slackbuilds/development/numpy
B. Watson 16c4c131e7
development/numpy: Fix slack-desc.
2016-11-14 16:47:23 +07:00
..
README development/numpy: Updated for version 1.11.1. 2016-08-28 00:22:40 +01:00
README.ATLAS development/numpy: Updated for version 1.11.1. 2016-08-28 00:22:40 +01:00
numpy.SlackBuild development/numpy: Updated for version 1.11.1. 2016-08-28 00:22:40 +01:00
numpy.info development/numpy: Updated for version 1.11.1. 2016-08-28 00:22:40 +01:00
slack-desc development/numpy: Fix slack-desc. 2016-11-14 16:47:23 +07:00

README

NumPy is a general-purpose array-processing package designed to
efficiently manipulate large multi-dimensional arrays of arbitrary
records without sacrificing too much speed for small multi-dimensional
arrays.  NumPy is built on the Numeric code base and adds features
introduced by numarray as well as an extended C-API and the ability to
create arrays of arbitrary type which also makes NumPy suitable for
interfacing with general-purpose data-base applications.

There are also basic facilities for discrete fourier transform, basic
linear algebra and random number generation.

If you need to build numpy for debugging, set DEBUG=y. If you use software
which is having problems with numpy's new relaxed strides checking, set
NPY_RSC=0.

It is highly recommended to install libraries implementing BLAS and LAPACK
before installing numpy. You may choose between:
   a) BLAS and LAPACK (reference but unoptimized and thus slow)
   b) OpenBLAS (optimized, provides LAPACK too)
   c) ATLAS and LAPACK (optimized), good to read README.ATLAS
All these are available on SlackBuilds.org.

If you want to use the UMFPACK library instead of SuperLU to solve unsymmetric
sparse linear systems, then run this Slackbuild with NO_UMFPACK set to "no"
and then install scikit-umfpack on top of scipy. In this context, UMFPACK is an
optional dependency for numpy. Nevertheless, note that presently scikit-umfpack
is not available on SlackBuilds.org while its dependencies are.

NOTE: If you use this SlackBuild, numpy will run with the python version
      provided by Slackware Linux, which is presently 2.7.xx. If you'd like to
      use python 3.x then you have to install numpy with the numpy3 SlackBuild.

IMPORTANT: The version installed by this SlackBuild does NOT include the
           oldnumeric and numarray compatibility modules since starting with
           version 1.9.0 these modules got removed by the numpy developers.
           If you need these compatibility modules please consider the
           numpy-legacy SlackBuild.
           THUS: This SlackBuild conflicts with the numpy-legacy SlackBuild
                 which installs versions < 1.9.0!