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Ran 11 Nov 2017 12:30AM UTC

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Committed 11 Nov 2017 12:09AM UTC coverage: 73.569%. First build

Job # 704.1

Build Type

push

travis-ci

Committed by

alubbock

Commit Message

Dynamic influence networks using Kappa

A potentially interesting visualisation was recently published using
Kappa: dynamic influence networks (DINs). Example here:
https://creativecodinglab.github.io/DynamicInfluenceNetworks/

The corresponding publication describing the method is here:
http://ieeexplore.ieee.org/document/8017593

Since this method uses Kappa, but no example Kappa code was given,
I figured out how to generate the necessary flux data in Kappa
and added this to our Kappa interface in PySB.

Example:

    from pysb.kappa import run_simulation
    from pysb.examples import earm_1_0
    _ = run_simulation(earm_1_0.model, cleanup=False, time=10000, \
                       din_zip_file=True, din_flux_segments=50)

There are two new arguments to `pysb.kappa.run_simulation`:
din_zip_file, which you set to True to generate the DIN, and
din_flux_segments, which specifies the number of (equally spaced)
time segments to split the flux analysis into across the simulation.

The result is a .zip file containing the flux data and observables'
trajectories, which can be uploaded to the live demo at the github.io
address given above.

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