Kappa integration (`pysb.kappa`)¶

Wrapper functions for running the Kappa programs KaSim and KaSa.

The path to the directory containing the KaSim and KaSa executables can be specified in one of three ways:

set the KAPPAPATH environment variable to the KaSim directory
move Kappa to /usr/local/share/KaSim (macOS, Linux) or c:Program FilesKaSim (Windows)
set the path using the pysb.pathfinder.set_path() function at runtime

exception pysb.kappa.KasaInterfaceError[source]¶

exception pysb.kappa.KasimInterfaceError[source]¶

class pysb.kappa.SimulationResult(timecourse, flux_map)¶

flux_map¶: Alias for field number 1

timecourse¶: Alias for field number 0

class pysb.kappa.StaticAnalysisResult(contact_map, influence_map)¶

contact_map¶: Alias for field number 0

influence_map¶: Alias for field number 1

pysb.kappa.contact_map(model, **kwargs)[source]¶

Generates the contact map via KaSa.

Parameters

modelpysb.core.Model: The model for generating the influence map.
**kwargsother keyword arguments: Any other keyword arguments are passed to the function run_static_analysis().

Returns

networkx MultiGraph object containing the contact map. For details on
viewing the contact map graphically seefunc:run_static_analysis (notes
section).

pysb.kappa.influence_map(model, **kwargs)[source]¶

Generates the influence map via KaSa.

Parameters

modelpysb.core.Model: The model for generating the influence map.
**kwargsother keyword arguments: Any other keyword arguments are passed to the function run_static_analysis().

Returns

networkx MultiGraph object containing the influence map. For details on
viewing the influence map graphically seefunc:run_static_analysis
(notes section).

pysb.kappa.run_simulation(model, time=10000, points=200, cleanup=True, output_prefix=None, output_dir=None, flux_map=False, perturbation=None, seed=None, verbose=False)[source]¶

Runs the given model using KaSim and returns the parsed results.

Deprecated since version 1.10.

Use pysb.simulator.KappaSimulator() instead

Parameters

modelpysb.core.Model: The model to simulate/analyze using KaSim.
timenumber: The amount of time (in arbitrary units) to run a simulation. Identical to the -u time -l argument when using KaSim at the command line. Default value is 10000. If set to 0, no simulation will be run.
pointsinteger: The number of data points to collect for plotting. Note that this is not identical to the -p argument of KaSim when called from the command line, which denotes plot period (time interval between points in plot). Default value is 200. Note that the number of points actually returned by the simulator will be points + 1 (including the 0 point).
cleanupboolean: Specifies whether output files produced by KaSim should be deleted after execution is completed. Default value is True.
output_prefix: str: Prefix of the temporary directory name. Default is ‘tmpKappa_<model name>_’.
output_dirstring: The directory in which to create the temporary directory for the .ka and other output files. Defaults to the system temporary file directory (e.g. /tmp). If the specified directory does not exist, an Exception is thrown.
flux_map: boolean: Specifies whether or not to produce the flux map (generated over the full duration of the simulation). Default value is False.
perturbationstring or None: Optional perturbation language syntax to be appended to the Kappa file. See KaSim manual for more details. Default value is None (no perturbation).
seedinteger: A seed integer for KaSim random number generator. Set to None to allow KaSim to use a random seed (default) or supply a seed for deterministic behaviour (e.g. for testing)
verboseboolean: Whether to pass the output of KaSim through to stdout/stderr.

Returns

If flux_map is False, returns the kasim simulation data as a Numpy ndarray.
Data is accessed using the syntax::: results[index_name]
The index ‘time’ gives the time coordinates of the simulation. Data for the
observables can be accessed by indexing the array with the names of the
observables. Each entry in the ndarray has length points + 1, due to the
inclusion of both the zero point and the final timepoint.
If flux_map is True, returns an instance of SimulationResult, a namedtuple
with two members, timecourse and flux_map. The timecourse field
contains the simulation ndarray, and the flux_map field is an instance of
a networkx MultiGraph containing the flux map. For details on viewing
the flux map graphically seefunc:run_static_analysis (notes section).

pysb.kappa.run_static_analysis(model, influence_map=False, contact_map=False, cleanup=True, output_prefix=None, output_dir=None, verbose=False)[source]¶

Run static analysis (KaSa) on to get the contact and influence maps.

If neither influence_map nor contact_map are set to True, then a ValueError is raised.

Parameters

modelpysb.core.Model: The model to simulate/analyze using KaSa.
influence_mapboolean: Whether to compute the influence map.
contact_mapboolean: Whether to compute the contact map.
cleanupboolean: Specifies whether output files produced by KaSa should be deleted after execution is completed. Default value is True.
output_prefix: str: Prefix of the temporary directory name. Default is ‘tmpKappa_<model name>_’.
output_dirstring: The directory in which to create the temporary directory for the .ka and other output files. Defaults to the system temporary file directory (e.g. /tmp). If the specified directory does not exist, an Exception is thrown.
verboseboolean: Whether to pass the output of KaSa through to stdout/stderr.

Returns

StaticAnalysisResult, a namedtuple with two fields, contact_map and
influence_map, each containing the respective result as an instance
of a networkx MultiGraph. If the either the contact_map or influence_map
argument to the function is False, the corresponding entry in the
StaticAnalysisResult returned by the function will be None.

Notes

To view a networkx file graphically, use draw_network:

import networkx as nx
nx.draw_networkx(g, with_labels=True)

You can use graphviz_layout to use graphviz for layout (requires pydot library):

import networkx as nx
pos = nx.drawing.nx_pydot.graphviz_layout(g, prog='dot')
nx.draw_networkx(g, pos, with_labels=True)

For further information, see the networkx documentation on visualization: https://networkx.github.io/documentation/latest/reference/drawing.html

pysb.kappa.set_kappa_path(path)[source]¶

Set the path to the KaSim and KaSa executables.

Deprecated. Use pysb.pathfinder.set_path() instead.

Parameters

path: string: Directory containing KaSim and KaSa executables.

Kappa integration (pysb.kappa)¶

Kappa integration (`pysb.kappa`)¶