_,T,\"namelength\"),textAlign:d.castHoverOption(_,T,\"align\"),hovertemplate:f.castOption(_,T,\"hovertemplate\"),hovertemplateLabels:f.extendFlat({},L,k),eventData:[L]},{container:n,gd:r,inOut_bbox:P}),L.bbox=P[0]}h.distance<5&&(h.buttons||w)?r.emit(\"plotly_click\",C):r.emit(\"plotly_hover\",C),this.oldEventData=C}else d.loneUnhover(n),this.oldEventData&&r.emit(\"plotly_unhover\",this.oldEventData),this.oldEventData=void 0;e.drawAnnotations(e)},k.recoverContext=function(){var t=this;t.glplot.dispose();var e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):f.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\")};requestAnimationFrame(e)};var M=[\"xaxis\",\"yaxis\",\"zaxis\"];function S(t,e,r){for(var n=t.fullSceneLayout,i=0;i<3;i++){var a=M[i],o=a.charAt(0),s=n[a],l=e[o],u=e[o+\"calendar\"],c=e[\"_\"+o+\"length\"];if(f.isArrayOrTypedArray(l))for(var h,p=0;p<(c||l.length);p++)if(f.isArrayOrTypedArray(l[p]))for(var d=0;dy[1][o])y[0][o]=-1,y[1][o]=1;else{var O=y[1][o]-y[0][o];y[0][o]-=O/32,y[1][o]+=O/32}if(b=[y[0][o],y[1][o]],b=_(b,l),y[0][o]=b[0],y[1][o]=b[1],l.isReversed()){var I=y[0][o];y[0][o]=y[1][o],y[1][o]=I}}else b=l.range,y[0][o]=l.r2l(b[0]),y[1][o]=l.r2l(b[1]);y[0][o]===y[1][o]&&(y[0][o]-=1,y[1][o]+=1),m[o]=y[1][o]-y[0][o],l.range=[y[0][o],y[1][o]],l.limitRange(),n.glplot.setBounds(o,{min:l.range[0]*p[o],max:l.range[1]*p[o]})}var z=c.aspectmode;if(\"cube\"===z)g=[1,1,1];else if(\"manual\"===z){var D=c.aspectratio;g=[D.x,D.y,D.z]}else{if(\"auto\"!==z&&\"data\"!==z)throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");var R=[1,1,1];for(o=0;o<3;++o){var F=x[u=(l=c[M[o]]).type];R[o]=Math.pow(F.acc,1/F.count)/p[o]}g=\"data\"===z||Math.max.apply(null,R)/Math.min.apply(null,R)<=4?R:[1,1,1]}c.aspectratio.x=f.aspectratio.x=g[0],c.aspectratio.y=f.aspectratio.y=g[1],c.aspectratio.z=f.aspectratio.z=g[2],n.glplot.setAspectratio(c.aspectratio),n.viewInitial.aspectratio||(n.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z}),n.viewInitial.aspectmode||(n.viewInitial.aspectmode=c.aspectmode);var B=c.domain||null,N=e._size||null;if(B&&N){var j=n.container.style;j.position=\"absolute\",j.left=N.l+B.x[0]*N.w+\"px\",j.top=N.t+(1-B.y[1])*N.h+\"px\",j.width=N.w*(B.x[1]-B.x[0])+\"px\",j.height=N.h*(B.y[1]-B.y[0])+\"px\"}n.glplot.redraw()}},k.destroy=function(){var t=this;t.glplot&&(t.camera.mouseListener.enabled=!1,t.container.removeEventListener(\"wheel\",t.camera.wheelListener),t.camera=null,t.glplot.dispose(),t.container.parentNode.removeChild(t.container),t.glplot=null)},k.getCamera=function(){var t,e=this;return e.camera.view.recalcMatrix(e.camera.view.lastT()),{up:{x:(t=e.camera).up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?\"orthographic\":\"perspective\"}}},k.setViewport=function(t){var e,r=this,n=t.camera;r.camera.lookAt.apply(this,[[(e=n).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),r.glplot.setAspectratio(t.aspectratio),\"orthographic\"===n.projection.type!==r.camera._ortho&&(r.glplot.redraw(),r.glplot.clearRGBA(),r.glplot.dispose(),r.initializeGLPlot())},k.isCameraChanged=function(t){var e=this.getCamera(),r=f.nestedProperty(t,this.id+\".camera\").get();function n(t,e,r,n){var i=[\"up\",\"center\",\"eye\"],a=[\"x\",\"y\",\"z\"];return e[i[r]]&&t[i[r]][a[n]]===e[i[r]][a[n]]}var i=!1;if(void 0===r)i=!0;else{for(var a=0;a<3;a++)for(var o=0;o<3;o++)if(!n(e,r,a,o)){i=!0;break}(!r.projection||e.projection&&e.projection.type!==r.projection.type)&&(i=!0)}return i},k.isAspectChanged=function(t){var e=this.glplot.getAspectratio(),r=f.nestedProperty(t,this.id+\".aspectratio\").get();return void 0===r||r.x!==e.x||r.y!==e.y||r.z!==e.z},k.saveLayout=function(t){var e,r,n,i,a,o,s=this,l=s.fullLayout,u=s.isCameraChanged(t),h=s.isAspectChanged(t),p=u||h;if(p){var d={};u&&(e=s.getCamera(),n=(r=f.nestedProperty(t,s.id+\".camera\")).get(),d[s.id+\".camera\"]=n),h&&(i=s.glplot.getAspectratio(),o=(a=f.nestedProperty(t,s.id+\".aspectratio\")).get(),d[s.id+\".aspectratio\"]=o),c.call(\"_storeDirectGUIEdit\",t,l._preGUI,d),u&&(r.set(e),f.nestedProperty(l,s.id+\".camera\").set(e)),h&&(a.set(i),f.nestedProperty(l,s.id+\".aspectratio\").set(i),s.glplot.redraw())}return p},k.updateFx=function(t,e){var r=this,n=r.camera;if(n)if(\"orbit\"===t)n.mode=\"orbit\",n.keyBindingMode=\"rotate\";else if(\"turntable\"===t){n.up=[0,0,1],n.mode=\"turntable\",n.keyBindingMode=\"rotate\";var i=r.graphDiv,a=i._fullLayout,o=r.fullSceneLayout.camera,s=o.up.x,l=o.up.y,u=o.up.z;if(u/Math.sqrt(s*s+l*l+u*u)<.999){var h=r.id+\".camera.up\",p={x:0,y:0,z:1},d={};d[h]=p;var v=i.layout;c.call(\"_storeDirectGUIEdit\",v,a._preGUI,d),o.up=p,f.nestedProperty(v,h).set(p)}}else n.keyBindingMode=t;r.fullSceneLayout.hovermode=e},k.toImage=function(t){var e=this;t||(t=\"png\"),e.staticMode&&e.container.appendChild(n),e.glplot.redraw();var r=e.glplot.gl,i=r.drawingBufferWidth,a=r.drawingBufferHeight;r.bindFramebuffer(r.FRAMEBUFFER,null);var o=new Uint8Array(i*a*4);r.readPixels(0,0,i,a,r.RGBA,r.UNSIGNED_BYTE,o),function(t,e,r){for(var n=0,i=r-1;n0)for(var s=255/o,l=0;l<3;++l)t[a+l]=Math.min(s*t[a+l],255)}}(o,i,a);var s=document.createElement(\"canvas\");s.width=i,s.height=a;var l,u=s.getContext(\"2d\",{willReadFrequently:!0}),c=u.createImageData(i,a);switch(c.data.set(o),u.putImageData(c,0,0),t){case\"jpeg\":l=s.toDataURL(\"image/jpeg\");break;case\"webp\":l=s.toDataURL(\"image/webp\");break;default:l=s.toDataURL(\"image/png\")}return e.staticMode&&e.container.removeChild(n),l},k.setConvert=function(){for(var t=0;t<3;t++){var e=this.fullSceneLayout[M[t]];p.setConvert(e,this.fullLayout),e.setScale=f.noop}},k.make4thDimension=function(){var t=this,e=t.graphDiv._fullLayout;t._mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},p.setConvert(t._mockAxis,e)},t.exports=T},52094:function(t){\"use strict\";t.exports=function(t,e,r,n){n=n||t.length;for(var i=new Array(n),a=0;aOpenStreetMap contributors',o=['© Carto',a].join(\" \"),s=['Map tiles by Stamen Design','under CC BY 3.0',\"|\",'Data by OpenStreetMap contributors','under ODbL'].join(\" 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e,r,s=this,u=s.isSmith,c=s.gd,f=s.layers,h=t._zoomlayer,p=S.MINZOOM,d=S.OFFEDGE,v=s.radius,x=s.innerRadius,T=s.cx,k=s.cy,A=s.cxx,M=s.cyy,L=s.sectorInRad,C=s.vangles,P=s.radialAxis,O=E.clampTiny,I=E.findXYatLength,z=E.findEnclosingVertexAngles,D=S.cornerHalfWidth,R=S.cornerLen/2,F=g.makeDragger(f,\"path\",\"maindrag\",!1===t.dragmode?\"none\":\"crosshair\");n.select(F).attr(\"d\",s.pathSubplot()).attr(\"transform\",l(T,k)),F.onmousemove=function(t){m.hover(c,t,s.id),c._fullLayout._lasthover=F,c._fullLayout._hoversubplot=s.id},F.onmouseout=function(t){c._dragging||y.unhover(c,t)};var B,N,j,U,V,q,H,G,W,Y={element:F,gd:c,subplot:s.id,plotinfo:{id:s.id,xaxis:s.xaxis,yaxis:s.yaxis},xaxes:[s.xaxis],yaxes:[s.yaxis]};function X(t,e){return Math.sqrt(t*t+e*e)}function Z(t,e){return X(t-A,e-M)}function K(t,e){return Math.atan2(M-e,t-A)}function J(t,e){return[t*Math.cos(e),t*Math.sin(-e)]}function $(t,e){if(0===t)return s.pathSector(2*D);var 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n=r(33428),i=r(49760),a=r(24040),o=r(3400),s=o.strTranslate,l=o._,u=r(76308),c=r(43616),f=r(78344),h=r(92880).extendFlat,p=r(7316),d=r(54460),v=r(86476),g=r(93024),y=r(72760),m=y.freeMode,x=y.rectMode,b=r(81668),_=r(22676).prepSelect,w=r(22676).selectOnClick,T=r(22676).clearOutline,k=r(22676).clearSelectionsCache,A=r(33816);function M(t,e){this.id=t.id,this.graphDiv=t.graphDiv,this.init(e),this.makeFramework(e),this.aTickLayout=null,this.bTickLayout=null,this.cTickLayout=null}t.exports=M;var S=M.prototype;S.init=function(t){this.container=t._ternarylayer,this.defs=t._defs,this.layoutId=t._uid,this.traceHash={},this.layers={}},S.plot=function(t,e){var r=this,n=e[r.id],i=e._size;r._hasClipOnAxisFalse=!1;for(var a=0;aE*b?i=(a=b)*E:a=(i=x)/E,o=y*i/x,l=m*a/b,r=e.l+e.w*v-i/2,n=e.t+e.h*(1-g)-a/2,p.x0=r,p.y0=n,p.w=i,p.h=a,p.sum=_,p.xaxis={type:\"linear\",range:[w+2*k-_,_-w-2*T],domain:[v-o/2,v+o/2],_id:\"x\"},f(p.xaxis,p.graphDiv._fullLayout),p.xaxis.setScale(),p.xaxis.isPtWithinRange=function(t){return t.a>=p.aaxis.range[0]&&t.a<=p.aaxis.range[1]&&t.b>=p.baxis.range[1]&&t.b<=p.baxis.range[0]&&t.c>=p.caxis.range[1]&&t.c<=p.caxis.range[0]},p.yaxis={type:\"linear\",range:[w,_-T-k],domain:[g-l/2,g+l/2],_id:\"y\"},f(p.yaxis,p.graphDiv._fullLayout),p.yaxis.setScale(),p.yaxis.isPtWithinRange=function(){return!0};var A=p.yaxis.domain[0],M=p.aaxis=h({},t.aaxis,{range:[w,_-T-k],side:\"left\",tickangle:(+t.aaxis.tickangle||0)-30,domain:[A,A+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(M,p.graphDiv._fullLayout),M.setScale();var S=p.baxis=h({},t.baxis,{range:[_-w-k,T],side:\"bottom\",domain:p.xaxis.domain,anchor:\"free\",position:0,_id:\"x\",_length:i});f(S,p.graphDiv._fullLayout),S.setScale();var L=p.caxis=h({},t.caxis,{range:[_-w-T,k],side:\"right\",tickangle:(+t.caxis.tickangle||0)+30,domain:[A,A+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(L,p.graphDiv._fullLayout),L.setScale();var C=\"M\"+r+\",\"+(n+a)+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDef.select(\"path\").attr(\"d\",C),p.layers.plotbg.select(\"path\").attr(\"d\",C);var P=\"M0,\"+a+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDefRelative.select(\"path\").attr(\"d\",P);var O=s(r,n);p.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",O),p.clipDefRelative.select(\"path\").attr(\"transform\",null);var I=s(r-S._offset,n+a);p.layers.baxis.attr(\"transform\",I),p.layers.bgrid.attr(\"transform\",I);var z=s(r+i/2,n)+\"rotate(30)\"+s(0,-M._offset);p.layers.aaxis.attr(\"transform\",z),p.layers.agrid.attr(\"transform\",z);var 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e,r=this,n=r.graphDiv,i=t._name,a=i.charAt(0),s=t._id,l=r.layers[i],u=a+\"tickLayout\",c=(e=t).ticks+String(e.ticklen)+String(e.showticklabels);r[u]!==c&&(l.selectAll(\".\"+s+\"tick\").remove(),r[u]=c),t.setScale();var f=d.calcTicks(t),h=d.clipEnds(t,f),p=d.makeTransTickFn(t),v=d.getTickSigns(t)[2],g=o.deg2rad(30),y=v*(t.linewidth||1)/2,m=v*t.ticklen,x=r.w,b=r.h,_=\"b\"===a?\"M0,\"+y+\"l\"+Math.sin(g)*m+\",\"+Math.cos(g)*m:\"M\"+y+\",0l\"+Math.cos(g)*m+\",\"+-Math.sin(g)*m,w={a:\"M0,0l\"+b+\",-\"+x/2,b:\"M0,0l-\"+x/2+\",-\"+b,c:\"M0,0l-\"+b+\",\"+x/2}[a];d.drawTicks(n,t,{vals:\"inside\"===t.ticks?h:f,layer:l,path:_,transFn:p,crisp:!1}),d.drawGrid(n,t,{vals:h,layer:r.layers[a+\"grid\"],path:w,transFn:p,crisp:!1}),d.drawLabels(n,t,{vals:f,layer:l,transFn:p,labelFns:d.makeLabelFns(t,0,30)})};var 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r=t/M.xaxis._m,n=e/M.yaxis._m,i=[(p={a:f.a-n,b:f.b+(r+n)/2,c:f.c-(r-n)/2}).a,p.b,p.c].sort(o.sorterAsc),a=i.indexOf(p.a),l=i.indexOf(p.b),u=i.indexOf(p.c);i[0]<0&&(i[1]+i[0]/2<0?(i[2]+=i[0]+i[1],i[0]=i[1]=0):(i[2]+=i[0]/2,i[1]+=i[0]/2,i[0]=0),p={a:i[a],b:i[l],c:i[u]},e=(f.a-p.a)*M.yaxis._m,t=(f.c-p.c-f.b+p.b)*M.xaxis._m);var h=s(M.x0+t,M.y0+e);M.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",h);var d=s(-t,-e);M.clipDefRelative.select(\"path\").attr(\"transform\",d),M.aaxis.range=[p.a,M.sum-p.b-p.c],M.baxis.range=[M.sum-p.a-p.c,p.b],M.caxis.range=[M.sum-p.a-p.b,p.c],M.drawAxes(!1),M._hasClipOnAxisFalse&&M.plotContainer.select(\".scatterlayer\").selectAll(\".trace\").call(c.hideOutsideRangePoints,M),L.emit(\"plotly_relayouting\",R(p))}function 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p(t){var r=t.name,i=t.categories,a=t.meta;if(e.modules[r])n.log(\"Type \"+r+\" already registered\");else{e.subplotsRegistry[t.basePlotModule.name]||function(t){var r=t.name;if(e.subplotsRegistry[r])n.log(\"Plot type \"+r+\" already registered.\");else for(var i in y(t),e.subplotsRegistry[r]=t,e.componentsRegistry)b(i,t.name)}(t.basePlotModule);for(var o={},l=0;l-1&&(f[p[r]].title={text:\"\"});for(r=0;r\")?\"\":e.html(t).text()}));return e.remove(),r}(w)).replace(/&(?!\\w+;|\\#[0-9]+;| \\#x[0-9A-F]+;)/g,\"&\")).replace(c,\"'\"),i.isIE()&&(w=(w=(w=w.replace(/\"/gi,\"'\")).replace(/(\\('#)([^']*)('\\))/gi,'(\"#$2\")')).replace(/(\\\\')/gi,'\"')),w}},84664:function(t,e,r){\"use strict\";var n=r(3400);t.exports=function(t,e){for(var r=0;rf+u||!n(c))}for(var p=0;p=0)return t}else if(\"string\"==typeof t&&\"%\"===(t=t.trim()).slice(-1)&&n(t.slice(0,-1))&&(t=+t.slice(0,-1))>=0)return t+\"%\"}function d(t,e,r,n,a,o){var 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n.inbox(r-e,i-e,w+(i-e)/(i-r)-1)}(B)+function(t){return P(A(t),M(t),w)}(B))/2,t[f+\"Spike\"]=D.c2p(B.p,!0),o(B,y,t),t.hovertemplate=y.hovertemplate,t}}function f(t,e){var r=e.mcc||t.marker.color,n=e.mlcc||t.marker.line.color,i=s(t,e);return a.opacity(r)?r:a.opacity(n)&&i?n:void 0}t.exports={hoverPoints:function(t,e,r,n,a){var o=c(t,e,r,n,a);if(o){var s=o.cd,l=s[0].trace,u=s[o.index];return o.color=f(l,u),i.getComponentMethod(\"errorbars\",\"hoverInfo\")(u,l,o),[o]}},hoverOnBars:c,getTraceColor:f}},51132:function(t,e,r){\"use 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i=e[0].trace;i.selectedpoints?function(t,e,r){a.selectedPointStyle(t.selectAll(\"path\"),e),function(t,e,r){t.each((function(t){var i,s=n.select(this);if(t.selected){i=o.ensureUniformFontSize(r,g(s,t,e,r));var l=e.selected.textfont&&e.selected.textfont.color;l&&(i.color=l),a.font(s,i)}else a.selectedTextStyle(s,e)}))}(t.selectAll(\"text\"),e,r)}(r,i,t):(d(r,i,t),s.getComponentMethod(\"errorbars\",\"style\")(r))},getInsideTextFont:m,getOutsideTextFont:x,getBarColor:_,resizeText:l}},55592:function(t,e,r){\"use strict\";var n=r(76308),i=r(94288).hasColorscale,a=r(27260),o=r(3400).coercePattern;t.exports=function(t,e,r,s,l){var u=r(\"marker.color\",s),c=i(t,\"marker\");c&&a(t,e,l,r,{prefix:\"marker.\",cLetter:\"c\"}),r(\"marker.line.color\",n.defaultLine),i(t,\"marker.line\")&&a(t,e,l,r,{prefix:\"marker.line.\",cLetter:\"c\"}),r(\"marker.line.width\"),r(\"marker.opacity\"),o(r,\"marker.pattern\",u,c),r(\"selected.marker.color\"),r(\"unselected.marker.color\")}},82744:function(t,e,r){\"use 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O=f.selectAll(\"g.value-bullet\").data([c.gauge.bar]);O.enter().append(\"g\").classed(\"value-bullet\",!0).append(\"rect\"),O.select(\"rect\").attr(\"height\",M).attr(\"y\",(A-M)/2).call(T),w(b)?O.select(\"rect\").transition().duration(b.duration).ease(b.easing).each(\"end\",(function(){_&&_()})).each(\"interrupt\",(function(){_&&_()})).attr(\"width\",Math.max(0,i.c2p(Math.min(c.gauge.axis.range[1],r[0].y)))):O.select(\"rect\").attr(\"width\",\"number\"==typeof r[0].y?Math.max(0,i.c2p(Math.min(c.gauge.axis.range[1],r[0].y))):0),O.exit().remove();var I=r.filter((function(){return 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r=\"slices.\"+t;a(r+\".show\")&&(a(r+\".fill\"),a(r+\".locations\"))})),a(\"spaceframe.show\")&&a(\"spaceframe.fill\"),a(\"surface.show\")&&(a(\"surface.count\"),a(\"surface.fill\"),a(\"surface.pattern\")),a(\"contour.show\")&&(a(\"contour.color\"),a(\"contour.width\")),[\"text\",\"hovertext\",\"hovertemplate\",\"lighting.ambient\",\"lighting.diffuse\",\"lighting.specular\",\"lighting.roughness\",\"lighting.fresnel\",\"lighting.vertexnormalsepsilon\",\"lighting.facenormalsepsilon\",\"lightposition.x\",\"lightposition.y\",\"lightposition.z\",\"flatshading\",\"opacity\"].forEach((function(t){a(t)})),o(t,e,n,a,{prefix:\"\",cLetter:\"c\"}),e._length=null):e.visible=!1}t.exports={supplyDefaults:function(t,e,r,i){s(t,e,0,i,(function(r,i){return n.coerce(t,e,a,r,i)}))},supplyIsoDefaults:s}},6296:function(t,e,r){\"use strict\";t.exports={attributes:r(50048),supplyDefaults:r(70548).supplyDefaults,calc:r(62624),colorbar:{min:\"cmin\",max:\"cmax\"},plot:r(31460).createIsosurfaceTrace,moduleType:\"trace\",name:\"isosurface\",basePlotModule:r(12536),categories:[\"gl3d\",\"showLegend\"],meta:{}}},52948:function(t,e,r){\"use strict\";var n=r(49084),i=r(29736).axisHoverFormat,a=r(21776).Ks,o=r(16716),s=r(45464),l=r(92880).extendFlat;t.exports=l({x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},i:{valType:\"data_array\",editType:\"calc\"},j:{valType:\"data_array\",editType:\"calc\"},k:{valType:\"data_array\",editType:\"calc\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:a({editType:\"calc\"}),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),delaunayaxis:{valType:\"enumerated\",values:[\"x\",\"y\",\"z\"],dflt:\"z\",editType:\"calc\"},alphahull:{valType:\"number\",dflt:-1,editType:\"calc\"},intensity:{valType:\"data_array\",editType:\"calc\"},intensitymode:{valType:\"enumerated\",values:[\"vertex\",\"cell\"],dflt:\"vertex\",editType:\"calc\"},color:{valType:\"color\",editType:\"calc\"},vertexcolor:{valType:\"data_array\",editType:\"calc\"},facecolor:{valType:\"data_array\",editType:\"calc\"},transforms:void 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n=r(67792).gl_mesh3d,i=r(67792).delaunay_triangulate,a=r(67792).alpha_shape,o=r(67792).convex_hull,s=r(33040).parseColorScale,l=r(3400).isArrayOrTypedArray,u=r(43080),c=r(8932).extractOpts,f=r(52094);function h(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name=\"\",this.color=\"#fff\",this.data=null,this.showContour=!1}var p=h.prototype;function d(t){for(var e=[],r=t.length,n=0;n=e-.5)return!1;return!0}p.handlePick=function(t){if(t.object===this.mesh){var e=t.index=t.data.index;t.data._cellCenter?t.traceCoordinate=t.data.dataCoordinate:t.traceCoordinate=[this.data.x[e],this.data.y[e],this.data.z[e]];var r=this.data.hovertext||this.data.text;return l(r)&&void 0!==r[e]?t.textLabel=r[e]:r&&(t.textLabel=r),!0}},p.update=function(t){var e=this.scene,r=e.fullSceneLayout;this.data=t;var 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o=e.yaxis,s=e.xaxis,l=!!s.rangebreaks;i.makeTraceGroups(a,r,\"trace ohlc\").each((function(t){var e=n.select(this),r=t[0],a=r.t;if(!0!==r.trace.visible||a.empty)e.remove();else{var u=a.tickLen,c=e.selectAll(\"path\").data(i.identity);c.enter().append(\"path\"),c.exit().remove(),c.attr(\"d\",(function(t){if(t.empty)return\"M0,0Z\";var e=s.c2p(t.pos-u,!0),r=s.c2p(t.pos+u,!0),n=l?(e+r)/2:s.c2p(t.pos,!0);return\"M\"+e+\",\"+o.c2p(t.o,!0)+\"H\"+n+\"M\"+n+\",\"+o.c2p(t.h,!0)+\"V\"+o.c2p(t.l,!0)+\"M\"+r+\",\"+o.c2p(t.c,!0)+\"H\"+n}))}}))}},97384:function(t){\"use strict\";t.exports=function(t,e){var r,n=t.cd,i=t.xaxis,a=t.yaxis,o=[],s=n[0].t.bPos||0;if(!1===e)for(r=0;r=t.length)return!1;if(void 0!==e[t[r]])return!1;e[t[r]]=!0}return!0}(r))for(e=0;e0||c(s);u&&(o=\"array\");var f=r(\"categoryorder\",o);\"array\"===f?(r(\"categoryarray\"),r(\"ticktext\")):(delete t.categoryarray,delete t.ticktext),u||\"array\"!==f||(e.categoryorder=\"trace\")}}t.exports=function(t,e,r,c){function h(r,i){return 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w=x.enter().append(\"path\").attr(\"class\",\"path\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",0);_(w),x.attr(\"d\",(function(t){return t.svgD})),w.empty()||x.sort(v),x.exit().remove(),x.on(\"mouseover\",g).on(\"mouseout\",y).on(\"click\",b),m.append(\"g\").attr(\"class\",\"dimensions\");var A=h.select(\"g.dimensions\").selectAll(\"g.dimension\").data((function(t){return t.dimensions}),p);A.enter().append(\"g\").attr(\"class\",\"dimension\"),A.attr(\"transform\",(function(t){return l(t.x,0)})),A.exit().remove();var M=A.selectAll(\"g.category\").data((function(t){return t.categories}),p),S=M.enter().append(\"g\").attr(\"class\",\"category\");M.attr(\"transform\",(function(t){return l(0,t.y)})),S.append(\"rect\").attr(\"class\",\"catrect\").attr(\"pointer-events\",\"none\"),M.select(\"rect.catrect\").attr(\"fill\",\"none\").attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})),T(S);var 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d(t)?\"start\":\"end\"})).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",f.makeTextShadow(D)).style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",(function(t){return d(t)?t.width+5:-5})).attr(\"y\",(function(t){return t.height/2})).text((function(t){return t.model.categoryLabel})).each((function(t){u.font(n.select(this),t.parcatsViewModel.categorylabelfont),f.convertToTspans(n.select(this),e)})),S.append(\"text\").attr(\"class\",\"dimlabel\"),M.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"})).attr(\"x\",(function(t){return t.width/2})).attr(\"y\",-5).text((function(t,e){return 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n=r(7316);e.name=\"pie\",e.plot=function(t,r,i,a){n.plotBasePlot(e.name,t,r,i,a)},e.clean=function(t,r,i,a){n.cleanBasePlot(e.name,t,r,i,a)}},45768:function(t,e,r){\"use strict\";var n=r(38248),i=r(49760),a=r(76308),o={};function s(t){return function(e,r){return!!e&&!!(e=i(e)).isValid()&&(e=a.addOpacity(e,e.getAlpha()),t[r]||(t[r]=e),e)}}function l(t,e){var r,n=JSON.stringify(t),a=e[n];if(!a){for(a=t.slice(),r=0;r=0})),(\"funnelarea\"===e.type?y:e.sort)&&a.sort((function(t,e){return e.v-t.v})),a[0]&&(a[0].vTotal=g),a},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r=\"pie\");var n=t._fullLayout,i=t.calcdata,a=n[r+\"colorway\"],s=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(a=l(a,o));for(var u=0,c=0;c0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:a,len:o}}function c(t,e,r,n,i){n(\"marker.line.width\")&&n(\"marker.line.color\",i?void 0:r.paper_bgcolor);var a=n(\"marker.colors\");l(n,\"marker.pattern\",a),t.marker&&!e.marker.pattern.fgcolor&&(e.marker.pattern.fgcolor=t.marker.colors),e.marker.pattern.bgcolor||(e.marker.pattern.bgcolor=r.paper_bgcolor)}t.exports={handleLabelsAndValues:u,handleMarkerDefaults:c,supplyDefaults:function(t,e,r,n){function l(r,n){return i.coerce(t,e,a,r,n)}var f=u(l(\"labels\"),l(\"values\")),h=f.len;if(e._hasLabels=f.hasLabels,e._hasValues=f.hasValues,!e._hasLabels&&e._hasValues&&(l(\"label0\"),l(\"dlabel\")),h){e._length=h,c(t,e,n,l,!0),l(\"scalegroup\");var p,d=l(\"text\"),v=l(\"texttemplate\");if(v||(p=l(\"textinfo\",i.isArrayOrTypedArray(d)?\"text+percent\":\"percent\")),l(\"hovertext\"),l(\"hovertemplate\"),v||p&&\"none\"!==p){var g=l(\"textposition\");s(t,e,n,l,g,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(g)||\"auto\"===g||\"outside\"===g)&&l(\"automargin\"),(\"inside\"===g||\"auto\"===g||Array.isArray(g))&&l(\"insidetextorientation\")}else\"none\"===p&&l(\"textposition\",\"none\");o(e,n,l);var y=l(\"hole\");if(l(\"title.text\")){var m=l(\"title.position\",y?\"middle center\":\"top center\");y||\"middle center\"!==m||(e.title.position=\"top center\"),i.coerceFont(l,\"title.font\",n.font)}l(\"sort\"),l(\"direction\"),l(\"rotation\"),l(\"pull\")}else e.visible=!1}}},53644:function(t,e,r){\"use strict\";var n=r(10624).appendArrayMultiPointValues;t.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,bbox:t.bbox,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),\"funnelarea\"===e.type&&(delete r.v,delete r.i),r}},21552:function(t,e,r){\"use strict\";var n=r(43616),i=r(76308);t.exports=function(t,e,r,a){var o=r.marker.pattern;o&&o.shape?n.pointStyle(t,r,a,e):i.fill(t,e.color)}},69656:function(t,e,r){\"use strict\";var n=r(3400);function i(t){return-1!==t.indexOf(\"e\")?t.replace(/[.]?0+e/,\"e\"):-1!==t.indexOf(\".\")?t.replace(/[.]?0+$/,\"\"):t}e.formatPiePercent=function(t,e){var r=i((100*t).toPrecision(3));return n.numSeparate(r,e)+\"%\"},e.formatPieValue=function(t,e){var r=i(t.toPrecision(10));return n.numSeparate(r,e)},e.getFirstFilled=function(t,e){if(n.isArrayOrTypedArray(t))for(var r=0;r\"),name:f.hovertemplate||-1!==h.indexOf(\"name\")?f.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:g.castOption(_.bgcolor,t.pts)||t.color,borderColor:g.castOption(_.bordercolor,t.pts),fontFamily:g.castOption(w.family,t.pts),fontSize:g.castOption(w.size,t.pts),fontColor:g.castOption(w.color,t.pts),nameLength:g.castOption(_.namelength,t.pts),textAlign:g.castOption(_.align,t.pts),hovertemplate:g.castOption(f.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[y(t,f)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e,inOut_bbox:T}),t.bbox=T[0],u._hasHoverLabel=!0}u._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[y(t,f)],event:n.event})}})),t.on(\"mouseout\",(function(t){var r=e._fullLayout,i=e._fullData[u.index],o=n.select(this).datum();u._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[y(o,i)],event:n.event}),u._hasHoverEvent=!1),u._hasHoverLabel&&(a.loneUnhover(r._hoverlayer.node()),u._hasHoverLabel=!1)})),t.on(\"click\",(function(t){var r=e._fullLayout,i=e._fullData[u.index];e._dragging||!1===r.hovermode||(e._hoverdata=[y(t,i)],a.click(e,n.event))}))}function b(t,e,r){var n=g.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=g.castOption(t._input.textfont.color,e.pts));var i=g.castOption(t.insidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,a=g.castOption(t.insidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size,s=g.castOption(t.insidetextfont.weight,e.pts)||g.castOption(t.textfont.weight,e.pts)||r.weight,l=g.castOption(t.insidetextfont.style,e.pts)||g.castOption(t.textfont.style,e.pts)||r.style,u=g.castOption(t.insidetextfont.variant,e.pts)||g.castOption(t.textfont.variant,e.pts)||r.variant;return{color:n||o.contrast(e.color),family:i,size:a,weight:s,style:l,variant:u}}function _(t,e){for(var r,n,i=0;ie&&e>n||r=-4;g-=2)y(Math.PI*g,\"tan\");for(g=4;g>=-4;g-=2)y(Math.PI*(g+1),\"tan\")}if(f||p){for(g=4;g>=-4;g-=2)y(Math.PI*(g+1.5),\"rad\");for(g=4;g>=-4;g-=2)y(Math.PI*(g+.5),\"rad\")}}if(s||d||f){var m=Math.sqrt(t.width*t.width+t.height*t.height);if((a={scale:i*n*2/m,rCenter:1-i,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,a.scale>=1)return a;v.push(a)}(d||p)&&((a=T(t,n,o,l,u)).textPosAngle=(e.startangle+e.stopangle)/2,v.push(a)),(d||h)&&((a=k(t,n,o,l,u)).textPosAngle=(e.startangle+e.stopangle)/2,v.push(a));for(var x=0,b=0,_=0;_=1)break}return v[x]}function T(t,e,r,n,i){e=Math.max(0,e-2*v);var a=t.width/t.height,o=S(a,n,e,r);return{scale:2*o/t.height,rCenter:A(a,o/e),rotate:M(i)}}function k(t,e,r,n,i){e=Math.max(0,e-2*v);var a=t.height/t.width,o=S(a,n,e,r);return{scale:2*o/t.width,rCenter:A(a,o/e),rotate:M(i+Math.PI/2)}}function A(t,e){return Math.cos(e)-t*e}function M(t){return(180/Math.PI*t+720)%180-90}function S(t,e,r,n){var i=t+1/(2*Math.tan(e));return r*Math.min(1/(Math.sqrt(i*i+.5)+i),n/(Math.sqrt(t*t+n/2)+t))}function E(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function L(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return r<0&&(i*=-1),n<0&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function C(t,e){var r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=O(a),-1!==a.title.position.indexOf(\"top\")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf(\"bottom\")&&(o.y+=(1+i)*t.r);var l,u=t.r/(void 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b=function(t){return{label:t.label,value:t.v,valueLabel:g.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:g.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(i,t.i,\"customdata\")}}(e),_=g.getFirstFilled(i.text,e.pts);(m(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,i._meta||{})}else e.text=\"\"}}function R(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}t.exports={plot:function(t,e){var r=t._context.staticPlot,a=t._fullLayout,h=a._size;d(\"pie\",a),_(e,t),I(e,h);var v=l.makeTraceGroups(a._pielayer,e,\"trace\").each((function(e){var d=n.select(this),v=e[0],y=v.trace;!function(t){var 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A=\"M\"+(u+i.px0[0])+\",\"+(c+i.px0[1])+P(i.px0,i.pxmid,!0,1)+P(i.pxmid,i.px0,!0,1)+\"Z\";k?d.attr(\"d\",\"M\"+(u+k*i.px0[0])+\",\"+(c+k*i.px0[1])+P(i.px0,i.pxmid,!1,k)+P(i.pxmid,i.px0,!1,k)+\"Z\"+A):d.attr(\"d\",A)}else{var M=P(i.px0,i.px1,!0,1);if(k){var S=1-k;d.attr(\"d\",\"M\"+(u+k*i.px1[0])+\",\"+(c+k*i.px1[1])+P(i.px1,i.px0,!1,k)+\"l\"+S*i.px0[0]+\",\"+S*i.px0[1]+M+\"Z\")}else d.attr(\"d\",\"M\"+u+\",\"+c+\"l\"+i.px0[0]+\",\"+i.px0[1]+M+\"Z\")}D(t,i,v);var E=g.castOption(y.textposition,i.pts),C=h.selectAll(\"g.slicetext\").data(i.text&&\"none\"!==E?[0]:[]);C.enter().append(\"g\").classed(\"slicetext\",!0),C.exit().remove(),C.each((function(){var r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),h=l.ensureUniformFontSize(t,\"outside\"===E?function(t,e,r){return{color:g.castOption(t.outsidetextfont.color,e.pts)||g.castOption(t.textfont.color,e.pts)||r.color,family:g.castOption(t.outsidetextfont.family,e.pts)||g.castOption(t.textfont.family,e.pts)||r.family,size:g.castOption(t.outsidetextfont.size,e.pts)||g.castOption(t.textfont.size,e.pts)||r.size,weight:g.castOption(t.outsidetextfont.weight,e.pts)||g.castOption(t.textfont.weight,e.pts)||r.weight,style:g.castOption(t.outsidetextfont.style,e.pts)||g.castOption(t.textfont.style,e.pts)||r.style,variant:g.castOption(t.outsidetextfont.variant,e.pts)||g.castOption(t.textfont.variant,e.pts)||r.variant}}(y,i,a.font):b(y,i,a.font));r.text(i.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,h).call(f.convertToTspans,t);var d,m=s.bBox(r.node());if(\"outside\"===E)d=L(m,i);else if(d=w(m,i,v),\"auto\"===E&&d.scale<1){var x=l.ensureUniformFontSize(t,y.outsidetextfont);r.call(s.font,x),d=L(m=s.bBox(r.node()),i)}var _=d.textPosAngle,k=void 0===_?i.pxmid:z(v.r,_);if(d.targetX=u+k[0]*d.rCenter+(d.x||0),d.targetY=c+k[1]*d.rCenter+(d.y||0),R(d,m),d.outside){var A=d.targetY;i.yLabelMin=A-m.height/2,i.yLabelMid=A,i.yLabelMax=A+m.height/2,i.labelExtraX=0,i.labelExtraY=0,T=!0}d.fontSize=h.size,p(y.type,d,a),e[o].transform=d,l.setTransormAndDisplay(r,d)}))}function P(t,e,r,n){var a=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return\"a\"+n*v.r+\",\"+n*v.r+\" 0 \"+i.largeArc+(r?\" 1 \":\" 0 \")+a+\",\"+o}}));var k=n.select(this).selectAll(\"g.titletext\").data(y.title.text?[0]:[]);if(k.enter().append(\"g\").classed(\"titletext\",!0),k.exit().remove(),k.each((function(){var e,r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),i=y.title.text;y._meta&&(i=l.templateString(i,y._meta)),r.text(i).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,y.title.font).call(f.convertToTspans,t),e=\"middle center\"===y.title.position?function(t){var e=Math.sqrt(t.titleBox.width*t.titleBox.width+t.titleBox.height*t.titleBox.height);return{x:t.cx,y:t.cy,scale:t.trace.hole*t.r*2/e,tx:0,ty:-t.titleBox.height/2+t.trace.title.font.size}}(v):C(v,h),r.attr(\"transform\",c(e.x,e.y)+u(Math.min(1,e.scale))+c(e.tx,e.ty))})),T&&function(t,e){var r,n,i,a,o,s,u,c,f,h,p,d,v;function y(t,e){return t.pxmid[1]-e.pxmid[1]}function m(t,e){return e.pxmid[1]-t.pxmid[1]}function x(t,r){r||(r={});var i,c,f,p,d=r.labelExtraY+(n?r.yLabelMax:r.yLabelMin),v=n?t.yLabelMin:t.yLabelMax,y=n?t.yLabelMax:t.yLabelMin,m=t.cyFinal+o(t.px0[1],t.px1[1]),x=d-v;if(x*u>0&&(t.labelExtraY=x),l.isArrayOrTypedArray(e.pull))for(c=0;c=(g.castOption(e.pull,f.pts)||0)||((t.pxmid[1]-f.pxmid[1])*u>0?(x=f.cyFinal+o(f.px0[1],f.px1[1])-v-t.labelExtraY)*u>0&&(t.labelExtraY+=x):(y+t.labelExtraY-m)*u>0&&(i=3*s*Math.abs(c-h.indexOf(t)),(p=f.cxFinal+a(f.px0[0],f.px1[0])+i-(t.cxFinal+t.pxmid[0])-t.labelExtraX)*s>0&&(t.labelExtraX+=p)))}for(n=0;n<2;n++)for(i=n?y:m,o=n?Math.max:Math.min,u=n?1:-1,r=0;r<2;r++){for(a=r?Math.max:Math.min,s=r?1:-1,(c=t[n][r]).sort(i),f=t[1-n][r],h=f.concat(c),d=[],p=0;pMath.abs(f)?s+=\"l\"+f*t.pxmid[0]/t.pxmid[1]+\",\"+f+\"H\"+(a+t.labelExtraX+u):s+=\"l\"+t.labelExtraX+\",\"+c+\"v\"+(f-c)+\"h\"+u}else s+=\"V\"+(t.yLabelMid+t.labelExtraY)+\"h\"+u;l.ensureSingle(r,\"path\",\"textline\").call(o.stroke,e.outsidetextfont.color).attr({\"stroke-width\":Math.min(2,e.outsidetextfont.size/8),d:s,fill:\"none\"})}else r.select(\"path.textline\").remove()}))}(m,y),T&&y.automargin){var A=s.bBox(d.node()),M=y.domain,S=h.w*(M.x[1]-M.x[0]),E=h.h*(M.y[1]-M.y[0]),P=(.5*S-v.r)/h.w,O=(.5*E-v.r)/h.h;i.autoMargin(t,\"pie.\"+y.uid+\".automargin\",{xl:M.x[0]-P,xr:M.x[1]+P,yb:M.y[0]-O,yt:M.y[1]+O,l:Math.max(v.cx-v.r-A.left,0),r:Math.max(A.right-(v.cx+v.r),0),b:Math.max(A.bottom-(v.cy+v.r),0),t:Math.max(v.cy-v.r-A.top,0),pad:5})}}))}));setTimeout((function(){v.selectAll(\"tspan\").each((function(){var t=n.select(this);t.attr(\"dy\")&&t.attr(\"dy\",t.attr(\"dy\"))}))}),0)},formatSliceLabel:D,transformInsideText:w,determineInsideTextFont:b,positionTitleOutside:C,prerenderTitles:_,layoutAreas:I,attachFxHandlers:x,computeTransform:R}},22152:function(t,e,r){\"use strict\";var 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n=r(52904);t.exports={x:n.x,y:n.y,xy:{valType:\"data_array\",editType:\"calc\"},indices:{valType:\"data_array\",editType:\"calc\"},xbounds:{valType:\"data_array\",editType:\"calc\"},ybounds:{valType:\"data_array\",editType:\"calc\"},text:n.text,marker:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},opacity:{valType:\"number\",min:0,max:1,dflt:1,arrayOk:!1,editType:\"calc\"},blend:{valType:\"boolean\",dflt:null,editType:\"calc\"},sizemin:{valType:\"number\",min:.1,max:2,dflt:.5,editType:\"calc\"},sizemax:{valType:\"number\",min:.1,dflt:20,editType:\"calc\"},border:{color:{valType:\"color\",arrayOk:!1,editType:\"calc\"},arearatio:{valType:\"number\",min:0,max:1,dflt:0,editType:\"calc\"},editType:\"calc\"},editType:\"calc\"},transforms:void 0}},11072:function(t,e,r){\"use strict\";var n=r(67792).gl_pointcloud2d,i=r(3400).isArrayOrTypedArray,a=r(43080),o=r(19280).findExtremes,s=r(44928);function 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w=t.node.groups,T={};for(e=0;e0&&s(L,_)&&s(C,_)&&(!T.hasOwnProperty(L)||!T.hasOwnProperty(C)||T[L]!==T[C])){T.hasOwnProperty(C)&&(C=T[C]),T.hasOwnProperty(L)&&(L=T[L]),C=+C,p[L=+L]=p[C]=!0;var P=\"\";a.label&&a.label[e]&&(P=a.label[e]);var O=null;P&&d.hasOwnProperty(P)&&(O=d[P]),u.push({pointNumber:e,label:P,color:c?a.color[e]:a.color,hovercolor:f?a.hovercolor[e]:a.hovercolor,customdata:h?a.customdata[e]:a.customdata,concentrationscale:O,source:L,target:C,value:+E}),S.source.push(L),S.target.push(C)}}var I=_+w.length,z=o(r.color),D=o(r.customdata),R=[];for(e=0;e_-1,childrenNodes:[],pointNumber:e,label:F,color:z?r.color[e]:r.color,customdata:D?r.customdata[e]:r.customdata})}var B=!1;return function(t,e,r){for(var a=i.init2dArray(t,0),o=0;o1}))}(I,S.source,S.target)&&(B=!0),{circular:B,links:u,nodes:R,groups:w,groupLookup:T}}(e);return a({circular:r.circular,_nodes:r.nodes,_links:r.links,_groups:r.groups,_groupLookup:r.groupLookup})}},11820:function(t){\"use 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n.coerce(v,g,i.node,t,e)}y(\"label\"),y(\"groups\"),y(\"x\"),y(\"y\"),y(\"pad\"),y(\"thickness\"),y(\"line.color\"),y(\"line.width\"),y(\"hoverinfo\",t.hoverinfo),l(v,g,y,d),y(\"hovertemplate\"),y(\"align\");var m=h.colorway;y(\"color\",g.label.map((function(t,e){return a.addOpacity(function(t){return m[t%m.length]}(e),.8)}))),y(\"customdata\");var x=t.link||{},b=u.newContainer(e,\"link\");function _(t,e){return n.coerce(x,b,i.link,t,e)}_(\"label\"),_(\"arrowlen\"),_(\"source\"),_(\"target\"),_(\"value\"),_(\"line.color\"),_(\"line.width\"),_(\"hoverinfo\",t.hoverinfo),l(x,b,_,d),_(\"hovertemplate\");var w,T=o(h.paper_bgcolor).getLuminance()<.333,k=_(\"color\",T?\"rgba(255, 255, 255, 0.6)\":\"rgba(0, 0, 0, 0.2)\");function A(t){var e=o(t);if(!e.isValid())return t;var r=e.getAlpha();return 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d(t){n.select(t).select(\"text.name\").style(\"fill\",\"black\")}function v(t){return function(e){return-1!==t.node.sourceLinks.indexOf(e.link)||-1!==t.node.targetLinks.indexOf(e.link)}}function g(t){return function(e){return-1!==e.node.sourceLinks.indexOf(t.link)||-1!==e.node.targetLinks.indexOf(t.link)}}function y(t,e,r){e&&r&&h(r,e).selectAll(\".\"+u.sankeyLink).filter(v(e)).call(x.bind(0,e,r,!1))}function m(t,e,r){e&&r&&h(r,e).selectAll(\".\"+u.sankeyLink).filter(v(e)).call(b.bind(0,e,r,!1))}function x(t,e,r,n){n.style(\"fill\",(function(t){if(!t.link.concentrationscale)return t.tinyColorHoverHue})).style(\"fill-opacity\",(function(t){if(!t.link.concentrationscale)return t.tinyColorHoverAlpha})),n.each((function(r){var n=r.link.label;\"\"!==n&&h(e,t).selectAll(\".\"+u.sankeyLink).filter((function(t){return t.link.label===n})).style(\"fill\",(function(t){if(!t.link.concentrationscale)return 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if(\"toself\"===s.fill||\"tonext\"===s.fill){for(p=[],i=0,t.splitNull=!0,a=0;a-1;for(v=0;v<_;v++){var L=r[v][0],C=L.trace,P=L.t,O=P.index,I=C._length,z=P.x,D=P.y;if(C.selectedpoints||S||E){if(S||(S=!0),C.selectedpoints){var R=m.selectBatch[O]=s.selIndices2selPoints(C),F={};for(g=0;g\")}function c(t){return t+\"°\"}}t.exports={hoverPoints:function(t,e,r){var o=t.cd,c=o[0].trace,f=t.xa,h=t.ya,p=t.subplot,d=[],v=l+c.uid+\"-circle\",g=c.cluster&&c.cluster.enabled;if(g){var y=p.map.queryRenderedFeatures(null,{layers:[v]});d=y.map((function(t){return t.id}))}var m=360*(e>=0?Math.floor((e+180)/360):Math.ceil((e-180)/360)),x=e-m;if(n.getClosest(o,(function(t){var e=t.lonlat;if(e[0]===s)return 1/0;if(g&&-1===d.indexOf(t.i+1))return 1/0;var n=i.modHalf(e[0],360),a=e[1],o=p.project([n,a]),l=o.x-f.c2p([x,a]),u=o.y-h.c2p([n,r]),c=Math.max(3,t.mrc||0);return Math.max(Math.sqrt(l*l+u*u)-c,1-3/c)}),t),!1!==t.index){var b=o[t.index],_=b.lonlat,w=[i.modHalf(_[0],360)+m,_[1]],T=f.c2p(w),k=h.c2p(w),A=b.mrc||1;t.x0=T-A,t.x1=T+A,t.y0=k-A,t.y1=k+A;var M={};M[c.subplot]={_subplot:p};var S=c._module.formatLabels(b,c,M);return t.lonLabel=S.lonLabel,t.latLabel=S.latLabel,t.color=a(c,b),t.extraText=u(c,b,o[0].t.labels),t.hovertemplate=c.hovertemplate,[t]}},getExtraText:u}},11572:function(t,e,r){\"use strict\";t.exports={attributes:r(31512),supplyDefaults:r(15752),colorbar:r(5528),formatLabels:r(11960),calc:r(25212),plot:r(9660),hoverPoints:r(63312).hoverPoints,eventData:r(37920),selectPoints:r(404),styleOnSelect:function(t,e){e&&e[0].trace._glTrace.update(e)},moduleType:\"trace\",name:\"scattermapbox\",basePlotModule:r(33688),categories:[\"mapbox\",\"gl\",\"symbols\",\"showLegend\",\"scatter-like\"],meta:{}}},9660:function(t,e,r){\"use strict\";var n=r(3400),i=r(59392),a=r(47552).traceLayerPrefix,o={cluster:[\"cluster\",\"clusterCount\",\"circle\"],nonCluster:[\"fill\",\"line\",\"circle\",\"symbol\"]};function s(t,e,r,n){this.type=\"scattermapbox\",this.subplot=t,this.uid=e,this.clusterEnabled=r,this.isHidden=n,this.sourceIds={fill:\"source-\"+e+\"-fill\",line:\"source-\"+e+\"-line\",circle:\"source-\"+e+\"-circle\",symbol:\"source-\"+e+\"-symbol\",cluster:\"source-\"+e+\"-circle\",clusterCount:\"source-\"+e+\"-circle\"},this.layerIds={fill:a+e+\"-fill\",line:a+e+\"-line\",circle:a+e+\"-circle\",symbol:a+e+\"-symbol\",cluster:a+e+\"-cluster\",clusterCount:a+e+\"-cluster-count\"},this.below=null}var l=s.prototype;l.addSource=function(t,e,r){var i={type:\"geojson\",data:e.geojson};r&&r.enabled&&n.extendFlat(i,{cluster:!0,clusterMaxZoom:r.maxzoom});var a=this.subplot.map.getSource(this.sourceIds[t]);a?a.setData(e.geojson):this.subplot.map.addSource(this.sourceIds[t],i)},l.setSourceData=function(t,e){this.subplot.map.getSource(this.sourceIds[t]).setData(e.geojson)},l.addLayer=function(t,e,r){var n={type:e.type,id:this.layerIds[t],source:this.sourceIds[t],layout:e.layout,paint:e.paint};e.filter&&(n.filter=e.filter);for(var i,a=this.layerIds[t],o=this.subplot.getMapLayers(),s=0;s=0;r--){var i=e[r];n.removeLayer(c.layerIds[i])}t||n.removeSource(c.sourceIds.circle)}(t):function(t){for(var e=o.nonCluster,r=e.length-1;r>=0;r--){var i=e[r];n.removeLayer(c.layerIds[i]),t||n.removeSource(c.sourceIds[i])}}(t)}function h(t){l?function(t){t||c.addSource(\"circle\",a.circle,e.cluster);for(var r=o.cluster,n=0;n=0;r--){var n=e[r];t.removeLayer(this.layerIds[n]),t.removeSource(this.sourceIds[n])}},t.exports=function(t,e){var r,n,a,l=e[0].trace,u=l.cluster&&l.cluster.enabled,c=!0!==l.visible,f=new s(t,l.uid,u,c),h=i(t.gd,e),p=f.below=t.belowLookup[\"trace-\"+l.uid];if(u)for(f.addSource(\"circle\",h.circle,l.cluster),r=0;r\")}}t.exports={hoverPoints:function(t,e,r,a){var o=n(t,e,r,a);if(o&&!1!==o[0].index){var s=o[0];if(void 0===s.index)return o;var l=t.subplot,u=s.cd[s.index],c=s.trace;if(l.isPtInside(u))return s.xLabelVal=void 0,s.yLabelVal=void 0,i(u,c,l,s),s.hovertemplate=c.hovertemplate,o}},makeHoverPointText:i}},76924:function(t,e,r){\"use strict\";t.exports={moduleType:\"trace\",name:\"scatterpolar\",basePlotModule:r(40872),categories:[\"polar\",\"symbols\",\"showLegend\",\"scatter-like\"],attributes:r(8319),supplyDefaults:r(85968).supplyDefaults,colorbar:r(5528),formatLabels:r(22852),calc:r(58320),plot:r(43456),style:r(49224).style,styleOnSelect:r(49224).styleOnSelect,hoverPoints:r(8504).hoverPoints,selectPoints:r(91560),meta:{}}},43456:function(t,e,r){\"use strict\";var n=r(96504),i=r(39032).BADNUM;t.exports=function(t,e,r){for(var 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n=r(38248),i=r(39032).BADNUM,a=r(90136),o=r(20148),s=r(4500),l=r(16356).calcMarkerSize;t.exports=function(t,e){for(var r=t._fullLayout,u=e.subplot,c=r[u].realaxis,f=r[u].imaginaryaxis,h=c.makeCalcdata(e,\"real\"),p=f.makeCalcdata(e,\"imag\"),d=e._length,v=new Array(d),g=0;g\")}}t.exports={hoverPoints:function(t,e,r,a){var o=n(t,e,r,a);if(o&&!1!==o[0].index){var s=o[0];if(void 0===s.index)return o;var l=t.subplot,u=s.cd[s.index],c=s.trace;if(l.isPtInside(u))return s.xLabelVal=void 0,s.yLabelVal=void 0,i(u,c,l,s),s.hovertemplate=c.hovertemplate,o}},makeHoverPointText:i}},95443:function(t,e,r){\"use 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e.listPath(t,\"label\").join(\"/\")+\"/\"},e.formatValue=o.formatPieValue,e.formatPercent=function(t,e){var r=n.formatPercent(t,0);return\"0%\"===r&&(r=o.formatPiePercent(t,e)),r}},5621:function(t,e,r){\"use strict\";t.exports={moduleType:\"trace\",name:\"sunburst\",basePlotModule:r(54904),categories:[],animatable:!0,attributes:r(424),layoutAttributes:r(84920),supplyDefaults:r(25244),supplyLayoutDefaults:r(28732),calc:r(3776).calc,crossTraceCalc:r(3776).crossTraceCalc,plot:r(96488).plot,style:r(85676).style,colorbar:r(5528),meta:{}}},84920:function(t){\"use strict\";t.exports={sunburstcolorway:{valType:\"colorlist\",editType:\"calc\"},extendsunburstcolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},28732:function(t,e,r){\"use strict\";var n=r(3400),i=r(84920);t.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"sunburstcolorway\",e.colorway),r(\"extendsunburstcolors\")}},96488:function(t,e,r){\"use strict\";var n=r(33428),i=r(74148),a=r(67756).qy,o=r(43616),s=r(3400),l=r(72736),u=r(82744),c=u.recordMinTextSize,f=u.clearMinTextSize,h=r(37820),p=r(69656).getRotationAngle,d=h.computeTransform,v=h.transformInsideText,g=r(85676).styleOne,y=r(60100).resizeText,m=r(45716),x=r(27328),b=r(78176);function _(t,r,u,f){var h=t._context.staticPlot,y=t._fullLayout,_=!y.uniformtext.mode&&b.hasTransition(f),T=n.select(u).selectAll(\"g.slice\"),k=r[0],A=k.trace,M=k.hierarchy,S=b.findEntryWithLevel(M,A.level),E=b.getMaxDepth(A),L=y._size,C=A.domain,P=L.w*(C.x[1]-C.x[0]),O=L.h*(C.y[1]-C.y[0]),I=.5*Math.min(P,O),z=k.cx=L.l+L.w*(C.x[1]+C.x[0])/2,D=k.cy=L.t+L.h*(1-C.y[0])-O/2;if(!S)return T.remove();var R=null,F={};_&&T.each((function(t){F[b.getPtId(t)]={rpx0:t.rpx0,rpx1:t.rpx1,x0:t.x0,x1:t.x1,transform:t.transform},!R&&b.isEntry(t)&&(R=t)}));var B=function(t){return i.partition().size([2*Math.PI,t.height+1])(t)}(S).descendants(),N=S.height+1,j=0,U=E;k.hasMultipleRoots&&b.isHierarchyRoot(S)&&(B=B.slice(1),N-=1,j=1,U+=1),B=B.filter((function(t){return t.y1<=U}));var V=p(A.rotation);V&&B.forEach((function(t){t.x0+=V,t.x1+=V}));var q=Math.min(N,E),H=function(t){return(t-j)/q*I},G=function(t,e){return[t*Math.cos(e),-t*Math.sin(e)]},W=function(t){return s.pathAnnulus(t.rpx0,t.rpx1,t.x0,t.x1,z,D)},Y=function(t){return z+w(t)[0]*(t.transform.rCenter||0)+(t.transform.x||0)},X=function(t){return D+w(t)[1]*(t.transform.rCenter||0)+(t.transform.y||0)};(T=T.data(B,b.getPtId)).enter().append(\"g\").classed(\"slice\",!0),_?T.exit().transition().each((function(){var t=n.select(this);t.select(\"path.surface\").transition().attrTween(\"d\",(function(t){var e=function(t){var e,r=b.getPtId(t),n=F[r],i=F[b.getPtId(S)];if(i){var o=(t.x1>i.x1?2*Math.PI:0)+V;e=t.rpx1Z?2*Math.PI:0)+V;e={x0:i,x1:i}}else e={rpx0:I,rpx1:I},s.extendFlat(e,$(t));else e={rpx0:0,rpx1:0};else e={x0:V,x1:V};return a(e,n)}(t);return function(t){return W(e(t))}})):f.attr(\"d\",W),u.call(m,S,t,r,{eventDataKeys:x.eventDataKeys,transitionTime:x.CLICK_TRANSITION_TIME,transitionEasing:x.CLICK_TRANSITION_EASING}).call(b.setSliceCursor,t,{hideOnRoot:!0,hideOnLeaves:!0,isTransitioning:t._transitioning}),f.call(g,i,A,t);var p=s.ensureSingle(u,\"g\",\"slicetext\"),w=s.ensureSingle(p,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),T=s.ensureUniformFontSize(t,b.determineTextFont(A,i,y.font));w.text(e.formatSliceLabel(i,S,A,r,y)).classed(\"slicetext\",!0).attr(\"text-anchor\",\"middle\").call(o.font,T).call(l.convertToTspans,t);var M=o.bBox(w.node());i.transform=v(M,i,k),i.transform.targetX=Y(i),i.transform.targetY=X(i);var E=function(t,e){var r=t.transform;return d(r,e),r.fontSize=T.size,c(A.type,r,y),s.getTextTransform(r)};_?w.transition().attrTween(\"transform\",(function(t){var e=function(t){var e,r=F[b.getPtId(t)],n=t.transform;if(r)e=r;else if(e={rpx1:t.rpx1,transform:{textPosAngle:n.textPosAngle,scale:0,rotate:n.rotate,rCenter:n.rCenter,x:n.x,y:n.y}},R)if(t.parent)if(Z){var i=t.x1>Z?2*Math.PI:0;e.x0=e.x1=i}else s.extendFlat(e,$(t));else e.x0=e.x1=V;else e.x0=e.x1=V;var o=a(e.transform.textPosAngle,t.transform.textPosAngle),l=a(e.rpx1,t.rpx1),u=a(e.x0,t.x0),f=a(e.x1,t.x1),h=a(e.transform.scale,n.scale),p=a(e.transform.rotate,n.rotate),d=0===n.rCenter?3:0===e.transform.rCenter?1/3:1,v=a(e.transform.rCenter,n.rCenter);return function(t){var e=l(t),r=u(t),i=f(t),a=function(t){return v(Math.pow(t,d))}(t),s={pxmid:G(e,(r+i)/2),rpx1:e,transform:{textPosAngle:o(t),rCenter:a,x:n.x,y:n.y}};return c(A.type,n,y),{transform:{targetX:Y(s),targetY:X(s),scale:h(t),rotate:p(t),rCenter:a}}}}(t);return function(t){return E(e(t),M)}})):w.attr(\"transform\",E(i,M))}))}function w(t){return e=t.rpx1,r=t.transform.textPosAngle,[e*Math.sin(r),-e*Math.cos(r)];var e,r}e.plot=function(t,e,r,i){var a,o,s=t._fullLayout,l=s._sunburstlayer,u=!r,c=!s.uniformtext.mode&&b.hasTransition(r);f(\"sunburst\",s),(a=l.selectAll(\"g.trace.sunburst\").data(e,(function(t){return t[0].trace.uid}))).enter().append(\"g\").classed(\"trace\",!0).classed(\"sunburst\",!0).attr(\"stroke-linejoin\",\"round\"),a.order(),c?(i&&(o=i()),n.transition().duration(r.duration).ease(r.easing).each(\"end\",(function(){o&&o()})).each(\"interrupt\",(function(){o&&o()})).each((function(){l.selectAll(\"g.trace\").each((function(e){_(t,e,this,r)}))}))):(a.each((function(e){_(t,e,this,r)})),s.uniformtext.mode&&y(t,s._sunburstlayer.selectAll(\".trace\"),\"sunburst\")),u&&a.exit().remove()},e.formatSliceLabel=function(t,e,r,n,i){var a=r.texttemplate,o=r.textinfo;if(!(a||o&&\"none\"!==o))return\"\";var l=i.separators,u=n[0],c=t.data.data,f=u.hierarchy,h=b.isHierarchyRoot(t),p=b.getParent(f,t),d=b.getValue(t);if(!a){var v,g=o.split(\"+\"),y=function(t){return-1!==g.indexOf(t)},m=[];if(y(\"label\")&&c.label&&m.push(c.label),c.hasOwnProperty(\"v\")&&y(\"value\")&&m.push(b.formatValue(c.v,l)),!h){y(\"current path\")&&m.push(b.getPath(t.data));var x=0;y(\"percent parent\")&&x++,y(\"percent entry\")&&x++,y(\"percent root\")&&x++;var _=x>1;if(x){var w,T=function(t){v=b.formatPercent(w,l),_&&(v+=\" of \"+t),m.push(v)};y(\"percent parent\")&&!h&&(w=d/b.getValue(p),T(\"parent\")),y(\"percent entry\")&&(w=d/b.getValue(e),T(\"entry\")),y(\"percent root\")&&(w=d/b.getValue(f),T(\"root\"))}}return y(\"text\")&&(v=s.castOption(r,c.i,\"text\"),s.isValidTextValue(v)&&m.push(v)),m.join(\"
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f=t.exports=u(l({z:{valType:\"data_array\"},x:{valType:\"data_array\"},y:{valType:\"data_array\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0},hovertemplate:o(),xhoverformat:a(\"x\"),yhoverformat:a(\"y\"),zhoverformat:a(\"z\"),connectgaps:{valType:\"boolean\",dflt:!1,editType:\"calc\"},surfacecolor:{valType:\"data_array\"}},i(\"\",{colorAttr:\"z or 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n=r(47128);t.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},79164:function(t,e,r){\"use strict\";var n=r(67792).gl_surface3d,i=r(67792).ndarray,a=r(67792).ndarray_linear_interpolate.d2,o=r(70448),s=r(11240),l=r(3400).isArrayOrTypedArray,u=r(33040).parseColorScale,c=r(43080),f=r(8932).extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?i:n.d2l(i,0,r)},p.getZat=function(t,e,r,n){var i=this.data.z[e][t];return null===i&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[e][t]),void 0===r?i:n.d2l(i,0,r)},p.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,i],t.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],t.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){null!=t.dataCoordinate[a]&&(t.dataCoordinate[a]*=this.scene.dataScale[a])}var o=this.data.hovertext||this.data.text;return l(o)&&o[i]&&void 0!==o[i][n]?t.textLabel=o[i][n]:t.textLabel=o||\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var 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v(t,e){if(t0){r=d[n];break}return r}function m(t,e){if(!(t<1||e<1)){for(var r=g(t),n=g(e),i=1,a=0;a_;)r--,r/=y(r),++r1?n:1},p.refineCoords=function(t){for(var e=this.dataScaleX,r=this.dataScaleY,n=t[0].shape[0],a=t[0].shape[1],o=0|Math.floor(t[0].shape[0]*e+1),s=0|Math.floor(t[0].shape[1]*r+1),l=1+n+1,u=1+a+1,c=i(new Float32Array(l*u),[l,u]),f=[1/e,0,0,0,1/r,0,0,0,1],h=0;h0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(i[t]=!0,e=this.contourStart[t];ea&&(this.minValues[e]=a),this.maxValues[e]\",maxDimensionCount:60,overdrag:45,releaseTransitionDuration:120,releaseTransitionEase:\"cubic-out\",scrollbarCaptureWidth:18,scrollbarHideDelay:1e3,scrollbarHideDuration:1e3,scrollbarOffset:5,scrollbarWidth:8,transitionDuration:100,transitionEase:\"cubic-out\",uplift:5,wrapSpacer:\" \",wrapSplitCharacter:\" 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0==(8191&e)&&(r+=13,e>>>=13),0==(127&e)&&(r+=7,e>>>=7),0==(15&e)&&(r+=4,e>>>=4),0==(3&e)&&(r+=2,e>>>=2),0==(1&e)&&r++,r},a.prototype.bitLength=function(){var t=this.words[this.length-1],e=this._countBits(t);return 26*(this.length-1)+e},a.prototype.zeroBits=function(){if(this.isZero())return 0;for(var t=0,e=0;et.length?this.clone().ior(t):t.clone().ior(this)},a.prototype.uor=function(t){return this.length>t.length?this.clone().iuor(t):t.clone().iuor(this)},a.prototype.iuand=function(t){var e;e=this.length>t.length?t:this;for(var r=0;rt.length?this.clone().iand(t):t.clone().iand(this)},a.prototype.uand=function(t){return this.length>t.length?this.clone().iuand(t):t.clone().iuand(this)},a.prototype.iuxor=function(t){var e,r;this.length>t.length?(e=this,r=t):(e=t,r=this);for(var n=0;nt.length?this.clone().ixor(t):t.clone().ixor(this)},a.prototype.uxor=function(t){return this.length>t.length?this.clone().iuxor(t):t.clone().iuxor(this)},a.prototype.inotn=function(t){n(\"number\"==typeof t&&t>=0);var e=0|Math.ceil(t/26),r=t%26;this._expand(e),r>0&&e--;for(var i=0;i0&&(this.words[i]=~this.words[i]&67108863>>26-r),this.strip()},a.prototype.notn=function(t){return this.clone().inotn(t)},a.prototype.setn=function(t,e){n(\"number\"==typeof t&&t>=0);var r=t/26|0,i=t%26;return this._expand(r+1),this.words[r]=e?this.words[r]|1<t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a>>26;for(;0!==i&&a>>26;if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;at.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,i=this.cmp(t);if(0===i)return this.negative=0,this.length=1,this.words[0]=0,this;i>0?(r=this,n=t):(r=t,n=this);for(var a=0,o=0;o>26,this.words[o]=67108863&e;for(;0!==a&&o>26,this.words[o]=67108863&e;if(0===a&&o>>13,p=0|o[1],d=8191&p,v=p>>>13,g=0|o[2],y=8191&g,m=g>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],L=8191&E,C=E>>>13,P=0|o[7],O=8191&P,I=P>>>13,z=0|o[8],D=8191&z,R=z>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],U=8191&j,V=j>>>13,q=0|s[1],H=8191&q,G=q>>>13,W=0|s[2],Y=8191&W,X=W>>>13,Z=0|s[3],K=8191&Z,J=Z>>>13,$=0|s[4],Q=8191&$,tt=$>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ut=st>>>13,ct=0|s[8],ft=8191&ct,ht=ct>>>13,pt=0|s[9],dt=8191&pt,vt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var gt=(u+(n=Math.imul(f,U))|0)+((8191&(i=(i=Math.imul(f,V))+Math.imul(h,U)|0))<<13)|0;u=((a=Math.imul(h,V))+(i>>>13)|0)+(gt>>>26)|0,gt&=67108863,n=Math.imul(d,U),i=(i=Math.imul(d,V))+Math.imul(v,U)|0,a=Math.imul(v,V);var yt=(u+(n=n+Math.imul(f,H)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,H)|0))<<13)|0;u=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(y,U),i=(i=Math.imul(y,V))+Math.imul(m,U)|0,a=Math.imul(m,V),n=n+Math.imul(d,H)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(v,H)|0,a=a+Math.imul(v,G)|0;var mt=(u+(n=n+Math.imul(f,Y)|0)|0)+((8191&(i=(i=i+Math.imul(f,X)|0)+Math.imul(h,Y)|0))<<13)|0;u=((a=a+Math.imul(h,X)|0)+(i>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(b,U),i=(i=Math.imul(b,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(y,H)|0,i=(i=i+Math.imul(y,G)|0)+Math.imul(m,H)|0,a=a+Math.imul(m,G)|0,n=n+Math.imul(d,Y)|0,i=(i=i+Math.imul(d,X)|0)+Math.imul(v,Y)|0,a=a+Math.imul(v,X)|0;var xt=(u+(n=n+Math.imul(f,K)|0)|0)+((8191&(i=(i=i+Math.imul(f,J)|0)+Math.imul(h,K)|0))<<13)|0;u=((a=a+Math.imul(h,J)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,H)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,H)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(y,Y)|0,i=(i=i+Math.imul(y,X)|0)+Math.imul(m,Y)|0,a=a+Math.imul(m,X)|0,n=n+Math.imul(d,K)|0,i=(i=i+Math.imul(d,J)|0)+Math.imul(v,K)|0,a=a+Math.imul(v,J)|0;var bt=(u+(n=n+Math.imul(f,Q)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,Q)|0))<<13)|0;u=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,U),i=(i=Math.imul(M,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,H)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,H)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,Y)|0,i=(i=i+Math.imul(b,X)|0)+Math.imul(_,Y)|0,a=a+Math.imul(_,X)|0,n=n+Math.imul(y,K)|0,i=(i=i+Math.imul(y,J)|0)+Math.imul(m,K)|0,a=a+Math.imul(m,J)|0,n=n+Math.imul(d,Q)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(v,Q)|0,a=a+Math.imul(v,tt)|0;var _t=(u+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;u=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,U),i=(i=Math.imul(L,V))+Math.imul(C,U)|0,a=Math.imul(C,V),n=n+Math.imul(M,H)|0,i=(i=i+Math.imul(M,G)|0)+Math.imul(S,H)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,Y)|0,i=(i=i+Math.imul(T,X)|0)+Math.imul(k,Y)|0,a=a+Math.imul(k,X)|0,n=n+Math.imul(b,K)|0,i=(i=i+Math.imul(b,J)|0)+Math.imul(_,K)|0,a=a+Math.imul(_,J)|0,n=n+Math.imul(y,Q)|0,i=(i=i+Math.imul(y,tt)|0)+Math.imul(m,Q)|0,a=a+Math.imul(m,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(v,rt)|0,a=a+Math.imul(v,nt)|0;var wt=(u+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;u=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(O,U),i=(i=Math.imul(O,V))+Math.imul(I,U)|0,a=Math.imul(I,V),n=n+Math.imul(L,H)|0,i=(i=i+Math.imul(L,G)|0)+Math.imul(C,H)|0,a=a+Math.imul(C,G)|0,n=n+Math.imul(M,Y)|0,i=(i=i+Math.imul(M,X)|0)+Math.imul(S,Y)|0,a=a+Math.imul(S,X)|0,n=n+Math.imul(T,K)|0,i=(i=i+Math.imul(T,J)|0)+Math.imul(k,K)|0,a=a+Math.imul(k,J)|0,n=n+Math.imul(b,Q)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,Q)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(y,rt)|0,i=(i=i+Math.imul(y,nt)|0)+Math.imul(m,rt)|0,a=a+Math.imul(m,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(v,at)|0,a=a+Math.imul(v,ot)|0;var Tt=(u+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ut)|0)+Math.imul(h,lt)|0))<<13)|0;u=((a=a+Math.imul(h,ut)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(D,U),i=(i=Math.imul(D,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(O,H)|0,i=(i=i+Math.imul(O,G)|0)+Math.imul(I,H)|0,a=a+Math.imul(I,G)|0,n=n+Math.imul(L,Y)|0,i=(i=i+Math.imul(L,X)|0)+Math.imul(C,Y)|0,a=a+Math.imul(C,X)|0,n=n+Math.imul(M,K)|0,i=(i=i+Math.imul(M,J)|0)+Math.imul(S,K)|0,a=a+Math.imul(S,J)|0,n=n+Math.imul(T,Q)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,Q)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(y,at)|0,i=(i=i+Math.imul(y,ot)|0)+Math.imul(m,at)|0,a=a+Math.imul(m,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ut)|0)+Math.imul(v,lt)|0,a=a+Math.imul(v,ut)|0;var kt=(u+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;u=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(D,H)|0,i=(i=i+Math.imul(D,G)|0)+Math.imul(R,H)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(O,Y)|0,i=(i=i+Math.imul(O,X)|0)+Math.imul(I,Y)|0,a=a+Math.imul(I,X)|0,n=n+Math.imul(L,K)|0,i=(i=i+Math.imul(L,J)|0)+Math.imul(C,K)|0,a=a+Math.imul(C,J)|0,n=n+Math.imul(M,Q)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(S,Q)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(y,lt)|0,i=(i=i+Math.imul(y,ut)|0)+Math.imul(m,lt)|0,a=a+Math.imul(m,ut)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(v,ft)|0,a=a+Math.imul(v,ht)|0;var At=(u+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,vt)|0)+Math.imul(h,dt)|0))<<13)|0;u=((a=a+Math.imul(h,vt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,H),i=(i=Math.imul(B,G))+Math.imul(N,H)|0,a=Math.imul(N,G),n=n+Math.imul(D,Y)|0,i=(i=i+Math.imul(D,X)|0)+Math.imul(R,Y)|0,a=a+Math.imul(R,X)|0,n=n+Math.imul(O,K)|0,i=(i=i+Math.imul(O,J)|0)+Math.imul(I,K)|0,a=a+Math.imul(I,J)|0,n=n+Math.imul(L,Q)|0,i=(i=i+Math.imul(L,tt)|0)+Math.imul(C,Q)|0,a=a+Math.imul(C,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ut)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ut)|0,n=n+Math.imul(y,ft)|0,i=(i=i+Math.imul(y,ht)|0)+Math.imul(m,ft)|0,a=a+Math.imul(m,ht)|0;var Mt=(u+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,vt)|0)+Math.imul(v,dt)|0))<<13)|0;u=((a=a+Math.imul(v,vt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,Y),i=(i=Math.imul(B,X))+Math.imul(N,Y)|0,a=Math.imul(N,X),n=n+Math.imul(D,K)|0,i=(i=i+Math.imul(D,J)|0)+Math.imul(R,K)|0,a=a+Math.imul(R,J)|0,n=n+Math.imul(O,Q)|0,i=(i=i+Math.imul(O,tt)|0)+Math.imul(I,Q)|0,a=a+Math.imul(I,tt)|0,n=n+Math.imul(L,rt)|0,i=(i=i+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,a=a+Math.imul(C,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ut)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ut)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(u+(n=n+Math.imul(y,dt)|0)|0)+((8191&(i=(i=i+Math.imul(y,vt)|0)+Math.imul(m,dt)|0))<<13)|0;u=((a=a+Math.imul(m,vt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,K),i=(i=Math.imul(B,J))+Math.imul(N,K)|0,a=Math.imul(N,J),n=n+Math.imul(D,Q)|0,i=(i=i+Math.imul(D,tt)|0)+Math.imul(R,Q)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(O,rt)|0,i=(i=i+Math.imul(O,nt)|0)+Math.imul(I,rt)|0,a=a+Math.imul(I,nt)|0,n=n+Math.imul(L,at)|0,i=(i=i+Math.imul(L,ot)|0)+Math.imul(C,at)|0,a=a+Math.imul(C,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ut)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ut)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(u+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,vt)|0)+Math.imul(_,dt)|0))<<13)|0;u=((a=a+Math.imul(_,vt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,Q),i=(i=Math.imul(B,tt))+Math.imul(N,Q)|0,a=Math.imul(N,tt),n=n+Math.imul(D,rt)|0,i=(i=i+Math.imul(D,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(O,at)|0,i=(i=i+Math.imul(O,ot)|0)+Math.imul(I,at)|0,a=a+Math.imul(I,ot)|0,n=n+Math.imul(L,lt)|0,i=(i=i+Math.imul(L,ut)|0)+Math.imul(C,lt)|0,a=a+Math.imul(C,ut)|0,n=n+Math.imul(M,ft)|0,i=(i=i+Math.imul(M,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Lt=(u+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,vt)|0)+Math.imul(k,dt)|0))<<13)|0;u=((a=a+Math.imul(k,vt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(D,at)|0,i=(i=i+Math.imul(D,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(O,lt)|0,i=(i=i+Math.imul(O,ut)|0)+Math.imul(I,lt)|0,a=a+Math.imul(I,ut)|0,n=n+Math.imul(L,ft)|0,i=(i=i+Math.imul(L,ht)|0)+Math.imul(C,ft)|0,a=a+Math.imul(C,ht)|0;var Ct=(u+(n=n+Math.imul(M,dt)|0)|0)+((8191&(i=(i=i+Math.imul(M,vt)|0)+Math.imul(S,dt)|0))<<13)|0;u=((a=a+Math.imul(S,vt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(D,lt)|0,i=(i=i+Math.imul(D,ut)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ut)|0,n=n+Math.imul(O,ft)|0,i=(i=i+Math.imul(O,ht)|0)+Math.imul(I,ft)|0,a=a+Math.imul(I,ht)|0;var Pt=(u+(n=n+Math.imul(L,dt)|0)|0)+((8191&(i=(i=i+Math.imul(L,vt)|0)+Math.imul(C,dt)|0))<<13)|0;u=((a=a+Math.imul(C,vt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ut))+Math.imul(N,lt)|0,a=Math.imul(N,ut),n=n+Math.imul(D,ft)|0,i=(i=i+Math.imul(D,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var Ot=(u+(n=n+Math.imul(O,dt)|0)|0)+((8191&(i=(i=i+Math.imul(O,vt)|0)+Math.imul(I,dt)|0))<<13)|0;u=((a=a+Math.imul(I,vt)|0)+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var It=(u+(n=n+Math.imul(D,dt)|0)|0)+((8191&(i=(i=i+Math.imul(D,vt)|0)+Math.imul(R,dt)|0))<<13)|0;u=((a=a+Math.imul(R,vt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863;var zt=(u+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,vt))+Math.imul(N,dt)|0))<<13)|0;return u=((a=Math.imul(N,vt))+(i>>>13)|0)+(zt>>>26)|0,zt&=67108863,l[0]=gt,l[1]=yt,l[2]=mt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=Pt,l[16]=Ot,l[17]=It,l[18]=zt,0!==u&&(l[19]=u,r.length++),r};function v(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(d=p),a.prototype.mulTo=function(t,e){var r,n=this.length+t.length;return r=10===this.length&&10===t.length?d(this,t,e):n<63?p(this,t,e):n<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):v(this,t,e),r},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o>>=1)i++;return 1<>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<o)for(this.length-=o,u=0;u=0&&(0!==c||u>=i);u--){var f=0|this.words[u];this.words[u]=c<<26-a|f>>>a,c=f&s}return l&&0!==c&&(l.words[l.length++]=c),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!=(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var u=0;u=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),u=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++u;for(var c=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(c),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,v=1;0==(r.words[0]&v)&&d<26;++d,v<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(c),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(u)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var u=0,c=1;0==(e.words[0]&c)&&u<26;++u,c<<=1);if(u>0)for(e.iushrn(u);u-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,i=1<>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];e=i===t?0:it.length)return 1;if(this.length=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){ni&&(e=1);break}}return e},a.prototype.gtn=function(t){return 1===this.cmpn(t)},a.prototype.gt=function(t){return 1===this.cmp(t)},a.prototype.gten=function(t){return this.cmpn(t)>=0},a.prototype.gte=function(t){return this.cmp(t)>=0},a.prototype.ltn=function(t){return-1===this.cmpn(t)},a.prototype.lt=function(t){return-1===this.cmp(t)},a.prototype.lten=function(t){return this.cmpn(t)<=0},a.prototype.lte=function(t){return this.cmp(t)<=0},a.prototype.eqn=function(t){return 0===this.cmpn(t)},a.prototype.eq=function(t){return 0===this.cmp(t)},a.red=function(t){return new T(t)},a.prototype.toRed=function(t){return n(!this.red,\"Already a number in reduction context\"),n(0===this.negative,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},a.prototype.fromRed=function(){return n(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},a.prototype._forceRed=function(t){return this.red=t,this},a.prototype.forceRed=function(t){return n(!this.red,\"Already a number in reduction context\"),this._forceRed(t)},a.prototype.redAdd=function(t){return n(this.red,\"redAdd works only with red numbers\"),this.red.add(this,t)},a.prototype.redIAdd=function(t){return n(this.red,\"redIAdd works only with red numbers\"),this.red.iadd(this,t)},a.prototype.redSub=function(t){return n(this.red,\"redSub works only with red numbers\"),this.red.sub(this,t)},a.prototype.redISub=function(t){return n(this.red,\"redISub works only with red numbers\"),this.red.isub(this,t)},a.prototype.redShl=function(t){return n(this.red,\"redShl works only with red numbers\"),this.red.shl(this,t)},a.prototype.redMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.mul(this,t)},a.prototype.redIMul=function(t){return n(this.red,\"redMul works only with red numbers\"),this.red._verify2(this,t),this.red.imul(this,t)},a.prototype.redSqr=function(){return n(this.red,\"redSqr works only with red numbers\"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var y={k256:null,p224:null,p192:null,p25519:null};function m(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function x(){m.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f\")}function b(){m.call(this,\"p224\",\"ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001\")}function _(){m.call(this,\"p192\",\"ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff\")}function w(){m.call(this,\"25519\",\"7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed\")}function T(t){if(\"string\"==typeof t){var e=a._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),\"modulus must be greater than 1\"),this.m=t,this.prime=null}function k(t){T.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new a(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}m.prototype._tmp=function(){var t=new 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t||(this.autoTicks=!0),f=!0,c=!0,this._firstInit=!1),f&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),c=!0),c){for(p=0;p<3;++p)r[p].sort((function(t,e){return t.x-e.x}));s.equal(r,this.ticks)?c=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(c=!0),l(\"tickFontStyle\")&&(c=!0),l(\"tickFontWeight\")&&(c=!0),l(\"tickFontVariant\")&&(c=!0),a(\"tickSize\"),a(\"tickAngle\"),a(\"tickPad\"),u(\"tickColor\");var v=l(\"labels\");l(\"labelFont\")&&(v=!0),l(\"labelFontStyle\")&&(v=!0),l(\"labelFontWeight\")&&(v=!0),l(\"labelFontVariant\")&&(v=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),u(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),u(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),u(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),u(\"gridColor\"),o(\"zeroEnable\"),u(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),u(\"backgroundColor\");var g=[{family:this.labelFont[0],style:this.labelFontStyle[0],weight:this.labelFontWeight[0],variant:this.labelFontVariant[0]},{family:this.labelFont[1],style:this.labelFontStyle[1],weight:this.labelFontWeight[1],variant:this.labelFontVariant[1]},{family:this.labelFont[2],style:this.labelFontStyle[2],weight:this.labelFontWeight[2],variant:this.labelFontVariant[2]}],y=[{family:this.tickFont[0],style:this.tickFontStyle[0],weight:this.tickFontWeight[0],variant:this.tickFontVariant[0]},{family:this.tickFont[1],style:this.tickFontStyle[1],weight:this.tickFontWeight[1],variant:this.tickFontVariant[1]},{family:this.tickFont[2],style:this.tickFontStyle[2],weight:this.tickFontWeight[2],variant:this.tickFontVariant[2]}];this._text?this._text&&(v||c)&&this._text.update(this.bounds,this.labels,g,this.ticks,y):this._text=n(this.gl,this.bounds,this.labels,g,this.ticks,y),this._lines&&c&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,u=n[e],c=0;c<3;++c)if(e!==c){var f=a,h=s,p=o,d=l;u&1<0?(p[c]=-1,d[c]=0):(p[c]=0,d[c]=1)}}var v=[0,0,0],g={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var y=[0,0,0],m=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||g;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,c=o(r,n,i,a,s),f=c.cubeEdges,h=c.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=f[A],this.lastCubeProps.axis[A]=h[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,f,h);e=this.gl;var S,E,L,C=v;for(A=0;A<3;++A)this.backgroundEnable[A]?C[A]=h[A]:C[A]=0;for(this._background.draw(r,n,i,a,C,this.backgroundColor),this._lines.bind(r,n,i,this),A=0;A<3;++A){var P=[0,0,0];h[A]>0?P[A]=a[1][A]:P[A]=a[0][A];for(var O=0;O<2;++O){var I=(A+1+O)%3,z=(A+1+(1^O))%3;this.gridEnable[I]&&this._lines.drawGrid(I,z,this.bounds,P,this.gridColor[I],this.gridWidth[I]*this.pixelRatio)}for(O=0;O<2;++O)I=(A+1+O)%3,z=(A+1+(1^O))%3,this.zeroEnable[z]&&Math.min(a[0][z],a[1][z])<=0&&Math.max(a[0][z],a[1][z])>=0&&this._lines.drawZero(I,z,this.bounds,P,this.zeroLineColor[z],this.zeroLineWidth[z]*this.pixelRatio)}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var D=u(y,M[A].primalMinor),R=u(m,M[A].mirrorMinor),F=this.lineTickLength;for(O=0;O<3;++O){var B=k/r[5*O];D[O]*=F[O]*B,R[O]*=F[O]*B}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,D,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,R,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}function N(t){(L=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio),A=0;A<3;++A){var U=M[A].primalMinor,V=M[A].mirrorMinor,q=u(x,M[A].primalOffset);for(O=0;O<3;++O)this.lineTickEnable[A]&&(q[O]+=k*U[O]*Math.max(this.lineTickLength[O],0)/r[5*O]);var H=[0,0,0];if(H[A]=1,this.tickEnable[A]){for(-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]=\"auto\"):this.tickAlign[A]=-1,E=1,\"auto\"===(S=[this.tickAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),L=[0,0,0],j(A,U,V),O=0;O<3;++O)q[O]+=k*U[O]*this.tickPad[O]/r[5*O];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],q,this.tickColor[A],H,L,S)}if(this.labelEnable[A]){for(E=0,L=[0,0,0],this.labels[A].length>4&&(N(A),E=1),\"auto\"===(S=[this.labelAlign[A],.5,E])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),O=0;O<3;++O)q[O]+=k*U[O]*this.labelPad[O]/r[5*O];q[A]+=.5*(a[0][A]+a[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],q,this.labelColor[A],[0,0,0],L,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},5304:function(t,e,r){\"use strict\";t.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var u=(l+1)%3,c=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[u]=d;for(var v=-1;v<=1;v+=2)f[c]=v,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var g=u;u=c,c=g}var y=n(t,new Float32Array(e)),m=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:y,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:y,type:t.FLOAT,size:3,offset:12,stride:24}],m),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,y,x,b)};var n=r(2762),i=r(8116),a=r(1879).bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},6429:function(t,e,r){\"use strict\";t.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var m=0,x=0;x<2;++x){c[2]=a[x][2];for(var b=0;b<2;++b){c[1]=a[b][1];for(var _=0;_<2;++_)c[0]=a[_][0],h(l[m],c,s),m+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)u[x][k]=l[x][k]/T;p&&(u[x][2]*=-1),T<0&&(w<0||u[x][2]E&&(w|=1<E&&(w|=1<u[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x)(N=R^1<u[B][0]&&(B=N))}var j=v;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===D?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=g,q=w;for(A=0;A<3;++A)V[A]=q&1< HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n b - PI :\\n b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n // if ratio is set to 0.5 then it is 50%, 50%.\\n // when using a higher ratio e.g. 0.75 the result would\\n // likely be more horizontal than vertical.\\n\\n float b = positive_angle(a);\\n\\n return\\n (b < ( ratio) * HALF_PI) ? 0.0 :\\n (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n 0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n float b = positive_angle(a);\\n float div = TWO_PI / float(n);\\n float c = roundTo(b, div);\\n return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n return\\n (option > 2) ? look_round_n_directions(rawAngle + delta, option) : // option 3-n: round to n directions\\n (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n (option == 1) ? rawAngle + delta : // use free angle, and flip to align with one direction of the axis\\n (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n (option ==-1) ? 0.0 : // useful for backward compatibility, all texts remains horizontal\\n rawAngle; // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n (axis.y == 0.0) &&\\n (axis.z == 0.0);\\n\\nvoid main() {\\n //Compute world offset\\n float axisDistance = position.z;\\n vec3 dataPosition = axisDistance * axis + offset;\\n\\n float beta = angle; // i.e. user defined attributes for each tick\\n\\n float axisAngle;\\n float clipAngle;\\n float flip;\\n\\n if (enableAlign) {\\n axisAngle = (isAxisTitle) ? HALF_PI :\\n computeViewAngle(dataPosition, dataPosition + axis);\\n clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n clipAngle += (sin(clipAngle) < 0.0) ? PI : 0.0;\\n\\n flip = (dot(vec2(cos(axisAngle), sin(axisAngle)),\\n vec2(sin(clipAngle),-cos(clipAngle))) > 0.0) ? 1.0 : 0.0;\\n\\n beta += applyAlignOption(clipAngle, flip * PI);\\n }\\n\\n //Compute plane offset\\n vec2 planeCoord = position.xy * pixelScale;\\n\\n mat2 planeXform = scale * mat2(\\n cos(beta), sin(beta),\\n -sin(beta), cos(beta)\\n );\\n\\n vec2 viewOffset = 2.0 * planeXform * planeCoord / resolution;\\n\\n //Compute clip position\\n vec3 clipPosition = project(dataPosition);\\n\\n //Apply text offset in clip coordinates\\n clipPosition += vec3(viewOffset, 0.0);\\n\\n //Done\\n gl_Position = vec4(clipPosition, 1.0);\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n gl_FragColor = color;\\n}\"]);e.Q=function(t){return i(t,s,l,null,[{name:\"position\",type:\"vec3\"}])};var u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec3 normal;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 enable;\\nuniform vec3 bounds[2];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n\\n vec3 signAxis = sign(bounds[1] - bounds[0]);\\n\\n vec3 realNormal = signAxis * normal;\\n\\n if(dot(realNormal, enable) > 0.0) {\\n vec3 minRange = min(bounds[0], bounds[1]);\\n vec3 maxRange = max(bounds[0], bounds[1]);\\n vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\\n gl_Position = projection * view * model * vec4(nPosition, 1.0);\\n } else {\\n gl_Position = vec4(0,0,0,0);\\n }\\n\\n colorChannel = abs(realNormal);\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 colors[3];\\n\\nvarying vec3 colorChannel;\\n\\nvoid main() {\\n gl_FragColor = colorChannel.x * colors[0] +\\n colorChannel.y * colors[1] +\\n colorChannel.z * colors[2];\\n}\"]);e.bg=function(t){return i(t,u,c,null,[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}])}},4935:function(t,e,r){\"use strict\";t.exports=function(t,e,r,n,o,l){var u=i(t),f=a(t,[{buffer:u,size:3}]),h=s(t);h.attributes.position.location=0;var p=new c(t,h,u,f);return p.update(e,r,n,o,l),p};var i=r(2762),a=r(8116),o=r(4359),s=r(1879).Q,l=window||n.global||{},u=l.__TEXT_CACHE||{};function c(t,e,r,n){this.gl=t,this.shader=e,this.buffer=r,this.vao=n,this.tickOffset=this.tickCount=this.labelOffset=this.labelCount=null}l.__TEXT_CACHE={};var f=c.prototype,h=[0,0];f.bind=function(t,e,r,n){this.vao.bind(),this.shader.bind();var i=this.shader.uniforms;i.model=t,i.view=e,i.projection=r,i.pixelScale=n,h[0]=this.gl.drawingBufferWidth,h[1]=this.gl.drawingBufferHeight,this.shader.uniforms.resolution=h},f.unbind=function(){this.vao.unbind()},f.update=function(t,e,r,n,i){var a=[];function s(t,e,r,n,i,s){var l=[r.style,r.weight,r.variant,r.family].join(\"_\"),c=u[l];c||(c=u[l]={});var f=c[e];f||(f=c[e]=function(t,e){try{return o(t,e)}catch(e){return console.warn('error vectorizing text:\"'+t+'\" error:',e),{cells:[],positions:[]}}}(e,{triangles:!0,font:r.family,fontStyle:r.style,fontWeight:r.weight,fontVariant:r.variant,textAlign:\"center\",textBaseline:\"middle\",lineSpacing:i,styletags:s}));for(var h=(n||12)/12,p=f.positions,d=f.cells,v=0,g=d.length;v=0;--m){var x=p[y[m]];a.push(h*x[0],-h*x[1],t)}}for(var l=[0,0,0],c=[0,0,0],f=[0,0,0],h=[0,0,0],p={breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},d=0;d<3;++d){f[d]=a.length/3|0,s(.5*(t[0][d]+t[1][d]),e[d],r[d],12,1.25,p),h[d]=(a.length/3|0)-f[d],l[d]=a.length/3|0;for(var v=0;v=0&&(i=r.length-n-1);var a=Math.pow(10,i),o=Math.round(t*e*a),s=o+\"\";if(s.indexOf(\"e\")>=0)return s;var l=o/a,u=o%a;o<0?(l=0|-Math.ceil(l),u=0|-u):(l=0|Math.floor(l),u|=0);var c=\"\"+l;if(o<0&&(c=\"-\"+c),i){for(var f=\"\"+u;f.length=t[0][i];--o)a.push({x:o*e[i],text:r(e[i],o)});n.push(a)}return n},e.equal=function(t,e){for(var r=0;r<3;++r){if(t[r].length!==e[r].length)return!1;for(var n=0;nr)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function c(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=u(this.gl,this.type,this.length,this.usage,t.data,e):this.length=u(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=u(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?c(t,\"uint16\"):c(t,\"float32\"),this.length=u(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=u(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof t&&void 0!==t)throw new Error(\"gl-buffer: Invalid data type\");if(e>=0)throw new Error(\"gl-buffer: Cannot specify offset when resizing buffer\");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},t.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error(\"gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER\");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error(\"gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW\");var i=t.createBuffer(),a=new s(t,r,i,0,n);return a.update(e),a}},6405:function(t,e,r){\"use strict\";var n=r(2931);t.exports=function(t,e){var r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,u=1/0,c=-1/0,f=1/0,h=-1/0,p=null,d=null,v=[],g=1/0,y=!1,m=\"raw\"===t.coneSizemode,x=0;xo&&(o=n.length(_)),x&&!m){var w=2*n.distance(p,b)/(n.length(d)+n.length(_));w?(g=Math.min(g,w),y=!1):y=!0}y||(p=b,d=_),v.push(_)}var T=[s,u,f],k=[l,c,h];e&&(e[0]=T,e[1]=k),0===o&&(o=1);var A=1/o;isFinite(g)||(g=1),a.vectorScale=g;var M=t.coneSize||(m?1:.5);t.absoluteConeSize&&(M=t.absoluteConeSize*A),a.coneScale=M,x=0;for(var S=0;x=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=c({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return u(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,v=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],v=+t.vertexIntensityBounds[1];else for(var g=0;g0){var v=this.triShader;v.bind(),v.uniforms=u,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?i.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},t.exports=function(t,e,r){var s=r.shaders;1===arguments.length&&(t=(e=t).gl);var l=function(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}(t,s),c=function(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}(t,s),f=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));f.generateMipmap(),f.minFilter=t.LINEAR_MIPMAP_LINEAR,f.magFilter=t.LINEAR;var p=i(t),d=i(t),v=i(t),g=i(t),y=i(t),m=new h(t,f,l,c,p,d,y,v,g,a(t,[{buffer:p,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:v,type:t.FLOAT,size:4},{buffer:g,type:t.FLOAT,size:2},{buffer:d,type:t.FLOAT,size:4}]),r.traceType||\"cone\");return m.update(e),m}},614:function(t,e,r){var n=r(3236),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n// segment + 0 top vertex\\n// segment + 1 perimeter vertex a+1\\n// segment + 2 perimeter vertex a\\n// segment + 3 center base vertex\\n// segment + 4 perimeter vertex a\\n// segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n const float segmentCount = 8.0;\\n\\n float index = rawIndex - floor(rawIndex /\\n (segmentCount * 6.0)) *\\n (segmentCount * 6.0);\\n\\n float segment = floor(0.001 + index/6.0);\\n float segmentIndex = index - (segment*6.0);\\n\\n normal = -normalize(d);\\n\\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n return mix(vec3(0.0), -d, coneOffset);\\n }\\n\\n float nextAngle = (\\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\\n (segmentIndex > 4.99 && segmentIndex < 5.01)\\n ) ? 1.0 : 0.0;\\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n vec3 v2 = v1 - d;\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d)*0.25;\\n vec3 y = v * sin(angle) * length(d)*0.25;\\n vec3 v3 = v2 + x + y;\\n if (segmentIndex < 3.0) {\\n vec3 tx = u * sin(angle);\\n vec3 ty = v * -cos(angle);\\n vec3 tangent = tx + ty;\\n normal = normalize(cross(v3 - v1, tangent));\\n }\\n\\n if (segmentIndex == 0.0) {\\n return mix(d, vec3(0.0), coneOffset);\\n }\\n return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n // Scale the vector magnitude to stay constant with\\n // model & view changes.\\n vec3 normal;\\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * conePosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n // vec4 m_position = model * vec4(conePosition, 1.0);\\n vec4 t_position = view * conePosition;\\n gl_Position = projection * t_position;\\n\\n f_color = color;\\n f_data = conePosition.xyz;\\n f_position = position.xyz;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n // Return up-vector for only-z vector.\\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n// segment + 0 top vertex\\n// segment + 1 perimeter vertex a+1\\n// segment + 2 perimeter vertex a\\n// segment + 3 center base vertex\\n// segment + 4 perimeter vertex a\\n// segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n const float segmentCount = 8.0;\\n\\n float index = rawIndex - floor(rawIndex /\\n (segmentCount * 6.0)) *\\n (segmentCount * 6.0);\\n\\n float segment = floor(0.001 + index/6.0);\\n float segmentIndex = index - (segment*6.0);\\n\\n normal = -normalize(d);\\n\\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n return mix(vec3(0.0), -d, coneOffset);\\n }\\n\\n float nextAngle = (\\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\\n (segmentIndex > 4.99 && segmentIndex < 5.01)\\n ) ? 1.0 : 0.0;\\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n vec3 v2 = v1 - d;\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d)*0.25;\\n vec3 y = v * sin(angle) * length(d)*0.25;\\n vec3 v3 = v2 + x + y;\\n if (segmentIndex < 3.0) {\\n vec3 tx = u * sin(angle);\\n vec3 ty = v * -cos(angle);\\n vec3 tangent = tx + ty;\\n normal = normalize(cross(v3 - v1, tangent));\\n }\\n\\n if (segmentIndex == 0.0) {\\n return mix(d, vec3(0.0), coneOffset);\\n }\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n vec3 normal;\\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n gl_Position = projection * view * conePosition;\\n f_id = id;\\n f_position = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec3\"}]},e.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec3\"}]}},737:function(t){t.exports={0:\"NONE\",1:\"ONE\",2:\"LINE_LOOP\",3:\"LINE_STRIP\",4:\"TRIANGLES\",5:\"TRIANGLE_STRIP\",6:\"TRIANGLE_FAN\",256:\"DEPTH_BUFFER_BIT\",512:\"NEVER\",513:\"LESS\",514:\"EQUAL\",515:\"LEQUAL\",516:\"GREATER\",517:\"NOTEQUAL\",518:\"GEQUAL\",519:\"ALWAYS\",768:\"SRC_COLOR\",769:\"ONE_MINUS_SRC_COLOR\",770:\"SRC_ALPHA\",771:\"ONE_MINUS_SRC_ALPHA\",772:\"DST_ALPHA\",773:\"ONE_MINUS_DST_ALPHA\",774:\"DST_COLOR\",775:\"ONE_MINUS_DST_COLOR\",776:\"SRC_ALPHA_SATURATE\",1024:\"STENCIL_BUFFER_BIT\",1028:\"FRONT\",1029:\"BACK\",1032:\"FRONT_AND_BACK\",1280:\"INVALID_ENUM\",1281:\"INVALID_VALUE\",1282:\"INVALID_OPERATION\",1285:\"OUT_OF_MEMORY\",1286:\"INVALID_FRAMEBUFFER_OPERATION\",2304:\"CW\",2305:\"CCW\",2849:\"LINE_WIDTH\",2884:\"CULL_FACE\",2885:\"CULL_FACE_MODE\",2886:\"FRONT_FACE\",2928:\"DEPTH_RANGE\",2929:\"DEPTH_TEST\",2930:\"DEPTH_WRITEMASK\",2931:\"DEPTH_CLEAR_VALUE\",2932:\"DEPTH_FUNC\",2960:\"STENCIL_TEST\",2961:\"STENCIL_CLEAR_VALUE\",2962:\"STENCIL_FUNC\",2963:\"STENCIL_VALUE_MASK\",2964:\"STENCIL_FAIL\",2965:\"STENCIL_PASS_DEPTH_FAIL\",2966:\"STENCIL_PASS_DEPTH_PASS\",2967:\"STENCIL_REF\",2968:\"STENCIL_WRITEMASK\",2978:\"VIEWPORT\",3024:\"DITHER\",3042:\"BLEND\",3088:\"SCISSOR_BOX\",3089:\"SCISSOR_TEST\",3106:\"COLOR_CLEAR_VALUE\",3107:\"COLOR_WRITEMASK\",3317:\"UNPACK_ALIGNMENT\",3333:\"PACK_ALIGNMENT\",3379:\"MAX_TEXTURE_SIZE\",3386:\"MAX_VIEWPORT_DIMS\",3408:\"SUBPIXEL_BITS\",3410:\"RED_BITS\",3411:\"GREEN_BITS\",3412:\"BLUE_BITS\",3413:\"ALPHA_BITS\",3414:\"DEPTH_BITS\",3415:\"STENCIL_BITS\",3553:\"TEXTURE_2D\",4352:\"DONT_CARE\",4353:\"FASTEST\",4354:\"NICEST\",5120:\"BYTE\",5121:\"UNSIGNED_BYTE\",5122:\"SHORT\",5123:\"UNSIGNED_SHORT\",5124:\"INT\",5125:\"UNSIGNED_INT\",5126:\"FLOAT\",5386:\"INVERT\",5890:\"TEXTURE\",6401:\"STENCIL_INDEX\",6402:\"DEPTH_COMPONENT\",6406:\"ALPHA\",6407:\"RGB\",6408:\"RGBA\",6409:\"LUMINANCE\",6410:\"LUMINANCE_ALPHA\",7680:\"KEEP\",7681:\"REPLACE\",7682:\"INCR\",7683:\"DECR\",7936:\"VENDOR\",7937:\"RENDERER\",7938:\"VERSION\",9728:\"NEAREST\",9729:\"LINEAR\",9984:\"NEAREST_MIPMAP_NEAREST\",9985:\"LINEAR_MIPMAP_NEAREST\",9986:\"NEAREST_MIPMAP_LINEAR\",9987:\"LINEAR_MIPMAP_LINEAR\",10240:\"TEXTURE_MAG_FILTER\",10241:\"TEXTURE_MIN_FILTER\",10242:\"TEXTURE_WRAP_S\",10243:\"TEXTURE_WRAP_T\",10497:\"REPEAT\",10752:\"POLYGON_OFFSET_UNITS\",16384:\"COLOR_BUFFER_BIT\",32769:\"CONSTANT_COLOR\",32770:\"ONE_MINUS_CONSTANT_COLOR\",32771:\"CONSTANT_ALPHA\",32772:\"ONE_MINUS_CONSTANT_ALPHA\",32773:\"BLEND_COLOR\",32774:\"FUNC_ADD\",32777:\"BLEND_EQUATION_RGB\",32778:\"FUNC_SUBTRACT\",32779:\"FUNC_REVERSE_SUBTRACT\",32819:\"UNSIGNED_SHORT_4_4_4_4\",32820:\"UNSIGNED_SHORT_5_5_5_1\",32823:\"POLYGON_OFFSET_FILL\",32824:\"POLYGON_OFFSET_FACTOR\",32854:\"RGBA4\",32855:\"RGB5_A1\",32873:\"TEXTURE_BINDING_2D\",32926:\"SAMPLE_ALPHA_TO_COVERAGE\",32928:\"SAMPLE_COVERAGE\",32936:\"SAMPLE_BUFFERS\",32937:\"SAMPLES\",32938:\"SAMPLE_COVERAGE_VALUE\",32939:\"SAMPLE_COVERAGE_INVERT\",32968:\"BLEND_DST_RGB\",32969:\"BLEND_SRC_RGB\",32970:\"BLEND_DST_ALPHA\",32971:\"BLEND_SRC_ALPHA\",33071:\"CLAMP_TO_EDGE\",33170:\"GENERATE_MIPMAP_HINT\",33189:\"DEPTH_COMPONENT16\",33306:\"DEPTH_STENCIL_ATTACHMENT\",33635:\"UNSIGNED_SHORT_5_6_5\",33648:\"MIRRORED_REPEAT\",33901:\"ALIASED_POINT_SIZE_RANGE\",33902:\"ALIASED_LINE_WIDTH_RANGE\",33984:\"TEXTURE0\",33985:\"TEXTURE1\",33986:\"TEXTURE2\",33987:\"TEXTURE3\",33988:\"TEXTURE4\",33989:\"TEXTURE5\",33990:\"TEXTURE6\",33991:\"TEXTURE7\",33992:\"TEXTURE8\",33993:\"TEXTURE9\",33994:\"TEXTURE10\",33995:\"TEXTURE11\",33996:\"TEXTURE12\",33997:\"TEXTURE13\",33998:\"TEXTURE14\",33999:\"TEXTURE15\",34e3:\"TEXTURE16\",34001:\"TEXTURE17\",34002:\"TEXTURE18\",34003:\"TEXTURE19\",34004:\"TEXTURE20\",34005:\"TEXTURE21\",34006:\"TEXTURE22\",34007:\"TEXTURE23\",34008:\"TEXTURE24\",34009:\"TEXTURE25\",34010:\"TEXTURE26\",34011:\"TEXTURE27\",34012:\"TEXTURE28\",34013:\"TEXTURE29\",34014:\"TEXTURE30\",34015:\"TEXTURE31\",34016:\"ACTIVE_TEXTURE\",34024:\"MAX_RENDERBUFFER_SIZE\",34041:\"DEPTH_STENCIL\",34055:\"INCR_WRAP\",34056:\"DECR_WRAP\",34067:\"TEXTURE_CUBE_MAP\",34068:\"TEXTURE_BINDING_CUBE_MAP\",34069:\"TEXTURE_CUBE_MAP_POSITIVE_X\",34070:\"TEXTURE_CUBE_MAP_NEGATIVE_X\",34071:\"TEXTURE_CUBE_MAP_POSITIVE_Y\",34072:\"TEXTURE_CUBE_MAP_NEGATIVE_Y\",34073:\"TEXTURE_CUBE_MAP_POSITIVE_Z\",34074:\"TEXTURE_CUBE_MAP_NEGATIVE_Z\",34076:\"MAX_CUBE_MAP_TEXTURE_SIZE\",34338:\"VERTEX_ATTRIB_ARRAY_ENABLED\",34339:\"VERTEX_ATTRIB_ARRAY_SIZE\",34340:\"VERTEX_ATTRIB_ARRAY_STRIDE\",34341:\"VERTEX_ATTRIB_ARRAY_TYPE\",34342:\"CURRENT_VERTEX_ATTRIB\",34373:\"VERTEX_ATTRIB_ARRAY_POINTER\",34466:\"NUM_COMPRESSED_TEXTURE_FORMATS\",34467:\"COMPRESSED_TEXTURE_FORMATS\",34660:\"BUFFER_SIZE\",34661:\"BUFFER_USAGE\",34816:\"STENCIL_BACK_FUNC\",34817:\"STENCIL_BACK_FAIL\",34818:\"STENCIL_BACK_PASS_DEPTH_FAIL\",34819:\"STENCIL_BACK_PASS_DEPTH_PASS\",34877:\"BLEND_EQUATION_ALPHA\",34921:\"MAX_VERTEX_ATTRIBS\",34922:\"VERTEX_ATTRIB_ARRAY_NORMALIZED\",34930:\"MAX_TEXTURE_IMAGE_UNITS\",34962:\"ARRAY_BUFFER\",34963:\"ELEMENT_ARRAY_BUFFER\",34964:\"ARRAY_BUFFER_BINDING\",34965:\"ELEMENT_ARRAY_BUFFER_BINDING\",34975:\"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING\",35040:\"STREAM_DRAW\",35044:\"STATIC_DRAW\",35048:\"DYNAMIC_DRAW\",35632:\"FRAGMENT_SHADER\",35633:\"VERTEX_SHADER\",35660:\"MAX_VERTEX_TEXTURE_IMAGE_UNITS\",35661:\"MAX_COMBINED_TEXTURE_IMAGE_UNITS\",35663:\"SHADER_TYPE\",35664:\"FLOAT_VEC2\",35665:\"FLOAT_VEC3\",35666:\"FLOAT_VEC4\",35667:\"INT_VEC2\",35668:\"INT_VEC3\",35669:\"INT_VEC4\",35670:\"BOOL\",35671:\"BOOL_VEC2\",35672:\"BOOL_VEC3\",35673:\"BOOL_VEC4\",35674:\"FLOAT_MAT2\",35675:\"FLOAT_MAT3\",35676:\"FLOAT_MAT4\",35678:\"SAMPLER_2D\",35680:\"SAMPLER_CUBE\",35712:\"DELETE_STATUS\",35713:\"COMPILE_STATUS\",35714:\"LINK_STATUS\",35715:\"VALIDATE_STATUS\",35716:\"INFO_LOG_LENGTH\",35717:\"ATTACHED_SHADERS\",35718:\"ACTIVE_UNIFORMS\",35719:\"ACTIVE_UNIFORM_MAX_LENGTH\",35720:\"SHADER_SOURCE_LENGTH\",35721:\"ACTIVE_ATTRIBUTES\",35722:\"ACTIVE_ATTRIBUTE_MAX_LENGTH\",35724:\"SHADING_LANGUAGE_VERSION\",35725:\"CURRENT_PROGRAM\",36003:\"STENCIL_BACK_REF\",36004:\"STENCIL_BACK_VALUE_MASK\",36005:\"STENCIL_BACK_WRITEMASK\",36006:\"FRAMEBUFFER_BINDING\",36007:\"RENDERBUFFER_BINDING\",36048:\"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE\",36049:\"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME\",36050:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL\",36051:\"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE\",36053:\"FRAMEBUFFER_COMPLETE\",36054:\"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\",36055:\"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\",36057:\"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\",36061:\"FRAMEBUFFER_UNSUPPORTED\",36064:\"COLOR_ATTACHMENT0\",36096:\"DEPTH_ATTACHMENT\",36128:\"STENCIL_ATTACHMENT\",36160:\"FRAMEBUFFER\",36161:\"RENDERBUFFER\",36162:\"RENDERBUFFER_WIDTH\",36163:\"RENDERBUFFER_HEIGHT\",36164:\"RENDERBUFFER_INTERNAL_FORMAT\",36168:\"STENCIL_INDEX8\",36176:\"RENDERBUFFER_RED_SIZE\",36177:\"RENDERBUFFER_GREEN_SIZE\",36178:\"RENDERBUFFER_BLUE_SIZE\",36179:\"RENDERBUFFER_ALPHA_SIZE\",36180:\"RENDERBUFFER_DEPTH_SIZE\",36181:\"RENDERBUFFER_STENCIL_SIZE\",36194:\"RGB565\",36336:\"LOW_FLOAT\",36337:\"MEDIUM_FLOAT\",36338:\"HIGH_FLOAT\",36339:\"LOW_INT\",36340:\"MEDIUM_INT\",36341:\"HIGH_INT\",36346:\"SHADER_COMPILER\",36347:\"MAX_VERTEX_UNIFORM_VECTORS\",36348:\"MAX_VARYING_VECTORS\",36349:\"MAX_FRAGMENT_UNIFORM_VECTORS\",37440:\"UNPACK_FLIP_Y_WEBGL\",37441:\"UNPACK_PREMULTIPLY_ALPHA_WEBGL\",37442:\"CONTEXT_LOST_WEBGL\",37443:\"UNPACK_COLORSPACE_CONVERSION_WEBGL\",37444:\"BROWSER_DEFAULT_WEBGL\"}},5171:function(t,e,r){var 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|| \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float opacity;\\nvarying vec3 fragPosition;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n if (\\n outOfRange(clipBounds[0], clipBounds[1], fragPosition) ||\\n fragColor.a * opacity == 0.\\n ) discard;\\n\\n gl_FragColor = opacity * fragColor;\\n}\"]);t.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"offset\",type:\"vec3\"}])}},2260:function(t,e,r){\"use strict\";var n=r(7766);t.exports=function(t,e,r,n){i||(i=t.FRAMEBUFFER_UNSUPPORTED,a=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,o=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,s=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var u=t.getExtension(\"WEBGL_draw_buffers\");if(!l&&u&&function(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);l=new Array(r+1);for(var n=0;n<=r;++n){for(var i=new Array(r),a=0;ac||r<0||r>c)throw new Error(\"gl-fbo: Parameters are too large for FBO\");var f=1;if(\"color\"in(n=n||{})){if((f=Math.max(0|n.color,0))<0)throw new Error(\"gl-fbo: Must specify a nonnegative number of colors\");if(f>1){if(!u)throw new Error(\"gl-fbo: Multiple draw buffer extension not supported\");if(f>t.getParameter(u.MAX_COLOR_ATTACHMENTS_WEBGL))throw new Error(\"gl-fbo: Context does not support \"+f+\" draw buffers\")}}var h=t.UNSIGNED_BYTE,p=t.getExtension(\"OES_texture_float\");if(n.float&&f>0){if(!p)throw new Error(\"gl-fbo: Context does not support floating point textures\");h=t.FLOAT}else 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s.magFilter=t.NEAREST,s.minFilter=t.NEAREST,s.mipSamples=1,s.bind(),t.framebufferTexture2D(t.FRAMEBUFFER,o,t.TEXTURE_2D,s.handle,0),s}function p(t,e,r,n,i){var a=t.createRenderbuffer();return t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function d(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var d=0;d1&&s.drawBuffersWEBGL(l[o]);var m=r.getExtension(\"WEBGL_depth_texture\");m?d?t.depth=h(r,i,a,m.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):v&&(t.depth=h(r,i,a,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):v&&d?t._depth_rb=p(r,i,a,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):v?t._depth_rb=p(r,i,a,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,i,a,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){for(t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null),y=0;yi||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=u(n),o=0;o>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var v=i.attributes;return this.positionBuffer.bind(),v.position.pointer(),this.weightBuffer.bind(),v.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),v.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var u,c,f,p,d=t.colorLevels||[0],v=t.colorValues||[0,0,0,1],g=d.length,y=this.bounds;l?(u=y[0]=r[0],c=y[1]=o[0],f=y[2]=r[r.length-1],p=y[3]=o[o.length-1]):(u=y[0]=r[0]+(r[1]-r[0])/2,c=y[1]=o[0]+(o[1]-o[0])/2,f=y[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=y[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var m=1/(f-u),x=1/(p-c),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),A=a.mallocUint8(2*w),M=a.mallocUint32(w),S=0,E=l?b-1:b,L=l?_-1:_,C=0;C max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float dashScale;\\nuniform float opacity;\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n if (\\n outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n fragColor.a * opacity == 0.\\n ) discard;\\n\\n float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n if(dashWeight < 0.5) {\\n discard;\\n }\\n gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX 1.70141184e38\\n#define FLOAT_MIN 1.17549435e-38\\n\\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\\nvec4 packFloat(float v) {\\n float av = abs(v);\\n\\n //Handle special cases\\n if(av < FLOAT_MIN) {\\n return vec4(0.0, 0.0, 0.0, 0.0);\\n } else if(v > FLOAT_MAX) {\\n return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n } else if(v < -FLOAT_MAX) {\\n return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n }\\n\\n vec4 c = vec4(0,0,0,0);\\n\\n //Compute exponent and mantissa\\n float e = floor(log2(av));\\n float m = av * pow(2.0, -e) - 1.0;\\n\\n //Unpack mantissa\\n c[1] = floor(128.0 * m);\\n m -= c[1] / 128.0;\\n c[2] = floor(32768.0 * m);\\n m -= c[2] / 32768.0;\\n c[3] = floor(8388608.0 * m);\\n\\n //Unpack exponent\\n float ebias = e + 127.0;\\n c[0] = floor(ebias / 2.0);\\n ebias -= c[0] * 2.0;\\n c[1] += floor(ebias) * 128.0;\\n\\n //Unpack sign bit\\n c[0] += 128.0 * step(0.0, -v);\\n\\n //Scale back to range\\n return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];e.createShader=function(t){return i(t,a,o,null,l)},e.createPickShader=function(t){return i(t,a,s,null,l)}},5714:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),c=u(new Array(1024),[256,1,4]),p=0;p<1024;++p)c.data[p]=255;var d=a(e,c);d.wrap=e.REPEAT;var v=new y(e,r,o,s,l,d);return v.update(t),v};var n=r(2762),i=r(8116),a=r(7766),o=new Uint8Array(4),s=new Float32Array(o.buffer),l=r(2478),u=r(9618),c=r(7319),f=c.createShader,h=c.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function v(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function g(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function y(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var m=y.prototype;m.isTransparent=function(){return this.hasAlpha},m.isOpaque=function(){return!this.hasAlpha},m.pickSlots=1,m.setPickBase=function(t){this.pickId=t},m.drawTransparent=m.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:v(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:v(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},m.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var i=[],a=[],o=[],s=0,c=0,f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],h=t.position||t.positions;if(h){var p=t.color||t.colors||[0,0,0,1],v=t.lineWidth||1,g=!1;t:for(e=1;e0){for(var w=0;w<24;++w)i.push(i[i.length-12]);c+=2,g=!0}continue t}f[0][r]=Math.min(f[0][r],b[r],_[r]),f[1][r]=Math.max(f[1][r],b[r],_[r])}Array.isArray(p[0])?(y=p.length>e-1?p[e-1]:p.length>0?p[p.length-1]:[0,0,0,1],m=p.length>e?p[e]:p.length>0?p[p.length-1]:[0,0,0,1]):y=m=p,3===y.length&&(y=[y[0],y[1],y[2],1]),3===m.length&&(m=[m[0],m[1],m[2],1]),!this.hasAlpha&&y[3]<1&&(this.hasAlpha=!0),x=Array.isArray(v)?v.length>e-1?v[e-1]:v.length>0?v[v.length-1]:[0,0,0,1]:v;var T=s;if(s+=d(b,_),g){for(r=0;r<2;++r)i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,y[0],y[1],y[2],y[3]);c+=2,g=!1}i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,y[0],y[1],y[2],y[3],b[0],b[1],b[2],_[0],_[1],_[2],T,-x,y[0],y[1],y[2],y[3],_[0],_[1],_[2],b[0],b[1],b[2],s,-x,m[0],m[1],m[2],m[3],_[0],_[1],_[2],b[0],b[1],b[2],s,x,m[0],m[1],m[2],m[3]),c+=4}}if(this.buffer.update(i),a.push(s),o.push(h[h.length-1].slice()),this.bounds=f,this.vertexCount=c,this.points=o,this.arcLength=a,\"dashes\"in t){var k=t.dashes.slice();for(k.unshift(0),e=1;e1.0001)return null;y+=g[f]}return Math.abs(y-1)>.001?null:[h,s(t,g),g]}},840:function(t,e,r){var n=r(3236),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n , view\\n , projection\\n , inverseModel;\\nuniform vec3 eyePosition\\n , lightPosition;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n gl_Position = project(position);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * vec4(position , 1.0);\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n f_color = color;\\n f_data = position;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n //Half angle vector\\n vec3 H = normalize(lightDirection + viewDirection);\\n\\n //Geometric term\\n float NdotH = max(dot(surfaceNormal, H), 0.0);\\n float VdotH = max(dot(viewDirection, H), 0.000001);\\n float LdotH = max(dot(lightDirection, H), 0.000001);\\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n float G = min(1.0, min(G1, G2));\\n \\n //Distribution term\\n float D = beckmannDistribution(NdotH, roughness);\\n\\n //Fresnel term\\n float F = pow(1.0 - VdotN, fresnel);\\n\\n //Multiply terms and done\\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n , fresnel\\n , kambient\\n , kdiffuse\\n , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n , f_lightDirection\\n , f_eyeDirection\\n , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (f_color.a == 0.0 ||\\n outOfRange(clipBounds[0], clipBounds[1], f_data)\\n ) discard;\\n\\n vec3 N = normalize(f_normal);\\n vec3 L = normalize(f_lightDirection);\\n vec3 V = normalize(f_eyeDirection);\\n\\n if(gl_FrontFacing) {\\n N = -N;\\n }\\n\\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\\n\\n gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n f_color = color;\\n f_data = position;\\n f_uv = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n } else {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n }\\n gl_PointSize = pointSize;\\n f_color = color;\\n f_uv = uv;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n if(dot(pointR, pointR) > 0.25) {\\n discard;\\n }\\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n f_id = id;\\n f_position = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute float pointSize;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n } else {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n gl_PointSize = pointSize;\\n }\\n f_id = id;\\n f_position = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},e.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},e.pointShader={vertex:l,fragment:u,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},e.pickShader={vertex:c,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},e.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},e.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},7201:function(t,e,r){\"use strict\";var n=r(9405),i=r(2762),a=r(8116),o=r(7766),s=r(8406),l=r(6760),u=r(7608),c=r(9618),f=r(6729),h=r(7765),p=r(1888),d=r(840),v=r(7626),g=d.meshShader,y=d.wireShader,m=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,T,k,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=c,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=u,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=g,this.edgeUVs=y,this.edgeIds=v,this.edgeVAO=m,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function A(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;rt&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function M(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function S(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function E(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function L(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()),this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};(s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;ai[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t],r.uniforms.angle=y[t],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t]&&T&&(c[1^t]-=M*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),c[1^t]=M*s[2+(1^t)]-1,d[t+2]&&(c[1^t]+=M*p*v[t+2],ki[k]&&(r.uniforms.dataAxis=u,r.uniforms.screenOffset=c,r.uniforms.color=g[t+2],r.uniforms.angle=y[t+2],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),m[t+2]&&T&&(c[1^t]+=M*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=c,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),v.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,u=r.pixelRatio;if(this.titleCount){for(var c=0;c<2;++c)e[c]=2*(o[c]*u-a[c])/(a[2+c]-a[c])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),v.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,u=.5*(n[o+2]+n[o]),c=n[o+2]-n[o],f=a[o],v=a[o+2]-f,g=i[o],y=i[o+2]-g;p[o]=2*l/c*v/y,h[o]=2*(s-u)/c*v/y}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),v.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,u=t.bounds;for(o=0;o<2;++o){var c=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e=0){var v=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(v,e[1],v,e[3],p[d],h[d]):o.drawLine(e[0],v,e[2],v,p[d],h[d])}}for(d=0;d=0;--t)this.objects[t].dispose();for(this.objects.length=0,t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},u.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},u.removeObject=function(t){for(var e=this.objects,r=0;rMath.abs(e))u.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-u.lastT())/20;u.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=r(3025),i=r(6296),a=r(351),o=r(8512),s=r(24),l=r(7520)},799:function(t,e,r){var n=r(3236),i=r(9405),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n uv = position;\\n gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);t.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},4100:function(t,e,r){\"use strict\";var n=r(4437),i=r(3837),a=r(5445),o=r(4449),s=r(3589),l=r(2260),u=r(7169),c=r(351),f=r(4772),h=r(4040),p=r(799),d=r(9216)({tablet:!0,featureDetect:!0});function v(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function g(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}return e>0?(r=Math.round(Math.pow(10,e)),Math.ceil(t/r)*r):Math.ceil(t)}function y(t){return\"boolean\"!=typeof t||t}t.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;e||(e=document.createElement(\"canvas\"),t.container?t.container.appendChild(e):document.body.appendChild(e));var r=t.gl;if(r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d})),!r)throw new Error(\"webgl not supported\");var m=t.bounds||[[-10,-10,-10],[10,10,10]],x=new v,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:w},k=t.axes||{},A=i(r,k);A.enable=!k.disable;var M=t.spikes||{},S=o(r,M),E=[],L=[],C=[],P=[],O=!0,I=!0,z={view:null,projection:new Array(16),model:new Array(16),_ortho:!1},D=(I=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),R=t.cameraObject||n(e,T),F={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:R,axes:A,axesPixels:null,spikes:S,bounds:m,objects:E,shape:D,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:y(t.autoResize),autoBounds:y(t.autoBounds),autoScale:!!t.autoScale,autoCenter:y(t.autoCenter),clipToBounds:y(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:z,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,I=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},B=[r.drawingBufferWidth/F.pixelRatio|0,r.drawingBufferHeight/F.pixelRatio|0];function N(){if(!F._stopped&&F.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*F.pixelRatio),a=0|Math.ceil(n*F.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",O=!0}}}function j(){for(var t=E.length,e=P.length,n=0;n0&&0===C[e-1];)C.pop(),P.pop().dispose()}function U(){if(F.contextLost)return!0;r.isContextLost()&&(F.contextLost=!0,F.mouseListener.enabled=!1,F.selection.object=null,F.oncontextloss&&F.oncontextloss())}F.autoResize&&N(),window.addEventListener(\"resize\",N),F.update=function(t){F._stopped||(t=t||{},O=!0,I=!0)},F.add=function(t){F._stopped||(t.axes=A,E.push(t),L.push(-1),O=!0,I=!0,j())},F.remove=function(t){if(!F._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),L.pop(),O=!0,I=!0,j())}},F.dispose=function(){if(!F._stopped&&(F._stopped=!0,window.removeEventListener(\"resize\",N),e.removeEventListener(\"webglcontextlost\",U),F.mouseListener.enabled=!1,!F.contextLost)){A.dispose(),S.dispose();for(var t=0;tx.distance)continue;for(var u=0;u 1.0) {\\n discard;\\n }\\n baseColor = mix(borderColor, color, step(radius, centerFraction));\\n gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n }\\n}\\n\"]),e.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n vec3 hgPosition = matrix * vec3(position, 1);\\n gl_Position = vec4(hgPosition.xy, 0, hgPosition.z);\\n gl_PointSize = pointSize;\\n\\n vec4 id = pickId + pickOffset;\\n id.y += floor(id.x / 256.0);\\n id.x -= floor(id.x / 256.0) * 256.0;\\n\\n id.z += floor(id.y / 256.0);\\n id.y -= floor(id.y / 256.0) * 256.0;\\n\\n id.w += floor(id.z / 256.0);\\n id.z -= floor(id.z / 256.0) * 256.0;\\n\\n fragId = id;\\n}\\n\"]),e.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n if(radius > 1.0) {\\n discard;\\n }\\n gl_FragColor = fragId / 255.0;\\n}\\n\"])},4696:function(t,e,r){\"use strict\";var n=r(9405),i=r(2762),a=r(1888),o=r(6640);function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}t.exports=function(t,e){var r=t.gl,a=new s(t,i(r),i(r),n(r,o.pointVertex,o.pointFragment),n(r,o.pickVertex,o.pickFragment));return a.update(e),t.addObject(a),a};var l,u,c=s.prototype;c.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},c.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),u=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e>>1;for(r=0;r=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),c=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=c<5,r.uniforms.pointSize=c,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(u[0]=255&t,u[1]=t>>8&255,u[2]=t>>16&255,u[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=u,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),c.draw=c.unifiedDraw,c.drawPick=c.unifiedDraw,c.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},783:function(t){t.exports=function(t,e,r,n){var i,a,o,s,l,u=e[0],c=e[1],f=e[2],h=e[3],p=r[0],d=r[1],v=r[2],g=r[3];return(a=u*p+c*d+f*v+h*g)<0&&(a=-a,p=-p,d=-d,v=-v,g=-g),1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n),t[0]=s*u+l*p,t[1]=s*c+l*d,t[2]=s*f+l*v,t[3]=s*h+l*g,t}},5964:function(t){\"use strict\";t.exports=function(t){return t||0===t?t.toString():\"\"}},9366:function(t,e,r){\"use strict\";var n=r(4359);t.exports=function(t,e,r){var a=[e.style,e.weight,e.variant,e.family].join(\"_\"),o=i[a];if(o||(o=i[a]={}),t in o)return o[t];var s={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e.family,fontStyle:e.style,fontWeight:e.weight,fontVariant:e.variant,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},l=n(t,s);s.triangles=!1;var u,c,f=n(t,s);if(r&&1!==r){for(u=0;u max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float scale = 1.0;\\n if(distance(highlightId, id) < 0.0001) {\\n scale = highlightScale;\\n }\\n\\n vec4 worldPosition = model * vec4(position, 1);\\n vec4 viewPosition = view * worldPosition;\\n viewPosition = viewPosition / viewPosition.w;\\n vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n gl_Position = clipPosition;\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = position;\\n }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float scale = pixelRatio;\\n if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n scale *= highlightScale;\\n }\\n\\n vec4 worldPosition = model * vec4(position, 1.0);\\n vec4 viewPosition = view * worldPosition;\\n vec4 clipPosition = projection * viewPosition;\\n clipPosition /= clipPosition.w;\\n\\n gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = position;\\n }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n gl_Position = vec4(0,0,0,0);\\n } else {\\n float lscale = pixelRatio * scale;\\n if(distance(highlightId, id) < 0.0001) {\\n lscale *= highlightScale;\\n }\\n\\n vec4 clipCenter = projection * view * model * vec4(position, 1);\\n vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n gl_Position = clipPosition;\\n interpColor = color;\\n pickId = id;\\n dataCoordinate = dataPosition;\\n }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (\\n outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n interpColor.a * opacity == 0.\\n ) discard;\\n gl_FragColor = interpColor * opacity;\\n}\\n\"]),u=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),c=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:c},h={vertex:o,fragment:l,attributes:c},p={vertex:s,fragment:l,attributes:c},d={vertex:a,fragment:u,attributes:c},v={vertex:o,fragment:u,attributes:c},g={vertex:s,fragment:u,attributes:c};function y(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}e.createPerspective=function(t){return y(t,f)},e.createOrtho=function(t){return y(t,h)},e.createProject=function(t){return y(t,p)},e.createPickPerspective=function(t){return y(t,d)},e.createPickOrtho=function(t){return y(t,v)},e.createPickProject=function(t){return y(t,g)}},8418:function(t,e,r){\"use strict\";var n=r(5219),i=r(2762),a=r(8116),o=r(1888),s=r(6760),l=r(1283),u=r(9366),c=r(5964),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function v(t){return!0===t||t>1?1:t}function g(t,e,r,n,i,a,o,s,l,u,c,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=u,this.pickOrthoShader=c,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}t.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),u=l.createPickOrtho(e),c=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),v=new g(e,r,n,o,f,h,p,d,a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),s,u,c);return v.update(t),v};var y=g.prototype;y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},y.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var m=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],A=[[0,0,0],[0,0,0]];function M(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}var L=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function C(t,e,r,n,i,a,o){var l=r.gl;if((a===r.projectHasAlpha||o)&&function(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,u=r.model||f,c=r.view||f,h=r.projection||f,d=e.axesBounds,v=function(t){for(var e=A,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],m[0]=2/o.drawingBufferWidth,m[1]=2/o.drawingBufferHeight,t.bind(),l.view=c,l.projection=h,l.screenSize=m,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=v,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var g=0;g<3;++g)if(a[g]){l.scale=e.projectScale[g],l.opacity=e.projectOpacity[g];for(var y=T,L=0;L<16;++L)y[L]=0;for(L=0;L<4;++L)y[5*L]=1;y[5*g]=0,i[g]<0?y[12+g]=d[0][g]:y[12+g]=d[1][g],s(y,u,y),l.model=y;var C=(g+1)%3,P=(g+2)%3,O=M(x),I=M(b);O[C]=1,I[P]=1;var z=p(0,0,0,S(_,O)),D=p(0,0,0,S(w,I));if(Math.abs(z[1])>Math.abs(D[1])){var R=z;z=D,D=R,R=O,O=I,I=R;var F=C;C=P,P=F}z[0]<0&&(O[C]=-1),D[1]>0&&(I[P]=-1);var B=0,N=0;for(L=0;L<4;++L)B+=Math.pow(u[4*C+L],2),N+=Math.pow(u[4*P+L],2);O[C]/=Math.sqrt(B),I[P]/=Math.sqrt(N),l.axes[0]=O,l.axes[1]=I,l.fragClipBounds[0]=E(k,v[0],g,-1e8),l.fragClipBounds[1]=E(k,v[1],g,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}(e,r,n,i),a===r.hasAlpha||o){t.bind();var u=t.uniforms;u.model=n.model||f,u.view=n.view||f,u.projection=n.projection||f,m[0]=2/l.drawingBufferWidth,m[1]=2/l.drawingBufferHeight,u.screenSize=m,u.highlightId=r.highlightId,u.highlightScale=r.highlightScale,u.fragClipBounds=L,u.clipBounds=r.axes.bounds,u.opacity=r.opacity,u.pickGroup=r.pickId/255,u.pixelRatio=i,r.vao.bind(),r.vao.draw(l.TRIANGLES,r.vertexCount),r.lineWidth>0&&(l.lineWidth(r.lineWidth*i),r.vao.draw(l.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function P(t,e,r,i){var a;a=Array.isArray(t)?e=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},y.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},y.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,\"projectOpacity\"in t){Array.isArray(t.projectOpacity)?this.projectOpacity=t.projectOpacity.slice():(r=+t.projectOpacity,this.projectOpacity=[r,r,r]);for(var n=0;n<3;++n)this.projectOpacity[n]=v(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=v(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var i,a,s=t.position,l={family:t.font||\"normal\",style:t.fontStyle||\"normal\",weight:t.fontWeight||\"normal\",variant:t.fontVariant||\"normal\"},u=t.alignment||[0,0];if(2===u.length)i=u[0],a=u[1];else for(i=[],a=[],n=0;n0){var I=0,z=x,D=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(y)&&Array.isArray(y[0]);t:for(n=0;n<_;++n){for(m+=1,w=s[n],T=0;T<3;++T){if(isNaN(w[T])||!isFinite(w[T]))continue t;f[T]=Math.max(f[T],w[T]),c[T]=Math.min(c[T],w[T])}k=(N=P(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(U=F?n0?1-M[0][0]:W<0?1+M[1][0]:1,Y*=Y>0?1-M[0][1]:Y<0?1+M[1][1]:1],Z=k.cells||[],K=k.positions||[];for(T=0;T0){var y=r*c;o.drawBox(f-y,h-y,p+y,h+y,a),o.drawBox(f-y,d-y,p+y,d+y,a),o.drawBox(f-y,h-y,f+y,d+y,a),o.drawBox(p-y,h-y,p+y,d+y,a)}}}},s.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},s.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},3589:function(t,e,r){\"use strict\";t.exports=function(t,e){var r=e[0],a=e[1];return new l(t,n(t,r,a,{}),i.mallocUint8(r*a*4))};var n=r(2260),i=r(1888),a=r(9618),o=r(8828).nextPow2;function s(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function l(t,e,r){this.gl=t,this.fbo=e,this.buffer=r,this._readTimeout=null;var n=this;this._readCallback=function(){n.gl&&(e.bind(),t.readPixels(0,0,e.shape[0],e.shape[1],t.RGBA,t.UNSIGNED_BYTE,n.buffer),n._readTimeout=null)}}var u=l.prototype;Object.defineProperty(u,\"shape\",{get:function(){return this.gl?this.fbo.shape.slice():[0,0]},set:function(t){if(this.gl){this.fbo.shape=t;var e=this.fbo.shape[0],r=this.fbo.shape[1];if(r*e*4>this.buffer.length){i.free(this.buffer);for(var n=this.buffer=i.mallocUint8(o(r*e*4)),a=0;ar)for(t=r;te)for(t=e;t=0){for(var T=0|w.type.charAt(w.type.length-1),k=new Array(T),A=0;A=0;)M+=1;_[m]=M}var S=new Array(r.length);function E(){h.program=o.program(p,h._vref,h._fref,b,_);for(var t=0;t=0){if((d=h.charCodeAt(h.length-1)-48)<2||d>4)throw new n(\"\",\"Invalid data type for attribute \"+f+\": \"+h);s(t,e,p[0],i,d,a,f)}else{if(!(h.indexOf(\"mat\")>=0))throw new n(\"\",\"Unknown data type for attribute \"+f+\": \"+h);var d;if((d=h.charCodeAt(h.length-1)-48)<2||d>4)throw new n(\"\",\"Invalid data type for attribute \"+f+\": 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a||(a[s[0]]=[]),a=a[s[0]];for(var l=1;l1)for(var l=0;l 0 U ||b|| > 0.\\n // Assign z = 0, x = -b, y = a:\\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n return normalize(vec3(-v.y, v.x, 0.0));\\n } else {\\n return normalize(vec3(0.0, v.z, -v.y));\\n }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n float segmentCount = 8.0;\\n\\n float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n vec3 u = getOrthogonalVector(d);\\n vec3 v = normalize(cross(u, d));\\n\\n vec3 x = u * cos(angle) * length(d);\\n vec3 y = v * sin(angle) * length(d);\\n vec3 v3 = x + y;\\n\\n normal = normalize(v3);\\n\\n return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n // Scale the vector magnitude to stay constant with\\n // model & view changes.\\n vec3 normal;\\n vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n //Lighting geometry parameters\\n vec4 cameraCoordinate = view * tubePosition;\\n cameraCoordinate.xyz /= cameraCoordinate.w;\\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n // vec4 m_position = model * vec4(tubePosition, 1.0);\\n vec4 t_position = view * tubePosition;\\n gl_Position = projection * t_position;\\n\\n f_color = color;\\n f_data = tubePosition.xyz;\\n f_position = position.xyz;\\n f_uv = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n float NdotH = max(x, 0.0001);\\n float cos2Alpha = NdotH * NdotH;\\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n float roughness2 = roughness * roughness;\\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n vec3 lightDirection,\\n vec3 viewDirection,\\n vec3 surfaceNormal,\\n float roughness,\\n float fresnel) {\\n\\n float VdotN = max(dot(viewDirection, surfaceNormal), 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dataCoordinate;\\n vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n vec4 clipPosition = projection * view * worldPosition;\\n clipPosition.z += zOffset;\\n\\n gl_Position = clipPosition;\\n value = f + objectOffset.z;\\n kill = -1.0;\\n planeCoordinate = uv.zw;\\n\\n vColor = texture2D(colormap, vec2(value, value));\\n\\n //Don't do lighting for contours\\n surfaceNormal = vec3(1,0,0);\\n eyeDirection = vec3(0,1,0);\\n lightDirection = vec3(0,0,1);\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n return ((p > max(a, b)) || \\n (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n return (outOfRange(a.x, b.x, p.x) ||\\n outOfRange(a.y, b.y, p.y) ||\\n outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n float vh = 255.0 * v;\\n float upper = floor(vh);\\n float lower = fract(vh);\\n return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n if ((kill > 0.0) ||\\n (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);e.createShader=function(t){var e=n(t,a,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},e.createPickShader=function(t){var e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},e.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},e.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},9499:function(t,e,r){\"use strict\";t.exports=function(t){var e=t.gl,r=m(e),n=b(e),s=x(e),l=_(e),u=i(e),c=a(e,[{buffer:u,size:4,stride:w,offset:0},{buffer:u,size:3,stride:w,offset:16},{buffer:u,size:3,stride:w,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),v=o(e,1,S,e.RGBA,e.UNSIGNED_BYTE);v.minFilter=e.LINEAR,v.magFilter=e.LINEAR;var g=new E(e,[0,0],[[0,0,0],[0,0,0]],r,n,u,c,v,s,l,f,h,p,d,[0,0,0]),y={levels:[[],[],[]]};for(var T in t)y[T]=t[T];return y.colormap=y.colormap||\"jet\",g.update(y),g};var n=r(8828),i=r(2762),a=r(8116),o=r(7766),s=r(1888),l=r(6729),u=r(5298),c=r(9994),f=r(9618),h=r(3711),p=r(6760),d=r(7608),v=r(2478),g=r(6199),y=r(990),m=y.createShader,x=y.createContourShader,b=y.createPickShader,_=y.createPickContourShader,w=40,T=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],k=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],A=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function M(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=A[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();var S=256;function E(t,e,r,n,i,a,o,l,u,c,h,p,d,v,g){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=g,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=u,this._contourPickShader=c,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new M([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=v,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var L=E.prototype;L.genColormap=function(t,e){var r=!1,n=c([l({colormap:t,nshades:S,format:\"rgba\"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;rt&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return u.divseq(n,255),this.hasAlphaScale=r,n},L.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},L.isOpaque=function(){return!this.isTransparent()},L.pickSlots=1,L.setPickBase=function(t){this.pickId=t};var C=[0,0,0],P={showSurface:!1,showContour:!1,projections:[T.slice(),T.slice(),T.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function O(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||C,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=P.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var u=P.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)u[i][n]=t.clipBounds[i][n];u[0][r]=-1e8,u[1][r]=1e8}return P.showSurface=o,P.showContour=s,P}var I={model:T,view:T,projection:T,inverseModel:T.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},z=T.slice(),D=[1,0,0,0,1,0,0,0,1];function R(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=I;n.model=t.model||T,n.view=t.view||T,n.projection=t.projection||T,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=D,n.vertexColor=this.vertexColor;var s=z;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var u=s[12+i];for(o=0;o<3;++o)u+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=u/l}var c=O(n,this);if(c.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=c.projections[i],this._shader.uniforms.clipBounds=c.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(c.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=A[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var u=r.position;u[0]=u[1]=u[2]=0;for(var c=0;c<2;++c)for(var f=c?a:1-a,h=0;h<2;++h)for(var p=i+c,d=s+h,g=f*(h?l:1-l),y=0;y<3;++y)u[y]+=this._field[y].get(p,d)*g;for(var m=this._pickResult.level,x=0;x<3;++x)if(m[x]=v.le(this.contourLevels[x],u[x]),m[x]<0)this.contourLevels[x].length>0&&(m[x]=0);else if(m[x]Math.abs(_-u[x])&&(m[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],y=0;y<3;++y)r.dataCoordinate[y]=this._field[y].get(r.index[0],r.index[1]);return r},L.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();u.assign(t.lo(1,1).hi(r[0],r[1]),e),u.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),u.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),u.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),u.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},L.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=B(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=B(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=B(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=j(t.contourColor)),\"contourProject\"in t&&(this.contourProject=B(t.contourProject,(function(t){return B(t,Boolean)}))),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=j(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=B(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=B(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0),\"colormap\"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var u=l[o];for(y=0;y<2;++y)if(u.shape[y]!==a[y])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],u)}}else if(t.ticks){var c=t.ticks;if(!Array.isArray(c)||2!==c.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=c[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var v=[0,0];v[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],v,0)}this._field[0].set(0,0,0);for(var y=0;y0){for(var xt=0;xt<5;++xt)$.pop();U-=1}continue t}$.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[Q]=et,this._contourCounts[Q]=rt}var bt=s.mallocFloat($.length);for(o=0;o<$.length;++o)bt[o]=$[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},L.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},L.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,u=(o+2)%3,c=this._field[o],f=this._field[l],p=this._field[u],d=h(c,r[o]),v=d.cells,g=d.positions;for(this._dynamicOffsets[o]=n,e=0;es||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=d(o,e.stride.slice()),u=0;\"float32\"===r?u=t.FLOAT:\"float64\"===r?(u=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?u=t.UNSIGNED_BYTE:(u=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var f,p,g=0;if(2===o.length)g=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])g=t.ALPHA;else if(2===o[2])g=t.LUMINANCE_ALPHA;else if(3===o[2])g=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");g=t.RGBA}}u!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(u=t.UNSIGNED_BYTE,l=!1);var y=e.size;if(l)f=0===e.offset&&e.data.length===y?e.data:e.data.subarray(e.offset,e.offset+y);else{var m=[o[2],o[2]*o[0],1];p=a.malloc(y,r);var x=n(p,o,m,0);\"float32\"!==r&&\"float64\"!==r||u!==t.UNSIGNED_BYTE?i.assign(x,e):c(x,e),f=p.subarray(0,y)}var b=v(t);return t.texImage2D(t.TEXTURE_2D,0,g,o[0],o[1],0,g,u,f),l||a.free(p),new h(t,b,o[0],o[1],g,u)}(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function u(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var c=function(t,e){i.muls(t,e,255)};function f(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function h(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var p=h.prototype;function d(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function v(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function g(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=v(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new h(t,o,e,r,n,i)}Object.defineProperties(p,{minFilter:{get:function(){return this._minFilter},set:function(t){this.bind();var e=this.gl;if(this.type===e.FLOAT&&o.indexOf(t)>=0&&(e.getExtension(\"OES_texture_float_linear\")||(t=e.NEAREST)),s.indexOf(t)<0)throw new Error(\"gl-texture2d: Unknown filter mode \"+t);return 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6:c.push([t-.5-.25*(-n-r+a+i)/(n-r+i-a),e-.5-.25*(-i-r+a+n)/(i-r+n-a)]);break;case 7:c.push([t-.75-.25*(a+i-2*h)/(i-a),e-.75-.25*(a+n-2*h)/(n-a)]);break;case 8:c.push([t-.75-.25*(-a-i+2*h)/(a-i),e-.75-.25*(-a-n+2*h)/(a-n)]);break;case 9:c.push([t-.5-.25*(n+r+-a-i)/(r-n+a-i),e-.5-.25*(i+r+-a-n)/(r-i+a-n)]);break;case 10:c.push([t-.5-.5*(-n-r-a-i+4*h)/(n-r+a-i),e-.5]);break;case 11:c.push([t-.25-.25*(-a-i+2*h)/(a-i),e-.75-.25*(i+r-2*h)/(r-i)]);break;case 12:c.push([t-.5,e-.5-.5*(-i-r-a-n+4*h)/(i-r+a-n)]);break;case 13:c.push([t-.75-.25*(n+r-2*h)/(r-n),e-.25-.25*(-a-n+2*h)/(a-n)]);break;case 14:c.push([t-.25-.25*(-n-r+2*h)/(n-r),e-.25-.25*(-i-r+2*h)/(i-r)])}},cell:function(t,e,r,n,i,a,o,s,l){i?s.push([t,e]):s.push([e,t])}});return function(t,e){var r=[],i=[];return n(t,r,i,e),{positions:r,cells:i}}}},o={}},529:function(t,e,r){\"use strict\";t.exports=function t(e,r,n){var 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Array(16);for(var u=0;u<16;++u)this.computedMatrix[u]=.5;this.recalcMatrix(0)}var p=h.prototype;p.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-1/0,e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},p.getDistanceLimits=function(t){var e=this.radius.bounds[0];return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},p.recalcMatrix=function(t){this.center.curve(t),this.up.curve(t),this.right.curve(t),this.radius.curve(t),this.angle.curve(t);for(var e=this.computedUp,r=this.computedRight,n=0,i=0,a=0;a<3;++a)i+=e[a]*r[a],n+=e[a]*e[a];var l=Math.sqrt(n),c=0;for(a=0;a<3;++a)r[a]-=e[a]*i/n,c+=r[a]*r[a],e[a]/=l;var f=Math.sqrt(c);for(a=0;a<3;++a)r[a]/=f;var h=this.computedToward;o(h,e,r),s(h,h);var p=Math.exp(this.computedRadius[0]),d=this.computedAngle[0],v=this.computedAngle[1],g=Math.cos(d),y=Math.sin(d),m=Math.cos(v),x=Math.sin(v),b=this.computedCenter,_=g*m,w=y*m,T=x,k=-g*x,A=-y*x,M=m,S=this.computedEye,E=this.computedMatrix;for(a=0;a<3;++a){var L=_*r[a]+w*h[a]+T*e[a];E[4*a+1]=k*r[a]+A*h[a]+M*e[a],E[4*a+2]=L,E[4*a+3]=0}var C=E[1],P=E[5],O=E[9],I=E[2],z=E[6],D=E[10],R=P*D-O*z,F=O*I-C*D,B=C*z-P*I,N=u(R,F,B);for(R/=N,F/=N,B/=N,E[0]=R,E[4]=F,E[8]=B,a=0;a<3;++a)S[a]=b[a]+E[2+4*a]*p;for(a=0;a<3;++a){c=0;for(var j=0;j<3;++j)c+=E[a+4*j]*S[j];E[12+a]=-c}E[15]=1},p.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;n<16;++n)e[n]=r[n];return e}return r};var d=[0,0,0];p.rotate=function(t,e,r,n){if(this.angle.move(t,e,r),n){this.recalcMatrix(t);var i=this.computedMatrix;d[0]=i[2],d[1]=i[6],d[2]=i[10];for(var o=this.computedUp,s=this.computedRight,l=this.computedToward,u=0;u<3;++u)i[4*u]=o[u],i[4*u+1]=s[u],i[4*u+2]=l[u];for(a(i,i,n,d),u=0;u<3;++u)o[u]=i[4*u],s[u]=i[4*u+1];this.up.set(t,o[0],o[1],o[2]),this.right.set(t,s[0],s[1],s[2])}},p.pan=function(t,e,r,n){e=e||0,r=r||0,n=n||0,this.recalcMatrix(t);var i=this.computedMatrix,a=(Math.exp(this.computedRadius[0]),i[1]),o=i[5],s=i[9],l=u(a,o,s);a/=l,o/=l,s/=l;var c=i[0],f=i[4],h=i[8],p=c*a+f*o+h*s,d=u(c-=a*p,f-=o*p,h-=s*p),v=(c/=d)*e+a*r,g=(f/=d)*e+o*r,y=(h/=d)*e+s*r;this.center.move(t,v,g,y);var m=Math.exp(this.computedRadius[0]);m=Math.max(1e-4,m+n),this.radius.set(t,Math.log(m))},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e,r,n){var a=1;\"number\"==typeof r&&(a=0|r),(a<0||a>3)&&(a=1);var o=(a+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var s=e[a],l=e[a+4],f=e[a+8];if(n){var h=Math.abs(s),p=Math.abs(l),d=Math.abs(f),v=Math.max(h,p,d);h===v?(s=s<0?-1:1,l=f=0):d===v?(f=f<0?-1:1,s=l=0):(l=l<0?-1:1,s=f=0)}else{var g=u(s,l,f);s/=g,l/=g,f/=g}var y,m,x=e[o],b=e[o+4],_=e[o+8],w=x*s+b*l+_*f,T=u(x-=s*w,b-=l*w,_-=f*w),k=l*(_/=T)-f*(b/=T),A=f*(x/=T)-s*_,M=s*b-l*x,S=u(k,A,M);if(k/=S,A/=S,M/=S,this.center.jump(t,H,G,W),this.radius.idle(t),this.up.jump(t,s,l,f),this.right.jump(t,x,b,_),2===a){var E=e[1],L=e[5],C=e[9],P=E*x+L*b+C*_,O=E*k+L*A+C*M;y=R<0?-Math.PI/2:Math.PI/2,m=Math.atan2(O,P)}else{var I=e[2],z=e[6],D=e[10],R=I*s+z*l+D*f,F=I*x+z*b+D*_,B=I*k+z*A+D*M;y=Math.asin(c(R)),m=Math.atan2(B,F)}this.angle.jump(t,m,y),this.recalcMatrix(t);var N=e[2],j=e[6],U=e[10],V=this.computedMatrix;i(V,e);var q=V[15],H=V[12]/q,G=V[13]/q,W=V[14]/q,Y=Math.exp(this.computedRadius[0]);this.center.jump(t,H-N*Y,G-j*Y,W-U*Y)},p.lastT=function(){return 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this._warningHistory[t.message]||(this._warningHistory[t.message]=!0,\"undefined\"!=typeof console&&console.warn(t.message)),this._defaultValue}};var hn=function(t,e){this.kind=t,this._styleExpression=e,this.isStateDependent=\"constant\"!==t&&!Xe(e.expression)};hn.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)},hn.prototype.evaluate=function(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)};var pn=function(t,e,r,n){this.kind=t,this.zoomStops=r,this._styleExpression=e,this.isStateDependent=\"camera\"!==t&&!Xe(e.expression),this.interpolationType=n};function dn(t,e){if(\"error\"===(t=fn(t,e)).result)return t;var r=t.value.expression,n=Ye(r);if(!n&&!Kr(e))return Zr([new qt(\"\",\"data expressions not supported\")]);var i=Ze(r,[\"zoom\"]);if(!i&&!Jr(e))return Zr([new qt(\"\",\"zoom expressions not supported\")]);var a=gn(r);if(!a&&!i)return Zr([new qt(\"\",'\"zoom\" expression may only be 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e=1;e\"===r||\"<=\"===r||\">=\"===r?Ln(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(En))):\"all\"===r?[\"all\"].concat(t.slice(1).map(En)):\"none\"===r?[\"all\"].concat(t.slice(1).map(En).map(On)):\"in\"===r?Cn(t[1],t.slice(2)):\"!in\"===r?On(Cn(t[1],t.slice(2))):\"has\"===r?Pn(t[1]):\"!has\"===r?On(Pn(t[1])):\"within\"!==r||t}function Ln(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function Cn(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some((function(t){return typeof t!=typeof e[0]}))?[\"filter-in-large\",t,[\"literal\",e.sort(Mn)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function Pn(t){switch(t){case\"$type\":return!0;case\"$id\":return[\"filter-has-id\"];default:return[\"filter-has\",t]}}function On(t){return[\"!\",t]}function In(t){return Tn(Vt(t.value))?_n(jt({},t,{expressionContext:\"filter\",valueSpec:{value:\"boolean\"}})):zn(t)}function zn(t){var e=t.value,r=t.key;if(\"array\"!==Qr(e))return[new Bt(r,e,\"array expected, \"+Qr(e)+\" found\")];var n,i=t.styleSpec,a=[];if(e.length<1)return[new Bt(r,e,\"filter array must have at least 1 element\")];switch(a=a.concat(wn({key:r+\"[0]\",value:e[0],valueSpec:i.filter_operator,style:t.style,styleSpec:t.styleSpec})),Ut(e[0])){case\"<\":case\"<=\":case\">\":case\">=\":e.length>=2&&\"$type\"===Ut(e[1])&&a.push(new Bt(r,e,'\"$type\" cannot be use with operator \"'+e[0]+'\"'));case\"==\":case\"!=\":3!==e.length&&a.push(new Bt(r,e,'filter array for operator \"'+e[0]+'\" must have 3 elements'));case\"in\":case\"!in\":e.length>=2&&\"string\"!==(n=Qr(e[1]))&&a.push(new Bt(r+\"[1]\",e[1],\"string expected, \"+n+\" found\"));for(var o=2;o=c[p+0]&&n>=c[p+1])?(o[h]=!0,a.push(u[h])):o[h]=!1}}},ri.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToCellCoord(t),u=this._convertToCellCoord(e),c=this._convertToCellCoord(r),f=this._convertToCellCoord(n),h=l;h<=c;h++)for(var p=u;p<=f;p++){var d=this.d*p+h;if((!s||s(this._convertFromCellCoord(h),this._convertFromCellCoord(p),this._convertFromCellCoord(h+1),this._convertFromCellCoord(p+1)))&&i.call(this,t,e,r,n,d,a,o,s))return}},ri.prototype._convertFromCellCoord=function(t){return(t-this.padding)/this.scale},ri.prototype._convertToCellCoord=function(t){return Math.max(0,Math.min(this.d-1,Math.floor(t*this.scale)+this.padding))},ri.prototype.toArrayBuffer=function(){if(this.arrayBuffer)return this.arrayBuffer;for(var t=this.cells,e=ei+this.cells.length+1+1,r=0,n=0;n=0)){var f=t[c];u[c]=ai[l].shallow.indexOf(c)>=0?f:ci(f,e)}t instanceof Error&&(u.message=t.message)}if(u.$name)throw new Error(\"$name property is reserved for worker serialization logic.\");return\"Object\"!==l&&(u.$name=l),u}throw new Error(\"can't serialize object of type \"+typeof t)}function 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this._structArray.uint8[this._pos1+38]},r.hidden.set=function(t){this._structArray.uint8[this._pos1+38]=t},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+10]=t},r.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(e.prototype,r),e}($i);Ma.prototype.size=48;var Sa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new Ma(this,t)},e}(ga);oi(\"PlacedSymbolArray\",Sa);var Ea=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var 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r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},r.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},r.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},r.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},r.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},r.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},r.key.get=function(){return this._structArray.uint16[this._pos2+8]},r.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},r.verticalTextBoxStartIndex.get=function(){return 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S=o.content;x=ju(h,0,S[0]),_=ju(p,0,S[1]),b=ju(h,S[0],S[2]),w=ju(p,S[1],S[3]),T=S[0]-x,A=S[1]-_,k=S[2]-S[0]-b,M=S[3]-S[1]-w}var E=function(n,i,l,u){var h=Vu(n.stretch-x,b,c,t.left),p=qu(n.fixed-T,k,n.stretch,v),d=Vu(i.stretch-_,w,f,t.top),y=qu(i.fixed-A,M,i.stretch,g),m=Vu(l.stretch-x,b,c,t.left),S=qu(l.fixed-T,k,l.stretch,v),E=Vu(u.stretch-_,w,f,t.top),L=qu(u.fixed-A,M,u.stretch,g),C=new a(h,d),P=new a(m,d),O=new a(m,E),I=new a(h,E),z=new a(p/s,y/s),D=new a(S/s,L/s),R=e*Math.PI/180;if(R){var F=Math.sin(R),B=Math.cos(R),N=[B,-F,F,B];C._matMult(N),P._matMult(N),I._matMult(N),O._matMult(N)}var j=n.stretch+n.fixed,U=l.stretch+l.fixed,V=i.stretch+i.fixed,q=u.stretch+u.fixed;return{tl:C,tr:P,bl:I,br:O,tex:{x:o.paddedRect.x+Bu+j,y:o.paddedRect.y+Bu+V,w:U-j,h:q-V},writingMode:void 0,glyphOffset:[0,0],sectionIndex:0,pixelOffsetTL:z,pixelOffsetBR:D,minFontScaleX:k/s/c,minFontScaleY:M/s/f,isSDF:r}};if(n&&(o.stretchX||o.stretchY))for(var L=Uu(h,y,v),C=Uu(p,m,g),P=0;P0&&(d=Math.max(10,d),this.circleDiameter=d)}else{var v=o.top*s-l,g=o.bottom*s+l,y=o.left*s-l,m=o.right*s+l,x=o.collisionPadding;if(x&&(y-=x[0]*s,v-=x[1]*s,m+=x[2]*s,g+=x[3]*s),c){var b=new a(y,v),_=new a(m,v),w=new a(y,g),T=new a(m,g),k=c*Math.PI/180;b._rotate(k),_._rotate(k),w._rotate(k),T._rotate(k),y=Math.min(b.x,_.x,w.x,T.x),m=Math.max(b.x,_.x,w.x,T.x),v=Math.min(b.y,_.y,w.y,T.y),g=Math.max(b.y,_.y,w.y,T.y)}t.emplaceBack(e.x,e.y,y,v,m,g,r,n,i)}this.boxEndIndex=t.length},Gu=function(t,e){if(void 0===t&&(t=[]),void 0===e&&(e=Wu),this.data=t,this.length=this.data.length,this.compare=e,this.length>0)for(var r=(this.length>>1)-1;r>=0;r--)this._down(r)};function Wu(t,e){return te?1:0}function Yu(t,e,r){void 0===e&&(e=1),void 0===r&&(r=!1);for(var n=1/0,i=1/0,o=-1/0,s=-1/0,l=t[0],u=0;uo)&&(o=c.x),(!u||c.y>s)&&(s=c.y)}var f=o-n,h=s-i,p=Math.min(f,h),d=p/2,v=new Gu([],Xu);if(0===p)return new a(n,i);for(var g=n;gm.d||!m.d)&&(m=b,r&&console.log(\"found best %d 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i=t-1>>1,a=e[i];if(r(n,a)>=0)break;e[t]=a,t=i}e[t]=n},Gu.prototype._down=function(t){for(var e=this.data,r=this.compare,n=this.length>>1,i=e[t];t=0)break;e[t]=o,t=a}e[t]=i};var Ku=7,Ju=Number.POSITIVE_INFINITY;function $u(t,e){return e[1]!==Ju?function(t,e,r){var n=0,i=0;switch(e=Math.abs(e),r=Math.abs(r),t){case\"top-right\":case\"top-left\":case\"top\":i=r-Ku;break;case\"bottom-right\":case\"bottom-left\":case\"bottom\":i=-r+Ku}switch(t){case\"top-right\":case\"bottom-right\":case\"right\":n=-e;break;case\"top-left\":case\"bottom-left\":case\"left\":n=e}return[n,i]}(t,e[0],e[1]):function(t,e){var r=0,n=0;e<0&&(e=0);var i=e/Math.sqrt(2);switch(t){case\"top-right\":case\"top-left\":n=i-Ku;break;case\"bottom-right\":case\"bottom-left\":n=-i+Ku;break;case\"bottom\":n=-e+Ku;break;case\"top\":n=e-Ku}switch(t){case\"top-right\":case\"bottom-right\":r=-i;break;case\"top-left\":case\"bottom-left\":r=i;break;case\"left\":r=e;break;case\"right\":r=-e}return[r,n]}(t,e[0])}function Qu(t){switch(t){case\"right\":case\"top-right\":case\"bottom-right\":return\"right\";case\"left\":case\"top-left\":case\"bottom-left\":return\"left\"}return\"center\"}var tc=255,ec=tc*Au;function rc(t,e,r,n,i,o,s,l,u,c,f,h,p,d,v){var g=function(t,e,r,n,i,o,s,l){for(var u=n.layout.get(\"text-rotate\").evaluate(o,{})*Math.PI/180,c=[],f=0,h=e.positionedLines;fec&&k(t.layerIds[0]+': Value for \"text-size\" is >= '+tc+'. Reduce your \"text-size\".'):\"composite\"===y.kind&&((m=[Au*d.compositeTextSizes[0].evaluate(s,{},v),Au*d.compositeTextSizes[1].evaluate(s,{},v)])[0]>ec||m[1]>ec)&&k(t.layerIds[0]+': Value for \"text-size\" is >= '+tc+'. 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this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},hc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},oi(\"SymbolBucket\",hc,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),hc.MAX_GLYPHS=65535,hc.addDynamicAttributes=lc;var pc=new Xi({\"symbol-placement\":new qi(Ft.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new qi(Ft.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new qi(Ft.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new Hi(Ft.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new qi(Ft.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new qi(Ft.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new qi(Ft.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new qi(Ft.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new qi(Ft.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new Hi(Ft.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new qi(Ft.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new qi(Ft.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new Hi(Ft.layout_symbol[\"icon-image\"]),\"icon-rotate\":new Hi(Ft.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new qi(Ft.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new qi(Ft.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new Hi(Ft.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new Hi(Ft.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new qi(Ft.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new qi(Ft.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new qi(Ft.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new Hi(Ft.layout_symbol[\"text-field\"]),\"text-font\":new Hi(Ft.layout_symbol[\"text-font\"]),\"text-size\":new Hi(Ft.layout_symbol[\"text-size\"]),\"text-max-width\":new Hi(Ft.layout_symbol[\"text-max-width\"]),\"text-line-height\":new qi(Ft.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new Hi(Ft.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new Hi(Ft.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new Hi(Ft.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new qi(Ft.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new Hi(Ft.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new qi(Ft.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new qi(Ft.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new Hi(Ft.layout_symbol[\"text-rotate\"]),\"text-padding\":new qi(Ft.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new qi(Ft.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new Hi(Ft.layout_symbol[\"text-transform\"]),\"text-offset\":new Hi(Ft.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new qi(Ft.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new qi(Ft.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new qi(Ft.layout_symbol[\"text-optional\"])}),dc={paint:new Xi({\"icon-opacity\":new Hi(Ft.paint_symbol[\"icon-opacity\"]),\"icon-color\":new Hi(Ft.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new Hi(Ft.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new Hi(Ft.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new Hi(Ft.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new qi(Ft.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new qi(Ft.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new Hi(Ft.paint_symbol[\"text-opacity\"]),\"text-color\":new Hi(Ft.paint_symbol[\"text-color\"],{runtimeType:Zt,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new Hi(Ft.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new Hi(Ft.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new Hi(Ft.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new qi(Ft.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new qi(Ft.paint_symbol[\"text-translate-anchor\"])}),layout:pc},vc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Gt,this.defaultValue=t};vc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},vc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},vc.prototype.outputDefined=function(){return!1},vc.prototype.serialize=function(){return null},oi(\"FormatSectionOverride\",vc,{omit:[\"defaultValue\"]});var gc=function(t){function e(e){t.call(this,e,dc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var n=this.layout.get(\"text-writing-mode\");if(n){for(var i=[],a=0,o=n;a\",targetMapId:n,sourceMapId:a.mapId})}}},Cc.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else S()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Cc.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Cc.prototype.processTask=function(t,e){var r=this;if(\"\"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(fi(e.error)):n(null,fi(e.data)))}else{var i=!1,a=C(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:\"\",sourceMapId:r.mapId,error:e?ci(e):null,data:ci(n,a)},a)}:function(t){i=!0},s=null,l=fi(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var u=e.type.split(\".\");s=this.parent.getWorkerSource(e.sourceMapId,u[0],l.source)[u[1]](l,o)}else o(new Error(\"Could not find function \"+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Cc.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};var Oc=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Oc.prototype.setNorthEast=function(t){return this._ne=t instanceof zc?new zc(t.lng,t.lat):zc.convert(t),this},Oc.prototype.setSouthWest=function(t){return this._sw=t instanceof zc?new zc(t.lng,t.lat):zc.convert(t),this},Oc.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof zc)e=t,r=t;else{if(!(t instanceof Oc)){if(Array.isArray(t)){if(4===t.length||t.every(Array.isArray)){var a=t;return this.extend(Oc.convert(a))}var o=t;return this.extend(zc.convert(o))}return this}if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new zc(e.lng,e.lat),this._ne=new zc(r.lng,r.lat)),this},Oc.prototype.getCenter=function(){return new zc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Oc.prototype.getSouthWest=function(){return this._sw},Oc.prototype.getNorthEast=function(){return this._ne},Oc.prototype.getNorthWest=function(){return new zc(this.getWest(),this.getNorth())},Oc.prototype.getSouthEast=function(){return new zc(this.getEast(),this.getSouth())},Oc.prototype.getWest=function(){return this._sw.lng},Oc.prototype.getSouth=function(){return this._sw.lat},Oc.prototype.getEast=function(){return this._ne.lng},Oc.prototype.getNorth=function(){return this._ne.lat},Oc.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Oc.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Oc.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Oc.prototype.contains=function(t){var e=zc.convert(t),r=e.lng,n=e.lat,i=this._sw.lat<=n&&n<=this._ne.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),i&&a},Oc.convert=function(t){return!t||t instanceof Oc?t:new Oc(t)};var Ic=6371008.8,zc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};zc.prototype.wrap=function(){return new zc(h(this.lng,-180,180),this.lat)},zc.prototype.toArray=function(){return[this.lng,this.lat]},zc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},zc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return Ic*Math.acos(Math.min(i,1))},zc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Oc(new zc(this.lng-r,this.lat-e),new zc(this.lng+r,this.lat+e))},zc.convert=function(t){if(t instanceof zc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new zc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new zc(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: , lat: }, an object {lon: , lat: }, or an array of [, ]\")};var Dc=2*Math.PI*Ic;function Rc(t){return Dc*Math.cos(t*Math.PI/180)}function Fc(t){return(180+t)/360}function Bc(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Nc(t,e){return t/Rc(e)}function jc(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var Uc=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};Uc.fromLngLat=function(t,e){void 0===e&&(e=0);var r=zc.convert(t);return new Uc(Fc(r.lng),Bc(r.lat),Nc(e,r.lat))},Uc.prototype.toLngLat=function(){return new zc(360*this.x-180,jc(this.y))},Uc.prototype.toAltitude=function(){return t=this.z,e=this.y,t*Rc(jc(e));var t,e},Uc.prototype.meterInMercatorCoordinateUnits=function(){return 1/Dc*(t=jc(this.y),1/Math.cos(t*Math.PI/180));var t};var Vc=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=Gc(0,t,t,e,r)};Vc.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},Vc.prototype.url=function(t,e){var r,n,i,a,o,s=(r=this.x,n=this.y,i=this.z,a=Pc(256*r,256*(n=Math.pow(2,i)-n-1),i),o=Pc(256*(r+1),256*(n+1),i),a[0]+\",\"+a[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<this.canonical.z?new Hc(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Hc(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},Hc.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?Gc(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):Gc(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},Hc.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ>e&&t.canonical.y===this.canonical.y>>e},Hc.prototype.children=function(t){if(this.overscaledZ>=t)return[new Hc(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new Hc(e,this.wrap,e,r,n),new Hc(e,this.wrap,e,r+1,n),new Hc(e,this.wrap,e,r,n+1),new Hc(e,this.wrap,e,r+1,n+1)]},Hc.prototype.isLessThan=function(t){return this.wrapt.wrap)&&(this.overscaledZt.overscaledZ)&&(this.canonical.xt.canonical.x)&&this.canonical.y=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},Wc.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},Wc.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},Wc.prototype.getPixels=function(){return new $o({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},Wc.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,u=a;u=0&&c[3]>=0&&s.insert(o,c[0],c[1],c[2],c[3])}},Jc.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new tl.VectorTile(new Ol(this.rawTileData)).layers,this.sourceLayerCoder=new Yc(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},Jc.prototype.query=function(t,e,r,n){var i=this;this.loadVTLayers();for(var o=t.params||{},s=po/t.tileSize/t.scale,l=An(o.filter),u=t.queryGeometry,c=t.queryPadding*s,f=Qc(u),h=this.grid.query(f.minX-c,f.minY-c,f.maxX+c,f.maxY+c),p=Qc(t.cameraQueryGeometry),d=0,v=this.grid3D.query(p.minX-c,p.minY-c,p.maxX+c,p.maxY+c,(function(e,r,n,i){return function(t,e,r,n,i){for(var o=0,s=t;o=l.x&&i>=l.y)return!0}var u=[new a(e,r),new a(e,i),new a(n,i),new a(n,r)];if(t.length>2)for(var c=0,f=u;c=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),d=this.vtLayers[h].feature(n);if(i.needGeometry){var v=mo(d,!0);if(!i.filter(new zi(this.tileID.overscaledZ),v,this.tileID.canonical))return}else if(!i.filter(new zi(this.tileID.overscaledZ),d))return;for(var g=this.getId(d,h),y=0;yn)i=!1;else if(e)if(this.expirationTimeht&&(t.getActor().send(\"enforceCacheSizeLimit\",ft),xt=0)},t.clamp=f,t.clearTileCache=function(t){var e=s.caches.delete(ct);t&&e.catch(t).then((function(){return t()}))},t.clipLine=Fu,t.clone=function(t){var e=new Fo(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},t.clone$1=w,t.clone$2=function(t){var e=new Fo(3);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e},t.collisionCircleLayout=Ml,t.config=j,t.create=function(){var t=new Fo(16);return Fo!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0),t[0]=1,t[5]=1,t[10]=1,t[15]=1,t},t.create$1=function(){var t=new Fo(9);return Fo!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[5]=0,t[6]=0,t[7]=0),t[0]=1,t[4]=1,t[8]=1,t},t.create$2=function(){var t=new Fo(4);return Fo!=Float32Array&&(t[1]=0,t[2]=0),t[0]=1,t[3]=1,t},t.createCommonjsModule=e,t.createExpression=fn,t.createLayout=ta,t.createStyleLayer=function(t){return\"custom\"===t.type?new _c(t):new wc[t.type](t)},t.cross=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=r[0],s=r[1],l=r[2];return t[0]=i*l-a*s,t[1]=a*o-n*l,t[2]=n*s-i*o,t},t.deepEqual=function t(e,r){if(Array.isArray(e)){if(!Array.isArray(r)||e.length!==r.length)return!1;for(var n=0;n0&&(a=1/Math.sqrt(a)),t[0]=e[0]*a,t[1]=e[1]*a,t[2]=e[2]*a,t},t.number=er,t.offscreenCanvasSupported=bt,t.ortho=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),u=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*u,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*u,t[15]=1,t},t.parseGlyphPBF=function(t){return new Ol(t).readFields(Ql,[])},t.pbf=Ol,t.performSymbolLayout=function(t,e,r,n,i,a,o){t.createArrays();var s=512*t.overscaling;t.tilePixelRatio=po/s,t.compareText={},t.iconsNeedLinear=!1;var l=t.layers[0].layout,u=t.layers[0]._unevaluatedLayout._values,c={};if(\"composite\"===t.textSizeData.kind){var f=t.textSizeData,h=f.minZoom,p=f.maxZoom;c.compositeTextSizes=[u[\"text-size\"].possiblyEvaluate(new zi(h),o),u[\"text-size\"].possiblyEvaluate(new zi(p),o)]}if(\"composite\"===t.iconSizeData.kind){var d=t.iconSizeData,v=d.minZoom,g=d.maxZoom;c.compositeIconSizes=[u[\"icon-size\"].possiblyEvaluate(new zi(v),o),u[\"icon-size\"].possiblyEvaluate(new zi(g),o)]}c.layoutTextSize=u[\"text-size\"].possiblyEvaluate(new zi(t.zoom+1),o),c.layoutIconSize=u[\"icon-size\"].possiblyEvaluate(new zi(t.zoom+1),o),c.textMaxSize=u[\"text-size\"].possiblyEvaluate(new zi(18));for(var y=l.get(\"text-line-height\")*Ll,m=\"map\"===l.get(\"text-rotation-alignment\")&&\"point\"!==l.get(\"symbol-placement\"),x=l.get(\"text-keep-upright\"),b=l.get(\"text-size\"),_=function(){var a=T[w],s=l.get(\"text-font\").evaluate(a,{},o).join(\",\"),u=b.evaluate(a,{},o),f=c.layoutTextSize.evaluate(a,{},o),h=c.layoutIconSize.evaluate(a,{},o),p={horizontal:{},vertical:void 0},d=a.text,v=[0,0];if(d){var g=d.toString(),_=l.get(\"text-letter-spacing\").evaluate(a,{},o)*Ll,A=function(t){for(var e=0,r=t;e=po||f.y<0||f.y>=po||function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v,g,y,m,x,b,_,w,T,A){var M,S,E,L,C,P=t.addToLineVertexArray(e,r),O=0,I=0,z=0,D=0,R=-1,F=-1,B={},N=ja(\"\"),j=0,U=0;if(void 0===s._unevaluatedLayout.getValue(\"text-radial-offset\")?(j=(M=s.layout.get(\"text-offset\").evaluate(b,{},T).map((function(t){return t*Ll})))[0],U=M[1]):(j=s.layout.get(\"text-radial-offset\").evaluate(b,{},T)*Ll,U=Ju),t.allowVerticalPlacement&&n.vertical){var V=s.layout.get(\"text-rotate\").evaluate(b,{},T)+90,q=n.vertical;L=new Hu(l,e,u,c,f,q,h,p,d,V),o&&(C=new Hu(l,e,u,c,f,o,g,y,d,V))}if(i){var H=s.layout.get(\"icon-rotate\").evaluate(b,{}),G=\"none\"!==s.layout.get(\"icon-text-fit\"),W=Nu(i,H,w,G),Y=o?Nu(o,H,w,G):void 0;E=new Hu(l,e,u,c,f,i,g,y,!1,H),O=4*W.length;var X=t.iconSizeData,Z=null;\"source\"===X.kind?(Z=[Au*s.layout.get(\"icon-size\").evaluate(b,{})])[0]>ec&&k(t.layerIds[0]+': Value for \"icon-size\" is >= '+tc+'. Reduce your \"icon-size\".'):\"composite\"===X.kind&&((Z=[Au*_.compositeIconSizes[0].evaluate(b,{},T),Au*_.compositeIconSizes[1].evaluate(b,{},T)])[0]>ec||Z[1]>ec)&&k(t.layerIds[0]+': Value for \"icon-size\" is >= '+tc+'. Reduce your \"icon-size\".'),t.addSymbols(t.icon,W,Z,x,m,b,!1,e,P.lineStartIndex,P.lineLength,-1,T),R=t.icon.placedSymbolArray.length-1,Y&&(I=4*Y.length,t.addSymbols(t.icon,Y,Z,x,m,b,lu.vertical,e,P.lineStartIndex,P.lineLength,-1,T),F=t.icon.placedSymbolArray.length-1)}for(var K in n.horizontal){var J=n.horizontal[K];if(!S){N=ja(J.text);var $=s.layout.get(\"text-rotate\").evaluate(b,{},T);S=new Hu(l,e,u,c,f,J,h,p,d,$)}var Q=1===J.positionedLines.length;if(z+=rc(t,e,J,a,s,d,b,v,P,n.vertical?lu.horizontal:lu.horizontalOnly,Q?Object.keys(n.horizontal):[K],B,R,_,T),Q)break}n.vertical&&(D+=rc(t,e,n.vertical,a,s,d,b,v,P,lu.vertical,[\"vertical\"],B,F,_,T));var tt=S?S.boxStartIndex:t.collisionBoxArray.length,et=S?S.boxEndIndex:t.collisionBoxArray.length,rt=L?L.boxStartIndex:t.collisionBoxArray.length,nt=L?L.boxEndIndex:t.collisionBoxArray.length,it=E?E.boxStartIndex:t.collisionBoxArray.length,at=E?E.boxEndIndex:t.collisionBoxArray.length,ot=C?C.boxStartIndex:t.collisionBoxArray.length,st=C?C.boxEndIndex:t.collisionBoxArray.length,lt=-1,ut=function(t,e){return t&&t.circleDiameter?Math.max(t.circleDiameter,e):e};lt=ut(S,lt),lt=ut(L,lt),lt=ut(E,lt);var ct=(lt=ut(C,lt))>-1?1:0;ct&&(lt*=A/Ll),t.glyphOffsetArray.length>=hc.MAX_GLYPHS&&k(\"Too many glyphs being rendered in a tile. See https://github.com/mapbox/mapbox-gl-js/issues/2907\"),void 0!==b.sortKey&&t.addToSortKeyRanges(t.symbolInstances.length,b.sortKey),t.symbolInstances.emplaceBack(e.x,e.y,B.right>=0?B.right:-1,B.center>=0?B.center:-1,B.left>=0?B.left:-1,B.vertical||-1,R,F,N,tt,et,rt,nt,it,at,ot,st,u,z,D,O,I,ct,0,h,j,U,lt)}(t,f,s,r,n,i,h,t.layers[0],t.collisionBoxArray,e.index,e.sourceLayerIndex,t.index,m,w,M,l,b,T,S,d,e,a,u,c,o)};if(\"line\"===E)for(var O=0,I=Fu(e.geometry,0,0,po,po);O1){var U=zu(j,A,r.vertical||v,n,g,x);U&&P(j,U)}}else if(\"Polygon\"===e.type)for(var V=0,q=Fs(e.geometry,0);V=E.maxzoom||\"none\"!==E.visibility&&(o(S,this.zoom,n),(v[E.id]=E.createBucket({index:c.bucketLayerIDs.length,layers:S,zoom:this.zoom,pixelRatio:this.pixelRatio,overscaling:this.overscaling,collisionBoxArray:this.collisionBoxArray,sourceLayerIndex:b,sourceID:this.source})).populate(_,g,this.tileID.canonical),c.bucketLayerIDs.push(S.map((function(t){return t.id}))))}}}var L=t.mapObject(g.glyphDependencies,(function(t){return Object.keys(t).map(Number)}));Object.keys(L).length?a.send(\"getGlyphs\",{uid:this.uid,stacks:L},(function(t,e){f||(f=t,h=e,O.call(l))})):h={};var C=Object.keys(g.iconDependencies);C.length?a.send(\"getImages\",{icons:C,source:this.source,tileID:this.tileID,type:\"icons\"},(function(t,e){f||(f=t,p=e,O.call(l))})):p={};var P=Object.keys(g.patternDependencies);function O(){if(f)return s(f);if(h&&p&&d){var e=new i(h),r=new t.ImageAtlas(p,d);for(var a in v){var l=v[a];l instanceof t.SymbolBucket?(o(l.layers,this.zoom,n),t.performSymbolLayout(l,h,e.positions,p,r.iconPositions,this.showCollisionBoxes,this.tileID.canonical)):l.hasPattern&&(l instanceof t.LineBucket||l instanceof t.FillBucket||l instanceof t.FillExtrusionBucket)&&(o(l.layers,this.zoom,n),l.addFeatures(g,this.tileID.canonical,r.patternPositions))}this.status=\"done\",s(null,{buckets:t.values(v).filter((function(t){return!t.isEmpty()})),featureIndex:c,collisionBoxArray:this.collisionBoxArray,glyphAtlasImage:e.image,imageAtlas:r,glyphMap:this.returnDependencies?h:null,iconMap:this.returnDependencies?p:null,glyphPositions:this.returnDependencies?e.positions:null})}}P.length?a.send(\"getImages\",{icons:P,source:this.source,tileID:this.tileID,type:\"patterns\"},(function(t,e){f||(f=t,d=e,O.call(l))})):d={},O.call(this)};var l=function(t,e,r,n){this.actor=t,this.layerIndex=e,this.availableImages=r,this.loadVectorData=n||s,this.loading={},this.loaded={}};l.prototype.loadTile=function(e,r){var n=this,i=e.uid;this.loading||(this.loading={});var o=!!(e&&e.request&&e.request.collectResourceTiming)&&new t.RequestPerformance(e.request),s=this.loading[i]=new a(e);s.abort=this.loadVectorData(e,(function(e,a){if(delete n.loading[i],e||!a)return s.status=\"done\",n.loaded[i]=s,r(e);var l=a.rawData,u={};a.expires&&(u.expires=a.expires),a.cacheControl&&(u.cacheControl=a.cacheControl);var c={};if(o){var f=o.finish();f&&(c.resourceTiming=JSON.parse(JSON.stringify(f)))}s.vectorTile=a.vectorTile,s.parse(a.vectorTile,n.layerIndex,n.availableImages,n.actor,(function(e,n){if(e||!n)return r(e);r(null,t.extend({rawTileData:l.slice(0)},n,u,c))})),n.loaded=n.loaded||{},n.loaded[i]=s}))},l.prototype.reloadTile=function(t,e){var r=this,n=this.loaded,i=t.uid,a=this;if(n&&n[i]){var o=n[i];o.showCollisionBoxes=t.showCollisionBoxes;var s=function(t,n){var i=o.reloadCallback;i&&(delete o.reloadCallback,o.parse(o.vectorTile,a.layerIndex,r.availableImages,a.actor,i)),e(t,n)};\"parsing\"===o.status?o.reloadCallback=s:\"done\"===o.status&&(o.vectorTile?o.parse(o.vectorTile,this.layerIndex,this.availableImages,this.actor,s):s())}},l.prototype.abortTile=function(t,e){var r=this.loading,n=t.uid;r&&r[n]&&r[n].abort&&(r[n].abort(),delete r[n]),e()},l.prototype.removeTile=function(t,e){var r=this.loaded,n=t.uid;r&&r[n]&&delete r[n],e()};var u=t.window.ImageBitmap,c=function(){this.loaded={}};c.prototype.loadTile=function(e,r){var n=e.uid,i=e.encoding,a=e.rawImageData,o=u&&a instanceof u?this.getImageData(a):a,s=new t.DEMData(n,o,i);this.loaded=this.loaded||{},this.loaded[n]=s,r(null,s)},c.prototype.getImageData=function(e){this.offscreenCanvas&&this.offscreenCanvasContext||(this.offscreenCanvas=new OffscreenCanvas(e.width,e.height),this.offscreenCanvasContext=this.offscreenCanvas.getContext(\"2d\")),this.offscreenCanvas.width=e.width,this.offscreenCanvas.height=e.height,this.offscreenCanvasContext.drawImage(e,0,0,e.width,e.height);var r=this.offscreenCanvasContext.getImageData(-1,-1,e.width+2,e.height+2);return this.offscreenCanvasContext.clearRect(0,0,this.offscreenCanvas.width,this.offscreenCanvas.height),new t.RGBAImage({width:r.width,height:r.height},r.data)},c.prototype.removeTile=function(t){var e=this.loaded,r=t.uid;e&&e[r]&&delete e[r]};var f=function t(e,r){var n,i=e&&e.type;if(\"FeatureCollection\"===i)for(n=0;n=0!=!!e&&t.reverse()}var d=t.vectorTile.VectorTileFeature.prototype.toGeoJSON,v=function(e){this._feature=e,this.extent=t.EXTENT,this.type=e.type,this.properties=e.tags,\"id\"in e&&!isNaN(e.id)&&(this.id=parseInt(e.id,10))};v.prototype.loadGeometry=function(){if(1===this._feature.type){for(var e=[],r=0,n=this._feature.geometry;r>31}function P(t,e){for(var r=t.loadGeometry(),n=t.type,i=0,a=0,o=r.length,s=0;s>1;z(t,e,o,n,i,a%2),I(t,e,r,n,o-1,a+1),I(t,e,r,o+1,i,a+1)}}function z(t,e,r,n,i,a){for(;i>n;){if(i-n>600){var o=i-n+1,s=r-n+1,l=Math.log(o),u=.5*Math.exp(2*l/3),c=.5*Math.sqrt(l*u*(o-u)/o)*(s-o/2<0?-1:1);z(t,e,r,Math.max(n,Math.floor(r-s*u/o+c)),Math.min(i,Math.floor(r+(o-s)*u/o+c)),a)}var f=e[2*r+a],h=n,p=i;for(D(t,e,n,r),e[2*i+a]>f&&D(t,e,n,i);hf;)p--}e[2*n+a]===f?D(t,e,n,p):D(t,e,++p,i),p<=r&&(n=p+1),r<=p&&(i=p-1)}}function D(t,e,r,n){R(t,r,n),R(e,2*r,2*n),R(e,2*r+1,2*n+1)}function R(t,e,r){var n=t[e];t[e]=t[r],t[r]=n}function F(t,e,r,n){var i=t-r,a=e-n;return i*i+a*a}_.fromVectorTileJs=w,_.fromGeojsonVt=T,_.GeoJSONWrapper=k;var B=function(t){return t[0]},N=function(t){return t[1]},j=function(t,e,r,n,i){void 0===e&&(e=B),void 0===r&&(r=N),void 0===n&&(n=64),void 0===i&&(i=Float64Array),this.nodeSize=n,this.points=t;for(var a=t.length<65536?Uint16Array:Uint32Array,o=this.ids=new a(t.length),s=this.coords=new i(2*t.length),l=0;l=r&&s<=i&&l>=n&&l<=a&&c.push(t[d]);else{var v=Math.floor((p+h)/2);s=e[2*v],l=e[2*v+1],s>=r&&s<=i&&l>=n&&l<=a&&c.push(t[v]);var g=(f+1)%2;(0===f?r<=s:n<=l)&&(u.push(p),u.push(v-1),u.push(g)),(0===f?i>=s:a>=l)&&(u.push(v+1),u.push(h),u.push(g))}}return c}(this.ids,this.coords,t,e,r,n,this.nodeSize)},j.prototype.within=function(t,e,r){return function(t,e,r,n,i,a){for(var o=[0,t.length-1,0],s=[],l=i*i;o.length;){var u=o.pop(),c=o.pop(),f=o.pop();if(c-f<=a)for(var h=f;h<=c;h++)F(e[2*h],e[2*h+1],r,n)<=l&&s.push(t[h]);else{var p=Math.floor((f+c)/2),d=e[2*p],v=e[2*p+1];F(d,v,r,n)<=l&&s.push(t[p]);var g=(u+1)%2;(0===u?r-i<=d:n-i<=v)&&(o.push(f),o.push(p-1),o.push(g)),(0===u?r+i>=d:n+i>=v)&&(o.push(p+1),o.push(c),o.push(g))}}return s}(this.ids,this.coords,t,e,r,this.nodeSize)};var U={minZoom:0,maxZoom:16,minPoints:2,radius:40,extent:512,nodeSize:64,log:!1,generateId:!1,reduce:null,map:function(t){return t}},V=function(t){this.options=Z(Object.create(U),t),this.trees=new Array(this.options.maxZoom+1)};function q(t,e,r,n,i){return{x:t,y:e,zoom:1/0,id:r,parentId:-1,numPoints:n,properties:i}}function H(t,e){var r=t.geometry.coordinates,n=r[0],i=r[1];return{x:Y(n),y:X(i),zoom:1/0,index:e,parentId:-1}}function G(t){return{type:\"Feature\",id:t.id,properties:W(t),geometry:{type:\"Point\",coordinates:[(n=t.x,360*(n-.5)),(e=t.y,r=(180-360*e)*Math.PI/180,360*Math.atan(Math.exp(r))/Math.PI-90)]}};var e,r,n}function W(t){var e=t.numPoints,r=e>=1e4?Math.round(e/1e3)+\"k\":e>=1e3?Math.round(e/100)/10+\"k\":e;return Z(Z({},t.properties),{cluster:!0,cluster_id:t.id,point_count:e,point_count_abbreviated:r})}function Y(t){return t/360+.5}function X(t){var e=Math.sin(t*Math.PI/180),r=.5-.25*Math.log((1+e)/(1-e))/Math.PI;return r<0?0:r>1?1:r}function Z(t,e){for(var r in e)t[r]=e[r];return t}function K(t){return t.x}function J(t){return t.y}function $(t,e,r,n){for(var i,a=n,o=r-e>>1,s=r-e,l=t[e],u=t[e+1],c=t[r],f=t[r+1],h=e+3;ha)i=h,a=p;else if(p===a){var d=Math.abs(h-o);dn&&(i-e>3&&$(t,e,i,n),t[i+2]=a,r-i>3&&$(t,i,r,n))}function Q(t,e,r,n,i,a){var o=i-r,s=a-n;if(0!==o||0!==s){var l=((t-r)*o+(e-n)*s)/(o*o+s*s);l>1?(r=i,n=a):l>0&&(r+=o*l,n+=s*l)}return(o=t-r)*o+(s=e-n)*s}function tt(t,e,r,n){var i={id:void 0===t?null:t,type:e,geometry:r,tags:n,minX:1/0,minY:1/0,maxX:-1/0,maxY:-1/0};return function(t){var e=t.geometry,r=t.type;if(\"Point\"===r||\"MultiPoint\"===r||\"LineString\"===r)et(t,e);else if(\"Polygon\"===r||\"MultiLineString\"===r)for(var n=0;n0&&(o+=n?(i*u-l*a)/2:Math.sqrt(Math.pow(l-i,2)+Math.pow(u-a,2))),i=l,a=u}var c=e.length-3;e[2]=1,$(e,0,c,r),e[c+2]=1,e.size=Math.abs(o),e.start=0,e.end=e.size}function at(t,e,r,n){for(var i=0;i1?1:r}function lt(t,e,r,n,i,a,o,s){if(n/=e,a>=(r/=e)&&o=n)return null;for(var l=[],u=0;u=r&&d=n)){var v=[];if(\"Point\"===h||\"MultiPoint\"===h)ut(f,v,r,n,i);else if(\"LineString\"===h)ct(f,v,r,n,i,!1,s.lineMetrics);else if(\"MultiLineString\"===h)ht(f,v,r,n,i,!1);else if(\"Polygon\"===h)ht(f,v,r,n,i,!0);else if(\"MultiPolygon\"===h)for(var g=0;g=r&&o<=n&&(e.push(t[a]),e.push(t[a+1]),e.push(t[a+2]))}}function ct(t,e,r,n,i,a,o){for(var s,l,u=ft(t),c=0===i?dt:vt,f=t.start,h=0;hr&&(l=c(u,p,d,g,y,r),o&&(u.start=f+s*l)):m>n?x=r&&(l=c(u,p,d,g,y,r),b=!0),x>n&&m<=n&&(l=c(u,p,d,g,y,n),b=!0),!a&&b&&(o&&(u.end=f+s*l),e.push(u),u=ft(t)),o&&(f+=s)}var _=t.length-3;p=t[_],d=t[_+1],v=t[_+2],(m=0===i?p:d)>=r&&m<=n&&pt(u,p,d,v),_=u.length-3,a&&_>=3&&(u[_]!==u[0]||u[_+1]!==u[1])&&pt(u,u[0],u[1],u[2]),u.length&&e.push(u)}function ft(t){var e=[];return e.size=t.size,e.start=t.start,e.end=t.end,e}function ht(t,e,r,n,i,a){for(var o=0;oo.maxX&&(o.maxX=c),f>o.maxY&&(o.maxY=f)}return o}function _t(t,e,r,n){var i=e.geometry,a=e.type,o=[];if(\"Point\"===a||\"MultiPoint\"===a)for(var s=0;s0&&e.size<(i?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;lo)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;i&&function(t,e){for(var r=0,n=0,i=t.length,a=i-2;n0===e)for(n=0,i=t.length;n24)throw new Error(\"maxZoom should be in the 0-24 range\");if(e.promoteId&&e.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n=n;u--){var c=+Date.now();s=this._cluster(s,u),this.trees[u]=new j(s,K,J,a,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",u,s.length,+Date.now()-c)}return r&&console.timeEnd(\"total time\"),this},V.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],u=[],c=0,f=l.range(Y(r),X(a),Y(i),X(n));ce&&(d+=m.numPoints||1)}if(d>=s){for(var x=c.x*p,b=c.y*p,_=o&&p>1?this._map(c,!0):null,w=(u<<5)+(e+1)+this.points.length,T=0,k=h;T1)for(var E=0,L=h;E>5},V.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},V.prototype._map=function(t,e){if(t.numPoints)return e?Z({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?Z({},n):n},Tt.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},Tt.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,u=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var c=1<1&&console.time(\"creation\"),h=this.tiles[f]=bt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),u)){u>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<1&&console.time(\"clipping\");var v,g,y,m,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;v=g=y=m=null,x=lt(t,c,r-_,r+T,0,h.minX,h.maxX,l),b=lt(t,c,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(v=lt(x,c,n-_,n+T,1,h.minY,h.maxY,l),g=lt(x,c,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(y=lt(b,c,n-_,n+T,1,h.minY,h.maxY,l),m=lt(b,c,n+w,n+k,1,h.minY,h.maxY,l),b=null),u>1&&console.timeEnd(\"clipping\"),s.push(v||[],e+1,2*r,2*n),s.push(g||[],e+1,2*r,2*n+1),s.push(y||[],e+1,2*r+1,2*n),s.push(m||[],e+1,2*r+1,2*n+1)}}},Tt.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,u=t,c=e,f=r;!l&&u>0;)u--,c=Math.floor(c/2),f=Math.floor(f/2),l=this.tiles[kt(u,c,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",u,c,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,u,c,f,t,e,r),a>1&&console.timeEnd(\"drilling down\"),this.tiles[s]?mt(this.tiles[s],i):null):null};var Mt=function(e){function r(t,r,n,i){e.call(this,t,r,n,At),i&&(this.loadGeoJSON=i)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&\"Idle\"!==this._state?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var i=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(a,o){if(a||!o)return r(a);if(\"object\"!=typeof o)return r(new Error(\"Input data given to '\"+n.source+\"' is not a valid GeoJSON object.\"));f(o,!0);try{if(n.filter){var s=t.createExpression(n.filter,{type:\"boolean\",\"property-type\":\"data-driven\",overridable:!1,transition:!1});if(\"error\"===s.result)throw new Error(s.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));var l=o.features.filter((function(t){return s.value.evaluate({zoom:0},t)}));o={type:\"FeatureCollection\",features:l}}e._geoJSONIndex=n.cluster?new V(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var i={},a={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),u=0,c=l;u=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var h=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e=0?1.2:1))}function y(t,e,r,n,i,a,o){for(var s=0;s65535)e(new Error(\"glyphs > 65535 not supported\"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=void 0,d=i/r*(n+1);if(l.isDash){var v=n-Math.abs(d);p=Math.sqrt(h*h+v*v)}else p=n-Math.sqrt(h*h+d*d);this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],u=0;u1&&(l=t[++s]);var c=Math.abs(u-l.left),f=Math.abs(u-l.right),h=Math.min(c,f),p=l.isDash?h:-h;this.data[o+u]=Math.max(0,Math.min(255,p+128))}},k.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o=n&&e.x=i&&e.y0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+10&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;\"string\"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+\".loadData\",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor;var a={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};e.request=this.actor.send(i,a,(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,\"reloadTile\"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),O=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),I=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;or.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(I),D=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return\"number\"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,O.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];tthis.max){var o=this._getAndRemoveByKey(this.order[0]);o&&this.onRemove(o)}return this},j.prototype.has=function(t){return t.wrapped().key in this.data},j.prototype.getAndRemove=function(t){return this.has(t)?this._getAndRemoveByKey(t.wrapped().key):null},j.prototype._getAndRemoveByKey=function(t){var e=this.data[t].shift();return e.timeout&&clearTimeout(e.timeout),0===this.data[t].length&&delete this.data[t],this.order.splice(this.order.indexOf(t),1),e.value},j.prototype.getByKey=function(t){var e=this.data[t];return e?e[0].value:null},j.prototype.get=function(t){return this.has(t)?this.data[t.wrapped().key][0].value:null},j.prototype.remove=function(t,e){if(!this.has(t))return this;var r=t.wrapped().key,n=void 0===e?0:this.data[r].indexOf(e),i=this.data[r][n];return this.data[r].splice(n,1),i.timeout&&clearTimeout(i.timeout),0===this.data[r].length&&delete this.data[r],this.onRemove(i.value),this.order.splice(this.order.indexOf(r),1),this},j.prototype.setMaxSize=function(t){for(this.max=t;this.order.length>this.max;){var e=this._getAndRemoveByKey(this.order[0]);e&&this.onRemove(e)}return this},j.prototype.filter=function(t){var e=[];for(var r in this.data)for(var n=0,i=this.data[r];n1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(zt(this._source.type)){for(var u={},c={},f=0,h=Object.keys(l);fthis._source.maxzoom){var g=d.children(this._source.maxzoom)[0],y=this.getTile(g);if(y&&y.hasData()){n[g.key]=g;continue}}else{var m=d.children(this._source.maxzoom);if(n[m[0].key]&&n[m[1].key]&&n[m[2].key]&&n[m[3].key])continue}for(var x=v.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(v=this.getTile(_))&&x&&(v=this._addTile(_)),v&&(n[_.key]=_,x=v.wasRequested(),v.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),u=s.map((function(t){return o.pointCoordinate(t)})),c=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,v=0,g=u;v=0&&y[1].y+g>=0){var m=l.map((function(t){return s.getTilePoint(t)})),x=u.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:m,cameraQueryGeometry:x,scale:v})}}},x=0;x=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||\"_geojsonTileLayer\",this._state.getState(t,e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles)this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,\"reloading\");this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function It(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function zt(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function Dt(){return new t.window.Worker(oa.workerUrl)}Ot.maxOverzooming=10,Ot.maxUnderzooming=3;var Rt=\"mapboxgl_preloaded_worker_pool\",Ft=function(){this.active={}};Ft.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Qt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ae(e,r,n,i,a,o,s,l){var u=i?e.textSizeData:e.iconSizeData,c=t.evaluateSizeForZoom(u,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,v=n.transform.width/n.transform.height,g=!1,y=0;yMath.abs(n.x-r.x)*i?{useVertical:!0}:(e===t.WritingMode.vertical?r.yn.x)?{needsFlipping:!0}:null}function le(e,r,n,i,a,o,s,l,u,c,f,h,p,d){var v,g=r/24,y=e.lineOffsetX*g,m=e.lineOffsetY*g;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=oe(g,l,y,m,n,f,h,e,u,o,p);if(!w)return{notEnoughRoom:!0};var T=re(w.first.point,s).point,k=re(w.last.point,s).point;if(i&&!n){var A=se(e.writingMode,T,k,d);if(A)return A}v=[w.first];for(var M=e.glyphStartIndex+1;M0?C.point:ue(h,L,S,1,a),O=se(e.writingMode,S,P,d);if(O)return O}var I=ce(g*l.getoffsetX(e.glyphStartIndex),y,m,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,u,o,p);if(!I)return{notEnoughRoom:!0};v=[I]}for(var z=0,D=v;z0?1:-1,v=0;i&&(d*=-1,v=Math.PI),d<0&&(v+=Math.PI);for(var g=d>0?l+s:l+s+1,y=a,m=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((g+=d)=u)return null;if(m=y,w.push(y),void 0===(y=h[g])){var T=new t.Point(c.getx(g),c.gety(g)),k=re(T,f);if(k.signedDistanceFromCamera>0)y=h[g]=k.point;else{var A=g-d;y=ue(0===x?o:new t.Point(c.getx(A),c.gety(A)),T,m,_-x+1,f)}}x+=b,b=m.dist(y)}var M=(_-x)/b,S=y.sub(m),E=S.mult(M)._add(m);E._add(S._unit()._perp()._mult(n*d));var L=v+Math.atan2(y.y-m.y,y.x-m.x);return w.push(E),{point:E,angle:L,path:w}}Qt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Qt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Qt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Qt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Qt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Qt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s0:o},Qt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var u=[],c={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(a,s,o,l,this._queryCellCircle,u,c,i),n?u.length>0:u},Qt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Qt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Qt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Qt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,u=this.boxCells[i];if(null!==u)for(var c=this.bboxes,f=0,h=u;f=c[d+0]&&n>=c[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:c[d],y1:c[d+1],x2:c[d+2],y2:c[d+3]})}}}var v=this.circleCells[i];if(null!==v)for(var g=this.circles,y=0,m=v;yo*o+s*s},Qt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var u=(o-i)/2,c=Math.abs(e-(i+u));if(c>u+r)return!1;if(l<=s||c<=u)return!0;var f=l-s,h=c-u;return f*f+h*h<=r*r};var fe=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function he(t,e){for(var r=0;r=1;P--)C.push(E.path[P]);for(var O=1;O0){for(var R=C[0].clone(),F=C[0].clone(),B=1;B=A.x&&F.x<=M.x&&R.y>=A.y&&F.y<=M.y?[C]:F.xM.x||F.yM.y?[]:t.clipLine([C],A.x,A.y,M.x,M.y)}for(var N=0,j=D;N=this.screenRightBoundary||nthis.screenBottomBoundary},ve.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t=0&&e0?(this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(v=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:g,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:v},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:y,placedGlyphBoxes:m}):void 0},Ae.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,u=a.textLabelPlaneMatrix,c=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,v=a.collisionGroup,g=s.get(\"text-optional\"),y=s.get(\"icon-optional\"),m=s.get(\"text-allow-overlap\"),x=s.get(\"icon-allow-overlap\"),b=\"map\"===s.get(\"text-rotation-alignment\"),_=\"map\"===s.get(\"text-pitch-alignment\"),w=\"none\"!==s.get(\"icon-text-fit\"),T=\"viewport-y\"===s.get(\"symbol-z-order\"),k=m&&(x||!o.hasIconData()||y),A=x&&(m||!o.hasTextData()||g);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var M=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new xe(!1,!1,!1);else{var p,T=!1,M=!1,S=!0,E=null,L={box:null,offscreen:null},C={box:null,offscreen:null},P=null,O=null,I=0,z=0,D=0;a.textFeatureIndex?I=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(I=e.featureIndex),a.verticalTextFeatureIndex&&(z=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,n=a,i.markUsedOrientation(o,n,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,u=e.textBoxScale,c=w&&!x?r:null,h={box:[],offscreen:!1},p=m?2*N.length:N.length,d=0;d=N.length,k=i.attemptAnchorPlacement(g,t,a,s,u,b,_,f,l,v,y,e,o,n,c);if(k&&(h=k.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=k.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox,n=L&&L.box&&L.box.length;return o.allowVerticalPlacement&&!n&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),L&&(T=L.box,S=L.offscreen);var V=F(L&&L.box);if(!T&&i.prevPlacement){var q=i.prevPlacement.variableOffsets[e.crossTileID];q&&(i.variableOffsets[e.crossTileID]=q,i.markUsedJustification(o,q.anchor,e,V))}}else{var H=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,m,f,l,v.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return H(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?H(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(L&&L.box&&L.box.length)}}if(T=(p=L)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),W=t.evaluateSizeForFeature(o.textSizeData,d,G),Y=s.get(\"text-padding\"),X=e.collisionCircleDiameter;P=i.collisionIndex.placeCollisionCircles(m,G,o.lineVertexArray,o.glyphOffsetArray,W,l,u,c,n,_,v.predicate,X,Y),T=m||P.circles.length>0&&!P.collisionDetected,S=S&&P.offscreen}if(a.iconFeatureIndex&&(D=a.iconFeatureIndex),a.iconBox){var Z=function(t){var e=w&&E?ke(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,v.predicate)};M=C&&C.box&&C.box.length&&a.verticalIconBox?(O=Z(a.verticalIconBox)).box.length>0:(O=Z(a.iconBox)).box.length>0,S=S&&O.offscreen}var K=g||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,J=y||0===e.numIconVertices;if(K||J?J?K||(M=M&&T):T=M&&T:M=T=M&&T,T&&p&&p.box&&(C&&C.box&&z?i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,z,v.ID):i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,I,v.ID)),M&&O&&i.collisionIndex.insertCollisionBox(O.box,s.get(\"icon-ignore-placement\"),o.bucketInstanceId,D,v.ID),P&&(T&&i.collisionIndex.insertCollisionCircles(P.circles,s.get(\"text-ignore-placement\"),o.bucketInstanceId,I,v.ID),n)){var $=o.bucketInstanceId,Q=i.collisionCircleArrays[$];void 0===Q&&(Q=i.collisionCircleArrays[$]=new be);for(var tt=0;tt=0;--E){var L=S[E];M(o.symbolInstances.get(L),o.collisionArrays[L])}else for(var C=e.symbolInstanceStart;C=0&&(e.text.placedSymbolArray.get(u).crossTileID=a>=0&&u!==a?0:n.crossTileID)}},Ae.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o0||l>0,x=a.numIconVertices>0,b=i.placedOrientations[a.crossTileID],_=b===t.WritingMode.vertical,w=b===t.WritingMode.horizontal||b===t.WritingMode.horizontalOnly;if(m){var T=ze(y.text),k=_?De:T;d(e.text,s,k);var A=w?De:T;d(e.text,l,A);var M=y.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=M||_?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=M||w?1:0);var S=i.variableOffsets[a.crossTileID];S&&i.markUsedJustification(e,S.anchor,a,b);var E=i.placedOrientations[a.crossTileID];E&&(i.markUsedJustification(e,\"left\",a,E),i.markUsedOrientation(e,E,a))}if(x){var L=ze(y.icon),C=!(h&&a.verticalPlacedIconSymbolIndex&&_);if(a.placedIconSymbolIndex>=0){var P=C?L:De;d(e.icon,a.numIconVertices,P),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=y.icon.isHidden()}if(a.verticalPlacedIconSymbolIndex>=0){var O=C?De:L;d(e.icon,a.numVerticalIconVertices,O),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=y.icon.isHidden()}}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var I=e.collisionArrays[n];if(I){var z=new t.Point(0,0);if(I.textBox||I.verticalTextBox){var D=!0;if(u){var R=i.variableOffsets[v];R?(z=Te(R.anchor,R.width,R.height,R.textOffset,R.textBoxScale),c&&z._rotate(f?i.transform.angle:-i.transform.angle)):D=!1}I.textBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!D||_,z.x,z.y),I.verticalTextBox&&Me(e.textCollisionBox.collisionVertexArray,y.text.placed,!D||w,z.x,z.y)}var F=Boolean(!w&&I.verticalIconBox);I.iconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,F,h?z.x:0,h?z.y:0),I.verticalIconBox&&Me(e.iconCollisionBox.collisionVertexArray,y.icon.placed,!F,h?z.x:0,h?z.y:0)}}},g=0;gt},Ae.prototype.setStale=function(){this.stale=!0};var Se=Math.pow(2,25),Ee=Math.pow(2,24),Le=Math.pow(2,17),Ce=Math.pow(2,16),Pe=Math.pow(2,9),Oe=Math.pow(2,8),Ie=Math.pow(2,1);function ze(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*Se+e*Ee+r*Le+e*Ce+r*Pe+e*Oe+r*Ie+e}var De=0,Re=function(t){this._sortAcrossTiles=\"viewport-y\"!==t.layout.get(\"symbol-z-order\")&&void 0!==t.layout.get(\"symbol-sort-key\").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Re.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Re(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},Fe.prototype.commit=function(t){return this.placement.commit(t),this.placement};var Be=512/t.EXTENT/2,Ne=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;nt.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var u=o[t.scaledTo(Number(a)).key];u&&u.findMatches(e.symbolInstances,t,i)}}for(var c=0;c1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,c())})),u=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),(function(t,e){u=null,o||(o=t,a=e,c())}));function c(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],u=l.width,c=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,v=l.stretchX,g=l.stretchY,y=l.content,m=new t.RGBAImage({width:u,height:c});t.RGBAImage.copy(e,m,{x:f,y:h},{x:0,y:0},{width:u,height:c}),r[s]={data:m,pixelRatio:d,sdf:p,stretchX:v,stretchY:g,content:y}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),u&&(u.cancel(),u=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast(\"setImages\",r._availableImages),r.fire(new t.Event(\"data\",{dataType:\"style\"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r0)throw new Error(\"Unimplemented: \"+i.map((function(t){return t.command})).join(\", \")+\".\");return n.forEach((function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this._afterImageUpdated(e)},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this._afterImageUpdated(e)},r.prototype._afterImageUpdated=function(e){this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.dispatcher.broadcast(\"setImages\",this._availableImages),this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0&&this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n))){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Ot(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else{var a;if(\"custom\"===e.type){if(qe(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&\"custom\"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,\"layers.\"+i.id+\".filter\",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;\"geojson\"===o&&i?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o=\"vector\"===a?e.sourceLayer:void 0;\"vector\"!==a||o?r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is required to remove its specific state property.\"))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if(\"vector\"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&\"raster\"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s=0;d--){var v=this._order[d];if(r(v))for(var g=i.length-1;g>=0;g--){var y=i[g].feature;if(n[y.layer.id] 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),nr=_r(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),ir=_r(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\"),ar=_r(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),or=_r(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),sr=_r(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),lr=_r(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),ur=_r(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),cr=_r(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),fr=_r(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggerationFactor=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;float exaggeration=u_zoom < 15.0 ? (u_zoom-15.0)*exaggerationFactor : 0.0;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/pow(2.0,exaggeration+(19.2562-u_zoom));gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),hr=_r(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),pr=_r(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),dr=_r(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp vec2 v_uv;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,v_uv);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;attribute float a_uv_x;attribute float a_split_index;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;uniform float u_image_height;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp vec2 v_uv;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;highp float texel_height=1.0/u_image_height;highp float half_texel_height=0.5*texel_height;v_uv=vec2(a_uv_x,a_split_index*texel_height-half_texel_height);vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),vr=_r(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}\"),gr=_r(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),yr=_r(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),mr=_r(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),xr=_r(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\"),br=_r(\"#define SDF_PX 8.0\\n#define SDF 1.0\\n#define ICON 0.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}\");function _r(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n=e.match(/attribute ([\\w]+) ([\\w]+)/g),i=t.match(/uniform ([\\w]+) ([\\w]+)([\\s]*)([\\w]*)/g),a=e.match(/uniform ([\\w]+) ([\\w]+)([\\s]*)([\\w]*)/g),o=a?a.concat(i):i,s={};return{fragmentSource:t=t.replace(r,(function(t,e,r,n,i){return s[i]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\nvarying \"+r+\" \"+n+\" \"+i+\";\\n#else\\nuniform \"+r+\" \"+n+\" u_\"+i+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+i+\"\\n \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\"})),vertexSource:e=e.replace(r,(function(t,e,r,n,i){var a=\"float\"===n?\"vec2\":\"vec4\",o=i.match(/color/)?\"color\":a;return s[i]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\nuniform lowp float u_\"+i+\"_t;\\nattribute \"+r+\" \"+a+\" a_\"+i+\";\\nvarying \"+r+\" \"+n+\" \"+i+\";\\n#else\\nuniform \"+r+\" \"+n+\" u_\"+i+\";\\n#endif\\n\":\"vec4\"===o?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n \"+i+\" = a_\"+i+\";\\n#else\\n \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n \"+i+\" = unpack_mix_\"+o+\"(a_\"+i+\", u_\"+i+\"_t);\\n#else\\n \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\nuniform lowp float u_\"+i+\"_t;\\nattribute \"+r+\" \"+a+\" a_\"+i+\";\\n#else\\nuniform \"+r+\" \"+n+\" u_\"+i+\";\\n#endif\\n\":\"vec4\"===o?\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n \"+r+\" \"+n+\" \"+i+\" = a_\"+i+\";\\n#else\\n \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+i+\"\\n \"+r+\" \"+n+\" \"+i+\" = unpack_mix_\"+o+\"(a_\"+i+\", u_\"+i+\"_t);\\n#else\\n \"+r+\" \"+n+\" \"+i+\" = u_\"+i+\";\\n#endif\\n\"})),staticAttributes:n,staticUniforms:o}}var wr=Object.freeze({__proto__:null,prelude:Ze,background:Ke,backgroundPattern:Je,circle:$e,clippingMask:Qe,heatmap:tr,heatmapTexture:er,collisionBox:rr,collisionCircle:nr,debug:ir,fill:ar,fillOutline:or,fillOutlinePattern:sr,fillPattern:lr,fillExtrusion:ur,fillExtrusionPattern:cr,hillshadePrepare:fr,hillshade:hr,line:pr,lineGradient:dr,linePattern:vr,lineSDF:gr,raster:yr,symbolIcon:mr,symbolSDF:xr,symbolTextAndIcon:br}),Tr=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};function kr(t){for(var e=[],r=0;r>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}Ar.prototype.draw=function(t,e,r,n,i,a,o,s,l,u,c,f,h,p,d,v){var g,y=t.gl;if(!this.failedToCreate){for(var m in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[m].set(o[m]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(g={},g[y.LINES]=2,g[y.TRIANGLES]=3,g[y.LINE_STRIP]=1,g)[e],b=0,_=c.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new Tr)).bind(t,this,l,p?p.getPaintVertexBuffers():[],u,w.vertexOffset,d,v),y.drawElements(e,w.primitiveLength*x,y.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var Sr=function(e,r,n,i){var a=r.style.light,o=a.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===a.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var u=a.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get(\"intensity\"),u_lightcolor:[u.r,u.g,u.b],u_vertical_gradient:+n,u_opacity:i}},Er=function(e,r,n,i,a,o,s){return t.extend(Sr(e,r,n,i),Mr(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},Lr=function(t){return{u_matrix:t}},Cr=function(e,r,n,i){return t.extend(Lr(e),Mr(n,r,i))},Pr=function(t,e){return{u_matrix:t,u_world:e}},Or=function(e,r,n,i,a){return t.extend(Cr(e,r,n,i),{u_world:a})},Ir=function(e,r,n,i){var a,o,s=e.transform;if(\"map\"===i.paint.get(\"circle-pitch-alignment\")){var l=ge(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===i.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get(\"circle-translate\"),i.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},zr=function(t,e,r){var n=ge(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},Dr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},Rr=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Fr=function(t){return{u_matrix:t}},Br=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:ge(e,1,r),u_intensity:n}},Nr=function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:n,u_color_ramp:i,u_opacity:r.paint.get(\"heatmap-opacity\")}},jr=function(e,r,n){var i=n.paint.get(\"hillshade-shadow-color\"),a=n.paint.get(\"hillshade-highlight-color\"),o=n.paint.get(\"hillshade-accent-color\"),s=n.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===n.paint.get(\"hillshade-illumination-anchor\")&&(s-=e.transform.angle);var l,u,c,f=!e.options.moving;return{u_matrix:e.transform.calculatePosMatrix(r.tileID.toUnwrapped(),f),u_image:0,u_latrange:(l=r.tileID,u=Math.pow(2,l.canonical.z),c=l.canonical.y,[new t.MercatorCoordinate(0,c/u).toLngLat().lat,new t.MercatorCoordinate(0,(c+1)/u).toLngLat().lat]),u_light:[n.paint.get(\"hillshade-exaggeration\"),s],u_shadow:i,u_highlight:a,u_accent:o}},Ur=function(e,r){var n=r.stride,i=t.create();return t.ortho(i,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(i,i,[0,-t.EXTENT,0]),{u_matrix:i,u_image:1,u_dimension:[n,n],u_zoom:e.overscaledZ,u_unpack:r.getUnpackVector()}};var Vr=function(e,r,n){var i=e.transform;return{u_matrix:Yr(e,r,n),u_ratio:1/ge(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},qr=function(e,r,n,i){return t.extend(Vr(e,r,n),{u_image:0,u_image_height:i})},Hr=function(e,r,n,i){var a=e.transform,o=Wr(r,a);return{u_matrix:Yr(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/ge(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},Gr=function(e,r,n,i,a){var o=e.transform,s=e.lineAtlas,l=Wr(r,o),u=\"round\"===n.layout.get(\"line-cap\"),c=s.getDash(i.from,u),f=s.getDash(i.to,u),h=c.width*a.fromScale,p=f.width*a.toScale;return t.extend(Vr(e,r,n),{u_patternscale_a:[l/h,-c.height/2],u_patternscale_b:[l/p,-f.height/2],u_sdfgamma:s.width/(256*Math.min(h,p)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:c.y,u_tex_y_b:f.y,u_mix:a.t})};function Wr(t,e){return 1/ge(t,1,e.tileZoom)}function Yr(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var Xr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get(\"raster-brightness-min\"),u_brightness_high:i.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=i.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get(\"raster-contrast\"),a>0?1/(1-a):1+a),u_spin_weights:Zr(i.paint.get(\"raster-hue-rotate\"))};var a,o};function Zr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Kr,Jr=function(t,e,r,n,i,a,o,s,l,u){var c=i.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:c.cameraToCenterDistance,u_pitch:c.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:c.width/c.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:u,u_texture:0}},$r=function(e,r,n,i,a,o,s,l,u,c,f){var h=a.transform;return t.extend(Jr(e,r,n,i,a,o,s,l,u,c),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},Qr=function(e,r,n,i,a,o,s,l,u,c){return t.extend($r(e,r,n,i,a,o,s,l,!0,u,!0),{u_texsize_icon:c,u_texture_icon:1})},tn=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},en=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,u=Math.pow(2,n.tileID.overscaledZ),c=n.tileSize*Math.pow(2,r.transform.tileZoom)/u,f=c*(n.tileID.canonical.x+n.tileID.wrap*u),h=c*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/ge(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},rn={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image),u_image_height:new t.Uniform1f(e,r.u_image_height)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function nn(e,r,n,i,a,o,s){for(var l=e.context,u=l.gl,c=e.useProgram(\"collisionBox\"),f=[],h=0,p=0,d=0;d0){var _=t.create(),w=m;t.mul(_,y.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,y.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&c.draw(l,u.LINES,Mt.disabled,Et.disabled,e.colorModeForRenderPass(),Ct.disabled,zr(m,e.transform,g),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram(\"collisionCircle\"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var A=0,M=0,S=f;M=0&&(v[y.associatedIconIndex]={shiftedAnchor:S,angle:E})}else he(y.numGlyphs,p)}if(f){d.clear();for(var C=e.icon.placedSymbolArray,P=0;P0){var s=t.browser.now(),l=(s-e.timeAdded)/o,u=r?(s-r.timeAdded)/o:-1,c=n.getSource(),f=a.coveringZoomLevel({tileSize:c.tileSize,roundZoom:c.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-u,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var gn=new t.Color(1,0,0,1),yn=new t.Color(0,1,0,1),mn=new t.Color(0,0,1,1),xn=new t.Color(1,0,1,1),bn=new t.Color(0,1,1,1);function _n(t){var e=t.transform.padding;wn(t,t.transform.height-(e.top||0),3,gn),wn(t,e.bottom||0,3,yn),Tn(t,e.left||0,3,mn),Tn(t,t.transform.width-(e.right||0),3,xn);var r=t.transform.centerPoint;!function(t,e,r,n){var i=20,a=2;kn(t,e-a/2,r-i/2,a,i,n),kn(t,e-i/2,r-a/2,i,a,n)}(t,r.x,t.transform.height-r.y,bn)}function wn(t,e,r,n){kn(t,0,e+r/2,t.transform.width,r,n)}function Tn(t,e,r,n){kn(t,e-r/2,0,r,t.transform.height,n)}function kn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function An(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=Mt.disabled,u=Et.disabled,c=e.colorModeForRenderPass(),f=\"$debug\";i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,u,c,Ct.disabled,Rr(o,t.Color.red),f,e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var h=r.getTileByID(n.key).latestRawTileData,p=h&&h.byteLength||0,d=Math.floor(p/1024),v=r.getTile(n).tileSize,g=512/Math.min(v,512)*(n.overscaledZ/e.transform.zoom)*.5,y=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(y+=\" => \"+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext(\"2d\");i.clearRect(0,0,r.width,r.height),i.shadowColor=\"white\",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle=\"white\",i.textBaseline=\"top\",i.font=\"bold 36px Open Sans, sans-serif\",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,y+\" \"+d+\"kb\"),s.draw(i,a.TRIANGLES,l,u,Lt.alphaBlended,Ct.disabled,Rr(o,t.Color.transparent,g),f,e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var Mn={symbol:function(e,r,n,i,a){if(\"translucent\"===e.renderPass){var o=Et.disabled,s=e.colorModeForRenderPass();n.layout.get(\"text-variable-anchor\")&&function(e,r,n,i,a,o,s){for(var l=r.transform,u=\"map\"===a,c=\"map\"===o,f=0,h=e;f256&&this.clearStencil(),r.setColorMode(Lt.disabled),r.setDepthMode(Mt.disabled);var i=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var a=0,o=e;a256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new Et({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},Sn.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new Et({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},Sn.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s=0;this.currentLayer--){var w=this.style._layers[i[this.currentLayer]],T=a[w.source],k=c[w.source];this._renderTileClippingMasks(w,k),this.renderLayer(this,T,w,k)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer0?e.pop():null},Sn.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},Sn.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e?e.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new Ar(this.context,t,wr[t],e,rn[t],this._showOverdrawInspector)),this.cache[r]},Sn.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},Sn.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},Sn.prototype.initDebugOverlayCanvas=function(){if(null==this.debugOverlayCanvas){this.debugOverlayCanvas=t.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var e=this.context.gl;this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,e.RGBA)}},Sn.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var En=function(t,e){this.points=t,this.planes=e};En.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new En(a,o)};var Ln=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};Ln.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var u=Number.MAX_VALUE,c=-Number.MAX_VALUE,f=0;fthis.max[l]-this.min[l])return 0}return 1};var Cn=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=t,this.bottom=e,this.left=r,this.right=n};Cn.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},Cn.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},Cn.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},Cn.prototype.clone=function(){return new Cn(this.top,this.bottom,this.left,this.right)},Cn.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var Pn=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new Cn,this._posMatrixCache={},this._alignedPosMatrixCache={}},On={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};Pn.prototype.clone=function(){var t=new Pn(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},On.minZoom.get=function(){return this._minZoom},On.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},On.maxZoom.get=function(){return this._maxZoom},On.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},On.minPitch.get=function(){return this._minPitch},On.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},On.maxPitch.get=function(){return this._maxPitch},On.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},On.renderWorldCopies.get=function(){return this._renderWorldCopies},On.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},On.worldSize.get=function(){return this.tileSize*this.scale},On.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},On.size.get=function(){return new t.Point(this.width,this.height)},On.bearing.get=function(){return-this.angle/Math.PI*180},On.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},On.pitch.get=function(){return this._pitch/Math.PI*180},On.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},On.fov.get=function(){return this._fov/Math.PI*180},On.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},On.zoom.get=function(){return this._zoom},On.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},On.center.get=function(){return this._center},On.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},On.padding.get=function(){return this._edgeInsets.toJSON()},On.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},On.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},Pn.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},Pn.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},Pn.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},Pn.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),u=s-1;u<=l+1;u++)0!==u&&r.push(new t.UnwrappedTileID(u,e));return r},Pn.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&re.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=En.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var u=function(t){return{aabb:new Ln([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},c=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)c.push(u(-d)),c.push(u(d));for(c.push(u(0));c.length>0;){var v=c.pop(),g=v.x,y=v.y,m=v.fullyVisible;if(!m){var x=v.aabb.intersects(s);if(0===x)continue;m=2===x}var b=v.aabb.distanceX(o),_=v.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_)),T=3+(1<T&&v.zoom>=l)f.push({tileID:new t.OverscaledTileID(v.zoom===h?p:v.zoom,v.wrap,v.zoom,g,y),distanceSq:t.sqrLen([o[0]-.5-g,o[1]-.5-y])});else for(var k=0;k<4;k++){var A=(g<<1)+k%2,M=(y<<1)+(k>>1);c.push({aabb:v.aabb.quadrant(k),zoom:v.zoom+1,x:A,y:M,wrap:v.wrap,fullyVisible:m})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},Pn.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},On.unmodified.get=function(){return this._unmodified},Pn.prototype.zoomScale=function(t){return Math.pow(2,t)},Pn.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},Pn.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},Pn.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},On.point.get=function(){return this.project(this.center)},Pn.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},Pn.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},Pn.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},Pn.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},Pn.prototype.coordinateLocation=function(t){return t.toLngLat()},Pn.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[0]/i,s=n[0]/a,l=r[1]/i,u=n[1]/a,c=r[2]/i,f=n[2]/a,h=c===f?0:(0-c)/(f-c);return new t.MercatorCoordinate(t.number(o,s,h)/this.worldSize,t.number(l,u,h)/this.worldSize)},Pn.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},Pn.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},Pn.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},Pn.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},Pn.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},Pn.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},Pn.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,u=this.size,c=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-ao&&(i=o-g)}if(this.lngRange){var y=p.x,m=u.x/2;y-ml&&(n=l-m)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=c,this._constraining=!1}},Pn.prototype._calcMatrices=function(){if(this.height){var e=this._fov/2,r=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(e)*this.height;var n=Math.PI/2+this._pitch,i=this._fov*(.5+r.y/this.height),a=Math.sin(i)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-n-i,.01,Math.PI-.01)),o=this.point,s=o.x,l=o.y,u=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),c=this.height/50,f=new Float64Array(16);t.perspective(f,this._fov,this.width/this.height,c,u),f[8]=2*-r.x/this.width,f[9]=2*r.y/this.height,t.scale(f,f,[1,-1,1]),t.translate(f,f,[0,0,-this.cameraToCenterDistance]),t.rotateX(f,f,this._pitch),t.rotateZ(f,f,this.angle),t.translate(f,f,[-s,-l,0]),this.mercatorMatrix=t.scale([],f,[this.worldSize,this.worldSize,this.worldSize]),t.scale(f,f,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=f,this.invProjMatrix=t.invert([],this.projMatrix);var h=this.width%2/2,p=this.height%2/2,d=Math.cos(this.angle),v=Math.sin(this.angle),g=s-Math.round(s)+d*h+v*p,y=l-Math.round(l)+d*p+v*h,m=new Float64Array(f);if(t.translate(m,m,[g>.5?g-1:g,y>.5?y-1:y,0]),this.alignedProjMatrix=m,f=t.create(),t.scale(f,f,[this.width/2,-this.height/2,1]),t.translate(f,f,[1,-1,0]),this.labelPlaneMatrix=f,f=t.create(),t.scale(f,f,[1,-1,1]),t.translate(f,f,[-1,-1,0]),t.scale(f,f,[2/this.width,2/this.height,1]),this.glCoordMatrix=f,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(f=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=f,this._posMatrixCache={},this._alignedPosMatrixCache={}}},Pn.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},Pn.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},Pn.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},In.prototype._updateHashUnthrottled=function(){var e=t.window.location.href.replace(/(#.+)?$/,this.getHashString());try{t.window.history.replaceState(t.window.history.state,null,e)}catch(t){}};var zn={linearity:.3,easing:t.bezier(0,0,.3,1)},Dn=t.extend({deceleration:2500,maxSpeed:1400},zn),Rn=t.extend({deceleration:20,maxSpeed:1400},zn),Fn=t.extend({deceleration:1e3,maxSpeed:360},zn),Bn=t.extend({deceleration:1e3,maxSpeed:90},zn),Nn=function(t){this._map=t,this.clear()};function jn(t,e){(!t.duration||t.duration0&&r-e[0].time>160;)e.shift()},Nn.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n=this._clickTolerance||this._map.fire(new Vn(t.type,this._map,t))},Gn.prototype.dblclick=function(t){return this._firePreventable(new Vn(t.type,this._map,t))},Gn.prototype.mouseover=function(t){this._map.fire(new Vn(t.type,this._map,t))},Gn.prototype.mouseout=function(t){this._map.fire(new Vn(t.type,this._map,t))},Gn.prototype.touchstart=function(t){return this._firePreventable(new qn(t.type,this._map,t))},Gn.prototype.touchmove=function(t){this._map.fire(new qn(t.type,this._map,t))},Gn.prototype.touchend=function(t){this._map.fire(new qn(t.type,this._map,t))},Gn.prototype.touchcancel=function(t){this._map.fire(new qn(t.type,this._map,t))},Gn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},Gn.prototype.isEnabled=function(){return!0},Gn.prototype.isActive=function(){return!1},Gn.prototype.enable=function(){},Gn.prototype.disable=function(){};var Wn=function(t){this._map=t};Wn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},Wn.prototype.mousemove=function(t){this._map.fire(new Vn(t.type,this._map,t))},Wn.prototype.mousedown=function(){this._delayContextMenu=!0},Wn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new Vn(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},Wn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new Vn(t.type,this._map,t)),this._map.listens(\"contextmenu\")&&t.preventDefault()},Wn.prototype.isEnabled=function(){return!0},Wn.prototype.isActive=function(){return!1},Wn.prototype.enable=function(){},Wn.prototype.disable=function(){};var Yn=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Xn(t,e){for(var r={},n=0;nthis.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n30)&&(this.aborted=!0)}}},Zn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Kn=function(t){this.singleTap=new Zn(t),this.numTaps=t.numTaps,this.reset()};Kn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Kn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Kn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Kn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Jn=function(){this._zoomIn=new Kn({numTouches:1,numTaps:2}),this._zoomOut=new Kn({numTouches:2,numTaps:1}),this.reset()};Jn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Jn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Jn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Jn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Jn.prototype.touchcancel=function(){this.reset()},Jn.prototype.enable=function(){this._enabled=!0},Jn.prototype.disable=function(){this._enabled=!1,this.reset()},Jn.prototype.isEnabled=function(){return this._enabled},Jn.prototype.isActive=function(){return this._active};var $n={};$n[0]=1,$n[2]=2;var Qn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};Qn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},Qn.prototype._correctButton=function(t,e){return!1},Qn.prototype._move=function(t,e){return{}},Qn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},Qn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r)if(t.preventDefault(),function(t,e){var r=$n[e];return void 0===t.buttons||(t.buttons&r)!==r}(t,this._eventButton))this.reset();else if(this._moved||!(e.dist(r)0&&(this._active=!0);var i=Xn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var u=i[l],c=this._touches[l];c&&(a._add(u),o._add(u.sub(c)),s++,i[l]=u)}if(this._touches=i,!(sMath.abs(t.x)}var fi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,ci(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid)return this._lastPoints=t,this._active=!0,{pitchDelta:(n.y+i.y)/2*-.5}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return ci(t)&&ci(e)&&a}},e}(ii),hi={panStep:100,bearingStep:15,pitchStep:10},pi=function(){var t=hi;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep,this._rotationDisabled=!1};function di(t){return t*(2-t)}pi.prototype.reset=function(){this._active=!1},pi.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return this._rotationDisabled&&(n=0,i=0),{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:\"keyboardHandler\",easing:di,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},pi.prototype.enable=function(){this._enabled=!0},pi.prototype.disable=function(){this._enabled=!1,this.reset()},pi.prototype.isEnabled=function(){return this._enabled},pi.prototype.isActive=function(){return this._active},pi.prototype.disableRotation=function(){this._rotationDisabled=!0},pi.prototype.enableRotation=function(){this._rotationDisabled=!1};var vi=4.000244140625,gi=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=.0022222222222222222,t.bindAll([\"_onTimeout\"],this)};gi.prototype.setZoomRate=function(t){this._defaultZoomRate=t},gi.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},gi.prototype.isEnabled=function(){return!!this._enabled},gi.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},gi.prototype.isZooming=function(){return!!this._zooming},gi.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},gi.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},gi.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%vi==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},gi.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(t)},gi.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},gi.prototype.renderFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>vi?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,u=this._easing,c=!1;if(\"wheel\"===this._type&&l&&u){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=u(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):c=!0}else o=s,c=!0;return this._active=!0,c&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!c,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},gi.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},gi.prototype.reset=function(){this._active=!1};var yi=function(t,e){this._clickZoom=t,this._tapZoom=e};yi.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},yi.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},yi.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},yi.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var mi=function(){this.reset()};mi.prototype.reset=function(){this._active=!1},mi.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},mi.prototype.enable=function(){this._enabled=!0},mi.prototype.disable=function(){this._enabled=!1,this.reset()},mi.prototype.isEnabled=function(){return this._enabled},mi.prototype.isActive=function(){return this._active};var xi=function(){this._tap=new Kn({numTouches:1,numTaps:1}),this.reset()};xi.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},xi.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},xi.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},xi.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},xi.prototype.touchcancel=function(){this.reset()},xi.prototype.enable=function(){this._enabled=!0},xi.prototype.disable=function(){this._enabled=!1,this.reset()},xi.prototype.isEnabled=function(){return this._enabled},xi.prototype.isActive=function(){return this._active};var bi=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};bi.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},bi.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},bi.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},bi.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var _i=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};_i.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},_i.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},_i.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},_i.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var wi=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};wi.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},wi.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},wi.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},wi.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},wi.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},wi.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var Ti=function(t){return t.zoom||t.drag||t.pitch||t.rotate},ki=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(t.Event);function Ai(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var Mi=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Nn(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var i=this._el;this._listeners=[[i,\"touchstart\",{passive:!0}],[i,\"touchmove\",{passive:!1}],[i,\"touchend\",void 0],[i,\"touchcancel\",void 0],[i,\"mousedown\",void 0],[i,\"mousemove\",void 0],[i,\"mouseup\",void 0],[t.window.document,\"mousemove\",{capture:!0}],[t.window.document,\"mouseup\",void 0],[i,\"mouseover\",void 0],[i,\"mouseout\",void 0],[i,\"dblclick\",void 0],[i,\"click\",void 0],[i,\"keydown\",{capture:!1}],[i,\"keyup\",void 0],[i,\"wheel\",{passive:!1}],[i,\"contextmenu\",void 0],[t.window,\"blur\",void 0]];for(var a=0,o=this._listeners;aa?Math.min(2,_):Math.max(.5,_),w=Math.pow(g,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(v));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event(\"movestart\",e)),this._zooming&&!n.zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&!n.rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&!n.pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event(\"zoomend\",e)),i&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),u=this.getPadding(),c=\"zoom\"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,p=\"padding\"in e?e.padding:a.padding,d=a.zoomScale(c-o),v=t.Point.convert(e.offset),g=a.centerPoint.add(v),y=a.pointLocation(g),m=t.LngLat.convert(e.center||y);this._normalizeCenter(m);var x=a.project(y),b=a.project(m).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if(\"minZoom\"in e){var A=t.clamp(Math.min(e.minZoom,o,c),a.minZoom,a.maxZoom),M=w/a.zoomScale(A-o);_=Math.sqrt(M/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function L(t){return(Math.exp(t)-Math.exp(-t))/2}function C(t){return(Math.exp(t)+Math.exp(-t))/2}var P=E(0),O=function(t){return C(P)/C(P+_*t)},I=function(t){return w*((C(P)*(L(e=P+_*t)/C(e))-L(P))/S)/k;var e},z=(E(1)-P)/_;if(Math.abs(k)<1e-6||!isFinite(z)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var D=Te.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*z,d=1/O(i);a.zoom=1===e?c:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(u,p,e),g=a.centerPoint.add(v));var y=1===e?m:a.unproject(x.add(b.mult(I(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?y.wrap():y,g),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop(!1)}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)180?-360:r<-180?360:0}},r}(t.Evented),Ei=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_toggleAttribution\",\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};Ei.prototype.getDefaultPosition=function(){return\"bottom-right\"},Ei.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._compactButton=r.create(\"button\",\"mapboxgl-ctrl-attrib-button\",this._container),this._compactButton.addEventListener(\"click\",this._toggleAttribution),this._setElementTitle(this._compactButton,\"ToggleAttribution\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),this._innerContainer.setAttribute(\"role\",\"list\"),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},Ei.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},Ei.prototype._setElementTitle=function(t,e){var r=this._map._getUIString(\"AttributionControl.\"+e);t.title=r,t.setAttribute(\"aria-label\",r)},Ei.prototype._toggleAttribution=function(){this._container.classList.contains(\"mapboxgl-compact-show\")?(this._container.classList.remove(\"mapboxgl-compact-show\"),this._compactButton.setAttribute(\"aria-pressed\",\"false\")):(this._container.classList.add(\"mapboxgl-compact-show\"),this._compactButton.setAttribute(\"aria-pressed\",\"true\"))},Ei.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n=0)return!1;return!0}))).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},Ei.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\",\"mapboxgl-compact-show\")};var Li=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};Li.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},Li.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},Li.prototype.getDefaultPosition=function(){return\"bottom-left\"},Li.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},Li.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t)if(t[e].getSource().mapbox_logo)return!0;return!1}},Li.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var Ci=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};Ci.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},Ci.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;re.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(null!=e.minPitch&&e.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(null!=e.maxPitch&&e.maxPitch>Di)throw new Error(\"maxPitch must be less than or equal to 60\");var i=new Pn(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new Ci,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},Pi,e.locale),this._clickTolerance=e.clickTolerance,this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof Ii))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_onMapScroll\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",(function(){return r._update(!1)})),this.on(\"moveend\",(function(){return r._update(!1)})),this.on(\"zoom\",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1),t.window.addEventListener(\"orientationchange\",this._onWindowResize,!1)),this.handlers=new Mi(this,e);var a=\"string\"==typeof e.hash&&e.hash||void 0;this._hash=e.hash&&new In(a).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new Ei({customAttribution:e.customAttribution})),this.addControl(new Li,e.logoPosition),this.on(\"style.load\",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on(\"data\",(function(e){r._update(\"style\"===e.dataType),r.fire(new t.Event(e.dataType+\"data\",e))})),this.on(\"dataloading\",(function(e){r.fire(new t.Event(e.dataType+\"dataloading\",e))}))}n&&(i.__proto__=n),i.prototype=Object.create(n&&n.prototype),i.prototype.constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&(r=e.getDefaultPosition?e.getDefaultPosition():\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.hasControl=function(t){return this._controls.indexOf(t)>-1},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e))),this.fire(new t.Event(\"resize\",e)),a&&this.fire(new t.Event(\"moveend\",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()Di)throw new Error(\"maxPitch must be less than or equal to 60\");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if(\"mouseenter\"===t||\"mouseover\"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new Vn(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new Vn(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new Vn(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;if(void 0===r)return n.prototype.off.call(this,t,e);return this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ui.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ui.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ui.prototype.off=function(){var t=this.element;r.removeEventListener(t,\"mousedown\",this.mousedown),r.removeEventListener(t,\"touchstart\",this.touchstart,{passive:!1}),r.removeEventListener(t,\"touchmove\",this.touchmove),r.removeEventListener(t,\"touchend\",this.touchend),r.removeEventListener(t,\"touchcancel\",this.reset),this.offTemp()},Ui.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,\"mousemove\",this.mousemove),r.removeEventListener(t.window,\"mouseup\",this.mouseup)},Ui.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,\"mousemove\",this.mousemove),r.addEventListener(t.window,\"mouseup\",this.mouseup)},Ui.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ui.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ui.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ui.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ui.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)=r}this._isDragging&&(this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",\"pending\"===this._state&&(this._state=\"active\",this.fire(new t.Event(\"dragstart\"))),this.fire(new t.Event(\"drag\")))},n.prototype._onUp=function(){this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._pointerdownPos=null,this._isDragging=!1,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),\"active\"===this._state&&this.fire(new t.Event(\"dragend\")),this._state=\"inactive\"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._pointerdownPos=t.point,this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||\"auto\",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&\"auto\"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Yi={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0};var Xi=0,Zi=!1,Ki=function(e){function n(r){e.call(this),this.options=t.extend({},Yi,r),t.bindAll([\"_onSuccess\",\"_onError\",\"_onZoom\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.onAdd=function(e){return this._map=e,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),n=this._setupUI,void 0!==Gi?n(Gi):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:\"geolocation\"}).then((function(t){Gi=\"denied\"!==t.state,n(Gi)})):(Gi=!!t.window.navigator.geolocation,n(Gi)),this._container;var n},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off(\"zoom\",this._onZoom),this._map=void 0,Xi=0,Zi=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitudee.getEast()||r.latitudee.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event(\"outofmaxbounds\",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+\"px\",this._circleElement.style.height=i+\"px\"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var r=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=r,this._geolocateButton.setAttribute(\"aria-label\",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&Zi)return;this._setErrorState()}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",!1===e){t.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var i=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute(\"aria-label\",i)}else{var a=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=a,this._geolocateButton.setAttribute(\"aria-label\",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new Wi(this._dotElement),this._circleElement=r.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new Wi({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",(function(e){var r=e.originalEvent&&\"resize\"===e.originalEvent.type;e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||r||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":Xi--,Zi=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}if(\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),++Xi>1?(e={maximumAge:6e5,timeout:0},Zi=!0):(e=this.options.positionOptions,Zi=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Ji={maxWidth:100,unit:\"metric\"},$i=function(e){this.options=t.extend({},Ji,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function Qi(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&\"imperial\"===r.unit){var l=3.2808*s;l>5280?ta(e,n,l/5280,t._getUIString(\"ScaleControl.Miles\")):ta(e,n,l,t._getUIString(\"ScaleControl.Feet\"))}else r&&\"nautical\"===r.unit?ta(e,n,s/1852,t._getUIString(\"ScaleControl.NauticalMiles\")):s>=1e3?ta(e,n,s/1e3,t._getUIString(\"ScaleControl.Kilometers\")):ta(e,n,s,t._getUIString(\"ScaleControl.Meters\"))}function ta(t,e,r,n){var i,a,o,s=(i=r,(a=Math.pow(10,(\"\"+Math.floor(i)).length-1))*((o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o))),l=s/r;t.style.width=e*l+\"px\",t.innerHTML=s+\" \"+n}$i.prototype.getDefaultPosition=function(){return\"bottom-left\"},$i.prototype._onMove=function(){Qi(this._map,this._container,this.options)},$i.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",t.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},$i.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},$i.prototype.setUnit=function(t){this.options.unit=t,Qi(this._map,this._container,this.options)};var ea=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce(\"Full screen control 'container' must be a DOM element.\")),t.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in t.window.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in t.window.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in t.window.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in t.window.document&&(this._fullscreenchange=\"MSFullscreenChange\")};ea.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},ea.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},ea.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},ea.prototype._setupUI=function(){var e=this._fullscreenButton=r.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);r.create(\"span\",\"mapboxgl-ctrl-icon\",e).setAttribute(\"aria-hidden\",!0),e.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},ea.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},ea.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},ea.prototype._isFullscreen=function(){return this._fullscreen},ea.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},ea.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var ra={closeButton:!0,closeOnClick:!0,focusAfterOpen:!0,className:\"\",maxWidth:\"240px\"},na=[\"a[href]\",\"[tabindex]:not([tabindex='-1'])\",\"[contenteditable]:not([contenteditable='false'])\",\"button:not([disabled])\",\"input:not([disabled])\",\"select:not([disabled])\",\"textarea:not([disabled])\"].join(\", \"),ia=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(ra),r),t.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._focusFirstElement(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){if(this._content)for(;this._content.hasChildNodes();)this._content.firstChild&&this._content.removeChild(this._content.firstChild);else this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container);return this._content.appendChild(t),this._createCloseButton(),this._update(),this._focusFirstElement(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.setOffset=function(t){return this.options.offset=t,this._update(),this},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createCloseButton=function(){this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"×\",this._closeButton.addEventListener(\"click\",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(t){var e=this,n=this._lngLat||this._trackPointer;if(this._map&&n&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach((function(t){return e._container.classList.add(t)})),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=Vi(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||t)){var i=this._pos=this._trackPointer&&t?t:this._map.project(this._lngLat),a=this.options.anchor,o=aa(this.options.offset);if(!a){var s,l=this._container.offsetWidth,u=this._container.offsetHeight;s=i.y+o.bottom.ythis._map.transform.height-u?[\"bottom\"]:[],i.xthis._map.transform.width-l/2&&s.push(\"right\"),a=0===s.length?\"bottom\":s.join(\"-\")}var c=i.add(o[a]).round();r.setTransform(this._container,qi[a]+\" translate(\"+c.x+\"px,\"+c.y+\"px)\"),Hi(this._container,a,\"popup\")}},n.prototype._focusFirstElement=function(){if(this.options.focusAfterOpen&&this._container){var t=this._container.querySelector(na);t&&t.focus()}},n.prototype._onClose=function(){this.remove()},n}(t.Evented);function aa(e){if(e){if(\"number\"==typeof e){var r=Math.round(Math.sqrt(.5*Math.pow(e,2)));return{center:new t.Point(0,0),top:new t.Point(0,e),\"top-left\":new t.Point(r,r),\"top-right\":new t.Point(-r,r),bottom:new t.Point(0,-e),\"bottom-left\":new t.Point(r,-r),\"bottom-right\":new t.Point(-r,-r),left:new t.Point(e,0),right:new t.Point(-e,0)}}if(e instanceof t.Point||Array.isArray(e)){var n=t.Point.convert(e);return{center:n,top:n,\"top-left\":n,\"top-right\":n,bottom:n,\"bottom-left\":n,\"bottom-right\":n,left:n,right:n}}return{center:t.Point.convert(e.center||[0,0]),top:t.Point.convert(e.top||[0,0]),\"top-left\":t.Point.convert(e[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(e[\"top-right\"]||[0,0]),bottom:t.Point.convert(e.bottom||[0,0]),\"bottom-left\":t.Point.convert(e[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(e[\"bottom-right\"]||[0,0]),left:t.Point.convert(e.left||[0,0]),right:t.Point.convert(e.right||[0,0])}}return aa(new t.Point(0,0))}var oa={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:Fi,NavigationControl:ji,GeolocateControl:Ki,AttributionControl:Ei,ScaleControl:$i,FullscreenControl:ea,Popup:ia,Marker:Wi,Style:Ye,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){jt().acquire(Rt)},clearPrewarmedResources:function(){var t=Bt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(Rt),Bt=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. 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_=h.seg.myFill;h.seg.myFill=h.seg.otherFill,h.seg.otherFill=_}f.push(h.seg)}a.getHead().remove()}return r&&r.done(),f}return t?{addRegion:function(t){for(var n,i,a,o=t[t.length-1],l=0;l0&&!this.aborted;){var r=this.ifds_to_read.shift();r.offset&&this.scan_ifd(r.id,r.offset,t)}},n.prototype.read_uint16=function(t){var r=this.input;if(t+2>r.length)throw e(\"unexpected EOF\",\"EBADDATA\");return this.big_endian?256*r[t]+r[t+1]:r[t]+256*r[t+1]},n.prototype.read_uint32=function(t){var r=this.input;if(t+4>r.length)throw e(\"unexpected EOF\",\"EBADDATA\");return this.big_endian?16777216*r[t]+65536*r[t+1]+256*r[t+2]+r[t+3]:r[t]+256*r[t+1]+65536*r[t+2]+16777216*r[t+3]},n.prototype.is_subifd_link=function(t,e){return 0===t&&34665===e||0===t&&34853===e||34665===t&&40965===e},n.prototype.exif_format_length=function(t){switch(t){case 1:case 2:case 6:case 7:return 1;case 3:case 8:return 2;case 4:case 9:case 11:return 4;case 5:case 10:case 12:return 8;default:return 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normalWidth * currNormal * .5;\\n\\t\\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\taBotCoord -= normalWidth * startBotJoin;\\n\\t\\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\\n\\t}\\n\\n\\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\\n\\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\\n\\n\\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\\n\\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\\n\\n\\t//position is normalized 0..1 coord on the screen\\n\\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\\n\\n\\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\\n\\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\\n\\n\\t//bevel miter cutoffs\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x) / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n\\n\\t//round miter cutoffs\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x) / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n}\\n\",frag:\"\\nprecision highp float;\\n\\nuniform float dashLength, pixelRatio, thickness, opacity, id, miterMode;\\nuniform sampler2D dashTexture;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nvoid main() {\\n\\tfloat alpha = 1., distToStart, distToEnd;\\n\\tfloat cutoff = thickness * .5;\\n\\n\\t//bevel miter\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToStart + 1., 0.), 1.);\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToEnd + 1., 0.), 1.);\\n\\t\\t}\\n\\t}\\n\\n\\t// round miter\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - startCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - endCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25;\\n\\tfloat dash = texture2D(dashTexture, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\",attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1},bColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:4,divisor:1},prevCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:0,divisor:1},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},nextCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:24,divisor:1}}},n))}catch(t){e=i}return{fill:t({primitive:\"triangle\",elements:function(t,e){return e.triangles},offset:0,vert:\"\\nprecision highp float;\\n\\nattribute vec2 position, positionFract;\\n\\nuniform vec4 color;\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio, id;\\nuniform vec4 viewport;\\nuniform float opacity;\\n\\nvarying vec4 fragColor;\\n\\nconst float MAX_LINES = 256.;\\n\\nvoid main() {\\n\\tfloat depth = (MAX_LINES - 4. - id) / (MAX_LINES);\\n\\n\\tvec2 position = position * scale + translate\\n + positionFract * scale + translateFract\\n + position * scaleFract\\n + positionFract * scaleFract;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n\\tfragColor.a *= opacity;\\n}\\n\",frag:\"\\nprecision highp float;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n\\tgl_FragColor = 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n.add(4-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=i.year(),e=i.month(),r=i.day(),t<0&&t++,e<=2&&(t--,e+=12),Math.floor(365.25*(t+4716))+Math.floor(30.6001*(e+1))+r-1524.5},fromJD:function(t){var e=Math.floor(t+.5)+1524,r=Math.floor((e-122.1)/365.25),n=Math.floor(365.25*r),i=Math.floor((e-n)/30.6001),a=i-Math.floor(i<14?1:13),o=r-Math.floor(a>2?4716:4715),s=e-n-Math.floor(30.6001*i);return o<=0&&o--,this.newDate(o,a,s)}}),n.calendars.julian=a},65616:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}function o(t,e){return t-e*Math.floor(t/e)}function s(t,e){return o(t-1,e)+1}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Mayan\",jdEpoch:584282.5,hasYearZero:!0,minMonth:0,firstMonth:0,minDay:0,regionalOptions:{\"\":{name:\"Mayan\",epochs:[\"\",\"\"],monthNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],monthNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\"],dayNames:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesShort:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],dayNamesMin:[\"0\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\",\"14\",\"15\",\"16\",\"17\",\"18\",\"19\"],digits:null,dateFormat:\"YYYY.m.d\",firstDay:0,isRTL:!1,haabMonths:[\"Pop\",\"Uo\",\"Zip\",\"Zotz\",\"Tzec\",\"Xul\",\"Yaxkin\",\"Mol\",\"Chen\",\"Yax\",\"Zac\",\"Ceh\",\"Mac\",\"Kankin\",\"Muan\",\"Pax\",\"Kayab\",\"Cumku\",\"Uayeb\"],tzolkinMonths:[\"Imix\",\"Ik\",\"Akbal\",\"Kan\",\"Chicchan\",\"Cimi\",\"Manik\",\"Lamat\",\"Muluc\",\"Oc\",\"Chuen\",\"Eb\",\"Ben\",\"Ix\",\"Men\",\"Cib\",\"Caban\",\"Etznab\",\"Cauac\",\"Ahau\"]}},leapYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),!0},extraInfo:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate).toJD(),a=this._toHaab(i),o=this._toTzolkin(i);return{haabMonthName:this.local.haabMonths[a[0]-1],haabMonth:a[0],haabDay:a[1],tzolkinDayName:this.local.tzolkinMonths[o[0]-1],tzolkinDay:o[0],tzolkinTrecena:o[1]}},_toHaab:function(t){var e=o(8+(t-=this.jdEpoch)+340,365);return[Math.floor(e/20)+1,o(e,20)]},_toTzolkin:function(t){return[s(20+(t-=this.jdEpoch),20),s(t+4,13)]},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return i.day()+20*i.month()+360*i.year()+this.jdEpoch},fromJD:function(t){t=Math.floor(t)+.5-this.jdEpoch;var e=Math.floor(t/360);t%=360,t+=t<0?360:0;var r=Math.floor(t/20),n=t%20;return this.newDate(e,r,n)}}),n.calendars.mayan=a},30632:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar;var o=n.instance(\"gregorian\");i(a.prototype,{name:\"Nanakshahi\",jdEpoch:2257673.5,daysPerMonth:[31,31,31,31,31,30,30,30,30,30,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Nanakshahi\",epochs:[\"BN\",\"AN\"],monthNames:[\"Chet\",\"Vaisakh\",\"Jeth\",\"Harh\",\"Sawan\",\"Bhadon\",\"Assu\",\"Katak\",\"Maghar\",\"Poh\",\"Magh\",\"Phagun\"],monthNamesShort:[\"Che\",\"Vai\",\"Jet\",\"Har\",\"Saw\",\"Bha\",\"Ass\",\"Kat\",\"Mgr\",\"Poh\",\"Mgh\",\"Pha\"],dayNames:[\"Somvaar\",\"Mangalvar\",\"Budhvaar\",\"Veervaar\",\"Shukarvaar\",\"Sanicharvaar\",\"Etvaar\"],dayNamesShort:[\"Som\",\"Mangal\",\"Budh\",\"Veer\",\"Shukar\",\"Sanichar\",\"Et\"],dayNamesMin:[\"So\",\"Ma\",\"Bu\",\"Ve\",\"Sh\",\"Sa\",\"Et\"],digits:null,dateFormat:\"dd-mm-yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[\"\"].invalidYear);return o.leapYear(e.year()+(e.year()<1?1:0)+1469)},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(1-(n.dayOfWeek()||7),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidMonth);(t=i.year())<0&&t++;for(var a=i.day(),s=1;s=this.toJD(e+1,1,1);)e++;for(var r=t-Math.floor(this.toJD(e,1,1)+.5)+1,n=1;r>this.daysInMonth(e,n);)r-=this.daysInMonth(e,n),n++;return this.newDate(e,n,r)}}),n.calendars.nanakshahi=a},73040:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"Nepali\",jdEpoch:1700709.5,daysPerMonth:[31,31,32,32,31,30,30,29,30,29,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,daysPerYear:365,regionalOptions:{\"\":{name:\"Nepali\",epochs:[\"BBS\",\"ABS\"],monthNames:[\"Baisakh\",\"Jestha\",\"Ashadh\",\"Shrawan\",\"Bhadra\",\"Ashwin\",\"Kartik\",\"Mangsir\",\"Paush\",\"Mangh\",\"Falgun\",\"Chaitra\"],monthNamesShort:[\"Bai\",\"Je\",\"As\",\"Shra\",\"Bha\",\"Ash\",\"Kar\",\"Mang\",\"Pau\",\"Ma\",\"Fal\",\"Chai\"],dayNames:[\"Aaitabaar\",\"Sombaar\",\"Manglbaar\",\"Budhabaar\",\"Bihibaar\",\"Shukrabaar\",\"Shanibaar\"],dayNamesShort:[\"Aaita\",\"Som\",\"Mangl\",\"Budha\",\"Bihi\",\"Shukra\",\"Shani\"],dayNamesMin:[\"Aai\",\"So\",\"Man\",\"Bu\",\"Bi\",\"Shu\",\"Sha\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:1,isRTL:!1}},leapYear:function(t){return this.daysInYear(t)!==this.daysPerYear},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){if(t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),void 0===this.NEPALI_CALENDAR_DATA[t])return this.daysPerYear;for(var e=0,r=this.minMonth;r<=12;r++)e+=this.NEPALI_CALENDAR_DATA[t][r];return e},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),void 0===this.NEPALI_CALENDAR_DATA[t]?this.daysPerMonth[e-1]:this.NEPALI_CALENDAR_DATA[t][e]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=n.instance(),o=0,s=e,l=t;this._createMissingCalendarData(t);var u=t-(s>9||9===s&&r>=this.NEPALI_CALENDAR_DATA[l][0]?56:57);for(9!==e&&(o=r,s--);9!==s;)s<=0&&(s=12,l--),o+=this.NEPALI_CALENDAR_DATA[l][s],s--;return 9===e?(o+=r-this.NEPALI_CALENDAR_DATA[l][0])<0&&(o+=a.daysInYear(u)):o+=this.NEPALI_CALENDAR_DATA[l][9]-this.NEPALI_CALENDAR_DATA[l][0],a.newDate(u,1,1).add(o,\"d\").toJD()},fromJD:function(t){var e=n.instance().fromJD(t),r=e.year(),i=e.dayOfYear(),a=r+56;this._createMissingCalendarData(a);for(var o=9,s=this.NEPALI_CALENDAR_DATA[a][0],l=this.NEPALI_CALENDAR_DATA[a][o]-s+1;i>l;)++o>12&&(o=1,a++),l+=this.NEPALI_CALENDAR_DATA[a][o];var u=this.NEPALI_CALENDAR_DATA[a][o]-(l-i);return this.newDate(a,o,u)},_createMissingCalendarData:function(t){var e=this.daysPerMonth.slice(0);e.unshift(17);for(var r=t-1;r0?474:473))%2820+474+38)%2816<682},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-(n.dayOfWeek()+1)%7,\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t-(t>=0?474:473),s=474+o(a,2820);return r+(e<=7?31*(e-1):30*(e-1)+6)+Math.floor((682*s-110)/2816)+365*(s-1)+1029983*Math.floor(a/2820)+this.jdEpoch-1},fromJD:function(t){var e=(t=Math.floor(t)+.5)-this.toJD(475,1,1),r=Math.floor(e/1029983),n=o(e,1029983),i=2820;if(1029982!==n){var a=Math.floor(n/366),s=o(n,366);i=Math.floor((2134*a+2816*s+2815)/1028522)+a+1}var l=i+2820*r+474;l=l<=0?l-1:l;var u=t-this.toJD(l,1,1)+1,c=u<=186?Math.ceil(u/31):Math.ceil((u-6)/30),f=t-this.toJD(l,c,1)+1;return this.newDate(l,c,f)}}),n.calendars.persian=a,n.calendars.jalali=a},51456:function(t,e,r){var n=r(38700),i=r(50896),a=n.instance();function o(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}o.prototype=new n.baseCalendar,i(o.prototype,{name:\"Taiwan\",jdEpoch:2419402.5,yearsOffset:1911,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Taiwan\",epochs:[\"BROC\",\"ROC\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:1,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return t=this._t2gYear(e.year()),a.leapYear(t)},weekOfYear:function(t,e,r){var i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return t=this._t2gYear(i.year()),a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=this._t2gYear(i.year()),a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)},_g2tYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)}}),n.calendars.taiwan=o},4592:function(t,e,r){var n=r(38700),i=r(50896),a=n.instance();function o(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}o.prototype=new n.baseCalendar,i(o.prototype,{name:\"Thai\",jdEpoch:1523098.5,yearsOffset:543,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Thai\",epochs:[\"BBE\",\"BE\"],monthNames:[\"January\",\"February\",\"March\",\"April\",\"May\",\"June\",\"July\",\"August\",\"September\",\"October\",\"November\",\"December\"],monthNamesShort:[\"Jan\",\"Feb\",\"Mar\",\"Apr\",\"May\",\"Jun\",\"Jul\",\"Aug\",\"Sep\",\"Oct\",\"Nov\",\"Dec\"],dayNames:[\"Sunday\",\"Monday\",\"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\"],dayNamesShort:[\"Sun\",\"Mon\",\"Tue\",\"Wed\",\"Thu\",\"Fri\",\"Sat\"],dayNamesMin:[\"Su\",\"Mo\",\"Tu\",\"We\",\"Th\",\"Fr\",\"Sa\"],digits:null,dateFormat:\"dd/mm/yyyy\",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return t=this._t2gYear(e.year()),a.leapYear(t)},weekOfYear:function(t,e,r){var i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return t=this._t2gYear(i.year()),a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);return t=this._t2gYear(i.year()),a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)},_g2tYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)}}),n.calendars.thai=o},45348:function(t,e,r){var n=r(38700),i=r(50896);function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"UmmAlQura\",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Umm al-Qura\",epochs:[\"BH\",\"AH\"],monthNames:[\"Al-Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' Al-Thani\",\"Jumada Al-Awwal\",\"Jumada Al-Thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-Ahad\",\"Yawm al-Ithnain\",\"Yawm al-Thalāthā’\",\"Yawm al-Arba‘ā’\",\"Yawm al-Khamīs\",\"Yawm al-Jum‘a\",\"Yawm al-Sabt\"],dayNamesMin:[\"Ah\",\"Ith\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!0}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 355===this.daysInYear(e.year())},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){for(var e=0,r=1;r<=12;r++)e+=this.daysInMonth(t,r);return e},daysInMonth:function(t,e){for(var r=this._validate(t,e,this.minDay,n.local.invalidMonth).toJD()-24e5+.5,i=0,a=0;ar)return o[i]-o[i-1];i++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate),a=12*(i.year()-1)+i.month()-15292;return i.day()+o[a-1]-1+24e5-.5},fromJD:function(t){for(var e=t-24e5+.5,r=0,n=0;ne);n++)r++;var i=r+15292,a=Math.floor((i-1)/12),s=a+1,l=i-12*a,u=e-o[r-1]+1;return this.newDate(s,l,u)},isValid:function(t,e,r){var i=n.baseCalendar.prototype.isValid.apply(this,arguments);return i&&(i=(t=null!=t.year?t.year:t)>=1276&&t<=1500),i},_validate:function(t,e,r,i){var a=n.baseCalendar.prototype._validate.apply(this,arguments);if(a.year<1276||a.year>1500)throw i.replace(/\\{0\\}/,this.local.name);return a}}),n.calendars.ummalqura=a;var 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n=r(50896);function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(u.local.invalidDate||u.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(u.local.invalidDate||u.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(u.local.differentCalendars||u.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,u.local.invalidMonth||u.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,u.local.invalidMonth||u.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,u.local.invalidYear||u.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,u.local.invalidDate||u.regionalOptions[\"\"].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,\"d\"===r||\"w\"===r){var n=t.toJD()+e*(\"w\"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+(\"y\"===r?e:0),o=t.monthOfYear()+(\"m\"===r?e:0);i=t.day(),\"y\"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):\"m\"===r&&(function(t){for(;oe-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw this._validateLevel--,t}},_correctAdd:function(t,e,r,n){if(!(this.hasYearZero||\"y\"!==n&&\"m\"!==n||0!==e[0]&&t.year()>0==e[0]>0)){var 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