SCIPY PACKAGE CODE

Using NumPy in Python gives functionality comparable to MATLAB since they are both interpreted, and they both allow the user to write fast programs as long as most operations work on arrays or matrices instead of scalars. NumPy addresses the slowness problem partly by providing multidimensional arrays and functions and operators that operate efficiently on arrays using these requires rewriting some code, mostly inner loops, using NumPy. Mathematical algorithms written for this version of Python often run much slower than compiled equivalents. NumPy targets the CPython reference implementation of Python, which is a non-optimizing bytecode interpreter. It is not yet fully compatible with NumPy. In 2011, PyPy started development on an implementation of the NumPy API for PyPy. Support for Python 3 was added in 2011 with NumPy version 1.5.0.

To avoid installing the large SciPy package just to get an array object, this new package was separated and called NumPy. In early 2005, NumPy developer Travis Oliphant wanted to unify the community around a single array package and ported Numarray's features to Numeric, releasing the result as NumPy 1.0 in 2006.

SCIPY PACKAGE CODE

There was a desire to get Numeric into the Python standard library, but Guido van Rossum decided that the code was not maintainable in its state then. The last version of Numeric (v24.2) was released on 11 November 2005, while the last version of numarray (v1.5.2) was released on 24 August 2006. Numarray had faster operations for large arrays, but was slower than Numeric on small ones, so for a time both packages were used in parallel for different use cases. :вЂЉ10ДЄ new package called Numarray was written as a more flexible replacement for Numeric. :вЂЉ10 Other early contributors include David Ascher, Konrad Hinsen and Travis Oliphant.

Hugunin, a graduate student at the Massachusetts Institute of Technology (MIT), :вЂЉ10 joined the Corporation for National Research Initiatives (CNRI) in 1997 to work on JPython, leaving Paul Dubois of Lawrence Livermore National Laboratory (LLNL) to take over as maintainer. ДЄn implementation of a matrix package was completed by Jim Fulton, then generalized by Jim Hugunin and called Numeric (also variously known as the 'Numerical Python extensions' or 'NumPy'). In 1995 the special interest group (SIG) matrix-sig was founded with the aim of defining an array computing package among its members was Python designer and maintainer Guido van Rossum, who extended Python's syntax (in particular the indexing syntax ) to make array computing easier. The Python programming language was not originally designed for numerical computing, but attracted the attention of the scientific and engineering community early on.

Scipy package