.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples\prepare\polygonize_raster.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_prepare_polygonize_raster.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_prepare_polygonize_raster.py:


Polygonize raster
=================

iMOD Python also provides convenience functions to polygonize rasters.

.. GENERATED FROM PYTHON SOURCE LINES 7-10

.. code-block:: Python


    import matplotlib.pyplot as plt








.. GENERATED FROM PYTHON SOURCE LINES 11-14

.. code-block:: Python

    import imod









.. GENERATED FROM PYTHON SOURCE LINES 16-18

We'll start off by creating an example raster ``lake_grid`` to convert to
polygons. This is similar to the `Rasterize shapefiles` example.

.. GENERATED FROM PYTHON SOURCE LINES 18-36

.. code-block:: Python


    temp_dir = imod.util.temporary_directory()
    lakes = imod.data.lakes_shp(temp_dir)

    # Create dummy grid
    xmin = 90950.0
    xmax = 115650.0
    dx = 200

    ymin = 445850.0
    ymax = 467550.0
    dy = -200.0

    like_2d = imod.util.empty_2d(dx, xmin, xmax, dy, ymin, ymax)

    # Rasterrize the shapes
    lake_grid = imod.prepare.rasterize(lakes, like=like_2d)








.. GENERATED FROM PYTHON SOURCE LINES 37-38

Our raster looks like this:

.. GENERATED FROM PYTHON SOURCE LINES 38-41

.. code-block:: Python

    fig, ax = plt.subplots()
    lake_grid.plot(ax=ax)




.. image-sg:: /examples/prepare/images/sphx_glr_polygonize_raster_001.png
   :alt: dx = 200.0, dy = -200.0
   :srcset: /examples/prepare/images/sphx_glr_polygonize_raster_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    <matplotlib.collections.QuadMesh object at 0x000001ECD6A0CA10>



.. GENERATED FROM PYTHON SOURCE LINES 42-43

Polygonize the lakes

.. GENERATED FROM PYTHON SOURCE LINES 43-47

.. code-block:: Python

    polygonized_lakes = imod.prepare.polygonize(lake_grid)

    polygonized_lakes.head(5)






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>value</th>
          <th>geometry</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>1.0</td>
          <td>POLYGON ((94950 467550, 94950 467150, 95350 46...</td>
        </tr>
        <tr>
          <th>1</th>
          <td>1.0</td>
          <td>POLYGON ((95150 466950, 95150 466750, 95350 46...</td>
        </tr>
        <tr>
          <th>2</th>
          <td>1.0</td>
          <td>POLYGON ((103150 467550, 103150 466950, 103350...</td>
        </tr>
        <tr>
          <th>3</th>
          <td>1.0</td>
          <td>POLYGON ((109150 467550, 109150 467350, 108750...</td>
        </tr>
        <tr>
          <th>4</th>
          <td>1.0</td>
          <td>POLYGON ((102550 465950, 102550 465750, 102150...</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 48-50

This also polygonized the areas with np.nan. So we can drop those, using
regular pandas functionality

.. GENERATED FROM PYTHON SOURCE LINES 50-55

.. code-block:: Python


    polygonized_lakes = polygonized_lakes.dropna()

    polygonized_lakes.head(5)






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }

        .dataframe tbody tr th {
            vertical-align: top;
        }

        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>value</th>
          <th>geometry</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>1.0</td>
          <td>POLYGON ((94950 467550, 94950 467150, 95350 46...</td>
        </tr>
        <tr>
          <th>1</th>
          <td>1.0</td>
          <td>POLYGON ((95150 466950, 95150 466750, 95350 46...</td>
        </tr>
        <tr>
          <th>2</th>
          <td>1.0</td>
          <td>POLYGON ((103150 467550, 103150 466950, 103350...</td>
        </tr>
        <tr>
          <th>3</th>
          <td>1.0</td>
          <td>POLYGON ((109150 467550, 109150 467350, 108750...</td>
        </tr>
        <tr>
          <th>4</th>
          <td>1.0</td>
          <td>POLYGON ((102550 465950, 102550 465750, 102150...</td>
        </tr>
      </tbody>
    </table>
    </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 56-57

Plotted, we see a similar picture to the plotted raster

.. GENERATED FROM PYTHON SOURCE LINES 57-60

.. code-block:: Python

    fig, ax = plt.subplots()
    polygonized_lakes.plot(ax=ax)




.. image-sg:: /examples/prepare/images/sphx_glr_polygonize_raster_002.png
   :alt: polygonize raster
   :srcset: /examples/prepare/images/sphx_glr_polygonize_raster_002.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    <Axes: >



.. GENERATED FROM PYTHON SOURCE LINES 61-63

Since it is a GeoDataFrame, we can now do vector operations. Like computing
the centroids and plotting them as points.

.. GENERATED FROM PYTHON SOURCE LINES 63-69

.. code-block:: Python


    centroids = polygonized_lakes.centroid

    fig, ax = plt.subplots()
    polygonized_lakes.plot(ax=ax)
    centroids.plot(ax=ax, color="k")



.. image-sg:: /examples/prepare/images/sphx_glr_polygonize_raster_003.png
   :alt: polygonize raster
   :srcset: /examples/prepare/images/sphx_glr_polygonize_raster_003.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    <Axes: >




.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 1.048 seconds)


.. _sphx_glr_download_examples_prepare_polygonize_raster.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: polygonize_raster.ipynb <polygonize_raster.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: polygonize_raster.py <polygonize_raster.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: polygonize_raster.zip <polygonize_raster.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_