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Created May 26, 2023 09:06
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EOCIS_QuickStartGuide_example.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"id": "5746a172",
"metadata": {
"ExecuteTime": {
"end_time": "2023-05-26T08:32:08.955924Z",
"start_time": "2023-05-26T08:32:08.946703Z"
}
},
"outputs": [],
"source": [
"import xarray as xr"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "38b041d8",
"metadata": {
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"end_time": "2023-05-26T08:33:15.196083Z",
"start_time": "2023-05-26T08:33:14.920091Z"
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
"Dimensions: (lat: 3600, lon: 7200, time: 1, bnds: 2)\n",
"Coordinates:\n",
" * lat (lat) float32 -89.97 -89.93 -89.88 ... 89.88 89.93 89.97\n",
" * lon (lon) float32 -180.0 -179.9 -179.9 ... 179.9 179.9 180.0\n",
" * time (time) datetime64[ns] 1996-01-12T21:06:12\n",
"Dimensions without coordinates: bnds\n",
"Data variables:\n",
" mask (time, lat, lon) float32 ...\n",
" lat_bnds (lat, bnds) float32 ...\n",
" lon_bnds (lon, bnds) float32 ...\n",
" analysed_sst (time, lat, lon) float32 ...\n",
" sea_ice_fraction (time, lat, lon) float32 ...\n",
" time_bnds (time, bnds) datetime64[ns] ...\n",
"Attributes: (12/58)\n",
" Conventions: CF-1.5, Unidata Observation Dataset v1.0\n",
" title: ESA SST CCI OSTIA L4 Climatology\n",
" summary: OSTIA L4 climatology product from the ES...\n",
" references: http://www.esa-sst-cci.org\n",
" institution: ESACCI\n",
" history: created with create_climatology.py v2.1\n",
" ... ...\n",
" source: ATSR&lt;1,2&gt;-ESACCI-L3U-v2.0, AATSR-ESACCI-...\n",
" platform: ERS-&lt;1,2&gt;, Envisat, NOAA-&lt;07,09,11,12,14...\n",
" creator_name: ESA SST CCI\n",
" product_specification_version: SST_CCI-PSD-UKMO-201-Issue-2\n",
" id: OSTIA-ESACCI-L4-GLOB-v2.1\n",
" product_version: 2.1</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-973ed0c0-82fc-4b54-93d9-74b1fca471b6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-973ed0c0-82fc-4b54-93d9-74b1fca471b6' 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'>lat</span>: 3600</li><li><span class='xr-has-index'>lon</span>: 7200</li><li><span class='xr-has-index'>time</span>: 1</li><li><span>bnds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b4225be5-9349-4c5b-80a5-91d3cc96cd71' class='xr-section-summary-in' type='checkbox' checked><label for='section-b4225be5-9349-4c5b-80a5-91d3cc96cd71' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.97 -89.93 ... 89.93 89.97</div><input id='attrs-17d5deab-eb63-44e4-8688-ad0e09c485c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17d5deab-eb63-44e4-8688-ad0e09c485c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1409161-fc8c-42bd-82e2-428cacd72a37' class='xr-var-data-in' type='checkbox'><label for='data-b1409161-fc8c-42bd-82e2-428cacd72a37' 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>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>comment :</span></dt><dd> Latitude geographical coordinates,WGS84 projection</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-89.975, -89.925, -89.875, ..., 89.875, 89.925, 89.975],\n",
" dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -179.9 ... 179.9 180.0</div><input id='attrs-4a4abd25-bc3e-4604-8f12-1bf8109c8084' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a4abd25-bc3e-4604-8f12-1bf8109c8084' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f729ea4-6c89-4b8b-aac6-4f858a814afc' class='xr-var-data-in' type='checkbox'><label for='data-8f729ea4-6c89-4b8b-aac6-4f858a814afc' 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>units :</span></dt><dd>degrees_east</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>comment :</span></dt><dd> Longitude geographical coordinates,WGS84 projection</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-179.975, -179.925, -179.875, ..., 179.875, 179.925, 179.975],\n",
" dtype=float32)</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'>1996-01-12T21:06:12</div><input id='attrs-c642b191-f2b9-426a-b078-357dff201d60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c642b191-f2b9-426a-b078-357dff201d60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-746f0810-4614-4ec1-94ec-b28bf53a5e2e' class='xr-var-data-in' type='checkbox'><label for='data-746f0810-4614-4ec1-94ec-b28bf53a5e2e' 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>reference time of sst field</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>comment :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1996-01-12T21:06:12.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cd8b490f-fcef-4a08-bc97-a3d37ae94a8f' class='xr-section-summary-in' type='checkbox' checked><label for='section-cd8b490f-fcef-4a08-bc97-a3d37ae94a8f' class='xr-section-summary' >Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>mask</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7430b532-5eba-4ef0-9272-9c6a8ff297b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7430b532-5eba-4ef0-9272-9c6a8ff297b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb112245-f2da-4b0a-a080-d7c9a3c796cc' class='xr-var-data-in' type='checkbox'><label for='data-cb112245-f2da-4b0a-a080-d7c9a3c796cc' 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>valid_min :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>31</dd><dt><span>flag_masks :</span></dt><dd>[ 1 2 4 8 16]</dd><dt><span>flag_meanings :</span></dt><dd>water land optional_lake_surface sea_ice optional_river_surface</dd><dt><span>source :</span></dt><dd>NAVOCEANO_landmask_v1.0 EUMETSAT_OSI-SAF_icemask ARCLake_lakemask</dd><dt><span>long_name :</span></dt><dd>sea/land/lake/ice field composite mask</dd><dt><span>comment :</span></dt><dd>b0: 1=grid cell is open sea water b1: 1=grid cell is land b2: 1=grid cell is lake surface b3: 1=grid cell is sea ice b4-b7: reserved for future grid mask data</dd></dl></div><div class='xr-var-data'><pre>[25920000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-197c0da4-58d1-46bb-81d0-691935269dba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-197c0da4-58d1-46bb-81d0-691935269dba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65856fbc-322c-4522-bec3-41a5f683175f' class='xr-var-data-in' type='checkbox'><label for='data-65856fbc-322c-4522-bec3-41a5f683175f' 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>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude cell boundaries</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>comment :</span></dt><dd>Contains the northern and southern boundaries of the grid cells.</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd></dl></div><div class='xr-var-data'><pre>[7200 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c8017f15-8130-4923-8090-f02463b3811d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c8017f15-8130-4923-8090-f02463b3811d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9224d5da-ef43-4361-9238-6f986d7e77c7' class='xr-var-data-in' type='checkbox'><label for='data-9224d5da-ef43-4361-9238-6f986d7e77c7' 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>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude cell boundaries</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>comment :</span></dt><dd>Contains the eastern and western boundaries of the grid cells.</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd></dl></div><div class='xr-var-data'><pre>[14400 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>analysed_sst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-63d6b4d0-6ec7-464b-bdab-4b659fed1c4b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63d6b4d0-6ec7-464b-bdab-4b659fed1c4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e52dc4ef-20e5-422f-9980-75c9a48dd21a' class='xr-var-data-in' type='checkbox'><label for='data-e52dc4ef-20e5-422f-9980-75c9a48dd21a' 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>analysed sea surface temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>-300</dd><dt><span>valid_max :</span></dt><dd>4500</dd><dt><span>source :</span></dt><dd>ATSR&lt;1,2&gt;-ESACCI-L3U-v2.0, AATSR-ESACCI-L3U-v2.0, AVHRR&lt;07,09,11,12,14,15,16,17,18,19&gt;_G-ESACCI-L3U-v2.0, AVHRRMTA_G-ESACCI-L3U-v2.0</dd><dt><span>depth :</span></dt><dd>20 cm</dd></dl></div><div class='xr-var-data'><pre>[25920000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sea_ice_fraction</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6584abc6-4de0-4d7e-9f26-3910b2496dda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6584abc6-4de0-4d7e-9f26-3910b2496dda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8533a9a3-ffb7-4494-add7-f2dbf1915365' class='xr-var-data-in' type='checkbox'><label for='data-8533a9a3-ffb7-4494-add7-f2dbf1915365' 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>sea ice area fraction</dd><dt><span>standard_name :</span></dt><dd>sea_ice_area_fraction</dd><dt><span>units :</span></dt><dd>1</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> Sea ice area fraction</dd><dt><span>source :</span></dt><dd>EUMETSAT_OSI-SAF-ICE-OSI-450-v2.0, EUMETSAT_OSI-SAF-ICE-OSI-430-v1.2</dd></dl></div><div class='xr-var-data'><pre>[25920000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9ab9d84b-b90d-4ad8-89a9-4c1a1452b588' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ab9d84b-b90d-4ad8-89a9-4c1a1452b588' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8ee43e8-6ea8-4dd0-9dae-48d40e3f6f48' class='xr-var-data-in' type='checkbox'><label for='data-f8ee43e8-6ea8-4dd0-9dae-48d40e3f6f48' 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 cell boundaries</dd><dt><span>comment :</span></dt><dd>Contains the start and end times for the time period the data represent.</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=datetime64[ns]]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4c733edd-227a-4ea2-b299-5d1f43993eac' class='xr-section-summary-in' type='checkbox' ><label for='section-4c733edd-227a-4ea2-b299-5d1f43993eac' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7d007f1a-bf25-4bdc-9698-67da5e150907' class='xr-index-data-in' type='checkbox'/><label for='index-7d007f1a-bf25-4bdc-9698-67da5e150907' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ -89.9749984741211, -89.92500305175781, -89.875,\n",
" -89.82499694824219, -89.7750015258789, -89.7249984741211,\n",
" -89.67500305175781, -89.625, -89.57499694824219,\n",
" -89.5250015258789,\n",
" ...\n",
" 89.5250015258789, 89.57499694824219, 89.625,\n",
" 89.67500305175781, 89.7249984741211, 89.7750015258789,\n",
" 89.82499694824219, 89.875, 89.92500305175781,\n",
" 89.9749984741211],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=3600))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0abfdfe3-dfee-4ee6-b0e6-cdc7aeccf49a' class='xr-index-data-in' type='checkbox'/><label for='index-0abfdfe3-dfee-4ee6-b0e6-cdc7aeccf49a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-179.97500610351562, -179.9250030517578, -179.875,\n",
" -179.8249969482422, -179.77499389648438, -179.72500610351562,\n",
" -179.6750030517578, -179.625, -179.5749969482422,\n",
" -179.52499389648438,\n",
" ...\n",
" 179.52499389648438, 179.5749969482422, 179.625,\n",
" 179.6750030517578, 179.72500610351562, 179.77499389648438,\n",
" 179.8249969482422, 179.875, 179.9250030517578,\n",
" 179.97500610351562],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=7200))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-04a67873-7fff-4c1e-a19d-1f2089e86cb0' class='xr-index-data-in' type='checkbox'/><label for='index-04a67873-7fff-4c1e-a19d-1f2089e86cb0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1996-01-12 21:06:12&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-806c82b3-aece-49db-ab88-5e20fab0de13' class='xr-section-summary-in' type='checkbox' ><label for='section-806c82b3-aece-49db-ab88-5e20fab0de13' class='xr-section-summary' >Attributes: <span>(58)</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-1.5, Unidata Observation Dataset v1.0</dd><dt><span>title :</span></dt><dd>ESA SST CCI OSTIA L4 Climatology</dd><dt><span>summary :</span></dt><dd>OSTIA L4 climatology product from the ESA SST CCI project</dd><dt><span>references :</span></dt><dd>http://www.esa-sst-cci.org</dd><dt><span>institution :</span></dt><dd>ESACCI</dd><dt><span>history :</span></dt><dd>created with create_climatology.py v2.1</dd><dt><span>comment :</span></dt><dd>These data were produced at the STFC CEMS as part of the ESA SST CCI project. WARNING Some applications are unable to properly handle signed byte values. If values are encountered &gt; 127, please subtract 256 from this reported value</dd><dt><span>license :</span></dt><dd>Creative Commons Licence by attribution (https://creativecommons.org/licenses/by/4.0/)</dd><dt><span>naming_authority :</span></dt><dd>org.ghrsst</dd><dt><span>uuid :</span></dt><dd>826c4162-ec03-4a23-9807-cf22318a8c78</dd><dt><span>tracking_id :</span></dt><dd>826c4162-ec03-4a23-9807-cf22318a8c78</dd><dt><span>gds_version_id :</span></dt><dd>2.0</dd><dt><span>date_created :</span></dt><dd>20181128T063658Z</dd><dt><span>file_quality_level :</span></dt><dd>3</dd><dt><span>spatial_resolution :</span></dt><dd>0.05 degree</dd><dt><span>start_time :</span></dt><dd>19820112T000000Z</dd><dt><span>time_coverage_start :</span></dt><dd>19820112T000000Z</dd><dt><span>stop_time :</span></dt><dd>20100112T000000Z</dd><dt><span>time_coverage_end :</span></dt><dd>20100112T000000Z</dd><dt><span>time_coverage_duration :</span></dt><dd>P1D</dd><dt><span>time_coverage_resolution :</span></dt><dd>P1D</dd><dt><span>northernmost_latitude :</span></dt><dd>90.0</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>southernmost_latitude :</span></dt><dd>-90.0</dd><dt><span>gepspatial_lat_min :</span></dt><dd>-90.0</dd><dt><span>easternmost_longitude :</span></dt><dd>180.00002</dd><dt><span>geospatial_lon_max :</span></dt><dd>180.00002</dd><dt><span>westernmost_longitude :</span></dt><dd>-180.0</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geospatial_vertical_min :</span></dt><dd>-0.2</dd><dt><span>geospatial_vertical_max :</span></dt><dd>-0.2</dd><dt><span>sensor :</span></dt><dd>ATSR, AATSR, AVHRR_GAC</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Dataset Discovery v1.0</dd><dt><span>metadata_link :</span></dt><dd>http://www.esa-cci.org</dd><dt><span>keywords :</span></dt><dd>Oceans &gt; Ocean Temperature &gt; Sea Surface Temperature</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Metadata Convention</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.05</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.05</dd><dt><span>acknowledgment :</span></dt><dd>Funded by ESA</dd><dt><span>creator_email :</span></dt><dd>science.leader@esa-sst-cci.org</dd><dt><span>creator_processing_institution :</span></dt><dd>These data were produced at the STFC CEMS as part of the ESA SST CCI project</dd><dt><span>creator_url :</span></dt><dd>http://www.esa-sst-cci.org</dd><dt><span>project :</span></dt><dd>Climate Change Initiative - European Space Agency</dd><dt><span>publisher_name :</span></dt><dd>ESACCI</dd><dt><span>publisher_url :</span></dt><dd>http://www.esa-sst-cci.org</dd><dt><span>publisher_email :</span></dt><dd>science.leader@esa-SST-cci.org</dd><dt><span>processing_level :</span></dt><dd>L4</dd><dt><span>cdm_data_type :</span></dt><dd>grid</dd><dt><span>netcdf_version_id :</span></dt><dd>4.4.1.1</dd><dt><span>source :</span></dt><dd>ATSR&lt;1,2&gt;-ESACCI-L3U-v2.0, AATSR-ESACCI-L3U-v2.0, AVHRR&lt;07,09,11,12,14,15,16,17,18,19&gt;_G-ESACCI-L3U-v2.0, AVHRRMTA_G-ESACCI-L3U-v2.0, EUMETSAT_OSI-SAF-ICE-OSI-450-v2.0, EUMETSAT_OSI-SAF-ICE-OSI-430-v1.2</dd><dt><span>platform :</span></dt><dd>ERS-&lt;1,2&gt;, Envisat, NOAA-&lt;07,09,11,12,14,15,16,17,18,19&gt;, MetOpA</dd><dt><span>creator_name :</span></dt><dd>ESA SST CCI</dd><dt><span>product_specification_version :</span></dt><dd>SST_CCI-PSD-UKMO-201-Issue-2</dd><dt><span>id :</span></dt><dd>OSTIA-ESACCI-L4-GLOB-v2.1</dd><dt><span>product_version :</span></dt><dd>2.1</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset>\n",
"Dimensions: (lat: 3600, lon: 7200, time: 1, bnds: 2)\n",
"Coordinates:\n",
" * lat (lat) float32 -89.97 -89.93 -89.88 ... 89.88 89.93 89.97\n",
" * lon (lon) float32 -180.0 -179.9 -179.9 ... 179.9 179.9 180.0\n",
" * time (time) datetime64[ns] 1996-01-12T21:06:12\n",
"Dimensions without coordinates: bnds\n",
"Data variables:\n",
" mask (time, lat, lon) float32 ...\n",
" lat_bnds (lat, bnds) float32 ...\n",
" lon_bnds (lon, bnds) float32 ...\n",
" analysed_sst (time, lat, lon) float32 ...\n",
" sea_ice_fraction (time, lat, lon) float32 ...\n",
" time_bnds (time, bnds) datetime64[ns] ...\n",
"Attributes: (12/58)\n",
" Conventions: CF-1.5, Unidata Observation Dataset v1.0\n",
" title: ESA SST CCI OSTIA L4 Climatology\n",
" summary: OSTIA L4 climatology product from the ES...\n",
" references: http://www.esa-sst-cci.org\n",
" institution: ESACCI\n",
" history: created with create_climatology.py v2.1\n",
" ... ...\n",
" source: ATSR<1,2>-ESACCI-L3U-v2.0, AATSR-ESACCI-...\n",
" platform: ERS-<1,2>, Envisat, NOAA-<07,09,11,12,14...\n",
" creator_name: ESA SST CCI\n",
" product_specification_version: SST_CCI-PSD-UKMO-201-Issue-2\n",
" id: OSTIA-ESACCI-L4-GLOB-v2.1\n",
" product_version: 2.1"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Open SST climatology dataset\n",
"filename = 'D012-ESACCI-L4_GHRSST-SSTdepth-OSTIA-GLOB_CDR2.1-v02.0-fv01.0.nc'\n",
"\n",
"d = xr.open_dataset(filename)\n",
"d"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "aa3d6a56",
"metadata": {
"ExecuteTime": {
"end_time": "2023-05-26T08:37:51.791275Z",
"start_time": "2023-05-26T08:37:50.612355Z"
}
},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Plot the analysed_sst variable\n",
"ax = d.analysed_sst[0].plot.imshow()\n",
"ax.axes.set_aspect('equal')"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "3e030bc4",
"metadata": {
"ExecuteTime": {
"end_time": "2023-05-26T08:43:30.804826Z",
"start_time": "2023-05-26T08:43:30.773413Z"
}
},
"outputs": [
{
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" grid-column: 2;\n",
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".xr-array-data,\n",
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" 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",
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".xr-var-dims {\n",
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"\n",
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" grid-column: 4;\n",
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".xr-index-preview {\n",
" grid-column: 2 / 5;\n",
" color: var(--xr-font-color2);\n",
"}\n",
"\n",
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".xr-var-dims,\n",
".xr-var-dtype,\n",
".xr-preview,\n",
".xr-attrs dt {\n",
" white-space: nowrap;\n",
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".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",
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"\n",
".xr-var-attrs,\n",
".xr-var-data,\n",
".xr-index-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",
".xr-index-data-in:checked ~ .xr-index-data {\n",
" display: block;\n",
"}\n",
"\n",
".xr-var-data > table {\n",
" float: right;\n",
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"\n",
".xr-var-name span,\n",
".xr-var-data,\n",
".xr-index-name div,\n",
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" padding-left: 25px !important;\n",
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"\n",
".xr-attrs,\n",
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".xr-index-data {\n",
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"\n",
"dl.xr-attrs {\n",
" padding: 0;\n",
" margin: 0;\n",
" display: grid;\n",
" grid-template-columns: 125px auto;\n",
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"\n",
".xr-attrs dt,\n",
".xr-attrs dd {\n",
" padding: 0;\n",
" margin: 0;\n",
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"\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",
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"\n",
".xr-icon-database,\n",
".xr-icon-file-text2,\n",
".xr-no-icon {\n",
" display: inline-block;\n",
" vertical-align: middle;\n",
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" 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.DataArray &#x27;analysed_sst&#x27; (time: 1, lat: 460, lon: 800)&gt;\n",
"[368000 values with dtype=float32]\n",
"Coordinates:\n",
" * lat (lat) float32 12.02 12.07 12.12 12.18 ... 34.83 34.88 34.92 34.97\n",
" * lon (lon) float32 -120.0 -119.9 -119.9 -119.8 ... -80.12 -80.07 -80.03\n",
" * time (time) datetime64[ns] 1996-01-12T21:06:12\n",
"Attributes:\n",
" long_name: analysed sea surface temperature\n",
" standard_name: sea_water_temperature\n",
" units: kelvin\n",
" valid_min: -300\n",
" valid_max: 4500\n",
" source: ATSR&lt;1,2&gt;-ESACCI-L3U-v2.0, AATSR-ESACCI-L3U-v2.0, AVHRR&lt;0...\n",
" depth: 20 cm</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'>'analysed_sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>lat</span>: 460</li><li><span class='xr-has-index'>lon</span>: 800</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2ac732ba-becb-47a4-b668-77807419cd6c' class='xr-array-in' type='checkbox' checked><label for='section-2ac732ba-becb-47a4-b668-77807419cd6c' 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>...</span></div><div class='xr-array-data'><pre>[368000 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-6eba4dfc-0fa9-4470-b43d-144280cf6760' class='xr-section-summary-in' type='checkbox' checked><label for='section-6eba4dfc-0fa9-4470-b43d-144280cf6760' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.02 12.07 12.12 ... 34.92 34.97</div><input id='attrs-f6c86f4d-7f41-4a71-aeed-85b6da02ee9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f6c86f4d-7f41-4a71-aeed-85b6da02ee9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce6167c5-ed76-4ea6-a830-93aaa1c66254' class='xr-var-data-in' type='checkbox'><label for='data-ce6167c5-ed76-4ea6-a830-93aaa1c66254' 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>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>comment :</span></dt><dd> Latitude geographical coordinates,WGS84 projection</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd></dl></div><div class='xr-var-data'><pre>array([12.025, 12.075, 12.125, ..., 34.875, 34.925, 34.975], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-120.0 -119.9 ... -80.07 -80.03</div><input id='attrs-0a5c7e15-09fa-4e62-bbd5-4318af72475c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a5c7e15-09fa-4e62-bbd5-4318af72475c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e857eb78-5444-4f48-a2fe-c57ab4116841' class='xr-var-data-in' type='checkbox'><label for='data-e857eb78-5444-4f48-a2fe-c57ab4116841' 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>units :</span></dt><dd>degrees_east</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>comment :</span></dt><dd> Longitude geographical coordinates,WGS84 projection</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-119.975, -119.925, -119.875, ..., -80.125, -80.075, -80.025],\n",
" dtype=float32)</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'>1996-01-12T21:06:12</div><input id='attrs-3f3a8a1a-2615-438f-8e66-7e997ed3e330' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f3a8a1a-2615-438f-8e66-7e997ed3e330' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6558bf18-c19f-4b0d-8827-c0e6c4dff837' class='xr-var-data-in' type='checkbox'><label for='data-6558bf18-c19f-4b0d-8827-c0e6c4dff837' 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>reference time of sst field</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>comment :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1996-01-12T21:06:12.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3f1cfce4-cf47-4783-a33b-e402b9ffbd72' class='xr-section-summary-in' type='checkbox' ><label for='section-3f1cfce4-cf47-4783-a33b-e402b9ffbd72' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-456cba37-2c76-4bc6-9769-68e290e4ef57' class='xr-index-data-in' type='checkbox'/><label for='index-456cba37-2c76-4bc6-9769-68e290e4ef57' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([12.024999618530273, 12.074999809265137, 12.125,\n",
" 12.175000190734863, 12.225000381469727, 12.274999618530273,\n",
" 12.324999809265137, 12.375, 12.425000190734863,\n",
" 12.475000381469727,\n",
" ...\n",
" 34.525001525878906, 34.57500076293945, 34.625,\n",
" 34.67499923706055, 34.724998474121094, 34.775001525878906,\n",
" 34.82500076293945, 34.875, 34.92499923706055,\n",
" 34.974998474121094],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=460))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4ea1514c-e608-403e-8a05-734216032494' class='xr-index-data-in' type='checkbox'/><label for='index-4ea1514c-e608-403e-8a05-734216032494' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([ -119.9749984741211, -119.92500305175781, -119.875,\n",
" -119.82499694824219, -119.7750015258789, -119.7249984741211,\n",
" -119.67500305175781, -119.625, -119.57499694824219,\n",
" -119.5250015258789,\n",
" ...\n",
" -80.4749984741211, -80.42500305175781, -80.375,\n",
" -80.32499694824219, -80.2750015258789, -80.2249984741211,\n",
" -80.17500305175781, -80.125, -80.07499694824219,\n",
" -80.0250015258789],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=800))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8abc18f8-0d34-4a30-a59b-313a6ca98dcc' class='xr-index-data-in' type='checkbox'/><label for='index-8abc18f8-0d34-4a30-a59b-313a6ca98dcc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1996-01-12 21:06:12&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d84b6142-f238-498a-8e31-8791baa1e6c2' class='xr-section-summary-in' type='checkbox' checked><label for='section-d84b6142-f238-498a-8e31-8791baa1e6c2' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>analysed sea surface temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>-300</dd><dt><span>valid_max :</span></dt><dd>4500</dd><dt><span>source :</span></dt><dd>ATSR&lt;1,2&gt;-ESACCI-L3U-v2.0, AATSR-ESACCI-L3U-v2.0, AVHRR&lt;07,09,11,12,14,15,16,17,18,19&gt;_G-ESACCI-L3U-v2.0, AVHRRMTA_G-ESACCI-L3U-v2.0</dd><dt><span>depth :</span></dt><dd>20 cm</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'analysed_sst' (time: 1, lat: 460, lon: 800)>\n",
"[368000 values with dtype=float32]\n",
"Coordinates:\n",
" * lat (lat) float32 12.02 12.07 12.12 12.18 ... 34.83 34.88 34.92 34.97\n",
" * lon (lon) float32 -120.0 -119.9 -119.9 -119.8 ... -80.12 -80.07 -80.03\n",
" * time (time) datetime64[ns] 1996-01-12T21:06:12\n",
"Attributes:\n",
" long_name: analysed sea surface temperature\n",
" standard_name: sea_water_temperature\n",
" units: kelvin\n",
" valid_min: -300\n",
" valid_max: 4500\n",
" source: ATSR<1,2>-ESACCI-L3U-v2.0, AATSR-ESACCI-L3U-v2.0, AVHRR<0...\n",
" depth: 20 cm"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Get a spatial subset\n",
"subset = d.analysed_sst.sel(lat=slice(12,35), lon=slice(-120,-80))\n",
"subset"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "16fb624c",
"metadata": {
"ExecuteTime": {
"end_time": "2023-05-26T08:43:32.649624Z",
"start_time": "2023-05-26T08:43:32.358825Z"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Plot the analysed_sst variable spatial subset\n",
"bx = subset[0].plot.imshow()\n",
"bx.axes.set_aspect('equal')"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "a866b469",
"metadata": {
"ExecuteTime": {
"end_time": "2023-05-26T08:58:36.364900Z",
"start_time": "2023-05-26T08:58:36.344231Z"
}
},
"outputs": [
{
"data": {
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;analysed_sst&#x27; (time: 1, lat: 12, lon: 20)&gt;\n",
"array([[[299.26883, 299.59628, 299.85223, 300.0256 , 300.2094 ,\n",
" 300.47913, 300.70135, 300.90747, 301.12595, 301.25296,\n",
" 300.80478, 299.57184, 299.1493 , 300.87653, 300.99817,\n",
" 300.53937, 300.3147 , nan, 300.09204, 300.2249 ],\n",
" [298.74512, 299.09604, 299.27563, 299.4989 , 299.71423,\n",
" 300.0967 , 300.5269 , 300.97546, 301.40594, 301.6634 ,\n",
" 301.4784 , 300.29782, 298.39578, 300.8796 , 301.5495 ,\n",
" 299.58887, 299.86368, 299.88837, 299.93375, 300.2079 ],\n",
" [297.53473, 297.93796, 298.27625, 298.60852, 298.9878 ,\n",
" 299.3624 , 299.79782, 300.39035, 301.02588, 301.43448,\n",
" 301.41733, 301.108 , 299.26166, nan, nan,\n",
" 299.47406, 299.89 , 299.97693, 300.0306 , 300.19644],\n",
" [296.12015, 296.6394 , 297.09787, 297.47195, 297.9958 ,\n",
" 298.32507, 298.42703, 299.49072, 300.56644, nan,\n",
" nan, 296.20676, 296.89688, 297.58472, 297.49915,\n",
" 298.75116, 299.84973, 299.9952 , 300.01956, 300.00208],\n",
" [294.52316, 295.0194 , 295.48624, 296.17395, 296.9367 ,\n",
" 297.13574, 297.52734, 297.94537, nan, nan,\n",
" nan, 296.12042, 297.07263, 297.49405, 297.19778,\n",
" 296.9748 , 299.13403, 299.78534, 299.5093 , 299.51996],\n",
"...\n",
" 292.04108, nan, nan, nan, nan,\n",
" nan, 292.90073, 295.18802, 295.42578, 295.74222,\n",
" 296.1491 , 296.9489 , 296.03348, 293.3251 , 295.28137],\n",
" [289.8106 , 289.77408, 289.7267 , 289.89236, 290.203 ,\n",
" nan, nan, nan, nan, nan,\n",
" nan, 289.47845, 290.30927, 290.83954, 291.21512,\n",
" 292.46313, 294.04898, 292.3974 , 289.6677 , 294.28754],\n",
" [288.63376, 288.8499 , 289.44843, 290.0292 , nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, 286.59668, 286.97623,\n",
" 287.5389 , 290.19333, 289.09692, 287.62332, 291.20853],\n",
" [287.83282, 288.3241 , nan, nan, nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, nan, 287.93307],\n",
" [287.4508 , nan, nan, nan, nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, nan, nan]]],\n",
" dtype=float32)\n",
"Coordinates:\n",
" * lat (lat) float32 13.0 15.0 17.0 19.0 21.0 ... 27.0 29.0 31.0 33.0 34.5\n",
" * lon (lon) float32 -119.0 -117.0 -115.0 -113.0 ... -85.0 -83.0 -81.0\n",
" * time (time) datetime64[ns] 1996-01-12T21:06:12\n",
"Attributes:\n",
" long_name: analysed sea surface temperature\n",
" standard_name: sea_water_temperature\n",
" units: kelvin\n",
" valid_min: -300\n",
" valid_max: 4500\n",
" source: ATSR&lt;1,2&gt;-ESACCI-L3U-v2.0, AATSR-ESACCI-L3U-v2.0, AVHRR&lt;0...\n",
" depth: 20 cm</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'>'analysed_sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>lat</span>: 12</li><li><span class='xr-has-index'>lon</span>: 20</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-d620d8b1-37cf-407e-b794-a27f0f664c67' class='xr-array-in' type='checkbox' checked><label for='section-d620d8b1-37cf-407e-b794-a27f0f664c67' 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>299.3 299.6 299.9 300.0 300.2 300.5 300.7 ... nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[[299.26883, 299.59628, 299.85223, 300.0256 , 300.2094 ,\n",
" 300.47913, 300.70135, 300.90747, 301.12595, 301.25296,\n",
" 300.80478, 299.57184, 299.1493 , 300.87653, 300.99817,\n",
" 300.53937, 300.3147 , nan, 300.09204, 300.2249 ],\n",
" [298.74512, 299.09604, 299.27563, 299.4989 , 299.71423,\n",
" 300.0967 , 300.5269 , 300.97546, 301.40594, 301.6634 ,\n",
" 301.4784 , 300.29782, 298.39578, 300.8796 , 301.5495 ,\n",
" 299.58887, 299.86368, 299.88837, 299.93375, 300.2079 ],\n",
" [297.53473, 297.93796, 298.27625, 298.60852, 298.9878 ,\n",
" 299.3624 , 299.79782, 300.39035, 301.02588, 301.43448,\n",
" 301.41733, 301.108 , 299.26166, nan, nan,\n",
" 299.47406, 299.89 , 299.97693, 300.0306 , 300.19644],\n",
" [296.12015, 296.6394 , 297.09787, 297.47195, 297.9958 ,\n",
" 298.32507, 298.42703, 299.49072, 300.56644, nan,\n",
" nan, 296.20676, 296.89688, 297.58472, 297.49915,\n",
" 298.75116, 299.84973, 299.9952 , 300.01956, 300.00208],\n",
" [294.52316, 295.0194 , 295.48624, 296.17395, 296.9367 ,\n",
" 297.13574, 297.52734, 297.94537, nan, nan,\n",
" nan, 296.12042, 297.07263, 297.49405, 297.19778,\n",
" 296.9748 , 299.13403, 299.78534, 299.5093 , 299.51996],\n",
"...\n",
" 292.04108, nan, nan, nan, nan,\n",
" nan, 292.90073, 295.18802, 295.42578, 295.74222,\n",
" 296.1491 , 296.9489 , 296.03348, 293.3251 , 295.28137],\n",
" [289.8106 , 289.77408, 289.7267 , 289.89236, 290.203 ,\n",
" nan, nan, nan, nan, nan,\n",
" nan, 289.47845, 290.30927, 290.83954, 291.21512,\n",
" 292.46313, 294.04898, 292.3974 , 289.6677 , 294.28754],\n",
" [288.63376, 288.8499 , 289.44843, 290.0292 , nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, 286.59668, 286.97623,\n",
" 287.5389 , 290.19333, 289.09692, 287.62332, 291.20853],\n",
" [287.83282, 288.3241 , nan, nan, nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, nan, 287.93307],\n",
" [287.4508 , nan, nan, nan, nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, nan, nan]]],\n",
" dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-fb8ddf92-c8b2-4b7c-90b7-4570644d78d5' class='xr-section-summary-in' type='checkbox' checked><label for='section-fb8ddf92-c8b2-4b7c-90b7-4570644d78d5' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.0 15.0 17.0 ... 31.0 33.0 34.5</div><input id='attrs-da472c59-ebfd-4dea-b50f-8da4e840d8b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da472c59-ebfd-4dea-b50f-8da4e840d8b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da88f7ca-eceb-4db7-83b3-71a32aab481e' class='xr-var-data-in' type='checkbox'><label for='data-da88f7ca-eceb-4db7-83b3-71a32aab481e' 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>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>comment :</span></dt><dd> Latitude geographical coordinates,WGS84 projection</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd></dl></div><div class='xr-var-data'><pre>array([13. , 15. , 17. , 19. , 21. , 23. , 25. , 27. , 29. , 31. , 33. , 34.5],\n",
" dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-119.0 -117.0 ... -83.0 -81.0</div><input id='attrs-7eca5137-fbe9-43e6-945e-0a844ad22a16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7eca5137-fbe9-43e6-945e-0a844ad22a16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60ca187d-dd52-4735-8ab6-a76cb49ec4ec' class='xr-var-data-in' type='checkbox'><label for='data-60ca187d-dd52-4735-8ab6-a76cb49ec4ec' 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>units :</span></dt><dd>degrees_east</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>comment :</span></dt><dd> Longitude geographical coordinates,WGS84 projection</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>reference_datum :</span></dt><dd>geographical coordinates, WGS84 projection</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-119., -117., -115., -113., -111., -109., -107., -105., -103., -101.,\n",
" -99., -97., -95., -93., -91., -89., -87., -85., -83., -81.],\n",
" dtype=float32)</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'>1996-01-12T21:06:12</div><input id='attrs-07fef32d-f937-4687-b562-5bfbf98b9810' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07fef32d-f937-4687-b562-5bfbf98b9810' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e566ffb-e604-4b91-bbc0-6045da71ca6d' class='xr-var-data-in' type='checkbox'><label for='data-8e566ffb-e604-4b91-bbc0-6045da71ca6d' 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>reference time of sst field</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>comment :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1996-01-12T21:06:12.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5ce74db1-cf61-4abd-a7b5-3c9f7720991a' class='xr-section-summary-in' type='checkbox' ><label for='section-5ce74db1-cf61-4abd-a7b5-3c9f7720991a' class='xr-section-summary' >Indexes: <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-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dfe05960-448d-4f9e-bf7e-1d26888cb3b3' class='xr-index-data-in' type='checkbox'/><label for='index-dfe05960-448d-4f9e-bf7e-1d26888cb3b3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([13.0, 15.0, 17.0, 19.0, 21.0, 23.0, 25.0, 27.0, 29.0, 31.0, 33.0,\n",
" 34.5],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-57499ec2-042d-4061-9e63-4b13b77a75e4' class='xr-index-data-in' type='checkbox'/><label for='index-57499ec2-042d-4061-9e63-4b13b77a75e4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-119.0, -117.0, -115.0, -113.0, -111.0, -109.0, -107.0, -105.0,\n",
" -103.0, -101.0, -99.0, -97.0, -95.0, -93.0, -91.0, -89.0,\n",
" -87.0, -85.0, -83.0, -81.0],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d0595205-8064-44fb-9879-34746c6a1510' class='xr-index-data-in' type='checkbox'/><label for='index-d0595205-8064-44fb-9879-34746c6a1510' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1996-01-12 21:06:12&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9ec3b30d-c5c0-4ab1-a51d-9f7e810a7899' class='xr-section-summary-in' type='checkbox' checked><label for='section-9ec3b30d-c5c0-4ab1-a51d-9f7e810a7899' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>analysed sea surface temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd><dt><span>units :</span></dt><dd>kelvin</dd><dt><span>valid_min :</span></dt><dd>-300</dd><dt><span>valid_max :</span></dt><dd>4500</dd><dt><span>source :</span></dt><dd>ATSR&lt;1,2&gt;-ESACCI-L3U-v2.0, AATSR-ESACCI-L3U-v2.0, AVHRR&lt;07,09,11,12,14,15,16,17,18,19&gt;_G-ESACCI-L3U-v2.0, AVHRRMTA_G-ESACCI-L3U-v2.0</dd><dt><span>depth :</span></dt><dd>20 cm</dd></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.DataArray 'analysed_sst' (time: 1, lat: 12, lon: 20)>\n",
"array([[[299.26883, 299.59628, 299.85223, 300.0256 , 300.2094 ,\n",
" 300.47913, 300.70135, 300.90747, 301.12595, 301.25296,\n",
" 300.80478, 299.57184, 299.1493 , 300.87653, 300.99817,\n",
" 300.53937, 300.3147 , nan, 300.09204, 300.2249 ],\n",
" [298.74512, 299.09604, 299.27563, 299.4989 , 299.71423,\n",
" 300.0967 , 300.5269 , 300.97546, 301.40594, 301.6634 ,\n",
" 301.4784 , 300.29782, 298.39578, 300.8796 , 301.5495 ,\n",
" 299.58887, 299.86368, 299.88837, 299.93375, 300.2079 ],\n",
" [297.53473, 297.93796, 298.27625, 298.60852, 298.9878 ,\n",
" 299.3624 , 299.79782, 300.39035, 301.02588, 301.43448,\n",
" 301.41733, 301.108 , 299.26166, nan, nan,\n",
" 299.47406, 299.89 , 299.97693, 300.0306 , 300.19644],\n",
" [296.12015, 296.6394 , 297.09787, 297.47195, 297.9958 ,\n",
" 298.32507, 298.42703, 299.49072, 300.56644, nan,\n",
" nan, 296.20676, 296.89688, 297.58472, 297.49915,\n",
" 298.75116, 299.84973, 299.9952 , 300.01956, 300.00208],\n",
" [294.52316, 295.0194 , 295.48624, 296.17395, 296.9367 ,\n",
" 297.13574, 297.52734, 297.94537, nan, nan,\n",
" nan, 296.12042, 297.07263, 297.49405, 297.19778,\n",
" 296.9748 , 299.13403, 299.78534, 299.5093 , 299.51996],\n",
"...\n",
" 292.04108, nan, nan, nan, nan,\n",
" nan, 292.90073, 295.18802, 295.42578, 295.74222,\n",
" 296.1491 , 296.9489 , 296.03348, 293.3251 , 295.28137],\n",
" [289.8106 , 289.77408, 289.7267 , 289.89236, 290.203 ,\n",
" nan, nan, nan, nan, nan,\n",
" nan, 289.47845, 290.30927, 290.83954, 291.21512,\n",
" 292.46313, 294.04898, 292.3974 , 289.6677 , 294.28754],\n",
" [288.63376, 288.8499 , 289.44843, 290.0292 , nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, 286.59668, 286.97623,\n",
" 287.5389 , 290.19333, 289.09692, 287.62332, 291.20853],\n",
" [287.83282, 288.3241 , nan, nan, nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, nan, 287.93307],\n",
" [287.4508 , nan, nan, nan, nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, nan, nan,\n",
" nan, nan, nan, nan, nan]]],\n",
" dtype=float32)\n",
"Coordinates:\n",
" * lat (lat) float32 13.0 15.0 17.0 19.0 21.0 ... 27.0 29.0 31.0 33.0 34.5\n",
" * lon (lon) float32 -119.0 -117.0 -115.0 -113.0 ... -85.0 -83.0 -81.0\n",
" * time (time) datetime64[ns] 1996-01-12T21:06:12\n",
"Attributes:\n",
" long_name: analysed sea surface temperature\n",
" standard_name: sea_water_temperature\n",
" units: kelvin\n",
" valid_min: -300\n",
" valid_max: 4500\n",
" source: ATSR<1,2>-ESACCI-L3U-v2.0, AATSR-ESACCI-L3U-v2.0, AVHRR<0...\n",
" depth: 20 cm"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Regridding to a coarser spatial resolution (40x coarser)\n",
"subset_coarse = subset.coarsen(lon=40, lat=40, boundary='pad').mean()\n",
"subset_coarse"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "ae0da31f",
"metadata": {
"ExecuteTime": {
"end_time": "2023-05-26T08:58:41.659674Z",
"start_time": "2023-05-26T08:58:41.407541Z"
}
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cx = subset_coarse[0].plot(edgecolor='k')\n",
"cx.axes.set_aspect('equal')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "58ed585c",
"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": "3.11.0"
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": false,
"sideBar": false,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {},
"toc_section_display": false,
"toc_window_display": false
},
"varInspector": {
"cols": {
"lenName": 16,
"lenType": 16,
"lenVar": 40
},
"kernels_config": {
"python": {
"delete_cmd_postfix": "",
"delete_cmd_prefix": "del ",
"library": "var_list.py",
"varRefreshCmd": "print(var_dic_list())"
},
"r": {
"delete_cmd_postfix": ") ",
"delete_cmd_prefix": "rm(",
"library": "var_list.r",
"varRefreshCmd": "cat(var_dic_list()) "
}
},
"types_to_exclude": [
"module",
"function",
"builtin_function_or_method",
"instance",
"_Feature"
],
"window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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