matplotlib.colors.LinearSegmentedColormap#

class matplotlib.colors.LinearSegmentedColormap(name, segmentdata, N=256, gamma=1.0)[source]#

Bases: Colormap

Colormap objects based on lookup tables using linear segments.

The lookup table is generated using linear interpolation for each primary color, with the 0-1 domain divided into any number of segments.

Create colormap from linear mapping segments

segmentdata argument is a dictionary with a red, green and blue entries. Each entry should be a list of x, y0, y1 tuples, forming rows in a table. Entries for alpha are optional.

Example: suppose you want red to increase from 0 to 1 over the bottom half, green to do the same over the middle half, and blue over the top half. Then you would use:

cdict = {'red':   [(0.0,  0.0, 0.0),
                   (0.5,  1.0, 1.0),
                   (1.0,  1.0, 1.0)],

         'green': [(0.0,  0.0, 0.0),
                   (0.25, 0.0, 0.0),
                   (0.75, 1.0, 1.0),
                   (1.0,  1.0, 1.0)],

         'blue':  [(0.0,  0.0, 0.0),
                   (0.5,  0.0, 0.0),
                   (1.0,  1.0, 1.0)]}

Each row in the table for a given color is a sequence of x, y0, y1 tuples. In each sequence, x must increase monotonically from 0 to 1. For any input value z falling between x[i] and x[i+1], the output value of a given color will be linearly interpolated between y1[i] and y0[i+1]:

row i:   x  y0  y1
               /
              /
row i+1: x  y0  y1

Hence y0 in the first row and y1 in the last row are never used.

See also

LinearSegmentedColormap.from_list

Static method; factory function for generating a smoothly-varying LinearSegmentedColormap.

static from_list(name, colors, N=256, gamma=1.0)[source]#

Create a LinearSegmentedColormap from a list of colors.

Parameters:
namestr

The name of the colormap.

colorsarray-like of colors or array-like of (value, color)

If only colors are given, they are equidistantly mapped from the range \([0, 1]\); i.e. 0 maps to colors[0] and 1 maps to colors[-1]. If (value, color) pairs are given, the mapping is from value to color. This can be used to divide the range unevenly.

Nint

The number of rgb quantization levels.

gammafloat
resampled(lutsize)[source]#

Return a new colormap with lutsize entries.

reversed(name=None)[source]#

Return a reversed instance of the Colormap.

Parameters:
namestr, optional

The name for the reversed colormap. If None, the name is set to self.name + "_r".

Returns:
LinearSegmentedColormap

The reversed colormap.

set_gamma(gamma)[source]#

Set a new gamma value and regenerate colormap.

Examples using matplotlib.colors.LinearSegmentedColormap#

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Bar chart with gradients

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Scatter plots with a legend

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Contour Demo

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Contour Image

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Contourf Demo

Contourf Demo

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Contourf and log color scale

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Image Demo

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Image Masked

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Image Nonuniform

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Layer Images

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pcolormesh

pcolormesh

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Shading example

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Axes box aspect

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Composing Custom Legends

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Using a text as a Path

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Creating a colormap from a list of colors

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Reference for Matplotlib artists

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Dolphins

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Demo CurveLinear Grid2

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Shaded & power normalized rendering

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Manual Contour

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AGG filter

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Matplotlib logo

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Table Demo

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Plot contour (level) curves in 3D

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Plot contour (level) curves in 3D using the extend3d option

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Filled contours

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Custom hillshading in a 3D surface plot

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3D plots as subplots

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3D surface (colormap)

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3D surface with polar coordinates

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Triangular 3D contour plot

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Triangular 3D filled contour plot

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More triangular 3D surfaces

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Hillshading

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Left ventricle bullseye

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Left ventricle bullseye
MRI with EEG

MRI with EEG

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Topographic hillshading

Topographic hillshading

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Dropped spines

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Colorbar Tick Labelling

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Customized Colorbars Tutorial

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Creating Colormaps in Matplotlib

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Colormap Normalization

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3D surface

3D surface

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Triangular 3D surfaces

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