HLS2_CPER_timeseries.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "31c5eda9-22cf-42b5-82c1-4e91c20c540b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import dask, concurrent.futures, time, warnings, os, re, pickle\n",
    "from osgeo import gdal\n",
    "import os\n",
    "import requests as r\n",
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "import numpy as np\n",
    "from dask.distributed import LocalCluster, Client\n",
    "import xarray as xr\n",
    "from urllib.request import urlopen\n",
    "from xml.etree.ElementTree import parse,fromstring\n",
    "from pandas import to_datetime\n",
    "from rasterio.crs import CRS\n",
    "from datetime import datetime, timedelta\n",
    "from netrc import netrc\n",
    "from pyproj import Proj\n",
    "from src.hls_funcs import fetch\n",
    "from src.hls_funcs.masks import mask_hls, shp2mask, bolton_mask\n",
    "from src.hls_funcs.indices import ndvi_func\n",
    "from src.hls_funcs.smooth import smooth_xr, despike_ts_xr\n",
    "import cartopy.crs as ccrs\n",
    "from rasterio.plot import show\n",
    "import coiled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "07c07dbf-58fa-4dbe-b3fa-64049f009de6",
   "metadata": {},
   "outputs": [],
   "source": [
    "cper_f = os.path.join('/mnt/d/', 'CPER/data/vectors/Pasture_Boundaries/Shapefiles/cper_pastures_2017_clip.shp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f2fe942b-9543-40ed-9f0d-9e63c9a24771",
   "metadata": {},
   "outputs": [],
   "source": [
    "start_date = \"2021-03-01\"\n",
    "end_date = \"2021-10-31\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "67dc95d5-65e6-48ad-a3c8-2ef78ee85346",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 's3_cred' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_6061/1130359231.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     27\u001b[0m                    \u001b[0mGDAL_HTTP_COOKIEJAR\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexpanduser\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'~/cookies.txt'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     28\u001b[0m                    \u001b[0mAWS_REGION\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'us-west-2'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 29\u001b[0;31m                    \u001b[0mAWS_SECRET_ACCESS_KEY\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0ms3_cred\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'secretAccessKey'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     30\u001b[0m                    \u001b[0mAWS_ACCESS_KEY_ID\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0ms3_cred\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'accessKeyId'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     31\u001b[0m                    AWS_SESSION_TOKEN=s3_cred['sessionToken'])\n",
      "\u001b[0;31mNameError\u001b[0m: name 's3_cred' is not defined"
     ]
    }
   ],
   "source": [
    "cluster_loc = 'coiled'\n",
    "\n",
    "if cluster_loc == 'local':\n",
    "    aws=False\n",
    "    fetch.setup_env(aws=aws)\n",
    "    cluster = LocalCluster(n_workers=8, threads_per_worker=2)\n",
    "    client = Client(cluster)\n",
    "    display(client)\n",
    "elif cluster_loc == 'coiled':\n",
    "    aws=True\n",
    "    fetch.setup_env(aws=aws, creds=['spkearney', '1mrChamu'])\n",
    "    s3_cred = setup_netrc(creds=['spkearney', '1mrChamu'], aws=aws)\n",
    "    cluster = coiled.Cluster(\n",
    "        name=\"hls_cog_coiled\",\n",
    "        software=\"kearney-sp/hls_cog_coiled\",\n",
    "        n_workers=5,\n",
    "        worker_cpu=2,\n",
    "        scheduler_cpu=2,\n",
    "        backend_options={\"region\": \"us-west-2\"},\n",
    "        environ=dict(GDAL_DISABLE_READDIR_ON_OPEN='FALSE', \n",
    "                   #AWS_NO_SIGN_REQUEST='YES',\n",
    "                   GDAL_MAX_RAW_BLOCK_CACHE_SIZE='200000000',\n",
    "                   GDAL_SWATH_SIZE='200000000',\n",
    "                   VSI_CURL_CACHE_SIZE='200000000',\n",
    "                   CPL_VSIL_CURL_ALLOWED_EXTENSIONS='TIF',\n",
    "                   GDAL_HTTP_UNSAFESSL='YES',\n",
    "                   GDAL_HTTP_COOKIEFILE=os.path.expanduser('~/cookies.txt'),\n",
    "                   GDAL_HTTP_COOKIEJAR=os.path.expanduser('~/cookies.txt'),\n",
    "                   AWS_REGION='us-west-2',\n",
    "                   AWS_SECRET_ACCESS_KEY=s3_cred['secretAccessKey'],\n",
    "                   AWS_ACCESS_KEY_ID=s3_cred['accessKeyId'],\n",
    "                   AWS_SESSION_TOKEN=s3_cred['sessionToken'])\n",
    "    )\n",
    "    client = Client(cluster)\n",
    "    display(client)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e1dced6b-f1ec-45ec-ad9c-256707b24fea",
   "metadata": {},
   "outputs": [],
   "source": [
    "from src.hls_funcs.fetch import setup_netrc\n",
    "s3_cred = setup_netrc(creds=['spkearney', '1mrChamu'], aws=aws)\n",
    "client.cluster.environ = dict(GDAL_DISABLE_READDIR_ON_OPEN='FALSE', \n",
    "                   #AWS_NO_SIGN_REQUEST='YES',\n",
    "                   GDAL_MAX_RAW_BLOCK_CACHE_SIZE='200000000',\n",
    "                   GDAL_SWATH_SIZE='200000000',\n",
    "                   VSI_CURL_CACHE_SIZE='200000000',\n",
    "                   CPL_VSIL_CURL_ALLOWED_EXTENSIONS='TIF',\n",
    "                   GDAL_HTTP_UNSAFESSL='YES',\n",
    "                   GDAL_HTTP_COOKIEFILE=os.path.expanduser('~/cookies.txt'),\n",
    "                   GDAL_HTTP_COOKIEJAR=os.path.expanduser('~/cookies.txt'),\n",
    "                   AWS_REGION='us-west-2',\n",
    "                   AWS_SECRET_ACCESS_KEY=s3_cred['secretAccessKey'],\n",
    "                   AWS_ACCESS_KEY_ID=s3_cred['accessKeyId'],\n",
    "                   AWS_SESSION_TOKEN=s3_cred['sessionToken'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "aa22b153-0bb5-42db-8a43-bc0ac391e1f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'GDAL_DISABLE_READDIR_ON_OPEN': 'FALSE',\n",
       " 'GDAL_MAX_RAW_BLOCK_CACHE_SIZE': '200000000',\n",
       " 'GDAL_SWATH_SIZE': '200000000',\n",
       " 'VSI_CURL_CACHE_SIZE': '200000000',\n",
       " 'CPL_VSIL_CURL_ALLOWED_EXTENSIONS': 'TIF',\n",
       " 'GDAL_HTTP_UNSAFESSL': 'YES',\n",
       " 'GDAL_HTTP_COOKIEFILE': '/home/spkearney/cookies.txt',\n",
       " 'GDAL_HTTP_COOKIEJAR': '/home/spkearney/cookies.txt',\n",
       " 'AWS_REGION': 'us-west-2',\n",
       " 'AWS_SECRET_ACCESS_KEY': 'hXGv8r7127415qUGFCt8xjXuEnqFGQRnQoRiqC2W',\n",
       " 'AWS_ACCESS_KEY_ID': 'ASIAZLX6ZES47VJOFL4K',\n",
       " 'AWS_SESSION_TOKEN': 'FwoGZXIvYXdzECgaDDmjXZ3QgY0mfWnDiCLaAYUHraQNAdzDdMpY/zd+jK0c3XsPHqDu2HqV/o9vsAAS125Dr6JYpGGLDX7oTmDBn3jiM1NzDsvGeXfhwU2o5zTG+s+sEdubqJ2Ei0AFxJxz0MoTICE6cgEp5AVp7jZcdWwD4qXSlPaZItvow7tE7A4LlueZtLwUSWUb1apEWIVORKMgmqmnfa2VQVhVtUgBcJC6BrPu+q7G1LIQzijfXwUDfaV/BdXpMZiT2FBWijnwZ/peerM9jQSgFNTXc7VpbnIyzgUykXbNC1NLzpDgBJ6AXKm1KUaTXWCrKM23lY0GMi2sQ9jK+9Jms1vpTq734kFj2tsuOKsSytFJO6VbRJtAv3CAmxB6kbcttCdlIhE='}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "client.cluster.environ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "01248f5e-3a68-43cb-bf73-8b2b057ee047",
   "metadata": {},
   "outputs": [],
   "source": [
    "date_rng = pd.date_range(start=start_date, end=end_date)#.tolist()#.to_pydatetime().tolist()\n",
    "#datetime(2021, 3, 1).date()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b7d7489f-4a40-4bc8-b50b-87d03c199dbb",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dict = {'date_range': [str(date_rng.min().date()), str(date_rng.max().date())]}\n",
    "hls_ds = fetch.get_hls(hls_data=data_dict, lim=500, aws=aws)\n",
    "hls_ds = hls_ds.where(hls_ds['eo:cloud_cover'] < 90)\n",
    "hls_ds = hls_ds.loc[dict(x=slice(517587.0, 527283.0), y=slice(4524402.0, 4514699.0))]#.chunk({'y': 100, 'x': 100, 'time':-1})\n",
    "hls_mask = mask_hls(hls_ds['FMASK'])\n",
    "hls_ds = hls_ds.where(hls_mask == 0)\n",
    "#hls_bolton_mask = bolton_mask(hls_ds)\n",
    "#hls_ds = hls_ds.where(hls_bolton_mask == 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2cae3e40-585e-4b60-8a3b-3ec5f8ab2ea7",
   "metadata": {},
   "outputs": [
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       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:         (time: 89, x: 324, y: 324)\n",
       "Coordinates:\n",
       "  * time            (time) datetime64[ns] 2021-03-02T10:02:36 ... 2021-10-30T...\n",
       "    id              (time) &lt;U34 dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "  * x               (x) float64 5.176e+05 5.176e+05 ... 5.272e+05 5.273e+05\n",
       "  * y               (y) float64 4.524e+06 4.524e+06 ... 4.515e+06 4.515e+06\n",
       "    eo:cloud_cover  (time) int64 dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "    epsg            int64 32613\n",
       "Data variables:\n",
       "    NDVI            (time, y, x) float64 dask.array&lt;chunksize=(1, 324, 324), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    spec:        RasterSpec(epsg=32613, bounds=(499950, 4489410, 611460, 4600...\n",
       "    crs:         epsg:32613\n",
       "    transform:   | 30.00, 0.00, 499950.00|\\n| 0.00,-30.00, 4600860.00|\\n| 0.0...\n",
       "    resolution:  30</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-3a089f8c-a733-4085-8163-37865d175d20' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3a089f8c-a733-4085-8163-37865d175d20' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 89</li><li><span class='xr-has-index'>x</span>: 324</li><li><span class='xr-has-index'>y</span>: 324</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d922571c-3109-4396-8882-bc1b9d75c46b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d922571c-3109-4396-8882-bc1b9d75c46b' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-03-02T10:02:36 ... 2021-10-...</div><input id='attrs-c00eb96d-e3a5-48a6-85a1-d25a23501d2b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c00eb96d-e3a5-48a6-85a1-d25a23501d2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8da5bf1f-1373-4440-88f6-5b9c4183cf02' class='xr-var-data-in' type='checkbox'><label for='data-8da5bf1f-1373-4440-88f6-5b9c4183cf02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-03-02T10:02:36.000000000&#x27;, &#x27;2021-03-07T10:02:36.000000000&#x27;,\n",
       "       &#x27;2021-03-09T09:52:40.000000000&#x27;, &#x27;2021-03-17T11:02:36.000000000&#x27;,\n",
       "       &#x27;2021-03-19T10:52:39.000000000&#x27;, &#x27;2021-03-22T11:02:35.000000000&#x27;,\n",
       "       &#x27;2021-03-24T10:52:39.000000000&#x27;, &#x27;2021-03-27T11:02:35.000000000&#x27;,\n",
       "       &#x27;2021-03-29T10:52:38.000000000&#x27;, &#x27;2021-04-01T11:02:33.000000000&#x27;,\n",
       "       &#x27;2021-04-03T10:52:38.000000000&#x27;, &#x27;2021-04-06T11:02:34.000000000&#x27;,\n",
       "       &#x27;2021-04-08T10:52:36.000000000&#x27;, &#x27;2021-04-11T11:02:31.000000000&#x27;,\n",
       "       &#x27;2021-04-13T10:52:37.000000000&#x27;, &#x27;2021-04-16T11:02:32.000000000&#x27;,\n",
       "       &#x27;2021-04-18T10:52:35.000000000&#x27;, &#x27;2021-04-23T10:52:35.000000000&#x27;,\n",
       "       &#x27;2021-04-26T11:02:31.000000000&#x27;, &#x27;2021-04-28T10:52:38.000000000&#x27;,\n",
       "       &#x27;2021-05-01T11:02:34.000000000&#x27;, &#x27;2021-05-06T11:02:34.000000000&#x27;,\n",
       "       &#x27;2021-05-08T10:52:39.000000000&#x27;, &#x27;2021-05-13T10:52:34.000000000&#x27;,\n",
       "       &#x27;2021-05-16T11:02:36.000000000&#x27;, &#x27;2021-05-18T10:52:41.000000000&#x27;,\n",
       "       &#x27;2021-05-23T10:52:41.000000000&#x27;, &#x27;2021-05-26T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-05-28T10:52:41.000000000&#x27;, &#x27;2021-05-31T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-06-02T10:52:41.000000000&#x27;, &#x27;2021-06-05T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-06-07T10:52:41.000000000&#x27;, &#x27;2021-06-10T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-06-12T10:52:42.000000000&#x27;, &#x27;2021-06-15T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-06-17T10:52:41.000000000&#x27;, &#x27;2021-06-20T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-06-22T10:52:41.000000000&#x27;, &#x27;2021-06-25T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-06-27T10:52:42.000000000&#x27;, &#x27;2021-06-30T11:02:38.000000000&#x27;,\n",
       "       &#x27;2021-07-02T10:52:42.000000000&#x27;, &#x27;2021-07-05T11:02:38.000000000&#x27;,\n",
       "       &#x27;2021-07-10T11:02:39.000000000&#x27;, &#x27;2021-07-12T10:52:42.000000000&#x27;,\n",
       "       &#x27;2021-07-15T11:02:38.000000000&#x27;, &#x27;2021-07-17T10:52:44.000000000&#x27;,\n",
       "       &#x27;2021-07-20T11:02:40.000000000&#x27;, &#x27;2021-07-22T10:52:43.000000000&#x27;,\n",
       "       &#x27;2021-07-25T11:02:38.000000000&#x27;, &#x27;2021-07-27T10:52:44.000000000&#x27;,\n",
       "       &#x27;2021-07-30T11:02:40.000000000&#x27;, &#x27;2021-08-01T10:52:42.000000000&#x27;,\n",
       "       &#x27;2021-08-04T11:02:38.000000000&#x27;, &#x27;2021-08-06T10:52:43.000000000&#x27;,\n",
       "       &#x27;2021-08-09T11:02:39.000000000&#x27;, &#x27;2021-08-11T10:52:41.000000000&#x27;,\n",
       "       &#x27;2021-08-14T11:02:37.000000000&#x27;, &#x27;2021-08-16T10:52:43.000000000&#x27;,\n",
       "       &#x27;2021-08-19T11:02:39.000000000&#x27;, &#x27;2021-08-21T10:52:39.000000000&#x27;,\n",
       "       &#x27;2021-08-24T11:02:35.000000000&#x27;, &#x27;2021-08-26T10:52:42.000000000&#x27;,\n",
       "       &#x27;2021-08-29T11:02:38.000000000&#x27;, &#x27;2021-08-31T10:52:37.000000000&#x27;,\n",
       "       &#x27;2021-09-03T11:02:33.000000000&#x27;, &#x27;2021-09-05T10:52:41.000000000&#x27;,\n",
       "       &#x27;2021-09-08T11:02:37.000000000&#x27;, &#x27;2021-09-10T10:52:37.000000000&#x27;,\n",
       "       &#x27;2021-09-13T11:02:33.000000000&#x27;, &#x27;2021-09-15T10:52:42.000000000&#x27;,\n",
       "       &#x27;2021-09-18T11:02:39.000000000&#x27;, &#x27;2021-09-20T10:52:38.000000000&#x27;,\n",
       "       &#x27;2021-09-23T11:02:34.000000000&#x27;, &#x27;2021-09-25T10:52:44.000000000&#x27;,\n",
       "       &#x27;2021-09-28T11:02:40.000000000&#x27;, &#x27;2021-09-30T10:52:40.000000000&#x27;,\n",
       "       &#x27;2021-10-03T11:02:36.000000000&#x27;, &#x27;2021-10-05T10:52:45.000000000&#x27;,\n",
       "       &#x27;2021-10-08T11:02:42.000000000&#x27;, &#x27;2021-10-10T10:52:41.000000000&#x27;,\n",
       "       &#x27;2021-10-13T11:02:38.000000000&#x27;, &#x27;2021-10-15T10:52:46.000000000&#x27;,\n",
       "       &#x27;2021-10-18T11:02:42.000000000&#x27;, &#x27;2021-10-20T10:52:42.000000000&#x27;,\n",
       "       &#x27;2021-10-25T10:52:46.000000000&#x27;, &#x27;2021-10-28T11:02:41.000000000&#x27;,\n",
       "       &#x27;2021-10-30T10:52:42.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>id</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>&lt;U34</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-e527ff13-7511-4c57-96f9-5400b04a3133' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e527ff13-7511-4c57-96f9-5400b04a3133' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ab8c632-71f2-4807-b77b-862516e9b751' class='xr-var-data-in' type='checkbox'><label for='data-6ab8c632-71f2-4807-b77b-862516e9b751' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 11.82 kiB </td>\n",
       "                        <td> 136 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (89,) </td>\n",
       "                        <td> (1,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 89 Tasks </td>\n",
       "                        <td> 89 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> <U34 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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       "\n",
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       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
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       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"25\" />\n",
       "  <line x1=\"68\" y1=\"0\" x2=\"68\" y2=\"25\" />\n",
       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
       "  <line x1=\"80\" y1=\"0\" x2=\"80\" y2=\"25\" />\n",
       "  <line x1=\"87\" y1=\"0\" x2=\"87\" y2=\"25\" />\n",
       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
       "  <line x1=\"99\" y1=\"0\" x2=\"99\" y2=\"25\" />\n",
       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
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       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
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       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.979238178701316 0.0,25.979238178701316\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.979238\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >89</text>\n",
       "  <text x=\"140.000000\" y=\"12.989619\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.989619)\">1</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.176e+05 5.176e+05 ... 5.273e+05</div><input id='attrs-d6d63812-3ea5-4f75-a932-ee61f00558cf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d6d63812-3ea5-4f75-a932-ee61f00558cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e9b9703-dd31-4a1f-9478-d2c0daa78d00' class='xr-var-data-in' type='checkbox'><label for='data-5e9b9703-dd31-4a1f-9478-d2c0daa78d00' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([517590., 517620., 517650., ..., 527220., 527250., 527280.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524e+06 4.524e+06 ... 4.515e+06</div><input id='attrs-1f985025-03e5-48c5-a3a3-944d44dab0b5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1f985025-03e5-48c5-a3a3-944d44dab0b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-790c67bb-25d1-4162-8afb-2e43d8462c73' class='xr-var-data-in' type='checkbox'><label for='data-790c67bb-25d1-4162-8afb-2e43d8462c73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([4524390., 4524360., 4524330., ..., 4514760., 4514730., 4514700.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>eo:cloud_cover</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-6946b320-4018-470a-928f-506467786f00' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6946b320-4018-470a-928f-506467786f00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-837e94bb-7cb4-4350-a313-40685c37d931' class='xr-var-data-in' type='checkbox'><label for='data-837e94bb-7cb4-4350-a313-40685c37d931' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
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       "<xarray.Dataset>\n",
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       "  * time            (time) datetime64[ns] 2021-03-02T10:02:36 ... 2021-10-30T...\n",
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     "execution_count": 16,
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   "source": [
    "ndvi_ds = ndvi_func(hls_ds).to_dataset()\n",
    "ndvi_ds.attrs = hls_ds.attrs\n",
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  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2a98c757-3ade-410c-80bb-36baa8f658d5",
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       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:         (time: 89, x: 324, y: 324)\n",
       "Coordinates:\n",
       "  * time            (time) datetime64[ns] 2021-03-02T10:02:36 ... 2021-10-30T...\n",
       "    id              (time) &lt;U34 dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "  * x               (x) float64 5.176e+05 5.176e+05 ... 5.272e+05 5.273e+05\n",
       "  * y               (y) float64 4.524e+06 4.524e+06 ... 4.515e+06 4.515e+06\n",
       "    eo:cloud_cover  (time) int64 dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "    epsg            int64 32613\n",
       "    Pasture         (y, x) &lt;U7 dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;\n",
       "Data variables:\n",
       "    NDVI            (time, y, x) float64 dask.array&lt;chunksize=(1, 50, 50), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    spec:        RasterSpec(epsg=32613, bounds=(499950, 4489410, 611460, 4600...\n",
       "    crs:         epsg:32613\n",
       "    transform:   | 30.00, 0.00, 499950.00|\\n| 0.00,-30.00, 4600860.00|\\n| 0.0...\n",
       "    resolution:  30</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1d949c92-40e4-417e-abd3-f4738c7d5254' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1d949c92-40e4-417e-abd3-f4738c7d5254' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 89</li><li><span class='xr-has-index'>x</span>: 324</li><li><span class='xr-has-index'>y</span>: 324</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-911f0788-493d-4c69-8a92-21547c055dbf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-911f0788-493d-4c69-8a92-21547c055dbf' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-03-02T10:02:36 ... 2021-10-...</div><input id='attrs-0b694425-c2d5-4f39-b1f6-6bd845e3959b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0b694425-c2d5-4f39-b1f6-6bd845e3959b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59fecc26-68ba-402c-b8b2-1bd80274659e' class='xr-var-data-in' type='checkbox'><label for='data-59fecc26-68ba-402c-b8b2-1bd80274659e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-03-02T10:02:36.000000000&#x27;, &#x27;2021-03-07T10:02:36.000000000&#x27;,\n",
       "       &#x27;2021-03-09T09:52:40.000000000&#x27;, &#x27;2021-03-17T11:02:36.000000000&#x27;,\n",
       "       &#x27;2021-03-19T10:52:39.000000000&#x27;, &#x27;2021-03-22T11:02:35.000000000&#x27;,\n",
       "       &#x27;2021-03-24T10:52:39.000000000&#x27;, &#x27;2021-03-27T11:02:35.000000000&#x27;,\n",
       "       &#x27;2021-03-29T10:52:38.000000000&#x27;, &#x27;2021-04-01T11:02:33.000000000&#x27;,\n",
       "       &#x27;2021-04-03T10:52:38.000000000&#x27;, &#x27;2021-04-06T11:02:34.000000000&#x27;,\n",
       "       &#x27;2021-04-08T10:52:36.000000000&#x27;, &#x27;2021-04-11T11:02:31.000000000&#x27;,\n",
       "       &#x27;2021-04-13T10:52:37.000000000&#x27;, &#x27;2021-04-16T11:02:32.000000000&#x27;,\n",
       "       &#x27;2021-04-18T10:52:35.000000000&#x27;, &#x27;2021-04-23T10:52:35.000000000&#x27;,\n",
       "       &#x27;2021-04-26T11:02:31.000000000&#x27;, &#x27;2021-04-28T10:52:38.000000000&#x27;,\n",
       "       &#x27;2021-05-01T11:02:34.000000000&#x27;, &#x27;2021-05-06T11:02:34.000000000&#x27;,\n",
       "       &#x27;2021-05-08T10:52:39.000000000&#x27;, &#x27;2021-05-13T10:52:34.000000000&#x27;,\n",
       "       &#x27;2021-05-16T11:02:36.000000000&#x27;, &#x27;2021-05-18T10:52:41.000000000&#x27;,\n",
       "       &#x27;2021-05-23T10:52:41.000000000&#x27;, &#x27;2021-05-26T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-05-28T10:52:41.000000000&#x27;, &#x27;2021-05-31T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-06-02T10:52:41.000000000&#x27;, &#x27;2021-06-05T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-06-07T10:52:41.000000000&#x27;, &#x27;2021-06-10T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-06-12T10:52:42.000000000&#x27;, &#x27;2021-06-15T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-06-17T10:52:41.000000000&#x27;, &#x27;2021-06-20T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-06-22T10:52:41.000000000&#x27;, &#x27;2021-06-25T11:02:37.000000000&#x27;,\n",
       "       &#x27;2021-06-27T10:52:42.000000000&#x27;, &#x27;2021-06-30T11:02:38.000000000&#x27;,\n",
       "       &#x27;2021-07-02T10:52:42.000000000&#x27;, &#x27;2021-07-05T11:02:38.000000000&#x27;,\n",
       "       &#x27;2021-07-10T11:02:39.000000000&#x27;, &#x27;2021-07-12T10:52:42.000000000&#x27;,\n",
       "       &#x27;2021-07-15T11:02:38.000000000&#x27;, &#x27;2021-07-17T10:52:44.000000000&#x27;,\n",
       "       &#x27;2021-07-20T11:02:40.000000000&#x27;, &#x27;2021-07-22T10:52:43.000000000&#x27;,\n",
       "       &#x27;2021-07-25T11:02:38.000000000&#x27;, &#x27;2021-07-27T10:52:44.000000000&#x27;,\n",
       "       &#x27;2021-07-30T11:02:40.000000000&#x27;, &#x27;2021-08-01T10:52:42.000000000&#x27;,\n",
       "       &#x27;2021-08-04T11:02:38.000000000&#x27;, &#x27;2021-08-06T10:52:43.000000000&#x27;,\n",
       "       &#x27;2021-08-09T11:02:39.000000000&#x27;, &#x27;2021-08-11T10:52:41.000000000&#x27;,\n",
       "       &#x27;2021-08-14T11:02:37.000000000&#x27;, &#x27;2021-08-16T10:52:43.000000000&#x27;,\n",
       "       &#x27;2021-08-19T11:02:39.000000000&#x27;, &#x27;2021-08-21T10:52:39.000000000&#x27;,\n",
       "       &#x27;2021-08-24T11:02:35.000000000&#x27;, &#x27;2021-08-26T10:52:42.000000000&#x27;,\n",
       "       &#x27;2021-08-29T11:02:38.000000000&#x27;, &#x27;2021-08-31T10:52:37.000000000&#x27;,\n",
       "       &#x27;2021-09-03T11:02:33.000000000&#x27;, &#x27;2021-09-05T10:52:41.000000000&#x27;,\n",
       "       &#x27;2021-09-08T11:02:37.000000000&#x27;, &#x27;2021-09-10T10:52:37.000000000&#x27;,\n",
       "       &#x27;2021-09-13T11:02:33.000000000&#x27;, &#x27;2021-09-15T10:52:42.000000000&#x27;,\n",
       "       &#x27;2021-09-18T11:02:39.000000000&#x27;, &#x27;2021-09-20T10:52:38.000000000&#x27;,\n",
       "       &#x27;2021-09-23T11:02:34.000000000&#x27;, &#x27;2021-09-25T10:52:44.000000000&#x27;,\n",
       "       &#x27;2021-09-28T11:02:40.000000000&#x27;, &#x27;2021-09-30T10:52:40.000000000&#x27;,\n",
       "       &#x27;2021-10-03T11:02:36.000000000&#x27;, &#x27;2021-10-05T10:52:45.000000000&#x27;,\n",
       "       &#x27;2021-10-08T11:02:42.000000000&#x27;, &#x27;2021-10-10T10:52:41.000000000&#x27;,\n",
       "       &#x27;2021-10-13T11:02:38.000000000&#x27;, &#x27;2021-10-15T10:52:46.000000000&#x27;,\n",
       "       &#x27;2021-10-18T11:02:42.000000000&#x27;, &#x27;2021-10-20T10:52:42.000000000&#x27;,\n",
       "       &#x27;2021-10-25T10:52:46.000000000&#x27;, &#x27;2021-10-28T11:02:41.000000000&#x27;,\n",
       "       &#x27;2021-10-30T10:52:42.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>id</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>&lt;U34</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-ec4ae790-8827-4e01-8fdb-56d06101d67f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ec4ae790-8827-4e01-8fdb-56d06101d67f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b438a3fc-faff-487a-b3d4-5ef34b693d02' class='xr-var-data-in' type='checkbox'><label for='data-b438a3fc-faff-487a-b3d4-5ef34b693d02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 11.82 kiB </td>\n",
       "                        <td> 136 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (89,) </td>\n",
       "                        <td> (1,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 89 Tasks </td>\n",
       "                        <td> 89 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> <U34 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.176e+05 5.176e+05 ... 5.273e+05</div><input id='attrs-ac007097-f2bd-44fd-aee8-782cfd629a1b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ac007097-f2bd-44fd-aee8-782cfd629a1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7910b041-e05a-4498-ac17-0d2b5d9d8f57' class='xr-var-data-in' type='checkbox'><label for='data-7910b041-e05a-4498-ac17-0d2b5d9d8f57' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([517590., 517620., 517650., ..., 527220., 527250., 527280.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524e+06 4.524e+06 ... 4.515e+06</div><input id='attrs-d026878b-d21c-40b0-8b87-e3ac0404321f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d026878b-d21c-40b0-8b87-e3ac0404321f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-204a2e06-6944-4f7d-a210-e44f2ab31382' class='xr-var-data-in' type='checkbox'><label for='data-204a2e06-6944-4f7d-a210-e44f2ab31382' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([4524390., 4524360., 4524330., ..., 4514760., 4514730., 4514700.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>eo:cloud_cover</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-275c82a3-e441-44a7-9698-0df0a1fc6ede' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-275c82a3-e441-44a7-9698-0df0a1fc6ede' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c156a8e-c009-4861-b38c-eaba283283c8' class='xr-var-data-in' type='checkbox'><label for='data-1c156a8e-c009-4861-b38c-eaba283283c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 712 B </td>\n",
       "                        <td> 8 B </td>\n",
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       "                        <td> (1,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 89 Tasks </td>\n",
       "                        <td> 89 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> int64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>epsg</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>32613</div><input id='attrs-24078adc-0a93-4fe3-8886-216800f628ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24078adc-0a93-4fe3-8886-216800f628ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7aef3e2a-b502-4b5c-9135-bc20be236d02' class='xr-var-data-in' type='checkbox'><label for='data-7aef3e2a-b502-4b5c-9135-bc20be236d02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(32613)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Pasture</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>&lt;U7</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;</div><input id='attrs-b89f7d4c-5f4d-441f-ae1f-486cdc1f4433' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b89f7d4c-5f4d-441f-ae1f-486cdc1f4433' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfb51355-ca46-4c74-bb4c-ac2b99027931' class='xr-var-data-in' type='checkbox'><label for='data-bfb51355-ca46-4c74-bb4c-ac2b99027931' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.80 MiB </td>\n",
       "                        <td> 68.36 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (324, 324) </td>\n",
       "                        <td> (50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 49 Tasks </td>\n",
       "                        <td> 49 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> <U7 </td>\n",
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       "                        <th> Count </th>\n",
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       "<xarray.Dataset>\n",
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       "  * time            (time) datetime64[ns] 2021-03-02T10:02:36 ... 2021-10-30T...\n",
       "    id              (time) <U34 dask.array<chunksize=(1,), meta=np.ndarray>\n",
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       "    eo:cloud_cover  (time) int64 dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "    epsg            int64 32613\n",
       "    Pasture         (y, x) <U7 dask.array<chunksize=(50, 50), meta=np.ndarray>\n",
       "Data variables:\n",
       "    NDVI            (time, y, x) float64 dask.array<chunksize=(1, 50, 50), meta=np.ndarray>\n",
       "Attributes:\n",
       "    spec:        RasterSpec(epsg=32613, bounds=(499950, 4489410, 611460, 4600...\n",
       "    crs:         epsg:32613\n",
       "    transform:   | 30.00, 0.00, 499950.00|\\n| 0.00,-30.00, 4600860.00|\\n| 0.0...\n",
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      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cper = gpd.read_file(cper_f)\n",
    "df_cper = df_cper.dissolve(by='Past_Name_').reset_index().rename(columns={'Past_Name_': 'Pasture'})\n",
    "cper_info = df_cper[['Pasture', 'geometry']].reset_index(drop=True).reset_index().rename(columns={'index': 'id'})\n",
    "past_dict = {row.id+1: row.Pasture for _, row in cper_info.iterrows()}\n",
    "past_dict[0] = 'UNK'\n",
    "cper_mask_shp = [(row.geometry, row.id+1) for _, row in cper_info.iterrows()]\n",
    "cper_mask = shp2mask(shp=cper_mask_shp, xr_object=ndvi_ds['NDVI'])\n",
    "past_mask = np.array([past_dict[i] for i in cper_mask.values.flatten()]).reshape(cper_mask.shape)\n",
    "ndvi_ds = ndvi_ds.assign(Pasture=(['y', 'x'], past_mask)).chunk({'y': 50, 'x': 50})\n",
    "ndvi_ds = ndvi_ds.set_coords('Pasture')\n",
    "ndvi_ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a38a445b-c26f-49c3-9593-0f73f9ec35a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#ndvi_test = ndvi_ds.isel(time=10)['NDVI'].compute()\n",
    "#ndvi_test = ndvi_ds.isel(time=slice(10, 30)).where(\n",
    "#    ndvi_ds['Pasture'].isin(['19N', '15E'])).compute()\n",
    "ndvi_test = ndvi_ds.where(\n",
    "    ndvi_ds['Pasture'].isin(['19N', '15E'])).compute()\n",
    "ndvi_test['time'] = ndvi_test['time'].dt.date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "55985586-e455-45a0-8a0a-64b405ca8691",
   "metadata": {},
   "outputs": [
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       "    eo:cloud_cover  (time) int64 0 56 99 62 0 35 15 36 ... 11 26 2 21 90 15 22\n",
       "    epsg            int64 32613\n",
       "    Pasture         (y, x) &lt;U7 &#x27;UNK&#x27; &#x27;UNK&#x27; &#x27;UNK&#x27; &#x27;UNK&#x27; ... &#x27;UNK&#x27; &#x27;UNK&#x27; &#x27;UNK&#x27;\n",
       "Data variables:\n",
       "    NDVI            (time, y, x) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "    pct_valid       (Pasture, time) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "Attributes:\n",
       "    spec:        RasterSpec(epsg=32613, bounds=(499950, 4489410, 611460, 4600...\n",
       "    crs:         epsg:32613\n",
       "    transform:   | 30.00, 0.00, 499950.00|\\n| 0.00,-30.00, 4600860.00|\\n| 0.0...\n",
       "    resolution:  30</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5a80763e-30bb-4a22-abbf-35e584917e4b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5a80763e-30bb-4a22-abbf-35e584917e4b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 89</li><li><span class='xr-has-index'>y</span>: 324</li><li><span class='xr-has-index'>x</span>: 324</li><li><span class='xr-has-index'>Pasture</span>: 58</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-7afe9cf8-50ed-47be-9d5d-22acee8a692b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7afe9cf8-50ed-47be-9d5d-22acee8a692b' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>2021-03-02 ... 2021-10-30</div><input id='attrs-fbd1573e-5b42-4895-816c-1e476e6adcea' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fbd1573e-5b42-4895-816c-1e476e6adcea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c557bc7a-06ff-46b2-a53b-55f66547e595' class='xr-var-data-in' type='checkbox'><label for='data-c557bc7a-06ff-46b2-a53b-55f66547e595' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([datetime.date(2021, 3, 2), datetime.date(2021, 3, 7),\n",
       "       datetime.date(2021, 3, 9), datetime.date(2021, 3, 17),\n",
       "       datetime.date(2021, 3, 19), datetime.date(2021, 3, 22),\n",
       "       datetime.date(2021, 3, 24), datetime.date(2021, 3, 27),\n",
       "       datetime.date(2021, 3, 29), datetime.date(2021, 4, 1),\n",
       "       datetime.date(2021, 4, 3), datetime.date(2021, 4, 6),\n",
       "       datetime.date(2021, 4, 8), datetime.date(2021, 4, 11),\n",
       "       datetime.date(2021, 4, 13), datetime.date(2021, 4, 16),\n",
       "       datetime.date(2021, 4, 18), datetime.date(2021, 4, 23),\n",
       "       datetime.date(2021, 4, 26), datetime.date(2021, 4, 28),\n",
       "       datetime.date(2021, 5, 1), datetime.date(2021, 5, 6),\n",
       "       datetime.date(2021, 5, 8), datetime.date(2021, 5, 13),\n",
       "       datetime.date(2021, 5, 16), datetime.date(2021, 5, 18),\n",
       "       datetime.date(2021, 5, 23), datetime.date(2021, 5, 26),\n",
       "       datetime.date(2021, 5, 28), datetime.date(2021, 5, 31),\n",
       "       datetime.date(2021, 6, 2), datetime.date(2021, 6, 5),\n",
       "       datetime.date(2021, 6, 7), datetime.date(2021, 6, 10),\n",
       "       datetime.date(2021, 6, 12), datetime.date(2021, 6, 15),\n",
       "       datetime.date(2021, 6, 17), datetime.date(2021, 6, 20),\n",
       "       datetime.date(2021, 6, 22), datetime.date(2021, 6, 25),\n",
       "       datetime.date(2021, 6, 27), datetime.date(2021, 6, 30),\n",
       "       datetime.date(2021, 7, 2), datetime.date(2021, 7, 5),\n",
       "       datetime.date(2021, 7, 10), datetime.date(2021, 7, 12),\n",
       "       datetime.date(2021, 7, 15), datetime.date(2021, 7, 17),\n",
       "       datetime.date(2021, 7, 20), datetime.date(2021, 7, 22),\n",
       "       datetime.date(2021, 7, 25), datetime.date(2021, 7, 27),\n",
       "       datetime.date(2021, 7, 30), datetime.date(2021, 8, 1),\n",
       "       datetime.date(2021, 8, 4), datetime.date(2021, 8, 6),\n",
       "       datetime.date(2021, 8, 9), datetime.date(2021, 8, 11),\n",
       "       datetime.date(2021, 8, 14), datetime.date(2021, 8, 16),\n",
       "       datetime.date(2021, 8, 19), datetime.date(2021, 8, 21),\n",
       "       datetime.date(2021, 8, 24), datetime.date(2021, 8, 26),\n",
       "       datetime.date(2021, 8, 29), datetime.date(2021, 8, 31),\n",
       "       datetime.date(2021, 9, 3), datetime.date(2021, 9, 5),\n",
       "       datetime.date(2021, 9, 8), datetime.date(2021, 9, 10),\n",
       "       datetime.date(2021, 9, 13), datetime.date(2021, 9, 15),\n",
       "       datetime.date(2021, 9, 18), datetime.date(2021, 9, 20),\n",
       "       datetime.date(2021, 9, 23), datetime.date(2021, 9, 25),\n",
       "       datetime.date(2021, 9, 28), datetime.date(2021, 9, 30),\n",
       "       datetime.date(2021, 10, 3), datetime.date(2021, 10, 5),\n",
       "       datetime.date(2021, 10, 8), datetime.date(2021, 10, 10),\n",
       "       datetime.date(2021, 10, 13), datetime.date(2021, 10, 15),\n",
       "       datetime.date(2021, 10, 18), datetime.date(2021, 10, 20),\n",
       "       datetime.date(2021, 10, 25), datetime.date(2021, 10, 28),\n",
       "       datetime.date(2021, 10, 30)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>id</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>&lt;U34</div><div class='xr-var-preview xr-preview'>&#x27;HLS.S30.T13TEF.2021061T175241.v...</div><input id='attrs-5b09fde3-c7fe-4e12-a8ba-6bc6d3741f96' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5b09fde3-c7fe-4e12-a8ba-6bc6d3741f96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4543f37d-ba5e-442a-a249-2692271f8e88' class='xr-var-data-in' type='checkbox'><label for='data-4543f37d-ba5e-442a-a249-2692271f8e88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;HLS.S30.T13TEF.2021061T175241.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021066T175109.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021068T174141.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021076T174959.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021078T174031.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021081T175011.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021083T173859.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021086T174909.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021088T173921.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021091T174901.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021093T173859.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021096T174909.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021098T173901.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021101T174901.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021103T173859.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021106T174909.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021108T173901.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021113T173859.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021116T174859.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021118T173901.v2.0&#x27;,\n",
       "...\n",
       "       &#x27;HLS.S30.T13TEF.2021253T173859.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021256T174909.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021258T173951.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021261T175011.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021263T173919.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021266T174949.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021268T174101.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021271T175131.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021273T174039.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021276T175059.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021278T174211.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021281T175241.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021283T174149.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021286T175309.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021288T174321.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021291T175341.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021293T174349.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021298T174421.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021301T175451.v2.0&#x27;,\n",
       "       &#x27;HLS.S30.T13TEF.2021303T174449.v2.0&#x27;], dtype=&#x27;&lt;U34&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.176e+05 5.176e+05 ... 5.273e+05</div><input id='attrs-58f1ebef-0b07-4a76-b53f-1c3eb8e288c2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-58f1ebef-0b07-4a76-b53f-1c3eb8e288c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25ceccfb-a306-4db5-a4b3-2725ca7c82a8' class='xr-var-data-in' type='checkbox'><label for='data-25ceccfb-a306-4db5-a4b3-2725ca7c82a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([517590., 517620., 517650., ..., 527220., 527250., 527280.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524e+06 4.524e+06 ... 4.515e+06</div><input id='attrs-8700d596-186f-4862-adf4-e119bf2c7cae' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8700d596-186f-4862-adf4-e119bf2c7cae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b9d9a0f-2832-4c26-acaf-4b867530ca79' class='xr-var-data-in' type='checkbox'><label for='data-8b9d9a0f-2832-4c26-acaf-4b867530ca79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([4524390., 4524360., 4524330., ..., 4514760., 4514730., 4514700.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>eo:cloud_cover</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 56 99 62 0 35 ... 2 21 90 15 22</div><input id='attrs-31adb31f-a528-4245-8f27-8053bb5651b6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-31adb31f-a528-4245-8f27-8053bb5651b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13b5adb3-c66d-4d25-82c7-0360ddc2e5f3' class='xr-var-data-in' type='checkbox'><label for='data-13b5adb3-c66d-4d25-82c7-0360ddc2e5f3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,  56,  99,  62,   0,  35,  15,  36,   0,   0,   0,  59,   4,\n",
       "         2, 100, 100,  14,  38,  90,  58,  88,   0,  59,  10,  98,  84,\n",
       "        66,  86,   0,  72,  51,   0,  13, 100,   0,   0,  78,   0,   0,\n",
       "        94,  80,  21,  21,   0,   3,  15,   6,   0,   1,   9,   1,   0,\n",
       "        60,  35,  52,  80,  35,  19,   1,   1,  69,   1,  19,  58,  75,\n",
       "         0,  63,   2,  77,  15,  91,   0,   0,  58,  47,   0,  33,  49,\n",
       "         1,   0, 100,  66,  11,  26,   2,  21,  90,  15,  22])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>epsg</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>32613</div><input id='attrs-94250f82-770c-4026-8c69-f1ef26af1537' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-94250f82-770c-4026-8c69-f1ef26af1537' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a0aedb0-0c32-42dc-9816-7d94a0664858' class='xr-var-data-in' type='checkbox'><label for='data-1a0aedb0-0c32-42dc-9816-7d94a0664858' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(32613)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Pasture</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>&lt;U7</div><div class='xr-var-preview xr-preview'>&#x27;UNK&#x27; &#x27;UNK&#x27; &#x27;UNK&#x27; ... &#x27;UNK&#x27; &#x27;UNK&#x27;</div><input id='attrs-aa9ab048-ac83-4baf-a149-ba86ad14dcd6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aa9ab048-ac83-4baf-a149-ba86ad14dcd6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4434e0f1-b295-464c-9df0-9be66caca3e4' class='xr-var-data-in' type='checkbox'><label for='data-4434e0f1-b295-464c-9df0-9be66caca3e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;UNK&#x27;, &#x27;UNK&#x27;, &#x27;UNK&#x27;, ..., &#x27;UNK&#x27;, &#x27;UNK&#x27;, &#x27;UNK&#x27;],\n",
       "       [&#x27;UNK&#x27;, &#x27;UNK&#x27;, &#x27;UNK&#x27;, ..., &#x27;UNK&#x27;, &#x27;UNK&#x27;, &#x27;UNK&#x27;],\n",
       "       [&#x27;UNK&#x27;, &#x27;UNK&#x27;, &#x27;UNK&#x27;, ..., &#x27;UNK&#x27;, &#x27;UNK&#x27;, &#x27;UNK&#x27;],\n",
       "       ...,\n",
       "       [&#x27;UNK&#x27;, &#x27;UNK&#x27;, &#x27;UNK&#x27;, ..., &#x27;UNK&#x27;, &#x27;UNK&#x27;, &#x27;UNK&#x27;],\n",
       "       [&#x27;UNK&#x27;, &#x27;UNK&#x27;, &#x27;UNK&#x27;, ..., &#x27;UNK&#x27;, &#x27;UNK&#x27;, &#x27;UNK&#x27;],\n",
       "       [&#x27;UNK&#x27;, &#x27;UNK&#x27;, &#x27;UNK&#x27;, ..., &#x27;UNK&#x27;, &#x27;UNK&#x27;, &#x27;UNK&#x27;]], dtype=&#x27;&lt;U7&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c8df3abc-539d-47be-a4ec-f18f3b90fdfe' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c8df3abc-539d-47be-a4ec-f18f3b90fdfe' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>NDVI</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-44b490af-8dda-4286-8d32-a969cf2428bb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-44b490af-8dda-4286-8d32-a969cf2428bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4e86d0a-c8f2-4441-a716-80885d8e015b' class='xr-var-data-in' type='checkbox'><label for='data-d4e86d0a-c8f2-4441-a716-80885d8e015b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pct_valid</span></div><div class='xr-var-dims'>(Pasture, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-57234fca-cbcd-499c-ba9c-542fea0ff5cf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-57234fca-cbcd-499c-ba9c-542fea0ff5cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a6a0e4b-b45c-4dc4-9a3d-3a536794625d' class='xr-var-data-in' type='checkbox'><label for='data-5a6a0e4b-b45c-4dc4-9a3d-3a536794625d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-82082f74-4f36-4904-88bd-e6d87ca1f860' class='xr-section-summary-in' type='checkbox'  checked><label for='section-82082f74-4f36-4904-88bd-e6d87ca1f860' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>spec :</span></dt><dd>RasterSpec(epsg=32613, bounds=(499950, 4489410, 611460, 4600860), resolutions_xy=(30, 30))</dd><dt><span>crs :</span></dt><dd>epsg:32613</dd><dt><span>transform :</span></dt><dd>| 30.00, 0.00, 499950.00|\n",
       "| 0.00,-30.00, 4600860.00|\n",
       "| 0.00, 0.00, 1.00|</dd><dt><span>resolution :</span></dt><dd>30</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:         (time: 89, y: 324, x: 324, Pasture: 58)\n",
       "Coordinates:\n",
       "  * time            (time) object 2021-03-02 2021-03-07 ... 2021-10-30\n",
       "    id              (time) <U34 'HLS.S30.T13TEF.2021061T175241.v2.0' ... 'HLS...\n",
       "  * x               (x) float64 5.176e+05 5.176e+05 ... 5.272e+05 5.273e+05\n",
       "  * y               (y) float64 4.524e+06 4.524e+06 ... 4.515e+06 4.515e+06\n",
       "    eo:cloud_cover  (time) int64 0 56 99 62 0 35 15 36 ... 11 26 2 21 90 15 22\n",
       "    epsg            int64 32613\n",
       "    Pasture         (y, x) <U7 'UNK' 'UNK' 'UNK' 'UNK' ... 'UNK' 'UNK' 'UNK'\n",
       "Data variables:\n",
       "    NDVI            (time, y, x) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "    pct_valid       (Pasture, time) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "Attributes:\n",
       "    spec:        RasterSpec(epsg=32613, bounds=(499950, 4489410, 611460, 4600...\n",
       "    crs:         epsg:32613\n",
       "    transform:   | 30.00, 0.00, 499950.00|\\n| 0.00,-30.00, 4600860.00|\\n| 0.0...\n",
       "    resolution:  30"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ndvi_test = ndvi_test.assign(pct_valid=(['Pasture', 'time'], \n",
    "                                               (ndvi_test['NDVI'].groupby('Pasture').count(dim=['stacked_y_x']) / \n",
    "                                                ndvi_test.groupby('Pasture').map(lambda x: x['stacked_y_x'].count()) * 100).transpose().data))\n",
    "ndvi_test\n",
    "#ndvi_test = ndvi_test.set_coords('pct_valid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ef56675c-043a-494e-855e-da7c915ee194",
   "metadata": {},
   "outputs": [],
   "source": [
    "ndvi_test = ndvi_test.chunk({'y': 50, 'x': 50, 'time':-1})\n",
    "#ndvi_test['pct_valid'].isel(time=10).values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "322a4355-8f1c-4ad6-9bc5-59154ef4f8c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "dat_out = xr.Dataset(coords={'time': date_rng,\n",
    "                             'y': ndvi_test.y,\n",
    "                             'x': ndvi_test.x}).chunk({'time': -1, 'y': 50, 'x': 50})\n",
    "\n",
    "dat_out['time'] = dat_out['time'].dt.date\n",
    "\n",
    "dat_out = dat_out.assign(NDVI=(['time', 'y', 'x'],\n",
    "                               np.zeros((dat_out.dims['time'], dat_out.dims['y'], dat_out.dims['x'])) * np.nan)\n",
    "                         )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "41dc35ee-a1d9-449a-a962-6612574e360f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "888cb9cd-ae6d-4b59-b30c-5188e02b8fe9",
   "metadata": {},
   "outputs": [],
   "source": [
    "#dat_out['time'].isin(list(ndvi_test['time'].values)).values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ce955b0d-27dc-4222-a342-f2efb045db2c",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:         (time: 245, y: 324, x: 324, Pasture: 58)\n",
       "Coordinates:\n",
       "  * time            (time) object 2021-03-01 2021-03-02 ... 2021-10-31\n",
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       "    eo:cloud_cover  (time) float64 dask.array&lt;chunksize=(245,), meta=np.ndarray&gt;\n",
       "    epsg            int64 32613\n",
       "    Pasture         (y, x) &lt;U7 dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;\n",
       "Data variables:\n",
       "    NDVI            (time, y, x) float64 dask.array&lt;chunksize=(245, 50, 50), meta=np.ndarray&gt;\n",
       "    pct_valid       (Pasture, time) float64 dask.array&lt;chunksize=(58, 245), meta=np.ndarray&gt;\n",
       "Attributes:\n",
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       "    crs:         epsg:32613\n",
       "    transform:   | 30.00, 0.00, 499950.00|\\n| 0.00,-30.00, 4600860.00|\\n| 0.0...\n",
       "    resolution:  30</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d6d3a121-02d7-4dc8-a003-7365b2e69b9c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d6d3a121-02d7-4dc8-a003-7365b2e69b9c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 245</li><li><span class='xr-has-index'>y</span>: 324</li><li><span class='xr-has-index'>x</span>: 324</li><li><span class='xr-has-index'>Pasture</span>: 58</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-09d06f68-c382-4fe9-a33e-0659c8e0002f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-09d06f68-c382-4fe9-a33e-0659c8e0002f' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>2021-03-01 ... 2021-10-31</div><input id='attrs-f640e526-3ff1-41cb-9926-5438de885bcc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f640e526-3ff1-41cb-9926-5438de885bcc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68188ae6-6563-4674-b28c-f60b74a21711' class='xr-var-data-in' type='checkbox'><label for='data-68188ae6-6563-4674-b28c-f60b74a21711' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([datetime.date(2021, 3, 1), datetime.date(2021, 3, 2),\n",
       "       datetime.date(2021, 3, 3), ..., datetime.date(2021, 10, 29),\n",
       "       datetime.date(2021, 10, 30), datetime.date(2021, 10, 31)], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>id</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(245,), meta=np.ndarray&gt;</div><input id='attrs-1e64fc8e-982c-4e62-aad0-141261cf1e05' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1e64fc8e-982c-4e62-aad0-141261cf1e05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86027540-545a-462e-8f69-4e5a50b35adc' class='xr-var-data-in' type='checkbox'><label for='data-86027540-545a-462e-8f69-4e5a50b35adc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.91 kiB </td>\n",
       "                        <td> 1.91 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (245,) </td>\n",
       "                        <td> (245,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 7 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> object </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.176e+05 5.176e+05 ... 5.273e+05</div><input id='attrs-7b90ed40-926b-4b33-accb-409a3f80e7c5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7b90ed40-926b-4b33-accb-409a3f80e7c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c608398e-0faa-476a-9176-9d5212cce700' class='xr-var-data-in' type='checkbox'><label for='data-c608398e-0faa-476a-9176-9d5212cce700' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([517590., 517620., 517650., ..., 527220., 527250., 527280.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524e+06 4.524e+06 ... 4.515e+06</div><input id='attrs-cc6528ae-080f-462b-92f7-12ed9d43566e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cc6528ae-080f-462b-92f7-12ed9d43566e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e61b5d7-6dae-433f-ab11-30f7cefe69c9' class='xr-var-data-in' type='checkbox'><label for='data-9e61b5d7-6dae-433f-ab11-30f7cefe69c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([4524390., 4524360., 4524330., ..., 4514760., 4514730., 4514700.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>eo:cloud_cover</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(245,), meta=np.ndarray&gt;</div><input id='attrs-ee96af99-487d-48c2-9fad-61ea302f803a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ee96af99-487d-48c2-9fad-61ea302f803a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b4cf486-5118-4d66-9b56-500bcb91f06d' class='xr-var-data-in' type='checkbox'><label for='data-8b4cf486-5118-4d66-9b56-500bcb91f06d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.91 kiB </td>\n",
       "                        <td> 1.91 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (245,) </td>\n",
       "                        <td> (245,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 7 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>epsg</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>32613</div><input id='attrs-c2c6b495-78be-4c40-9b4b-d15135250fa1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c2c6b495-78be-4c40-9b4b-d15135250fa1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5cb58e7-5aa9-4077-bc7d-30f949d6a753' class='xr-var-data-in' type='checkbox'><label for='data-b5cb58e7-5aa9-4077-bc7d-30f949d6a753' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(32613)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Pasture</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>&lt;U7</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 50), meta=np.ndarray&gt;</div><input id='attrs-e21c9e53-101c-40ef-ad15-f112d6965e2d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e21c9e53-101c-40ef-ad15-f112d6965e2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62bbfada-3d25-4817-94cd-e93a2f11377c' class='xr-var-data-in' type='checkbox'><label for='data-62bbfada-3d25-4817-94cd-e93a2f11377c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.80 MiB </td>\n",
       "                        <td> 68.36 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (324, 324) </td>\n",
       "                        <td> (50, 50) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 49 Tasks </td>\n",
       "                        <td> 49 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> <U7 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-2c98526d-0711-4b3d-b6aa-ce7e8fdc83ab' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2c98526d-0711-4b3d-b6aa-ce7e8fdc83ab' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>NDVI</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(245, 50, 50), meta=np.ndarray&gt;</div><input id='attrs-cb02920f-498d-4fcf-a736-d01b4fba47d9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cb02920f-498d-4fcf-a736-d01b4fba47d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97dc62ca-44f5-4c5b-b0a7-b32c814ee182' class='xr-var-data-in' type='checkbox'><label for='data-97dc62ca-44f5-4c5b-b0a7-b32c814ee182' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 196.22 MiB </td>\n",
       "                        <td> 4.67 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 282 Tasks </td>\n",
       "                        <td> 49 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pct_valid</span></div><div class='xr-var-dims'>(Pasture, time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(58, 245), meta=np.ndarray&gt;</div><input id='attrs-47d68571-9d73-45fe-84b3-fe756a9eaeb4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-47d68571-9d73-45fe-84b3-fe756a9eaeb4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4857fa8-d8f8-467b-a53f-75f0f7801c2a' class='xr-var-data-in' type='checkbox'><label for='data-d4857fa8-d8f8-467b-a53f-75f0f7801c2a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 111.02 kiB </td>\n",
       "                        <td> 111.02 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (58, 245) </td>\n",
       "                        <td> (58, 245) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 9 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-7ea3fd94-6fc4-4cf9-b191-62be4f700348' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7ea3fd94-6fc4-4cf9-b191-62be4f700348' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>spec :</span></dt><dd>RasterSpec(epsg=32613, bounds=(499950, 4489410, 611460, 4600860), resolutions_xy=(30, 30))</dd><dt><span>crs :</span></dt><dd>epsg:32613</dd><dt><span>transform :</span></dt><dd>| 30.00, 0.00, 499950.00|\n",
       "| 0.00,-30.00, 4600860.00|\n",
       "| 0.00, 0.00, 1.00|</dd><dt><span>resolution :</span></dt><dd>30</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:         (time: 245, y: 324, x: 324, Pasture: 58)\n",
       "Coordinates:\n",
       "  * time            (time) object 2021-03-01 2021-03-02 ... 2021-10-31\n",
       "    id              (time) object dask.array<chunksize=(245,), meta=np.ndarray>\n",
       "  * x               (x) float64 5.176e+05 5.176e+05 ... 5.272e+05 5.273e+05\n",
       "  * y               (y) float64 4.524e+06 4.524e+06 ... 4.515e+06 4.515e+06\n",
       "    eo:cloud_cover  (time) float64 dask.array<chunksize=(245,), meta=np.ndarray>\n",
       "    epsg            int64 32613\n",
       "    Pasture         (y, x) <U7 dask.array<chunksize=(50, 50), meta=np.ndarray>\n",
       "Data variables:\n",
       "    NDVI            (time, y, x) float64 dask.array<chunksize=(245, 50, 50), meta=np.ndarray>\n",
       "    pct_valid       (Pasture, time) float64 dask.array<chunksize=(58, 245), meta=np.ndarray>\n",
       "Attributes:\n",
       "    spec:        RasterSpec(epsg=32613, bounds=(499950, 4489410, 611460, 4600...\n",
       "    crs:         epsg:32613\n",
       "    transform:   | 30.00, 0.00, 499950.00|\\n| 0.00,-30.00, 4600860.00|\\n| 0.0...\n",
       "    resolution:  30"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test3 = xr.merge([ndvi_test, dat_out], compat='override')\n",
    "test3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "a926bafa-455e-46c0-a664-7532d67d2227",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#test3.sel(time=datetime(2021, 5, 1).date())\n",
    "show(test3.isel(time=61)['NDVI'].data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "59336c47-63eb-46cc-911f-479b8e3b0a16",
   "metadata": {},
   "outputs": [],
   "source": [
    "test3['NDVI_despike'] = despike_ts_xr(test3['NDVI'], dat_thresh=0.07, dims=['time'])\n",
    "test3['NDVI_smooth'] = smooth_xr(test3['NDVI_despike'], dims=['time'], double=True, kwargs={'window1_min':5, 'window2': 5})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "fc706fb1-849a-439d-ba81-687dddad395a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#ndvi_test['NDVI_despike'] = despike_ts_xr(ndvi_test['NDVI'], dat_thresh=0.1, dims=['time'])\n",
    "#ndvi_test['NDVI_smooth'] = smooth_xr(ndvi_test['NDVI_despike'], dims=['time'], double=True, kwargs={'window1_min':5, 'window2': 5})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "b1cfc312-ebad-43aa-ad5c-3a45317b7d14",
   "metadata": {},
   "outputs": [],
   "source": [
    "test1 = test3.drop('pct_valid').groupby('Pasture').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b6a9b2ad-0feb-4bf6-b136-171d6f0c96c4",
   "metadata": {},
   "outputs": [
    {
     "ename": "KilledWorker",
     "evalue": "(\"('getitem-9ccaeef8ae55867469b8acc66d693bb8', 0, 6, 2)\", <WorkerState 'tls://10.6.26.50:34383', name: coiled-dask-kearney58-73235-worker-57e1c8d5a3, status: closed, memory: 0, processing: 12>)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKilledWorker\u001b[0m                              Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_6061/811865342.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mtest1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'pct_valid'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtest3\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'pct_valid'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mtest\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtest1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_dataframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/xarray/core/dataset.py\u001b[0m in \u001b[0;36mto_dataframe\u001b[0;34m(self, dim_order)\u001b[0m\n\u001b[1;32m   5392\u001b[0m         \u001b[0mordered_dims\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_normalize_dim_order\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdim_order\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdim_order\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5393\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5394\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_to_dataframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mordered_dims\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mordered_dims\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5395\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5396\u001b[0m     def _set_sparse_data_from_dataframe(\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/xarray/core/dataset.py\u001b[0m in \u001b[0;36m_to_dataframe\u001b[0;34m(self, ordered_dims)\u001b[0m\n\u001b[1;32m   5356\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_to_dataframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mordered_dims\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mMapping\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mAny\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5357\u001b[0m         \u001b[0mcolumns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvariables\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdims\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5358\u001b[0;31m         data = [\n\u001b[0m\u001b[1;32m   5359\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_variables\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_dims\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mordered_dims\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5360\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mcolumns\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/xarray/core/dataset.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m   5357\u001b[0m         \u001b[0mcolumns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvariables\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdims\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5358\u001b[0m         data = [\n\u001b[0;32m-> 5359\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_variables\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_dims\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mordered_dims\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5360\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mcolumns\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5361\u001b[0m         ]\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/xarray/core/variable.py\u001b[0m in \u001b[0;36mvalues\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    517\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    518\u001b[0m         \u001b[0;34m\"\"\"The variable's data as a numpy.ndarray\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 519\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_as_array_or_item\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    520\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    521\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetter\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/xarray/core/variable.py\u001b[0m in \u001b[0;36m_as_array_or_item\u001b[0;34m(data)\u001b[0m\n\u001b[1;32m    257\u001b[0m     \u001b[0mTODO\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mremove\u001b[0m \u001b[0mthis\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mreplace\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0monce\u001b[0m \u001b[0mthese\u001b[0m \u001b[0missues\u001b[0m \u001b[0mare\u001b[0m \u001b[0mfixed\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    258\u001b[0m     \"\"\"\n\u001b[0;32m--> 259\u001b[0;31m     \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    260\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    261\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkind\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"M\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/dask/array/core.py\u001b[0m in \u001b[0;36m__array__\u001b[0;34m(self, dtype, **kwargs)\u001b[0m\n\u001b[1;32m   1532\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1533\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__array__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1534\u001b[0;31m         \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcompute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1535\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mdtype\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdtype\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1536\u001b[0m             \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/dask/base.py\u001b[0m in \u001b[0;36mcompute\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m    286\u001b[0m         \u001b[0mdask\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbase\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcompute\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    287\u001b[0m         \"\"\"\n\u001b[0;32m--> 288\u001b[0;31m         \u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcompute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtraverse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    289\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    290\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/dask/base.py\u001b[0m in \u001b[0;36mcompute\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    568\u001b[0m         \u001b[0mpostcomputes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__dask_postcompute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    569\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 570\u001b[0;31m     \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mschedule\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdsk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkeys\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    571\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mrepack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresults\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpostcomputes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    572\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/client.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, dsk, keys, workers, allow_other_workers, resources, sync, asynchronous, direct, retries, priority, fifo_timeout, actors, **kwargs)\u001b[0m\n\u001b[1;32m   2720\u001b[0m                     \u001b[0mshould_rejoin\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2721\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2722\u001b[0;31m                 \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgather\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpacked\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0masynchronous\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0masynchronous\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdirect\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdirect\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2723\u001b[0m             \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2724\u001b[0m                 \u001b[0;32mfor\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfutures\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/client.py\u001b[0m in \u001b[0;36mgather\u001b[0;34m(self, futures, errors, direct, asynchronous)\u001b[0m\n\u001b[1;32m   1975\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1976\u001b[0m                 \u001b[0mlocal_worker\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1977\u001b[0;31m             return self.sync(\n\u001b[0m\u001b[1;32m   1978\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_gather\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1979\u001b[0m                 \u001b[0mfutures\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/client.py\u001b[0m in \u001b[0;36msync\u001b[0;34m(self, func, asynchronous, callback_timeout, *args, **kwargs)\u001b[0m\n\u001b[1;32m    863\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mfuture\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    864\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 865\u001b[0;31m             return sync(\n\u001b[0m\u001b[1;32m    866\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcallback_timeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcallback_timeout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    867\u001b[0m             )\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/utils.py\u001b[0m in \u001b[0;36msync\u001b[0;34m(loop, func, callback_timeout, *args, **kwargs)\u001b[0m\n\u001b[1;32m    325\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0merror\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    326\u001b[0m         \u001b[0mtyp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0merror\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 327\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    328\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    329\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/utils.py\u001b[0m in \u001b[0;36mf\u001b[0;34m()\u001b[0m\n\u001b[1;32m    308\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mcallback_timeout\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    309\u001b[0m                 \u001b[0mfuture\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0masyncio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwait_for\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfuture\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcallback_timeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 310\u001b[0;31m             \u001b[0mresult\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32myield\u001b[0m \u001b[0mfuture\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    311\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    312\u001b[0m             \u001b[0merror\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexc_info\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/tornado/gen.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    760\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    761\u001b[0m                     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 762\u001b[0;31m                         \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfuture\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    763\u001b[0m                     \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    764\u001b[0m                         \u001b[0mexc_info\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexc_info\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/client.py\u001b[0m in \u001b[0;36m_gather\u001b[0;34m(self, futures, errors, direct, local_worker)\u001b[0m\n\u001b[1;32m   1840\u001b[0m                             \u001b[0mexc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCancelledError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1841\u001b[0m                         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1842\u001b[0;31m                             \u001b[0;32mraise\u001b[0m \u001b[0mexception\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtraceback\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1843\u001b[0m                         \u001b[0;32mraise\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1844\u001b[0m                     \u001b[0;32mif\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"skip\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKilledWorker\u001b[0m: (\"('getitem-9ccaeef8ae55867469b8acc66d693bb8', 0, 6, 2)\", <WorkerState 'tls://10.6.26.50:34383', name: coiled-dask-kearney58-73235-worker-57e1c8d5a3, status: closed, memory: 0, processing: 12>)"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.client - ERROR - Failed to reconnect to scheduler after 30.00 seconds, closing client\n",
      "_GatheringFuture exception was never retrieved\n",
      "future: <_GatheringFuture finished exception=CancelledError()>\n",
      "asyncio.exceptions.CancelledError\n",
      "distributed.deploy.cluster - WARNING - Failed to sync cluster info multiple times - perhaps there's a connection issue? Error:\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/comm/tcp.py\", line 398, in connect\n",
      "    stream = await self.client.connect(\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/tornado/tcpclient.py\", line 275, in connect\n",
      "    af, addr, stream = await connector.start(connect_timeout=timeout)\n",
      "asyncio.exceptions.CancelledError\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/asyncio/tasks.py\", line 492, in wait_for\n",
      "    fut.result()\n",
      "asyncio.exceptions.CancelledError\n",
      "\n",
      "The above exception was the direct cause of the following exception:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/comm/core.py\", line 284, in connect\n",
      "    comm = await asyncio.wait_for(\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/asyncio/tasks.py\", line 494, in wait_for\n",
      "    raise exceptions.TimeoutError() from exc\n",
      "asyncio.exceptions.TimeoutError\n",
      "\n",
      "The above exception was the direct cause of the following exception:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/deploy/cluster.py\", line 115, in _sync_cluster_info\n",
      "    await self.scheduler_comm.set_metadata(\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/core.py\", line 785, in send_recv_from_rpc\n",
      "    comm = await self.live_comm()\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/core.py\", line 742, in live_comm\n",
      "    comm = await connect(\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/comm/core.py\", line 308, in connect\n",
      "    raise OSError(\n",
      "OSError: Timed out trying to connect to tls://52.25.139.227:8786 after 30 s\n"
     ]
    }
   ],
   "source": [
    "test1['pct_valid'] = test3['pct_valid']\n",
    "test = test1.to_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8d95ad2b-4370-415b-878c-fb9232ac177e",
   "metadata": {},
   "outputs": [],
   "source": [
    "test2 = test.reset_index(drop=False)[test.reset_index(drop=False)['Pasture'].isin(['19N', '15E'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3a77cd87-dfdd-4f58-90ca-afb84c6e0959",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pasture</th>\n",
       "      <th>time</th>\n",
       "      <th>NDVI</th>\n",
       "      <th>id</th>\n",
       "      <th>eo:cloud_cover</th>\n",
       "      <th>epsg</th>\n",
       "      <th>NDVI_despike</th>\n",
       "      <th>NDVI_smooth</th>\n",
       "      <th>pct_valid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2450</th>\n",
       "      <td>15E</td>\n",
       "      <td>2021-03-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32613</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.170060</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2451</th>\n",
       "      <td>15E</td>\n",
       "      <td>2021-03-02</td>\n",
       "      <td>0.168695</td>\n",
       "      <td>HLS.S30.T13TEF.2021061T175241.v2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32613</td>\n",
       "      <td>0.168695</td>\n",
       "      <td>0.170048</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2452</th>\n",
       "      <td>15E</td>\n",
       "      <td>2021-03-03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32613</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.169909</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2453</th>\n",
       "      <td>15E</td>\n",
       "      <td>2021-03-04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32613</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.169734</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2454</th>\n",
       "      <td>15E</td>\n",
       "      <td>2021-03-05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32613</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.169572</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Pasture        time      NDVI                                  id  \\\n",
       "2450     15E  2021-03-01       NaN                                 NaN   \n",
       "2451     15E  2021-03-02  0.168695  HLS.S30.T13TEF.2021061T175241.v2.0   \n",
       "2452     15E  2021-03-03       NaN                                 NaN   \n",
       "2453     15E  2021-03-04       NaN                                 NaN   \n",
       "2454     15E  2021-03-05       NaN                                 NaN   \n",
       "\n",
       "      eo:cloud_cover   epsg  NDVI_despike  NDVI_smooth  pct_valid  \n",
       "2450             NaN  32613           NaN     0.170060        NaN  \n",
       "2451             0.0  32613      0.168695     0.170048      100.0  \n",
       "2452             NaN  32613           NaN     0.169909        NaN  \n",
       "2453             NaN  32613           NaN     0.169734        NaN  \n",
       "2454             NaN  32613           NaN     0.169572        NaN  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "2b507f66-994c-415c-845a-91d4920d83e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='time', ylabel='NDVI_despike'>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.worker - WARNING - Heartbeat to scheduler failed\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/tornado/iostream.py\", line 971, in _handle_write\n",
      "    num_bytes = self.write_to_fd(self._write_buffer.peek(size))\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/tornado/iostream.py\", line 1148, in write_to_fd\n",
      "    return self.socket.send(data)  # type: ignore\n",
      "TimeoutError: [Errno 110] Connection timed out\n",
      "\n",
      "The above exception was the direct cause of the following exception:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/worker.py\", line 1190, in heartbeat\n",
      "    response = await retry_operation(\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/utils_comm.py\", line 385, in retry_operation\n",
      "    return await retry(\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/utils_comm.py\", line 370, in retry\n",
      "    return await coro()\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/core.py\", line 863, in send_recv_from_rpc\n",
      "    result = await send_recv(comm=comm, op=key, **kwargs)\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/core.py\", line 640, in send_recv\n",
      "    response = await comm.read(deserializers=deserializers)\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/comm/tcp.py\", line 221, in read\n",
      "    convert_stream_closed_error(self, e)\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/comm/tcp.py\", line 126, in convert_stream_closed_error\n",
      "    raise CommClosedError(f\"in {obj}: {exc.__class__.__name__}: {exc}\") from exc\n",
      "distributed.comm.core.CommClosedError: in <TCP (closed) ConnectionPool.heartbeat_worker local=tcp://127.0.0.1:33338 remote=tcp://127.0.0.1:43631>: TimeoutError: [Errno 110] Connection timed out\n",
      "distributed.worker - WARNING - Heartbeat to scheduler failed\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/tornado/iostream.py\", line 971, in _handle_write\n",
      "    num_bytes = self.write_to_fd(self._write_buffer.peek(size))\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/tornado/iostream.py\", line 1148, in write_to_fd\n",
      "    return self.socket.send(data)  # type: ignore\n",
      "TimeoutError: [Errno 110] Connection timed out\n",
      "\n",
      "The above exception was the direct cause of the following exception:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/worker.py\", line 1190, in heartbeat\n",
      "    response = await retry_operation(\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/utils_comm.py\", line 385, in retry_operation\n",
      "    return await retry(\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/utils_comm.py\", line 370, in retry\n",
      "    return await coro()\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/core.py\", line 863, in send_recv_from_rpc\n",
      "    result = await send_recv(comm=comm, op=key, **kwargs)\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/core.py\", line 640, in send_recv\n",
      "    response = await comm.read(deserializers=deserializers)\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/comm/tcp.py\", line 221, in read\n",
      "    convert_stream_closed_error(self, e)\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/comm/tcp.py\", line 126, in convert_stream_closed_error\n",
      "    raise CommClosedError(f\"in {obj}: {exc.__class__.__name__}: {exc}\") from exc\n",
      "distributed.comm.core.CommClosedError: in <TCP (closed) ConnectionPool.heartbeat_worker local=tcp://127.0.0.1:33332 remote=tcp://127.0.0.1:43631>: TimeoutError: [Errno 110] Connection timed out\n"
     ]
    }
   ],
   "source": [
    "ax=test2[test2['Pasture']=='19N'].plot.scatter(x='time', y='NDVI', c='green')\n",
    "ax=test2[test2['Pasture']=='19N'].plot.scatter(x='time', y='NDVI_despike', c='orange', ax=ax)\n",
    "test2[test2['Pasture']=='19N'].plot(x='time', y='NDVI_smooth', ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "ac15b450-afe2-4258-9f71-0056ae658619",
   "metadata": {},
   "outputs": [],
   "source": [
    "from src.hls_funcs.smooth import despike_ts, double_savgol\n",
    "test2['NDVI_smooth2'] = test2.groupby('Pasture')['NDVI'].apply(double_savgol, double=False, window1_min=5, window2=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4831aa01-4f7c-4fd9-befc-19b540af2378",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "620c51c0-e599-40e4-ac56-1722a9384bf7",
   "metadata": {},
   "outputs": [],
   "source": [
    "ndvi_despike = despike_ts_xr(ndvi_test, dat_thresh=0.1, dims=['time'])\n",
    "ndvi_sm = smooth_xr(ndvi_despike, dims=['time'], double=True, kwargs={'window1_min':5, 'window2': 5})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "728711bc-d01c-4d96-94b5-5f9d9e8e2155",
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'seaborn'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_954/2392715083.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mseaborn\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msns\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'seaborn'"
     ]
    }
   ],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "5c3ca82b-3fa3-4900-a7cd-f116ba9e9464",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.16875508, 0.17463448, 0.18003539, 0.18326259,        nan,\n",
       "              nan, 0.18872243,        nan,        nan, 0.26117325,\n",
       "       0.22882797, 0.24263185, 0.25242543, 0.28867242, 0.36582979,\n",
       "              nan, 0.37327333,        nan, 0.34813588, 0.42817396])"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ndvi_test.mean(dim=['x', 'y']).values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "cf238556-deb8-48a1-bb31-e3cba9340e14",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "show(ndvi_test.isel(time=2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "985ddfc6-d2d2-4b4a-9efd-4a0a584e7f5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.patches.Polygon at 0x7f1a2c208730>]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "#from descartes import PolygonPatch\n",
    "fig, ax = plt.subplots(figsize=(12, 8))\n",
    "show(ndvi_test['NDVI'].isel(time=3), transform=ndvi_ds.attrs['transform'], ax=ax)\n",
    "#ax = mpl.pyplot.gca()\n",
    "xs, ys = cper_mask_shp[0][0].exterior.xy\n",
    "ax.fill(xs, ys, alpha=0.5, fc='r', ec='none')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "593a267c-64fc-4f2f-8415-8c25bf74b591",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['10S', '10SNE', '11NS', '11NW', '12C', '12NE', '12NW', '13E',\n",
       "       '13W', '14', '15E', '15NWS', '15SW', '17N', '17S', '18N', '18S',\n",
       "       '19N', '19S', '1E', '1W', '20NW', '20SE', '21N', '21S', '21SW',\n",
       "       '22E', '22W', '23E', '23W', '24E', '24Strip', '24W', '25NW',\n",
       "       '25SE', '26E', '26W', '28N', '29-30', '30NW', '30SW', '31E', '31W',\n",
       "       '32W', '5E', '5W', '6EE', '6EW', '7NW', '7SE', '8E', '8NW', '8SE',\n",
       "       '8SW', 'CN', 'HQ', 'Slayton', 'UNK'], dtype='<U7')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(ndvi_ds['Pasture'].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "d00ad354-602f-4dce-93dd-fc7f5ff91394",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Affine(30.0, 0.0, 517575.0,\n",
       "       0.0, -30.0, 4524405.0)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ndvi_ds.rio.transform()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "46423e0a-e7d9-4f83-860a-1a9d1ba9aaf6",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dict = {'date_range': [str(datetime(2021, 3, 1).date()), str(datetime(2021, 10, 30).date())]}\n",
    "tmp_data = fetch.get_hls(['spkearney', '1mrChamu'], hls_data=data_dict, aws=True)\n",
    "da = tmp_data.loc[dict(x=slice(517587.0, 527283.0), y=slice(4524402.0, 4514699.0))]\n",
    "da_mask = mask_hls(da['FMASK'])\n",
    "da = da.where(da_mask == 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "fe4eac93-b564-4242-b654-0c83fc0c2673",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.16473306, 0.16378575,        nan,        nan, 0.0634091 ,\n",
       "       0.00390197, 0.11879054, 0.16833161, 0.15954587, 0.15991301,\n",
       "       0.16094027, 0.16725394, 0.17561154, 0.17685513,        nan,\n",
       "              nan, 0.18337277, 0.19368803,        nan, 0.27445619,\n",
       "       0.2253724 , 0.24056128, 0.24424153, 0.2877616 , 0.36418753,\n",
       "              nan, 0.33788244, 0.34569757, 0.33123684, 0.40755053,\n",
       "       0.37426155, 0.36762935, 0.38202716,        nan, 0.38124757,\n",
       "       0.37398769,        nan, 0.36399018, 0.33478624,        nan,\n",
       "       0.43606091])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ndvi = ndvi_func(da)\n",
    "ndvi_ts = ndvi.mean(dim=['y', 'x'])\n",
    "ndvi_ts.values\n",
    "#show(ndvi.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "210cb434-f20e-4243-be87-0b4bf879060a",
   "metadata": {},
   "outputs": [],
   "source": [
    "ndvi_ts.to_pandas().to_csv('ndvi_ts_test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "040bf39c-aec6-4f63-976e-3110440f091c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.client - ERROR - Failed to reconnect to scheduler after 30.00 seconds, closing client\n",
      "_GatheringFuture exception was never retrieved\n",
      "future: <_GatheringFuture finished exception=CancelledError()>\n",
      "asyncio.exceptions.CancelledError\n"
     ]
    }
   ],
   "source": [
    "coiled.list_clusters()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6cfc7d52-980d-4849-9862-d2a8f278542d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "distributed.deploy.cluster - WARNING - Failed to sync cluster info multiple times - perhaps there's a connection issue? Error:\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/comm/tcp.py\", line 398, in connect\n",
      "    stream = await self.client.connect(\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/tornado/tcpclient.py\", line 275, in connect\n",
      "    af, addr, stream = await connector.start(connect_timeout=timeout)\n",
      "asyncio.exceptions.CancelledError\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/asyncio/tasks.py\", line 492, in wait_for\n",
      "    fut.result()\n",
      "asyncio.exceptions.CancelledError\n",
      "\n",
      "The above exception was the direct cause of the following exception:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/comm/core.py\", line 284, in connect\n",
      "    comm = await asyncio.wait_for(\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/asyncio/tasks.py\", line 494, in wait_for\n",
      "    raise exceptions.TimeoutError() from exc\n",
      "asyncio.exceptions.TimeoutError\n",
      "\n",
      "The above exception was the direct cause of the following exception:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/deploy/cluster.py\", line 115, in _sync_cluster_info\n",
      "    await self.scheduler_comm.set_metadata(\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/core.py\", line 785, in send_recv_from_rpc\n",
      "    comm = await self.live_comm()\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/core.py\", line 742, in live_comm\n",
      "    comm = await connect(\n",
      "  File \"/home/spkearney/miniconda3/envs/hls_cog2_env/lib/python3.9/site-packages/distributed/comm/core.py\", line 308, in connect\n",
      "    raise OSError(\n",
      "OSError: Timed out trying to connect to tls://54.184.250.220:8786 after 30 s\n"
     ]
    }
   ],
   "source": [
    "#coiled.delete_cluster(name='hls_cog_coiled')  # Add your cluster name here\n",
    "client.close()  # Close the client as well"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c0c466c0-6825-4901-bdbc-08e8c7bfc44d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#%%time\n",
    "#items = pystac_client.Client.open(\n",
    "#    \"https://earth-search.aws.element84.com/v0\"\n",
    "#).search(\n",
    "#    intersects=dict(type=\"Point\", coordinates=[-106, 35.7]),\n",
    "#    collections=[\"sentinel-s2-l2a-cogs\"],\n",
    "#    datetime=\"2019-01-01/2020-01-01\",\n",
    "#    limit=10_000,\n",
    "#).get_all_items()\n",
    "#len(items)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "50e4e42f-fe8d-4212-929b-308bda4667d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "from src.hls_funcs import fetch\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "50b1c46a-97c2-40cf-b9f2-f1c43bafe27a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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