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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 is designed to follow the structure and workflow of NumPy as closely as possible and works with TensorFlow as well as other frameworks such as PyTorch. The primary functions of JAX are: [71] grad: automatic differentiation; jit: compilation; vmap: auto-vectorization; pmap: SPMD programming
BASIC (Beginners' All-purpose Symbolic Instruction Code) [1] is a family of general-purpose, high-level programming languages designed for ease of use. The original version was created by John G. Kemeny and Thomas E. Kurtz at Dartmouth College in 1963.
Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.
Open-source software, NumPy, SciPy, Anaconda (Python distribution), Probabilistic programming Travis Oliphant is an American data scientist and businessman. He is a co-founder [ 2 ] of NumFOCUS , a 501(c)(3) nonprofit charity in the United States, and sits on its advisory board. [ 3 ]
The PyPy project also accepts donations through its status blog pages. [36] As of 2013, a variety of sub-projects had funding: Python 3 version compatibility, built-in optimized NumPy support for numerical calculations and software transactional memory support to allow better parallelism.
Some special cases of nonlinear programming have specialized solution methods: If the objective function is concave (maximization problem), or convex (minimization problem) and the constraint set is convex, then the program is called convex and general methods from convex optimization can be used in most cases.
In Latin hypercube sampling one must first decide how many sample points to use and for each sample point remember in which row and column the sample point was taken. Such configuration is similar to having N rooks on a chess board without threatening each other. In orthogonal sampling, the sample space is partitioned into equally probable ...