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matplotlib-venn 0.6

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

Latest Version: 0.9

Routines for plotting area-weighted two- and three-circle venn diagrams.

Important changes in version 0.3

As the use of package name matplotlib.venn was causing occasional conflicts with matplotlib, in version 0.3, the package name was changed to matplotlib_venn. I.e., if in version 0.2 you had to do things like:

from matplotlib.venn import venn3

now the correct way is:

from matplotlib_venn import venn3

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.

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.

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.

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 Venn2 or Venn3 respectively, which gives access to constituent patches and text elements.

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):

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])

Perhaps the most common use case is generating a Venn diagram given three sets of objects. To do that you will first need to count set sizes. Here's one possible way to do it:

# Given three sets ...
set1 = set(['A', 'B', 'C', 'D'])
set2 = set(['B', 'C', 'D', 'E'])
set3 = set(['C', 'D',' E', 'F', 'G'])

# Compute the union of all elements
union = set1.union(set2).union(set3)

# For each element compute its 'indicator'
# (e.g. an indicator of 110 means element belongs to set1 and set2 but not set3)
indicators = ['%d%d%d' % (a in set1, a in set2, a in set3) for a in union]

# Use the standard Counter object (Python 2.7+) to count the frequency for each indicator
from collections import Counter
subsets = Counter(indicators)

# Provide the resulting dictionary as the subsets parameter to venn3:
venn3(subsets, ('Set1', 'Set2', 'Set3'))
 
File Type Py Version Uploaded on Size
matplotlib-venn-0.6.zip (md5) Source 2013-06-17 25KB
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