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‎doc/README.txt

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@@ -6,7 +6,7 @@ documentation. All of the documentation is written using sphinx, a
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python documentation system built on top of ReST. This directory contains
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* users - the user documentation, eg plotting tutorials, configuration
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* users - the user documentation, e.g. plotting tutorials, configuration
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tips, etc.
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* devel - documentation for matplotlib developers

‎doc/_templates/search.html

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@@ -10,7 +10,7 @@ <h1 id="search-documentation">{{ _('Search') }}</h1>
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words. Pages containing less words won't appear in the result
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list.{% endtrans %} If you want to limit your search to working code examples,
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include the keyword "codex" (mnemonic for <i>code example</i>) in your
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search, eg "codex ellipse";
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search, e.g. "codex ellipse";
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see <a href="{{ pathto('faq/howto_faq.html#search-examples') }}">search&nbsp;examples</a>.
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</p>
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<form action="" method="get">

‎doc/api/api_changes.rst

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@@ -657,7 +657,7 @@ Changes for 0.91.0
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should be changed to ``${\cal R}$``. Alternatively, you may use the
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new LaTeX-style font commands (``\mathcal``, ``\mathrm``,
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``\mathit``, ``\mathtt``) which do affect the following group,
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eg. ``$\mathcal{R}$``.
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e.g. ``$\mathcal{R}$``.
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* Text creation commands have a new default linespacing and a new
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``linespacing`` kwarg, which is a multiple of the maximum vertical
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units.ConversionInterface.tickers renamed to
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units.ConversionInterface.axisinfo and it now returns a
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units.AxisInfo object rather than a tuple. This will make it
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easier to add axis info functionality (eg I added a default label
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easier to add axis info functionality (e.g. I added a default label
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on this iteration) w/o having to change the tuple length and hence
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the API of the client code everytime new functionality is added.
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Also, units.ConversionInterface.convert_to_value is now simply
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pylab still imports most of the symbols from Numerix, MLab, fft,
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etc, but is more cautious. For names that clash with python names
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(min, max, sum), pylab keeps the builtins and provides the numeric
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versions with an a* prefix, eg (amin, amax, asum)
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versions with an a* prefix, e.g. (amin, amax, asum)
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Changes for 0.70
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================
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removed add_axes and add_subplot from backend_bases. Use
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figure.add_axes and add_subplot instead. The figure now manages the
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current axes with gca and sca for get and set current axe. If you
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have code you are porting which called, eg, figmanager.add_axes, you
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have code you are porting which called, e.g., figmanager.add_axes, you
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can now simply do figmanager.canvas.figure.add_axes.
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Changes for 0.65
@@ -1334,7 +1334,7 @@ pcolor_classic and scatter_classic.
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The return value from pcolor is a PolyCollection. Most of the
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propertes that are available on rectangles or other patches are also
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available on PolyCollections, eg you can say::
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available on PolyCollections, e.g. you can say::
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c = scatter(blah, blah)
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c.set_linewidth(1.0)
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entire list.
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If you want the different elements of a collection to vary on a
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property, eg to have different line widths, see matplotlib.collections
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property, e.g. to have different line widths, see matplotlib.collections
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for a discussion on how to set the properties as a sequence.
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For scatter, the size argument is now in points^2 (the area of the
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needed with double buffered drawing. Ditto with state change.
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Text instances have a get_prop_tup method that returns a hashable
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tuple of text properties which you can use to see if text props
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have changed, eg by caching a font or layout instance in a dict
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have changed, e.g. by caching a font or layout instance in a dict
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with the prop tup as a key -- see RendererGTK.get_pango_layout in
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backend_gtk for an example.
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* matplotlib.matlab._get_current_fig_manager renamed to
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matplotlib.matlab.get_current_fig_manager to allow user access to
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the GUI window attribute, eg figManager.window for GTK and
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the GUI window attribute, e.g. figManager.window for GTK and
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figManager.frame for wx
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Changes for 0.40

‎doc/devel/coding_guide.rst

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@@ -66,10 +66,10 @@ We prefer this over the equivalent ``from matplotlib import cbook``
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because the latter is ambiguous as to whether ``cbook`` is a module or a
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function. The former makes it explicit that you
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are importing a module or package. There are some modules with names
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that match commonly used local variable names, eg
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that match commonly used local variable names, e.g.
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:mod:`matplotlib.lines` or :mod:`matplotlib.colors`. To avoid the clash,
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use the prefix 'm' with the ``import some.thing as
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mthing`` syntax, eg::
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mthing`` syntax, e.g.::
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import matplotlib.lines as mlines
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import matplotlib.transforms as transforms # OK
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ACCEPTS: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]
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"""
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Since matplotlib uses a lot of pass-through ``kwargs``, eg. in every
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Since matplotlib uses a lot of pass-through ``kwargs``, e.g. in every
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function that creates a line (:func:`~matplotlib.pyplot.plot`,
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:func:`~matplotlib.pyplot.semilogx`,
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:func:`~matplotlib.pyplot.semilogy`, etc...), it can be difficult for
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artist.kwdocd['Line2D'] = artist.kwdoc(Line2D)
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Then in any function accepting :class:`~matplotlib.lines.Line2D`
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pass-through ``kwargs``, eg. :meth:`matplotlib.axes.Axes.plot`::
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pass-through ``kwargs``, e.g. :meth:`matplotlib.axes.Axes.plot`::
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# in axes.py
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def plot(self, *args, **kwargs):
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plot.__doc__ = cbook.dedent(plot.__doc__) % artist.kwdocd
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Note there is a problem for :class:`~matplotlib.artist.Artist`
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``__init__`` methods, eg. :meth:`matplotlib.patches.Patch.__init__`,
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``__init__`` methods, e.g. :meth:`matplotlib.patches.Patch.__init__`,
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which supports ``Patch`` ``kwargs``, since the artist inspector cannot
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work until the class is fully defined and we can't modify the
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``Patch.__init__.__doc__`` docstring outside the class definition.
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To run a single test from the command line, you can provide a
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dot-separated path to the module followed by the function separated by
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a colon, eg. (this is assuming the test is installed)::
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a colon, e.g. (this is assuming the test is installed)::
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python tests.py matplotlib.tests.test_simplification:test_clipping
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toolkit. If you include code, make sure you include a copy of that
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code's license in the license directory if the code's license requires
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you to distribute the license with it. Non-BSD compatible licenses
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are acceptable in matplotlib toolkits (eg basemap), but make sure you
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are acceptable in matplotlib toolkits (e.g. basemap), but make sure you
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Why BSD compatible?

‎doc/devel/documenting_mpl.rst

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@@ -275,7 +275,7 @@ Referring to mpl documents
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In the documentation, you may want to include to a document in the
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matplotlib src, e.g. a license file or an image file from `mpl-data`,
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refer to it via a relative path from the document where the rst file
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resides, eg, in :file:`users/navigation_toolbar.rst`, we refer to the
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resides, e.g., in :file:`users/navigation_toolbar.rst`, we refer to the
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image icons with::
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We used to use a symlink for :file:`mpl-data` too, but the distro
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becomes very large on platforms that do not support links (eg the font
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becomes very large on platforms that do not support links (e.g. the font
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.. _internal-section-refs:
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===========================
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To maximize internal consistency in section labeling and references,
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use hypen separated, descriptive labels for section references, eg::
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use hypen separated, descriptive labels for section references, e.g.::
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.. _howto-webapp:
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==================
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For everything but top level chapters, please use ``Upper lower`` for
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section titles, eg ``Possible hangups`` rather than ``Possible
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section titles, e.g. ``Possible hangups`` rather than ``Possible
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Hangups``
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Inheritance diagrams

‎doc/devel/outline.rst

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"has author". Once you have completed draft and checked it in, you
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can change the status to "submitted" and try to find a reviewer if you
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don't have one. The reviewer should read your chapter, test it for
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correctness (eg try your examples) and change the status to "complete"
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correctness (e.g. try your examples) and change the status to "complete"
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when done.
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You are free to lift and convert as much material from the web site or
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The UI chapters should give an example or two of using mpl with your
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GUI and any relevant info, such as version, installation, config,
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etc... The backend chapters should cover backend specific
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configuration (eg PS only options), what features are missing, etc...
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configuration (e.g. PS only options), what features are missing, etc...
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Please feel free to add units, volunteer to review or author a
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chapter, etc...
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user's guide out. - MGD
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#. This section might also benefit from a little more detail on the
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customizations that are possible (eg an example fleshing out the rc
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customizations that are possible (e.g. an example fleshing out the rc
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options a little bit). Admittedly, this is pretty clear from
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‎doc/devel/release_guide.rst

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* Run :file:`unit/nose_tests.py` and make sure all the unit tests are passing
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* try some GUI examples, eg :file:`simple_plot.py` with GTKAgg, TkAgg, etc...
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* try some GUI examples, e.g. :file:`simple_plot.py` with GTKAgg, TkAgg, etc...
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* remove font cache and tex cache from :file:`.matplotlib` and test
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with and without cache on some example script
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then the "File Releases" tab. Go to the bottom and click "add
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release" and enter the package name but not the version number in
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the "Package Name" box. You will then be prompted for the "New
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release name" at which point you can add the version number, eg
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release name" at which point you can add the version number, e.g.
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‎doc/faq/howto_faq.rst

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Every matplotlib artist (see :ref:`artist-tutorial`) has a method
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called :meth:`~matplotlib.artist.Artist.findobj` that can be used to
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recursively search the artist for any artists it may contain that meet
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some criteria (eg match all :class:`~matplotlib.lines.Line2D`
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some criteria (e.g. match all :class:`~matplotlib.lines.Line2D`
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instances or match some arbitrary filter function). For example, the
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following snippet finds every object in the figure which has a
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backgrounds transparent when saving, but will not affect the displayed
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image on the screen. If you need finer grained control, eg you do not
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image on the screen. If you need finer grained control, e.g. you do not
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want full transparency or you to affect the screen displayed version
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as well, you can set the alpha properties directly. The figure has a
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:class:`matplotlib.patches.Rectangle` instance called *patch*
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on individual elements, e.g.::
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ax.plot(x, y, alpha=0.5)
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connecting
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(:meth:`matplotlib.backend_bases.FigureCanvasBase.mpl_connect`) to the
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"on_draw" signal (:class:`~matplotlib.backend_bases.DrawEvent`) and
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get the window extent there, and then do something with it, eg move
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get the window extent there, and then do something with it, e.g. move
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Skip dates where there is no data
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to leave out days on which there is no data, eg weekends. By passing
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When plotting time series, e.g. financial time series, one often wants
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to leave out days on which there is no data, e.g. weekends. By passing
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in dates on the x-xaxis, you get large horizontal gaps on periods when
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there is not data. The solution is to pass in some proxy x-data, eg
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there is not data. The solution is to pass in some proxy x-data, e.g.
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evenly sampled indices, and then use a custom formatter to format
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external tool to convert them to a movie. You can use `mencoder
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The sphinx website is a good resource for learning sphinx, but we have
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Once your documentation contributions are working (and hopefully

‎doc/faq/installing_faq.rst

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then you will need to set your PYTHONPATH, e.g.::
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<http://sourceforge.net/project/platformdownload.php?group_id=80706>`_
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site. Choose the files that match your version of python (e.g.
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``py2.5`` if you installed Python 2.5) which have the ``exe``
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‎doc/faq/troubleshooting_faq.rst

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‎doc/faq/usage_faq.rst

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renderer for user interfaces is ``Agg`` which uses the `Anti-Grain
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``WXAgg``, ``GTKAgg``, ``QT4Agg``, ``TkAgg``. In
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‎doc/pyplots/matplotlibrc

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# - an rgb tuple, such as (1.0, 0.5, 0.0)
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#interactive : False # see http://matplotlib.sourceforge.net/interactive.html
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