.. _sphx_glr_gallery_waves.py:


Filled contours
---------------

An example of contourf on manufactured data.





.. image:: /gallery/images/sphx_glr_waves_001.png
    :align: center





.. code-block:: python


    import matplotlib.pyplot as plt
    import numpy as np

    import cartopy.crs as ccrs


    def sample_data(shape=(73, 145)):
        """Return ``lons``, ``lats`` and ``data`` of some fake data."""
        nlats, nlons = shape
        lats = np.linspace(-np.pi / 2, np.pi / 2, nlats)
        lons = np.linspace(0, 2 * np.pi, nlons)
        lons, lats = np.meshgrid(lons, lats)
        wave = 0.75 * (np.sin(2 * lats) ** 8) * np.cos(4 * lons)
        mean = 0.5 * np.cos(2 * lats) * ((np.sin(2 * lats)) ** 2 + 2)

        lats = np.rad2deg(lats)
        lons = np.rad2deg(lons)
        data = wave + mean

        return lons, lats, data


    def main():
        fig = plt.figure(figsize=(10, 5))
        ax = fig.add_subplot(1, 1, 1, projection=ccrs.Mollweide())

        lons, lats, data = sample_data()

        ax.contourf(lons, lats, data,
                    transform=ccrs.PlateCarree(),
                    cmap='nipy_spectral')
        ax.coastlines()
        ax.set_global()
        plt.show()


    if __name__ == '__main__':
        main()

**Total running time of the script:** ( 0 minutes  1.453 seconds)



.. container:: sphx-glr-footer


  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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

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

    `Generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_