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‎doc/README.txt

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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/api/api_changes.rst

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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 every time 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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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/documenting_mpl.rst

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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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files are duplicated and large)
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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 hyphen separated, descriptive labels for section references, eg::
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use hyphen 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/license.rst

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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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clearly state the licenses you are using.
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Why BSD compatible?

‎doc/devel/release_guide.rst

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* Run :file:`unit/memleak_hawaii3.py` and make sure there are no
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memory leaks
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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

‎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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`set_color` property and makes the object blue::
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backgrounds transparent when saving, but will not affect the displayed
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image on the screen.
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If you need finer grained control, eg you do not want full transparency
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If you need finer grained control, e.g., you do not want full transparency
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or you want to affect the screen displayed version as well, you can set
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the alpha properties directly. The figure has a
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:class:`~matplotlib.patches.Rectangle` instance called *patch*
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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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the left of the canvas over; see :ref:`event-handling-tutorial`.
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Here is an example that gets a bounding box in relative figure coordinates
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Skip dates where there is no data
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---------------------------------
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When plotting time series, eg financial time series, one often wants
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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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these as dates. The example below shows how to use an 'index formatter'
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to achieve the desired plot::
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The sphinx website is a good resource for learning sphinx, but we have
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put together a cheat-sheet at :ref:`documenting-matplotlib` which
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shows you how to get started, and outlines the matplotlib conventions
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and extensions, eg for including plots directly from external code in
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and extensions, e.g., for including plots directly from external code in
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your documents.
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Once your documentation contributions are working (and hopefully

‎doc/faq/installing_faq.rst

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If you have already installed Python and numpy, you can use one of the
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matplotlib binary installers for windows -- you can get these from the
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`download <http://matplotlib.org/downloads.html>`_ site. Chose the files with
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an ``.exe`` extension that match your version of Python (eg ``py2.7`` if you
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an ``.exe`` extension that match your version of Python (e.g., ``py2.7`` if you
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installed Python 2.7). If you haven't already installed Python, you can get
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the official version from the `Python web site
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<http://python.org/download/>`_.

‎doc/faq/usage_faq.rst

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renderer for user interfaces is ``Agg`` which uses the `Anti-Grain
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agg rendering, eg
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agg rendering, e.g.,
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``WXAgg``, ``GTKAgg``, ``QT4Agg``, ``TkAgg``. In
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‎doc/users/artists.rst

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====================== =========================================================
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Accessor method Description
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====================== =========================================================
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get_scale The scale of the axis, eg 'log' or 'linear'
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get_scale The scale of the axis, e.g., 'log' or 'linear'
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get_view_interval The interval instance of the axis view limits
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‎doc/users/event_handling.rst

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:class:`~matplotlib.artist.Artist` (e.g., a matplotlib
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points and the the artist will fire off an event if its data is
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within epsilon of the mouse event. For some artists like lines
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the pick event that is generated, eg the indices of the data
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``function``
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coords in display space, e.g., pixels from left, bottom) and xdata,
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ydata (the coords in data space). Additionally, you can get
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‎doc/users/license.rst

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the `PSF <http://www.python.org/psf/license>`_ license. See the Open
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Source Initiative `licenses page
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<http://www.opensource.org/licenses>`_ for details on individual
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licenses. Non-BSD compatible licenses (eg LGPL) are acceptable in
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licenses. Non-BSD compatible licenses (e.g., LGPL) are acceptable in
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matplotlib toolkits. For a discussion of the motivations behind the
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‎doc/users/path_tutorial.rst

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:meth:`~matplotlib.axes.Axes.bar`, which create a number of
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primitives, e.g., a bunch of Rectangles, can usually be implemented more
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efficiently using a compound path. The reason ``bar`` creates a list
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of rectangles and not a compound path is largely historical: the
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:class:`~matplotlib.path.Path` code is comparatively new and ``bar``
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predates it. While we could change it now, it would break old code,
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efficiency reasons, e.g., you are creating an animated bar plot.
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‎doc/users/pyplot_tutorial.rst

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‎doc/users/recipes.rst

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a higher degree of precision, e.g., giving us the exact date out mouse is
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hovering over. To fix the first problem, we can use
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‎doc/users/text_intro.rst

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matplotlib has excellent text support, including mathematical
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or PDF, what you see on the screen is what you get in the hardcopy.
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`freetype2 <http://freetype.sourceforge.net/index2.html>`_ support
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‎doc/users/text_props.rst

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size or fontsize [ size in points | relative size, e.g., ``'smaller'``, ``'x-large'`` ]
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style or fontstyle [ ``'normal'`` | ``'italic'`` | ``'oblique'``]
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‎doc/users/transforms_tutorial.rst

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‎doc/users/whats_new.rst

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the rest markup in the ipython shell also confused the docstrings.
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‎examples/README.txt

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‎examples/api/date_index_formatter.py

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‎examples/api/font_family_rc.py

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"""
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‎examples/pylab_examples/accented_text.py

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\ddot{o}. The shortcuts are also provided, e.g.,: \"o \'e \`e \~n \.x
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