.. _pylab_examples-contourf_demo:

pylab_examples example code: contourf_demo.py
=============================================



.. plot:: /home/tcaswell/source/p/matplotlib/doc/mpl_examples/pylab_examples/contourf_demo.py

::

    import numpy as np
    import matplotlib.pyplot as plt
    
    origin = 'lower'
    #origin = 'upper'
    
    delta = 0.025
    
    x = y = np.arange(-3.0, 3.01, delta)
    X, Y = np.meshgrid(x, y)
    Z1 = plt.mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
    Z2 = plt.mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
    Z = 10 * (Z1 - Z2)
    
    nr, nc = Z.shape
    
    # put NaNs in one corner:
    Z[-nr//6:, -nc//6:] = np.nan
    # contourf will convert these to masked
    
    
    Z = np.ma.array(Z)
    # mask another corner:
    Z[:nr//6, :nc//6] = np.ma.masked
    
    # mask a circle in the middle:
    interior = np.sqrt((X**2) + (Y**2)) < 0.5
    Z[interior] = np.ma.masked
    
    # We are using automatic selection of contour levels;
    # this is usually not such a good idea, because they don't
    # occur on nice boundaries, but we do it here for purposes
    # of illustration.
    CS = plt.contourf(X, Y, Z, 10,
                      #[-1, -0.1, 0, 0.1],
                      #alpha=0.5,
                      cmap=plt.cm.bone,
                      origin=origin)
    
    # Note that in the following, we explicitly pass in a subset of
    # the contour levels used for the filled contours.  Alternatively,
    # We could pass in additional levels to provide extra resolution,
    # or leave out the levels kwarg to use all of the original levels.
    
    CS2 = plt.contour(CS, levels=CS.levels[::2],
                      colors='r',
                      origin=origin)
    
    plt.title('Nonsense (3 masked regions)')
    plt.xlabel('word length anomaly')
    plt.ylabel('sentence length anomaly')
    
    # Make a colorbar for the ContourSet returned by the contourf call.
    cbar = plt.colorbar(CS)
    cbar.ax.set_ylabel('verbosity coefficient')
    # Add the contour line levels to the colorbar
    cbar.add_lines(CS2)
    
    plt.figure()
    
    # Now make a contour plot with the levels specified,
    # and with the colormap generated automatically from a list
    # of colors.
    levels = [-1.5, -1, -0.5, 0, 0.5, 1]
    CS3 = plt.contourf(X, Y, Z, levels,
                       colors=('r', 'g', 'b'),
                       origin=origin,
                       extend='both')
    # Our data range extends outside the range of levels; make
    # data below the lowest contour level yellow, and above the
    # highest level cyan:
    CS3.cmap.set_under('yellow')
    CS3.cmap.set_over('cyan')
    
    CS4 = plt.contour(X, Y, Z, levels,
                      colors=('k',),
                      linewidths=(3,),
                      origin=origin)
    plt.title('Listed colors (3 masked regions)')
    plt.clabel(CS4, fmt='%2.1f', colors='w', fontsize=14)
    
    # Notice that the colorbar command gets all the information it
    # needs from the ContourSet object, CS3.
    plt.colorbar(CS3)
    
    # Illustrate all 4 possible "extend" settings:
    extends = ["neither", "both", "min", "max"]
    cmap = plt.cm.get_cmap("winter")
    cmap.set_under("magenta")
    cmap.set_over("yellow")
    # Note: contouring simply excludes masked or nan regions, so
    # instead of using the "bad" colormap value for them, it draws
    # nothing at all in them.  Therefore the following would have
    # no effect:
    # cmap.set_bad("red")
    
    fig, axs = plt.subplots(2, 2)
    fig.subplots_adjust(hspace=0.3)
    
    for ax, extend in zip(axs.ravel(), extends):
        cs = ax.contourf(X, Y, Z, levels, cmap=cmap, extend=extend, origin=origin)
        fig.colorbar(cs, ax=ax, shrink=0.9)
        ax.set_title("extend = %s" % extend)
        ax.locator_params(nbins=4)
    
    plt.show()
    

Keywords: python, matplotlib, pylab, example, codex (see :ref:`how-to-search-examples`)