def test_run_experiment(self):
mockMSI = mock.Mock(spec=Model)
mockMSI.name = 'test'
mockMSI.uncertainties = [
RealParameter("a", 0, 10),
RealParameter("b", 0, 10)
]
msis = NamedObjectMap(AbstractModel)
msis['test'] = mockMSI
runner = ExperimentRunner(msis)
experiment = Case('test', mockMSI.name, Policy('none'),
Scenario(a=1, b=2), 0)
runner.run_experiment(experiment)
sc, p = mockMSI.run_model.call_args[0]
self.assertEqual(sc.name, experiment.scenario.name)
self.assertEqual(p, experiment.policy)
mockMSI.reset_model.assert_called_once_with()
# assert handling of case error
mockMSI = mock.Mock(spec=Model)
mockMSI.name = 'test'
mockMSI.run_model.side_effect = Exception('some exception')
msis = NamedObjectMap(AbstractModel)
msis['test'] = mockMSI
runner = ExperimentRunner(msis)
experiment = Case('test', mockMSI.name, Policy('none'),
Scenario(a=1, b=2), 0)
with self.assertRaises(EMAError):
runner.run_experiment(experiment)
# assert handling of case error
mockMSI = mock.Mock(spec=Model)
mockMSI.name = 'test'
mockMSI.run_model.side_effect = CaseError("message", {})
msis = NamedObjectMap(AbstractModel)
msis['test'] = mockMSI
runner = ExperimentRunner(msis)
experiment = Case('test', mockMSI.name, Policy('none'),
Scenario(a=1, b=2), 0)
runner.run_experiment(experiment)
def test_store_results(self):
nr_experiments = 3
uncs = [RealParameter("a", 0, 1), RealParameter("b", 0, 1)]
outcomes = [TimeSeriesOutcome("test")]
model = NamedObject('test')
experiment = Case(0, model, Policy('policy'), Scenario(a=1, b=0), 0)
# case 1 scalar shape = (1)
callback = DefaultCallback(uncs, [],
outcomes,
nr_experiments=nr_experiments)
model_outcomes = {outcomes[0].name: 1}
callback(experiment, model_outcomes)
_, out = callback.get_results()
self.assertIn(outcomes[0].name, out.keys())
self.assertEqual(out[outcomes[0].name].shape, (3, ))
# case 2 time series shape = (1, nr_time_steps)
callback = DefaultCallback(uncs, [],
outcomes,
nr_experiments=nr_experiments)
model_outcomes = {outcomes[0].name: np.random.rand(10)}
callback(experiment, model_outcomes)
_, out = callback.get_results()
self.assertIn(outcomes[0].name, out.keys())
self.assertEqual(out[outcomes[0].name].shape, (3, 10))
# case 3 maps etc. shape = (x,y)
callback = DefaultCallback(uncs, [],
outcomes,
nr_experiments=nr_experiments)
model_outcomes = {outcomes[0].name: np.random.rand(2, 2)}
callback(experiment, model_outcomes)
_, out = callback.get_results()
self.assertIn(outcomes[0].name, out.keys())
self.assertEqual(out[outcomes[0].name].shape, (3, 2, 2))
# case 4 assert raises EMAError
callback = DefaultCallback(uncs, [],
outcomes,
nr_experiments=nr_experiments)
model_outcomes = {outcomes[0].name: np.random.rand(2, 2, 2)}
self.assertRaises(EMAError, callback, experiment, model_outcomes)
def test_store_results(self):
nr_experiments = 3
uncs = [RealParameter("a", 0, 1),
RealParameter("b", 0, 1)]
outcomes = [TimeSeriesOutcome("test")]
constraints = []
model = NamedObject('test')
experiment = Case(0, model, Policy('policy'),
Scenario(a=1, b=0), 0)
# case 1 scalar shape = (1)
callback = DefaultCallback(uncs, [], outcomes, constraints,
nr_experiments=nr_experiments)
model_outcomes = {outcomes[0].name: 1}
model_constraints = {}
callback(experiment, model_outcomes, model_constraints)
_, out = callback.get_results()
self.assertIn(outcomes[0].name, out.keys())
self.assertEqual(out[outcomes[0].name].shape, (3,))
# case 2 time series shape = (1, nr_time_steps)
callback = DefaultCallback(uncs, [], outcomes, constraints,
nr_experiments=nr_experiments)
model_outcomes = {outcomes[0].name: np.random.rand(10)}
model_constraints = {}
callback(experiment, model_outcomes, model_constraints)
_, out = callback.get_results()
self.assertIn(outcomes[0].name, out.keys())
self.assertEqual(out[outcomes[0].name].shape, (3,10))
# case 3 maps etc. shape = (x,y)
callback = DefaultCallback(uncs, [], outcomes, constraints,
nr_experiments=nr_experiments)
model_outcomes = {outcomes[0].name: np.random.rand(2,2)}
model_constraints = {}
callback(experiment, model_outcomes, model_constraints)
_, out = callback.get_results()
self.assertIn(outcomes[0].name, out.keys())
self.assertEqual(out[outcomes[0].name].shape, (3,2,2))
# case 4 assert raises EMAError
callback = DefaultCallback(uncs, [], outcomes, constraints,
nr_experiments=nr_experiments)
model_outcomes = {outcomes[0].name: np.random.rand(2,2,2)}
model_constraints = {}
self.assertRaises(EMAError, callback, experiment, model_outcomes,
model_constraints)
# KeyError
with mock.patch('ema_workbench.util.ema_logging.debug') as mocked_logging:
callback = DefaultCallback(uncs, [], outcomes, constraints,
nr_experiments=nr_experiments)
model_outcomes = {'incorrect': np.random.rand(2,)}
model_constraints = {}
callback(experiment, model_outcomes, model_constraints)
for outcome in outcomes:
mocked_logging.assert_called_with("%s not specified as outcome in msi" % outcome.name)
def test_store_cases(self):
nr_experiments = 3
uncs = [RealParameter("a", 0, 1),
RealParameter("b", 0, 1),
CategoricalParameter('c', [0, 1, 2]),
IntegerParameter("d", 0, 1)]
outcomes = [TimeSeriesOutcome("test")]
constraints = []
case = {unc.name:random.random() for unc in uncs}
case["c"] = int(round(case["c"]*2))
case["d"] = int(round(case["d"]))
model = NamedObject('test')
policy = Policy('policy')
scenario = Scenario(**case)
experiment = Case(0, model.name, policy, scenario, 0)
callback = DefaultCallback(uncs, [],outcomes, constraints,
nr_experiments=nr_experiments,
reporting_interval=1)
model_outcomes = {outcomes[0].name: 1}
model_constraints = {}
callback(experiment, model_outcomes, model_constraints)
experiments, _ = callback.get_results()
design = case
design['policy'] = policy.name
design['model'] = model.name
design['scenario_id'] = scenario.name
names = rf.get_names(experiments.dtype)
for name in names:
entry_a = experiments[name][0]
entry_b = design[name]
self.assertEqual(entry_a, entry_b, "failed for "+name)
# with levers
nr_experiments = 3
uncs = [RealParameter("a", 0, 1),
RealParameter("b", 0, 1)]
levers = [RealParameter("c", 0, 1),
RealParameter("d", 0, 1)]
outcomes = [TimeSeriesOutcome("test")]
case = {unc.name:random.random() for unc in uncs}
model = NamedObject('test')
policy = Policy('policy', c=1, d=1)
scenario = Scenario(**case)
experiment = Case(0, model.name, policy, scenario, 0)
callback = DefaultCallback(uncs, levers,outcomes,constraints,
nr_experiments=nr_experiments,
reporting_interval=1)
model_outcomes = {outcomes[0].name: 1}
model_constraints = {}
callback(experiment, model_outcomes, model_constraints)
experiments, _ = callback.get_results()
design = case
design['c'] = 1
design['d'] = 1
design['policy'] = policy.name
design['model'] = model.name
design['scenario_id'] = scenario.name
names = rf.get_names(experiments.dtype)
for name in names:
self.assertEqual(experiments[name][0], design[name])