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Copy file name to clipboardExpand all lines: doc/users/colormaps.rst
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@@ -13,8 +13,12 @@ colorspace for your data set. The best colormap for any given data set depends
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on many things including:
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- Whether representing form or metric data ([Ware]_)
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- Your knowledge of the data set (*e.g.*, is there a critical value from which the other values deviate?)
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- Your knowledge of the data set (*e.g.*, is there a critical value
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from which the other values deviate?)
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- If there is an intuitive color scheme for the parameter you are plotting
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- If there is a standard in the field the audience may be expecting
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For many applications, a perceptually uniform colormap is the best
@@ -41,9 +45,19 @@ Classes of colormaps
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Colormaps are often split into several categories based on their function (see,
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*e.g.*, [Moreland]_):
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1. Sequential: change in lightness and often saturation of color incrementally, often using a single hue; should be used for representing information that has ordering.
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2. Diverging: change in lightness and possibly saturation of two different colors that meet in the middle at an unsaturated color; should be used when the information being plotted has a critical middle value, such as topography or when the data deviates around zero.
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3. Qualitative: often are miscellaneous colors; should be used to represent information which does not have ordering or relationships.
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1. Sequential: change in lightness and often saturation of color
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incrementally, often using a single hue; should be used for
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representing information that has ordering.
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2. Diverging: change in lightness and possibly saturation of two
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different colors that meet in the middle at an unsaturated color;
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should be used when the information being plotted has a critical
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middle value, such as topography or when the data deviates around
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zero.
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3. Qualitative: often are miscellaneous colors; should be used to
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represent information which does not have ordering or
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