# numpy

**Repository Path**: mirrors_intel/numpy

## Basic Information

- **Project Name**: numpy
- **Description**: This fork of numpy/numpy is dedicated to improve its performance on CPU device, in particular Intel® Xeon® processors and Intel® Xeon Phi™ processors.
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-08
- **Last Updated**: 2025-10-11

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

DISCONTINUATION OF PROJECT.

This project will no longer be maintained by Intel.

Intel has ceased development and contributions including, but not limited to, maintenance, bug fixes, new releases, or updates, to this project. 

Intel no longer accepts patches to this project.

If you have an ongoing need to use this project, are interested in independently developing it, or would like to maintain patches for the open source software community, please create your own fork of this project. 
<div align="center">
  <img src="http://www.numpy.org/_static/numpy_logo.png"><br>
</div>
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NumPy is the fundamental package needed for scientific computing with Python.
This package contains:

   * 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.

It derives from the old Numeric code base and can be used as a replacement for Numeric. It also adds the features introduced by numarray and can be used to replace numarray.

More information can be found at the website:

* http://www.numpy.org

After installation, tests can be run (if ``nose`` is installed) with:

    python -c 'import numpy; numpy.test()'

The most current development version is always available from our
git repository:

* http://github.com/numpy/numpy