Open Source Python Scientific/Engineering Software

GeographicLib is a small C++ library for: geodesic and rhumb line calculations; conversions between geographic, UTM, UPS, MGRS, geocentric, and local cartesian coordinates; gravity (e.g., EGM2008) and geomagnetic field (e.g., WMM2020) calculations.

Build, Design and Test your network in a risk-free virtual environment and access the largest networking community to help. Whether you are studying for your first networking exam or building out a state-wide telecommunications network, GNS3 offers an easy way to design and build networks of any size without the need for hardware.

A data visualization and processing tool for scanning probe microscopy (SPM, i.e. AFM, STM, MFM, SNOM/NSOM, ...) and profilometry data, useful also for general image and 2D data analysis.

Snap7, through three specialized components: Client and the inedited Server and Partner, allows you to definitively integrate your PC based systems into a PLC automation chain. Designed to transfer large amounts of hi-speed data in industrial facilities, it scales easily, down to small Linux Arm boards such as Raspberry PI. Hi level object oriented wrappers are provided, currently C/C++, .NET/Mono, Pascal, LabVIEW, Python with many source code examples. Very easy to use, a full working server example is not bigger than the “Hello world”. Many projects/makefiles are ready to run to easily rebuild Snap7 in any platform without the need of be a C++ guru. Very detailed documentation provided.

A cross-platform, open-source, alternative to NIST REFPROP. Based on reference-accuracy equations of state and transport property correlations for refrigerants like Water, CO2, R134a, Nitrogen, Argon, Ammonia, Air, R404a, R410a, Propane and many others. A selection of secondary working fluid properties are also available. Can also make use of REFPROP when available. In addition, calculations for Humid Air Properties based on ASHRAE RP-1485 are provided. Wrappers are available for MATLAB, Octave, Python, C#, Fortran and many more.

NEWS: NumPy 1.11.2 is the last release that will be made on sourceforge. Wheels for Windows, Mac, and Linux as well as archived source distributions can be found on PyPI. Numerical Python adds a fast and sophisticated array facility to the Python language. NumPy is the most recent and most actively supported package. Numarray and Numeric are no longer supported.

The Hamlib project's purpose is to develop flexible and portable shared libraries that offer a standardized API to control any radio oriented equipment through a computer interface.

BioSig is a software library for processing of biomedical signals (EEG, ECG, etc.) with Matlab, Octave, C/C++ and Python. About 50 different data formats are supported.

Florence is an extensible scalable on-screen virtual keyboard for GNOME that stays out of your way when not needed. You need it if you can't use a real keyboard either because of a handicap, broken keyboard or tablet PC but you can use a pointing devide.

ASCEND is a modelling environment and solver for large or small systems of non-linear equations, for use in engineering, thermodynamics, chemistry, physics, mathematics and biology. Solvers for both steady and dynamic (NLA & DAE) problems, are provid

The Linux GPIB Package is a support package for GPIB (IEEE 488.2) hardware. The package contains a development environment consisting of a GPIB library written in C, kernel driver modules, and bindings for several other languages.

Arabeyes is a Meta project that is aimed at fully supporting the Arabic language in the Unix/Linux environment. It is designed to be a central location to standardize the Arabization process. Arabeyes relies on voluntary contributions.

This is an implementation of post-process phonon analyzer, which calculates crystal phonon properties from input information calculated by external codes, e.g., first-principles calculation code.

Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) is a computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology. For instructions and documentations, please refer to the wiki page. MAGeCK is developed by Wei Li and Han Xu from Dr. Xiaole Shirley Liu's lab at Dana-Farber Cancer Institute/Harvard School of Public Health, and is maintained by Wei Li lab at Children's National Medical Center. We thank the support from Claudia Adams Barr Program in Innovative Basic Cancer Research and NIH/NHGRI to develop MAGeCK.

Advanced Trigonometry Calculator is equipped with a user-friendly interface that allows for easy input of problems and instant computation. Professionals such as engineers who need to perform advanced trigonometric calculations in their work will find this tool extremely useful. More info by clicking below: https://advantrigoncalc.sourceforge.io/ Advanced Trigonometry Calculator was only and always only developed by the Portuguese Renato Alexandre dos Santos Freitas. Also author of poems, reflections and thoughts published on the platform https://www.pensador.com/autor/renato_alexandre_dos_santos_freitas/ ATC is Made in Portugal. He was born in Coimbra on July 6, 1991. He has a degree in Electrical and Telecommunications Engineering and began developing ATC at the beginning of his undergraduate studies. He works for Miclearning, Lda since April 2020. Providing services to Multimac Hito Innovation.

Madagascar is a software package for geophysical data processing and reproducible numerical experiments. The package mission is to provide a convenient environment for researchers working with digital image and data processing in geophysics and related fields.

BioXTAS RAW is a program for analysis of Small-Angle X-ray Scattering (SAXS) data. The software enables: creation of 1D scattering profiles from 2D detector images, standard data operations such as averaging and subtraction, analysis of radius of gyration (Rg) and molecular weight, and advanced analysis using GNOM and DAMMIF as well as electron density reconstructions using DENSS. It also allows easy processing of inline SEC-SAXS data and data deconvolution using the evolving factor analysis (EFA) or the regularized alternating least squares (REGALS) methods. Active source code is now maintained on github: https://github.com/jbhopkins/bioxtasraw To install: Check the instructions available at: http://bioxtas-raw.readthedocs.io/en/latest/install.html and in the Files tab. User guides: RAW guides are available at: http://bioxtas-raw.readthedocs.io/ and in the Files tab. To contact us, see: https://bioxtas-raw.readthedocs.io/en/latest/help.html

To use precompiled wheels: 1) go to releases (Files) and download tarball needed; 2) install it with command: python3 -m pip install /path/to/wheel.whl Or simply use URL in pip: python3 -m pip install https://sourceforge.net/projects/gdal-wheels-for-linux/files/GDAL-3.1.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl/download URL may be found under "View details" button (i) To use GDAL in C/C++ project you need to link gdal lib AND all libs located at dir GDAL.libs (usually this folder resides inside python site-packages) To compile your own wheels see information given at forefather project: https://github.com/youngpm/gdalmanylinux Usually this is done via command `make wheels` GDAL wheels for Windows are provided by Christoph Gohlke at https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal Built with PROJ (proj.db is included), GEOS, EXPAT. See Dockerfile.wheels for additional components.

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/

The Sashimi project hosts the Trans-Proteomic Pipeline (TPP), a mature suite of tools for mass-spec (MS, MS/MS) based proteomics: statistical validation, quantitation, visualization, and converters from raw MS data to the open mzML/mzXML formats.

A free, industrial quality library for simulating articulated rigid body dynamics - for example ground vehicles, legged creatures, and moving objects in VR environments. It's fast, flexible & robust. Built-in collision detection.

Presage (formerly Soothsayer) is an intelligent predictive text entry system. Presage generates predictions by modelling natural language as a combination of redundant information sources. Presage computes probabilities for words which are most likely to be entered next by merging predictions generated by the different predictive algorithms. Presage's modular and extensible architecture allows its language model to be extended and customized to utilize statistical, syntactic, and semantic predictive algorithms. Presage's predictive capabilities are implemented by predictive plugins. Predictive plugins use services provided by the platform to implement multiple prediction techniques.

Xplico is a Network Forensic Analysis Tool (NFAT). The goal of Xplico is extract from an internet traffic capture the applications data contained. For example, from a pcap file Xplico extracts each email (POP, IMAP, and SMTP protocols), all HTTP contents, each VoIP call (SIP, MGCP, MEGACO, RTP), IRC, WhatsApp... Xplico is able to classify more than 140 (application) protocols. Xplico cam be used as sniffer-decoder if used in "live mode" or in conjunction with netsniff-ng. Xplico is used also in CapAnalysis: http://www.capanalysis.net

The auditory modeling toolbox (AMT) is a Matlab/Octave toolbox for the development and application of auditory computational models. Over 50 auditory models implemented in Matlab, Octave, C, C++, and Python can be run from Matlab and Octave, on Windows and Linux. The AMT provides a well-structured in-code documentation, includes auditory data required to run the models. It integrates functionality to reproduce the model predictions. Model implementations can be evaluated in two stages, by running so-called demonstrations which are quick presentations of a model and by starting so-called experiments aimed at reproducing results from the corresponding publications. Easy installation and user-friendly access help students and researchers to work with and to advance existing models.

Python module for creating functions computing the Cyclic Redundancy Check (CRC). Any generating polynomial producing 8, 16, 24, 32, or 64 bit CRCs is allowed. Generated functions can be used in Python or C/C++ source code can be generated.