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NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3]
Following Lisp, other high-level programming languages which feature linked lists as primitive data structures have adopted an append. To append lists, as an operator, Haskell uses ++, OCaml uses @. Other languages use the + or ++ symbols to nondestructively concatenate a string, list, or array.
Matrix types (special types like bidiagonal/tridiagonal are not listed): Real – general (nonsymmetric) real; Complex – general (nonsymmetric) complex; SPD – symmetric positive definite (real)
SciPy. SciPy is a python programming language library to take advantage of Python's ability to handle large data sets. [4] ... Add languages ...
SciPy (pronounced / ˈ s aɪ p aɪ / "sigh pie" [2]) is a free and open-source Python library used for scientific computing and technical computing. [3]SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
It is best known for the early development and maintenance of the SciPy library of mathematics, science, and engineering algorithms [3] and for its Python for scientific computing distribution Enthought Canopy (formerly EPD). [4] The company was founded in 2001 by Travis Vaught and Eric Jones. [1] [2]
Add j to P. Remove j from R. Let A P be A restricted to the variables included in P. Let s be vector of same length as x. Let s P denote the sub-vector with indexes from P, and let s R denote the sub-vector with indexes from R. Set s P = ((A P) T A P) −1 (A P) T y; Set s R to zero; While min(s P) ≤ 0: Let α = min x i / x i − s i ...