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-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.
-
-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!
-
-This numpy3 SlackBuild creates bindings for python3 and can be installed
-without conflict alongside the standard numpy SlackBuild.