slideWindow.ipynb

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   "source": [
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
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   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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     "output_type": "stream",
     "text": [
      "Requirement already satisfied: netCDF4 in c:\\users\\gustavi\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (1.5.8)\n",
      "Requirement already satisfied: cftime in c:\\users\\gustavi\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from netCDF4) (1.6.0)\n",
      "Requirement already satisfied: numpy>=1.9 in c:\\users\\gustavi\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from netCDF4) (1.22.3)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.2.4; however, version 22.1.2 is available.\n",
      "You should consider upgrading via the 'c:\\Users\\Gustavi\\AppData\\Local\\Programs\\Python\\Python39\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "pip install netCDF4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: scipy in c:\\users\\gustavi\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (1.8.1)\n",
      "Requirement already satisfied: numpy<1.25.0,>=1.17.3 in c:\\users\\gustavi\\appdata\\local\\programs\\python\\python39\\lib\\site-packages (from scipy) (1.22.3)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: You are using pip version 21.2.4; however, version 22.1.2 is available.\n",
      "You should consider upgrading via the 'c:\\Users\\Gustavi\\AppData\\Local\\Programs\\Python\\Python39\\python.exe -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "pip install scipy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                         (time: 3070, x: 480, y: 480)\n",
       "Coordinates:\n",
       "  * x                               (x) int32 549850 550350 ... 788850 789350\n",
       "  * y                               (y) int32 5271250 5270750 ... 5031750\n",
       "  * time                            (time) datetime64[ns] 2010-11-01 ... 2010...\n",
       "Data variables:\n",
       "    transverse_mercator             (time) |S1 b&#x27;&#x27; b&#x27;&#x27; b&#x27;&#x27; b&#x27;&#x27; ... b&#x27;&#x27; b&#x27;&#x27; b&#x27;&#x27;\n",
       "    equivalent_reflectivity_factor  (time, y, x) float32 dask.array&lt;chunksize=(286, 480, 480), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    Conventions:         CF-1.7\n",
       "    GDAL_AREA_OR_POINT:  Area\n",
       "    title:               MAX(Z) Reflectivity day 2010-11-01\n",
       "    institution:         Meteotrentino, Fondazione Bruno Kessler\n",
       "    source:              radar observation mt.Macaion\n",
       "    site_lat_lon_elev:   46.494002, 11.208826, 1876\n",
       "    references:          original dataset https://doi.org/10.5281/zenodo.3577451\n",
       "    comments:            NetCDF generation code https://github.com/MPBA/TAASR...\n",
       "    chunks:              164 122\n",
       "    tags:                rain snow</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-5ffccbb8-23dd-42c6-b92d-1581a4f60e3f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5ffccbb8-23dd-42c6-b92d-1581a4f60e3f' 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>: 3070</li><li><span class='xr-has-index'>x</span>: 480</li><li><span class='xr-has-index'>y</span>: 480</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6f83eb96-fc15-49a5-8696-f2f568af2412' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6f83eb96-fc15-49a5-8696-f2f568af2412' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>549850 550350 ... 788850 789350</div><input id='attrs-f829a818-9119-44eb-813f-9646b781fa7f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f829a818-9119-44eb-813f-9646b781fa7f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5557b130-e2ed-4c8b-8ec2-408c4ea4261c' class='xr-var-data-in' type='checkbox'><label for='data-5557b130-e2ed-4c8b-8ec2-408c4ea4261c' 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>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([549850, 550350, 550850, ..., 788350, 788850, 789350])</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'>int32</div><div class='xr-var-preview xr-preview'>5271250 5270750 ... 5032250 5031750</div><input id='attrs-86c30b36-3549-4792-8b0b-0e5a398be186' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86c30b36-3549-4792-8b0b-0e5a398be186' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3bd534e2-7b95-438f-917a-716b9139745a' class='xr-var-data-in' type='checkbox'><label for='data-3bd534e2-7b95-438f-917a-716b9139745a' 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>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([5271250, 5270750, 5270250, ..., 5032750, 5032250, 5031750])</pre></div></li><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'>2010-11-01 ... 2010-11-26T23:55:00</div><input id='attrs-478fb93e-ccd4-4772-9898-e56950d2500b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-478fb93e-ccd4-4772-9898-e56950d2500b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a97275c2-5540-430c-961c-a5d80bde5e45' class='xr-var-data-in' type='checkbox'><label for='data-a97275c2-5540-430c-961c-a5d80bde5e45' 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>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2010-11-01T00:00:00.000000000&#x27;, &#x27;2010-11-01T00:05:00.000000000&#x27;,\n",
       "       &#x27;2010-11-01T00:10:00.000000000&#x27;, ..., &#x27;2010-11-26T23:45:00.000000000&#x27;,\n",
       "       &#x27;2010-11-26T23:50:00.000000000&#x27;, &#x27;2010-11-26T23:55:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6f91ec71-8e20-4028-9d95-16b97c428348' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6f91ec71-8e20-4028-9d95-16b97c428348' 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>transverse_mercator</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>b&#x27;&#x27; b&#x27;&#x27; b&#x27;&#x27; b&#x27;&#x27; ... b&#x27;&#x27; b&#x27;&#x27; b&#x27;&#x27; b&#x27;&#x27;</div><input id='attrs-825527d7-3b19-4ba0-8c83-bc8917708a7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-825527d7-3b19-4ba0-8c83-bc8917708a7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d77915a9-aec2-43d5-a546-43bc911820a4' class='xr-var-data-in' type='checkbox'><label for='data-d77915a9-aec2-43d5-a546-43bc911820a4' 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>grid_mapping_name :</span></dt><dd>transverse_mercator</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>9.0</dd><dt><span>false_easting :</span></dt><dd>500000.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>scale_factor_at_central_meridian :</span></dt><dd>0.9996</dd><dt><span>long_name :</span></dt><dd>CRS definition</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 32N&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;,9],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;32632&quot;]] </dd><dt><span>crs_wkt :</span></dt><dd>PROJCS[&quot;WGS 84 / UTM zone 32N&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;,9],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;32632&quot;]] </dd></dl></div><div class='xr-var-data'><pre>array([b&#x27;&#x27;, b&#x27;&#x27;, b&#x27;&#x27;, ..., b&#x27;&#x27;, b&#x27;&#x27;, b&#x27;&#x27;], dtype=&#x27;|S1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>equivalent_reflectivity_factor</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(286, 480, 480), meta=np.ndarray&gt;</div><input id='attrs-7e3e883f-4d14-4f3c-a96e-02c29af49361' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e3e883f-4d14-4f3c-a96e-02c29af49361' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70e80d17-b791-47a2-827b-7562428b59cc' class='xr-var-data-in' type='checkbox'><label for='data-70e80d17-b791-47a2-827b-7562428b59cc' 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>standard_name :</span></dt><dd>equivalent_reflectivity_factor</dd><dt><span>units :</span></dt><dd>dBZ</dd><dt><span>long_name :</span></dt><dd>MAX(Z) Reflectivity (dBZ)</dd><dt><span>valid_range :</span></dt><dd>[ 0.  52.5]</dd><dt><span>grid_mapping :</span></dt><dd>transverse_mercator</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
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       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.64 GiB </td>\n",
       "                        <td> 253.12 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (3070, 480, 480) </td>\n",
       "                        <td> (288, 480, 480) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 36 Tasks </td>\n",
       "                        <td> 12 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </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-90bd043a-2740-469f-9f47-d64af2c83f8b' class='xr-section-summary-in' type='checkbox'  ><label for='section-90bd043a-2740-469f-9f47-d64af2c83f8b' class='xr-section-summary' >Attributes: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>GDAL_AREA_OR_POINT :</span></dt><dd>Area</dd><dt><span>title :</span></dt><dd>MAX(Z) Reflectivity day 2010-11-01</dd><dt><span>institution :</span></dt><dd>Meteotrentino, Fondazione Bruno Kessler</dd><dt><span>source :</span></dt><dd>radar observation mt.Macaion</dd><dt><span>site_lat_lon_elev :</span></dt><dd>46.494002, 11.208826, 1876</dd><dt><span>references :</span></dt><dd>original dataset https://doi.org/10.5281/zenodo.3577451</dd><dt><span>comments :</span></dt><dd>NetCDF generation code https://github.com/MPBA/TAASRAD19</dd><dt><span>chunks :</span></dt><dd>164 122</dd><dt><span>tags :</span></dt><dd>rain snow</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                         (time: 3070, x: 480, y: 480)\n",
       "Coordinates:\n",
       "  * x                               (x) int32 549850 550350 ... 788850 789350\n",
       "  * y                               (y) int32 5271250 5270750 ... 5031750\n",
       "  * time                            (time) datetime64[ns] 2010-11-01 ... 2010...\n",
       "Data variables:\n",
       "    transverse_mercator             (time) |S1 b'' b'' b'' b'' ... b'' b'' b''\n",
       "    equivalent_reflectivity_factor  (time, y, x) float32 dask.array<chunksize=(286, 480, 480), meta=np.ndarray>\n",
       "Attributes:\n",
       "    Conventions:         CF-1.7\n",
       "    GDAL_AREA_OR_POINT:  Area\n",
       "    title:               MAX(Z) Reflectivity day 2010-11-01\n",
       "    institution:         Meteotrentino, Fondazione Bruno Kessler\n",
       "    source:              radar observation mt.Macaion\n",
       "    site_lat_lon_elev:   46.494002, 11.208826, 1876\n",
       "    references:          original dataset https://doi.org/10.5281/zenodo.3577451\n",
       "    comments:            NetCDF generation code https://github.com/MPBA/TAASR...\n",
       "    chunks:              164 122\n",
       "    tags:                rain snow"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#FILE = './training/*.nc'\n",
    "#ds = xr.open_mfdataset(FILE)\n",
    "files = [\"./training/20101101.nc\", \"./training/20101102.nc\", \"./training/20101107.nc\", \"./training/20101108.nc\",\n",
    "        \"./training/20101109.nc\", \"./training/20101115.nc\", \"./training/20101116.nc\", \"./training/20101118.nc\",\n",
    "        \"./training/20101119.nc\", \"./training/20101121.nc\", \"./training/20101122.nc\", \"./training/20101126.nc\"]\n",
    "ds = xr.open_mfdataset(files)\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "reflectivity_ds = ds.equivalent_reflectivity_factor  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def window_generator_xarray(dataset, n_steps):\n",
    "    x, y = list(), list()\n",
    "    for i in range(len(dataset)):\n",
    "        end_ix = i + n_steps\n",
    "        end_iy = end_ix + n_steps\n",
    "\n",
    "        x_data = dataset.isel(time=slice(i,end_ix))\n",
    "        x_data = x_data.expand_dims(dim='sample', axis=0)\n",
    "        y_data = dataset.isel(time=slice(end_ix,end_iy))\n",
    "        y_data = y_data.expand_dims(dim='sample', axis=0)\n",
    "\n",
    "        if y_data.time.size < n_steps:\n",
    "            break\n",
    "        \n",
    "        x_data = x_data.drop(labels='time')\n",
    "        x.append(x_data)\n",
    "        y_data = y_data.drop(labels='time')\n",
    "        y.append(y_data)\n",
    "\n",
    "    return x, y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sample size with X:  3061\n",
      "Sample size with y:  3061\n"
     ]
    }
   ],
   "source": [
    "x_list, y_list = window_generator_xarray(reflectivity_ds, n_steps=5)\n",
    "x_data = xr.concat(x_list, dim='sample')\n",
    "x_data = x_data.expand_dims(dim='channel', axis=-1)\n",
    "\n",
    "y_data = xr.concat(y_list, dim='sample')\n",
    "y_data = y_data.expand_dims(dim='channel', axis=-1)\n",
    "\n",
    "print('Sample size with X: ', x_data.sample.size)\n",
    "print('Sample size with y: ', y_data.sample.size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;equivalent_reflectivity_factor&#x27; (sample: 3061, time: 5,\n",
       "                                                    y: 480, x: 480, channel: 1)&gt;\n",
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       "    standard_name:  equivalent_reflectivity_factor\n",
       "    units:          dBZ\n",
       "    long_name:      MAX(Z) Reflectivity (dBZ)\n",
       "    valid_range:    [ 0.  52.5]\n",
       "    grid_mapping:   transverse_mercator</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'equivalent_reflectivity_factor'</div><ul class='xr-dim-list'><li><span>sample</span>: 3061</li><li><span>time</span>: 5</li><li><span class='xr-has-index'>y</span>: 480</li><li><span class='xr-has-index'>x</span>: 480</li><li><span>channel</span>: 1</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ca550e72-890c-47f4-8384-20829986a639' class='xr-array-in' type='checkbox' checked><label for='section-ca550e72-890c-47f4-8384-20829986a639' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 1, 480, 480, 1), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
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       "</table></div></div></li><li class='xr-section-item'><input id='section-85ca30be-b8b0-45a2-9160-6b633a643b54' class='xr-section-summary-in' type='checkbox'  checked><label for='section-85ca30be-b8b0-45a2-9160-6b633a643b54' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>549850 550350 ... 788850 789350</div><input id='attrs-3b3c6268-eda9-4dce-a159-d779e2d4999b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b3c6268-eda9-4dce-a159-d779e2d4999b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c0861c7-f901-49a0-b45e-80ecb7a24414' class='xr-var-data-in' type='checkbox'><label for='data-0c0861c7-f901-49a0-b45e-80ecb7a24414' 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>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([549850, 550350, 550850, ..., 788350, 788850, 789350])</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'>int32</div><div class='xr-var-preview xr-preview'>5271250 5270750 ... 5032250 5031750</div><input id='attrs-92ffb335-68c5-44b2-981d-3514607cd39a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-92ffb335-68c5-44b2-981d-3514607cd39a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5c88800-d642-4a9b-99e8-7993a36aca15' class='xr-var-data-in' type='checkbox'><label for='data-f5c88800-d642-4a9b-99e8-7993a36aca15' 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>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([5271250, 5270750, 5270250, ..., 5032750, 5032250, 5031750])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-863a5977-4ec1-4aa8-b1d3-bffa9da4a8c2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-863a5977-4ec1-4aa8-b1d3-bffa9da4a8c2' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>equivalent_reflectivity_factor</dd><dt><span>units :</span></dt><dd>dBZ</dd><dt><span>long_name :</span></dt><dd>MAX(Z) Reflectivity (dBZ)</dd><dt><span>valid_range :</span></dt><dd>[ 0.  52.5]</dd><dt><span>grid_mapping :</span></dt><dd>transverse_mercator</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'equivalent_reflectivity_factor' (sample: 3061, time: 5,\n",
       "                                                    y: 480, x: 480, channel: 1)>\n",
       "dask.array<transpose, shape=(3061, 5, 480, 480, 1), dtype=float32, chunksize=(1, 1, 480, 480, 1), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * x        (x) int32 549850 550350 550850 551350 ... 788350 788850 789350\n",
       "  * y        (y) int32 5271250 5270750 5270250 ... 5032750 5032250 5031750\n",
       "Dimensions without coordinates: sample, time, channel\n",
       "Attributes:\n",
       "    standard_name:  equivalent_reflectivity_factor\n",
       "    units:          dBZ\n",
       "    long_name:      MAX(Z) Reflectivity (dBZ)\n",
       "    valid_range:    [ 0.  52.5]\n",
       "    grid_mapping:   transverse_mercator"
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     "execution_count": 11,
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   "cell_type": "code",
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3061, 5, 480, 480, 1)"
      ]
     },
     "execution_count": 16,
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  {
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   "execution_count": 19,
   "metadata": {},
   "outputs": [
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       "                                                    time: 5, x: 480, y: 480)&gt;\n",
       "dask.array&lt;transpose, shape=(3061, 1, 5, 480, 480), dtype=float32, chunksize=(1, 1, 1, 480, 480), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
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       "  * y        (y) int32 5271250 5270750 5270250 ... 5032750 5032250 5031750\n",
       "Dimensions without coordinates: sample, channel, time\n",
       "Attributes:\n",
       "    standard_name:  equivalent_reflectivity_factor\n",
       "    units:          dBZ\n",
       "    long_name:      MAX(Z) Reflectivity (dBZ)\n",
       "    valid_range:    [ 0.  52.5]\n",
       "    grid_mapping:   transverse_mercator</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'equivalent_reflectivity_factor'</div><ul class='xr-dim-list'><li><span>sample</span>: 3061</li><li><span>channel</span>: 1</li><li><span>time</span>: 5</li><li><span class='xr-has-index'>x</span>: 480</li><li><span class='xr-has-index'>y</span>: 480</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-839346f7-67eb-4971-88a5-713b99095b83' class='xr-array-in' type='checkbox' checked><label for='section-839346f7-67eb-4971-88a5-713b99095b83' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(1, 1, 1, 480, 480), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
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       "                        <td> 13.14 GiB </td>\n",
       "                        <td> 900.00 kiB </td>\n",
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       "                        <td> 15305 Chunks </td>\n",
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       "<xarray.DataArray 'equivalent_reflectivity_factor' (sample: 3061, channel: 1,\n",
       "                                                    time: 5, x: 480, y: 480)>\n",
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       "Dimensions without coordinates: sample, channel, time\n",
       "Attributes:\n",
       "    standard_name:  equivalent_reflectivity_factor\n",
       "    units:          dBZ\n",
       "    long_name:      MAX(Z) Reflectivity (dBZ)\n",
       "    valid_range:    [ 0.  52.5]\n",
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      ]
     },
     "execution_count": 19,
     "metadata": {},
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