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(<2)", "PyTest (<5)", "PyTest-Cov (<2.6)", "pytest", "pytest-cov"] + [[package]] name = "distlib" version = "0.3.4" @@ -135,7 +149,7 @@ pipenv = ["pipenv"] name = "filelock" version = "3.6.0" description = "A platform independent file lock." -category = "dev" +category = "main" optional = false python-versions = ">=3.7" @@ -143,6 +157,20 @@ python-versions = ">=3.7" docs = ["furo (>=2021.8.17b43)", "sphinx (>=4.1)", "sphinx-autodoc-typehints (>=1.12)"] testing = ["covdefaults (>=1.2.0)", "coverage (>=4)", "pytest (>=4)", "pytest-cov", "pytest-timeout (>=1.4.2)"] +[[package]] +name = "grpcio" +version = "1.44.0" +description = "HTTP/2-based RPC framework" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +six = ">=1.5.2" + +[package.extras] +protobuf = ["grpcio-tools (>=1.44.0)"] + [[package]] name = "identify" version = "2.4.11" @@ -186,6 +214,21 @@ docs = ["sphinx", "jaraco.packaging (>=9)", "rst.linker (>=1.9)"] perf = ["ipython"] testing = 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Schema validation for Python" +category = "main" +optional = false +python-versions = ">=3.7" + +[package.dependencies] +attrs = ">=17.4.0" +importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""} +pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2" + +[package.extras] +format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"] +format_nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"] + [[package]] name = "livereload" version = "2.6.3" @@ -236,6 +296,14 @@ category = "dev" optional = false python-versions = ">=3.7" +[[package]] +name = "msgpack" +version = "1.0.3" +description = "MessagePack (de)serializer." +category = "main" +optional = false +python-versions = "*" + [[package]] name = "mypy" version = "0.930" @@ -296,7 +364,7 @@ python-versions = ">=3.8" 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[tool.poetry.dev-dependencies] pytest = "^7.0.0" diff --git a/src/m2stitch/stitching.py b/src/m2stitch/stitching.py index 1dc5802..3ee15df 100644 --- a/src/m2stitch/stitching.py +++ b/src/m2stitch/stitching.py @@ -10,8 +10,8 @@ import numpy as np import pandas as pd +import ray from sklearn.covariance import EllipticEnvelope -from tqdm import tqdm from ._constrained_refinement import refine_translations from ._global_optimization import compute_final_position @@ -157,36 +157,44 @@ def get_index(col, row): ) ###### translationComputation ###### - for direction in ["left", "top"]: - for i2, g in tqdm(grid.iterrows(), total=len(grid)): - i1 = g[direction] - if pd.isna(i1): - continue - image1 = images[i1] - image2 = images[i2] - - PCM = pcm(image1, image2).real - if position_initial_guess is not None: - - def get_lims(dimension, size): - val = g[f"{direction}_{dimension}_init_guess"] - r = size * overlap_diff_threshold / 100.0 - return np.round([val - r, val + r]).astype(np.int64) - - lims = np.array( - [ - get_lims(dimension, size) - for dimension, size in zip("yx", [sizeY, sizeX]) - ] - ) - else: - lims = np.array([[-sizeY, sizeY], [-sizeX, sizeX]]) - yins, xins, _ = multi_peak_max(PCM) - max_peak = interpret_translation( - image1, image2, yins, xins, *lims[0], *lims[1] + @ray.remote + def calc_first_translation(i2, direction): + g = grid.loc[i2] + i1 = g[direction] + if pd.isna(i1): + return None + image1 = images[i1] + image2 = images[i2] + + PCM = pcm(image1, image2).real + if position_initial_guess is not None: + + def get_lims(dimension, size): + val = g[f"{direction}_{dimension}_init_guess"] + r = size * overlap_diff_threshold / 100.0 + return np.round([val - r, val + r]).astype(np.int64) + + lims = np.array( + [ + get_lims(dimension, size) + for dimension, size in zip("yx", [sizeY, sizeX]) + ] ) - for j, key in enumerate(["ncc", "y", "x"]): - grid.loc[i2, f"{direction}_{key}_first"] = max_peak[j] + else: + lims = np.array([[-sizeY, sizeY], [-sizeX, sizeX]]) + yins, xins, _ = multi_peak_max(PCM) + max_peak = interpret_translation(image1, image2, yins, xins, *lims[0], *lims[1]) + return max_peak + + for direction in ["left", "top"]: + print("computing translation for", direction) + res = ray.get( + [calc_first_translation.remote(i2, direction) for i2 in grid.index] + ) + for i2, max_peak in zip(grid.index, res): + if max_peak is not None: + for j, key in enumerate(["ncc", "y", "x"]): + grid.loc[i2, f"{direction}_{key}_first"] = max_peak[j] # TODO make threshold adjustable assert np.any(grid["top_ncc_first"] > 0.5), "there is no good top pair"