NumPy adds a fast and sophisticated array facility to the Python language and is the fundamental package needed for scientific computing with Python.
The NumPy 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.
Numeric users should find the transition relatively easy (although not without some effort). There is a module (numpy.oldnumeric.alter_code1) that can make most of the necessary changes to your Python code that used Numeric to work with NumPy`s Numeric compatibility module.
Users of num array can also transition their code using the numpy.numarray compatibility layer and a similar module (numpy.numarray.alter_code1).
NOTE: NumPy is licensed and distributed under the terms of an OSI-Approved Open Source License.
Requirements:
· Python 2.5 or later
What`s New in This Release: [ read full changelog ]
· #937: linalg: lstsq should always return real residual
· #1196: lib: fix negative indices in s_ and index_exp
· #1287: core: fix uint64 -> Python int cast
· #1491: core: richcompare should return Py_NotImplemented when undefined
· #1517: lib: close file handles after use in numpy.lib.npyio.*
· 1605: core: ensure PEP 3118 buffers can be released in exception handler
· #1617: core: fix clongdouble cast to Python complex()
· #1625: core: fix detection for ``isfinite`` routine
· #1626: core: fix compilation with Solaris 10 / Sun Studio 12.1
· #----: f2py: make f2py script runnable on Python 3
· #1604: distutils: potential infinite loop in numpy.distutils
· #1609: core: use accelerated BLAS, when available
· #1610: core: ensure tofile and fromfile maintain file handle positions
