mirror of
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38 lines
1.9 KiB
Text
38 lines
1.9 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
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software which is having problems with numpy's new relaxed strides
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checking, set NPY_RSC=0.
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It is highly recommended to install libraries implementing BLAS and
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LAPACK 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
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unsymmetric sparse linear systems, then run this Slackbuild with
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NO_UMFPACK set to "no" and then install scikit-umfpack on top of
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scipy. In this context, UMFPACK is an optional dependency for
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numpy.
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IMPORTANT: The version installed by this SlackBuild does NOT include the
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oldnumeric and numarray compatibility modules since
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starting with version 1.9.0 these modules got removed by
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the numpy developers. If you need these compatibility
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modules please consider the numpy-legacy SlackBuild which
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is available for python2 only and does not conflict with this
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installation of numpy.
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This python3-numpy SlackBuild creates bindings for python3 and can be
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installed without conflict alongside the python2-numpy SlackBuild.
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