mobspy.sbml_simulator package
Submodules
mobspy.sbml_simulator.SBMLWriter module
This module is responsible for converting a model_str into a SBML format
- mobspy.sbml_simulator.SBMLWriter.check(value, message='error')
If ‘value’ is None, prints an error message constructed using ‘message’ and then exits with status code 1. If ‘value’ is an integer, it assumes it is a libSBML return status code. If the code value is LIBSBML_OPERATION_SUCCESS, returns without further action; if it is not, prints an error message constructed using ‘message’ along with text from libSBML explaining the meaning of the code, and exits with status code 1.
- mobspy.sbml_simulator.SBMLWriter.create_model(species={}, parameters={}, reactions={}, events={})
Returns an SBML Level 3 model. Example: species = { ‘E’: 1,
‘EM’: 0, ‘EM2’: 0, ‘F’: 100, },
- parameters = {‘k’: (1e-06,’per_min’),
}
- reactions = { ‘Production_E’:
- { ‘re’: [(1,’E’),(1,’F’)],
‘pr’: [(2,’E’)], ‘kin’ : ‘k * E * F’
},
},
- events = {‘e’:
- { ‘trigger’: ‘true’,
‘delay’: ‘10’, ‘assignments’: [(‘M’,’1’),],
},
}
mobspy.sbml_simulator.builder module
Picks and translates a python model into an SBML readable by Copasi. New models must be references here as well.
- mobspy.sbml_simulator.builder.build(species, parameters, reactions, events)
Constructs the sbml file for a model from the dictionary syntax for python sbml lib
- Parameters:
species – (dict) species as keys and counts as values
parameters – (dict) parameter name and value
reactions – (dict) reaction name and reaction in python sbml writer format
events – (dict) event name and event in python sbml writer format
- Returns:
sbml_str (str) = string describing the model in sbml format
mobspy.sbml_simulator.run module
- mobspy.sbml_simulator.run.job_execution(params, models, jobs)
This is defined for parallelism purposes Uses multiple cores from the processor to execute stochastic simulations
- Parameters:
params – (dict) = simulation parameters
models – (list) [{‘species_for_sbml’:, ‘parameters_for_sbml’:, ‘reactions_for_sbml’:, ‘events_for_sbml’:, ‘species_not_mapped’:, ‘mappings’:}]
jobs – (int) = number of cores to use, -1 for all available
- Returns:
parallel_data data of all the individual simulations executed in parallel
- mobspy.sbml_simulator.run.reformat_time_series(data)
Transforms the _dot_ in from the results into .
- Parameters:
data – (pd.dataframe) simulation data results from BasiCO
- mobspy.sbml_simulator.run.simulate(jobs, list_of_params, models)
This function coordinates the simulation by calling the necessary jobs In the future we hope to implement parallel cluster computing compatibility
- Parameters:
list_of_params – (dict) simulation parameters from the text file
models – (list) [{‘species_for_sbml’:, ‘parameters_for_sbml’:, ‘reactions_for_sbml’:, ‘events_for_sbml’:, ‘species_not_mapped’:, ‘mappings’:}]
- Returns:
data (dict) = dictionary containing the resulting data from simulation