Skip to content

Time-resolved spectroscopy toolbox for python

License

Notifications You must be signed in to change notification settings

cZahn/skultrafast

 
 

Repository files navigation

skultrafast

Documentation Status

image

What is skultrafast?

Skultrafast stands for scikit.ultrafast and is an python package which aims to include everything needed to analyze data from time-resolved spectroscopy experiments in the femtosecond domain. Its current features are listed further below.

The latest version of the software is available on github <https://github .com/Tillsten/skultrafast>. A build of the documentation can be found at Read the docs.

The package was created and is maintained by Till Stensitzki. All coding was done while being employed in the Heyne group <http://www.physik.fu-berlin .de/einrichtungen/ag/ag-heyne/> and was therefore founded by the DFG via SFB 1078 and SFB 1114.

Aims of the project

I like to include any kind of algorithm or data structure which comes up in ultrafast physics. I am also open to add a graphical interface to the package, but as experience shows, a GUI brings in a lot of maintenance burden. Hence, the first target is a interactive data-explorer for the jupyter notebook.

Features

The current releases centers around working with time-resolved spectra:

  • Publication ready plots with few lines.
  • Automatic dispersion correction.
  • Easy data processing.
  • Very fast exponential fitting, which can make use of your GPU.
  • Modern error estimates of the fitting results via lmfit.
  • Lifetime-density analyses using regularization regression.

This package also tries its best to follow modern software practices. This includes version control using git, continues integration testing via travisCI and decent documentation.

Users

At the moment it is mostly me and other people in my group. I would be happy if anyone would like to join the project!

License

Standard BSD-License. See the LICENSE file for details.

About

Time-resolved spectroscopy toolbox for python

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 100.0%