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Metadata-Version: 1.1
Name: matplotlib-venn
Version: 0.11.5
Summary: Functions for plotting area-proportional two- and three-way Venn diagrams in matplotlib.
Home-page: https://github.com/konstantint/matplotlib-venn
Author: Konstantin Tretyakov
Author-email: kt@ut.ee
License: MIT
Description: ====================================================
Venn diagram plotting routines for Python/Matplotlib
====================================================
.. image:: https://travis-ci.org/konstantint/matplotlib-venn.png?branch=master
:target: https://travis-ci.org/konstantint/matplotlib-venn
Routines for plotting area-weighted two- and three-circle venn diagrams.
Installation
------------
The simplest way to install the package is via ``easy_install`` or
``pip``::
$ easy_install matplotlib-venn
Dependencies
------------
- ``numpy``,
- ``scipy``,
- ``matplotlib``.
Usage
-----
The package provides four main functions: ``venn2``,
``venn2_circles``, ``venn3`` and ``venn3_circles``.
The functions ``venn2`` and ``venn2_circles`` accept as their only
required argument a 3-element list ``(Ab, aB, AB)`` of subset sizes,
e.g.::
venn2(subsets = (3, 2, 1))
and draw a two-circle venn diagram with respective region areas. In
the particular example, the region, corresponding to subset ``A and
not B`` will be three times larger in area than the region,
corresponding to subset ``A and B``. Alternatively, you can simply
provide a list of two ``set`` or ``Counter`` (i.e. multi-set) objects instead (new in version 0.7),
e.g.::
venn2([set(['A', 'B', 'C', 'D']), set(['D', 'E', 'F'])])
Similarly, the functions ``venn3`` and ``venn3_circles`` take a
7-element list of subset sizes ``(Abc, aBc, ABc, abC, AbC, aBC,
ABC)``, and draw a three-circle area-weighted venn
diagram. Alternatively, you can provide a list of three ``set`` or ``Counter`` objects
(rather than counting sizes for all 7 subsets).
The functions ``venn2_circles`` and ``venn3_circles`` draw just the
circles, whereas the functions ``venn2`` and ``venn3`` draw the
diagrams as a collection of colored patches, annotated with text
labels. In addition (version 0.7+), functions ``venn2_unweighted`` and
``venn3_unweighted`` draw the Venn diagrams without area-weighting.
Note that for a three-circle venn diagram it is not in general
possible to achieve exact correspondence between the required set
sizes and region areas, however in most cases the picture will still
provide a decent indication.
The functions ``venn2_circles`` and ``venn3_circles`` return the list of ``matplotlib.patch.Circle`` objects that may be tuned further
to your liking. The functions ``venn2`` and ``venn3`` return an object of class ``VennDiagram``,
which gives access to constituent patches, text elements, and (since
version 0.7) the information about the centers and radii of the
circles.
Basic Example::
from matplotlib_venn import venn2
venn2(subsets = (3, 2, 1))
For the three-circle case::
from matplotlib_venn import venn3
venn3(subsets = (1, 1, 1, 2, 1, 2, 2), set_labels = ('Set1', 'Set2', 'Set3'))
A more elaborate example::
from matplotlib import pyplot as plt
import numpy as np
from matplotlib_venn import venn3, venn3_circles
plt.figure(figsize=(4,4))
v = venn3(subsets=(1, 1, 1, 1, 1, 1, 1), set_labels = ('A', 'B', 'C'))
v.get_patch_by_id('100').set_alpha(1.0)
v.get_patch_by_id('100').set_color('white')
v.get_label_by_id('100').set_text('Unknown')
v.get_label_by_id('A').set_text('Set "A"')
c = venn3_circles(subsets=(1, 1, 1, 1, 1, 1, 1), linestyle='dashed')
c[0].set_lw(1.0)
c[0].set_ls('dotted')
plt.title("Sample Venn diagram")
plt.annotate('Unknown set', xy=v.get_label_by_id('100').get_position() - np.array([0, 0.05]), xytext=(-70,-70),
ha='center', textcoords='offset points', bbox=dict(boxstyle='round,pad=0.5', fc='gray', alpha=0.1),
arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=0.5',color='gray'))
plt.show()
An example with multiple subplots (new in version 0.6)::
from matplotlib_venn import venn2, venn2_circles
figure, axes = plt.subplots(2, 2)
venn2(subsets={'10': 1, '01': 1, '11': 1}, set_labels = ('A', 'B'), ax=axes[0][0])
venn2_circles((1, 2, 3), ax=axes[0][1])
venn3(subsets=(1, 1, 1, 1, 1, 1, 1), set_labels = ('A', 'B', 'C'), ax=axes[1][0])
venn3_circles({'001': 10, '100': 20, '010': 21, '110': 13, '011': 14}, ax=axes[1][1])
plt.show()
Perhaps the most common use case is generating a Venn diagram given
three sets of objects::
set1 = set(['A', 'B', 'C', 'D'])
set2 = set(['B', 'C', 'D', 'E'])
set3 = set(['C', 'D',' E', 'F', 'G'])
venn3([set1, set2, set3], ('Set1', 'Set2', 'Set3'))
plt.show()
Questions
---------
* If you ask your questions at `StackOverflow <http://stackoverflow.com/>`_ and tag them `matplotlib-venn <http://stackoverflow.com/questions/tagged/matplotlib-venn>`_, chances are high you'll get an answer from the maintainer of this package.
See also
--------
* Report issues and submit fixes at Github:
https://github.com/konstantint/matplotlib-venn
Check out the ``DEVELOPER-README.rst`` for development-related notes.
* Some alternative means of plotting a Venn diagram (as of
October 2012) are reviewed in the blog post:
http://fouryears.eu/2012/10/13/venn-diagrams-in-python/
* The `matplotlib-subsets
<https://pypi.python.org/pypi/matplotlib-subsets>`_ package
visualizes a hierarchy of sets as a tree of rectangles.
Keywords: matplotlib plotting charts venn-diagrams
Platform: Platform Independent
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Visualization
|
