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  2. List of numerical libraries - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_libraries

    SageMath is a large mathematical software application which integrates the work of nearly 100 free software projects and supports linear algebra, combinatorics, numerical mathematics, calculus, and more. [17] SciPy, [18] [19] [20] a large BSD-licensed library of scientific tools. De facto standard for scientific computations in Python.

  3. Gekko (optimization software) - Wikipedia

    en.wikipedia.org/wiki/Gekko_(optimization_software)

    GEKKO works on all platforms and with Python 2.7 and 3+. By default, the problem is sent to a public server where the solution is computed and returned to Python. There are Windows, MacOS, Linux, and ARM (Raspberry Pi) processor options to solve without an Internet connection.

  4. SageMath - Wikipedia

    en.wikipedia.org/wiki/SageMath

    Both binaries and source code are available for SageMath from the download page. If SageMath is built from source code, many of the included libraries such as OpenBLAS, FLINT, GAP (computer algebra system), and NTL will be tuned and optimized for that computer, taking into account the number of processors, the size of their caches, whether there is hardware support for SSE instructions, etc.

  5. SU2 code - Wikipedia

    en.wikipedia.org/wiki/SU2_code

    New in-memory Python wrapping of SU2 using SWIG with accompanying high-level API. Class enhancements for multiphysics applications, including interpolation and transfer. Free-form deformation (FFD) extensions, including Bézier curves and improved usability. Reorganization of the incompressible solver for future expansion.

  6. HiGHS optimization solver - Wikipedia

    en.wikipedia.org/wiki/HiGHS_optimization_solver

    Written in C++ and published under an MIT license, HiGHS provides programming interfaces to C, Python, Julia, Rust, R, JavaScript, Fortran, and C#. It has no external dependencies. A convenient thin wrapper to Python is available via the highspy PyPI package. Although generally single-threaded, some solver components can utilize multi-core ...

  7. Pyomo - Wikipedia

    en.wikipedia.org/wiki/Pyomo

    Pyomo allows users to formulate optimization problems in Python in a manner that is similar to the notation commonly used in mathematical optimization. Pyomo supports an object-oriented style of formulating optimization models, which are defined with a variety of modeling components: sets, scalar and multidimensional parameters, decision variables, objectives, constraints, equations ...

  8. Couenne - Wikipedia

    en.wikipedia.org/wiki/Couenne

    github.com /coin-or /Couenne Convex Over and Under ENvelopes for Nonlinear Estimation ( Couenne ) is an open-source library for solving global optimization problems, also termed mixed integer nonlinear optimization problems. [ 1 ]

  9. SymPy - Wikipedia

    en.wikipedia.org/wiki/SymPy

    SymPy is an open-source Python library for symbolic computation. It provides computer algebra capabilities either as a standalone application, as a library to other applications, or live on the web as SymPy Live [2] or SymPy Gamma. [3] SymPy is simple to install and to inspect because it is written entirely in Python with few dependencies.