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# Contour Label Demo

Illustrate some of the more advanced things that one can do with contour labels.

See also contour_demo.py.

    import matplotlib
    import numpy as np
    import matplotlib.cm as cm
    import matplotlib.mlab as mlab
    import matplotlib.ticker as ticker
    import matplotlib.pyplot as plt

    matplotlib.rcParams['xtick.direction'] = 'out'
    matplotlib.rcParams['ytick.direction'] = 'out'

Define our surface

    delta = 0.025
    x = np.arange(-3.0, 3.0, delta)
    y = np.arange(-2.0, 2.0, delta)
    X, Y = np.meshgrid(x, y)
    Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
    Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
    # difference of Gaussians
    Z = 10.0 * (Z2 - Z1)

Make contour labels using creative float classes Follows suggestion of Manuel Metz

    plt.figure()

    # Basic contour plot
    CS = plt.contour(X, Y, Z)

    # Define a class that forces representation of float to look a certain way
    # This remove trailing zero so '1.0' becomes '1'
    class nf(float):
        def __repr__(self):
            str = '%.1f' % (self.__float__(),)
            if str[-1] == '0':
                return '%.0f' % self.__float__()
            else:
                return '%.1f' % self.__float__()

    # Recast levels to new class
    CS.levels = [nf(val) for val in CS.levels]

    # Label levels with specially formatted floats
    if plt.rcParams["text.usetex"]:
        fmt = r'%r \%%'
    else:
        fmt = '%r %%'
    plt.clabel(CS, CS.levels, inline=True, fmt=fmt, fontsize=10)

Label contours with arbitrary strings using a dictionary

    plt.figure()

    # Basic contour plot
    CS = plt.contour(X, Y, Z)

    fmt = {}
    strs = ['first', 'second', 'third', 'fourth', 'fifth', 'sixth', 'seventh']
    for l, s in zip(CS.levels, strs):
        fmt[l] = s

    # Label every other level using strings
    plt.clabel(CS, CS.levels[::2], inline=True, fmt=fmt, fontsize=10)

    # Use a Formatter

    plt.figure()

    CS = plt.contour(X, Y, 100**Z, locator=plt.LogLocator())
    fmt = ticker.LogFormatterMathtext()
    fmt.create_dummy_axis()
    plt.clabel(CS, CS.levels, fmt=fmt)
    plt.title("$100^Z$")

    plt.show()

Total running time of the script: ( 0 minutes 0.257 seconds)

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