Armadillo is a C++ linear algebra library (matrix maths) aiming towards a good balance between speed and ease of use. The API is deliberately similar to Matlab's. Integer, floating point, and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS numerics libraries. A delayed evaluation approach, based on template meta-programming, is used (during compile time) to combine several operations into one and reduce or eliminate the need for temporaries.
DEDiscover is a workflow-based differential equation modeling software tool for scientists, statisticians, and modelers. Whether you need to do quick simulation, develop sophisticated models, or teach mathematical concepts, DEDiscover combines a powerful computation engine with a user-friendly interface to give you a tool that's better, faster, and easier-to-use.
Isoline Retrieval uses supervised statistical classification to retrieve isolines from cross-track scanning or similar satellites. It contains software to generate training data using collocation or radiative transfer simulations, as well as routines to interpolate the final fields using a variation of multi-linear interpolation or kernel estimation. The currently-supported satellites are the Advance Microwave Sounding Unit (AMSU) series and, to a lesser extent, the Global Ozone Measurement Experiment (GOME). An ambitious researcher, however, could easily adapt the codes to a similar satellite.
LibBi is used for state-space modelling and Bayesian inference on high-performance computer hardware, including multi-core CPUs, many-core GPUs (graphics processing units), and distributed-memory clusters. The staple methods of LibBi are based on sequential Monte Carlo (SMC), also known as particle filtering. These methods include particle Markov chain Monte Carlo (PMCMC) and SMC2. Other methods include the extended Kalman filter and some parameter optimization routines. LibBi consists of a C++ template library and a parser and compiler, written in Perl, for its own modelling language.
HEALPix is a set of scientific tools implementing the Hierarchical Equal Area isoLatitude Pixelation of the sphere. As suggested in the name, this pixelation produces a subdivision of a spherical surface in which every single pixel covers the same surface area. HEALPix provides various programs and libraries in C, C++, Fortran, GDL/IDL, Java, and Python which facilitate discretization, simulation, processing, analysis, and visualization of data on the sphere up to very high resolution. It is the state-of-the-art program used in astronomy and cosmology to deal with massive full-sky data sets.
The Graphical Models Toolkit (GMTK) is a toolkit for rapidly prototyping statistical models using dynamic graphical models (DGMs) and dynamic Bayesian networks (DBNs). It can be used for speech and language processing, bioinformatics, activity recognition, and any time series application. It features exact and approximate inference, many built-in factors including dense, sparse, and deterministic conditional probability tables, native support for ARPA backoff-based factors and factored language models, parameter sharing, gamma and beta distributions, dense and sparse Gaussian factors, heterogeneous mixtures, deep neural network factors, and time-inhomogeneous trellis factors, arbitrary order embedded Markov chains, a GUI graph viewer, and much more.
The Shared Scientific Toolbox is a library that facilitates development of efficient, modular, and robust scientific/distributed computing applications in Java. It features multidimensional arrays with extensive linear algebra and FFT support, an asynchronous, scalable networking layer, and advanced class loading, message passing, and statistics packages.
pepper is a commandline tool for retrieving statistics and generating reports from source code repositories. It ships with several graphical and textual reports, and is easily extensible using the Lua scripting language. It includes support for multiple version control systems, including Git and Subversion.
KeyFrog monitors the keyboard and visualizes its usage statistics. The user can obtain much information about keyboard activity: the intensity of keyboard usage, how was it distributed in time, which applications were used, etc. This may be very useful, for example, to developers to monitor their productivity. The environment being monitored is the X Window System (text applications are explicitly supported if run inside an X terminal).