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HOTFIX: Test all solvers #794

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merged 2 commits into from
May 16, 2022
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HOTFIX: Test all solvers #794

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53309cf
Fixed the test_all_solvers module.
BryanRumsey May 11, 2022
c438b37
Merge branch 'develop' of https://github.com/StochSS/GillesPy2 into h…
BryanRumsey May 16, 2022
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197 changes: 105 additions & 92 deletions test/test_all_solvers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,93 +32,92 @@

class TestAllSolvers(unittest.TestCase):

solvers = [
SSACSolver,
ODESolver,
NumPySSASolver,
TauLeapingSolver,
TauHybridSolver,
ODECSolver,
TauLeapingCSolver,
TauHybridCSolver,
]

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.
solver_supported_sbml_features = {
NumPySSASolver: [],
TauLeapingSolver: [],
ODESolver: [],
TauHybridSolver: [
"AssignmentRule",
"RateRule",
"Event",
"FunctionDefinition",
],

SSACSolver: [],
ODECSolver: [],
TauLeapingCSolver: [],
TauHybridCSolver: [
"RateRule",
"Event",
],
}

model = Example()
for sp in model.listOfSpecies.values():
sp.mode = 'discrete'
results = {}
labeled_results = {}
labeled_results_more_trajectories = {}

for solver in solvers:
solver = solver(model=model)
labeled_results[solver.name] = model.run(solver=solver, number_of_trajectories=1, seed=1)
labeled_results_more_trajectories[solver.name] = model.run(solver=solver, number_of_trajectories=2)

def test_instantiated(self):
@classmethod
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 = Example()

cls.results = {}
cls.labeled_results = {}
cls.labeled_results_more_trajectories = {}

def test_extraneous_args(self):
for solver in self.solvers:
self.model.run(solver=solver(model=self.model))
with self.subTest(solver=solver.name), self.assertLogs('GillesPy2', level='WARN'):
model = Example()
solver = solver(model=model)
model.run(solver=solver, nonsense='ABC')

def test_to_array(self):
for solver in self.solvers:
self.assertTrue(isinstance(self.labeled_results[solver.name].to_array()[0], np.ndarray))
def test_instantiated(self):
for sp in self.model.listOfSpecies.values():
sp.mode = 'discrete'

def test_return_type_show_labels(self):
for solver in self.solvers:
self.assertTrue(isinstance(self.labeled_results[solver.name], Results))
self.assertTrue(isinstance(self.labeled_results[solver.name]['Sp'], np.ndarray))
self.assertTrue(isinstance(self.labeled_results[solver.name]['Sp'][0], np.float))

self.assertTrue(isinstance(self.labeled_results[solver.name][0], Trajectory))

self.assertTrue(isinstance(self.labeled_results_more_trajectories[solver.name], Results))
self.assertTrue(isinstance(self.labeled_results_more_trajectories[solver.name][0], Trajectory))
self.assertTrue(isinstance(self.labeled_results_more_trajectories[solver.name][0]['Sp'], np.ndarray))
self.assertTrue(isinstance(self.labeled_results_more_trajectories[solver.name][0]['Sp'][0], np.float))
with self.subTest(solver=solver.name):
solver = solver(model=self.model)
if "ODE" in solver.name:
self.labeled_results[solver.name] = self.model.run(solver=solver, number_of_trajectories=1)
else:
self.labeled_results[solver.name] = self.model.run(solver=solver, number_of_trajectories=1, seed=1)
self.labeled_results_more_trajectories[solver.name] = self.model.run(solver=solver, number_of_trajectories=2)

def test_random_seed(self):
for solver in self.solvers:
with self.subTest(solver=solver.name):
solver = solver(model=self.model)
same_results = self.model.run(solver=solver, seed=1)
compare_results = self.model.run(solver=solver,seed=1)
if "ODE" in solver.name:
same_results = self.model.run(solver=solver)
compare_results = self.model.run(solver=solver)
else:
same_results = self.model.run(solver=solver, seed=1)
compare_results = self.model.run(solver=solver,seed=1)
self.assertTrue(np.array_equal(same_results.to_array(), compare_results.to_array()))
if solver.name in ["ODESolver", "ODECSolver"]: continue
diff_results = self.model.run(solver=solver, seed=2)
Expand All @@ -133,27 +132,29 @@ def test_random_seed_unnamed_reactions(self):
for solver in self.solvers:
with self.subTest(solver=solver.name):
solver = solver(model=self.model)
same_results = self.model.run(solver=solver, seed=1)
compare_results = self.model.run(solver=solver,seed=1)
if "ODE" in solver.name:
same_results = self.model.run(solver=solver)
compare_results = self.model.run(solver=solver)
else:
same_results = self.model.run(solver=solver, seed=1)
compare_results = self.model.run(solver=solver,seed=1)
self.assertTrue(np.array_equal(same_results.to_array(), compare_results.to_array()))
if solver.name in ["ODESolver", "ODECSolver"]: continue
diff_results = self.model.run(solver=solver, seed=2)
self.assertFalse(np.array_equal(diff_results.to_array(), same_results.to_array()))

def test_extraneous_args(self):
def test_return_type_show_labels(self):
for solver in self.solvers:
with self.subTest(solver=solver.name), self.assertLogs('GillesPy2', level='WARN'):
model = Example()
solver = solver(model=model)
model.run(solver=solver, nonsense='ABC')
self.assertTrue(isinstance(self.labeled_results[solver.name], Results))
self.assertTrue(isinstance(self.labeled_results[solver.name]['Sp'], np.ndarray))
self.assertTrue(isinstance(self.labeled_results[solver.name]['Sp'][0], np.float))

def test_timeout(self):
for solver in self.solvers:
with self.subTest(solver=solver.name), self.assertLogs('GillesPy2', level='WARN'):
model = Oregonator()
model.timespan(np.linspace(0, 1000000, 1001))
solver = solver(model=model)
model.run(solver=solver, timeout=0.1)
self.assertTrue(isinstance(self.labeled_results[solver.name][0], Trajectory))

self.assertTrue(isinstance(self.labeled_results_more_trajectories[solver.name], Results))
self.assertTrue(isinstance(self.labeled_results_more_trajectories[solver.name][0], Trajectory))
self.assertTrue(isinstance(self.labeled_results_more_trajectories[solver.name][0]['Sp'], np.ndarray))
self.assertTrue(isinstance(self.labeled_results_more_trajectories[solver.name][0]['Sp'][0], np.float))

def test_sbml_feature_validation(self):
class TestModel(gillespy2.Model):
Expand Down Expand Up @@ -181,6 +182,18 @@ def __init__(self):
add_sbml_feature(model, "S")
solver.validate_sbml_features(model=model)

def test_timeout(self):
for solver in self.solvers:
with self.subTest(solver=solver.name), self.assertLogs('GillesPy2', level='WARN'):
model = Oregonator()
model.timespan(np.linspace(0, 1000000, 1001))
solver = solver(model=model)
model.run(solver=solver, timeout=0.1)

def test_to_array(self):
for solver in self.solvers:
self.assertTrue(isinstance(self.labeled_results[solver.name].to_array()[0], np.ndarray))


if __name__ == '__main__':
unittest.main()