.. _graphics-orca_projection:


Tri-Polar Grid Projected Plotting
================================

This example demonstrates cell plots of data on the semi-structured ORCA2 model
grid.

First, the data is projected into the PlateCarree coordinate reference system.

Second four pcolormesh plots are created from this projected dataset,
using different projections for the output image.



.. plot:: /net/home/h04/dkillick/git/iris/docs/iris/example_code/graphics/orca_projection.py

::

    """
    Tri-Polar Grid Projected Plotting
    ================================
    
    This example demonstrates cell plots of data on the semi-structured ORCA2 model
    grid.
    
    First, the data is projected into the PlateCarree coordinate reference system.
    
    Second four pcolormesh plots are created from this projected dataset,
    using different projections for the output image.
    
    """
    
    import matplotlib
    import matplotlib.pyplot as plt
    
    import cartopy.crs as ccrs
    import iris
    import iris.analysis.cartography
    import iris.quickplot as qplt
    
    
    def main():
        # Load data
        filepath = iris.sample_data_path('orca2_votemper.nc')
        cube = iris.load_cube(filepath)
    
        # Choose plot projections
        projections = {}
        projections['Mollweide'] = ccrs.Mollweide()
        projections['PlateCarree'] = ccrs.PlateCarree()
        projections['NorthPolarStereo'] = ccrs.NorthPolarStereo()
        projections['Orthographic'] = ccrs.Orthographic(central_longitude=-90,
                                                        central_latitude=45)
    
        pcarree = projections['PlateCarree']
        # Transform cube to target projection
        new_cube, extent = iris.analysis.cartography.project(cube, pcarree,
                                                             nx=400, ny=200)
    
        # Plot data in each projection
        for name in sorted(projections):
            fig = plt.figure()
            fig.suptitle('ORCA2 Data Projected to {}'.format(name))
            # Set up axes and title
            ax = plt.subplot(projection=projections[name])
            # Set limits
            ax.set_global()
            # plot with Iris quickplot pcolormesh
            qplt.pcolormesh(new_cube)
            # Draw coastlines
            ax.coastlines()
    
            plt.show()
    
    if __name__ == '__main__':
        main()