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Python (programming language) scientific libraries (36 P) Pages in category "Python (programming language) libraries" The following 43 pages are in this category, out of 43 total.
GEKKO is an extension of the APMonitor Optimization Suite but has integrated the modeling and solution visualization directly within Python. A mathematical model is expressed in terms of variables and equations such as the Hock & Schittkowski Benchmark Problem #71 [ 2 ] used to test the performance of nonlinear programming solvers.
Dask is an open-source Python library for parallel computing.Dask [1] scales Python code from multi-core local machines to large distributed clusters in the cloud. Dask provides a familiar user interface by mirroring the APIs of other libraries in the PyData ecosystem including: Pandas, scikit-learn and NumPy.
Construct, a python library for the declarative construction and deconstruction of data structures; Genshi, a template engine for XML-based vocabularies; IPython, a development shell both written in and designed for Python; Jinja, a Python-powered template engine, inspired by Django's template engine; Kid, simple template engine for XML-based ...
Hermes Project: C++/Python library for rapid prototyping of space- and space-time adaptive hp-FEM solvers. IML++ is a C++ library for solving linear systems of equations, capable of dealing with dense, sparse, and distributed matrices. IT++ is a C++ library for linear algebra (matrices and vectors), signal processing and communications ...
The FEniCS Project is a collection of free and open-source software components with the common goal to enable automated solution of differential equations.The components provide scientific computing tools for working with computational meshes, finite-element variational formulations of ordinary and partial differential equations, and numerical linear algebra.
Theano is a Python library and optimizing compiler for manipulating and evaluating mathematical expressions, especially matrix-valued ones. [2] In Theano, computations are expressed using a NumPy -esque syntax and compiled to run efficiently on either CPU or GPU architectures.
MicroPython is a lean and efficient implementation of Python with libraries similar to those in Python. [25] Some standard Python libraries have an equivalent library in MicroPython renamed to distinguish between the two. MicroPython libraries are smaller with less popular features removed or modified to save memory. [19]