(from the scilab homepage...)
Scilab is a scientific software package for numerical computations providing a powerful open computing environment for engineering and scientific applications.
Scilab is an open source software. Since 1994 it has been distributed freely along with the source code
... [More] via the Internet. It is currently used in educational and industrial environments around the world. Scilab is now maintained by Scilab Enterprises: http://www.scilab-enterprises.com/
Note that Scilab has been using code review since 2010 (explaining the diminution in term of number of commits). [Less]
A mathematical open source library written in C#/.Net, aiming to provide a self contained clean framework for symbolic algebraic and numerical / scientific computations.
OptaPlanner optimizes business resource usage. Every organization faces planning problems: provide products or services with a limited set of constrained resources (employees, assets, time and money). OptaPlanner optimizes such planning to do more business with less resources.
OptaPlanner is a
... [More] lightweight, embeddable planning engine written in Java™. It helps normal Java™ programmers solve constraint satisfaction problems efficiently. Under the hood, it combines optimization heuristics and metaheuristics with very efficient score calculation.
OptaPlanner is open source software, released under the Apache Software License. It is 100% pure Java™, runs on any JVM and is available in the Maven Central Repository too. [Less]
RobOptim is a generic C++ nonlinear optimization library for robotics. The core level allows users to define optimization problems in a generic way in order to use different back-ends.
Ceres Solver is a portable C++ library that allows for modeling and solving large complicated nonlinear least squares problems. Features include:
* A friendly API: build your objective function one term at a time.
* Automatic differentiation.
* Robust loss functions.
* Local
... [More] parameterizations.
* Threaded Jacobian evaluators and linear solvers.
* Levenberg-Marquardt and Dogleg (Powell & Subspace) solvers.
* Dense QR and Cholesky factorization (using Eigen) for small problems.
* Sparse Cholesky factorization (using SuiteSparse) for large sparse problems.
* Specialized solvers for bundle adjustment problems in computer vision.
* Iterative linear solvers for general sparse and bundle adjustment problems. [Less]
Compiler written to use as a reference to others who write real compilers. The emphasis is here on readability of code than anything else. It is written in Python for this very same reason. And even trivial things are commented or documented.
The idea is that one who wants to write a compiler
... [More] should be able to use this as a reference to get started and then write their compiler as efficiently as they want. [Less]
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