parasweep 2019.2.2

Utility for facilitating parallel parameter sweeps.

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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.

* Free software: MIT license
* Documentation: http://www.parasweep.io.

Dependencies
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* Python 3.6+
* xarray
* numpy
* scipy
* Mako (optional)
* drmaa-python (optional)

Credits
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Developed by `Eviatar Bach <http://eviatarbach.com/>`_ <[e-mail]>.

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage


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History
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2019.02.2 (2019-02-18)
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* Adding process limit for subprocess dispatching
* Adding RandomSweep sweep type
* Adding HashNamer naming
* Clarifying version dependencies
* More examples

2019.02 (2019-02-07)
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* Separating sweep logic into a separate module
* Adding FilteredCartesianSweep sweep type
* Numerous documentation changes, including many more examples

2019.01 (2019-01-21)
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* First release on PyPI