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NumPy is the fundamental package for scientific computing with Python. It
contains among other things:
- a powerful N-dimensional array object
- sophisticated (broadcasting) functions
- tools for integrating C/C++ and Fortran code
- useful linear algebra, Fourier transform, and random number capabilities
Besides its obvious scientific uses, NumPy can also be used as an efficient
multi-dimensional container of generic data. Arbitrary data-types can be
defined. This allows NumPy to seamlessly and speedily integrate with a wide
variety of databases.
NOTE: If this package has multiple flavors (see below), then use one of them instead of the name specified above. NOTE: This is a Python port. Instead of py311-numpy listed in the above command, you can pick from the names under the Packages section.
===> The following configuration options are available for py311-numpy-2.4.6_1,1:
DOCS=on: Build and/or install documentation
====> Options available for the single BLASLIB: you have to select exactly one of them
BLIS=off: BLIS BLAS-like implementation
FLEXIBLAS=off: FlexiBLAS BLAS implementation
NETLIB=off: BLAS implementation from Netlib
OPENBLAS=on: OpenBLAS BLAS implementation
====> Use CPU-specific optimizations: you have to select exactly one of them
MIN=on: Minimum recommended CPU features (x86-64-v2 microarchitecture)
NATIVE=off: Use native optimization (-march=native)
NONE=off: Dispatched optimizations only (not recommended except old CPUs)
===> Use 'make config' to modify these settings