The iFit library (pronounce [eye-fit]) is a set of methods to load, analyse, plot, fit and optimize models, and export results. iFit is based on Matlab, but can also be launched without Matlab license (stand-alone version).Matlab It does not currently include advanced graphical user interfaces (GUI), and rather focuses on doing the math right. Any text file can be imported straight away, and a set of binary files are supported. Any data dimensionality can be handled, including event based data sets (even though not all methods do work for these). Any model can be assembled for fitting data sets. Last, a number of routines are dedicated to the analyses of S(q,w) and S(alpha,beta). More advanced features include the full automation to compute phonon dispersions in materials, using DFT codes such as ABINIT, ELK, VASP, QuantumEspresso, GPAW and more (Models/sqw_phonons). The software can also compute the neutron TAS resolution function (4D) and fits to experimental data with full resolution convolution (ResLibCal). An interface for McStas and McXtrace is also available to automate and optimize instrument simulations.


MDANSE (Molecular Dynamics Analysis for Neutron Scattering Experiments) is a python application designed for computing properties that can be directly compared with neutron scattering experiments such as the coherent and incoherent intermediate scattering functions and their Fourier transforms, the elastic incoherent structure factor, the static coherent structure factor or the radial distribution function. Moreover, it can also compute quantities such as the mean-square displacement, the velocity autocorrelation function as well as its Fourier Transform (the so-called vibrational density of states) enlarging the scope of the program to a broader range of physico-chemical properties. Most of MDANSE calculations can be applied to the whole system or to arbitrary subsets that can be defined in the graphical interface while less common selections can be specified via the command-line interface. MDANSE is written in Python and currently works on Linux/debian, MacOS and Windows.

Unscrambler X

Commercial software product for multivariate data analysis, used for calibration of multivariate data which is often in the application of analytical data such as near infrared spectroscopy and Raman spectroscopy, and development of predictive models for use in spectroscopic analysis of materials. Unscrambler X was an early adaptation of the use of partial least squares (PLS). Other techniques supported include principal component analysis (PCA), 3-way PLS, multivariate curve resolution, design of experiments, supervised classification, unsupervised classification and cluster analysis.