MathGL is a library for making high-quality scientific graphics under Linux and Windows, fast data plotting and handling of large data arrays, working in window and console modes, and easily embedding into other programs. It has more than 40 general types of graphics for 1d, 2d, and 3d data arrays. It can export graphics to raster and vector (EPS or SVG) formats. It has an OpenGL interface and can be used from console programs. It has functions for data handling and MGL language scripting for simplification of data plotting. It has several types of transparency and smoothed lightning, vector fonts and TeX-like formula drawing, an arbitrary curvilinear coordinate system, and many other useful things.
astroPluto is modular Godunov-type code intended mainly for astrophysical applications and high Mach number flows in multiple spatial dimensions. The code embeds different hydrodynamic modules and multiple algorithms to solve the equations describing Newtonian, relativistic, MHD, or relativistic MHD fluids in Cartesian or curvilinear coordinates.
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.
GetData is a library that provides an API to interface with dirfile databases. The dirfile database format is designed to provide a fast, scalable format for storing and reading binary, synchronously-sampled, time-ordered data. GetData was originally written for the BOOMERanG and BLAST experiments as a data format suitable for use for both quick-look and data reduction. It is now used by many other cosmological and astrophysical experiments including ACT, Planck, Spider, Keck, as well as other projects.
TAU (Tuning and Analysis Utilities) is a set of tools for analyzing the performance of C, C++, Fortran and Java programs. It collects much more information than is available through prof or gprof, the standard Unix utilities, including per-process, per-thread, and per-host information, inclusive and exclusive function times, profiling groups that allow you to organize data collection, access to hardware counters on some systems, per-class and per-instance information, the ability to separate data for each template instantiation, start/stop timers for profiling arbitrary sections of code, and support for collection of statistics on user-defined events.
ffnet is a fast and easy-to-use feed-forward neural network training solution for Python. You can use it to train, test, save, load, and use an artificial neural network with sigmoid activation functions. Any network connectivity without cycles is allowed (not only layered). Training can be performed with several optimization schemes, including genetic alorithm based optimization. There is access to exact partial derivatives of network outputs versus its inputs. Normalization of data is handled automatically by ffnet.
The TIGL Geometry Library can be used for easy processing of geometric data stored inside CPACS data sets. TIGL offers query functions for the geometry structure. These functions can be used, for example, to detect how many segments are attached to a certain segment, which indices these segments have, or how many wings and fuselages the current airplane configuration contains. This functionality is necessary because TIGL targets not only the modeling of simple wings or fuselages but also the description of quite complicated structures with branches or flaps. The library uses the OpenCASCADE software to represent the airplane geometry by B-spline surfaces in order to compute surface points and also to export the geometry in the IGES/VTK format. The library provides external interfaces for C, C++, Python, Java, and FORTRAN.
OpenMPF is a library for solving large, dense, multi-RHS linear systems. It is based on MPI/openMP parallelism, and relies on BLAS/LAPACK/MUMPS for the single node computations. It implements direct and iterative solvers, out-of-core matrices and vectors, and is easily accessible through a Python interface.