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Copy file name to clipboardExpand all lines: doc/users/colormaps.rst
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@@ -45,7 +45,7 @@ For the Sequential plots, the lightness value increases monotonically through th
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Sequential2
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Many of the :math:`L^*` values from the Sequential2 plots are monotonically increasing, but some (autumn, cool, spring, and winter) plateau or even go both up and down in :math:`L^*` space. Others (afmhot, copper, gist_heat, and hot) have kinks in the :math:`L^*` functions. Data that is being represented in a region of the colormap that is at a plateau or kink will lead to a perception of banding of the data in those values in the colormap (see [mycarta_banding]_ for an excellent example of this).
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Many of the :math:`L^*` values from the Sequential2 plots are monotonically increasing, but some (autumn, cool, spring, and winter) plateau or even go both up and down in :math:`L^*` space. Others (afmhot, copper, gist_heat, and hot) have kinks in the :math:`L^*` functions. Data that is being represented in a region of the colormap that is at a plateau or kink will lead to a perception of banding of the data in those values in the colormap (see [mycarta-banding]_ for an excellent example of this).
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Diverging
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Some of the miscellaneous colormaps have particular uses they have been created for. For example, gist_earth, ocean, and terrain all seem to be created for plotting topography (green/brown) and water depths (blue) together. We would expect to see a divergence in these colormaps, then, but multiple kinks may not be ideal, such as in gist_earth and terrain. CMRmap was created to convert well to grayscale, though it does appear to have some small kinks in :math:`L^*`. cubehelix was created to vary smoothly in both lightness 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 that the :math:`L^*` values vary widely throughout the colormap, making it a poor choice for representing data for viewers to see perceptually. See an extension on this idea at [mycarta_jet]_.
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The often-used jet colormap is included in this set of colormaps. We can see that the :math:`L^*` values vary widely throughout the colormap, making it a poor choice for representing data for viewers to see perceptually. See an extension on this idea at [mycarta-jet]_.
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.. plot:: users/plotting/colormaps/lightness.py
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:math:`L^*` function
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====================
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There are multiple approaches to finding the best function for :math:`L^*` across a colormap. Linear gives reasonable results (*e.g.*, [mycarta_banding]_, [mycarta_lablinear]_). However, the Weber-Fechner law, and more generally and recently, Stevens' Law, indicates that a logarithmic or geometric relationship might be better (see effort on this front at [mycarta_cubelaw]_).
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There are multiple approaches to finding the best function for :math:`L^*` across a colormap. Linear gives reasonable results (*e.g.*, [mycarta-banding]_, [mycarta-lablinear]_). However, the Weber-Fechner law, and more generally and recently, Stevens' Law, indicates that a logarithmic or geometric relationship might be better (see effort on this front at [mycarta-cubelaw]_).
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