def test_default_surrogate_change(self):
metamodel = MetaModel()
mmins = set(metamodel.list_inputs())
mmouts = set(metamodel.list_outputs())
metamodel.default_surrogate = KrigingSurrogate()
metamodel.model = Simple()
metamodel.default_surrogate = LogisticRegression()
attrs = metamodel.get_attributes(io_only=False)
for s in attrs['Slots']:
self.assertNotEqual(s['name'], 'c')
self.assertNotEqual(s['name'], 'd')
inputs = set(metamodel.list_inputs())
outputs = set(metamodel.list_outputs())
self.assertEquals(inputs - mmins, set(['a', 'b']))
self.assertEquals(outputs - mmouts, set(['c', 'd']))
for i in range(3):
metamodel.train_next = True
metamodel.run()
self.assertTrue(len(metamodel._training_data['c']) == 3)
self.assertTrue(len(metamodel._training_data['d']) == 3)
self.assertTrue(len(metamodel._training_input_history) == 3)
metamodel.includes = ['a', 'b', 'c', 'd']
self.assertTrue(len(metamodel._training_data['c']) == 3)
self.assertTrue(len(metamodel._training_data['d']) == 3)
self.assertTrue(len(metamodel._training_input_history) == 3)
# removing an output should not clobber the rest of the training data
metamodel.includes = ['a', 'b', 'c']
self.assertTrue(len(metamodel._training_data['c']) == 3)
self.assertTrue('d' not in metamodel._training_data)
self.assertTrue(len(metamodel._training_input_history) == 3)
# now put a different model in with the same inputs/outputs
metamodel.model = SimpleMatch()
metamodel.includes = ['a', 'b', 'c', 'd']
inputs = set(metamodel.list_inputs())
outputs = set(metamodel.list_outputs())
self.assertEquals(inputs - mmins, set(['a', 'b']))
self.assertEquals(outputs - mmouts, set(['c', 'd']))
self.assertTrue(len(metamodel._training_data['c']) == 0)
self.assertTrue(len(metamodel._training_data['d']) == 0)
self.assertTrue(len(metamodel._training_input_history) == 0)
# now put a different model in
metamodel.model = Simple2()
metamodel.includes = ['w', 'x', 'y', 'z']
inputs = set(metamodel.list_inputs())
outputs = set(metamodel.list_outputs())
self.assertEquals(inputs - mmins, set(['w', 'x']))
self.assertEquals(outputs - mmouts, set(['y', 'z']))
def test_default_surrogate_change(self):
metamodel = MetaModel()
mmins = set(metamodel.list_inputs())
mmouts = set(metamodel.list_outputs())
metamodel.default_surrogate = KrigingSurrogate()
metamodel.model = Simple()
metamodel.default_surrogate = LogisticRegression()
attrs = metamodel.get_attributes(io_only=False)
for s in attrs['Slots']:
self.assertNotEqual(s['name'], 'c')
self.assertNotEqual(s['name'], 'd')
inputs = set(metamodel.list_inputs())
outputs = set(metamodel.list_outputs())
self.assertEquals(inputs-mmins, set(['a','b']))
self.assertEquals(outputs-mmouts, set(['c','d']))
for i in range(3):
metamodel.train_next = True
metamodel.run()
self.assertTrue(len(metamodel._training_data['c']) == 3)
self.assertTrue(len(metamodel._training_data['d']) == 3)
self.assertTrue(len(metamodel._training_input_history) == 3)
metamodel.includes = ['a','b','c','d']
self.assertTrue(len(metamodel._training_data['c']) == 3)
self.assertTrue(len(metamodel._training_data['d']) == 3)
self.assertTrue(len(metamodel._training_input_history) == 3)
# removing an output should not clobber the rest of the training data
metamodel.includes = ['a','b','c']
self.assertTrue(len(metamodel._training_data['c']) == 3)
self.assertTrue('d' not in metamodel._training_data)
self.assertTrue(len(metamodel._training_input_history) == 3)
# now put a different model in with the same inputs/outputs
metamodel.model = SimpleMatch()
metamodel.includes = ['a','b','c','d']
inputs = set(metamodel.list_inputs())
outputs = set(metamodel.list_outputs())
self.assertEquals(inputs-mmins, set(['a','b']))
self.assertEquals(outputs-mmouts, set(['c', 'd']))
self.assertTrue(len(metamodel._training_data['c']) == 0)
self.assertTrue(len(metamodel._training_data['d']) == 0)
self.assertTrue(len(metamodel._training_input_history) == 0)
# now put a different model in
metamodel.model = Simple2()
metamodel.includes = ['w','x','y','z']
inputs = set(metamodel.list_inputs())
outputs = set(metamodel.list_outputs())
self.assertEquals(inputs-mmins, set(['w','x']))
self.assertEquals(outputs-mmouts, set(['y','z']))
metamodel.name = 'meta'
metamodel.surrogate = {'d': KrigingSurrogate()}
try:
metamodel.model = Simple()
except ValueError, err:
self.assertEqual(
'meta: No default surrogate model was specified. '
'Either specify a default, or specify a surrogate model for all '
'outputs', str(err))
else:
self.fail('ValueError expected')
metamodel = MetaModel()
metamodel.name = 'meta'
metamodel.surrogate = {'d': KrigingSurrogate()}
metamodel.includes = ['a', 'b', 'd']
try:
metamodel.model = Simple()
except ValueError, err:
if 'meta: Dict provided for "surrogates" does not include a value for "c". All outputs must be specified' == str(
err):
self.fail(
'should not get a value error for variable c. It is not included in the metamodel'
)
def test_multi_surrogate_models(self):
metamodel = MetaModel()
metamodel.name = 'meta'
metamodel.surrogate = {
'd': KrigingSurrogate(),
'c': LogisticRegression()
metamodel = MetaModel()
metamodel.name = 'meta'
metamodel.surrogate = {'d':KrigingSurrogate()}
try:
metamodel.model = Simple()
except ValueError,err:
self.assertEqual('meta: No default surrogate model was specified. '
'Either specify a default, or specify a surrogate model for all '
'outputs',str(err))
else:
self.fail('ValueError expected')
metamodel = MetaModel()
metamodel.name = 'meta'
metamodel.surrogate = {'d':KrigingSurrogate()}
metamodel.includes = ['a','b','d']
try:
metamodel.model = Simple()
except ValueError,err:
if 'meta: Dict provided for "surrogates" does not include a value for "c". All outputs must be specified'==str(err):
self.fail('should not get a value error for variable c. It is not included in the metamodel')
def test_multi_surrogate_models(self):
metamodel = MetaModel()
metamodel.name = 'meta'
metamodel.surrogate = {'d':KrigingSurrogate(),
'c':LogisticRegression()}
metamodel.model = Simple()
metamodel.recorder = DumbRecorder()
simple = Simple()
try:
metamodel.model = Simple()
except ValueError, err:
self.assertEqual(
"meta: No default surrogate model was specified. "
"Either specify a default, or specify a surrogate model for all "
"outputs",
str(err),
)
else:
self.fail("ValueError expected")
metamodel = MetaModel()
metamodel.name = "meta"
metamodel.surrogate = {"d": KrigingSurrogate()}
metamodel.includes = ["a", "b", "d"]
try:
metamodel.model = Simple()
except ValueError, err:
if (
'meta: Dict provided for "surrogates" does not include a value for "c". All outputs must be specified'
== str(err)
):
self.fail("should not get a value error for variable c. It is not included in the metamodel")
def test_multi_surrogate_models(self):
metamodel = MetaModel()
metamodel.name = "meta"
metamodel.surrogate = {"d": KrigingSurrogate(), "c": LogisticRegression()}
metamodel.model = Simple()
metamodel.recorder = DumbRecorder()
