Wednesday, July 7, 2021

Upcoming features of QSoas and github repository

For the past years, most of the development has happened behind the scene in a private repository, and the code has appeared in the public repository only a couple of months before the release, in the release branch. I have now decided to publish the current code of QSoas in the github repository (in the public branch). This way, you can follow and use all the good things that were developed since the last release, and also verify whether any bug you have is still present in the currently developed version !

Upcoming features

This is the occasion to write a bit about the some of the features that have been added since the publication of the 3.0 release. Not all of them are polished nor documented yet, but here are a few teasers. The current version in github has:
  • a comprehensive handling of column/row names, which makes it much easier to work with files with named columns (like the output files QSoas produces !);
  • better handling of lists of meta-data, when there is one value of the meta for each segment or each Y column;
  • handling of complex numbers in apply-formula;
  • defining fits using external python code;
  • a command for linear least squares (which has the huge advantage of being exact and not needing any initial parameters);
  • commands to pause in a script or sort datasets in the stack;
  • improvements over previous commands, in particular with eval;
  • ... and more...
Check out the github repository if you want to know more about the new features !

As of now, no official date is planned for the 3.1 release, but this could happen during fall.

About QSoas

QSoas is a powerful open source data analysis program that focuses on flexibility and powerful fitting capacities. It is released under the GNU General Public License. It is described in Fourmond, Anal. Chem., 2016, 88 (10), pp 5050–5052. Current version is 3.0. You can download its source code there (or clone from the GitHub repository) and compile it yourself, or buy precompiled versions for MacOS and Windows there.

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