parasweep 2019.2.3

Utility for facilitating parallel parameter sweeps.

parasweep

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.

• Free software: MIT license

• Documentation: http://www.parasweep.io

• Code: https://github.com/eviatarbach/parasweep

Dependencies

• Python 3.6+

• xarray

• numpy

• scipy

• Mako (optional)

• drmaa-python (optional)

Credits

Developed by Eviatar Bach <[e-mail]>.

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

History

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