def test_store_results(self):
nr_experiments = 3
uncs = [ParameterUncertainty((0,1), "a"),
ParameterUncertainty((0,1), "b")]
outcomes = [Outcome("test", time=True)]
case = {unc.name:random.random() for unc in uncs}
policy = {'name':'none'}
name = "test"
# case 1 scalar shape = (1)
callback = DefaultCallback(uncs,
[outcome.name for outcome in outcomes],
nr_experiments=nr_experiments)
result = {outcomes[0].name: 1}
callback(0, case, policy, name, result)
_, 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,
[outcome.name for outcome in outcomes],
nr_experiments=nr_experiments)
result = {outcomes[0].name: np.random.rand(10)}
callback(0, case, policy, name, result)
_, 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,
[outcome.name for outcome in outcomes],
nr_experiments=nr_experiments)
result = {outcomes[0].name: np.random.rand(2,2)}
callback(0, case, policy, name, result)
_, 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,
[outcome.name for outcome in outcomes],
nr_experiments=nr_experiments)
result = {outcomes[0].name: np.random.rand(2,2,2)}
self.assertRaises(EMAError, callback, 0, case, policy, name, result)
# KeyError
with mock.patch('util.ema_logging.debug') as mocked_logging:
callback = DefaultCallback(uncs,
[outcome.name for outcome in outcomes],
nr_experiments=nr_experiments)
result = {'incorrect': np.random.rand(2,)}
callback(0, case, policy, name, result)
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 = [
ParameterUncertainty((0, 1), "a"),
ParameterUncertainty((0, 1), "b"),
CategoricalUncertainty([0, 1, 2], "c"),
ParameterUncertainty((0, 1), "d", integer=True),
]
outcomes = [Outcome("test", time=True)]
case = {unc.name: random.random() for unc in uncs}
case["c"] = int(round(case["c"] * 2))
case["d"] = int(round(case["d"]))
policy = {'name': 'none'}
name = "test"
callback = DefaultCallback(uncs,
[outcome.name for outcome in outcomes],
nr_experiments=nr_experiments,
reporting_interval=1)
result = {outcomes[0].name: 1}
callback(0, case, policy, name, result)
experiments, _ = callback.get_results()
design = case
design['policy'] = policy['name']
design['model'] = name
names = rf.get_names(experiments.dtype)
for name in names:
self.assertEqual(experiments[name][0], design[name])
def test_store_cases(self):
nr_experiments = 3
uncs = [ParameterUncertainty((0,1), "a"),
ParameterUncertainty((0,1), "b"),
CategoricalUncertainty([0, 1, 2], "c"),
ParameterUncertainty((0,1), "d", integer=True),]
outcomes = [Outcome("test", time=True)]
case = {unc.name:random.random() for unc in uncs}
case["c"] = int(round(case["c"]*2))
case["d"] = int(round(case["d"]))
policy = {'name':'none'}
name = "test"
callback = DefaultCallback(uncs,
[outcome.name for outcome in outcomes],
nr_experiments=nr_experiments,
reporting_interval=1)
result = {outcomes[0].name: 1}
callback(0, case, policy, name, result)
experiments, _ = callback.get_results()
design = case
design['policy'] = policy['name']
design['model'] = name
names = rf.get_names(experiments.dtype)
for name in names:
self.assertEqual(experiments[name][0], design[name])
def test_store_results(self):
nr_experiments = 3
uncs = [
ParameterUncertainty((0, 1), "a"),
ParameterUncertainty((0, 1), "b")
]
outcomes = [Outcome("test", time=True)]
case = {unc.name: random.random() for unc in uncs}
policy = {'name': 'none'}
name = "test"
# case 1 scalar shape = (1)
callback = DefaultCallback(uncs,
[outcome.name for outcome in outcomes],
nr_experiments=nr_experiments)
result = {outcomes[0].name: 1}
callback(0, case, policy, name, result)
_, 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,
[outcome.name for outcome in outcomes],
nr_experiments=nr_experiments)
result = {outcomes[0].name: np.random.rand(10)}
callback(0, case, policy, name, result)
_, 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,
[outcome.name for outcome in outcomes],
nr_experiments=nr_experiments)
result = {outcomes[0].name: np.random.rand(2, 2)}
callback(0, case, policy, name, result)
_, 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,
[outcome.name for outcome in outcomes],
nr_experiments=nr_experiments)
result = {outcomes[0].name: np.random.rand(2, 2, 2)}
self.assertRaises(EMAError, callback, 0, case, policy, name, result)
# KeyError
with mock.patch('util.ema_logging.debug') as mocked_logging:
callback = DefaultCallback(uncs,
[outcome.name for outcome in outcomes],
nr_experiments=nr_experiments)
result = {'incorrect': np.random.rand(2, )}
callback(0, case, policy, name, result)
for outcome in outcomes:
mocked_logging.assert_called_with(
"%s not specified as outcome in msi" % outcome.name)