8000 Install guide tweaks by tacaswell · Pull Request #3397 · matplotlib/matplotlib · GitHub
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Aug 22, 2014
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Install guide tweaks #3397

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5300ddb
DOC : slight re-organization of INSTALL
tacaswell Aug 22, 2014
1b59d20
DOC : reorganized/simplified INSTALL
tacaswell Aug 22, 2014
584f6af
DOC : tweaked text of INSTALL
tacaswell Aug 22, 2014
104f963
DOC : mention miniconda
tacaswell Aug 22, 2014
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DOC : reorganized/simplified INSTALL
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@tacaswell
tacaswell committed Aug 22, 2014
commit 1b59d20418af67b0ea5d23fad568a06f46ed36ff
83 changes: 13 additions & 70 deletions INSTALL
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Expand Up @@ -12,8 +12,11 @@ installed, and how you want to use it. To avoid wading through all
the details (and potential complications) on this page, there are several
convenient options.

Installing pre-built packages
=============================

Most platforms : scientific Python distributions
================================================
------------------------------------------------

The first option is to use one of the pre-packaged python distributions that
already provide matplotlib built-in. The Continuum.io Python distribution
Expand All @@ -24,88 +27,26 @@ Linux platforms. Both of these distributions include matplotlib and *lots* of
other useful tools. Another excellent alternative for Windows users is
`Python (x, y) <https://code.google.com/p/pythonxy>`_ .


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I would consider mentioning miniconda since one of the most often raised complaints from users over Anaconda and Canopy is the large size and the many packages installed. Miniconda allows you to only install the packages you need.

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A reduction in the size of the current installers. The Anaconda installers were becoming too big, due to the inclusion of some large packages. These packages have been removed from the installers, but are still supported and available in the repository, meaning you can still use conda to install them. These packages include mayavi, netcdf4, vtk, and 10 others.

It looks like they have done some thing about that already, but added miniconda link as well.

Linux : using your package manager
==================================
----------------------------------

If you are on Linux, you might prefer to use your package manager. matplotlib
is packaged for almost every major Linux distribution.

* Debian / Ubuntu : ``sudo apt-get install python-matplotlib``
* Fedora / Redhat : ``sudo yum install python-matplotlib``

Mac OSX - using pip
===================
Mac OSX : using pip
-------------------

If you are on Mac OSX you can probably install matplotlib binaries using the
standard Python installation program `pip <https://pypi.python.org/pip>`_.
See :ref:`installing-osx-binaries`.

Manually installing pre-built packages
======================================

General instructions
--------------------

For some people, the prepackaged pythons discussed above are not an
option. That's OK, it's usually pretty easy to get a custom install
working. You will first need to find out if you have python installed
on your machine, and if not, install it. The official python builds
are available for download `here <http://www.python.org/download>`_,
but OS X users please read :ref:`which-python-for-osx`.

Once you have Python up and running, you will need to install `numpy
<http://www.numpy.org/>`_. numpy provides high-performance array data
structures and mathematical functions, and is a requirement for
matplotlib. You can test your progress::

>>> import numpy
>>> print numpy.__version__

matplotlib requires numpy version |minimum_numpy_version| or later.
Although it is not a requirement to use matplotlib, we strongly
encourage you to install `ipython <http://ipython.org>`_, which is an
interactive shell for python that is matplotlib-aware.

Next, we need to get matplotlib installed. We provide prebuilt
binaries for OS X and Windows on the matplotlib `download
<http://matplotlib.org/downloads.html>`_. Click on
the latest release of the "matplotlib" package, choose your python
version (2.6, 2.7, 3.3, or 3.4) and your platform (macosx or win32). If you
have any problems, please check the :ref:`installing-faq`, search
using Google, and/or post a question the `mailing list
<http://sourceforge.net/project/showfiles.php?group_id=80706>`_.

If you are on Debian/Ubuntu linux, it suffices to do::
See :ref:`install_osx_binaries`.

> sudo apt-get install python-matplotlib

Instructions for installing our OSX binaries are found in the FAQ
:ref:`install_osx_binaries`.


Once you have ipython, numpy and matplotlib installed, you can use
ipython's "pylab" mode to have a MATLAB-like environment that automatically
handles most of the configuration details for you, so you can get up
and running quickly::

johnh@flag:~> ipython -pylab
Python 2.4.5 (#4, Apr 12 2008, 09:09:16)
IPython 0.9.0 -- An enhanced Interactive Python.

Welcome to pylab, a matplotlib-based Python environment.
For more information, type 'help(pylab)'.

In [1]: x = randn(10000)

In [2]: hist(x, 100)

Note that when testing matplotlib installations from the interactive
python console, there are some issues relating to user interface
toolkits and interactive settings that are discussed in
:ref:`mpl-shell`.

Installing on Windows
---------------------
Windows
-------

If you don't already have Python installed, we recommend using
one of the `scipy-stack compatible Python distributions
Expand Down Expand Up @@ -175,6 +116,8 @@ sys.prefix\Lib\site-packages\mpl_toolkits respectively, and install
Pillow, MiKTeX, GhostScript, ffmpeg, avconv, mencoder, ImageMagick, and
`Inkscape <http://inkscape.org/>`_.



.. _install_from_source:

Installing from source
Expand Down
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