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   "source": [
    "# Providing a bespoke function to the temporal reduce methods"
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   "source": [
    "# If first time running, uncomment the line below to install any additional dependencies\n",
    "# !bash requirements-for-notebooks.sh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
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   "source": [
    "from statsmodels import api as sm\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from earthkit.transforms import aggregate as ek_aggregate\n",
    "from earthkit import data as ek_data\n",
    "\n",
    "from earthkit.data.testing import earthkit_remote_test_data_file\n",
    "ek_data.settings.set(\"cache-policy\", \"user\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load some test data\n",
    "\n",
    "All `earthkit-transforms` methods can be called with `earthkit-data` objects (Readers and Wrappers) or with the \n",
    "pre-loaded `xarray`.\n",
    "\n",
    "In this example we will use hourly ERA5 2m temperature data on a 0.5x0.5 spatial grid for the year 2015 as\n",
    "our physical data.\n",
    "\n",
    "First we download (if not already cached) lazily load the ERA5 data (please see tutorials in `earthkit-data` for more details in cache management).\n",
    "\n",
    "We inspect the data using the describe method and see we have some 2m air temperature data. For a more detailed representation of the data you can use the to_xarray method."
   ]
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   "execution_count": 3,
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    "# Get some demonstration ERA5 data, this could be any url or path to an ERA5 grib or netCDF file.\n",
    "remote_era5_file = earthkit_remote_test_data_file(\"test-data\", \"era5_temperature_europe_2015.grib\")\n",
    "era5_data = ek_data.from_source(\"url\", remote_era5_file)\n",
    "era5_data.describe()\n",
    "# era5_data.to_xarray()"
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    "## Reduce the ERA5 data using a bespoke function over the time dimension\n",
    "\n",
    "The default reduction method is `mean`, other methods can be applied using the `how` kwarg.\n",
    "\n",
    "Note that we do not need to worry about the data format of the input array, earthkit will convert it to the required xarray format internally."
   ]
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   "cell_type": "markdown",
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   "source": [
    "### Define a bespoke function for the reduction\n",
    "\n",
    "When providing a our own function to the reduce method it must conform the the Xarray requirements defined in their [documentation pages](https://docs.xarray.dev/en/stable/generated/xarray.DataArray.reduce.html#xarray-dataarray-reduce). Specifically:\n",
    "\n",
    "*\"Function which can be called in the form f(x, axis=axis, \\*\\*kwargs) to return the result of reducing an np.ndarray over an integer valued axis.\"*\n",
    "\n",
    "We will define a function which calculates the trend based on the [statsmodels Ordinary Least Squares model]https://www.statsmodels.org/dev/generated/statsmodels.regression.linear_model.OLS.html.\n",
    "\n",
    "Note that you will need to install statsmodels for the following function, it is available via PyPi and conda."
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    "def trend(x, axis=0, **kwargs):\n",
    "    # Add a constant for the intercept\n",
    "    X = sm.add_constant(np.arange(x.shape[axis]))\n",
    "\n",
    "    _x = np.rollaxis(x, axis)\n",
    "    _x_shape = _x.shape\n",
    "\n",
    "    _x_flat = _x.reshape(_x_shape[0], -1)\n",
    "    _out = np.zeros_like(_x_flat[0])\n",
    "    for point in range(_x_flat.shape[1]):\n",
    "        model = sm.OLS(_x_flat[:, point], X).fit()\n",
    "        _out[point] = model.params[1]\n",
    "\n",
    "    return _out.reshape(_x_shape[1:])"
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   "source": [
    "We can now use this method in our temporal reduce function to calculate the trend at each grid point."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
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       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 230kB\n",
       "Dimensions:    (number: 1, step: 1, surface: 1, latitude: 201, longitude: 281)\n",
       "Coordinates:\n",
       "  * number     (number) int64 8B 0\n",
       "  * step       (step) timedelta64[ns] 8B 00:00:00\n",
       "  * surface    (surface) float64 8B 0.0\n",
       "  * latitude   (latitude) float64 2kB 80.0 79.75 79.5 79.25 ... 30.5 30.25 30.0\n",
       "  * longitude  (longitude) float64 2kB -10.0 -9.75 -9.5 ... 59.5 59.75 60.0\n",
       "Data variables:\n",
       "    t2m        (number, step, surface, latitude, longitude) float32 226kB 0.0...\n",
       "Attributes:\n",
       "    GRIB_edition:            1\n",
       "    GRIB_centre:             ecmf\n",
       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             European Centre for Medium-Range Weather Forecasts\n",
       "    history:                 2024-10-15T14:46 GRIB to CDM+CF via cfgrib-0.9.1...</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-fa0ddcd7-11b2-4e17-9fe9-5686b74c41a7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fa0ddcd7-11b2-4e17-9fe9-5686b74c41a7' 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'>number</span>: 1</li><li><span class='xr-has-index'>step</span>: 1</li><li><span class='xr-has-index'>surface</span>: 1</li><li><span class='xr-has-index'>latitude</span>: 201</li><li><span class='xr-has-index'>longitude</span>: 281</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2790c26a-71a5-443e-aadc-5ce8847a7794' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2790c26a-71a5-443e-aadc-5ce8847a7794' class='xr-section-summary' >Coordinates: <span>(5)</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'>number</span></div><div class='xr-var-dims'>(number)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-dd83a85c-6155-47d1-8188-7d4c201130b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd83a85c-6155-47d1-8188-7d4c201130b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8c7a7ae-2c96-47a4-b5ec-836cf62a08cc' class='xr-var-data-in' type='checkbox'><label for='data-f8c7a7ae-2c96-47a4-b5ec-836cf62a08cc' 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>ensemble member numerical id</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>standard_name :</span></dt><dd>realization</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>step</span></div><div class='xr-var-dims'>(step)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>00:00:00</div><input id='attrs-93cb8f26-bdd5-408b-b764-ef43c8d8d845' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93cb8f26-bdd5-408b-b764-ef43c8d8d845' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0fcaa258-577c-4218-a445-b4bdd7d2c89b' class='xr-var-data-in' type='checkbox'><label for='data-0fcaa258-577c-4218-a445-b4bdd7d2c89b' 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 since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array([0], dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>surface</span></div><div class='xr-var-dims'>(surface)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-e127878c-263b-4018-903f-5e5ece2e8afc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e127878c-263b-4018-903f-5e5ece2e8afc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-334a0f36-5024-41a1-938f-4d7858a57d1d' class='xr-var-data-in' type='checkbox'><label for='data-334a0f36-5024-41a1-938f-4d7858a57d1d' 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>original GRIB coordinate for key: level(surface)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>80.0 79.75 79.5 ... 30.5 30.25 30.0</div><input id='attrs-4adef15d-fdd7-41f1-b47c-c17d46470a5f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4adef15d-fdd7-41f1-b47c-c17d46470a5f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a507ed7b-6625-4f8c-86c6-d2a002b280f0' class='xr-var-data-in' type='checkbox'><label for='data-a507ed7b-6625-4f8c-86c6-d2a002b280f0' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>stored_direction :</span></dt><dd>decreasing</dd></dl></div><div class='xr-var-data'><pre>array([80.  , 79.75, 79.5 , ..., 30.5 , 30.25, 30.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-10.0 -9.75 -9.5 ... 59.75 60.0</div><input id='attrs-1b405087-de09-4469-8cc4-f35546fe855d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b405087-de09-4469-8cc4-f35546fe855d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-820c49a0-c0fe-4425-a6b3-704e8289c08c' class='xr-var-data-in' type='checkbox'><label for='data-820c49a0-c0fe-4425-a6b3-704e8289c08c' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-10.  ,  -9.75,  -9.5 , ...,  59.5 ,  59.75,  60.  ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-debc6307-50b3-414f-a37d-892568ef8f35' class='xr-section-summary-in' type='checkbox'  checked><label for='section-debc6307-50b3-414f-a37d-892568ef8f35' class='xr-section-summary' >Data variables: <span>(1)</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>t2m</span></div><div class='xr-var-dims'>(number, step, surface, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.002469 0.00255 ... 0.001132</div><input id='attrs-1a2a93e8-fae5-4066-95e9-dac8c92239bb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a2a93e8-fae5-4066-95e9-dac8c92239bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77ecd8e1-d6f7-4899-b412-3a7cdf0dc2b1' class='xr-var-data-in' type='checkbox'><label for='data-77ecd8e1-d6f7-4899-b412-3a7cdf0dc2b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[[[0.00246916, 0.00254952, 0.00263007, ..., 0.0096086 ,\n",
       "           0.00958664, 0.00954637],\n",
       "          [0.00230726, 0.00239793, 0.00248861, ..., 0.00979828,\n",
       "           0.00980114, 0.00980355],\n",
       "          [0.0021973 , 0.00229007, 0.00238072, ..., 0.0101192 ,\n",
       "           0.01010588, 0.01009233],\n",
       "          ...,\n",
       "          [0.00397737, 0.0039945 , 0.00398622, ..., 0.00109193,\n",
       "           0.00119997, 0.00129892],\n",
       "          [0.00394296, 0.00386546, 0.00385728, ..., 0.0009384 ,\n",
       "           0.00098176, 0.00117158],\n",
       "          [0.00397888, 0.00401072, 0.00412463, ..., 0.00069417,\n",
       "           0.00081606, 0.00113239]]]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-09ccffc5-81f1-46bc-a664-4b0e30e7fa4c' class='xr-section-summary-in' type='checkbox'  ><label for='section-09ccffc5-81f1-46bc-a664-4b0e30e7fa4c' class='xr-section-summary' >Indexes: <span>(5)</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>number</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f559a1c3-f0b9-442c-ac64-7ba378d74e6b' class='xr-index-data-in' type='checkbox'/><label for='index-f559a1c3-f0b9-442c-ac64-7ba378d74e6b' 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(Index([0], dtype=&#x27;int64&#x27;, name=&#x27;number&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>step</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-41d4b200-1a29-491b-9fb5-4044f8d7c9c8' class='xr-index-data-in' type='checkbox'/><label for='index-41d4b200-1a29-491b-9fb5-4044f8d7c9c8' 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(TimedeltaIndex([&#x27;0 days&#x27;], dtype=&#x27;timedelta64[ns]&#x27;, name=&#x27;step&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>surface</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-adccb59f-eb89-4468-93db-b4cb10811f10' class='xr-index-data-in' type='checkbox'/><label for='index-adccb59f-eb89-4468-93db-b4cb10811f10' 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(Index([0.0], dtype=&#x27;float64&#x27;, name=&#x27;surface&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-763b87a9-d51b-4536-93b2-6e12a754cdd3' class='xr-index-data-in' type='checkbox'/><label for='index-763b87a9-d51b-4536-93b2-6e12a754cdd3' 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(Index([ 80.0, 79.75,  79.5, 79.25,  79.0, 78.75,  78.5, 78.25,  78.0, 77.75,\n",
       "       ...\n",
       "       32.25,  32.0, 31.75,  31.5, 31.25,  31.0, 30.75,  30.5, 30.25,  30.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;, length=201))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3df26a9a-ee89-4371-9829-d608b463faa1' class='xr-index-data-in' type='checkbox'/><label for='index-3df26a9a-ee89-4371-9829-d608b463faa1' 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(Index([-10.0, -9.75,  -9.5, -9.25,  -9.0, -8.75,  -8.5, -8.25,  -8.0, -7.75,\n",
       "       ...\n",
       "       57.75,  58.0, 58.25,  58.5, 58.75,  59.0, 59.25,  59.5, 59.75,  60.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;, length=281))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b1033b50-d91b-4639-82e5-90f0d0e1b63f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b1033b50-d91b-4639-82e5-90f0d0e1b63f' 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>GRIB_edition :</span></dt><dd>1</dd><dt><span>GRIB_centre :</span></dt><dd>ecmf</dd><dt><span>GRIB_centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>GRIB_subCentre :</span></dt><dd>0</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>history :</span></dt><dd>2024-10-15T14:46 GRIB to CDM+CF via cfgrib-0.9.14.1/ecCodes-2.38.0 with {&quot;source&quot;: &quot;N/A&quot;, &quot;filter_by_keys&quot;: {}, &quot;encode_cf&quot;: [&quot;parameter&quot;, &quot;time&quot;, &quot;geography&quot;, &quot;vertical&quot;]}</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 230kB\n",
       "Dimensions:    (number: 1, step: 1, surface: 1, latitude: 201, longitude: 281)\n",
       "Coordinates:\n",
       "  * number     (number) int64 8B 0\n",
       "  * step       (step) timedelta64[ns] 8B 00:00:00\n",
       "  * surface    (surface) float64 8B 0.0\n",
       "  * latitude   (latitude) float64 2kB 80.0 79.75 79.5 79.25 ... 30.5 30.25 30.0\n",
       "  * longitude  (longitude) float64 2kB -10.0 -9.75 -9.5 ... 59.5 59.75 60.0\n",
       "Data variables:\n",
       "    t2m        (number, step, surface, latitude, longitude) float32 226kB 0.0...\n",
       "Attributes:\n",
       "    GRIB_edition:            1\n",
       "    GRIB_centre:             ecmf\n",
       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
       "    GRIB_subCentre:          0\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             European Centre for Medium-Range Weather Forecasts\n",
       "    history:                 2024-10-15T14:46 GRIB to CDM+CF via cfgrib-0.9.1..."
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "era5_t_trend = ek_aggregate.temporal.reduce(era5_data, how=trend)\n",
    "era5_t_trend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'ERA5 2m Temperature Trend 20150101')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A simple matplotlib plot to view the data:\n",
    "era5_t_trend.t2m.plot(cmap=\"coolwarm\", vmin=-0.01, vmax=0.01)\n",
    "plt.title(\"ERA5 2m Temperature Trend 20150101\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "EARTHKIT",
   "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": "3.12.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}