def test_to_robust_problem(self, mocked_platypus):
mocked_model = Model('test', function=mock.Mock())
mocked_model.levers = [
RealParameter('a', 0, 1),
RealParameter('b', 0, 1)
]
mocked_model.uncertainties = [
RealParameter('c', 0, 1),
RealParameter('d', 0, 1)
]
mocked_model.outcomes = [ScalarOutcome('x'), ScalarOutcome('y')]
scenarios = 5
robustness_functions = [
ScalarOutcome('mean x', variable_name='x', function=mock.Mock()),
ScalarOutcome('mean y', variable_name='y', function=mock.Mock())
]
problem = to_robust_problem(mocked_model, scenarios,
robustness_functions)
self.assertEqual('robust', problem.searchover)
for entry in problem.parameters:
self.assertIn(entry.name, mocked_model.levers.keys())
self.assertEqual(['a', 'b'], problem.parameter_names)
self.assertEqual(['mean x', 'mean y'], problem.outcome_names)
def test_to_problem(self, mocked_platypus):
mocked_model = Model('test', function=mock.Mock())
mocked_model.levers = [
RealParameter('a', 0, 1),
RealParameter('b', 0, 1)
]
mocked_model.uncertainties = [
RealParameter('c', 0, 1),
RealParameter('d', 0, 1)
]
mocked_model.outcomes = [ScalarOutcome('x'), ScalarOutcome('y')]
mocked_model.constraints = []
searchover = 'levers'
problem = to_problem(mocked_model, searchover)
self.assertEqual(searchover, problem.searchover)
for entry in problem.parameters:
self.assertIn(entry.name, mocked_model.levers.keys())
self.assertIn(entry, list(mocked_model.levers))
for entry in problem.outcome_names:
self.assertIn(entry.name, mocked_model.outcomes.keys())
searchover = 'uncertainties'
problem = to_problem(mocked_model, searchover)
self.assertEqual(searchover, problem.searchover)
for entry in problem.parameters:
self.assertIn(entry.name, mocked_model.uncertainties.keys())
self.assertIn(entry, list(mocked_model.uncertainties))
for entry in problem.outcome_names:
self.assertIn(entry.name, mocked_model.outcomes.keys())
def test_to_problem(self, mocked_platypus):
mocked_model = Model('test', function=mock.Mock())
mocked_model.levers = [RealParameter('a', 0, 1),
RealParameter('b', 0, 1)]
mocked_model.uncertainties = [RealParameter('c', 0, 1),
RealParameter('d', 0, 1)]
mocked_model.outcomes = [ScalarOutcome('x', kind=1),
ScalarOutcome('y', kind=1)]
searchover = 'levers'
problem = to_problem(mocked_model, searchover)
self.assertEqual(searchover, problem.searchover)
for entry in problem.parameters:
self.assertIn(entry.name, mocked_model.levers.keys())
self.assertIn(entry, list(mocked_model.levers))
for entry in problem.outcome_names:
self.assertIn(entry, mocked_model.outcomes.keys())
searchover = 'uncertainties'
problem = to_problem(mocked_model, searchover)
self.assertEqual(searchover, problem.searchover)
for entry in problem.parameters:
self.assertIn(entry.name, mocked_model.uncertainties.keys())
self.assertIn(entry, list(mocked_model.uncertainties))
for entry in problem.outcome_names:
self.assertIn(entry, mocked_model.outcomes.keys())
def test_to_robust_problem(self, mocked_platypus):
mocked_model = Model('test', function=mock.Mock())
mocked_model.levers = [RealParameter('a', 0, 1),
RealParameter('b', 0, 1)]
mocked_model.uncertainties = [RealParameter('c', 0, 1),
RealParameter('d', 0, 1)]
mocked_model.outcomes = [ScalarOutcome('x'), ScalarOutcome('y')]
scenarios = 5
robustness_functions = [ScalarOutcome('mean x', variable_name='x',
function=mock.Mock()),
ScalarOutcome('mean y', variable_name='y',
function=mock.Mock())]
problem = to_robust_problem(mocked_model, scenarios,
robustness_functions)
self.assertEqual('robust', problem.searchover)
for entry in problem.parameters:
self.assertIn(entry.name, mocked_model.levers.keys())
self.assertEqual(['mean x', 'mean y'], problem.outcome_names)
def test_perform_experiments(self):
# everything shared
model_a = Model("A", mock.Mock())
model_b = Model("B", mock.Mock())
model_c = Model("C", mock.Mock())
models = [model_a, model_b, model_c]
# let's add some uncertainties to this
shared_abc_1 = RealParameter("shared abc 1", 0, 1)
shared_abc_2 = RealParameter("shared abc 2", 0, 1)
shared_ab_1 = RealParameter("shared ab 1", 0, 1)
shared_bc_1 = RealParameter("shared bc 1", 0, 1)
a_1 = RealParameter("a 1", 0, 1)
b_1 = RealParameter("b 1", 0, 1)
model_a.uncertainties = [shared_abc_1, shared_abc_2, shared_ab_1, a_1]
model_b.uncertainties = [
shared_abc_1, shared_abc_2, shared_ab_1, shared_bc_1, b_1
]
model_c.uncertainties = [shared_abc_1, shared_abc_2, shared_bc_1]
#let's add an outcome to this
outcome_shared = TimeSeriesOutcome("test")
model_a.outcomes = [outcome_shared]
model_b.outcomes = [outcome_shared]
model_c.outcomes = [outcome_shared]
for model in models:
model.function.return_value = {
a: [0.1] * 10
for a in outcome_shared.variable_name
}
ensemble = ModelEnsemble()
ensemble.model_structures = [model_a, model_b, model_c]
ensemble.policies = [Policy('None')]
ensemble.perform_experiments(10,
uncertainty_union=True,
outcome_union=True,
reporting_interval=1)
# for model in models:
# model.function.assert_has_calls() TODO::
ensemble.perform_experiments(10,
uncertainty_union=True,
outcome_union=False,
reporting_interval=1)
ensemble.perform_experiments(10,
uncertainty_union=False,
outcome_union=True,
reporting_interval=1)
ensemble.perform_experiments(10,
uncertainty_union=False,
outcome_union=False,
reporting_interval=1)
#
# self.assertRaises(ValueError, ensemble.perform_experiments,
# 10, uncertainty_union=False,
# union_outcomes='Label')
with mock.patch(
'ema_workbench.em_framework.ensemble.MultiprocessingPool'
) as MockPool:
ensemble.parallel = True
mockedCallback = mock.Mock(DefaultCallback)
mockedCallback.configure_mock(**{'i': 30})
mockedCallback.return_value = mockedCallback
ensemble.perform_experiments(10,
uncertainty_union=True,
outcome_union=True,
reporting_interval=1,
callback=mockedCallback)
self.assertEqual(2, len(MockPool.mock_calls))
MockPool.reset_mock()
mockedCallback = mock.Mock(DefaultCallback)
mockedCallback.configure_mock(**{'i': 10})
mockedCallback.return_value = mockedCallback
self.assertRaises(EMAError,
ensemble.perform_experiments,
10,
uncertainty_union=True,
outcome_union=True,
reporting_interval=1,
callback=mockedCallback)
def test_perform_experiments(self):
# everything shared
model_a = Model("A", mock.Mock())
model_b = Model("B", mock.Mock())
model_c = Model("C", mock.Mock())
models = [model_a, model_b, model_c]
# let's add some uncertainties to this
shared_abc_1 = RealParameter("shared abc 1", 0, 1)
shared_abc_2 = RealParameter("shared abc 2", 0, 1)
shared_ab_1 = RealParameter("shared ab 1", 0, 1)
shared_bc_1 = RealParameter("shared bc 1", 0, 1)
a_1 = RealParameter("a 1", 0, 1)
b_1 = RealParameter("b 1", 0, 1)
model_a.uncertainties = [shared_abc_1, shared_abc_2, shared_ab_1, a_1]
model_b.uncertainties = [shared_abc_1, shared_abc_2, shared_ab_1, shared_bc_1, b_1]
model_c.uncertainties = [shared_abc_1, shared_abc_2, shared_bc_1]
#let's add an outcome to this
outcome_shared = TimeSeriesOutcome("test")
model_a.outcomes = [outcome_shared]
model_b.outcomes = [outcome_shared]
model_c.outcomes = [outcome_shared]
for model in models:
model.function.return_value = {a: [0.1]*10 for a in outcome_shared.variable_name}
ensemble = ModelEnsemble()
ensemble.model_structures = [model_a, model_b, model_c]
ensemble.policies = [Policy('None')]
ensemble.perform_experiments(10, uncertainty_union=True,
outcome_union=True,
reporting_interval=1 )
# for model in models:
# model.function.assert_has_calls() TODO::
ensemble.perform_experiments(10, uncertainty_union=True,
outcome_union=False,
reporting_interval=1 )
ensemble.perform_experiments(10, uncertainty_union=False,
outcome_union=True,
reporting_interval=1 )
ensemble.perform_experiments(10, uncertainty_union=False,
outcome_union=False,
reporting_interval=1 )
#
# self.assertRaises(ValueError, ensemble.perform_experiments,
# 10, uncertainty_union=False,
# union_outcomes='Label')
with mock.patch('ema_workbench.em_framework.ensemble.MultiprocessingPool') as MockPool:
ensemble.parallel = True
mockedCallback = mock.Mock(DefaultCallback)
mockedCallback.configure_mock(**{'i':30})
mockedCallback.return_value = mockedCallback
ensemble.perform_experiments(10, uncertainty_union=True,
outcome_union=True,
reporting_interval=1,
callback=mockedCallback)
self.assertEqual(2, len(MockPool.mock_calls))
MockPool.reset_mock()
mockedCallback = mock.Mock(DefaultCallback)
mockedCallback.configure_mock(**{'i':10})
mockedCallback.return_value = mockedCallback
self.assertRaises(EMAError, ensemble.perform_experiments,
10, uncertainty_union=True,
outcome_union=True, reporting_interval=1,
callback=mockedCallback)
