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Python computational experiment management

Project Description

Overview

epyc is a Python module for controlling a long-running series of computational experiments, as is often found when writing simulations of complex networks and other such domains. There is often a need to perform a computation across a multi-dimensional parameter space, varying the parameters, performing and aggregating multiple repetitions, and wrangling results for analysis and presentation. Often the experiments being performed are on such a scale as to require the use of a computing cluster to perform multiple experiments simultaneously.

Managing all these tasks is complicated, so epyc tries to automate it. It provides a way to define a “laboratory” performing a collection of “experiments” whose parameters and results are recorded in a “lab notebook” for later retrieval. Laboratories can be sequential (for a single machine) or parallel (to use a multicore or cluster of machines); lab notebooks can be persistent to allow experiments to be fired-off and their results retrieved later – handy if you use a laptop. Notebooks store all the data and metadata in a portable format to improve the reproducibility of computational experiments.

Source distribution

epyc is distributed on GitHub. To obtain a copy:

git clone git@github.com:simoninireland/epyc.git cd epyc python setup.py install

Documentation

The doc/ directory contains an IPython notebook that describes the use of epyc in detail. You can also read it directly [online](https://github.com/simoninireland/epyc/blob/master/doc/epyc.ipynb).

Author and license

Copyright (c) 2016, Simon Dobson <simon.dobson@computer.org>

Licensed under the GNU General Public Licence v.2.0

Release History

Release History

This version
History Node

0.1.1

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
epyc-0.1.1.tar.gz (124.7 kB) Copy SHA256 Checksum SHA256 Source Jul 15, 2016

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