gillespy2.solvers.utilities package

Submodules

gillespy2.solvers.utilities.Tau module

This Python module contains the initialization and selection methods for the Tau-Leaping method described in Cao, Y.; Gillespie, D. T.; Petzold, L. R. (2006). “Efficient step size selection for the tau-leaping simulation method” (PDF). The Journal of Chemical Physics. 124 (4): 044109. Bibcode:2006JChPh.124d4109C. doi:10.1063/1.2159468. PMID 16460151. This module is for use in the basic_tau_leaping_solver and basic_tau_hybrid solver only.

gillespy2.solvers.utilities.Tau.initialize(model, epsilon)[source]

This method initailizes the state for tau-leaping selections to be made. Based on Cao, Y.; Gillespie, D. T.; Petzold, L. R. (2006). “Efficient step size selection for the tau-leaping simulation method” (PDF). The Journal of Chemical Physics. 124 (4): 044109. Bibcode:2006JChPh.124d4109C. doi:10.1063/1.2159468. PMID 16460151

gillespy2.solvers.utilities.Tau.select(*tau_args)[source]

Tau Selection method based on Cao, Y.; Gillespie, D. T.; Petzold, L. R. (2006). “Efficient step size selection for the tau-leaping simulation method” (PDF). The Journal of Chemical Physics. 124 (4): 044109. Bibcode:2006JChPh.124d4109C. doi:10.1063/1.2159468. PMID 16460151

gillespy2.solvers.utilities.cpp_support_test module

This file contains a function and variable for testing a machines support of GillesPy2 C++ solvers. Used in model.py

gillespy2.solvers.utilities.cpp_support_test.check_cpp_support()[source]

gillespy2.solvers.utilities.solverutils module

gillespy2.solvers.utilities.solverutils.change_param_values(listOfParameters, parameters, volume, variables)[source]
gillespy2.solvers.utilities.solverutils.dependency_grapher(model, reactions)[source]

This function returns a dependency graph for a models reactions in the form of a dictionary containing {species name: {‘dependencies’}:[list of reaction names]}.

Parameters:

  • model – Model to used to create a reaction dependency graph

  • reactions – list[model.listOfReactions]

Returns:

Dependency graph dictionary

gillespy2.solvers.utilities.solverutils.numpy_initialization(model)[source]
gillespy2.solvers.utilities.solverutils.numpy_resume(timeStopped, simulation_data, resume=None)[source]

Helper function for when resuming a simulation in a numpy based solver.

Parameters:

  • timeStopped – The time in which the simulation was stopped.

  • simulation_data – The current models simulation data, after being parsed in the numpy solver of choice.

  • resume (gillespy2.core.Results) – The previous simulations data, that is being resumed

Returns:

Combined simulation data, the old resume data and the current simulation data.

gillespy2.solvers.utilities.solverutils.numpy_trajectory_base_initialization(model, number_of_trajectories, timeline, species, resume=None)[source]
gillespy2.solvers.utilities.solverutils.species_parse(model, custom_prop_fun)[source]

This function uses Pythons AST module to parse custom propensity function, looking for Species in a model

Parameters:

  • model – Model to be checked for species

  • custom_prop_fun – The custom propensity function to be parsed

Returns:

List of species objects that are found in a custom propensity function

gillespy2.solvers.utilities.solverutils.update_species_init_values(listOfSpecies, species, variables, resume=None)[source]

Module contents