New Upstream Snapshot - python-matplotlib-venn
Ready changes
Summary
Merged new upstream version: 0.11.7 (was: 0.11.6).
Resulting package
Built on 2022-04-17T19:17 (took 4m38s)
The resulting binary packages can be installed (if you have the apt repository enabled) by running one of:
apt install -t fresh-snapshots python3-matplotlib-venn
Lintian Result
Diff
diff --git a/CHANGELOG.txt b/CHANGELOG.txt
index 9cc10cf..626bd94 100644
--- a/CHANGELOG.txt
+++ b/CHANGELOG.txt
@@ -1,3 +1,8 @@
+Version 0.11.7
+--------------
+
+ - Fixed Travis-CI-related error messages.
+
Version 0.11.6
--------------
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000..6ed986a
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,7 @@
+Copyright (c) 2012, Konstantin Tretyakov
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
\ No newline at end of file
diff --git a/PKG-INFO b/PKG-INFO
index ea8ffe8..2ba6379 100644
--- a/PKG-INFO
+++ b/PKG-INFO
@@ -1,149 +1,11 @@
-Metadata-Version: 1.1
+Metadata-Version: 2.1
Name: matplotlib-venn
-Version: 0.11.6
+Version: 0.11.7
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.
- * The `matplotlib_venn_wordcloud <https://pypi.python.org/pypi/matplotlib_venn_wordcloud>`_ package
- combines Venn diagrams with word clouds for a pretty amazing (and amusing) result.
Keywords: matplotlib plotting charts venn-diagrams
Platform: Platform Independent
Classifier: Development Status :: 4 - Beta
@@ -153,3 +15,144 @@ Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Visualization
+License-File: LICENSE
+
+====================================================
+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.
+* The `matplotlib_venn_wordcloud <https://pypi.python.org/pypi/matplotlib_venn_wordcloud>`_ package
+ combines Venn diagrams with word clouds for a pretty amazing (and amusing) result.
+
diff --git a/debian/changelog b/debian/changelog
index a78cded..66147b9 100644
--- a/debian/changelog
+++ b/debian/changelog
@@ -1,3 +1,10 @@
+python-matplotlib-venn (0.11.7-1) UNRELEASED; urgency=low
+
+ * New upstream release.
+ * Drop patch fix_build_time_test.patch, present upstream.
+
+ -- Debian Janitor <janitor@jelmer.uk> Sun, 17 Apr 2022 19:14:51 -0000
+
python-matplotlib-venn (0.11.6-3) unstable; urgency=medium
* Move package to Debian Python Team
diff --git a/debian/patches/fix_build_time_test.patch b/debian/patches/fix_build_time_test.patch
deleted file mode 100644
index e7f9678..0000000
--- a/debian/patches/fix_build_time_test.patch
+++ /dev/null
@@ -1,16 +0,0 @@
-Description: Fix build time test
-Bug-Debian: https://bugs.debian.org/884040
-Author: Andreas Tille <tille@debian.org>
-Last-Update: Mon, 11 Dec 2017 09:07:00 +0100
-
---- a/setup.cfg
-+++ b/setup.cfg
-@@ -3,7 +3,7 @@
- tag_svn_revision = false
- tag_date = 0
-
--[pytest]
-+[tool:pytest]
- addopts = --ignore=setup.py --ignore=build --ignore=dist --doctest-modules
- norecursedirs = *.egg
-
diff --git a/debian/patches/numpy_1.14.patch b/debian/patches/numpy_1.14.patch
index 8e0f699..71dfd88 100644
--- a/debian/patches/numpy_1.14.patch
+++ b/debian/patches/numpy_1.14.patch
@@ -7,9 +7,11 @@ Bug-Debian: https://bugs.debian.org/902516
Author: Andreas Tille <tille@debian.org>
Last-Update: Fri, 06 Jul 2018 02:51:00 +1000
---- a/matplotlib_venn/_venn2.py
-+++ b/matplotlib_venn/_venn2.py
-@@ -14,6 +14,12 @@
+Index: python-matplotlib-venn/matplotlib_venn/_venn2.py
+===================================================================
+--- python-matplotlib-venn.orig/matplotlib_venn/_venn2.py
++++ python-matplotlib-venn/matplotlib_venn/_venn2.py
+@@ -14,6 +14,12 @@ if 'py.test' in os.path.basename(sys.arg
matplotlib.use('Agg')
import numpy as np
diff --git a/debian/patches/series b/debian/patches/series
index bea0cf5..cb77ecc 100644
--- a/debian/patches/series
+++ b/debian/patches/series
@@ -1,2 +1 @@
-fix_build_time_test.patch
numpy_1.14.patch
diff --git a/matplotlib_venn.egg-info/PKG-INFO b/matplotlib_venn.egg-info/PKG-INFO
index ea8ffe8..2ba6379 100644
--- a/matplotlib_venn.egg-info/PKG-INFO
+++ b/matplotlib_venn.egg-info/PKG-INFO
@@ -1,149 +1,11 @@
-Metadata-Version: 1.1
+Metadata-Version: 2.1
Name: matplotlib-venn
-Version: 0.11.6
+Version: 0.11.7
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.
- * The `matplotlib_venn_wordcloud <https://pypi.python.org/pypi/matplotlib_venn_wordcloud>`_ package
- combines Venn diagrams with word clouds for a pretty amazing (and amusing) result.
Keywords: matplotlib plotting charts venn-diagrams
Platform: Platform Independent
Classifier: Development Status :: 4 - Beta
@@ -153,3 +15,144 @@ Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Visualization
+License-File: LICENSE
+
+====================================================
+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.
+* The `matplotlib_venn_wordcloud <https://pypi.python.org/pypi/matplotlib_venn_wordcloud>`_ package
+ combines Venn diagrams with word clouds for a pretty amazing (and amusing) result.
+
diff --git a/matplotlib_venn.egg-info/SOURCES.txt b/matplotlib_venn.egg-info/SOURCES.txt
index cb41023..fbe17a6 100644
--- a/matplotlib_venn.egg-info/SOURCES.txt
+++ b/matplotlib_venn.egg-info/SOURCES.txt
@@ -1,4 +1,5 @@
CHANGELOG.txt
+LICENSE
MANIFEST.in
README.rst
setup.cfg
diff --git a/matplotlib_venn/__init__.py b/matplotlib_venn/__init__.py
index f96bb35..cb3e9e2 100644
--- a/matplotlib_venn/__init__.py
+++ b/matplotlib_venn/__init__.py
@@ -56,4 +56,4 @@ from matplotlib_venn._venn2 import venn2, venn2_circles
from matplotlib_venn._venn3 import venn3, venn3_circles
from matplotlib_venn._util import venn2_unweighted, venn3_unweighted
___all___ = ['venn2', 'venn2_circles', 'venn3', 'venn3_circles', 'venn2_unweighted', 'venn3_unweighted']
-__version__ = '0.11.6'
\ No newline at end of file
+__version__ = '0.11.7'
diff --git a/matplotlib_venn/_arc.py b/matplotlib_venn/_arc.py
index 073cbec..70d8040 100644
--- a/matplotlib_venn/_arc.py
+++ b/matplotlib_venn/_arc.py
@@ -155,12 +155,12 @@ class Arc(object):
Converts a given angle in degrees to the point coordinates on the arc's circle.
Inverse of point_to_angle.
- >>> Arc((1, 1), 1, 0, 0, True).angle_as_point(0)
- array([ 2., 1.])
- >>> Arc((1, 1), 1, 0, 0, True).angle_as_point(90)
- array([ 1., 2.])
- >>> Arc((1, 1), 1, 0, 0, True).angle_as_point(-270)
- array([ 1., 2.])
+ >>> Arc((1, 1), 1, 0, 0, True).angle_as_point(0).tolist()
+ [2.0, 1.0]
+ >>> Arc((1, 1), 1, 0, 0, True).angle_as_point(90).tolist()
+ [1.0, 2.0]
+ >>> np.all(np.isclose(Arc((1, 1), 1, 0, 0, True).angle_as_point(-270), [1.0, 2.0]))
+ True
'''
angle_rad = angle * np.pi / 180.0
return self.center + self.radius * np.array([np.cos(angle_rad), np.sin(angle_rad)])
@@ -169,10 +169,10 @@ class Arc(object):
'''
Returns a 2x1 numpy array with the coordinates of the arc's start point.
- >>> Arc((0, 0), 1, 0, 0, True).start_point()
- array([ 1., 0.])
- >>> Arc((0, 0), 1, 45, 0, True).start_point()
- array([ 0.707..., 0.707...])
+ >>> Arc((0, 0), 1, 0, 0, True).start_point().tolist()
+ [1.0, 0.0]
+ >>> Arc((0, 0), 1, 45, 0, True).start_point().tolist()
+ [0.707..., 0.707...]
'''
return self.angle_as_point(self.from_angle)
@@ -280,22 +280,22 @@ class Arc(object):
Intersection with the same circle as the arc's own (which means infinitely many points usually) is reported as no intersection at all.
>>> a = Arc((0, 0), 1, -60, 60, True)
- >>> a.intersect_circle((1, 0), 1)
- [array([ 0.5..., -0.866...]), array([ 0.5..., 0.866...])]
+ >>> str(a.intersect_circle((1, 0), 1)).replace(' ', '')
+ '[array([0.5...,-0.866...]),array([0.5...,0.866...])]'
>>> a.intersect_circle((0.9, 0), 1)
[]
- >>> a.intersect_circle((1,-0.1), 1)
- [array([ 0.586..., 0.810...])]
- >>> a.intersect_circle((1, 0.1), 1)
- [array([ 0.586..., -0.810...])]
+ >>> str(a.intersect_circle((1,-0.1), 1)).replace(' ', '')
+ '[array([0.586...,0.810...])]'
+ >>> str(a.intersect_circle((1, 0.1), 1)).replace(' ', '')
+ '[array([0.586...,-0.810...])]'
>>> a.intersect_circle((0, 0), 1) # Infinitely many intersection points
[]
- >>> a.intersect_circle((2, 0), 1) # Touching point, hence repeated twice
- [array([ 1., 0.]), array([ 1., 0.])]
+ >>> str(a.intersect_circle((2, 0), 1)).replace(' ', '') # Touching point, hence repeated twice
+ '[array([1.,0.]),array([1.,0.])]'
>>> a = Arc((0, 0), 1, 60, -60, False) # Same arc, different direction
- >>> a.intersect_circle((1, 0), 1)
- [array([ 0.5..., 0.866...]), array([ 0.5..., -0.866...])]
+ >>> str(a.intersect_circle((1, 0), 1)).replace(' ', '')
+ '[array([0.5...,0.866...]),array([0.5...,-0.866...])]'
>>> a = Arc((0, 0), 1, 120, -120, True)
>>> a.intersect_circle((-1, 0), 1)
@@ -339,14 +339,14 @@ class Arc(object):
Intersection with the arc along the same circle (which means infinitely many points usually) is reported as no intersection at all.
>>> a = Arc((0, 0), 1, -90, 90, True)
- >>> a.intersect_arc(Arc((1, 0), 1, 90, 270, True))
- [array([ 0.5 , -0.866...]), array([ 0.5 , 0.866...])]
- >>> a.intersect_arc(Arc((1, 0), 1, 90, 180, True))
- [array([ 0.5 , 0.866...])]
+ >>> str(a.intersect_arc(Arc((1, 0), 1, 90, 270, True))).replace(' ', '')
+ '[array([0.5,-0.866...]),array([0.5,0.866...])]'
+ >>> str(a.intersect_arc(Arc((1, 0), 1, 90, 180, True))).replace(' ', '')
+ '[array([0.5,0.866...])]'
>>> a.intersect_arc(Arc((1, 0), 1, 121, 239, True))
[]
- >>> a.intersect_arc(Arc((1, 0), 1, 120-tol, 240+tol, True)) # Without -tol and +tol the results differ on different architectures due to rounding (see Debian #813782).
- [array([ 0.5 , -0.866...]), array([ 0.5 , 0.866...])]
+ >>> str(a.intersect_arc(Arc((1, 0), 1, 120-tol, 240+tol, True))).replace(' ', '') # Without -tol and +tol the results differ on different architectures due to rounding (see Debian #813782).
+ '[array([0.5,-0.866...]),array([0.5,0.866...])]'
'''
intersections = self.intersect_circle(arc.center, arc.radius)
isections = [pt for pt in intersections if arc.contains_angle_degrees(arc.point_as_angle(pt))]
diff --git a/matplotlib_venn/_common.py b/matplotlib_venn/_common.py
index aca4d14..7653c0d 100644
--- a/matplotlib_venn/_common.py
+++ b/matplotlib_venn/_common.py
@@ -76,10 +76,10 @@ def mix_colors(col1, col2, col3=None):
Inputs are (up to) three RGB triples of floats 0.0-1.0 given as numpy arrays.
- >>> mix_colors(np.array([1.0, 0., 0.]), np.array([1.0, 0., 0.])) # doctest: +NORMALIZE_WHITESPACE
- array([ 1., 0., 0.])
- >>> mix_colors(np.array([1.0, 1., 0.]), np.array([1.0, 0.9, 0.]), np.array([1.0, 0.8, 0.1])) # doctest: +NORMALIZE_WHITESPACE
- array([ 1. , 1. , 0.04])
+ >>> mix_colors(np.array([1.0, 0., 0.]), np.array([1.0, 0., 0.])).tolist()
+ [1.0, 0.0, 0.0]
+ >>> np.round(mix_colors(np.array([1.0, 1., 0.]), np.array([1.0, 0.9, 0.]), np.array([1.0, 0.8, 0.1])), 3).tolist()
+ [1.0, 1.0, 0.04]
'''
if col3 is None:
mix_color = 0.7 * (col1 + col2)
diff --git a/matplotlib_venn/_math.py b/matplotlib_venn/_math.py
index edcde31..256f615 100644
--- a/matplotlib_venn/_math.py
+++ b/matplotlib_venn/_math.py
@@ -79,9 +79,8 @@ def circle_line_intersection(center, r, a, b):
>>> circle_line_intersection(np.array([0.0, 0.0]), 1, np.array([-1.0, 0.0]), np.array([1.0, 0.0]))
array([[ 1., 0.],
[-1., 0.]])
- >>> abs(np.round(circle_line_intersection(np.array([1.0, 1.0]), np.sqrt(2), np.array([-1.0, 1.0]), np.array([1.0, -1.0])), 6))
- array([[ 0., 0.],
- [ 0., 0.]])
+ >>> abs(np.round(circle_line_intersection(np.array([1.0, 1.0]), np.sqrt(2), np.array([-1.0, 1.0]), np.array([1.0, -1.0])), 6)).tolist()
+ [[0.0, 0.0], [0.0, 0.0]]
'''
s = b - a
# Quadratic eqn coefs
@@ -140,12 +139,10 @@ def circle_circle_intersection(C_a, r_a, C_b, r_b):
>>> circle_circle_intersection([0, 0], 1, [1, 0], 1) # Two intersection points
array([[ 0.5 , -0.866...],
[ 0.5 , 0.866...]])
- >>> circle_circle_intersection([0, 0], 1, [2, 0], 1) # Single intersection point (circles touch from outside)
- array([[ 1., 0.],
- [ 1., 0.]])
- >>> circle_circle_intersection([0, 0], 1, [0.5, 0], 0.5) # Single intersection point (circles touch from inside)
- array([[ 1., 0.],
- [ 1., 0.]])
+ >>> circle_circle_intersection([0, 0], 1, [2, 0], 1).tolist() # Single intersection point (circles touch from outside)
+ [[1.0, 0.0], [1.0, 0.0]]
+ >>> circle_circle_intersection([0, 0], 1, [0.5, 0], 0.5).tolist() # Single intersection point (circles touch from inside)
+ [[1.0, 0.0], [1.0, 0.0]]
>>> circle_circle_intersection([0, 0], 1, [0, 0], 1) is None # Infinite number of intersections (circles coincide)
True
>>> circle_circle_intersection([0, 0], 1, [0, 0.1], 0.8) is None # No intersections (one circle inside another)
diff --git a/matplotlib_venn/_region.py b/matplotlib_venn/_region.py
index 85ff9e4..fe52ecd 100644
--- a/matplotlib_venn/_region.py
+++ b/matplotlib_venn/_region.py
@@ -90,8 +90,8 @@ class VennEmptyRegion(VennRegion):
>>> assert v.make_patch() is None
>>> assert v.is_empty()
>>> v = VennEmptyRegion((0, 0))
- >>> v.label_position()
- array([ 0., 0.])
+ >>> v.label_position().tolist()
+ [0.0, 0.0]
'''
def __init__(self, label_pos = None):
self.label_pos = None if label_pos is None else np.asarray(label_pos, float)
@@ -115,8 +115,8 @@ class VennCircleRegion(VennRegion):
>>> vcr = VennCircleRegion((0, 0), 1)
>>> vcr.size()
3.1415...
- >>> vcr.label_position()
- array([ 0., 0.])
+ >>> vcr.label_position().tolist()
+ [0.0, 0.0]
>>> vcr.make_patch()
<matplotlib.patches.Circle object at ...>
>>> sr, ir = vcr.subtract_and_intersect_circle((0.5, 0), 1)
@@ -197,10 +197,10 @@ class VennCircleRegion(VennRegion):
'''
The label should be positioned in the center of the circle
- >>> VennCircleRegion((0, 0), 1).label_position()
- array([ 0., 0.])
- >>> VennCircleRegion((-1.2, 3.4), 1).label_position()
- array([-1.2, 3.4])
+ >>> VennCircleRegion((0, 0), 1).label_position().tolist()
+ [0.0, 0.0]
+ >>> VennCircleRegion((-1.2, 3.4), 1).label_position().tolist()
+ [-1.2, 3.4]
'''
return self.center
@@ -211,8 +211,8 @@ class VennCircleRegion(VennRegion):
>>> patch = VennCircleRegion((1, 2), 3).make_patch()
>>> patch
<matplotlib.patches.Circle object at ...>
- >>> patch.center, patch.radius
- (array([ 1., 2.]), 3.0)
+ >>> patch.center.tolist(), patch.radius
+ ([1.0, 2.0], 3.0)
'''
return Circle(self.center, self.radius)
diff --git a/matplotlib_venn/_venn2.py b/matplotlib_venn/_venn2.py
index 9e77cbf..21cac0e 100644
--- a/matplotlib_venn/_venn2.py
+++ b/matplotlib_venn/_venn2.py
@@ -65,11 +65,11 @@ def solve_venn2_circles(venn_areas):
In particular, the first two values must be positive.
>>> c, r = solve_venn2_circles((1, 1, 0))
- >>> np.round(r, 3)
- array([ 0.564, 0.564])
+ >>> np.round(r, 3).tolist()
+ [0.564, 0.564]
>>> c, r = solve_venn2_circles(compute_venn2_areas((1, 2, 3)))
- >>> np.round(r, 3)
- array([ 0.461, 0.515])
+ >>> np.round(r, 3).tolist()
+ [0.461, 0.515]
'''
(A_a, A_b, A_ab) = list(map(float, venn_areas))
r_a, r_b = np.sqrt(A_a / np.pi), np.sqrt(A_b / np.pi)
@@ -106,8 +106,8 @@ def compute_venn2_colors(set_colors):
Given two base colors, computes combinations of colors corresponding to all regions of the venn diagram.
returns a list of 3 elements, providing colors for regions (10, 01, 11).
- >>> compute_venn2_colors(('r', 'g'))
- (array([ 1., 0., 0.]), array([ 0. , 0.5, 0. ]), array([ 0.7 , 0.35, 0. ]))
+ >>> str(compute_venn2_colors(('r', 'g'))).replace(' ', '')
+ '(array([1.,0.,0.]),array([0.,0.5,0.]),array([0.7,0.35,0.]))'
'''
ccv = ColorConverter()
base_colors = [np.array(ccv.to_rgb(c)) for c in set_colors]
diff --git a/matplotlib_venn/_venn3.py b/matplotlib_venn/_venn3.py
index 0588aab..0496014 100644
--- a/matplotlib_venn/_venn3.py
+++ b/matplotlib_venn/_venn3.py
@@ -81,11 +81,11 @@ def solve_venn3_circles(venn_areas):
three pairwise intersections).
>>> c, r = solve_venn3_circles((1, 1, 1, 0, 0, 0, 0))
- >>> np.round(r, 3)
- array([ 0.564, 0.564, 0.564])
+ >>> np.round(r, 3).tolist()
+ [0.564, 0.564, 0.564]
>>> c, r = solve_venn3_circles(compute_venn3_areas((1, 2, 40, 30, 4, 40, 4)))
- >>> np.round(r, 3)
- array([ 0.359, 0.476, 0.453])
+ >>> np.round(r, 3).tolist()
+ [0.359, 0.476, 0.453]
'''
(A_a, A_b, A_c, A_ab, A_bc, A_ac, A_abc) = list(map(float, venn_areas))
r_a, r_b, r_c = np.sqrt(A_a / np.pi), np.sqrt(A_b / np.pi), np.sqrt(A_c / np.pi)
@@ -207,8 +207,8 @@ def compute_venn3_colors(set_colors):
Given three base colors, computes combinations of colors corresponding to all regions of the venn diagram.
returns a list of 7 elements, providing colors for regions (100, 010, 110, 001, 101, 011, 111).
- >>> compute_venn3_colors(['r', 'g', 'b'])
- (array([ 1., 0., 0.]),..., array([ 0.4, 0.2, 0.4]))
+ >>> str(compute_venn3_colors(['r', 'g', 'b'])).replace(' ', '')
+ '(array([1.,0.,0.]),...,array([0.4,0.2,0.4]))'
'''
ccv = ColorConverter()
base_colors = [np.array(ccv.to_rgb(c)) for c in set_colors]
diff --git a/setup.cfg b/setup.cfg
index 31beba0..a21f7df 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -3,7 +3,8 @@ tag_build =
tag_svn_revision = false
tag_date = 0
-[pytest]
+[tool:pytest]
addopts = --ignore=setup.py --ignore=build --ignore=dist --doctest-modules
norecursedirs = *.egg
+doctest_optionflags = NORMALIZE_WHITESPACE ELLIPSIS
Debdiff
[The following lists of changes regard files as different if they have different names, permissions or owners.]
Files in second set of .debs but not in first
-rw-r--r-- root/root /usr/lib/python3/dist-packages/matplotlib_venn-0.11.7.egg-info/PKG-INFO -rw-r--r-- root/root /usr/lib/python3/dist-packages/matplotlib_venn-0.11.7.egg-info/dependency_links.txt -rw-r--r-- root/root /usr/lib/python3/dist-packages/matplotlib_venn-0.11.7.egg-info/requires.txt -rw-r--r-- root/root /usr/lib/python3/dist-packages/matplotlib_venn-0.11.7.egg-info/top_level.txt -rw-r--r-- root/root /usr/lib/python3/dist-packages/matplotlib_venn-0.11.7.egg-info/zip-safe
Files in first set of .debs but not in second
-rw-r--r-- root/root /usr/lib/python3/dist-packages/matplotlib_venn-0.11.6.egg-info/PKG-INFO -rw-r--r-- root/root /usr/lib/python3/dist-packages/matplotlib_venn-0.11.6.egg-info/dependency_links.txt -rw-r--r-- root/root /usr/lib/python3/dist-packages/matplotlib_venn-0.11.6.egg-info/requires.txt -rw-r--r-- root/root /usr/lib/python3/dist-packages/matplotlib_venn-0.11.6.egg-info/top_level.txt -rw-r--r-- root/root /usr/lib/python3/dist-packages/matplotlib_venn-0.11.6.egg-info/zip-safe
No differences were encountered in the control files