def check_cpp_support():
from gillespy2.example_models import Example
try:
model = Example()
results = model.run(solver=SSACSolver)
return True
except:
return False
class TestBasicTauHybridSolver(unittest.TestCase):
model = Example()
results = model.run(solver=BasicTauHybridSolver, show_labels=False)
labels_results = model.run(solver=BasicTauHybridSolver, show_labels=True)
def test_return_type(self):
assert(isinstance(self.results, np.ndarray))
assert(isinstance(self.results[0], np.ndarray))
assert(isinstance(self.results[0][0], np.ndarray))
assert(isinstance(self.results[0][0][0], np.float))
def test_return_type_show_labels(self):
assert(isinstance(self.labels_results, list))
assert(isinstance(self.labels_results[0], dict))
assert(isinstance(self.labels_results[0]['Sp'], np.ndarray))
assert(isinstance(self.labels_results[0]['Sp'][0], np.float))
def test_add_rate_rule(self):
species = gillespy2.Species('test_species', initial_value=1, mode='continuous')
rule = gillespy2.RateRule(species, 'cos(t)')
self.model.add_species([species])
self.model.add_rate_rule([rule])
self.model.run(solver=BasicTauHybridSolver)
def test_add_rate_rule_dict(self):
species2 = gillespy2.Species('test_species2',initial_value=2, mode ='continuous')
species3 = gillespy2.Species('test_species3',initial_value=3, mode='continuous')
rule2 = gillespy2.RateRule(species2, 'cos(t)')
rule3 = gillespy2.RateRule(species3, 'sin(t)')
rate_rule_dict = {'rule2' :rule2, 'rule3':rule3}
self.model.add_species([species2,species3])
with self.assertRaises(ParameterError):
self.model.add_rate_rule(rate_rule_dict)
class TestBasicTauHybridSolver(unittest.TestCase):
model = Example()
def test_add_rate_rule(self):
species = gillespy2.Species('test_species', initial_value=1, mode='continuous')
rule = gillespy2.RateRule(species, 'cos(t)')
self.model.add_species([species])
self.model.add_rate_rule([rule])
self.model.run(solver=BasicTauHybridSolver)
def test_add_rate_rule_dict(self):
species2 = gillespy2.Species('test_species2', initial_value=2, mode='continuous')
species3 = gillespy2.Species('test_species3', initial_value=3, mode='continuous')
rule2 = gillespy2.RateRule(species2, 'cos(t)')
rule3 = gillespy2.RateRule(species=species3, expression='sin(t)')
rate_rule_dict = {'rule2': rule2, 'rule3': rule3}
self.model.add_species([species2, species3])
with self.assertRaises(ParameterError):
self.model.add_rate_rule(rate_rule_dict)
def test_add_bad_species_rate_rule_dict(self):
species2 = gillespy2.Species('test_species2', initial_value=2, mode='continuous')
rule = gillespy2.RateRule(expression='sin(t)')
with self.assertRaises(ModelError):
self.model.add_rate_rule(rule)
def test_add_bad_expression_rate_rule_dict(self):
species2 = gillespy2.Species('test_species2', initial_value=2, mode='continuous')
rule = gillespy2.RateRule(species=species2, expression='')
with self.assertRaises(ModelError):
self.model.add_rate_rule(rule)
class TestAllSolvers(unittest.TestCase):
solvers = [SSACSolver, BasicODESolver, NumPySSASolver, BasicTauLeapingSolver, BasicTauHybridSolver]
if can_use_cython:
solvers.append(CythonSSASolver)
model = Example()
results = {}
labeled_results = {}
labeled_results_more_trajectories = {}
for solver in solvers:
results[solver] = model.run(solver=solver, show_labels=False, seed=1)
labeled_results[solver] = model.run(solver=solver, show_labels=True,number_of_trajectories=1)
labeled_results_more_trajectories[solver] = model.run(solver=solver, show_labels=True,number_of_trajectories=2)
def test_instantiated(self):
for solver in self.solvers:
self.model.run(solver=solver())
def test_return_type(self):
for solver in self.solvers:
self.assertTrue(isinstance(self.results[solver], np.ndarray))
self.assertTrue(isinstance(self.results[solver][0], np.ndarray))
self.assertTrue(isinstance(self.results[solver][0][0], np.ndarray))
self.assertTrue(isinstance(self.results[solver][0][0][0], np.float))
def test_return_type_show_labels(self):
for solver in self.solvers:
self.assertTrue(isinstance(self.labeled_results[solver], Results))
self.assertTrue(isinstance(self.labeled_results[solver]['Sp'], np.ndarray))
self.assertTrue(isinstance(self.labeled_results[solver]['Sp'][0], np.float))
with self.assertWarns(Warning):
self.assertTrue(isinstance(self.labeled_results[solver][0], Results))
self.assertTrue(isinstance(self.labeled_results_more_trajectories[solver], EnsembleResults))
self.assertTrue(isinstance(self.labeled_results_more_trajectories[solver][0], Results))
self.assertTrue(isinstance(self.labeled_results_more_trajectories[solver][0]['Sp'], np.ndarray))
self.assertTrue(isinstance(self.labeled_results_more_trajectories[solver][0]['Sp'][0], np.float))
def test_random_seed(self):
for solver in self.solvers:
same_results = self.model.run(solver=solver, show_labels=False, seed=1)
self.assertTrue(np.array_equal(same_results, self.results[solver]))
diff_results = self.model.run(solver=solver, show_labels=False, seed=2)
if solver.name != 'BasicODESolver':
self.assertFalse(np.array_equal(diff_results, self.results[solver]))
def test_extraneous_args(self):
for solver in self.solvers:
print(solver.name)
with self.assertWarns(Warning):
model = Example()
results = model.run(solver=solver, nonsense='ABC')
def test_run_example(self):
model = Example()
for i in [1, self.number_of_trajectories]:
for label in [True, False]:
with self.subTest(number_of_trajectories=i, show_labels=label):
if i > 1:
with self.assertWarns(Warning):
results = model.run(solver=BasicODESolver,
show_labels=label,
number_of_trajectories=i)
else:
results = model.run(solver=BasicODESolver,
show_labels=label,
number_of_trajectories=i)
self.assertEqual(len(results), i)
self.assertTrue(
all([
isinstance(result, dict if label else np.ndarray)
for result in results
]))
if label:
result = results[0]
for species in model.listOfSpecies.keys():
self.assertIn(species, result.keys())
self.assertIsInstance(result[species], np.ndarray)
self.assertListEqual(list(result[species].shape),
list(model.tspan.shape))
else:
self.assertIsInstance(results, np.ndarray)
self.assertListEqual(list(results.shape), [
i,
len(model.tspan),
len(model.listOfSpecies.keys()) + 1
])
for result in results[1:]:
if label:
self.assertDictEqual(results[0], result)
else:
self.assertTrue(np.array_equal(results[0], result))
class TestAllSolvers(unittest.TestCase):
solvers = [
SSACSolver, BasicODESolver, NumPySSASolver, BasicTauLeapingSolver,
BasicTauHybridSolver, CythonSSASolver
]
model = Example()
results = {}
labeled_results = {}
for solver in solvers:
results[solver] = model.run(solver=solver, show_labels=False, seed=1)
labeled_results[solver] = model.run(solver=solver, show_labels=True)
def test_return_type(self):
for solver in self.solvers:
self.assertTrue(isinstance(self.results[solver], np.ndarray))
self.assertTrue(isinstance(self.results[solver][0], np.ndarray))
self.assertTrue(isinstance(self.results[solver][0][0], np.ndarray))
self.assertTrue(isinstance(self.results[solver][0][0][0],
np.float))
def test_return_type_show_labels(self):
for solver in self.solvers:
self.assertTrue(isinstance(self.labeled_results[solver], list))
self.assertTrue(isinstance(self.labeled_results[solver][0], dict))
self.assertTrue(
isinstance(self.labeled_results[solver][0]['Sp'], np.ndarray))
self.assertTrue(
isinstance(self.labeled_results[solver][0]['Sp'][0], np.float))
def test_random_seed(self):
for solver in self.solvers:
same_results = self.model.run(solver=solver,
show_labels=False,
seed=1)
self.assertTrue(np.array_equal(same_results, self.results[solver]))
diff_results = self.model.run(solver=solver,
show_labels=False,
seed=2)
if solver.name != 'BasicODESolver':
self.assertFalse(
np.array_equal(diff_results, self.results[solver]))
def test_extraneous_args(self):
for solver in self.solvers:
print(solver.name)
with self.assertWarns(Warning):
model = Example()
results = model.run(solver=solver, nonsense='ABC')
def test_run_example(self):
model = Example()
for i in [1, self.number_of_trajectories]:
for label in [True, False]:
with self.subTest(number_of_trajectories=i, show_labels=label):
if i > 1:
with self.assertWarns(Warning):
results = model.run(solver=BasicODESolver,
show_labels=label,
number_of_trajectories=i)
self.assertEqual(len(results), i)
else:
results = model.run(solver=BasicODESolver,
show_labels=label,
number_of_trajectories=i)
if i > 1 or not label:
for result in results[1:]:
if label:
self.assertEqual(results[0], result)
else:
self.assertTrue(
np.array_equal(results[0], result))
class TestBasicTauLeapingSolver(unittest.TestCase):
model = Example()
results = model.run(solver=BasicTauLeapingSolver, show_labels=False)
labels_results = model.run(solver=BasicTauLeapingSolver, show_labels=True)
def test_return_type(self):
assert (isinstance(self.results, np.ndarray))
assert (isinstance(self.results[0], np.ndarray))
assert (isinstance(self.results[0][0], np.ndarray))
assert (isinstance(self.results[0][0][0], np.float))
def test_return_type_show_labels(self):
assert (isinstance(self.labels_results, list))
assert (isinstance(self.labels_results[0], dict))
assert (isinstance(self.labels_results[0]['Sp'], np.ndarray))
assert (isinstance(self.labels_results[0]['Sp'][0], np.float))
def test_run_example(self):
model = Example()
results = model.run(solver=BasicTauHybridSolver)
def test_run_example(self):
model = Example()
results = model.run(solver=BasicTauLeapingSolver)
def test_extraneous_args(self):
for solver in self.solvers:
print(solver.name)
with self.assertWarns(Warning):
model = Example()
results = model.run(solver=solver, nonsense='ABC')
def test_StochML_from_and_to_model(self):
model = Example()
stochml = StochMLDocument.from_model(model)
stochml_model = stochml.to_model('model')
stochml_model.run(solver=BasicODESolver)
stochml_model.run(solver=NumPySSASolver)
def test_run_example(self):
if can_use_cython:
model = Example()
results = model.run(solver=CythonSSASolver)
class TestBasicTauLeapingSolver(unittest.TestCase):
model = Example()
def test_file_with_directory_name_exists(self):
with self.assertRaises(DirectoryError):
temp = tempfile.NamedTemporaryFile()
model = Example()
solver = SSACSolver(model, temp.name)
def test_run_example(self):
model = Example()
results = model.run(solver=NumPySSASolver)
class TestNumPySSASolver(unittest.TestCase):
model = Example()
def test_run_example_precompiled(self):
model = Example()
solver = SSACSolver(model)
results = model.run(solver=solver)
def test_create(self):
model = Example()
solver = SSACSolver(model)
