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case).
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Matplotlib does this mapping in two steps, with a normalization from
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- [0, 1] occurring first, and then mapping onto the indices in the
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- colormap. Normalizations are classes defined in the
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- :func:`matplotlib.colors` module. The default, linear normalization is
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- :func:`matplotlib.colors.Normalize`.
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+ the input data to [0, 1] occurring first, and then mapping onto the
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+ indices in the colormap. Normalizations are classes defined in the
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+ :func:`matplotlib.colors` module. The default, linear normalization
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+ is :func:`matplotlib.colors.Normalize`.
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Artists that map data to color pass the arguments *vmin* and *vmax* to
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construct a :func:`matplotlib.colors.Normalize` instance, then call it:
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:math:`log_{10}`. In the example below, there are two bumps, one much smaller
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than the other. Using `.colors.LogNorm`, the shape and location of each bump
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can clearly be seen:
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"""
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import numpy as np
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import matplotlib .pyplot as plt
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