4_irregularly_sampled_data.ipynb

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    "# Working with irregularly sampled data"
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    "In this example we will have a look at the [**HSAF Surface Soil Moisture NRT**][hsaf] product.\n",
    "\n",
    "The product is provided on a **(non-rectangular) [spherical Fibonacci grid][fibgrid]** and the data is stored in a **[contiguous ragged array][cont_ragged]** representation.\n",
    "\n",
    "It has an approx. pixel-spacing of 6.26km.\n",
    "\n",
    "[hsaf]: https://hsaf.meteoam.it/Products/ProductsList?type=soil_moisture\n",
    "[cont_ragged]: http://cfconventions.org/cf-conventions/cf-conventions.html#_contiguous_ragged_array_representation\n",
    "[fibgrid]: https://arxiv.org/pdf/0912.4540"
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    "from pathlib import Path\n",
    "import xarray as xar\n",
    "\n",
    "from eomaps import Maps, widgets"
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    "%matplotlib qt\n",
    "Maps.config(always_on_top=True)  # keep Qt figures \"always on top\""
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    "# get a list of all files\n",
    "swath_files = list(Path(\"swath_data\").iterdir())"
   ]
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 6MB\n",
       "Dimensions:                            (obs: 47330)\n",
       "Coordinates:\n",
       "    latitude                           (obs) float64 379kB ...\n",
       "    longitude                          (obs) float64 379kB ...\n",
       "    time                               (obs) datetime64[ns] 379kB ...\n",
       "Dimensions without coordinates: obs\n",
       "Data variables: (12/18)\n",
       "    location_id                        (obs) float64 379kB ...\n",
       "    as_des_pass                        (obs) float32 189kB ...\n",
       "    swath_indicator                    (obs) float32 189kB ...\n",
       "    surface_soil_moisture              (obs) float64 379kB ...\n",
       "    surface_soil_moisture_noise        (obs) float64 379kB ...\n",
       "    backscatter40                      (obs) float64 379kB ...\n",
       "    ...                                 ...\n",
       "    surface_flag                       (obs) float32 189kB ...\n",
       "    snow_cover_probability             (obs) float32 189kB ...\n",
       "    frozen_soil_probability            (obs) float32 189kB ...\n",
       "    wetland_fraction                   (obs) float32 189kB ...\n",
       "    topographic_complexity             (obs) float32 189kB ...\n",
       "    subsurface_scattering_probability  (obs) float32 189kB ...\n",
       "Attributes: (12/19)\n",
       "    product_name:            W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_...\n",
       "    title:                   ASCAT surface soil moisture near real-time product\n",
       "    summary:                 ASCAT surface soil moisture expressed in degree ...\n",
       "    doi:                     unset\n",
       "    keywords:                Metop-C ASCAT surface soil moisture\n",
       "    history:                 original generated product\n",
       "    ...                      ...\n",
       "    sensing_start_time_utc:  2023-06-29 00:00:00.000\n",
       "    sensing_end_time_utc:    2023-06-29 00:59:59.999\n",
       "    references:              h-saf.eumetsat.int\n",
       "    date_created_utc:        2024-02-19 09:57:53.294\n",
       "    software_version:        warp_nrt 0.0.0\n",
       "    conventions:             CF-1.10</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-6b61acea-7752-490d-a22e-588ec1828cb4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6b61acea-7752-490d-a22e-588ec1828cb4' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>obs</span>: 47330</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4b67691c-34e9-40ec-b337-e4e86654e515' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4b67691c-34e9-40ec-b337-e4e86654e515' 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>latitude</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8f0cd95b-b75a-4108-8b0a-582450ee8d3a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f0cd95b-b75a-4108-8b0a-582450ee8d3a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21009c8b-ac05-400f-8f28-cd38071a887c' class='xr-var-data-in' type='checkbox'><label for='data-21009c8b-ac05-400f-8f28-cd38071a887c' 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>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>valid_min :</span></dt><dd>-90000000</dd><dt><span>valid_max :</span></dt><dd>89999999</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4fc55b7a-44b5-4308-942e-206694840b9a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4fc55b7a-44b5-4308-942e-206694840b9a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63963f0b-dc02-4470-a8c9-8c5fa464a1eb' class='xr-var-data-in' type='checkbox'><label for='data-63963f0b-dc02-4470-a8c9-8c5fa464a1eb' 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>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>valid_min :</span></dt><dd>-180000000</dd><dt><span>valid_max :</span></dt><dd>179999999</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3944cfcd-f04e-4609-9152-00018f8402f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3944cfcd-f04e-4609-9152-00018f8402f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b3913f5-faef-426c-8213-47ed32ac4bae' class='xr-var-data-in' type='checkbox'><label for='data-4b3913f5-faef-426c-8213-47ed32ac4bae' 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>long_name :</span></dt><dd>time</dd><dt><span>calender :</span></dt><dd>standard</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=datetime64[ns]]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-254f818e-7706-45dd-8594-681acbb9f64d' class='xr-section-summary-in' type='checkbox'  ><label for='section-254f818e-7706-45dd-8594-681acbb9f64d' class='xr-section-summary' >Data variables: <span>(18)</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>location_id</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5ce220ce-3a21-4a74-b450-412eda40775e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ce220ce-3a21-4a74-b450-412eda40775e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13ad57c9-fcb5-4e0b-9a1f-13e5a18e6d73' class='xr-var-data-in' type='checkbox'><label for='data-13ad57c9-fcb5-4e0b-9a1f-13e5a18e6d73' 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>long_name :</span></dt><dd>Location identifier (Grid Point ID)</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>3300000</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>as_des_pass</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a94e2c4b-76a0-45fd-ae0c-93014a958a31' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a94e2c4b-76a0-45fd-ae0c-93014a958a31' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8deb56e-9932-45a9-9c50-a3dc55c6e7ab' class='xr-var-data-in' type='checkbox'><label for='data-a8deb56e-9932-45a9-9c50-a3dc55c6e7ab' 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>long_name :</span></dt><dd>orbit overpass direction (ascending, descending)</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>ascending descending</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swath_indicator</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8944ab19-6b54-44bc-a041-15f89e7b2df3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8944ab19-6b54-44bc-a041-15f89e7b2df3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-743bca62-9030-4f1e-91dc-1daf1a464bfd' class='xr-var-data-in' type='checkbox'><label for='data-743bca62-9030-4f1e-91dc-1daf1a464bfd' 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>long_name :</span></dt><dd>swath indicator (left, right)</dd><dt><span>flag_values :</span></dt><dd>[0 1]</dd><dt><span>flag_meanings :</span></dt><dd>left right</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surface_soil_moisture</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9571aadf-d6bf-4aa1-ad98-13234481b7f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9571aadf-d6bf-4aa1-ad98-13234481b7f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb80f7ff-d033-475e-8ae5-2a6c8d0d72f3' class='xr-var-data-in' type='checkbox'><label for='data-eb80f7ff-d033-475e-8ae5-2a6c8d0d72f3' 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>long_name :</span></dt><dd>surface soil moisture</dd><dt><span>units :</span></dt><dd>percent saturation</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surface_soil_moisture_noise</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-87192a6b-ac88-4181-acc2-76f5efe9b3eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87192a6b-ac88-4181-acc2-76f5efe9b3eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a8d0c0f-8744-4840-b771-94f3aa0c527e' class='xr-var-data-in' type='checkbox'><label for='data-3a8d0c0f-8744-4840-b771-94f3aa0c527e' 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>long_name :</span></dt><dd>surface soil moisture noise</dd><dt><span>units :</span></dt><dd>percent saturation</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter40</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-29c1a81b-238c-4abb-9f00-9cb4d6a8984a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29c1a81b-238c-4abb-9f00-9cb4d6a8984a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c10b0be-2802-42fd-b0a7-90ad0f612ac9' class='xr-var-data-in' type='checkbox'><label for='data-3c10b0be-2802-42fd-b0a7-90ad0f612ac9' 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>long_name :</span></dt><dd>backscatter interpolated at 40 degree incidence angle</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>valid_min :</span></dt><dd>-300000000</dd><dt><span>valid_max :</span></dt><dd>300000000</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slope40</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8f438482-812e-4380-812d-6bae262feacb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f438482-812e-4380-812d-6bae262feacb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3e9863e-7c6f-4709-bca9-237bf24b7bf1' class='xr-var-data-in' type='checkbox'><label for='data-c3e9863e-7c6f-4709-bca9-237bf24b7bf1' 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>long_name :</span></dt><dd>slope at 40 degree incidence angle</dd><dt><span>units :</span></dt><dd>dB/deg</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>curvature40</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-316cd4e0-aefb-477a-b537-a02a0730e78c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-316cd4e0-aefb-477a-b537-a02a0730e78c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86a16ec3-b82a-46eb-a88e-139d513ab072' class='xr-var-data-in' type='checkbox'><label for='data-86a16ec3-b82a-46eb-a88e-139d513ab072' 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>long_name :</span></dt><dd>curvature at 40 degree incidence angle</dd><dt><span>units :</span></dt><dd>dB/deg^2</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surface_soil_moisture_sensitivity</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-63312146-cd86-4489-ba6c-b22949e7ff9a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63312146-cd86-4489-ba6c-b22949e7ff9a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c163c4e5-f1dc-42f4-b5d3-18fd24916568' class='xr-var-data-in' type='checkbox'><label for='data-c163c4e5-f1dc-42f4-b5d3-18fd24916568' 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>long_name :</span></dt><dd>surface soil moisture sensitivity</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>valid_min :</span></dt><dd>-300000000</dd><dt><span>valid_max :</span></dt><dd>300000000</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter_flag</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3a9107c1-4a19-4a56-9336-3752f606eb29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a9107c1-4a19-4a56-9336-3752f606eb29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-afd67add-e1be-401a-b176-2f6f429f396b' class='xr-var-data-in' type='checkbox'><label for='data-afd67add-e1be-401a-b176-2f6f429f396b' 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>long_name :</span></dt><dd>backscatter flag</dd><dt><span>flag_masks :</span></dt><dd>[ 1  2  4  8 16 32 64]</dd><dt><span>flag_meanings :</span></dt><dd>fore_beam_sigma0_valid mid_beam_sigma0_valid aft_beam_sigma0_valid reserved_for_future_use reserved_for_future_use reserved_for_future_use reserved_for_future_use</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>127</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>correction_flag</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3ee12cf2-f9d0-4cfd-ac9a-a55b1065ace5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ee12cf2-f9d0-4cfd-ac9a-a55b1065ace5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37b244d4-fd71-4ada-a7a7-76b2b90ee1d4' class='xr-var-data-in' type='checkbox'><label for='data-37b244d4-fd71-4ada-a7a7-76b2b90ee1d4' 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>long_name :</span></dt><dd>correction flag</dd><dt><span>flag_masks :</span></dt><dd>[ 1  2  4  8 16 32 64]</dd><dt><span>flag_meanings :</span></dt><dd>wet_correction_applied ssm_set_to_0%_was_between_-25%_and_0% ssm_set_to_100%_was_between_100%_and_125% reserved_for_future_use reserved_for_future_use reserved_for_future_use reserved_for_future_use</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>127</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>processing_flag</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-09342e86-cbf2-447f-9895-641caf7f42b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-09342e86-cbf2-447f-9895-641caf7f42b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-092231ad-003f-4467-9052-ea939d400916' class='xr-var-data-in' type='checkbox'><label for='data-092231ad-003f-4467-9052-ea939d400916' 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>long_name :</span></dt><dd>processing flag</dd><dt><span>flag_masks :</span></dt><dd>[ 1  2  4  8 16 32 64]</dd><dt><span>flag_meanings :</span></dt><dd>model_parameter_not_usable backscatter_not_usable ssm_below_-25%_saturation ssm_above_125%_saturation reserved_for_future_use reserved_for_future_use reserved_for_future_use</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>127</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surface_flag</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0db6a33c-8a28-4bd0-a682-7a46c6d2660b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0db6a33c-8a28-4bd0-a682-7a46c6d2660b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18f44c9b-a7ed-45ef-bef1-eb43f0fb8316' class='xr-var-data-in' type='checkbox'><label for='data-18f44c9b-a7ed-45ef-bef1-eb43f0fb8316' 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>long_name :</span></dt><dd>surface flag</dd><dt><span>flag_masks :</span></dt><dd>[ 1  2  4  8 16 32 64]</dd><dt><span>flag_meanings :</span></dt><dd>open_water frozen_soil snow_cover reserved_for_future_use reserved_for_future_use reserved_for_future_use reserved_for_future_use</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>127</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>snow_cover_probability</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b9381664-1ece-4ec3-9442-5c0d66779da4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9381664-1ece-4ec3-9442-5c0d66779da4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-125c0b7f-607d-45ac-9b44-8db37a127eb6' class='xr-var-data-in' type='checkbox'><label for='data-125c0b7f-607d-45ac-9b44-8db37a127eb6' 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>long_name :</span></dt><dd>snow cover probability</dd><dt><span>units :</span></dt><dd>percent</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>100</dd><dt><span>comment :</span></dt><dd>based on ERA5 Snow Cover data (1980-2020)</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frozen_soil_probability</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-33f32487-17f8-4eae-abaa-01a7b0c259e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33f32487-17f8-4eae-abaa-01a7b0c259e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e97904c-c506-44f6-ae6f-7225e5f881f4' class='xr-var-data-in' type='checkbox'><label for='data-3e97904c-c506-44f6-ae6f-7225e5f881f4' 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>long_name :</span></dt><dd>frozen soil probability</dd><dt><span>units :</span></dt><dd>percent</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>100</dd><dt><span>comment :</span></dt><dd>based on ERA5 Soil Temperature Level 1 data (1980-2020)</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wetland_fraction</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-27ccac6d-3513-407e-9914-fa18906d1d2e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27ccac6d-3513-407e-9914-fa18906d1d2e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1dd3cfbe-4825-4e4d-b14c-339d988d6db0' class='xr-var-data-in' type='checkbox'><label for='data-1dd3cfbe-4825-4e4d-b14c-339d988d6db0' 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>long_name :</span></dt><dd>wetland fraction</dd><dt><span>units :</span></dt><dd>percent</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>100</dd><dt><span>comment :</span></dt><dd>based on Global Lakes and Wetlands Database (GLWD) data</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>topographic_complexity</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-889433cb-bec1-4bf8-8640-9db2e8f3231a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-889433cb-bec1-4bf8-8640-9db2e8f3231a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3065969-943c-41fc-8dcc-83b1bda0e807' class='xr-var-data-in' type='checkbox'><label for='data-b3065969-943c-41fc-8dcc-83b1bda0e807' 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>long_name :</span></dt><dd>topographic complexity</dd><dt><span>units :</span></dt><dd>percent</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>100</dd><dt><span>comment :</span></dt><dd>normalized standard deviation of CopDEM90m data</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>subsurface_scattering_probability</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-edac3464-b314-42ae-ad92-fe8f687e15e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-edac3464-b314-42ae-ad92-fe8f687e15e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4ffeb91-ccef-4cb4-8d7e-2f0bd31ea126' class='xr-var-data-in' type='checkbox'><label for='data-e4ffeb91-ccef-4cb4-8d7e-2f0bd31ea126' 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>long_name :</span></dt><dd>subsurface scattering probability</dd><dt><span>units :</span></dt><dd>percent</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>100</dd></dl></div><div class='xr-var-data'><pre>[47330 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0f452e92-086a-43dd-9c2b-d61087d701b4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0f452e92-086a-43dd-9c2b-d61087d701b4' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-424df73e-462f-4ba7-b46f-c514fcce8ec7' class='xr-section-summary-in' type='checkbox'  ><label for='section-424df73e-462f-4ba7-b46f-c514fcce8ec7' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>product_name :</span></dt><dd>W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_C_LIIB_20240219095753_20230629000000_20230629005959____.nc</dd><dt><span>title :</span></dt><dd>ASCAT surface soil moisture near real-time product</dd><dt><span>summary :</span></dt><dd>ASCAT surface soil moisture expressed in degree of saturation</dd><dt><span>doi :</span></dt><dd>unset</dd><dt><span>keywords :</span></dt><dd>Metop-C ASCAT surface soil moisture</dd><dt><span>history :</span></dt><dd>original generated product</dd><dt><span>institution :</span></dt><dd>H SAF</dd><dt><span>spacecraft :</span></dt><dd>Metop-C</dd><dt><span>instrument :</span></dt><dd>ASCAT</dd><dt><span>product_level :</span></dt><dd>2</dd><dt><span>mission_type :</span></dt><dd>Global</dd><dt><span>disposition_mode :</span></dt><dd>Operational</dd><dt><span>environment :</span></dt><dd>Operational</dd><dt><span>sensing_start_time_utc :</span></dt><dd>2023-06-29 00:00:00.000</dd><dt><span>sensing_end_time_utc :</span></dt><dd>2023-06-29 00:59:59.999</dd><dt><span>references :</span></dt><dd>h-saf.eumetsat.int</dd><dt><span>date_created_utc :</span></dt><dd>2024-02-19 09:57:53.294</dd><dt><span>software_version :</span></dt><dd>warp_nrt 0.0.0</dd><dt><span>conventions :</span></dt><dd>CF-1.10</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 6MB\n",
       "Dimensions:                            (obs: 47330)\n",
       "Coordinates:\n",
       "    latitude                           (obs) float64 379kB ...\n",
       "    longitude                          (obs) float64 379kB ...\n",
       "    time                               (obs) datetime64[ns] 379kB ...\n",
       "Dimensions without coordinates: obs\n",
       "Data variables: (12/18)\n",
       "    location_id                        (obs) float64 379kB ...\n",
       "    as_des_pass                        (obs) float32 189kB ...\n",
       "    swath_indicator                    (obs) float32 189kB ...\n",
       "    surface_soil_moisture              (obs) float64 379kB ...\n",
       "    surface_soil_moisture_noise        (obs) float64 379kB ...\n",
       "    backscatter40                      (obs) float64 379kB ...\n",
       "    ...                                 ...\n",
       "    surface_flag                       (obs) float32 189kB ...\n",
       "    snow_cover_probability             (obs) float32 189kB ...\n",
       "    frozen_soil_probability            (obs) float32 189kB ...\n",
       "    wetland_fraction                   (obs) float32 189kB ...\n",
       "    topographic_complexity             (obs) float32 189kB ...\n",
       "    subsurface_scattering_probability  (obs) float32 189kB ...\n",
       "Attributes: (12/19)\n",
       "    product_name:            W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_...\n",
       "    title:                   ASCAT surface soil moisture near real-time product\n",
       "    summary:                 ASCAT surface soil moisture expressed in degree ...\n",
       "    doi:                     unset\n",
       "    keywords:                Metop-C ASCAT surface soil moisture\n",
       "    history:                 original generated product\n",
       "    ...                      ...\n",
       "    sensing_start_time_utc:  2023-06-29 00:00:00.000\n",
       "    sensing_end_time_utc:    2023-06-29 00:59:59.999\n",
       "    references:              h-saf.eumetsat.int\n",
       "    date_created_utc:        2024-02-19 09:57:53.294\n",
       "    software_version:        warp_nrt 0.0.0\n",
       "    conventions:             CF-1.10"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ncfile = xar.open_dataset(swath_files[0])\n",
    "ncfile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2b8efdfb-d1b6-4747-8797-79a80eee4ea8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>surface_soil_moisture</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>location_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>-52.523292</td>\n",
       "      <td>2023-06-29 00:25:42.828999936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92.0</th>\n",
       "      <td>75.68</td>\n",
       "      <td>0.003216</td>\n",
       "      <td>-50.714296</td>\n",
       "      <td>2023-06-29 00:25:36.035000064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236.0</th>\n",
       "      <td>81.61</td>\n",
       "      <td>0.008250</td>\n",
       "      <td>-51.832316</td>\n",
       "      <td>2023-06-29 00:25:40.282000128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>325.0</th>\n",
       "      <td>77.64</td>\n",
       "      <td>0.011361</td>\n",
       "      <td>-50.023316</td>\n",
       "      <td>2023-06-29 00:25:33.488000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>469.0</th>\n",
       "      <td>80.73</td>\n",
       "      <td>0.016395</td>\n",
       "      <td>-51.141340</td>\n",
       "      <td>2023-06-29 00:25:37.734000128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3299017.0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.034399</td>\n",
       "      <td>-52.360176</td>\n",
       "      <td>2023-06-29 00:25:41.981000192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3299250.0</th>\n",
       "      <td>74.15</td>\n",
       "      <td>-0.026254</td>\n",
       "      <td>-51.669196</td>\n",
       "      <td>2023-06-29 00:25:39.432999936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3299627.0</th>\n",
       "      <td>74.76</td>\n",
       "      <td>-0.013074</td>\n",
       "      <td>-52.096244</td>\n",
       "      <td>2023-06-29 00:25:41.131000064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3299860.0</th>\n",
       "      <td>81.46</td>\n",
       "      <td>-0.004929</td>\n",
       "      <td>-51.405268</td>\n",
       "      <td>2023-06-29 00:25:38.583000064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3299949.0</th>\n",
       "      <td>69.01</td>\n",
       "      <td>-0.001817</td>\n",
       "      <td>-49.596268</td>\n",
       "      <td>2023-06-29 00:25:31.788999936</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>47330 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             surface_soil_moisture  latitude  longitude  \\\n",
       "location_id                                               \n",
       "3.0                            NaN  0.000104 -52.523292   \n",
       "92.0                         75.68  0.003216 -50.714296   \n",
       "236.0                        81.61  0.008250 -51.832316   \n",
       "325.0                        77.64  0.011361 -50.023316   \n",
       "469.0                        80.73  0.016395 -51.141340   \n",
       "...                            ...       ...        ...   \n",
       "3299017.0                      NaN -0.034399 -52.360176   \n",
       "3299250.0                    74.15 -0.026254 -51.669196   \n",
       "3299627.0                    74.76 -0.013074 -52.096244   \n",
       "3299860.0                    81.46 -0.004929 -51.405268   \n",
       "3299949.0                    69.01 -0.001817 -49.596268   \n",
       "\n",
       "                                     time  \n",
       "location_id                                \n",
       "3.0         2023-06-29 00:25:42.828999936  \n",
       "92.0        2023-06-29 00:25:36.035000064  \n",
       "236.0       2023-06-29 00:25:40.282000128  \n",
       "325.0       2023-06-29 00:25:33.488000000  \n",
       "469.0       2023-06-29 00:25:37.734000128  \n",
       "...                                   ...  \n",
       "3299017.0   2023-06-29 00:25:41.981000192  \n",
       "3299250.0   2023-06-29 00:25:39.432999936  \n",
       "3299627.0   2023-06-29 00:25:41.131000064  \n",
       "3299860.0   2023-06-29 00:25:38.583000064  \n",
       "3299949.0   2023-06-29 00:25:31.788999936  \n",
       "\n",
       "[47330 rows x 4 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ssm_df = ncfile[[\"location_id\", \"surface_soil_moisture\"]].to_dataframe()\n",
    "ssm_mean = ssm_df.groupby([\"location_id\"]).mean()\n",
    "ssm_mean"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4680db0e-e3cd-4d3e-a977-3e22daf0052f",
   "metadata": {},
   "source": [
    "## Visualize the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1cf0fe95-e0b4-4ead-8fbf-478ba473f689",
   "metadata": {},
   "outputs": [],
   "source": [
    "m = Maps()\n",
    "m.add_feature.preset(\"ocean\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7834fa58-b6e3-4ea1-b0d1-16d8c70b804d",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m.set_data(ssm_mean.dropna(), x=\"longitude\", y=\"latitude\", parameter=\"surface_soil_moisture\", crs=4326)\n",
    "m.set_shape.geod_circles(radius=6250)\n",
    "m.plot_map(set_extent=False)\n",
    "m.add_colorbar()\n",
    "m.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f1d2693-5bdd-46d2-a7b2-215a3a3fdc4d",
   "metadata": {},
   "source": [
    "## Visualize multiple files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "313272d4-a6b4-4292-a576-4b9eaf577717",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m = Maps(figsize=(6, 3))\n",
    "m.add_feature.preset(\"ocean\", layer=\"all\")\n",
    "m.set_shape.shade_points() # child maps will use the shape of the parent by default\n",
    "\n",
    "def on_layer(m, filepath, parameter):\n",
    "    with xar.open_dataset(filepath) as ncfile:\n",
    "        ssm_df = ncfile[[\"location_id\", parameter]].to_dataframe()\n",
    "        data = ssm_df.groupby([\"location_id\"]).mean()\n",
    "        \n",
    "    m.set_data(data, \"longitude\", \"latitude\", parameter=parameter, crs=4326)\n",
    "    m.plot_map(set_extent=False, cmap=\"viridis\", vmin=0, vmax=100)\n",
    "\n",
    "for filepath in swath_files:\n",
    "    m.on_layer_activation(on_layer, layer=filepath.stem, filepath=filepath, parameter=\"surface_soil_moisture\")\n",
    "\n",
    "m.show_layer(swath_files[0].stem)\n",
    "m.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "45f8a357-4b07-4153-8916-9e422bea281a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1e875e03c060403396421be4e03294b4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "LayerSelectionSlider(description='Layers', layout=Layout(width='90%'), options=(('W_IT-HSAF-ROME,SAT,SSM-ASCAT…"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "widgets.LayerSelectionSlider(m, layers=sorted([i.stem for i in swath_files]), layout=dict(width=\"90%\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b2503d5b-da93-4381-9b16-c71617ac3b1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "789a53229b1d41f0b10f8bcbe0159b74",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "LayerSelectMultiple(description='Layers', index=(0, 0), layout=Layout(height='300px', width='1000px'), options…"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "widgets.LayerSelectMultiple(m, layers=sorted([i.stem for i in swath_files]), layout=dict(width=\"1000px\", height=\"300px\"))"
   ]
  }
 ],
 "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": "3.11.4"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "0b35747f1f9c48318df425891d169010": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "SliderStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "0ca2b35c69d84a2794a7ac01610ce99d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "description_width": ""
      }
     },
     "1b1f44002426417388f564bae429950f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "height": "300px",
       "width": "1000px"
      }
     },
     "1e875e03c060403396421be4e03294b4": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "SelectionSliderModel",
      "state": {
       "_options_labels": [
        "W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_C_LIIB_20240219095753_20230629000000_20230629005959____",
        "W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_C_LIIB_20240219095755_20230629010000_20230629015959____",
        "W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_C_LIIB_20240219095756_20230629020000_20230629025959____",
        "W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_C_LIIB_20240219095758_20230629030000_20230629035959____",
        "W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_C_LIIB_20240219095801_20230629040000_20230629045959____",
        "W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_C_LIIB_20240219095806_20230629050000_20230629055959____",
        "W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_C_LIIB_20240219095808_20230629060000_20230629065959____",
        "W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_C_LIIB_20240219095808_20230629070000_20230629075959____",
        "W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_C_LIIB_20240219095808_20230629080000_20230629085959____",
        "W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_C_LIIB_20240219095808_20230629090000_20230629095959____",
        "W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_C_LIIB_20240219095809_20230629100000_20230629105959____",
        "W_IT-HSAF-ROME,SAT,SSM-ASCAT-METOPC-12.5km-H121_C_LIIB_20240219095810_20230629110000_20230629115959____",
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