ESKit is a portable C library that provides implementations of some self-adaptive evolution strategies. It features a simple API, comprehensive documentation, three state of the art self-adaptive evolution strategies (Isotropic CSA-ES, CMA-ES, and Separable CMA-ES), and can optionaly uses LAPACK. The implementation strictly follows the published papers introducing those evolution strategies and performs as in the published papers. A basic benchmark program is provided.
Polymul is a self-contained C++ template library for efficient multiplication of multivariate polynomials. It is intended for low order polynomials of a few variables, but is in principle limited only by the compiler's maximal template recursion depth. Polynomials can be created over any scalar type, such as integers or double precision floating point numbers.
Mathnetics is an API for creating advanced, interactive, Web-based mathematical applications. It defines various important mathematical objects that are inter-related and on which many numerical calculations can be done. It also features rendering of 3D objects onto an SVG canvas (to do so, it includes certain utilities such as browser sniffing, DOM node selection, and DOM readiness detection), which is quite robust. A few basic 3D objects are given (Line, Sphere, Cube), but the user can define any 3D object desired as per the specification.
PyMVPA (Python MultiVariate Pattern Analysis) is a Python module intended to ease pattern classification analyses of large data sets. It provides high-level abstraction of typical processing steps and a number of implementations of some popular algorithms. While it is not limited to the neuroimaging domain, it is eminently suited for such data sets. It requires nothing but free software to run.