.. _graphics-rotated_pole_mapping:


Rotated pole mapping
=====================

This example uses several visualisation methods to achieve an array of
differing images, including:

 * Visualisation of point based data
 * Contouring of point based data
 * Block plot of contiguous bounded data
 * Non native projection and a Natural Earth shaded relief image underlay



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

::

    """
    Rotated pole mapping
    =====================
    
    This example uses several visualisation methods to achieve an array of
    differing images, including:
    
     * Visualisation of point based data
     * Contouring of point based data
     * Block plot of contiguous bounded data
     * Non native projection and a Natural Earth shaded relief image underlay
    
    """
    import cartopy.crs as ccrs
    import matplotlib.pyplot as plt
    
    import iris
    import iris.plot as iplt
    import iris.quickplot as qplt
    import iris.analysis.cartography
    
    
    def main():
        fname = iris.sample_data_path('rotated_pole.nc')
        air_pressure = iris.load_cube(fname)
    
        # Plot #1: Point plot showing data values & a colorbar
        plt.figure()
        points = qplt.points(air_pressure, c=air_pressure.data)
        cb = plt.colorbar(points, orientation='horizontal')
        cb.set_label(air_pressure.units)
        plt.gca().coastlines()
        plt.show()
    
        # Plot #2: Contourf of the point based data
        plt.figure()
        qplt.contourf(air_pressure, 15)
        plt.gca().coastlines()
        plt.show()
    
        # Plot #3: Contourf overlayed by coloured point data
        plt.figure()
        qplt.contourf(air_pressure)
        iplt.points(air_pressure, c=air_pressure.data)
        plt.gca().coastlines()
        plt.show()
    
        # For the purposes of this example, add some bounds to the latitude
        # and longitude
        air_pressure.coord('grid_latitude').guess_bounds()
        air_pressure.coord('grid_longitude').guess_bounds()
    
        # Plot #4: Block plot
        plt.figure()
        plt.axes(projection=ccrs.PlateCarree())
        iplt.pcolormesh(air_pressure)
        plt.gca().stock_img()
        plt.gca().coastlines()
        plt.show()
    
    
    if __name__ == '__main__':
        main()