8000 Merge branch 'v1.4.0-doc' into v1.4.x · matplotlib/matplotlib@e981c68 · GitHub
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Merge branch 'v1.4.0-doc' into v1.4.x
- manually fixed version number
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INSTALL

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@@ -66,7 +66,7 @@ you will also need to install compatible versions of
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`pyparsing <https://pypi.python.org/pypi/pyparsing/>`_ and
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`six <https://pypi.python.org/pypi/six>`_
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in addition to
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`matplotlib <https://pypi.python.org/pypi/matplotlib>`_.
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`matplotlib <http://matplotlib.org/downloads.html>`_.
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In case Python is not installed for all users (not the default), the
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Microsoft Visual C++ 2008 (
@@ -106,14 +106,15 @@ standard Python shell or IPython. It is enabled as the default backend
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for the official binaries. GTK3 is not supported on Windows.
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The Windows installers (:file:`*.exe`) and wheels (:file:`*.whl`) on
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the download page do not contain test data or example code.
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the `download page <http://matplotlib.org/downloads.html>`_ do not
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contain test data or example code.
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If you want to try the many demos that come in the matplotlib source
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distribution, download the zip file and look in the :file:`examples`
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subdirectory.
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To run the test suite, copy the lib\matplotlib\tests and
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lib\mpl_toolkits\tests directories from the source distribution to
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sys.prefix\Lib\site-packages\matplotlib and
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sys.prefix\Lib\site-packages\mpl_toolkits respectively, and install
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distribution, download the :file:`*.tar.gz` file and look in the
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:file:`examples` subdirectory.
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To run the test suite, copy the :file:`lib\matplotlib\tests` and
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:file:`lib\mpl_toolkits\tests` directories from the source distribution to
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:file:`sys.prefix\Lib\site-packages\matplotlib` and
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:file:`sys.prefix\Lib\site-packages\mpl_toolkits` respectively, and install
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`nose <https://pypi.python.org/pypi/nose>`_,
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`mock <https://pypi.python.org/pypi/mock>`_,
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Pillow, MiKTeX, GhostScript, ffmpeg, avconv, mencoder, ImageMagick, and
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selection of image file formats.
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:term:`freetype` 1.4 (or later)
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library for reading true type font files.
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:term:`freetype` 2.4 or later
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library for reading true type font files. Matplotlib in known
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to work with freetype 2.3, and the required version will be reduced
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in 1.4.1. If you need to build from source on a system which only has
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freetype 2.3 available, please edit L945 of `setupext.py` to reduce
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`min_version` to 2.3.
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`pytz`
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Required if you want to manipulate datetime objects which are time-zone
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aware. An exception will be raised if you try to make time-zone aware
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plots with out `pytz` installed. It will become a required dependency
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in 1.4.1.
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Required libraries that ship with matplotlib

doc/_templates/citing.html

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@@ -24,4 +24,11 @@ <h1>Citing matplotlib</h1>
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year = 2007
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}
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</pre>
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<h2>DOIs</h2>
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<dl>
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<dt>v1.4.0</dt><dd><a href="http://dx.doi.org/10.5281/zenodo.11451"><img src="https://zenodo.org/badge/doi/10.5281/zenodo.11451.png" alt="10.5281/zenodo.11451"></a></dd>
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</dl>
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{% endblock %}

doc/_templates/layout.html

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@@ -178,25 +178,6 @@ <h3>{{ _('Navigation') }}</h3>
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{% block relbar1 %}
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<!-- Piwik -->
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<script type="text/javascript">
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if ("matplotlib.sourceforge.net" == document.location.hostname ||
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"matplotlib.sf.net" == document.location.hostname) {
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var pkBaseURL = (("https:" == document.location.protocol) ? "https://apps.sourceforge.net/piwik/matplotlib/" : "http://apps.sourceforge.net/piwik/matplotlib/");
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document.write(unescape("%3Cscript src='" + pkBaseURL + "piwik.js' type='text/javascript'%3E%3C/script%3E"));
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}
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</script>
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<script type="text/javascript">
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if ("matplotlib.sourceforge.net" == document.location.hostname ||
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"matplotlib.sf.net" == document.location.hostname) {
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piwik_action_name = '';
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piwik_idsite = 1;
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piwik_url = pkBaseURL + "piwik.php";
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piwik_log(piwik_action_name, piwik_idsite, piwik_url);
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document.write(unescape('%3Cobject%3E%3Cnoscript%3E%3Cp%3E%3Cimg src="http://apps.sourceforge.net/piwik/matplotlib/piwik.php?idsite=1" alt="piwik"/%3E%3C/p%3E%3C/noscript%3E%3C/object%3E'));
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}
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</script>
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<!-- End Piwik Tag -->
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<link rel="shortcut icon" href="/_static/favicon.ico">
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<!-- The "Fork me on github" ribbon -->

doc/users/plotting/colormaps/Lfunction.py

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'''
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Recreate Josef Albers plot illustrating the Weber-Fechner law and illustrate
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with the binary matplotlib colormap, too. Trying to show the difference between
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Recreate Josef Albers plot illustrating the Weber-Fechner law and illustrate
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with the binary matplotlib colormap, too. Trying to show the difference between
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adding blackness to a color at different rates.
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'''
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import numpy as np
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import matplotlib.pyplot as plt
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from skimage import io, color
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import pdb
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from skimage import color
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import matplotlib as mpl
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from mpl_toolkits.mplot3d import Axes3D
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from matplotlib import cm, colors
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from matplotlib import cm
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mpl.rcParams.update({'font.size': 20})
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# common ylabel
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ax1.text(-0.3, 3.8, 'Additional Parts Black',
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ax1.text(-0.3, 3.8, 'Additional Parts Black',
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rotation=90, transform=ax1.transAxes)
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ax2.spines['left'].set_visible(False)
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# common ylabel
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ax1.text(-0.3, 4.0, 'Steps through map indices',
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ax1.text(-0.3, 4.0, 'Steps through map indices',
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rotation=90, transform=ax1.transAxes)
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fig.subplots_adjust(hspace=0.0)

doc/users/plotting/colormaps/grayscale.py

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Uses lightness L* as a proxy for grayscale value.
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'''
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from skimage import io, color
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from skimage import color
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib import cm
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import matplotlib as mpl
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import pdb
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from scipy.optimize import curve_fit
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mpl.rcParams.update({'font.size': 14})
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mpl.rcParams['font.sans-serif'] = 'Arev Sans, Bitstream Vera Sans, Lucida Grande, Verdana, Geneva, Lucid, Helvetica, Avant Garde, sans-serif'
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10000 'gnuplot', 'gnuplot2', 'ocean', 'rainbow',
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'terrain', 'flag', 'prism'])]
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# indices to step through colormap
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# indices to step through colormap
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x = np.linspace(0.0, 1.0, 100)
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nrows = max(len(cmap_list) for cmap_category, cmap_list in cmaps)
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for cmap_category, cmap_list in cmaps:
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plot_color_gradients(cmap_category, cmap_list)
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doc/users/plotting/colormaps/lightness.py

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For each colormap, plot the lightness parameter L* from CIELAB colorspace along the y axis vs index through the colormap. Colormaps are examined in categories as in the original matplotlib gallery of colormaps.
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'''
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from skimage import io, color
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from skimage import color
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib import cm
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import matplotlib as mpl
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import pdb
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from scipy.optimize import curve_fit
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mpl.rcParams.update({'font.size': 14})
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mpl.rcParams['font.sans-serif'] = 'Arev Sans, Bitstream Vera Sans, Lucida Grande, Verdana, Geneva, Lucid, Helvetica, Avant Garde, sans-serif'
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'gnuplot', 'gnuplot2', 'ocean', 'rainbow',
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'terrain', 'flag', 'prism'])]
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# indices to step through colormap
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# indices to step through colormap
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x = np.linspace(0.0, 1.0, 100)
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# Do plot
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dsub = 5 # number of colormaps per subplot
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if cmap_category == 'Diverging': # because has 13 colormaps
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dsub = 6
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elif cmap_category == 'Sequential2':
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elif cmap_category == 'Sequential2':
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dsub = 7
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elif cmap_category == 'Sequential':
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elif cmap_category == 'Sequential':
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dsub = 7
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nsubplots = int(np.ceil(len(cmap_list)/float(dsub)))
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ax = fig.add_subplot(nsubplots, 1, i+1)
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# pdb.set_trace()
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for j, cmap in enumerate(cmap_list[i*dsub:(i+1)*dsub]):
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# Get rgb values for colormap
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ax.scatter(x+j*dc, lab[0,:,0], c=x, cmap=cmap, s=300, linewidths=0.)
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ax.axis([-0.1,6.1,0,100])
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locs.append(x[int(x.size/2.)]+j*dc) # store locations for colormap labels
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# Set up labels for colormaps
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ax.xaxis.set_ticks_position('top')
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ticker = mpl.ticker.FixedLocator(locs)

doc/users/whats_new.rst

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colorblind-friendly colormap is now available at :class:`matplotlib.cm.Wistia`.
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This colormap maintains the red/green symbolism while achieving deuteranopic
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legibility through brightness variations. See
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`here <https://github.com/wistia/heatmap-palette>`
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`here <https://github.com/wistia/heatmap-palette>`_
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for more information.
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Documentation changes
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a second method, :func:`~matplotlib.Axes.bxp` is called to draw the boxplots
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based on the stats.
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The :func:~matplotlib.pyplot.boxplot function can be used as before to
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The :func:`~matplotlib.pyplot.boxplot` function can be used as before to
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generate boxplots from data in one step. But now the user has the
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flexibility to generate the statistics independently, or to modify the
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output of :func:~matplotlib.cbook.boxplot_stats prior to plotting
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with :func:~matplotlib.Axes.bxp.
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output of :func:`~matplotlib.cbook.boxplot_stats` prior to plotting
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with :func:`~matplotlib.Axes.bxp`.
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Lastly, each artist (e.g., the box, outliers, cap, notches) can now be
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toggled on or off and their styles can be passed in through individual
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kwargs. See the examples:
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:ref:`~examples/statistics/boxplot_demo.py` and
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:ref:`~examples/statistics/bxp_demo.py`
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:ref:`statistics-boxplot_demo` and
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:ref:`statistics-bxp_demo`
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Added a bool kwarg, `manage_xticks`, which if False disables the management
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of the xtick and xlim by `boxplot`.
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Added a bool kwarg, :code:`manage_xticks`, which if False disables the management
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of the ticks and limits on the x-axis by :func:`~matplotlib.axes.Axes.bxp`.
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Support for datetime axes in 2d plots
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`````````````````````````````````````
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The Qt5Agg backend currently does not work with IPython's %matplotlib magic.
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The 1.4.0 release has a known bug where the toolbar is broken. This can be
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fixed by: ::
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cd path/to/installed/matplotlib
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wget https://github.com/matplotlib/matplotlib/pull/3322.diff
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# unix2dos 3322.diff (if on windows to fix line endings)
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patch -p2 < 3322.diff
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Qt4 backend
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```````````
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Rudolf Höfler changed the appearance of the subplottool. All sliders are

lib/matplotlib/__init__.py

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import sys
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import distutils.version
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__version__ = '1.4.0'
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__version__ = '1.4.x'
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__version__numpy__ = '1.6' # minimum required numpy version
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try:

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