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parasweep

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parasweep is a free and open-source Python utility for facilitating parallel parameter sweeps with computational models. Instead of requiring parameters to be passed by command-line, which can be error-prone and time-consuming, parasweep leverages the model’s existing configuration files using a template system, requiring minimal code changes. After the sweep values are specified, a parallel job is dispatched for each parameter set, with support for common high-performance computing job schedulers. Post-processing is facilitated by providing a mapping between the parameter sets and the simulations.

The following paper gives a description as well as a simple example to get started: https://arxiv.org/pdf/1905.03448.pdf. Please cite it if you find parasweep useful for your project!

Dependencies

  • Python 3.6+

  • xarray

  • numpy

  • scipy

  • Mako (optional)

  • drmaa-python (optional)

Credits

Developed by Eviatar Bach <eviatarbach@protonmail.com>. Special thanks to Daniel Philipps (danielphili) for a bug fix and feature suggestion.

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

History

2021.01 (2021-01-06)

  • Changing wait option to be True by default

  • Minor fixes to Lorenz example

2020.10 (2020-10-27)

  • Adding option to exclude simulation IDs

  • Allowing empty sweep ID

2020.09 (2020-09-02)

  • Incorporating sweep_id into SequentialNamer (thanks to danielphili)

2020.02 (2020-02-17)

  • Fixing bug with default sweep_id on Windows (thanks to danielphili)

  • Unicode support for PythonFormatTemplate

2019.02.3 (2019-02-20)

  • Adding SetNamer naming

2019.02.2 (2019-02-18)

  • Adding process limit for subprocess dispatching

  • Adding RandomSweep sweep type

  • Adding HashNamer naming

  • Clarifying version dependencies

  • More examples

2019.02 (2019-02-07)

  • Separating sweep logic into a separate module

  • Adding FilteredCartesianSweep sweep type

  • Numerous documentation changes, including many more examples

2019.01 (2019-01-21)

  • First release on PyPI

Metadata

Release files for parasweep 2021.1

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