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.
CloudBuddy Analytics is a Web-based tool that generates exhaustive statistical reports about your S3 bucket access. It has an intuitive interface for a rich user experience and takes care of enabling logging, fetching logs and generating reports. It can be configured for multiple S3 accounts, uses the AWStats engine, employs caching for faster reports, and gives details on bandwidth usage, visits, unique visitors, visit durations, last visits, days of week and rush hours (pages, hits, KB for each hour and day of week), domains/countries of visitors, and more.
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.
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).