def test_model_add__multiple_components__in_order(self):
import gillespy2
s1 = gillespy2.Species(name="s1", initial_value=29)
k1 = gillespy2.Parameter(name="k1", expression=29)
r1 = gillespy2.Reaction(name="r1", reactants={"s1": 1}, rate="k1")
rr1 = gillespy2.RateRule(name="rr1", variable="k1", formula="29")
ar1 = gillespy2.AssignmentRule(name="ar1", variable="s1", formula="29")
ea = gillespy2.EventAssignment(name="ea",
variable="k1",
expression="29")
et = gillespy2.EventTrigger(expression="t > 29")
e1 = gillespy2.Event(name="e1", trigger=et, assignments=[ea])
divide = gillespy2.FunctionDefinition(name="divide",
function="x / y",
args=["x", "y"])
tspan = gillespy2.TimeSpan(range(100))
model = gillespy2.Model(name="Test Model")
model.add([s1, k1, r1, rr1, ar1, e1, divide, tspan])
self.assertIn("ar1", model.listOfAssignmentRules)
self.assertIn("e1", model.listOfEvents)
self.assertIn("divide", model.listOfFunctionDefinitions)
self.assertIn("k1", model.listOfParameters)
self.assertIn("rr1", model.listOfRateRules)
self.assertIn("r1", model.listOfReactions)
self.assertIn("s1", model.listOfSpecies)
self.assertEqual(tspan, model.tspan)
def setUpClass(cls):
cls.solvers = [
SSACSolver,
ODESolver,
NumPySSASolver,
TauLeapingSolver,
TauHybridSolver,
ODECSolver,
TauLeapingCSolver,
TauHybridCSolver,
]
cls.sbml_features = {
"AssignmentRule": lambda model, variable:
model.add_assignment_rule(gillespy2.AssignmentRule(variable=variable, formula="1/(t+1)")),
"RateRule": lambda model, variable:
model.add_rate_rule(gillespy2.RateRule(variable=variable, formula="2*t")),
"Event": lambda model, variable:
model.add_event(gillespy2.Event(
trigger=gillespy2.EventTrigger(expression="t>1"),
assignments=[gillespy2.EventAssignment(variable=variable, expression="100")]
)),
"FunctionDefinition": lambda model, variable:
model.add_function_definition(
gillespy2.FunctionDefinition(name="fn", function="variable", args=["variable"])),
}
# List of supported SBML features for each solver.
# When a feature is implemented for a particular solver, add the feature to its list.
cls.solver_supported_sbml_features = {
NumPySSASolver: [],
TauLeapingSolver: [],
ODESolver: [],
TauHybridSolver: [
"AssignmentRule",
"RateRule",
"Event",
"FunctionDefinition",
],
SSACSolver: [],
ODECSolver: [],
TauLeapingCSolver: [],
TauHybridCSolver: [
"RateRule",
"Event",
],
}
cls.model = create_decay()
cls.results = {}
cls.labeled_results = {}
cls.labeled_results_more_trajectories = {}
def __get_function_definitions(sbml_model, gillespy_model):
# TODO:
# DOES NOT CURRENTLY SUPPORT ALL MATHML
# ALSO DOES NOT SUPPORT NON-MATHML
for i in range(sbml_model.getNumFunctionDefinitions()):
function = sbml_model.getFunctionDefinition(i)
function_name = function.getId()
function_tree = function.getMath()
num_nodes = function_tree.getNumChildren()
function_args = [function_tree.getChild(i).getName() for i in range(num_nodes-1)]
function_string = __get_math(function_tree.getChild(num_nodes-1))
gillespy_function = gillespy2.FunctionDefinition(name=function_name, function=function_string, args=function_args)
gillespy_model.add_function_definition(gillespy_function)
init_state[gillespy_function.name] = gillespy_function.function
def test_add_function_definition(self):
model = Example()
funcdef = gillespy2.FunctionDefinition(name='fun', function='Sp+1')
model.add_function_definition(funcdef)
results = model.run()
self.assertEqual(results[0].solver_name,'TauHybridSolver')
