Open Source Python Molecular Science Software

QMForge reads output from various quantum mechanical calculations and provides tools for analyzing these results. Specifically, population (Mulliken and C-squared), fragment, and charge decomposition analyses are available. See https://qmforge.net for more info.

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.

We are proud to introduce version 5 of CAMPARI. We have added a number of new features, most notably a Python interface for interpreting user-supplied code (with the help of ForPy), a novel trajectory storage standard (with the help of libpqxx/PostgreSQL), and a module for performing transition path theory. Naturally, CAMPARI continues to provide the reference implementation of the ABSINTH force field paradigm and implicit solvation model. CAMPARI is a joint package for performing and analyzing molecular simulations, in particular of systems of biological relevance. It focuses on a wide availability of algorithms for (advanced) sampling and is capable of combining Monte Carlo and molecular dynamics in seamless fashion. CAMPARI offers the user a very high level of control over all implemented features. For more information and features, please refer to the project's homepage at http://campari.sourceforge.net/V5

PLEASE NOTE ORBKIT HAS BEEN MOVED TO https://github.com/orbkit/orbkit orbkit is a parallel Python program package for post-processing wave function data extracted from output files of MOLPRO (Molden File Format), TURBOMOLE (AOMix file format), GAMESS-US, PROAIMS/AIMPAC (wfn/wfx file format), and Gaussian (Output File and Formatted Checkpoint File) output files. Futhermore, an interface to cclib, a parser for quantum chemical logfiles, is provided. If you use orbkit in your work, please cite it as follows: Gunter Hermann, Vincent Pohl, Jean Christophe Tremblay, Beate Paulus, Hans-Christian Hege, and Axel Schild, "ORBKIT: A Modular Python Toolbox for Cross-Platform Postprocessing of Quantum Chemical Wavefunction Data", J. Comput. Chem. 2016, DOI: 10.1002/jcc.24358. orbkit's documentation can be found at http://orbkit.github.io/

2DFLT it is first out of two programs which allows implementation of Phase Sensitive Detection (PSD) and/or Modulated Enhanced Diffraction (MED) techniques on the in situ data. This software allows collecting individual data files from in situ experiment into one dataset. After that this data set can be visualized, edited, normalized and averaged. Resulted data can be saved as one flat file (FLT-format) which can be used for PSD/MED calculations via 2DMED software (http://sourceforge.net/projects/twodmed/?source=directory). 2DFLT specifically was written to target in situ X-ray Powder Diffraction data from synchrotron measurements. Hence it can read CHI, XYE (TOPAS), FXYE(GSAS/ GSASII) and XY- files formats. However it can read general in situ data written into individual TXT or XY – files.

2DMED it is the second out of two programs which allows implementation of Phase Sensitive Detection (PSD) and/or Modulated Enhanced Diffraction (MED) techniques on the in situ data. This software takes normalized and averaged in situ data in flat file format (FLT) and performs PSD transformation which has been described in Urakawa, A.et al. Chem. Eng. Science 2008, 63, 4902. User can choose demodulation index k and perform several demodulation calculations. This is extremely important since demodulation calculations at k = 2 on in situ powder diffraction data represent implementation of MED method which been described in Chernyshov, D. et al. Acta Cryst. 2011, A67, 327. Demodulated data can be then viewed on 2D and/or 1D plot and analyses with different tools including In Phase Plot, Maximum Amplitude Plot and Positive Pattern Plot. Demodulated data also can be saved in ASCII format for further analysis.

This software has moved to http://www.poissonboltzmann.org/.

A toolkit in C++ and python to process both experimental and simulation data of colloidal particles. Includes among others * a multiscale particle tracking algorithm [1] whose C++ implementation is optimised for 3D confocal data. Python implementation is more versatile (2D and 3D data). * a Leica file reader, * Steindhard bond orientational order calculation * a VTK file writer 1. Leocmach, M. & Tanaka, H. A novel particle tracking method with individual particle size measurement and its application to ordering in glassy hard sphere colloids. Soft Matter 9, 1447–1457 (2013). https://dx.doi.org/10.1039/C2SM27107A (http://arxiv.org/pdf/1301.7237.pdf)

DArmstadt MAgnetic Resonance Instrument Software

ED Software project contains several programs used (mostly) for processing gas-phase electron diffraction (GED) experimental data.

LOOS is a light-weight object oriented software library for creating new tools for analyzing molecular simulation data, written in C++. The main design goal is to allow casual programmers to easily implement new analysis methods. THIS PAGE IS NO LONGER UPDATED. Please see https://github.com/GrossfieldLab/loos for all recent developments

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).

PySpline is a graphical, cross-platform program for processing X-ray absorption spectroscopy (XAS) and Extended X-ray absorption fine structure (EXAFS) data. It allows processing parameters to be adjusted and observe the effect on R-space data.

SMMP (Simple Molecular Mechanics for Proteins) is a program library for protein simulations with an emphasis on advanced Monte Carlo algorithms. It includes various force fields to calculate the energy of a protein and protein-protein interactions.

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.

**(9 march 2016) this project is continued on github : http://jaapkroe.github.io/polypy ** Python script to analyze (shortest-path) rings in structures read from xyz-files. It can be useful for example to identify defects in crystal structures or molecules.

pyitc is designed for processing and analysing isothermal titration calorimetry experimental data (Microcal instruments).