Module: color¶
Inheritance diagram for mpltools.color:
LinearColormap¶
- class mpltools.color.LinearColormap(name, color_data, index=None, **kwargs)¶
Bases: matplotlib.colors.LinearSegmentedColormap
Create Matplotlib colormap with color values specified at key points.
This class simplifies the call signature of LinearSegmentedColormap. By default, colors specified by color_data are equally spaced along the colormap.
Parameters : name : str
Name of colormap.
color_data : list or dict
Colors at each index value. Two input types are supported:
List of RGB or RGBA tuples. For example, red and blue:
color_data = [(1, 0, 0), (0, 0, 1)]
Dict of ‘red’, ‘green’, ‘blue’, and (optionally) ‘alpha’ values. For example, the following would give a red-to-blue gradient:
color_data = {'red': [1, 0], 'green': [0, 0], 'blue': [0, 1]}
index : list of floats (0, 1)
Note that these indices must match the length of color_data. If None, colors in color_data are equally spaced in colormap.
Examples
Linear colormap going from white to red
>>> white_red = LinearColormap('white_red', [(1, 1, 1), (0.8, 0, 0)])
Colormap going from blue to white to red
>>> bwr = LinearColormap('blue_white_red', [(0.0, 0.2, 0.4), # blue ... (1.0, 1.0, 1.0), # white ... (0.4, 0.0, 0.1)]) # red
You can use a repeated index to get a segmented color. - Blue below midpoint of colormap, red above mid point. - Alpha maximum at the edges, minimum in the middle.
>>> bcr_rgba = [(0.02, 0.2, 0.4, 1), # grayish blue, opaque ... (0.02, 0.2, 0.4, 0.3), # grayish blue, transparent ... (0.4, 0.0, 0.1, 0.3), # dark red, transparent ... (0.4, 0.0, 0.1, 1)] # dark red, opaque >>> blue_clear_red = color.LinearColormap('blue_clear_red', bcr_rgba, ... index=[0, 0.5, 0.5, 1])
Methods
from_list(name, colors[, N, gamma]) Make a linear segmented colormap with name from a sequence of colors which evenly transitions from colors[0] at val=0 to colors[-1] at val=1. is_gray() set_bad([color, alpha]) Set color to be used for masked values. set_gamma(gamma) Set a new gamma value and regenerate color map. set_over([color, alpha]) Set color to be used for high out-of-range values. set_under([color, alpha]) Set color to be used for low out-of-range values. - __init__(name, color_data, index=None, **kwargs)¶
- static from_list(name, colors, N=256, gamma=1.0)¶
Make a linear segmented colormap with name from a sequence of colors which evenly transitions from colors[0] at val=0 to colors[-1] at val=1. N is the number of rgb quantization levels. Alternatively, a list of (value, color) tuples can be given to divide the range unevenly.
- is_gray()¶
- set_bad(color='k', alpha=None)¶
Set color to be used for masked values.
- set_gamma(gamma)¶
Set a new gamma value and regenerate color map.
- set_over(color='k', alpha=None)¶
Set color to be used for high out-of-range values. Requires norm.clip = False
- set_under(color='k', alpha=None)¶
Set color to be used for low out-of-range values. Requires norm.clip = False
LinearSegmentedColormap¶
- class mpltools.color.LinearSegmentedColormap(name, segmentdata, N=256, gamma=1.0)¶
Bases: matplotlib.colors.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.
Methods
from_list(name, colors[, N, gamma]) Make a linear segmented colormap with name from a sequence of colors which evenly transitions from colors[0] at val=0 to colors[-1] at val=1. is_gray() set_bad([color, alpha]) Set color to be used for masked values. set_gamma(gamma) Set a new gamma value and regenerate color map. set_over([color, alpha]) Set color to be used for high out-of-range values. set_under([color, alpha]) Set color to be used for low out-of-range values. - __init__(name, segmentdata, N=256, gamma=1.0)¶
Create color map 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 y1Hence 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.
- makeMappingArray()
- For information about making a mapping array.
- static from_list(name, colors, N=256, gamma=1.0)¶
Make a linear segmented colormap with name from a sequence of colors which evenly transitions from colors[0] at val=0 to colors[-1] at val=1. N is the number of rgb quantization levels. Alternatively, a list of (value, color) tuples can be given to divide the range unevenly.
- is_gray()¶
- set_bad(color='k', alpha=None)¶
Set color to be used for masked values.
- set_gamma(gamma)¶
Set a new gamma value and regenerate color map.
- set_over(color='k', alpha=None)¶
Set color to be used for high out-of-range values. Requires norm.clip = False
- set_under(color='k', alpha=None)¶
Set color to be used for low out-of-range values. Requires norm.clip = False
| mpltools.color.color_mapper(parameter_range) | Return color mapper, which returns color based on parameter value. |
| mpltools.color.colors_from_cmap([length, ...]) | Return color cycle from a given colormap. |
| mpltools.color.cycle_cmap([length, cmap, ...]) | Set default color cycle of matplotlib based on colormap. |
| mpltools.color.rgb_list_to_colordict(rgb_list) |
color_mapper¶
- mpltools.color.color_mapper(parameter_range, cmap=None, start=None, stop=None)[source]¶
Return color mapper, which returns color based on parameter value.
Parameters : parameter_range : tuple of floats
Minimum and maximum value of parameter.
cmap : str or colormap
A matplotlib colormap (see matplotlib.pyplot.cm) or the name of one.
start, stop: 0 <= float <= 1 :
Limit colormap to this range (start < stop 1). You should limit the range of colormaps with light values (assuming a white background).
Returns : map_color : function
Function that returns an RGBA color from a parameter value.
colors_from_cmap¶
- mpltools.color.colors_from_cmap(length=50, cmap=None, start=None, stop=None)[source]¶
Return color cycle from a given colormap.
Parameters : length : int
The number of colors in the cycle. When length is large (> ~10), it is difficult to distinguish between successive lines because successive colors are very similar.
cmap : str
Name of a matplotlib colormap (see matplotlib.pyplot.cm).
start, stop: 0 <= float <= 1 :
Limit colormap to this range (start < stop 1). You should limit the range of colormaps with light values (assuming a white background). Some colors have default start/stop values (see CMAP_RANGE).
Returns : colors : list
List of RGBA colors.
See also
cycle_cmap¶
- mpltools.color.cycle_cmap(length=50, cmap=None, start=None, stop=None, ax=None)[source]¶
Set default color cycle of matplotlib based on colormap.
Note that the default color cycle is not changed if ax parameter is set; only the axes’s color cycle will be changed.
Parameters : length : int
The number of colors in the cycle. When length is large (> ~10), it is difficult to distinguish between successive lines because successive colors are very similar.
cmap : str
Name of a matplotlib colormap (see matplotlib.pyplot.cm).
start, stop: 0 <= float <= 1 :
Limit colormap to this range (start < stop 1). You should limit the range of colormaps with light values (assuming a white background). Some colors have default start/stop values (see CMAP_RANGE).
ax : matplotlib axes
If ax is not None, then change the axes’s color cycle instead of the default color cycle.
See also
