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Solving differential equations, nonlinear approximations, Monte-Carlo calculations, engineering math, interactive plots, Python an R interface J: Jsoftware 1989 1990 J9.5.1 20 December 2023: Free GPL: online access to: J Application Library (JAL) Julia: Jeff Bezanson, Stefan Karpinski, Viral B. Shah, Alan Edelman: 2009 2012 1.11.2 2 December ...
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.
1.0.2 / 10.2019 Free GPL: 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
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]
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
It was released alongside PyPy 2.3.1 and bears the same version number. On 21 March 2017, the PyPy project released version 5.7 of both PyPy and PyPy3, with the latter introducing beta-quality support for Python 3.5. [25] On 26 April 2018, version 6.0 was released, with support for Python 2.7 and 3.5 (still beta-quality on Windows). [26]
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.
Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...