def create_simple_hybrid_model(parameter_values=None):
model = Model(name="Simple_Hybrid_Model")
# Species
A = Species(name='A', initial_value=0)
B = Species(name='B', initial_value=0)
model.add_species([A, B])
# Parameters
k1 = Parameter(name='k1', expression=1)
k2 = Parameter(name='k2', expression=10)
model.add_parameter([k1, k2])
# Rate Rule
rate_rule = RateRule(name='Brate', variable='B', formula="cos(t)")
model.add_rate_rule(rate_rule)
# Reactions
r1 = Reaction(name='r1',
reactants={A: 1},
products={},
propensity_function="k1*B")
r2 = Reaction(name='r2', reactants={}, products={B: 1}, rate=k2)
model.add_reaction([r1, r2])
model.timespan(numpy.linspace(0, 1, 11))
return model
def test_species_parameter_name_substrings(self):
model = Model()
rate = Parameter(name='rate', expression=1)
model.add_parameter(rate)
species1 = Species('A', initial_value=100)
species2 = Species('AA', initial_value=0)
model.add_species([species1, species2])
reaction1 = Reaction(name="reaction1",
reactants={species1: 1},
products={species2: 1},
rate=rate)
model.add_reaction(reaction1)
number_points = 11
model.timespan(np.linspace(0, 1, number_points))
from gillespy2.solvers.numpy.ssa_solver import NumPySSASolver
results = model.run(number_of_trajectories=1,
solver=NumPySSASolver,
seed=1)
self.assertTrue(len(results['time']) == number_points)
self.assertTrue(len(results[species1.name]) == number_points)
self.assertTrue(len(results[species2.name]) == number_points)
self.assertGreater(results[species1.name][0],
results[species1.name][-1])
self.assertLess(results[species2.name][0], results[species2.name][-1])
self.assertEqual(
np.sum(results[species1.name]) + np.sum(results[species2.name]),
number_points * species1.initial_value)
def test_uniform_timespan(self):
model = Model()
model.timespan(np.linspace(0, 1, 100))
with self.assertRaises(InvalidModelError):
model.timespan(np.array([0, 0.1, 0.5]))
def create_oregonator(parameter_values=None):
# Superclass initialization
model = Model(name="Oregonator")
# Species
F = Species(name="F", initial_value=2)
A = Species(name="A", initial_value=250)
B = Species(name="B", initial_value=500)
C = Species(name="C", initial_value=1000)
P = Species(name="P", initial_value=0)
model.add_species([F, A, B, C, P])
# Parameters (rates)
k1 = Parameter(name="k1", expression=2.0)
k2 = Parameter(name="k2", expression=0.1)
k3 = Parameter(name="k3", expression=104)
k4 = Parameter(name="k4", expression=4e-7)
k5 = Parameter(name="k5", expression=26.0)
model.add_parameter([k1, k2, k3, k4, k5])
# Reactions
reaction1 = Reaction(name="reaction1",
reactants={
B: 1,
F: 1
},
products={
A: 1,
F: 1
},
rate=k1)
reaction2 = Reaction(name="reaction2",
reactants={
A: 1,
B: 1
},
products={P: 1},
rate=k2)
reaction3 = Reaction(name="reaction3",
reactants={
A: 1,
F: 1
},
products={
A: 2,
C: 1,
F: 1
},
rate=k3)
reaction4 = Reaction(name="reaction4",
reactants={A: 2},
products={P: 1},
rate=k4)
reaction5 = Reaction(name="reaction5",
reactants={
C: 1,
F: 1
},
products={
B: 1,
F: 1
},
rate=k5)
model.add_reaction([reaction1, reaction2, reaction3, reaction4, reaction5])
if sys.argv[1] != 'ODESolver':
model.timespan(np.linspace(0, 5, 501))
else:
model.timespan(np.linspace(0, 5, 500001))
return model
