First official release of the TIMEleSS-tools and first publication from outside users

The TIMEleSS-tools were developed in the course of the TIMEleSS project to streamline the processing of multigrain crystallography data from diamond anvil cell experiments. They were actively developed in the course of the project, guided by our needs for data processing, and used in all TIMEleSS publications involving multigrain X-ray diffraction. They are a set of python programs, open-source, under the terms of the GNU GENERAL PUBLIC LICENSE, Version 2, and part of the more general FABLE-3DXRD project.

After years of development, we finally reach the time for a 1.0.0 release. TIMEleSS-tools were uploaded to PyPI and will now be easily installable on any python distribution, by simply typing those three magical words pip install timeless-tools. The latest and most up-to-date version will remain at our TIMEleSS-tools github homepage, but this release is easier to install for starting users.

This official release also come with our first user publication! Robin Fréville, Agnès Dewaele, and co-authors published a Physical Review B paper on a Comparison between mechanisms and microstructures of α−γ, γ−ε, and α−ε−α phase transitions in iron on March 14, 2023. It is the first non-TIMEleSS published paper that relies on the TIMEleSS-tools. Congratulations to all!

TIMEleSS Tools for Multigrain X-ray Diffraction

TIMEleSS toolsIn addition to contributing the TIMEleSS Multigrain Wiki, TIMEleSS members also released a set of python and matlab utilities to process, analyze, plot, and understand multigrain X-ray diffraction data. All are released under an open-source licence at GitHub on the TIMEleSS-tools and TIMEleSS-Matlab repositories.

TIMEleSS-tools include various utilities to process images, clean up parasite signals on the X-ray diffraction images, manage your peaks and grains, and post-process the output of the various multigrain XRD sofwares.

TIMEleSS-Matlab are MTEX functions one can use to represent grain orientations in pole or inverse pole figures with efficient and intuitive color scales.

Enjoy, and do not hesitate to push any improvement you might make!