matplotlib.colors.LinearSegmentedColormap#

classmatplotlib.colors.LinearSegmentedColormap(name,segmentdata,N=256,gamma=1.0,*,bad=None,under=None,over=None)[source]#

Bases:Colormap

Colormap objects based on lookup tables using linear segments.

The lookup table is generated using linear interpolation for eachprimary color, with the 0-1 domain divided into any number ofsegments.

Create colormap from linear mapping segments.

Parameters:
namestr

The name of the colormap.

segmentdatadict

A dictionary with keys "red", "green", "blue" for the color channels.Each entry should be a list ofx,y0,y1 tuples, forming rowsin a table. Entries for alpha are optional.

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

{'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 ofx,y0,y1 tuples. In each sequence,x must increasemonotonically from 0 to 1. For any input valuez fallingbetweenx[i] andx[i+1], the output value of a given colorwill be linearly interpolated betweeny1[i] andy0[i+1]:

rowi:xy0y1//rowi+1:xy0y1

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

Nint

The number of RGB quantization levels.

gammafloat

Gamma correction factor for input distribution x of the mapping.See alsohttps://en.wikipedia.org/wiki/Gamma_correction.

badcolor, default: transparent

The color for invalid values (NaN or masked).

Added in version 3.11.

undercolor, default: color of the lowest value

The color for low out-of-range values.

Added in version 3.11.

overcolor, default: color of the highest value

The color for high out-of-range values.

Added in version 3.11.

See also

LinearSegmentedColormap.from_list

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

staticfrom_list(name,colors,N=256,gamma=1.0,*,bad=None,under=None,over=None)[source]#

Create aLinearSegmentedColormap from a list of colors.

Parameters:
namestr

The name of the colormap.

colorslist ofcolor or list of (value, color)

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

Nint

The number of RGB quantization levels.

gammafloat
badcolor, default: transparent

The color for invalid values (NaN or masked).

undercolor, default: color of the lowest value

The color for low out-of-range values.

overcolor, default: color of the highest value

The color for high out-of-range values.

resampled(lutsize)[source]#

Return a new colormap withlutsize entries.

reversed(name=None)[source]#

Return a reversed instance of the Colormap.

Parameters:
namestr, optional

The name for the reversed colormap. If None, thename is set toself.name+"_r".

Returns:
LinearSegmentedColormap

The reversed colormap.

set_gamma(gamma)[source]#

Set a new gamma value and regenerate colormap.

Examples usingmatplotlib.colors.LinearSegmentedColormap#

Histogram as colorbar

Histogram as colorbar

Create a colormap from a list of colors

Create a colormap from a list of colors

Contour image

Contour image

Contourf demo

Contourf demo

Image resampling

Image resampling

Image with masked values

Image with masked values

pcolormesh

pcolormesh

Matplotlib logo

Matplotlib logo

Hatchcolor Demo

Hatchcolor Demo

Left ventricle bullseye

Left ventricle bullseye

Topographic hillshading

Topographic hillshading

Compose custom legends

Compose custom legends

Creating Colormaps in Matplotlib

Creating Colormaps in Matplotlib

Colormap normalization

Colormap normalization