Armadillo is a C++ linear algebra library (matrix maths) aiming towards a good balance between speed and ease of use. 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 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.
SOFA is a statistics, analysis, and reporting program with an emphasis on ease of use, learning as you go, and beautiful output. SOFA can connect directly to your database and lets you display results in an attractive format ready to share or put in a spreadsheet. SOFA will help you learn as you go, whether you are a student, business analyst, or researcher.
superseriousstats is a small and efficient program for creating a Web page with statistics from various types of IRC logs. It keeps track of its parse history and only processes new activity before storing any accumulated data in a SQLite or MySQL database. It is suitable for high volume IRC channels and large log archives, and is relatively easy to integrate with IRC services (e.g. bots) that interact with the database and provide last seen information and many other statistics directly in your channel.
SCaVis is an environment for scientific computation, data analysis, and data visualization designed for scientists, engineers, and students. The program can be used for function and data plotting in 2D and 3D, histograms, statistical analysis, and symbolic calculations using the Matlab/Octave high-level interpreted language.
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.
Strategico is an engine for running statistical analysis over groups of time series. It can manage one or more groups (projects) of time series: by default, you can get data from a database or CSV files, normalize them, and then save them inside the engine. The first statistical analysis implemented inside Strategico is the "Long Term Prediction": it automatically finds the best model that fits each time series. Some of the models implemented are mean, trend, linear, exponential smoothing, and Arima. Strategico is scalable: the statistical analysis over each time series (of a project) can be run separately and independently. It is suggested that you set up an HPC Cluster (High Performance Computing) and/or use a resource scheduler like slurm. It is developed with R, one of the most famous statistical languages.
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.
The program arbtt, the automatic rule-based time tracker, allows you to investigate how you spend your time, without having to manually specify what you are doing. arbtt records which windows are open and active, and provides you with a powerful rule-based language to afterwards categorize your work.
Meta.Numerics is a Mono-compatible .NET library for scientific and numerical programming. It includes functionality for matrix algebra (including SVD, non-symmetric eigensystems, and sparse matrices), special functions of real and complex numbers (including Bessel functions and the complex error function), statistics and data analysis (including PCA, logistic and nonlinear regression, statistical tests, and nonuniform random deviates), and signal processing (including arbitrary-length FFTs).
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).