def _simulate(self, model: Model, final_time=0.0):
starter = model.update(self.starter)
system = model.update(self.variant)
starter = starter.run_to_steady_state()
system = system.update_initial(starter)
return BioluciaSystemSimulation(system, final_time)
def test_updating(self):
m = equilibrium_model()
con1 = InitialValueExperiment(equilibrium_dose_variant())
con2 = InitialValueExperiment(Model().add('A0 = 15', 'kf = 0.3'))
active_parameters = ActiveParameters.from_model_experiments(
m, [con1, con2], ['kr'], [[], ['A0', 'kf']])
updated_parameters = active_parameters.update_parameters(
[4.0, 1.3, 2.0])
self.assertEqual(
updated_parameters,
ActiveParameters(OrderedDict([
('kr', 4.0)
]), [OrderedDict(),
OrderedDict([('A0', 1.3), ('kf', 2.0)])]))
active_parameters = ActiveParameters.from_model_experiments(
m, [con2, con2], ['kr'], [['kf'], ['A0', 'kf']])
updated_parameters = active_parameters.update_parameters(
[4.0, 3.4, 1.3, 2.0])
self.assertEqual(
updated_parameters,
ActiveParameters(OrderedDict([('kr', 4.0)]), [
OrderedDict([('kf', 3.4)]),
OrderedDict([('A0', 1.3), ('kf', 2.0)])
]))
def __init__(self, system: Model, final_time: float = 0.0):
self._observable_names = system.observable_names()
self.ode_system = system.build_odes()
self.final_time = 0.0
self.final_state = self.ode_system.ics()
self.solution_times = [0.0]
self.solution_states = [self.final_state]
# Ensure the discontinuities are sorted and there is always an infinity and never a 0
sorted_disc = sorted(set(self.ode_system.discontinuities + self.ode_system.dose_times + (inf,)))
zeroless_disc = sorted_disc if sorted_disc[0] != 0.0 else sorted_disc[1:]
self.all_discontinuities = zeroless_disc
self.i_next_discontinuity = 0
self.integrate_to(final_time)
def make_model(x):
maybe_options, components = x
if maybe_options:
raise NotImplementedError
parts, events = collapse_components(components)
new_model = Model(parts, events)
return new_model
def test_basic_fitting(self):
m = Model().add('k = 10')
con = InitialValueExperiment()
obj = LinearWeightedSumOfSquaresObservation(
[0], ['k'], AffineMeasurementUncertainty(1, 0)).objective([20])
fitted_parameters = fit_parameters(m, [con], [obj],
model_parameters='k')
self.assertAlmostEqual(fitted_parameters.model_parameters['k'], 20)
def test_extraction(self):
m = equilibrium_model()
con1 = InitialValueExperiment(equilibrium_dose_variant())
con2 = InitialValueExperiment(Model().add('A0 = 15', 'kf = 0.3'))
active_parameters = ActiveParameters.from_model_experiments(
m, [con1], ['kf', 'kr'], [[]])
self.assertEqual(
active_parameters,
ActiveParameters(OrderedDict([('kf', 0.5), ('kr', 0.2)]),
[OrderedDict()]))
active_parameters = ActiveParameters.from_model_experiments(
m, [con1, con2], ['kf', 'kr'], [])
self.assertEqual(
active_parameters,
ActiveParameters(OrderedDict([('kf', 0.5), ('kr', 0.2)]),
[OrderedDict(), OrderedDict()]))
active_parameters = ActiveParameters.from_model_experiments(
m, [con1, con2], ['kr', 'kf'], [])
self.assertEqual(
active_parameters,
ActiveParameters(OrderedDict([('kr', 0.2), ('kf', 0.5)]),
[OrderedDict(), OrderedDict()]))
active_parameters = ActiveParameters.from_model_experiments(
m, [con1, con2], ['kr', 'kf'], [])
self.assertEqual(
active_parameters,
ActiveParameters(OrderedDict([('kr', 0.2), ('kf', 0.5)]),
[OrderedDict(), OrderedDict()]))
active_parameters = ActiveParameters.from_model_experiments(
m, [con1, con2], [], [[], ['A0']])
self.assertEqual(
active_parameters,
ActiveParameters(
OrderedDict(),
[OrderedDict(), OrderedDict([('A0', 15)])]))
active_parameters = ActiveParameters.from_model_experiments(
m, [con1, con2], [], [[], ['A0', 'kf']])
self.assertEqual(
active_parameters,
ActiveParameters(
OrderedDict(),
[OrderedDict(),
OrderedDict([('A0', 15), ('kf', 0.3)])]))
def _simulate(self, model: Model, final_time=0.0):
system = model.update(self.variant)
return BioluciaSystemSimulation(system, final_time)
def __init__(self, starter: Model = Model(), variant: Model = Model()):
self.starter = starter
self.variant = variant
def __init__(self, variant: Model = Model()):
self.variant = variant
