def test_get_simulation_engine(self):
model = MakeModel.make_test_model(
'2 species, 1 reaction, with rates given by reactant population')
simulation = Simulation(model)
self.assertEqual(simulation.get_simulation_engine(), None)
with CaptureOutput(relay=False):
simulation.run(time_max=5)
self.assertTrue(
isinstance(simulation.get_simulation_engine(), SimulationEngine))
def test_provide_event_counts(self):
model = MakeModel.make_test_model(
'2 species, 1 reaction, with rates given by reactant population')
simulation = Simulation(model)
self.assertTrue('execute run() to obtain event counts' in
simulation.provide_event_counts())
with CaptureOutput(relay=False):
simulation.run(time_max=100)
self.assertTrue('Event type' in simulation.provide_event_counts())
def _default(self):
args = self.app.pargs
simulation = Simulation(args.model_file)
simulation.run(time_max=args.time_max,
results_dir=args.results_dir,
checkpoint_period=args.checkpoint_period,
dfba_time_step=args.dfba_time_step,
profile=args.profile,
verbose=args.verbose)
def simulate(self, end_time, checkpoint_period, peturbation=None):
if perturbation:
model = copy.deepcopy(self.MODEL)
peturbation(model)
else:
model = self.MODEL
sim = Simulation(self.MODEL)
sim.run(time_max=end_time,
results_dir=self._results_path,
checkpoint_period=checkpoint_period)
return RunResults(self._results_path)
def simulate(self, model, time_max=100.):
# simulate
env = EnvironmentVarGuard()
env.set(
'CONFIG__DOT__wc_lang__DOT__validation__DOT__validate_element_charge_balance',
'0')
with env:
simulation = Simulation(model)
_, results_dirname = simulation.run(time_max=time_max,
ode_time_step=1.,
checkpoint_period=1.,
results_dir=self.tempdir)
# get results
results = RunResults(results_dirname)
agg_states = results.get('aggregate_states')
comp_mass = agg_states[(self.comp.id, 'mass')]
comp_vol = results.get('functions')[self.volume.id]
pops = results.get('populations')
time = pops.index
pop_constant = pops[self.spec_constant.id]
pop_dynamic = pops[self.spec_dynamic.id]
return (time, pop_constant, pop_dynamic, comp_mass, comp_vol)
def run_model(model, results_dir, checkpoint_period=5, end_time=100):
""" Simulates model """
if not os.path.exists(results_dir):
os.makedirs(results_dir)
simulation = Simulation(model)
results = simulation.run(end_time, results_dir, checkpoint_period)
return results
def simulate(self, end_time, checkpoint_period=None, n_sims=1):
results = []
simulation = Simulation(self.model)
for i_sim in range(n_sims):
temp_dir = tempfile.mkdtemp(dir=self.results_dir)
results_dir = simulation.run(
time_max=end_time,
results_dir=temp_dir,
checkpoint_period=checkpoint_period).results_dir
run_results = RunResults(results_dir)
results.append(run_results)
return results
def test_simulate_deterministic_simulation_algorithm_submodel(self):
model = MakeModel.make_test_model('1 species, 1 reaction')
self.transform_model_for_dsa_simulation(model)
simulation = Simulation(model)
num_events, _ = simulation.run(time_max=100)
self.assertGreater(num_events, 0)
def test_check_simul_results(self):
init_volume = 1E-16
init_density = 1000
molecular_weight = 100.
default_species_copy_number = 10_000
init_accounted_mass = molecular_weight * default_species_copy_number / Avogadro
init_accounted_density = init_accounted_mass / init_volume
expected_initial_values_compt_1 = dict(
init_volume=init_volume,
init_accounted_mass=init_accounted_mass,
init_mass=init_volume * init_density,
init_density=init_density,
init_accounted_density=init_accounted_density,
accounted_fraction=init_accounted_density / init_density)
expected_initial_values = {'compt_1': expected_initial_values_compt_1}
model = MakeModel.make_test_model(
'1 species, 1 reaction',
init_vols=[expected_initial_values_compt_1['init_volume']],
init_vol_stds=[0],
density=init_density,
molecular_weight=molecular_weight,
default_species_copy_number=default_species_copy_number,
default_species_std=0,
submodel_framework='WC:deterministic_simulation_algorithm')
multialgorithm_simulation = MultialgorithmSimulation(
model, self.wc_sim_config)
_, dynamic_model = multialgorithm_simulation.build_simulation()
check_simul_results(self,
dynamic_model,
None,
expected_initial_values=expected_initial_values)
# test dynamics
simulation = Simulation(model)
_, results_dir = simulation.run(time_max=2, **self.args)
nan = float('NaN')
check_simul_results(self, dynamic_model, results_dir,
expected_initial_values=expected_initial_values,
expected_species_trajectories=\
{'spec_type_0[compt_1]':[10000., 9999., 9998.]})
check_simul_results(self, dynamic_model, results_dir,
expected_initial_values=expected_initial_values,
expected_species_trajectories=\
{'spec_type_0[compt_1]':[nan, nan, nan]})
with self.assertRaises(AssertionError):
check_simul_results(self, dynamic_model, results_dir,
expected_initial_values=expected_initial_values,
expected_species_trajectories=\
{'spec_type_0[compt_1]':[10000., 10000., 9998.]})
with self.assertRaises(AssertionError):
check_simul_results(self, dynamic_model, results_dir,
expected_initial_values=expected_initial_values,
expected_species_trajectories=\
{'spec_type_0[compt_1]':[10000., 10000.]})
check_simul_results(self, dynamic_model, results_dir,
expected_initial_values=expected_initial_values,
expected_species_trajectories=\
{'spec_type_0[compt_1]':[10000., 9999., 9998.]},
rel_tol=1E-5)
check_simul_results(self,
dynamic_model,
results_dir,
expected_property_trajectories={
'compt_1': {
'mass': [1.000e-13, 9.999e-14, 9.998e-14]
}
})
check_simul_results(self,
dynamic_model,
results_dir,
expected_property_trajectories={
'compt_1': {
'mass': [nan, nan, nan]
}
})
with self.assertRaises(AssertionError):
check_simul_results(self,
dynamic_model,
results_dir,
expected_property_trajectories={
'compt_1': {
'mass':
[1.000e-13, 1.000e-13, 9.999e-14]
}
},
rel_tol=0)
plots_dir = os.path.abspath(
os.path.join(os.path.dirname(__file__), '..', '..', 'tests',
'results'))
os.makedirs(plots_dir, exist_ok=True)
plot_expected_vs_simulated(dynamic_model,
'ordinary_differential_equations',
results_dir,
trajectory_times=[0, 1, 2],
plots_dir=plots_dir,
expected_species_trajectories=\
{'spec_type_0[compt_1]':[10000., 10000., 9998.]},
expected_property_trajectories=\
{'compt_1':
{'mass':[1.000e-13, 1.000e-13, 9.999e-14]}})
plot_expected_vs_simulated(dynamic_model,
'ordinary_differential_equations',
results_dir,
trajectory_times=[0, 1, 2],
plots_dir=plots_dir,
expected_property_trajectories=\
{'compt_1':
{'mass':[1.000e-13, 1.000e-13, 9.999e-14]}})
plot_expected_vs_simulated(dynamic_model,
'ordinary_differential_equations',
results_dir,
trajectory_times=[0, 1, 2],
plots_dir=plots_dir,
expected_species_trajectories=\
{'spec_type_0[compt_1]':[10000., 10000., 9998.]})
plot_expected_vs_simulated(dynamic_model,
'ordinary_differential_equations',
results_dir,
trajectory_times=[0, 1, 2],
plots_dir=plots_dir,
expected_species_trajectories=\
{'spec_type_0[compt_1]':[nan, nan, nan]},
expected_property_trajectories=\
{'compt_1':
{'mass':[nan, nan, nan]}})