48 lines
1.3 KiB
Python
Executable file
48 lines
1.3 KiB
Python
Executable file
'''
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Demonstrate use of a log color scale in contourf
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'''
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from matplotlib import pyplot as P
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import numpy as np
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from numpy import ma
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from matplotlib import colors, ticker
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from matplotlib.mlab import bivariate_normal
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N = 100
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x = np.linspace(-3.0, 3.0, N)
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y = np.linspace(-2.0, 2.0, N)
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X, Y = np.meshgrid(x, y)
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# A low hump with a spike coming out of the top right.
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# Needs to have z/colour axis on a log scale so we see both hump and spike.
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# linear scale only shows the spike.
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z = (bivariate_normal(X, Y, 0.1, 0.2, 1.0, 1.0)
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+ 0.1 * bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0))
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# Put in some negative values (lower left corner) to cause trouble with logs:
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z[:5, :5] = -1
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# The following is not strictly essential, but it will eliminate
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# a warning. Comment it out to see the warning.
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z = ma.masked_where(z<= 0, z)
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# Automatic selection of levels works; setting the
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# log locator tells contourf to use a log scale:
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cs = P.contourf(X, Y, z, locator=ticker.LogLocator())
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# Alternatively, you can manually set the levels
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# and the norm:
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#lev_exp = np.arange(np.floor(np.log10(z.min())-1),
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# np.ceil(np.log10(z.max())+1))
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#levs = np.power(10, lev_exp)
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#cs = P.contourf(X, Y, z, levs, norm=colors.LogNorm())
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#The 'extend' kwarg does not work yet with a log scale.
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cbar = P.colorbar()
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P.show()
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