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  2. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    To avoid installing the large SciPy package just to get an array object, this new package was separated and called NumPy. Support for Python 3 was added in 2011 with NumPy version 1.5.0. [15] In 2011, PyPy started development on an implementation of the NumPy API for PyPy. [16] As of 2023, it is not yet fully compatible with NumPy. [17]

  3. List of numerical libraries - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_libraries

    NumPy, a BSD-licensed library that adds support for the manipulation of large, multi-dimensional arrays and matrices; it also includes a large collection of high-level mathematical functions. NumPy serves as the backbone for a number of other numerical libraries, notably SciPy. De facto standard for matrix/tensor operations in Python.

  4. Comparison of linear algebra libraries - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_linear...

    Blitz++ is a C++ template class library that provides high-performance multidimensional array containers for scientific computing. Boost uBLAS J. Walter, M. Koch C++ 2000 1.84.0 / 12.2023 Free Boost Software License uBLAS is a C++ template class library that provides BLAS level 1, 2, 3 functionality for dense, packed and sparse matrices. Dlib

  5. Linear congruential generator - Wikipedia

    en.wikipedia.org/wiki/Linear_congruential_generator

    If a ≡ +3, X alternates ±1↔±3, while if a ≡ −3, X alternates ±1↔∓3 (all modulo 8). It can be shown that this form is equivalent to a generator with modulus m/4 and c ≠ 0. [1] A more serious issue with the use of a power-of-two modulus is that the low bits have a shorter period than the high bits.

  6. Matrix multiplication algorithm - Wikipedia

    en.wikipedia.org/wiki/Matrix_multiplication...

    The definition of matrix multiplication is that if C = AB for an n × m matrix A and an m × p matrix B, then C is an n × p matrix with entries = =. From this, a simple algorithm can be constructed which loops over the indices i from 1 through n and j from 1 through p, computing the above using a nested loop:

  7. Array programming - Wikipedia

    en.wikipedia.org/wiki/Array_programming

    The following mathematical statements hold when A is a full rank square matrix: A^-1 *(A * x)==A^-1 * (b) (A^-1 * A)* x ==A^-1 * b (matrix-multiplication associativity) x = A^-1 * b. where == is the equivalence relational operator. The previous statements are also valid MATLAB expressions if the third one is executed before the others ...

  8. Basic Linear Algebra Subprograms - Wikipedia

    en.wikipedia.org/wiki/Basic_Linear_Algebra...

    ATLAS is a portable library that automatically optimizes itself for an arbitrary architecture. iMKL is a freeware [7] and proprietary [8] vendor library optimized for x86 and x86-64 with a performance emphasis on Intel processors. [9] OpenBLAS is an open-source library that is hand-optimized for many of the popular architectures.

  9. Matrix multiplication - Wikipedia

    en.wikipedia.org/wiki/Matrix_multiplication

    Matrix multiplication is thus a basic tool of linear algebra, and as such has numerous applications in many areas of mathematics, as well as in applied mathematics, statistics, physics, economics, and engineering. [3] [4] Computing matrix products is a central operation in all computational applications of linear algebra.