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Artist for matplotlib to display a color bar

Project description

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Provides a new artist for matplotlib to display a colorbar, instead of an axis as it is the default in matplotlib. The position of the colorbar artist can be decided as for the legend.

https://raw.githubusercontent.com/ppinard/matplotlib-colorbar/master/doc/example1.png

The artist supports customization either directly from the Colorbar object or from the matplotlibrc.

Installation

Easiest way to install using pip:

$ pip install matplotlib-colorbar

For development installation from the git repository:

$ git clone git@github.com:ppinard/matplotlib-colorbar.git
$ pip install -e matplotlib-colorbar

Example

Here is an example how to add a color bar:

>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> import matplotlib.cbook as cbook
>>> from matplotlib_colorbar.colorbar import Colorbar
>>> plt.figure()
>>> data = np.array(plt.imread(cbook.get_sample_data('grace_hopper.png')))
>>> mappable = plt.imshow(data[...,0], cmap='viridis')
>>> colorbar = Colorbar(mappable, location='lower left')
>>> colorbar.set_ticks([0.0, 0.5, 1.0])
>>> plt.gca().add_artist(colorbar)
>>> plt.show()

Colorbar arguments

Here are parameters of the Colorbar class constructor.

  • mappable: scalar mappable object which implements the methods get_cmap and get_array (default: None, the mappable can be specified later)
  • label: label on top of the color bar (default: None, no label is shown)
  • orientation: orientation, vertical or horizontal (default: vertical)
  • length_fraction: length of the color bar as a fraction of the axes’s width (horizontal) or height (vertical) depending on the orientation (default: 0.2)
  • width_fraction: width of the color bar as a fraction of the axes’s height (horizontal) or width (vertical) depending on the orientation (default: 0.02)
  • location: a location code (same as legend) (default: upper right)
  • pad: fraction of the font size (default: 0.2)
  • border_pad: fraction of the font size (default: 0.1)
  • sep: separation between color bar and label in points (default: 5)
  • frameon: if True, will draw a box around the color bar (default: True)
  • color: color for the tick text and label (default: k)
  • box_color: color of the box (if frameon) (default: w)
  • box_alpha: transparency of box (default: 1.0)
  • font_properties: font properties of the label text, specified either as dict or fontconfig pattern (XML).
  • ticks: ticks location (default: minimal and maximal values)
  • ticklabels: a list of tick labels (same length as ticks argument)
  • ticklocation: location of the ticks: left or right for vertical oriented colorbar, bottom or top for horizontal oriented colorbar, or ``auto for automatic adjustment (right for vertical and bottom for horizontal oriented colorbar). (default: auto)

matplotlibrc parameters

Here are parameters that can be customized in the matplotlibrc file.

  • orientation: orientation, vertical or horizontal (default: vertical)
  • length_fraction: length of the color bar as a fraction of the axes’s width (horizontal) or height (vertical) depending on the orientation (default: 0.2)
  • width_fraction: width of the color bar as a fraction of the axes’s height (horizontal) or width (vertical) depending on the orientation (default: 0.02)
  • location: a location code (same as legend) (default: upper right)
  • pad: fraction of the font size (default: 0.2)
  • border_pad: fraction of the font size (default: 0.1)
  • sep: separation between color bar and label in points (default: 5)
  • frameon: if True, will draw a box around the color bar (default: True)
  • color: color for the tick text and label (default: k)
  • box_color: color of the box (if frameon) (default: w)
  • box_alpha: transparency of box (default: 1.0)
  • ticklocation: location of the ticks (default: auto)

Release notes

0.3.6

  • Fix deprecated usage of is_string_like

0.3.5

  • Fix: UserWarning This call to matplotlib.use() has no effect (#9)

Contributors

@cphyc and @jnth

License

License under the BSD License, compatible with matplotlib.

Copyright (c) 2015-2017 Philippe Pinard

Project details


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