Biomechanical ToolKit (BTK) is a cross-platform library for biomechanical analysis. It can read and write a large variety of file formats used in biomechanics, and can modify them. All these operations can be done with the C++ API or with the wrappers included (Python, Octave, and Matlab). The goal of this project is to help the community share data without the restriction of the file format or the biomecanical model provided by the manufacturer of the acquisition system.
OSCATS (Open-Source Computerized Adaptive Testing System) implements Item Response Theory (IRT) and cognitively diagnostic (latent classification) models and item selection algorithms used in Computerized Adaptive Testing (CAT). OSCATS facilitates the development of CATs and simulations of CATs by providing ready-to-use code for running the CAT item selection and ability/classification estimation in an extensible, modular framework. The library is written in object-oriented C using GObject, and has bindings to Python, Perl, PHP, and Java.
Chebfun is a collection of algorithms and a software system in object-oriented MATLAB that extends familiar powerful methods of numerical computation involving numbers to continuous or piecewise-continuous functions. It also implements continuous analogues of linear algebra notions like the QR decomposition and the SVD, and solves ordinary differential equations. The mathematical basis of the system combines tools of Chebyshev expansions, fast Fourier transform, barycentric interpolation, recursive zerofinding, and automatic differentiation.
The Jacket platform consists of a runtime and language processing system that automatically optimizes existing applications or new algorithms for GPU computing. Jacket currently supports the MATLAB language as a frontend to the platform. Jacket's language processing system automatically translates MATLAB code to high performance primitives required for best utilization of Nvidia, CUDA capable GPUs. Working in concert with the translation system, Jacket's runtime system optimizes memory transfers, compiles code on-the-fly for realtime tuned performance, and launches GPU kernels efficiently for maximal performance. All GPU-specific programming details are handled by Jacket, freeing the user to focus on science, engineering, and analytics.
FinMetrics is a MATLAB-based quantitative portfolio management environment. Built on concepts of bottom-up approach to application design, it allows users to define most basic, low level building blocks, e.g. assets and transactions, to be further pieced together in higher level objects, e.g. positions or portfolios. Data analysis and statistics functions, implemented within the environment and native to MATLAB, enable users to conduct scenario analysis, stress testing, performance measurement and attribution, risk measurement and attribution, design hedge strategies, etc. The open architecture of the environment allows users to work with objects of any level, depending on their requirements and expertise. The object structure and data types are specifically designed to make integration with MATLAB and native FinMetrics functions as easy as possible. The FinMetrics user interface application and MATLAB scripting may be utilized to facilitate or automate complex and repetitive tasks, as well as extend the functionality of the environment.
RWTH Mindstorms NXT Toolbox controls LEGO Mindstorms NXT robots with MATLAB via a wireless Bluetooth connection. The toolbox functions are based on the LEGO Mindstorms NXT Bluetooth Communication Protocol to control the intelligent NXT Brick via a wireless Bluetooth connection. Although a Bluetooth connection is not recommended for realtime robot control in general, because of its high latency, this toolbox provides MATLAB functions to interact with a robot directly. The main advantage of this remote control concept is that it enables users to combine robot applications with complex mathematical operations and visualizations within MATLAB.