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"info": {
"author": "Konstantin Tretyakov",
"author_email": "kt@ut.ee",
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"classifiers": [
"Development Status :: 4 - Beta",
"Intended Audience :: Science/Research",
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"Programming Language :: Python :: 2",
"Programming Language :: Python :: 3",
"Topic :: Scientific/Engineering :: Visualization"
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"description": "====================================================\nVenn diagram plotting routines for Python/Matplotlib\n====================================================\n\n.. image:: https://travis-ci.org/konstantint/matplotlib-venn.png?branch=master\n :target: https://travis-ci.org/konstantint/matplotlib-venn\n\nRoutines for plotting area-weighted two- and three-circle venn diagrams.\n\nInstallation\n------------\n\nThe simplest way to install the package is via ``easy_install`` or\n``pip``::\n\n $ easy_install matplotlib-venn\n\nDependencies\n------------\n\n- ``numpy``,\n- ``scipy``,\n- ``matplotlib``.\n\nUsage\n-----\nThe package provides four main functions: ``venn2``,\n``venn2_circles``, ``venn3`` and ``venn3_circles``.\n\nThe functions ``venn2`` and ``venn2_circles`` accept as their only\nrequired argument a 3-element list ``(Ab, aB, AB)`` of subset sizes,\ne.g.::\n\n venn2(subsets = (3, 2, 1))\n\nand draw a two-circle venn diagram with respective region areas. In\nthe particular example, the region, corresponding to subset ``A and\nnot B`` will be three times larger in area than the region,\ncorresponding to subset ``A and B``. Alternatively, you can simply\nprovide a list of two ``set`` or ``Counter`` (i.e. multi-set) objects instead (new in version 0.7),\ne.g.::\n\n venn2([set(['A', 'B', 'C', 'D']), set(['D', 'E', 'F'])])\n\nSimilarly, the functions ``venn3`` and ``venn3_circles`` take a\n7-element list of subset sizes ``(Abc, aBc, ABc, abC, AbC, aBC,\nABC)``, and draw a three-circle area-weighted venn\ndiagram. Alternatively, you can provide a list of three ``set`` or ``Counter`` objects\n(rather than counting sizes for all 7 subsets).\n\nThe functions ``venn2_circles`` and ``venn3_circles`` draw just the\ncircles, whereas the functions ``venn2`` and ``venn3`` draw the\ndiagrams as a collection of colored patches, annotated with text\nlabels. In addition (version 0.7+), functions ``venn2_unweighted`` and\n``venn3_unweighted`` draw the Venn diagrams without area-weighting.\n\nNote that for a three-circle venn diagram it is not in general\npossible to achieve exact correspondence between the required set\nsizes and region areas, however in most cases the picture will still\nprovide a decent indication.\n\nThe functions ``venn2_circles`` and ``venn3_circles`` return the list of ``matplotlib.patch.Circle`` objects that may be tuned further\nto your liking. The functions ``venn2`` and ``venn3`` return an object of class ``VennDiagram``,\nwhich gives access to constituent patches, text elements, and (since\nversion 0.7) the information about the centers and radii of the\ncircles.\n\nBasic Example::\n\n from matplotlib_venn import venn2\n venn2(subsets = (3, 2, 1))\n\nFor the three-circle case::\n\n from matplotlib_venn import venn3\n venn3(subsets = (1, 1, 1, 2, 1, 2, 2), set_labels = ('Set1', 'Set2', 'Set3'))\n\nA more elaborate example::\n\n from matplotlib import pyplot as plt\n import numpy as np\n from matplotlib_venn import venn3, venn3_circles\n plt.figure(figsize=(4,4))\n v = venn3(subsets=(1, 1, 1, 1, 1, 1, 1), set_labels = ('A', 'B', 'C'))\n v.get_patch_by_id('100').set_alpha(1.0)\n v.get_patch_by_id('100').set_color('white')\n v.get_label_by_id('100').set_text('Unknown')\n v.get_label_by_id('A').set_text('Set \"A\"')\n c = venn3_circles(subsets=(1, 1, 1, 1, 1, 1, 1), linestyle='dashed')\n c[0].set_lw(1.0)\n c[0].set_ls('dotted')\n plt.title(\"Sample Venn diagram\")\n plt.annotate('Unknown set', xy=v.get_label_by_id('100').get_position() - np.array([0, 0.05]), xytext=(-70,-70),\n ha='center', textcoords='offset points', bbox=dict(boxstyle='round,pad=0.5', fc='gray', alpha=0.1),\n arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=0.5',color='gray'))\n plt.show()\n\nAn example with multiple subplots (new in version 0.6)::\n\n from matplotlib_venn import venn2, venn2_circles\n figure, axes = plt.subplots(2, 2)\n venn2(subsets={'10': 1, '01': 1, '11': 1}, set_labels = ('A', 'B'), ax=axes[0][0])\n venn2_circles((1, 2, 3), ax=axes[0][1])\n venn3(subsets=(1, 1, 1, 1, 1, 1, 1), set_labels = ('A', 'B', 'C'), ax=axes[1][0])\n venn3_circles({'001': 10, '100': 20, '010': 21, '110': 13, '011': 14}, ax=axes[1][1])\n plt.show()\n\nPerhaps the most common use case is generating a Venn diagram given\nthree sets of objects::\n\n set1 = set(['A', 'B', 'C', 'D'])\n set2 = set(['B', 'C', 'D', 'E'])\n set3 = set(['C', 'D',' E', 'F', 'G'])\n\n venn3([set1, set2, set3], ('Set1', 'Set2', 'Set3'))\n plt.show()\n\n\nQuestions\n---------\n* 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.\n\n\nSee also\n--------\n\n* Report issues and submit fixes at Github:\n https://github.com/konstantint/matplotlib-venn\n \n Check out the ``DEVELOPER-README.rst`` for development-related notes.\n* Some alternative means of plotting a Venn diagram (as of\n October 2012) are reviewed in the blog post:\n http://fouryears.eu/2012/10/13/venn-diagrams-in-python/\n* The `matplotlib-subsets\n `_ package\n visualizes a hierarchy of sets as a tree of rectangles.\n* The `matplotlib_venn_wordcloud `_ package\n combines Venn diagrams with word clouds for a pretty amazing (and amusing) result.",
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