Functions for plotting area-proportional two- and three-way Venn diagrams in matplotlib.

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 and tag them 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 package visualizes a hierarchy of sets as a tree of rectangles.

The matplotlib_venn_wordcloud package combines Venn diagrams with word clouds for a pretty amazing (and amusing) result.

## Download Files

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File Name & Checksum SHA256 Checksum Help | Version | File Type | Upload Date |
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matplotlib-venn-0.11.5.zip (40.4 kB) Copy SHA256 Checksum SHA256 | – | Source | Jan 14, 2017 |