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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 an open-source cross-platform integrated development environment (IDE) for scientific programming in the Python language. Spyder integrates with a number of prominent packages in the scientific Python stack, including NumPy, SciPy, Matplotlib, pandas, IPython, SymPy and Cython, as well as other open-source software. [4] [5]
It can be downloaded or used through a web site. SageMath comprises a variety of other free packages, with a common interface and language. SageMath is developed in Python. SageMath was initiated by William Stein, of Harvard University in 2005 for his personal project in number theory. It was originally known as "HECKE and Manin".
General purpose numerical analysis library with C++, C#, Python, FreePascal interfaces. Armadillo [2] [3] NICTA: C++ 2009 12.6.6 / 10.2023 Free Apache License 2.0: C++ template library for linear algebra; includes various decompositions and factorisations; syntax is similar to MATLAB. ATLAS: R. Clint Whaley et al. C 2001 3.10.3 / 07.2016 Free BSD
10 June 2020: Not free (commercial), Free (non-commercial) Proprietary: A modern dialect of APL, enhanced with features for functional and object-oriented programming. Euler Math Toolbox: René Grothmann 1987 1988 2022-02-10 10 February 2022: Free GPL: Also a computer algebra system through interface with Maxima: Fityk: Marcin Wojdyr 2002 1.3.1 ...
Yahoo! Groups uses Python "to maintain its discussion groups" [citation needed] YouTube uses Python "to produce maintainable features in record times, with a minimum of developers" [25] Enthought uses Python as the main language for many custom applications in Geophysics, Financial applications, Astrophysics, simulations for consumer product ...
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.
Given a transformation between input and output values, described by a mathematical function, optimization deals with generating and selecting the best solution from some set of available alternatives, by systematically choosing input values from within an allowed set, computing the output of the function and recording the best output values found during the process.