The fundamental package needed for scientific computing with Python is called NumPy. This package contains:
- a powerful N-dimensional array object
- sophisticated (broadcasting) functions
- basic linear algebra functions
- basic Fourier transforms
- sophisticated random number capabilities
- tools for integrating Fortran code
- tools for integrating C/C++ code
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. NumPy 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 also be used to replace Numarray.
released on 19 September 2016
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|BSD 3Clause||Deborah Nicholson||9 July 2008|
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This entry (in part or in whole) was last reviewed on 25 February 2017.
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