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

.. only:: html

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

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

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

.. _sphx_glr_examples_formats_GINI_Water_Vapor.py:


========================
GINI Water Vapor Imagery
========================

Use MetPy's support for GINI files to read in a water vapor satellite image and plot the
data using CartoPy.

.. GENERATED FROM PYTHON SOURCE LINES 12-19

.. code-block:: Python

    import cartopy.feature as cfeature
    import matplotlib.pyplot as plt
    import xarray as xr

    from metpy.cbook import get_test_data
    from metpy.plots import add_metpy_logo, add_timestamp, colortables








.. GENERATED FROM PYTHON SOURCE LINES 20-25

.. code-block:: Python


    # Use Xarray together with MetPy's GINI backend to directly open the file from the test data
    ds = xr.open_dataset(get_test_data('WEST-CONUS_4km_WV_20151208_2200.gini', as_file_obj=False))
    print(ds)





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

 .. code-block:: none

    <xarray.Dataset> Size: 28MB
    Dimensions:     (y: 1280, x: 1100)
    Coordinates:
      * x           (x) float64 9kB -4.226e+06 -4.222e+06 ... 2.357e+05 2.397e+05
      * y           (y) float64 10kB 4.365e+06 4.36e+06 ... -8.286e+05 -8.327e+05
        lon         (y, x) float64 11MB ...
        lat         (y, x) float64 11MB ...
        time        datetime64[ns] 8B ...
    Data variables:
        projection  int64 8B ...
        WV          (y, x) float32 6MB ...
    Attributes:
        satellite:  GOES-15
        sector:     West CONUS




.. GENERATED FROM PYTHON SOURCE LINES 26-28

Pull out the data and (x, y) coordinates. We use `metpy.parse_cf` to handle parsing some
netCDF Climate and Forecasting (CF) metadata to simplify working with projections.

.. GENERATED FROM PYTHON SOURCE LINES 28-32

.. code-block:: Python

    x = ds.variables['x'][:]
    y = ds.variables['y'][:]
    dat = ds.metpy.parse_cf('WV')








.. GENERATED FROM PYTHON SOURCE LINES 33-35

Plot the image. We use MetPy's xarray/cartopy integration to automatically handle parsing
the projection information.

.. GENERATED FROM PYTHON SOURCE LINES 35-46

.. code-block:: Python

    fig = plt.figure(figsize=(10, 12))
    add_metpy_logo(fig, 125, 145)
    ax = fig.add_subplot(1, 1, 1, projection=dat.metpy.cartopy_crs)
    wv_norm, wv_cmap = colortables.get_with_range('WVCIMSS', 100, 260)
    wv_cmap.set_under('k')
    im = ax.imshow(dat[:], cmap=wv_cmap, norm=wv_norm,
                   extent=(x.min(), x.max(), y.min(), y.max()), origin='upper')
    ax.add_feature(cfeature.COASTLINE.with_scale('50m'))
    add_timestamp(ax, ds.time.dt, y=0.02, high_contrast=True)

    plt.show()



.. image-sg:: /examples/formats/images/sphx_glr_GINI_Water_Vapor_001.png
   :alt: GINI Water Vapor
   :srcset: /examples/formats/images/sphx_glr_GINI_Water_Vapor_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.869 seconds)


.. _sphx_glr_download_examples_formats_GINI_Water_Vapor.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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