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.. _building-from-source:
Building from source
====================
A general overview of building NumPy from source is given here, with detailed
instructions for specific platforms given seperately.
Prerequisites
-------------
Building NumPy requires the following software installed:
1) Python 2.6.x, 2.7.x, 3.2.x or newer
On Debian and derivatives (Ubuntu): python, python-dev (or python3-dev)
On Windows: the official python installer at
`www.python.org <http://www.python.org>`_ is enough
Make sure that the Python package distutils is installed before
continuing. For example, in Debian GNU/Linux, installing python-dev
also installs distutils.
Python must also be compiled with the zlib module enabled. This is
practically always the case with pre-packaged Pythons.
2) Compilers
To build any extension modules for Python, you'll need a C compiler.
Various NumPy modules use FORTRAN 77 libraries, so you'll also need a
FORTRAN 77 compiler installed.
Note that NumPy is developed mainly using GNU compilers. Compilers from
other vendors such as Intel, Absoft, Sun, NAG, Compaq, Vast, Porland,
Lahey, HP, IBM, Microsoft are only supported in the form of community
feedback, and may not work out of the box. GCC 4.x (and later) compilers
are recommended.
3) Linear Algebra libraries
NumPy does not require any external linear algebra libraries to be
installed. However, if these are available, NumPy's setup script can detect
them and use them for building. A number of different LAPACK library setups
can be used, including optimized LAPACK libraries such as ATLAS, MKL or the
Accelerate/vecLib framework on OS X.
Basic Installation
------------------
To install NumPy run::
python setup.py install
To perform an in-place build that can be run from the source folder run::
python setup.py build_ext --inplace
The NumPy build system uses ``distutils`` and ``numpy.distutils``.
``setuptools`` is only used when building via ``pip`` or with ``python
setupegg.py``. Using ``virtualenv`` should work as expected.
*Note: for build instructions to do development work on NumPy itself, see
:ref:`development-environment`*.
.. _parallel-builds:
Parallel builds
~~~~~~~~~~~~~~~
From NumPy 1.10.0 on it's also possible to do a parallel build with::
python setup.py build -j 4 install --prefix $HOME/.local
This will compile numpy on 4 CPUs and install it into the specified prefix.
to perform a parallel in-place build, run::
python setup.py build_ext --inplace -j 4
The number of build jobs can also be specified via the environment variable
``NPY_NUM_BUILD_JOBS``.
FORTRAN ABI mismatch
--------------------
The two most popular open source fortran compilers are g77 and gfortran.
Unfortunately, they are not ABI compatible, which means that concretely you
should avoid mixing libraries built with one with another. In particular, if
your blas/lapack/atlas is built with g77, you *must* use g77 when building
numpy and scipy; on the contrary, if your atlas is built with gfortran, you
*must* build numpy/scipy with gfortran. This applies for most other cases
where different FORTRAN compilers might have been used.
Choosing the fortran compiler
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
To build with g77::
python setup.py build --fcompiler=gnu
To build with gfortran::
python setup.py build --fcompiler=gnu95
For more information see::
python setup.py build --help-fcompiler
How to check the ABI of blas/lapack/atlas
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
One relatively simple and reliable way to check for the compiler used to build
a library is to use ldd on the library. If libg2c.so is a dependency, this
means that g77 has been used. If libgfortran.so is a a dependency, gfortran
has been used. If both are dependencies, this means both have been used, which
is almost always a very bad idea.
Disabling ATLAS and other accelerated libraries
-----------------------------------------------
Usage of ATLAS and other accelerated libraries in Numpy can be disabled
via::
BLAS=None LAPACK=None ATLAS=None python setup.py build
Supplying additional compiler flags
-----------------------------------
Additional compiler flags can be supplied by setting the ``OPT``,
``FOPT`` (for Fortran), and ``CC`` environment variables.
Building with ATLAS support
---------------------------
Ubuntu
~~~~~~
You can install the necessary package for optimized ATLAS with this command::
sudo apt-get install libatlas-base-dev
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