python-scipy 0.18.1-2 / usr / lib / python2.7 / dist-packages / scipy / INSTALL.rst.txt

Building and installing SciPy
+++++++++++++++++++++++++++++

See https://www.scipy.org/Installing_SciPy/

.. Contents::


INTRODUCTION
============

It is *strongly* recommended that you use either a complete scientific Python
distribution or binary packages on your platform if they are available, in
particular on Windows and Mac OS X. You should not attempt to build SciPy if
you are not familiar with compiling software from sources.

Recommended distributions are:

  - Enthought Canopy (https://www.enthought.com/products/canopy/)
  - Anaconda (https://www.continuum.io/anaconda)
  - Python(x,y) (http://python-xy.github.io/)
  - WinPython (https://winpython.github.io/)

The rest of this install documentation does summarize how to build Scipy.  Note
that more extensive (and possibly more up-to-date) build instructions are
maintained at http://scipy.org/scipylib/building/index.html


PREREQUISITES
=============

SciPy requires the following software installed for your platform:

1) Python__ 2.7 or >= 3.4

__ http://www.python.org

2) NumPy__ >= 1.7.1

__ http://www.numpy.org/

3) For building from source: setuptools__

__ https://github.com/pypa/setuptools

4) If you want to build the documentation: Sphinx__ >= 1.2.1

__ http://sphinx-doc.org/

5) If you want to build SciPy master or other unreleased version from source
   (Cython-generated C sources are included in official releases):
   Cython__ >= 0.22

__ http://cython.org/

Windows
-------

Compilers
~~~~~~~~~

There are two ways to build Scipy on Windows:

1. Use Intel MKL, and Intel compilers or ifort + MSVC.  This is currently the
   most robust method.
2. Use MingwPy__.  This is a GCC toolchain that will be used in the future to
   distribute Scipy binaries on PyPi.  See the MingwPy website for details.

__ https://mingwpy.github.io/ 


Mac OS X
--------

Compilers
~~~~~~~~~

It is recommended to use gcc or clang, both work fine. Gcc is available for
free when installing Xcode, the developer toolsuite on Mac OS X. You also
need a fortran compiler, which is not included with Xcode: you should use a
recent gfortran from an OS X package manager (like Homebrew).

Please do NOT use gfortran from `hpc.sourceforge.net <http://hpc.sourceforge.net>`_,
it is known to generate buggy scipy binaries.


Blas/Lapack
~~~~~~~~~~~

Mac OS X includes the Accelerate framework: it should be detected without any
intervention when building SciPy.

Linux
-----

Most common distributions include all the dependencies.  You will need to
install a BLAS/LAPACK (all of ATLAS, OpenBLAS, MKL work fine) including
development headers, as well as development headers for Python itself.  Those
are typically packaged as python-dev


INSTALLING SCIPY
================

For the latest information, see the web site:

  https://www.scipy.org


Development version from Git
----------------------------
Use the command::

  git clone https://github.com/scipy/scipy.git

  cd scipy
  git clean -xdf
  python setup.py install --user
 
Documentation
-------------
Type::

  cd scipy/doc
  make html

From tarballs
-------------
Unpack ``SciPy-<version>.tar.gz``, change to the ``SciPy-<version>/``
directory, and run::

  python setup.py install --user

This may take several minutes to half an hour depending on the speed of your
computer.  To install to a user-specific location instead, run::

  python setup.py install --prefix=$MYDIR

where $MYDIR is, for example, $HOME or $HOME/usr.

        ** Note 1: On Unix, you should avoid installing in /usr, but rather in
        /usr/local or somewhere else. /usr is generally 'owned' by your package
        manager, and you may overwrite a packaged Scipy this way.

TESTING
=======

To test SciPy after installation (highly recommended), execute in Python

   >>> import scipy
   >>> scipy.test()

To run the full test suite use

   >>> scipy.test('full')

Please note that you must have version 1.0 or later of the 'nose' test
framework installed in order to run the tests.  More information about nose is
available on the website__.

__ https://nose.readthedocs.org/en/latest/

COMPILER NOTES
==============

You can specify which Fortran compiler to use by using the following
install command::

  python setup.py config_fc --fcompiler=<Vendor> install

To see a valid list of <Vendor> names, run::

  python setup.py config_fc --help-fcompiler

IMPORTANT: It is highly recommended that all libraries that scipy uses (e.g.
BLAS and ATLAS libraries) are built with the same Fortran compiler. In most
cases, if you mix compilers, you will not be able to import Scipy at best, have
crashes and random results at worst.

UNINSTALLING
============

When installing with ``python setup.py install`` or a variation on that, you do
not get proper uninstall behavior for an older already installed Scipy version.
In many cases that's not a problem, but if it turns out to be an issue, you
need to manually uninstall it first (remove from e.g. in
``/usr/lib/python3.4/site-packages/scipy`` or
``$HOME/lib/python3.4/site-packages/scipy``).

Alternatively, you can use ``pip install . --user`` instead of ``python
setup.py install --user`` in order to get reliable uninstall behavior.
The downside is that ``pip`` doesn't show you a build log and doesn't support
incremental rebuilds (it copies the whole source tree to a tempdir).

TROUBLESHOOTING
===============

If you experience problems when building/installing/testing SciPy, you
can ask help from scipy-user@scipy.org or scipy-dev@scipy.org mailing
lists. Please include the following information in your message:

NOTE: You can generate some of the following information (items 1-5,7)
in one command:: 

  python -c 'from numpy.f2py.diagnose import run; run()'

1) Platform information::

     python -c 'import os, sys; print(os.name, sys.platform)'
     uname -a
     OS, its distribution name and version information
     etc.

2) Information about C,C++,Fortran compilers/linkers as reported by
   the compilers when requesting their version information, e.g.,
   the output of
   ::

     gcc -v
     g77 --version

3) Python version::

     python -c 'import sys; print(sys.version)'

4) NumPy version::

     python -c 'import numpy; print(numpy.__version__)'

5) ATLAS version, the locations of atlas and lapack libraries, building
   information if any. If you have ATLAS version 3.3.6 or newer, then
   give the output of the last command in
   ::

     cd scipy/Lib/linalg
     python setup_atlas_version.py build_ext --inplace --force
     python -c 'import atlas_version'

7) The output of the following commands
   ::

     python INSTALLDIR/numpy/distutils/system_info.py

   where INSTALLDIR is, for example, /usr/lib/python3.4/site-packages/.

8) Feel free to add any other relevant information.
   For example, the full output (both stdout and stderr) of the SciPy
   installation command can be very helpful. Since this output can be
   rather large, ask before sending it into the mailing list (or
   better yet, to one of the developers, if asked).

9) In case of failing to import extension modules, the output of
   ::

     ldd /path/to/ext_module.so

   can be useful.