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Showing content from http://matplotlib.org/mpl-probscale/ below:

Real probability scales for matplotlib — probscale 0.2.3 documentation

https://github.com/matplotlib/mpl-probscale

Official releases are available through the conda-forge channel or pip:

conda install mpl-probscale --channel=conda-forge

or

pip install probscale

This is a pure-python package, so building from source is easy on all platforms:

git clone [email protected]:matplotlib/mpl-probscale.git
cd mpl-probscale
pip install -e .

Simply importing probscale lets you use probability scales in your matplotlib figures:

import matplotlib.pyplot as plt
import probscale
import seaborn
clear_bkgd = {'axes.facecolor':'none', 'figure.facecolor':'none'}
seaborn.set(style='ticks', context='notebook', rc=clear_bkgd)

fig, ax = plt.subplots(figsize=(8, 4))
ax.set_ylim(1e-2, 1e2)
ax.set_yscale('log')

ax.set_xlim(0.5, 99.5)
ax.set_xscale('prob')
seaborn.despine(fig=fig)

It’s easiest to run the tests from an interactive python session:

import matplotlib
matplotlib.use('agg')
import probscale
probscale.test()

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