data_visualization_demo.ipynb

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   "execution_count": 2,
   "id": "d80051d6-058b-4e6e-99ad-4011d06562cf",
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    "tags": []
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   "source": [
    "import os\n",
    "import s3fs\n",
    "import glob\n",
    "import zarr\n",
    "import boto3\n",
    "import fsspec\n",
    "import pathlib\n",
    "import dask.array\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "import geopandas as gpd\n",
    "import rioxarray as rxr\n",
    "\n",
    "import rasterio\n",
    "from rasterio.crs import CRS\n",
    "from rasterio.transform import Affine\n",
    "from rasterio.plot import show, plotting_extent\n",
    "\n",
    "import cartopy\n",
    "import cartopy.crs as ccrs\n",
    "\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from shapely.geometry import box, mapping, shape, Point, LineString, MultiPolygon, LinearRing, Polygon\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "768ce41f-b0e5-4b1f-9628-72c4aef2c7a0",
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   "outputs": [],
   "source": [
    "# Delete this block once we are in GDAL >= 3.5\n",
    "awsdir = pathlib.Path(\"~/.aws\").expanduser()\n",
    "awsdir.mkdir(exist_ok=True)\n",
    "awscred = awsdir / \"credentials\"\n",
    "\n",
    "session = boto3.session.Session()\n",
    "credentials = session.get_credentials()\n",
    "credentials = credentials.get_frozen_credentials()\n",
    "\n",
    "#Credentials are refreshable, so accessing your access key / secret key\n",
    "#separately can lead to a race condition. Use this to get an actual matched\n",
    "#set. \n",
    "\n",
    "outstring = f\"\"\"\n",
    "[default]\n",
    "aws_access_key_id={credentials.access_key}\n",
    "aws_secret_access_key={credentials.secret_key}\n",
    "aws_session_token={credentials.token}\n",
    "\"\"\"\n",
    "with awscred.open(mode='w') as f:\n",
    "    f.write(outstring)"
   ]
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  {
   "cell_type": "markdown",
   "id": "a12d46ee-90ab-4d20-a9be-ae8111cf281a",
   "metadata": {},
   "source": [
    "# Read in AVIRIS data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a7f1a645-17a0-4fa0-a37c-d1a3f1b66fd2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Connect to AWS S3 storage\n",
    "s3 = s3fs.S3FileSystem(anon=False, client_kwargs=dict(region_name='us-west-2'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a96fa617-e57b-4e85-a5ff-135f070d6b5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "bucket = 'dh-shift-curated'\n",
    "key = 'aviris/20220228/'\n",
    "s3_key = os.path.join(bucket, key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "af5053dc-d919-4834-804f-07c0511f0def",
   "metadata": {},
   "outputs": [],
   "source": [
    "# An example flight path from the date 20220228\n",
    "item = 'ang20220228t190702'\n",
    "s3_path = f's3://{s3_key}{item}_100-100-100.zarr'\n",
    "store = s3fs.S3Map(root=s3_path, s3=s3, check=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "44c50a21-fc9d-461d-9e65-d144fe8123ba",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Read in Zarr dataset using xarray\n",
    "ds = xr.open_zarr(store=store, decode_coords='all', consolidated=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fc3b1e57-e5f9-45c7-ab45-c003f52b37c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CRS.from_epsg(32610)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check the coordinate reference system\n",
    "ds.rio.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a130255e-f298-44a3-890f-dc91442bac1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set dimensions and coordinates\n",
    "ds = ds.rio.set_spatial_dims(x_dim='x', y_dim='y')\n",
    "ds = ds.set_coords(('Easting', 'Northing'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fd0d802-f4f7-4a9f-bcc5-24d6fc7bf045",
   "metadata": {},
   "source": [
    "The Zarr dataset has dimensions `x`, `y`, and `wavelength`. The coordinates include the `Easting` and `Northing` coordinates. Data variables include `Elevation`, `Radiance`, and `Reflectance`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c71e2497-534e-49db-b88c-52766cf2256d",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:      (x: 598, y: 16418, wavelength: 425)\n",
       "Coordinates:\n",
       "    Easting      (x, y) float64 dask.array&lt;chunksize=(100, 100), meta=np.ndarray&gt;\n",
       "    Northing     (x, y) float64 dask.array&lt;chunksize=(100, 100), meta=np.ndarray&gt;\n",
       "    band         (wavelength) int64 dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;\n",
       "    fwhm         (wavelength) float64 dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;\n",
       "    spatial_ref  int64 ...\n",
       "  * wavelength   (wavelength) float64 377.1 382.1 387.1 ... 2.496e+03 2.501e+03\n",
       "  * x            (x) float64 0.5 1.5 2.5 3.5 4.5 ... 594.5 595.5 596.5 597.5\n",
       "  * y            (y) float64 0.5 1.5 2.5 3.5 ... 1.642e+04 1.642e+04 1.642e+04\n",
       "Data variables:\n",
       "    Elevation    (x, y) float64 dask.array&lt;chunksize=(100, 100), meta=np.ndarray&gt;\n",
       "    Radiance     (x, y, wavelength) float32 dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;\n",
       "    Reflectance  (x, y, wavelength) float32 dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;</pre><div class='xr-wrap' style='display:none'><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-f50a6f38-5530-4ef9-bae5-c765e1c59c88' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f50a6f38-5530-4ef9-bae5-c765e1c59c88' 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'>x</span>: 598</li><li><span class='xr-has-index'>y</span>: 16418</li><li><span class='xr-has-index'>wavelength</span>: 425</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f01babc0-f5d8-4b0d-997e-b9448a3440a3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f01babc0-f5d8-4b0d-997e-b9448a3440a3' class='xr-section-summary' >Coordinates: <span>(8)</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>Easting</span></div><div class='xr-var-dims'>(x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 100), meta=np.ndarray&gt;</div><input id='attrs-4481cc9c-a7c2-49b5-9bef-d3692225f104' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4481cc9c-a7c2-49b5-9bef-d3692225f104' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84ef04e8-500d-4681-9db5-3b1e6eda911f' class='xr-var-data-in' type='checkbox'><label for='data-84ef04e8-500d-4681-9db5-3b1e6eda911f' 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> 74.91 MiB </td>\n",
       "                        <td> 78.12 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (598, 16418) </td>\n",
       "                        <td> (100, 100) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 991 Tasks </td>\n",
       "                        <td> 990 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "            </table>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Northing</span></div><div class='xr-var-dims'>(x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 100), meta=np.ndarray&gt;</div><input id='attrs-34e1e98c-b985-443b-9587-096d67379ac9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-34e1e98c-b985-443b-9587-096d67379ac9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9950c24c-9339-4dcb-9f8d-a0926cb59ce7' class='xr-var-data-in' type='checkbox'><label for='data-9950c24c-9339-4dcb-9f8d-a0926cb59ce7' 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> 74.91 MiB </td>\n",
       "                        <td> 78.12 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (598, 16418) </td>\n",
       "                        <td> (100, 100) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 991 Tasks </td>\n",
       "                        <td> 990 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>band</span></div><div class='xr-var-dims'>(wavelength)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-5339e14d-ff37-414f-bb5b-0281269b9688' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5339e14d-ff37-414f-bb5b-0281269b9688' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d7c3c60-7082-4437-8b10-3dc8e0389104' class='xr-var-data-in' type='checkbox'><label for='data-5d7c3c60-7082-4437-8b10-3dc8e0389104' 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",
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       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 3.32 kiB </td>\n",
       "                        <td> 800 B </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (100,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 6 Tasks </td>\n",
       "                        <td> 5 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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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fwhm</span></div><div class='xr-var-dims'>(wavelength)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-6a2da5cd-c6b3-4018-9db3-dbbeddbcc4cd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6a2da5cd-c6b3-4018-9db3-dbbeddbcc4cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8feb9cde-aec3-4138-8af1-255e4ac48d85' class='xr-var-data-in' type='checkbox'><label for='data-8feb9cde-aec3-4138-8af1-255e4ac48d85' 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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       "        <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> 3.32 kiB </td>\n",
       "                        <td> 800 B </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (425,) </td>\n",
       "                        <td> (100,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 6 Tasks </td>\n",
       "                        <td> 5 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </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>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-743f553f-e655-4889-aff6-25cc76507d4c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-743f553f-e655-4889-aff6-25cc76507d4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4f16a3d-cb08-4706-beb4-fb9a96bce9cb' class='xr-var-data-in' type='checkbox'><label for='data-a4f16a3d-cb08-4706-beb4-fb9a96bce9cb' 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'><dt><span>GeoTransform :</span></dt><dd>0.0 1.0 0.0 0.0 0.0 1.0</dd><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 10N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,-123],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32610&quot;]]</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>-123.0</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 10N</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 10N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,-123],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32610&quot;]]</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>wavelength</span></div><div class='xr-var-dims'>(wavelength)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>377.1 382.1 ... 2.496e+03 2.501e+03</div><input id='attrs-81c05e3e-4d6c-44a3-83c6-af987f730c98' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-81c05e3e-4d6c-44a3-83c6-af987f730c98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e17f7af0-dacb-46a7-ab7a-00d061455b31' class='xr-var-data-in' type='checkbox'><label for='data-e17f7af0-dacb-46a7-ab7a-00d061455b31' 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([ 377.071821,  382.081821,  387.091821, ..., 2490.731821, 2495.741821,\n",
       "       2500.751821])</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'>0.5 1.5 2.5 ... 595.5 596.5 597.5</div><input id='attrs-be1600a7-54a7-4778-b791-df2137ba16ca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-be1600a7-54a7-4778-b791-df2137ba16ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f6a0fb0-a4ad-4a11-99f6-46485f42084a' class='xr-var-data-in' type='checkbox'><label for='data-9f6a0fb0-a4ad-4a11-99f6-46485f42084a' 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([5.000e-01, 1.500e+00, 2.500e+00, ..., 5.955e+02, 5.965e+02, 5.975e+02])</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'>0.5 1.5 2.5 ... 1.642e+04 1.642e+04</div><input id='attrs-a94ae5bc-c92d-4bd6-a7ed-f0c76bc0a02a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a94ae5bc-c92d-4bd6-a7ed-f0c76bc0a02a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef3e9a57-faf8-4e2e-a494-623430c476e9' class='xr-var-data-in' type='checkbox'><label for='data-ef3e9a57-faf8-4e2e-a494-623430c476e9' 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([5.00000e-01, 1.50000e+00, 2.50000e+00, ..., 1.64155e+04, 1.64165e+04,\n",
       "       1.64175e+04])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-932bc0fc-66a7-40b1-b473-15ea9bf3e018' class='xr-section-summary-in' type='checkbox'  checked><label for='section-932bc0fc-66a7-40b1-b473-15ea9bf3e018' class='xr-section-summary' >Data variables: <span>(3)</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>Elevation</span></div><div class='xr-var-dims'>(x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 100), meta=np.ndarray&gt;</div><input id='attrs-6085ece6-deb7-42dd-8ad6-d6f41f91cce9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6085ece6-deb7-42dd-8ad6-d6f41f91cce9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4a5fa03-62bd-4db8-a3db-6262b57b23b1' class='xr-var-data-in' type='checkbox'><label for='data-e4a5fa03-62bd-4db8-a3db-6262b57b23b1' 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> 74.91 MiB </td>\n",
       "                        <td> 78.12 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (598, 16418) </td>\n",
       "                        <td> (100, 100) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 991 Tasks </td>\n",
       "                        <td> 990 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Radiance</span></div><div class='xr-var-dims'>(x, y, wavelength)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 100, 100), meta=np.ndarray&gt;</div><input id='attrs-05170853-2cf0-4279-9760-29de3730f635' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05170853-2cf0-4279-9760-29de3730f635' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6490dadf-b621-4b05-9374-f8721e276777' class='xr-var-data-in' type='checkbox'><label for='data-6490dadf-b621-4b05-9374-f8721e276777' 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'><dt><span>bad_pixel_map :</span></dt><dd>/home/jchapman/src/isat/ang/cal/data/ANGv5_bad</dd><dt><span>bands :</span></dt><dd>425</dd><dt><span>byte_order :</span></dt><dd>0</dd><dt><span>crosstrack_scatter_file :</span></dt><dd>/home/jchapman/src/isat/ang/cal/data/20170125_via_ang20160925t182412_crf</dd><dt><span>data_type :</span></dt><dd>4</dd><dt><span>description :</span></dt><dd>  AVIRIS-NG Measured Radiances in uW nm-1 cm-2 sr-1</dd><dt><span>file_type :</span></dt><dd>ENVI</dd><dt><span>flat_field_file :</span></dt><dd>/home/jchapman/src/isat/ang/cal/data/20210420_ang20210417_BLUSS_avg_rows300-340_ff</dd><dt><span>header_offset :</span></dt><dd>0</dd><dt><span>interleave :</span></dt><dd>bil</dd><dt><span>lines :</span></dt><dd>16418</dd><dt><span>long_name :</span></dt><dd>[&#x27;377.071821 Nanometers&#x27;, &#x27;382.081821 Nanometers&#x27;, &#x27;387.091821 Nanometers&#x27;, &#x27;392.10182100000003 Nanometers&#x27;, &#x27;397.10182100000003 Nanometers&#x27;, &#x27;402.11182099999996 Nanometers&#x27;, &#x27;407.121821 Nanometers&#x27;, &#x27;412.131821 Nanometers&#x27;, 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       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"29.15429033702463,19.15429033702463 59.66981020524871,19.15429033702463 59.66981020524871,139.15429033702463 29.15429033702463,139.15429033702463\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"44.412050\" y=\"159.154290\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >425</text>\n",
       "  <text x=\"79.669810\" y=\"79.154290\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,79.669810,79.154290)\">16418</text>\n",
       "  <text x=\"9.577145\" y=\"149.577145\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,9.577145,149.577145)\">598</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6dd50577-0d50-4435-a583-ccb914b94b82' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6dd50577-0d50-4435-a583-ccb914b94b82' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:      (x: 598, y: 16418, wavelength: 425)\n",
       "Coordinates:\n",
       "    Easting      (x, y) float64 dask.array<chunksize=(100, 100), meta=np.ndarray>\n",
       "    Northing     (x, y) float64 dask.array<chunksize=(100, 100), meta=np.ndarray>\n",
       "    band         (wavelength) int64 dask.array<chunksize=(100,), meta=np.ndarray>\n",
       "    fwhm         (wavelength) float64 dask.array<chunksize=(100,), meta=np.ndarray>\n",
       "    spatial_ref  int64 ...\n",
       "  * wavelength   (wavelength) float64 377.1 382.1 387.1 ... 2.496e+03 2.501e+03\n",
       "  * x            (x) float64 0.5 1.5 2.5 3.5 4.5 ... 594.5 595.5 596.5 597.5\n",
       "  * y            (y) float64 0.5 1.5 2.5 3.5 ... 1.642e+04 1.642e+04 1.642e+04\n",
       "Data variables:\n",
       "    Elevation    (x, y) float64 dask.array<chunksize=(100, 100), meta=np.ndarray>\n",
       "    Radiance     (x, y, wavelength) float32 dask.array<chunksize=(100, 100, 100), meta=np.ndarray>\n",
       "    Reflectance  (x, y, wavelength) float32 dask.array<chunksize=(100, 100, 100), meta=np.ndarray>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30b9edfb-7f9c-49e9-8cd8-31b21d8dc2bc",
   "metadata": {},
   "source": [
    "# Visualize RGB composite map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "05323d83-54d9-41ba-9b53-fc1b5a763b47",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Select single wavelength bands\n",
    "Red = ds.sel(wavelength=670, method='nearest').Reflectance\n",
    "Green = ds.sel(wavelength=550, method='nearest').Reflectance\n",
    "Blue = ds.sel(wavelength=440, method='nearest').Reflectance"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1826e49b-7b0d-43f2-9aba-cf869ba3de30",
   "metadata": {},
   "source": [
    "Plot individual band maps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "fbf529cd-9bcc-4364-8523-ba91ceaee8ff",
   "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"
    }
   ],
   "source": [
    "Red.plot.pcolormesh('Easting', 'Northing', robust=True, add_colorbar=False)\n",
    "plt.title('Red band');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "fc38c3fd-b121-4dae-848d-524ac886a711",
   "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"
    }
   ],
   "source": [
    "Green.plot.pcolormesh('Easting', 'Northing', robust=True, add_colorbar=False)\n",
    "plt.title('Green band');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "56e7190a-9bdc-4e6d-b1f8-4dd3f4412b99",
   "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"
    }
   ],
   "source": [
    "Blue.plot.pcolormesh('Easting', 'Northing', robust=True, add_colorbar=False)\n",
    "plt.title('Blue band');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "9a597caa-bdc7-48df-844a-750e346fa254",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Select an RGB composite \n",
    "RGB = ds.sel(wavelength=[670,550,440], method='nearest').Reflectance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "654d1c9c-2fb8-41d4-a43b-6497b5f94a2e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,1))\n",
    "RGB.plot.imshow();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b0c307d-fa65-4612-afd0-bc174c0bc7bd",
   "metadata": {},
   "source": [
    "Need a functionality to plot RGB composite in spatially correct space (with Northing and Easting coordinates)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fbaf054-a486-483e-8fbf-ea5bf2c7003b",
   "metadata": {},
   "source": [
    "# Subset spatial region \n",
    "\n",
    "A common data operation is to subset a particular region using a shape vector. We first attempted to use available spatial tools, such as the `rasterio` package (Method 1 below). However, some custom code that implements shape masking is required to successfully subset a region (Method 2)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac9afc48-dcdc-4877-a82d-5d39a38575cb",
   "metadata": {},
   "source": [
    "## Method 1: Using available spatial packages\n",
    "\n",
    "This method attempts to define an affine transform for the dataset, create a shape using geopanda GeoDataFrame, and clip the region defined by the shape using `clip()` from rasterio. However, this function subsets the data based on the data dimensions `x` and `y` while we wish to work in Easting and Northing coordinates. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "a0117a56-6567-4e1c-a22e-fbb396dc0607",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Simple box: top left and bottom right Easting and Northing coordinates\n",
    "box_minx = 723500 \n",
    "box_maxx = 726000 \n",
    "box_miny = 3824000 \n",
    "box_maxy = 3826000 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "da466968-73db-46da-93a7-a40638cd59a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def affine_from_bounds(ds):\n",
    "    m = len(ds.x)  # Number of columns\n",
    "    n = len(ds.y)  # Number of rows\n",
    "    \n",
    "    ul = ds.isel(x=0, y=0)  # Upper left corner\n",
    "    ur = ds.isel(x=-1, y=0) # Upper right corner\n",
    "    ll = ds.isel(x=0, y=-1) # Lower left corner\n",
    "    lr = ds.isel(x=-1, y=-1) # Lower right corner\n",
    "    \n",
    "    ul2 = (ul.Easting.values, ul.Northing.values)\n",
    "    ur2 = (ur.Easting.values, ur.Northing.values)\n",
    "    ll2 = (ll.Easting.values, ll.Northing.values)\n",
    "    lr2 = (lr.Easting.values, lr.Northing.values)\n",
    "\n",
    "    # Affine transform is defined by 6 values as follows:\n",
    "    #   x' = ax + by + c\n",
    "    #   y' = dx + ey + f\n",
    "    # where...\n",
    "    #   x', y' --> True coordinates\n",
    "    #   x, y --> \"Relative\"/pixel coordinates; defined such that (0,0) is the top\n",
    "    #     left corner, and (m-1,n-1) is the bottom right corner (note: y axis is\n",
    "    #     implicitly upside down here!).\n",
    "\n",
    "    # Upper left corner: x=0, y=0, so this just simplifies to:\n",
    "    #   x'(ul) = c\n",
    "    #   y'(ul) = f\n",
    "    c = ul2[0]\n",
    "    f = ul2[0]\n",
    "\n",
    "    # Upper right corner: x=m-1, y=0.\n",
    "    # Plug in and rearrange:\n",
    "    a = (ur2[0] - c) / (m-1)\n",
    "    d = (ur2[1] - f) / (m-1)\n",
    "\n",
    "    # Lower right corner: x=0, y=n-1\n",
    "    # Plug in and rearrange:\n",
    "    b = (ll2[0] - c) / (n-1)\n",
    "    e = (ll2[1] - f) / (n-1)\n",
    "\n",
    "    return Affine(a, b, c,\n",
    "                  d, e, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "717e5190-e80e-4379-94f9-f89bece1a725",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Affine(-3.0722393616072607, 3.374327498608259, 720069.5182464843,\n",
       "       5195.55192133833, 191.447497381507, 720069.5182464843)"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_transform = affine_from_bounds(ds)\n",
    "ds_transform"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "ad1ae41e-f5b0-4387-a77c-5d9cedb1617c",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = ds.rio.write_transform(ds_transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "ca571527-4df2-45a8-92ff-591c4a6e7016",
   "metadata": {},
   "outputs": [],
   "source": [
    "geodf = gpd.GeoDataFrame(geometry=[box(box_minx, box_miny,\n",
    "                                       box_maxx, box_maxy)],\n",
    "                         crs='EPSG:32610')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "007c52df-6079-4945-85a3-e343447fd0aa",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.9/site-packages/rioxarray/rioxarray.py:620: UserWarning: Transform that is non-rectilinear or with rotation found. Unable to recalculate.\n",
      "  warnings.warn(\n",
      "/opt/conda/lib/python3.9/site-packages/rioxarray/rioxarray.py:620: UserWarning: Transform that is non-rectilinear or with rotation found. Unable to recalculate.\n",
      "  warnings.warn(\n",
      "/opt/conda/lib/python3.9/site-packages/rioxarray/rioxarray.py:620: UserWarning: Transform that is non-rectilinear or with rotation found. Unable to recalculate.\n",
      "  warnings.warn(\n",
      "/opt/conda/lib/python3.9/site-packages/rioxarray/rioxarray.py:620: UserWarning: Transform that is non-rectilinear or with rotation found. Unable to recalculate.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "clipped = ds.rio.clip(geodf.geometry, geodf.crs, drop=True, invert=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "62a0b490-24dc-4d12-a946-1b2498c8a564",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f2669addfd0>"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PN8ex99hN+77MxlI2acxK1dbWRl2dZ0qbWft1SJcvoG7d+d3bN7XaMSXNioja0vQiv2djZmZVNHX9r6pdhX/x7WrMzKxwDjZmZu3EoGt+wq2LPlLtamwUBxszszZu3xOzQf3nv34mR+38eJVrs3EcbMzM2rhZV1f+9jGtzcHGzMwK52BjZmaFc7AxM7PCOdiYmVnhHGzMzKxwDjZmZm3E0M9eVu0qFMa3qzEzawM+8pUrePz2M6pdjcK4ZWNm1gZ0+We1a1Ast2zMzKps/V8HM+P//lTtahTKLRszsyp69eUBdHlvxw404GBjZlZV+9387WpXoVU42JiZVdGzpzvYmJmZVURhwUZST0kzJT0laZ6kCxvIs6Wku3J5Rqf0gZIelLQgpY/NlblV0uy0PC9pdm7bOZIWSVooaUQufV9Jc9K2n0tSUedtZmbvVmTLZg0wLCL2BoYAIyUdUJLnZGB+yvNJ4HJJmwFrgdMjYjfgAOBkSR8CiIijImJIRAwBJgGTAdL2o4HdgZHALyR1Tce5CjgR+GBaRhZyxmZmOXt8Z1y1q9BmFDb1OSICWJ0edk9LlGYD+qSWRm/gNWBtRCwFlqb9rJK0ANgBmF9fMJX5IjAsJR0O3BIRa4DnJC0C9pP0PNA3Iv6Yyt0IHAFMqegJm5kl+3xzHF3WwtwO8Ds0lVLomI2krqmbaxkwNSJmlGS5EtgNeBmYA4yNiPUl+xgE7AOUlh0KvBIRf06PdwBezG1fktJ2SOul6WZmDfrY5zfttjFP/uJbHeIHzyqp0C91RsQ6YIikfsDtkvaIiLm5LCOA2WStk52AqZIejog3ACT1JusqO60+LedLwM25xw2Nw0QT6e8i6USy7jZ23HHHpk/OzDqcQz76A9Zt0Y1Hp55d7ap0OK1yB4GIWClpGtlYST7YjAYuTl1uiyQ9B+wKzJTUnSzQTIyIyfn9SeoGHAnsm0teAgzMPR5A1mJaktZL0xuq59XA1QC1tbUNBiQz65hGbvU1pr7+v9WuRodV5Gy0mtSiQVIv4GDgmZJsLwDDU57tgF2AxWk85lpgQURc0cDuDwaeiYh899hvgKMl9ZD0frKJADPT+M8qSQek/R4H3Fmp8zSzjiHefrvaVejQimzZ9AduSDPCugC3RcTdksYARMR44CJggqQ5ZN1dZ0XECkkHAscCc3JTm8+NiHvS+tFs2IVGRMyTdBvZJIK1wMmpGw/gJGAC0ItsYoAnB5jZBu77+43VrkKHpqwHy0rV1tZGXV1dtathZtauSJoVEbWl6b6DgJmZFc7BxszMCudgY2ZmhXOwMbNOY78TGprcaq3Bv9RpZp3C7mePY/2OvgdvtTjYmFmH99GjLmferadXuxqdmoONmXVoI3c/j8fm/bDa1ej0HGzMrMMa9cHvcO+fL612NQxPEDCzDmyKA02b4WBjZmaFc7AxM7PCOdiYmVnhHGzMzKxwno1mZu3KqEHfgn+uhc17wVtrmPLiz6pdJSuDg42ZtQujBvwHU5b8nCnPj6t2VWwjuBvNzNqFKUt+Xu0q2CZwsDEzs8I52JiZWeEcbMzMrHCFBRtJPSXNlPSUpHmSLmwgz5aS7srlGZ3SB0p6UNKClD62pNypkhambZemtGMkzc4t6yUNSdumpfz127Yt6rzNrOVGbv31alfBClbkbLQ1wLCIWC2pO/CIpCkRMT2X52RgfkQcJqkGWChpIrAWOD0inpDUB5glaWpEzJd0EHA4sFdErKkPHBExEZgIIGlP4M6ImJ071jERUVfg+ZpZCx3S9SjURfzun7dUuypWsMJaNpFZnR52T0uUZgP6SBLQG3gNWBsRSyPiibSfVcACYIdU5iTg4ohYk7Yva+DwXwJuruT5mFllHdLlCwAONJ1EoWM2krpKmg0sA6ZGxIySLFcCuwEvA3OAsRGxvmQfg4B9gPqyg4GhkmZIekjSRxo49FG8O9hcn7rQzk/BraH6niipTlLd8uXLyz9RM9soU9fdWu0qWCspNNhExLqIGAIMAPaTtEdJlhHAbGB7YAhwpaS+9Rsl9QYmAadFxBspuRuwFXAAcCZwWz54SNof+EdEzM0d55iI2BMYmpZjG6nv1RFRGxG1NTU1G3fSZlaWqet/Ve0qWCtqldloEbESmAaMLNk0GpicutwWAc8BuwKkcZ5JwMSImJwrsyRXZiawHtgmt/1oSlo1EfFS+rsKuAnYrzJnZmZm5ShyNlqNpH5pvRdwMPBMSbYXgOEpz3bALsDi1FK5FlgQEVeUlLkDGJbKDAY2A1akx12ALwD/6gSW1E3SNmm9O/BpYC5mZtZqipyN1h+4QVJXsqB2W0TcLWkMQESMBy4CJkiaAwg4KyJWSDqQrKtrThrzATg3Iu4BrgOukzQXeBs4PiLqJx58HFgSEYtz9egB3JcCTVfgfuCa4k7bzMxK6Z33acurra2NujrPlDbbWId0+YLHZTohSbMiorY03XcQMLOKG7nV1+iy2WbVroa1IQ42ZlZx2qw79701sdrVsDbEwcbMKmrUe7/JlFeuqnY1rI1xsDGzihm1w6lM+esvql0Na4McbMysctaurXYNrI1ysDGzinH3mTXGwcbMzApX1pc6JTX0499/A+oi4s7KVsnMzDqacls2PclulPnntOwFbA18VdJPC6mZmZl1GOXermZnsh9CWwsg6Srgd8AhZD8NYGZm1qhyWzY7AFvkHm8BbB8R68h+kdPM2rDdvjuuxWVG7n4eo3Y5m1EfOreAGllnU27L5lJgtqRpZDfM/DjwI0lbkN3Y0szakMGTLqLL07155sJvAbDg+99q8T7unffDSlfLOrGyb8QpqT/Z78AImBkRLxdZsWrzjTitvRo0/jKeH3NGtathnVQlbsTZBVgOvAbsLOnjlaqcmVWOA421ReVOfb4EOAqYR/bLmAAB/KGgepmZWQdS7pjNEcAuEeHJAGZm1mLldqMtBroXWREzM+u4ym3Z/INsNtoD5KY6R8R/FFIrMzPrUMoNNr9Ji5mZWYuVFWwi4oaW7lhST7IJBD3ScX4dEd8rybMl8Etgx5Tnsoi4XtJA4EbgvWQTEq6OiJ/lyp0KnAKsBX4bEd+RNAhYACxM2aZHxJiUf19gAtALuAcYG+XO+TYzs03WZLCRdFtEfFHSHLLZZxuIiL2aKL6G7BY3qyV1Bx6RNCUipufynAzMj4jDJNUACyVNJAsip0fEE5L6ALMkTY2I+ZIOAg4H9oqINZK2ze3v2YgY0kBdrgJOBKaTBZuRwJSmzt3MzCqnuZbN2PT30y3dcWo5rE4Pu6elNGAF0EeSgN5k3+FZGxFLgaVpP6skLSC7Zc584CTg4vqZcRGxrKl6pC+j9o2IP6bHN5LNrnOwMTNrJU3ORktv+kTEXxpamtu5pK6SZgPLgKkRMaMky5XAbsDLZDf0HBsR60v2MQjYB6gvOxgYKmmGpIckfSSX/f2SnkzpQ1PaDsCSXJ4lKa2h+p4oqU5S3fLly5s7PbOq2+PMlt/zzKwaypr6LOlISX+W9DdJb0haJemN5spFxLrUrTUA2E/SHiVZRgCzge3JfsLgSkl9c8ftDUwCTouI+uN1A7YCDgDOBG5LLaOlwI4RsQ/wbeCmtC81VLVG6nt1RNRGRG1NTU1zp2dWNYN/kAWZuT9p+T3PzKqh3O/ZXAp8JiK2jIi+EdEnIvo2WyqJiJXANLKxkrzRwOTILAKeA3YFSOM8k4CJETE5V2ZJrsxMsgkE20TEmoh4NR1vFvAsWStoCVmwqzeArCVl1i7tftY4/vSfDjLWvpQbbF6JiAUt2bGkGkn90nov4GDgmZJsLwDDU57tgF2Axamlci2wICKuKClzBzAslRkMbAasSMfrmtI/AHwQWJy6AldJOiDt9zjAvy5q7dK+J45j3iUONNb+NDcb7ci0WifpVrI3+vyXOic3VC7pD9yQAkAX4LaIuFvSmFR2PHARMCHNdhNwVkSskHQgcCwwJ435AJwbEfcA1wHXSZoLvA0cHxGRbgz6fUlrgXXAmIh4LZU9iXemPk/BkwOsHfrwN8bxxNUONNY+NfkTA5Kub6JsRMRXKl+ltsE/MWBm1nKN/cRAky2biBidCn8sIh4t2eHHKltFMzPrqMods/mvMtPMrBk7XzKOwx4+lVsXfYS9vu2py9Y5NDdm82/AR4EaSd/ObeoLdC2yYmYdzb5fH8esa77ForPeGXc5qnT6i1kH1dwdBDYj+2Z/N6BPLv0N4PNFVcqsI5p1jQf3rfNqbszmIUmPAHtGxIWtVCczM+tgmh2ziYh1wNatUBczM+ugyv09mycl/Qb4FfD3+sRmvmdjZmYGlB9stgZeJX1zPwnAwcbMzJpV7o+njS66Imbt3QHHXM70iadXuxpmbVK5d30eIOl2ScskvSJpkqQBzZc06xz2O+EKBxqzJpT7pc7rgd+Q/RTADsBdKc2sUxu185kAzJzw7WZymnVu5Qabmoi4PiLWpmUC4B98sU5t5O7nMWXRT6pdDbN2odxgs0LSl9Mvb3aV9GWyCQNmnda9835Y7SqYtRvlBpuvAF8E/kr2i5ifT2lmZmbNKnc22gvAZwqui5mZdVDN3Yjzu01sjoi4qML1MTOzDqi5ls3fG0jbAvgq8B6yX9o0MzNrUnM34ry8fl1SH2AsMBq4Bbi8sXJm7d3wYT+my9vrmfrIedWuilmH0OyYjaStgW8DxwA3AB+OiNeLrphZtXxy5CV0BQcaswpqbszmJ8CRwNVkPzOwutwdS+oJ/AHokY7z64j4XkmeLYFfAjumPJdFxPWSBgI3Au8F1gNXR8TPcuVOBU4B1gK/jYjvSDoEuJjsN3jeBs6MiN+n/NOA/sCbaReHRsSycs/FOoeDDr2E9T268NC9Z1W7KmYdjiKi8Y3SemAN2Zt6PqPIJgj0baKsgC0iYrWk7sAjwNiImJ7Lcy6wZUScJakGWEgWYN4D9I+IJ1L33SzgiIiYL+kg4Dzg3yNijaRtI2KZpH2AVyLiZUl7APdFxA7pONO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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Produces something weird...\n",
    "clipped_red = clipped.sel(wavelength=670, method='nearest').Reflectance\n",
    "clipped_red.plot.pcolormesh('Easting', 'Northing', robust=True, add_colorbar=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "678e78c5-ad02-42ef-9088-c87eb371a32c",
   "metadata": {},
   "source": [
    "## Method 2. Using masking\n",
    "\n",
    "Looking at the source code of `ds.rio.clip()`: Under the hood, it’s essentially doing two main things: 1) rasterize the provided geometry/shape vector into a boolean mask, and 2) apply the mask to the dataset with `ds.where(mask)`. We successfully attemptted to replicate this masking concept for this particular dataset. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9dee68b-bb17-44e8-a4ba-771f66d5607f",
   "metadata": {},
   "source": [
    "### A. Subset a box\n",
    "\n",
    "Subset the simple box defined above by create masks that zero out pixels outside of the provided Easting and Northing range of values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "b6acaba3-562b-4906-b706-dc0c2697ca0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "mask_easting = (ds.Easting >= box_minx) & (ds.Easting <= box_maxx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "f06d9d76-4c16-4abd-99b3-c84b8aac4b83",
   "metadata": {},
   "outputs": [],
   "source": [
    "mask_northing = (ds.Northing >= box_miny) & (ds.Northing <= box_maxy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "1377e99e-503b-49cc-8736-d0e603b0b575",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Equivalent of &: np.logical_and()\n",
    "cropped_ds = ds.where(mask_easting & mask_northing, drop=True) # Drop coordinate labels that only correspond to False values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "5e965f6e-5676-42ce-a18b-04187d0958b0",
   "metadata": {},
   "outputs": [
    {
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       "  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:      (x: 598, y: 743, wavelength: 425)\n",
       "Coordinates:\n",
       "    Easting      (x, y) float64 dask.array&lt;chunksize=(100, 1), meta=np.ndarray&gt;\n",
       "    Northing     (x, y) float64 dask.array&lt;chunksize=(100, 1), meta=np.ndarray&gt;\n",
       "    band         (wavelength) int64 dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;\n",
       "    fwhm         (wavelength) float64 dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;\n",
       "    spatial_ref  int64 0\n",
       "  * wavelength   (wavelength) float64 377.1 382.1 387.1 ... 2.496e+03 2.501e+03\n",
       "  * x            (x) float64 0.5 1.5 2.5 3.5 4.5 ... 594.5 595.5 596.5 597.5\n",
       "  * y            (y) float64 1.3e+03 1.3e+03 1.302e+03 ... 2.04e+03 2.042e+03\n",
       "Data variables:\n",
       "    Elevation    (x, y) float64 dask.array&lt;chunksize=(100, 1), meta=np.ndarray&gt;\n",
       "    Radiance     (x, y, wavelength) float32 dask.array&lt;chunksize=(100, 1, 100), meta=np.ndarray&gt;\n",
       "    Reflectance  (x, y, wavelength) float32 dask.array&lt;chunksize=(100, 1, 100), meta=np.ndarray&gt;</pre><div class='xr-wrap' style='display:none'><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-4456bb36-5a10-49a8-aff3-ac6f4b551efc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4456bb36-5a10-49a8-aff3-ac6f4b551efc' 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'>x</span>: 598</li><li><span class='xr-has-index'>y</span>: 743</li><li><span class='xr-has-index'>wavelength</span>: 425</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-874e03eb-f8c8-4183-95e2-41b72a34d04c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-874e03eb-f8c8-4183-95e2-41b72a34d04c' class='xr-section-summary' >Coordinates: <span>(8)</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>Easting</span></div><div class='xr-var-dims'>(x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 1), meta=np.ndarray&gt;</div><input id='attrs-2b51923b-fa1c-4c15-b733-0cbc2492ec16' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2b51923b-fa1c-4c15-b733-0cbc2492ec16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-285260ba-5ce8-4ba3-8965-82d97a3c96d9' class='xr-var-data-in' type='checkbox'><label for='data-285260ba-5ce8-4ba3-8965-82d97a3c96d9' 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> 3.39 MiB </td>\n",
       "                        <td> 78.12 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (598, 743) </td>\n",
       "                        <td> (100, 100) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 1045 Tasks </td>\n",
       "                        <td> 54 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "  <text x=\"140.000000\" y=\"48.290713\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.290713)\">598</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Northing</span></div><div class='xr-var-dims'>(x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 1), meta=np.ndarray&gt;</div><input id='attrs-2ee899ed-6b2c-459a-91db-0b3c450019c8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2ee899ed-6b2c-459a-91db-0b3c450019c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3129f067-dce0-4295-8177-d13e80e88a22' class='xr-var-data-in' type='checkbox'><label for='data-3129f067-dce0-4295-8177-d13e80e88a22' 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> 3.39 MiB </td>\n",
       "                        <td> 78.12 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (598, 743) </td>\n",
       "                        <td> (100, 100) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 1045 Tasks </td>\n",
       "                        <td> 54 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>band</span></div><div class='xr-var-dims'>(wavelength)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-f363d0ee-62e4-4284-a613-032046b2ed4b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f363d0ee-62e4-4284-a613-032046b2ed4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4fe2ab2-fe5f-4172-9d50-9e9fd9f52463' class='xr-var-data-in' type='checkbox'><label for='data-a4fe2ab2-fe5f-4172-9d50-9e9fd9f52463' 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> 3.32 kiB </td>\n",
       "                        <td> 800 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (425,) </td>\n",
       "                        <td> (100,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 6 Tasks </td>\n",
       "                        <td> 5 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> int64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fwhm</span></div><div class='xr-var-dims'>(wavelength)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100,), meta=np.ndarray&gt;</div><input id='attrs-9302f11f-c298-432c-9820-cae227bc2fb8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9302f11f-c298-432c-9820-cae227bc2fb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1869dc9b-5574-4afc-86f9-e57ed3c3efd8' class='xr-var-data-in' type='checkbox'><label for='data-1869dc9b-5574-4afc-86f9-e57ed3c3efd8' 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> 3.32 kiB </td>\n",
       "                        <td> 800 B </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (425,) </td>\n",
       "                        <td> (100,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 6 Tasks </td>\n",
       "                        <td> 5 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-03d9eb76-d079-428d-9ccd-5afc1a2962ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-03d9eb76-d079-428d-9ccd-5afc1a2962ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5ab877d-5b03-453f-ae22-6d1bddf9ae46' class='xr-var-data-in' type='checkbox'><label for='data-e5ab877d-5b03-453f-ae22-6d1bddf9ae46' 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'><dt><span>GeoTransform :</span></dt><dd>720069.5182464843 -3.0722393616072607 3.374327498608259 720069.5182464843 5195.55192133833 191.447497381507</dd><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 10N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,-123],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32610&quot;]]</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>-123.0</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>projected_crs_name :</span></dt><dd>WGS 84 / UTM zone 10N</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 10N&quot;,GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;latitude_of_origin&quot;,0],PARAMETER[&quot;central_meridian&quot;,-123],PARAMETER[&quot;scale_factor&quot;,0.9996],PARAMETER[&quot;false_easting&quot;,500000],PARAMETER[&quot;false_northing&quot;,0],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH],AUTHORITY[&quot;EPSG&quot;,&quot;32610&quot;]]</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>wavelength</span></div><div class='xr-var-dims'>(wavelength)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>377.1 382.1 ... 2.496e+03 2.501e+03</div><input id='attrs-360d342a-9d09-4846-a47e-db391fda8a35' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-360d342a-9d09-4846-a47e-db391fda8a35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0c1b0a0-5696-4faa-a58e-9eefec452e99' class='xr-var-data-in' type='checkbox'><label for='data-b0c1b0a0-5696-4faa-a58e-9eefec452e99' 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([ 377.071821,  382.081821,  387.091821, ..., 2490.731821, 2495.741821,\n",
       "       2500.751821])</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'>0.5 1.5 2.5 ... 595.5 596.5 597.5</div><input id='attrs-310c089f-d384-4041-b83c-6deb1e549ef6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-310c089f-d384-4041-b83c-6deb1e549ef6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b10863d9-d27f-4c0b-b355-f5e49899aca5' class='xr-var-data-in' type='checkbox'><label for='data-b10863d9-d27f-4c0b-b355-f5e49899aca5' 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([5.000e-01, 1.500e+00, 2.500e+00, ..., 5.955e+02, 5.965e+02, 5.975e+02])</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'>1.3e+03 1.3e+03 ... 2.042e+03</div><input id='attrs-03bc34ef-e216-426d-b21b-a03ebd44d51d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-03bc34ef-e216-426d-b21b-a03ebd44d51d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7d64313-effe-481c-a782-a232fe617d5b' class='xr-var-data-in' type='checkbox'><label for='data-a7d64313-effe-481c-a782-a232fe617d5b' 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([1299.5, 1300.5, 1301.5, ..., 2039.5, 2040.5, 2041.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e9030fe6-5318-49af-8aef-d20c1eae3aa6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e9030fe6-5318-49af-8aef-d20c1eae3aa6' class='xr-section-summary' >Data variables: <span>(3)</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>Elevation</span></div><div class='xr-var-dims'>(x, y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 1), meta=np.ndarray&gt;</div><input id='attrs-de7e8aea-b594-455d-8259-bec932e17401' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-de7e8aea-b594-455d-8259-bec932e17401' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6cac4ed7-c756-433f-9ff7-ba3d8446ce2c' class='xr-var-data-in' type='checkbox'><label for='data-6cac4ed7-c756-433f-9ff7-ba3d8446ce2c' 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> 3.39 MiB </td>\n",
       "                        <td> 78.12 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (598, 743) </td>\n",
       "                        <td> (100, 100) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 10065 Tasks </td>\n",
       "                        <td> 54 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Radiance</span></div><div class='xr-var-dims'>(x, y, wavelength)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100, 1, 100), meta=np.ndarray&gt;</div><input id='attrs-39c7b082-2721-4570-ab0c-665e85270648' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39c7b082-2721-4570-ab0c-665e85270648' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e357bc30-836b-46ca-a703-64dbdee700a5' class='xr-var-data-in' type='checkbox'><label for='data-e357bc30-836b-46ca-a703-64dbdee700a5' 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'><dt><span>bad_pixel_map :</span></dt><dd>/home/jchapman/src/isat/ang/cal/data/ANGv5_bad</dd><dt><span>bands 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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-ccfe6bfd-5e85-4a6a-a493-6c744c95cd87' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ccfe6bfd-5e85-4a6a-a493-6c744c95cd87' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:      (x: 598, y: 743, wavelength: 425)\n",
       "Coordinates:\n",
       "    Easting      (x, y) float64 dask.array<chunksize=(100, 1), meta=np.ndarray>\n",
       "    Northing     (x, y) float64 dask.array<chunksize=(100, 1), meta=np.ndarray>\n",
       "    band         (wavelength) int64 dask.array<chunksize=(100,), meta=np.ndarray>\n",
       "    fwhm         (wavelength) float64 dask.array<chunksize=(100,), meta=np.ndarray>\n",
       "    spatial_ref  int64 0\n",
       "  * wavelength   (wavelength) float64 377.1 382.1 387.1 ... 2.496e+03 2.501e+03\n",
       "  * x            (x) float64 0.5 1.5 2.5 3.5 4.5 ... 594.5 595.5 596.5 597.5\n",
       "  * y            (y) float64 1.3e+03 1.3e+03 1.302e+03 ... 2.04e+03 2.042e+03\n",
       "Data variables:\n",
       "    Elevation    (x, y) float64 dask.array<chunksize=(100, 1), meta=np.ndarray>\n",
       "    Radiance     (x, y, wavelength) float32 dask.array<chunksize=(100, 1, 100), meta=np.ndarray>\n",
       "    Reflectance  (x, y, wavelength) float32 dask.array<chunksize=(100, 1, 100), meta=np.ndarray>"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " # Original ds dims: (x: 598. y: 16418, wavelength: 425)\n",
    "cropped_ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1637fe1f-1a3d-42d7-b59e-462360aa252c",
   "metadata": {},
   "source": [
    "This simple masking produces the correct box, with visible coastlines as quick sanity check."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "3bdb1eef-a82e-4a5f-b381-65c206e3c302",
   "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"
    }
   ],
   "source": [
    "box_red = cropped_ds.sel(wavelength=670, method='nearest').Reflectance\n",
    "box_red.plot.pcolormesh('Easting', 'Northing', robust=True, add_colorbar=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e3c160e-c6e6-49fb-b80a-9aa74795172c",
   "metadata": {},
   "source": [
    "### B. Subset a more complex polygon"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2607fb09-499c-4aca-96a4-8933add03c4a",
   "metadata": {},
   "source": [
    "We expand the masking idea above to accomodate more arbitrary shapes. The approach: Given the approximate Easting and Northing coordinates that make up the vertices of the shape, for each coordinate, find the index of the grid point closest to that coordinate (by taking the min of the l-infinity norm). Then, use that index to get the xy dimension values. From this point on with vertices in xy values, rasterize this shape vector and mask the dataset.\n",
    "\n",
    "Inspired by: https://github.com/blaylockbk/pyBKB_v3/blob/master/demo/Nearest_lat-lon_Grid.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "c73e6389-a009-4909-a5c1-67042221f64a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Triangle\n",
    "vertex_1 = (723500, 3824500)\n",
    "vertex_2 = (724700, 3825500)\n",
    "vertex_3 = (726000, 3824500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "f091f459-b9e1-433f-9e85-fb9b6fbc9df1",
   "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"
    }
   ],
   "source": [
    "# Want this triangular region...\n",
    "triangle_en_coords = Polygon([vertex_1, vertex_2, vertex_3])\n",
    "triangle_pts = np.array(list(triangle_en_coords.exterior.coords))\n",
    "Red.plot.pcolormesh('Easting', 'Northing', robust=True, add_colorbar=False)\n",
    "plt.plot(triangle_pts[:,0], triangle_pts[:,1], c='r');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "d19156a0-73d9-411d-90de-8e191834da2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def find_nearest_point_xy(point):\n",
    "    easting = point[0]\n",
    "    northing = point[1]\n",
    "    \n",
    "    abs_easting = np.abs(ds.Easting.values - easting)\n",
    "    abs_northing = np.abs(ds.Northing.values - northing)\n",
    "    max_abs = np.maximum(abs_easting, abs_northing)\n",
    "    xloc, yloc = np.where(max_abs == np.min(max_abs))\n",
    "    \n",
    "    xy_point = ds.isel(x=xloc[0], y=yloc[0])\n",
    "    \n",
    "    return xy_point.x.values, xy_point.y.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "9536062c-ec7b-4fd5-8bf8-9ea8bd85f10c",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_1, y_1 = find_nearest_point_xy(vertex_1)\n",
    "x_2, y_2 = find_nearest_point_xy(vertex_2)\n",
    "x_3, y_3 = find_nearest_point_xy(vertex_3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "167e00aa-77ac-4a20-a3c8-df3b46416a36",
   "metadata": {},
   "outputs": [],
   "source": [
    "triangle = Polygon([(x_1, y_1), (x_2, y_2), (x_3, y_3)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "7b596d54-8c28-4162-b779-16d27f4b3962",
   "metadata": {},
   "outputs": [],
   "source": [
    "triangle_mask = rasterio.features.rasterize([triangle], out_shape=(ds.y.shape[0], ds.x.shape[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "985000e7-2623-471c-bbad-d75855303972",
   "metadata": {},
   "outputs": [],
   "source": [
    "triangle_mask = xr.DataArray(triangle_mask, dims=['y', 'x'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "34df9692-a590-480a-8686-a31f32f337f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "subset_ds = ds.where(triangle_mask, drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "4baf30fc-6985-4b0c-a26a-0c95580a3f9d",
   "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"
    }
   ],
   "source": [
    "triangle_red = subset_ds.sel(wavelength=670, method='nearest').Reflectance\n",
    "triangle_red.plot.pcolormesh('Easting', 'Northing', robust=True, add_colorbar=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "100d692e-9e47-40dd-be0a-f3a44ba75c14",
   "metadata": {},
   "source": [
    "#### Another arbitrary polygon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "eac3d26b-ff4d-44eb-bedb-ae52c3008f06",
   "metadata": {},
   "outputs": [],
   "source": [
    "vertex_1 = (724500, 3826000)\n",
    "vertex_2 = (726000, 3825000)\n",
    "vertex_3 = (725500, 3823000)\n",
    "vertex_4 = (724000, 3824000)\n",
    "vertex_5 = (723500, 3825000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "5d47c4b6-6f37-410f-bf1c-6761d910296a",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_1, y_1 = find_nearest_point_xy(vertex_1)\n",
    "x_2, y_2 = find_nearest_point_xy(vertex_2)\n",
    "x_3, y_3 = find_nearest_point_xy(vertex_3)\n",
    "x_4, y_4 = find_nearest_point_xy(vertex_4)\n",
    "x_5, y_5 = find_nearest_point_xy(vertex_5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "beb166b5-ac48-4be3-ac64-0ffabfd12406",
   "metadata": {},
   "outputs": [],
   "source": [
    "shape = Polygon([(x_1, y_1), (x_2, y_2), (x_3, y_3), (x_4, y_4), (x_5, y_5)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "aedbf0dd-9980-4499-aec1-9a3d29417f2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "mask = rasterio.features.rasterize([shape], out_shape=(ds.y.shape[0], ds.x.shape[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "ad5e50b1-0c9c-4ecb-8d0e-8c85a3461c72",
   "metadata": {},
   "outputs": [],
   "source": [
    "mask = xr.DataArray(mask, dims=['y', 'x'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "606e45a2-8dcf-4f4c-9a22-c5ac97eaf086",
   "metadata": {},
   "outputs": [],
   "source": [
    "small_ds = ds.where(mask, drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "cbbb4a5d-6deb-433c-b464-b7d10f234240",
   "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"
    }
   ],
   "source": [
    "small_ds_red = small_ds.sel(wavelength=670, method='nearest').Reflectance\n",
    "small_ds_red.plot.pcolormesh('Easting', 'Northing', robust=True, add_colorbar=False);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e6dc411e-b0d2-4c8e-8e8c-31290bc4b159",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}