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Scraps is a package designed to help you analyze lots of data from superconducting resonators. The basic idea is that you hook up your VNA (or mixer) and measure S21 at several different temperatures and driving powers. Maybe you have a PID and some decent automation software that take several hundred traces, and now you don’t know what to do with all that data. Enter scraps. Scraps will organize it all and run fits on it, and make pretty pictures you can show your advisor or funding committee or spouse (when asked what you do all day upon returning home) or even put into a journal article.

Currently scraps is designed to handle resonator S21 data at varying temperatures and input powers. There are plans to extend scraps to handle varying magnetic field also, as well as noise in addition to S21. If you would like to be a part of that, get involved by posting a message here.

Who is using scraps?

Scraps is in use at Argonne National Laboratory, Caltech, University of Chicago, Oxford and probably many other places! Recently a group at Oxford used scraps to fit MKID resonator data for this publication: MKID digital readout tuning with deep learning

License

Scraps is licensed under the MIT license, so feel free to copy it, play with it, modify it, etc. under those terms (which are pretty loose!).

Documentation

Installation is as simple as:

pip install scraps

or if you want to get the may-not-be-stable developer version:

git clone http://github.com/FaustinCarter/scraps
pip install -e /dir/where/you/cloned/scraps
cd /dir/where/you/cloned/scraps
git checkout develop

For complete API documentation, more in depth installation instructions and some example tutorials, see the official documentation at: http://scraps.readthedocs.io

Citation

If you use scraps to make plots or analyze data for a publication, please cite the IEEE Applied Superconductivity Manuscript, DOI: 10.1109/TASC.2016.2625767:

@article{Carter2016,
   author={F. W. Carter and T. S. Khaire and V. Novosad and C. L. Chang},
   journal={IEEE Transactions on Applied Superconductivity},
   title={scraps: An Open-Source Python-Based Analysis Package for Analyzing and Plotting Superconducting Resonator Data},
   year={2017},
   volume={27},
   number={4},
   pages={1-5},
   doi={10.1109/TASC.2016.2625767},
   ISSN={1051-8223},
   month={June}
}

Short description of files that aren’t code:

  • Example1: a JuPyter notebook that will help you get started with the basics. Focus is on a single S21 sweep.

  • Example2: a slightly more advanced tutorial that focuses on lots of sweeps at several temperatures and powers.

  • Example3: an example showcasing some of the more advanced plotting features. The data for this notebook is at: http://dx.doi.org/10.5281/zenodo.61575

  • ExampleData.zip: A ton of actual superconducting resonator data from a Nb microstrip resonator made at ANL.

  • convert_notebooks.sh: A handy little bash script to turn the Example# notebooks into rst files in the docs folder properly.

  • readthedocs.yml and environment.yml: These are needed to properly build the documentation hosted at RTD.

Support

Please post any bugs or feature requests here on GitHub. Bugs will be squashed ASAP. Feature requests will be seriously considered!

Copyright 2016, Faustin W. Carter

Release files for scraps 0.5.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Source distribution for scraps 0.5.3
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Table of built distributions (wheels) for scraps 0.5.3
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scraps-0.5.3-py3-none-any.whl Python 3 none any Details

Total release size: 39.0 MB

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