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README.rst
magni_reproducibility_example.ipynb
magni_reproducibility_example.py
mandelbrot.hdf5
scipy16_reproducibility_paper.pdf
scipy16_reproducibility_poster.pdf
scipy16_validation_paper.pdf
scipy16_validation_poster.pdf

README.rst

SciPy 2016 Material

This repository contains material related to the two contributions

  • Storing Reproducible Results from Computational Experiments using Scientific Python Packages
  • Validating Function Arguments in Python Signal Processing Applications

presented at the 15th annual Scientific Computing with Python (SciPy 2016) conference held in Austin, Texas, USA, July 11-17, 2016. The two contributions were part of the poster session.

Two papers that further detail the above contributions have been accepted for publication in the conference proceedings. The open peer review process is documented on GitHub: https://github.com/scipy-conference/scipy_proceedings/pull/191 and https://github.com/scipy-conference/scipy_proceedings/pull/215

Files Overview

Files related to the contribution Storing Reproducible Results from Computational Experiments using Scientific Python Packages

  • scipy16_reproducibility_poster.pdf - The poster.
  • scipy16_reproducibility_paper.pdf - The accompanying paper (publised version)
  • magni_reproduciblity_example.ipynb - A Jupyter IPython Notebook detailing an extensive example of the use of the 'magni.reproduciblity' Python package.
  • magni_reproducibility_example.py - The script used to generate the results in the extensive example.
  • mandlebrot.hdf5 - The results database that is part of the extensive example.

The extensive example is also available at: http://dx.doi.org/10.5278/VBN/MISC/MagniRE

Files related to the contribution Validating Function Arguments in Python Signal Processing Applications

  • scipy16_validation_poster.pdf - The poster.
  • scipy16_validation_paper.pdf - The accompanying paper (published version).

Magni

Reference implementations of the proposed reproducibility and validation packages are part of the open source 'magni' Python package. Further information about 'magni' is available at

Licenses

The scipy16_reproducibility_poster.pdf poster is subject to the following copyright notice

Copyright (C) Christian Schou Oxvig, Thomas Arildsen, and Torben Larsen. Aalborg University, Department of Electronic Systems, Signal and Information Processing, Fredrik Bajers Vej 7, DK-9220 Aalborg, Denmark. This work is licensed under a Creative Common Attribution 4.0 International License (CC-BY 4.0).

The scipy16_validation_poster.pdf poster is subject to the following copyright notice

Copyright (C) Patrick Steffen Pedersen, Christian Schou Oxvig, Jan Østergaard, and Torben Larsen. Aalborg University, Department of Electronic Systems, Signal and Information Processing, Fredrik Bajers Vej 7, DK-9220 Aalborg, Denmark. This work is licensed under a Creative Common Attribution 4.0 International License (CC-BY 4.0).

See the individual file for the license for the remaining files.