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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 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 numpy-legacy3
- 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 numpy SlackBuild
- which installs versions >= 1.9.0!
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