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.
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.
MLPACK is a C++ machine learning library with an emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and maximum flexibility for expert users. It contains algorithms such as k-means, Gaussian mixture models, hidden Markov models, density estimation trees, kernel PCA, locality-sensitive hashing, sparse coding, linear regression and least-angle regression.
n2 is a client/server system for transmitting forensic snapshots from a number of hosts to a receiver node. This receiver collects statistics and is able to present an overview of the current and historical situation on a server. n2 provides a robust solution for real-time monitoring, optimizing performance, and analyzing crashes.
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.
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.
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).
Libfbm is a C++ library for fast and accurate bulk-simulation of multi-dimensional (1D, 2D, 3D, .., 8D) Gaussian stationary processes, fractional Brownian motion, and fields with power-law power spectrum. It makes use of the circulant matrix embedding and FFT. Random number generation is provided by SFMT (SIMD-optimized Mersenne Twister) with a ziggurat based algorithm for normal distribution. For FFT functions, it depends on the FFTW library.
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.