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‎INSTALL

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@@ -9,19 +9,36 @@ Installing
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There are many different ways to install matplotlib, and the best way
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depends on what operating system you are using, what you already have
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installed, and how you want to use it. To avoid wading through all
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the details (and potential complications) on this page, the easiest
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thing for you to do is use one of the pre-packaged python
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distributions that already provide matplotlib built-in. The Continuum.io
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Python distribution `(Anaconda)
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<https://store.continuum.io/cshop/anaconda/>`_ and the Enthought
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distribution `(Canopy) <https://www.enthought.com/products/canopy/>`_
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are both excellent choices that "just work" out of the box for any
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platform. Both of these packages include matplotlib and
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*lots* of other useful tools.
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Another excellent alternative for Windows users is `Python (x, y)
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<https://code.google.com/p/pythonxy>`_ . matplotlib is also packaged for almost
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every major Linux distribution. So if you are on Linux, your package
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manager will probably provide matplotlib prebuilt.
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the details (and potential complications) on this page, there are several
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convenient options.
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Most platforms : scientific Python distributions
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================================================
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The first option is to use one of the pre-packaged python distributions that
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already provide matplotlib built-in. The Continuum.io Python distribution
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`(Anaconda) <https://store.continuum.io/cshop/anaconda/>`_ and the Enthought
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distribution `(Canopy) <https://www.enthought.com/products/canopy/>`_ are both
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excellent choices that "just work" out of the box for Windows, OSX and common
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Linux platforms. Both of these distributions include matplotlib and *lots* of
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other useful tools. Another excellent alternative for Windows users is
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`Python (x, y) <https://code.google.com/p/pythonxy>`_ .
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Linux : using your package manager
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==================================
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If you are on Linux, you might prefer to use your package manager. matplotlib
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is packaged for almost every major Linux distribution.
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* Debian / Ubuntu : ``sudo apt-get install python-matplotlib``
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* Fedora / Redhat : ``sudo yum install python-matplotlib``
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Mac OSX - using pip
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===================
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If you are on Mac OSX you can probably install matplotlib binaries using the
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standard Python installation program `pip <https://pypi.python.org/pip>`_.
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See :ref:`installing-osx-binaries`.
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Manually installing pre-built packages
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======================================
@@ -36,7 +53,7 @@ on your machine, and if not, install it. The official python builds
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are available for download `here <http://www.python.org/download>`_,
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but OS X users please read :ref:`which-python-for-osx`.
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Once you have python up and running, you will need to install `numpy
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Once you have Python up and running, you will need to install `numpy
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<http://www.numpy.org/>`_. numpy provides high-performance array data
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structures and mathematical functions, and is a requirement for
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matplotlib. You can test your progress::
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toolkits and interactive settings that are discussed in
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:ref:`mpl-shell`.
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Installing on Windows
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---------------------
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.. note::
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If you are on debian/ubuntu, you can get all the dependencies
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If you are on Debian/Ubuntu, you can get all the dependencies
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required to build matplotlib with::
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sudo apt-get build-dep python-matplotlib

‎doc/api/artist_api.rst

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artists
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*******
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.. inheritance-diagram:: matplotlib.patches matplotlib.lines matplotlib.text matplotlib.offsetbox
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.. inheritance-diagram:: matplotlib.patches matplotlib.lines matplotlib.text matplotlib.offsetbox matplotlib.image
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:parts: 2
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:mod:`matplotlib.artist`
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:undoc-members:
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:show-inheritance:
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:mod:`matplotlib.lines`
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=======================
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.. automodule:: matplotlib.lines
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:members:
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:undoc-members:
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:show-inheritance:
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:mod:`matplotlib.patches`
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=========================
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.. automodule:: matplotlib.patches
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:members:
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:undoc-members:
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:show-inheritance:
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:mod:`matplotlib.text`
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======================
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.. automodule:: matplotlib.text
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:members:
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:undoc-members:
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:show-inheritance:
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:mod:`matplotlib.offsetbox`
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===========================
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.. automodule:: matplotlib.offsetbox
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/api/image_api.rst

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*****
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image
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*****
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:mod:`matplotlib.image`
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=======================
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.. automodule:: matplotlib.image
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/api/index.rst

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finance_api.rst
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font_manager_api.rst
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gridspec_api.rst
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image_api.rst
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legend_api.rst
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lines_api.rst
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markers_api.rst
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mathtext_api.rst
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mlab_api.rst
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offsetbox_api.rst
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patches_api.rst
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path_api.rst
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patheffects_api.rst
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pyplot_api.rst
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sankey_api.rst
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spines_api.rst
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text_api.rst
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ticker_api.rst
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tight_layout_api.rst
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tri_api.rst

‎doc/api/lines_api.rst

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*****
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lines
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*****
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:mod:`matplotlib.lines`
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=======================
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.. automodule:: matplotlib.lines
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/api/offsetbox_api.rst

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*********
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offsetbox
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*********
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:mod:`matplotlib.offsetbox`
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===========================
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.. automodule:: matplotlib.offsetbox
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/api/patches_api.rst

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*******
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patches
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*******
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:mod:`matplotlib.patches`
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=========================
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.. automodule:: matplotlib.patches
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/api/text_api.rst

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****
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text
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****
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:mod:`matplotlib.text`
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=======================
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.. automodule:: matplotlib.text
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/faq/howto_faq.rst

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.. _howto-supress_offset:
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How to prevent ticklabels from having an offset
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-----------------------------------------------
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The default formatter will use an offset to reduce
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the length of the ticklabels. To turn this feature
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off on a per-axis basis::
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ax.get_xaxis().get_major_formatter().set_useOffset(False)
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set the rcParam ``axes.formatter.useoffset``, or use a different
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.. seealso::
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:ref:`howto-webapp` for information about running matplotlib inside
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of a web application.
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in these environments. Most importantly, you need to decide what
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kinds of images you want to generate (PNG, PDF, SVG) and configure the
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appropriate default backend. For 99% of users, this will be the Agg
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backend, which uses the C++ `antigrain <http://antigrain.com>`_
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backend, which uses the C++
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`antigrain <http://agg.sourceforge.net/antigrain.com/index.html>`_
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rendering engine to make nice PNGs. The Agg backend is also
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configured to recognize requests to generate other output formats
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(PDF, PS, EPS, SVG). The easiest way to configure matplotlib to use
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import sys
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fig.savefig(sys.stdout)
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Here is an example using `Pillow <http://python-imaging.github.io/>__.
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Here is an example using `Pillow <http://python-imaging.github.io/>`_.
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First, the figure is saved to a StringIO object which is then fed to
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Pillow for further processing::
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