mirror of
https://github.com/Ponce/slackbuilds
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38 lines
2 KiB
Text
38 lines
2 KiB
Text
NumPy is a general-purpose array-processing package designed to
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efficiently manipulate large multi-dimensional arrays of arbitrary
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records without sacrificing too much speed for small multi-dimensional
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arrays. NumPy is built on the Numeric code base and adds features
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introduced by numarray as well as an extended C-API and the ability to
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create arrays of arbitrary type which also makes NumPy suitable for
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interfacing with general-purpose data-base applications.
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There are also basic facilities for discrete fourier transform, basic
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linear algebra and random number generation.
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If you need to build numpy for debugging, set DEBUG=y. If you use software
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which is having problems with numpy's new relaxed strides checking, set
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NPY_RSC=0.
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It is highly recommended to install libraries implementing BLAS and LAPACK
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before installing numpy. You may choose between:
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a) BLAS and LAPACK (reference but unoptimized and thus slow)
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b) OpenBLAS (optimized, provides LAPACK too)
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c) ATLAS and LAPACK (optimized), good to read README.ATLAS
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All these are available on SlackBuilds.org.
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If you want to use the UMFPACK library instead of SuperLU to solve unsymmetric
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sparse linear systems, then run this Slackbuild with NO_UMFPACK set to "no"
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and then install scikit-umfpack on top of scipy. In this context, UMFPACK is an
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optional dependency for numpy. Nevertheless, note that presently scikit-umfpack
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is not available on SlackBuilds.org while its dependencies are.
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NOTE: If you use this SlackBuild numpy will run with the python 3 version
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installed on your system. If you'd like to use python 2.7.xx as
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provided by Slackware Linux then you have to install it with the
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numpy-legacy SlackBuild.
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IMPORTANT: This version, 1.8.2, is the latest to include the oldnumeric
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and numarray compatibility modules. Starting with version
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1.9.0 these modules got removed by the numpy developers.
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THUS: This SlackBuild conflicts with the numpy3 SlackBuild
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which installs versions >= 1.9.0!
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