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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]
It provides a rich Excel-like user interface and its built-in vector programming language FPScript has a syntax similar to MATLAB. FreeMat, an open-source MATLAB-like environment with a GPL license. GNU Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command-line interface for solving ...
MATLAB (an abbreviation of "MATrix LABoratory" [18]) is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks.MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
Non-free Intel Simplified Software License Numerical analysis library optimized for Intel CPUs and GPUs. C++ SYCL based reference API implementation available in source for free. Math.NET Numerics: C. Rüegg, M. Cuda, et al. C# 2009 5.0.0 / 04.2022 Free MIT License: C# numerical analysis library with linear algebra support Matrix Template Library
FreeMat is a free open-source numerical computing environment and programming language, [1] similar to MATLAB and GNU Octave. [2] In addition to supporting many MATLAB functions and some IDL functionality, it features a codeless interface to external C, C++, and Fortran code, further parallel distributed algorithm development (via MPI), and has plotting and 3D visualization capabilities. [3]
Mesh generation is deceptively difficult: it is easy for humans to see how to create a mesh of a given object, but difficult to program a computer to make good decisions for arbitrary input a priori. There is an infinite variety of geometry found in nature and man-made objects. Many mesh generation researchers were first users of meshes.
Both MATLAB and GNU Octave natively support linear algebra operations such as matrix multiplication, matrix inversion, and the numerical solution of system of linear equations, even using the Moore–Penrose pseudoinverse. [7] [8] The Nial example of the inner product of two arrays can be implemented using the native matrix multiplication operator.
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] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.