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Build # 704

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.

Run Details

6221 of 8217 relevant lines covered (75.71%)

1.33 hits per line