This library provides different building blocks that users can combine, convolute and plug in different frameworks for visualizing or fitting Quasi Elastic Neutron Scattering (QENS) data S(Q, omega). It was developed as part of SINE2020 Workpackage 10 on Data Treatment to develop an exhaustive library of dynamical models in order to increase interoperability and modularity for a rapid prototyping.
The models are written in Python for easy integration in workflows. In order to help users, a few examples of data analyses using different standard fitting engines (lmfit, scipy, bumps) are provided as Jupyter notebooks5. Tools are also provided to help those interested in contributing to the project by adding models or sharing examples of data treatment.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 654000.
|Licenses||GNU General Public License 3.0|
|Categories||Data analysis Spectroscopies Library Molecular Dynamics|
|Software Requirements||numpy, scipy|
|Hardware Requirements||-||Platforms||There are no platforms associated to this software.|
|Input Formats||There are no input formats associated to this software.|
|Output Formats||There are no output formats associated to this software.|
|There is not a how-to for this software.|
|Documentation / Tutorials|
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|Instruments||This software is not associated to any instruments.|