Open Source Python Data Management Systems for Linux

Software for pixelization, hierarchical indexation, synthesis, analysis, and visualization of data on the sphere. Please acknowledge HEALPix by quoting the web page http://healpix.sourceforge.net (or https://healpix.sourceforge.io) and publication: K.M. Gorski et al., 2005, Ap.J., 622, p.759 Full software documentation available at https://healpix.sourceforge.io/documentation.php Wiki Pages: https://sourceforge.net/p/healpix/wiki/Home Exchanging Data with HEALPix (in FITS files): https://sourceforge.net/p/healpix/wiki/Exchanging%20Data%20with%20HEALPix/ GDL and FL users should read https://sourceforge.net/p/healpix/wiki/HEALPix%20and%20GDL/

PLplot is a cross-platform, scientific graphics plotting library that supports math symbols and human languages (via UTF-8 user input strings); plot capabilities for multiple non-interactive plot file formats and in multiple interactive environments; and bindings for multiple computer languages.

g2 is an easy to use, portable and powerful 2D graphics library. It provides a comprehensive set of functions for simultaneous generation of graphical output on different types of devices.

NanoCap is a generic application for the construction of low energy fullerene and capped nanotube structures. It provides an ideal tool to accompany the study of finite carbon molecules using computer simulation. The implementation involves a standalone application which includes a GUI and allows for dynamic visual inspection through 3D rendering. In addition, the NanoCap core libraries can be used in custom Python scripts that enabled the user to produce structures in bulk or to include the structure generation routines into pre-existing code.

The aim of this project is to translate the geostatistical BMELib Matlab Toolbox (http://www.unc.edu/depts/case/BMELIB/) into Python.

This is a Fortran Module that merges the performance of the computation of the Fortran with the power of a Python Package called Matplotlib plot the data computed by your fortran code. It allows you to divide you data into groups of datafiles and each group is stored on its own directory. It allows you to create different types of plotting files such as, PNG file for each datafile and PDF and MPEG files for each group of datafiles. It works with FORMATTED and UNFORMATTED fortran datafiles. When you call the main subroutine in this module which is called FORTPLOT, it creates a python coded file that you can execute it at any time to get the plots and take a decision about continue the run or halt it. So, with multiple nodes machine you can assign a node for running the python coded file created by the Fortran code to get you data plotted.

Analysis software for Nbody/SPH or SPH simulations (e.g. performed with Gadget II). See http://sourceforge.net/apps/wordpress/hyplot/about and http://sourceforge.net/apps/trac/hyplot/wiki for more information.

Larch is a scientific data processing language that is designed to be easy to use for novices and complete enough for advanced data processing and analysis. Larch provides a wide range of functionality for dealing with arrays of scientific data, and basic tools to make it easy to use and organize complex data. Larch has been primarily developed for dealing with x-ray spectroscopic and scattering data, especially the kind of data collected at modern synchrotrons and x-ray sources. Larch is written in Python and relies heavily on the standard tools for scientific computing with Python (numpy, scipy, matplotlib, and h5py).

A High-Order Multi-Variate Approximation Scheme for Arbitrary Data Sets, C implementation of the method described in http://web.mit.edu/qiqi/www/paper/interpolation.pdf, with Python and Fortran interfaces.

OpenFrames has moved its primary development repository to GitHub! Everything else will follow. Get it at https://github.com/ravidavi/OpenFrames/wiki OpenFrames is an Application Programming Interface (API) that allows developers to provides the ability to add interactive 3D graphics to any scientific simulation. A simulation developer can use OpenFrames to specify what they want to visualize, without having to know any details of computer graphics programming. OpenFrames is currently used by three NASA programs: Copernicus (NASA JSC), the General Mission Analysis Tool (GMAT, NASA GSFC), and a Virtual Reality exploration tool (NASA GSFC).

Now maintained at github.com/spacepy/spacepy Space Science library for Python - contains superposed epoch classes, drift shell tracing, access to magnetic field models, streamline tracing, bootstrap confidence limits, time and coordinate conversions, etc.

Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT), is a powerful and complete front-end to a rich set of visual-data exploration and analysis capabilities well suited for climate-data analysis problems.

Cca-forum unifies the Common Component Architecture tools and tutorial. It includes the CCA specifications, the Ccaffeine framework for HPC, and related tools. These support multilanguage scientific and parallel computing.