Area-weighted venn-diagrams for Python/matplotlib

Overview

Venn diagram plotting routines for Python/Matplotlib

https://travis-ci.org/konstantint/matplotlib-venn.png?branch=master

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

Owner
Konstantin Tretyakov
Konstantin Tretyakov
Some problems of SSLC ( High School ) before outputs and after outputs

Some problems of SSLC ( High School ) before outputs and after outputs 1] A Python program and its output (output1) while running the program is given

Fayas Noushad 3 Dec 01, 2021
Generate a 3D Skyline in STL format and a OpenSCAD file from Gitlab contributions

Your Gitlab's contributions in a 3D Skyline gitlab-skyline is a Python command to generate a skyline figure from Gitlab contributions as Github did at

Félix Gómez 70 Dec 22, 2022
A python-generated website for visualizing the novel coronavirus (COVID-19) data for Greece.

COVID-19-Greece A python-generated website for visualizing the novel coronavirus (COVID-19) data for Greece. Data sources Data provided by Johns Hopki

Isabelle Viktoria Maciohsek 23 Jan 03, 2023
A workshop on data visualization in Python with notebooks and exercises for following along.

Beyond the Basics: Data Visualization in Python The human brain excels at finding patterns in visual representations, which is why data visualizations

Stefanie Molin 162 Dec 05, 2022
Designed a greedy algorithm based on Markov sequential decision-making process in MATLAB/Python to optimize using Gurobi solver

Designed a greedy algorithm based on Markov sequential decision-making process in MATLAB/Python to optimize using Gurobi solver, the wheel size, gear shifting sequence by modeling drivetrain constrai

Sabbella Prasanna 1 Jan 11, 2022
DALLE-tools provided useful dataset utilities to improve you workflow with WebDatasets.

DALLE tools DALLE-tools is a github repository with useful tools to categorize, annotate or check the sanity of your datasets. Installation Just clone

11 Dec 25, 2022
Scientific measurement library for instruments, experiments, and live-plotting

PyMeasure scientific package PyMeasure makes scientific measurements easy to set up and run. The package contains a repository of instrument classes a

PyMeasure 445 Jan 04, 2023
🐍PyNode Next allows you to easily create beautiful graph visualisations and animations

PyNode Next A complete rewrite of PyNode for the modern era. Up to five times faster than the original PyNode. PyNode Next allows you to easily create

ehne 3 Feb 12, 2022
Easily configurable, chart dashboards from any arbitrary API endpoint. JSON config only

Flask JSONDash Easily configurable, chart dashboards from any arbitrary API endpoint. JSON config only. Ready to go. This project is a flask blueprint

Chris Tabor 3.3k Dec 31, 2022
VDLdraw - Batch plot the log files exported from VisualDL using Matplotlib

VDLdraw Batch plot the log files exported from VisualDL using Matplotlib. At pre

Yizhou Chen 5 Sep 26, 2022
BrowZen correlates your emotional states with the web sites you visit to give you actionable insights about how you spend your time browsing the web.

BrowZen BrowZen correlates your emotional states with the web sites you visit to give you actionable insights about how you spend your time browsing t

Nick Bild 36 Sep 28, 2022
Regress.me is an easy to use data visualization tool powered by Dash/Plotly.

Regress.me Regress.me is an easy to use data visualization tool powered by Dash/Plotly. Regress.me.-.Google.Chrome.2022-05-10.15-58-59.mp4 Get Started

Amar 14 Aug 14, 2022
Uniform Manifold Approximation and Projection

UMAP Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, bu

Leland McInnes 6k Jan 08, 2023
A simple python tool for explore your object detection dataset

A simple tool for explore your object detection dataset. The goal of this library is to provide simple and intuitive visualizations from your dataset and automatically find the best parameters for ge

GRADIANT - Centro Tecnolóxico de Telecomunicacións de Galicia 142 Dec 25, 2022
JSNAPY example: Validate NAT policies

JSNAPY example: Validate NAT policies Overview This example will show how to use JSNAPy to make sure the expected NAT policy matches are taking place.

Calvin Remsburg 1 Jan 07, 2022
basemap - Plot on map projections (with coastlines and political boundaries) using matplotlib.

Basemap Plot on map projections (with coastlines and political boundaries) using matplotlib. ⚠️ Warning: this package is being deprecated in favour of

Matplotlib Developers 706 Dec 28, 2022
Rick and Morty Data Visualization with python

Rick and Morty Data Visualization For this project I looked at data for the TV show Rick and Morty Number of Episodes at a Certain Location Here is th

7 Aug 29, 2022
The plottify package is makes matplotlib plots more legible

plottify The plottify package is makes matplotlib plots more legible. It's a thin wrapper around matplotlib that automatically adjusts font sizes, sca

Andy Jones 97 Nov 04, 2022
An interactive UMAP visualization of the MNIST data set.

Code for an interactive UMAP visualization of the MNIST data set. Demo at https://grantcuster.github.io/umap-explorer/. You can read more about the de

grant 70 Dec 27, 2022
A minimal Python package that produces slice plots through h5m DAGMC geometry files

A minimal Python package that produces slice plots through h5m DAGMC geometry files Installation pip install dagmc_geometry_slice_plotter Python API U

Fusion Energy 4 Dec 02, 2022