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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.
-
-NOTE: If you use this SlackBuild numpy will run with the python 3 version
- installed on your system. If you'd like to use python 2.7.xx as
- provided by Slackware Linux then you have to install it with the
- numpy-legacy SlackBuild.
-
-IMPORTANT: This version, 1.8.2, is the latest to include the oldnumeric
- and numarray compatibility modules. Starting with version
- 1.9.0 these modules got removed by the numpy developers.
- THUS: This SlackBuild conflicts with the numpy3 SlackBuild
- which installs versions >= 1.9.0!