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‎.mailmap

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@@ -28,6 +28,7 @@ John Hunter <[email protected]>
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Jorrit Wronski <[email protected]>
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Jouni K. Seppänen <[email protected]>
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Joseph Fox-Rabinovitz <[email protected]> Mad Physicist <[email protected]>
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Joseph Fox-Rabinovitz <[email protected]> Joseph Fox-Rabinovitz <[email protected]>
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Julien Schueller <[email protected]> <[email protected]>
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Julien Schueller <[email protected]> <[email protected]>
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Kevin Davies <[email protected]> <[email protected]>

‎.travis.yml

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deactivate
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source ~/virtualenv/python2.7/bin/activate
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pip install pip --upgrade
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pip install linkchecker
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# linkchecker is currently broken with requests 2.10.0 so force an earlier version
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pip install $PRE requests==2.9.2 linkchecker
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linkchecker build/html/index.html
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fi
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- rm -rf $HOME/.cache/matplotlib/tex.cache

‎INSTALL

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Used to manipulate time-zone aware datetimes. http://pypi.python.org/pypi/pytz
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:term:`FreeType` 2.3 or later
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Library for reading true type font files. If using pip, easy_install or
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Library for reading true type font files. If using pip, easy_install or
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installing from source, the installer will attempt to locate FreeType in
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expected locations. If it cannot, try installing `pkg-config
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expected locations. If it cannot, try installing `pkg-config
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<http://matplotlib.org/users/installing.html#optional-dependencies>`__,
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a tool used to find required non-python libraries.
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`cycler <http://matplotlib.org/cycler/>`__ 0.9 or later
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`cycler <http://matplotlib.org/cycler/>`__ 0.10.0 or later
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Composable cycle class used for constructing style-cycles
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`functools32`

‎doc/thirdpartypackages/index.rst

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===============
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`mplstereonet <https://github.com/joferkington/mplstereonet>`_ provides stereonets for plotting and analyzing orientation data in Matplotlib.
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pyupset
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===============
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`pyUpSet <https://github.com/ImSoErgodic/py-upset>`_ is a static Python implementation of the `UpSet suite by Lex et al. <http://www.caleydo.org/tools/upset/>`_ to explore complex intersections of sets and data frames.

‎doc/users/whats_new/rcparams.rst

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+----------------------------+--------------------------------------------------+
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|`date.autoformatter.second` | format string for 'second' scale times |
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+----------------------------+--------------------------------------------------+
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|`scatter.marker` | default marker for scatter plot |
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+----------------------------+--------------------------------------------------+
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|`svg.hashsalt` | see note |
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+----------------------------+--------------------------------------------------+
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‎doc/users/whats_new/uptade_subplot2grid.rst renamed to ‎doc/users/whats_new/update_subplot2grid.rst

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New Firgure Parameter for subplot2grid
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New Figure Parameter for subplot2grid
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--------------------------------------
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A ``fig`` parameter now exists for the method :func:`subplot2grid`. This allows
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for the figure that the subplots will be created in to be specified. If ``fig``
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a user to specify the figure where the subplots will be created. If ``fig``
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is ``None`` (default) then the method will use the current figure retrieved by
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:func:`gcf`.
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‎examples/animation/dynamic_image.py

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#!/usr/bin/env python
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"""
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An animated image
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"""

‎examples/animation/dynamic_image2.py

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#!/usr/bin/env python
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"""
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An animated image
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"""

‎examples/api/agg_oo.py

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#!/usr/bin/env python
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# -*- noplot -*-
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"""
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A pure OO (look Ma, no pylab!) example using the agg backend

‎examples/api/barchart_demo.py

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#!/usr/bin/env python
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# a bar plot with errorbars
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import numpy as np
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import matplotlib.pyplot as plt

‎examples/api/collections_demo.py

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#!/usr/bin/env python
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'''Demonstration of LineCollection, PolyCollection, and
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RegularPolyCollection with autoscaling.
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‎examples/api/date_demo.py

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#!/usr/bin/env python
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"""
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Show how to make date plots in matplotlib using date tick locators and
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formatters. See major_minor_demo1.py for more information on

‎examples/api/joinstyle.py

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"""
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Illustrate the three different join styles
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"""

‎examples/api/power_norm_demo.py

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#!/usr/bin/python
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from matplotlib import pyplot as plt
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import matplotlib.colors as mcolors
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import numpy as np

‎examples/api/sankey_demo_old.py

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#!/usr/bin/env python
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from __future__ import print_function
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__author__ = "Yannick Copin <[email protected]>"

‎examples/api/two_scales.py

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#!/usr/bin/env python
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"""
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Demonstrate how to do two plots on the same axes with different left

‎examples/event_handling/keypress_demo.py

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#!/usr/bin/env python
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"""
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Show how to connect to keypress events
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"""

‎examples/event_handling/pick_event_demo.py

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#!/usr/bin/env python
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"""
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You can enable picking by setting the "picker" property of an artist

‎examples/event_handling/pipong.py

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#!/usr/bin/env python
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# A matplotlib based game of Pong illustrating one way to write interactive
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# animation which are easily ported to multiple backends
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# pipong.py was written by Paul Ivanov <http://pirsquared.org>

‎examples/event_handling/pong_gtk.py

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#!/usr/bin/env python
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from __future__ import print_function
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# For detailed comments on animation and the techniques used here, see

‎examples/event_handling/test_mouseclicks.py

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#!/usr/bin/env python
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from __future__ import print_function
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import matplotlib

‎examples/misc/ftface_props.py

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#!/usr/bin/env python
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"""
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This is a demo script to show you how to use all the properties of an

‎examples/mplot3d/2dcollections3d_demo.py

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'''
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Demonstrates using ax.plot's zdir keyword to plot 2D scatterplot data on
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selective axes of a 3D plot.
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'''
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from mpl_toolkits.mplot3d import Axes3D
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import numpy as np
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import matplotlib.pyplot as plt
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fig = plt.figure()
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ax = fig.gca(projection='3d')
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# Plot a sin curve using the x and y axes.
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x = np.linspace(0, 1, 100)
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y = np.sin(x * 2 * np.pi) / 2 + 0.5
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ax.plot(x, y, zs=0, zdir='z', label='zs=0, zdir=z')
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ax.plot(x, y, zs=0, zdir='z', label='curve in (x,y)')
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# Plot scatterplot data (20 2D points per colour) on the x and z axes.
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colors = ('r', 'g', 'b', 'k')
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x = np.random.sample(20*len(colors))
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y = np.random.sample(20*len(colors))
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c_list = []
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for c in colors:
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x = np.random.sample(20)
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y = np.random.sample(20)
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ax.scatter(x, y, 0, zdir='y', c=c)
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c_list.append([c]*20)
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# By using zdir='y', the y value of these points is fixed to the zs value 0
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# and the (x,y) points are plotted on the x and z axes.
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ax.scatter(x, y, zs=0, zdir='y', c=c_list, label='points in (x,z)')
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# Make legend, set axes limits and labels
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ax.legend()
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ax.set_xlim3d(0, 1)
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ax.set_ylim3d(0, 1)
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ax.set_zlim3d(0, 1)
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ax.set_xlabel('X')
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ax.set_ylabel('Y')
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ax.set_zlabel('Z')
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# Customize the view angle so it's easier to see that the scatter points lie
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# on the plane y=0
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ax.view_init(elev=20., azim=-35)
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plt.show()

‎examples/mplot3d/bars3d_demo.py

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'''
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Demonstrates making a 3D plot which has 2D bar graphs projected onto
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planes y=0, y=1, etc.
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'''
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import matplotlib.pyplot as plt
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import numpy as np
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fig = plt.figure()
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ax = fig.add_subplot(111, projection='3d')
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for c, z in zip(['r', 'g', 'b', 'y'], [30, 20, 10, 0]):
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colors = ['r', 'g', 'b', 'y']
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yticks = [3, 2, 1, 0]
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for c, k in zip(colors, yticks):
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# Generate the random data for the y=k 'layer'.
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xs = np.arange(20)
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ys = np.random.rand(20)
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# You can provide either a single color or an array. To demonstrate this,
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# the first bar of each set will be colored cyan.
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# You can provide either a single color or an array with the same length as
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# xs and ys. To demonstrate this, we color the first bar of each set cyan.
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cs = [c] * len(xs)
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cs[0] = 'c'
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ax.bar(xs, ys, zs=z, zdir='y', color=cs, alpha=0.8)
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# Plot the bar graph given by xs and ys on the plane y=k with 80% opacity.
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ax.bar(xs, ys, zs=k, zdir='y', color=cs, alpha=0.8)
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ax.set_xlabel('X')
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ax.set_ylabel('Y')
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# On the y axis let's only label the discrete values that we have data for.
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ax.set_yticks(yticks)
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‎examples/mplot3d/contour3d_demo.py

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'''
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Demonstrates plotting contour (level) curves in 3D.
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This is like a contour plot in 2D except that the f(x,y)=c curve is plotted
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on the plane z=c.
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'''
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from mpl_toolkits.mplot3d import axes3d
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from matplotlib import cm
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fig = plt.figure()
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ax = fig.add_subplot(111, projection='3d')
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ax = fig.gca(projection='3d')
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X, Y, Z = axes3d.get_test_data(0.05)
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# Plot contour curves
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cset = ax.contour(X, Y, Z, cmap=cm.coolwarm)
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‎examples/mplot3d/contour3d_demo2.py

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'''
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Demonstrates plotting contour (level) curves in 3D using the extend3d option.
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This modification of the contour3d_demo example uses extend3d=True to
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extend the curves vertically into 'ribbons'.
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'''
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import matplotlib.pyplot as plt
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from matplotlib import cm
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fig = plt.figure()
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ax = fig.gca(projection='3d')
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X, Y, Z = axes3d.get_test_data(0.05)
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cset = ax.contour(X, Y, Z, extend3d=True, cmap=cm.coolwarm)
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‎examples/mplot3d/contour3d_demo3.py

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'''
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Demonstrates displaying a 3D surface while also projecting contour 'profiles'
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onto the 'walls' of the graph.
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See contourf3d_demo2 for the filled version.
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'''
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from matplotlib import cm
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fig = plt.figure()
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ax = fig.gca(projection='3d')
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X, Y, Z = axes3d.get_test_data(0.05)
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# Plot the 3D surface
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ax.plot_surface(X, Y, Z, rstride=8, cstride=8, alpha=0.3)
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# Plot projections of the contours for each dimension. By choosing offsets
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# that match the appropriate axes limits, the projected contours will sit on
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# the 'walls' of the graph
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cset = ax.contour(X, Y, Z, zdir='z', offset=-100, cmap=cm.coolwarm)
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cset = ax.contour(X, Y, Z, zdir='x', offset=-40, cmap=cm.coolwarm)
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cset = ax.contour(X, Y, Z, zdir='y', offset=40, cmap=cm.coolwarm)
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ax.set_xlabel('X')
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ax.set_xlim(-40, 40)
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ax.set_ylabel('Y')
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ax.set_ylim(-40, 40)
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ax.set_zlabel('Z')
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ax.set_zlim(-100, 100)
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ax.set_xlabel('X')
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ax.set_ylabel('Y')
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ax.set_zlabel('Z')
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‎examples/mplot3d/contourf3d_demo.py

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'''
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contourf differs from contour in that it creates filled contours, ie.
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a discrete number of colours are used to shade the domain.
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This is like a contourf plot in 2D except that the shaded region corresponding
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to the level c is graphed on the plane z=c.
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'''
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from mpl_toolkits.mplot3d import axes3d
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from matplotlib import cm
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fig = plt.figure()
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ax = fig.gca(projection='3d')
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X, Y, Z = axes3d.get_test_data(0.05)
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cset = ax.contourf(X, Y, Z, cmap=cm.coolwarm)
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‎examples/mplot3d/contourf3d_demo2.py

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"""
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.. versionadded:: 1.1.0
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This demo depends on new features added to contourf3d.
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"""
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'''
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Demonstrates displaying a 3D surface while also projecting filled contour
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'profiles' onto the 'walls' of the graph.
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See contour3d_demo2 for the unfilled version.
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'''
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from mpl_toolkits.mplot3d import axes3d
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fig = plt.figure()
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X, Y, Z = axes3d.get_test_data(0.05)
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# Plot the 3D surface
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ax.plot_surface(X, Y, Z, rstride=8, cstride=8, alpha=0.3)
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# Plot projections of the contours for each dimension. By choosing offsets
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# that match the appropriate axes limits, the projected contours will sit on
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# the 'walls' of the graph
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cset = ax.contourf(X, Y, Z, zdir='z', offset=-100, cmap=cm.coolwarm)
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cset = ax.contourf(X, Y, Z, zdir='x', offset=-40, cmap=cm.coolwarm)
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cset = ax.contourf(X, Y, Z, zdir='y', offset=40, cmap=cm.coolwarm)
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ax.set_xlabel('X')
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ax.set_xlim(-40, 40)
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ax.set_ylabel('Y')
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ax.set_ylim(-40, 40)
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ax.set_zlabel('Z')
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ax.set_zlim(-100, 100)
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ax.set_xlabel('X')
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ax.set_ylabel('Y')
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ax.set_zlabel('Z')
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plt.show()

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