8000 Address @QuLogic's feedback · matplotlib/matplotlib@e01552c · GitHub
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Address @QuLogic's feedback
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‎doc/users/colormaps.rst‎

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@@ -109,14 +109,15 @@ These would not be good options for use as perceptual colormaps.
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Miscellaneous
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-------------
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Some of the miscellaneous colormaps have particular uses they have been created
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for. For example, gist_earth, ocean, and terrain all seem to be created for
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plotting topography (green/brown) and water depths (blue) together. We would
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expect to see a divergence in these colormaps, then, but multiple kinks may not
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be ideal, such as in gist_earth and terrain. CMRmap was created to convert well
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to grayscale, though it does appear to have some small kinks in :math:`L^*`.
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cubehelix was created to vary smoothly in both lightness and hue, but appears to
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have a small hump in the green hue area.
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Some of the miscellaneous colormaps have particular uses for which
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they have been created. For example, gist_earth, ocean, and terrain
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all seem to be created for plotting topography (green/brown) and water
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depths (blue) together. We would expect to see a divergence in these
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colormaps, then, but multiple kinks may not be ideal, such as in
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gist_earth and terrain. CMRmap was created to convert well to
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grayscale, though it does appear to have some small kinks in
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:math:`L^*`. cubehelix was created to vary smoothly in both lightness
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and hue, but appears to have a small hump in the green hue area.
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The often-used jet colormap is included in this set of colormaps. We can see
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that the :math:`L^*` values vary widely throughout the colormap, making it a
@@ -141,17 +142,18 @@ might be better (see effort on this front at [mycarta-cubelaw]_).
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Grayscale conversion
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====================
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Conversion to grayscale is important to pay attention to for printing
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publications that have color plots. If this is not paid attention to ahead of
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time, your readers may end up with indecipherable plots because the grayscale
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changes unpredictably through the colormap.
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It is important to pay attention to conversion to grayscale for color
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plots, since they may be printed on black and white printers. If not
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carefully considered, your readers may end up with indecipherable
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plots because the grayscale changes unpredictably through the
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colormap.
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Conversion to grayscale is done in many different ways [bw]_. Some of the better
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ones use a linear combination of the rgb values of a pixel, but weighted
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according to how we perceive color intensity. A nonlinear method of conversion
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to grayscale is to use the :math:`L^*` values of the pixels. In general, similar
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principles apply for this question as they do for presenting one's information
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perceptually; that is, if a colormap is chosen that has monotonically increasing
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perceptually; that is, if a colormap is chosen that is monotonically increasing
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in :math:`L^*` values, it will print in a reasonable manner to grayscale.
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With this in mind, we see that the Sequential colormaps have reasonable

‎doc/users/plotting/colormaps/Lfunction.py‎

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@@ -7,15 +7,16 @@
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import matplotlib.pyplot as plt
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import colorconv as color
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#from skimage import color
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# we are using a local copy of colorconv from scikit-image to reduce dependencies.
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# You should probably use the one from scikit-image in most cases.
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# we are using a local copy of colorconv from scikit-image to reduce dependencies.
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# You should probably use the one from scikit-image in most cases.
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import matplotlib as mpl
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from matplotlib import cm
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mpl.rcParams.update({'font.size': 12})
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mpl.rcParams['font.sans-serif'] = ('Arev Sans, Bitstream Vera Sans,'
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'Lucida Grande, Verdana, Geneva, Lucid, Helvetica, Avant Garde, sans-serif')
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mpl.rcParams['font.sans-serif'] = ('Arev Sans, Bitstream Vera Sans, '
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'Lucida Grande, Verdana, Geneva, Lucid, '
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'Helvetica, Avant Garde, sans-serif')
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mpl.rcParams['mathtext.fontset'] = 'custom'
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mpl.rcParams['mathtext.cal'] = 'cursive'
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mpl.rcParams['mathtext.rm'] = 'sans'
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# common ylabel
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ax1.text(-0.3, 4.5, 'Steps through map indices',
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rotation=90, transform=ax1.transAxes)
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rotation=90, transform=ax1.transAxes)
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fig.subplots_adjust(hspace=0.0)
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plt.show()

‎doc/users/plotting/colormaps/grayscale.py‎

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import matplotlib as mpl
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mpl.rcParams.update({'font.size': 14})
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mpl.rcParams['font.sans-serif'] = ('Arev Sans, Bitstream Vera Sans,'
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'Lucida Grande, Verdana, Geneva, Lucid, Helvetica, Avant Garde, sans-serif')
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mpl.rcParams['font.sans-serif'] = ('Arev Sans, Bitstream Vera Sans, '
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'Lucida Grande, Verdana, Geneva, Lucid, '
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'Helvetica, Avant Garde, sans-serif')
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mpl.rcParams['mathtext.fontset'] = 'custom'
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mpl.rcParams['mathtext.cal'] = 'cursive'
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mpl.rcParams['mathtext.rm'] = 'sans'

‎doc/users/plotting/colormaps/lightness.py‎

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import matplotlib as mpl
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mpl.rcParams.update({'font.size': 12})
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mpl.rcParams['font.sans-serif'] = ('Arev Sans, Bitstream Vera Sans,'
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'Lucida Grande, Verdana, Geneva, Lucid, Helvetica, Avant Garde, sans-serif')
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mpl.rcParams['font.sans-serif'] = ('Arev Sans, Bitstream Vera Sans, '
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'Lucida Grande, Verdana, Geneva, Lucid, '
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'Helvetica, Avant Garde, sans-serif')
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mpl.rcParams['mathtext.fontset'] = 'custom'
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mpl.rcParams['mathtext.cal'] = 'cursive'
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mpl.rcParams['mathtext.rm'] = 'sans'

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