def test_default_execute(self):
metamodel = MetaModel()
metamodel.name = 'meta'
metamodel.default_surrogate = KrigingSurrogate()
metamodel.model = Simple()
metamodel.recorder = DumbRecorder()
simple = Simple()
#import pdb; pdb.set_trace()
metamodel.a = simple.a = 1.
metamodel.b = simple.b = 2.
metamodel.train_next = True
simple.run()
metamodel.run()
metamodel.a = simple.a = 1.
metamodel.b = simple.b = 2.
metamodel.train_next = True
simple.run()
metamodel.run()
self.assertEqual(metamodel.c.getvalue(), 3.)
self.assertEqual(metamodel.d.getvalue(), -1.)
self.assertEqual(metamodel.c.getvalue(), simple.c)
self.assertEqual(metamodel.d.getvalue(), simple.d)
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()
metamodel.a = simple.a = 1.
metamodel.b = simple.b = 2.
metamodel.train_next = True
simple.run()
metamodel.run()
metamodel.a = simple.a = 3.
metamodel.b = simple.b = 4.
metamodel.train_next = True
simple.run()
metamodel.run()
self.assertTrue(isinstance(metamodel.d, NormalDistribution))
self.assertTrue(isinstance(metamodel.c, float))
def test_default_execute(self):
metamodel = MetaModel()
metamodel.name = 'meta'
metamodel.default_surrogate = KrigingSurrogate()
metamodel.model = Simple()
metamodel.recorder = DumbRecorder()
simple = Simple()
#import pdb; pdb.set_trace()
metamodel.a = simple.a = 1.
metamodel.b = simple.b = 2.
metamodel.train_next = True
simple.run()
metamodel.run()
metamodel.a = simple.a = 1.
metamodel.b = simple.b = 2.
metamodel.train_next = True
simple.run()
metamodel.run()
self.assertEqual(metamodel.c.getvalue(), 3.)
self.assertEqual(metamodel.d.getvalue(), -1.)
self.assertEqual(metamodel.c.getvalue(), simple.c)
self.assertEqual(metamodel.d.getvalue(), simple.d)
def test_warm_start(self):
metamodel = MetaModel()
metamodel.name = 'meta'
metamodel.default_surrogate = KrigingSurrogate()
metamodel.model = Simple()
metamodel.recorder = DumbRecorder()
simple = Simple()
cases = []
metamodel.a = 1.
metamodel.b = 2.
metamodel.train_next = True
metamodel.run()
inputs = [('meta2.a', metamodel.a), ('meta2.b', metamodel.b)]
outputs = [('meta2.c', metamodel.c.mu), ('meta2.d', metamodel.d.mu)]
cases.append(Case(inputs=inputs, outputs=outputs))
metamodel.a = 3.
metamodel.b = 5.
metamodel.train_next = True
metamodel.run()
inputs = [('meta2.a', metamodel.a), ('meta2.b', metamodel.b)]
outputs = [('meta2.c', metamodel.c.mu), ('meta2.d', metamodel.d.mu)]
cases.append(Case(inputs=inputs, outputs=outputs))
case_iter = ListCaseIterator(cases)
metamodel2 = MetaModel()
metamodel2.name = 'meta2'
metamodel2.default_surrogate = KrigingSurrogate()
metamodel2.model = Simple()
metamodel2.recorder = DumbRecorder()
metamodel2.warm_start_data = case_iter
metamodel2.a = simple.a = 1
metamodel2.b = simple.b = 2
metamodel.train_next = True
metamodel2.run()
simple.run()
self.assertEqual(metamodel2.c.getvalue(), 3.)
self.assertEqual(metamodel2.d.getvalue(), -1.)
self.assertEqual(metamodel2.c.getvalue(), simple.c)
self.assertEqual(metamodel2.d.getvalue(), simple.d)
def test_warm_start(self):
metamodel = MetaModel()
metamodel.name = 'meta'
metamodel.default_surrogate = KrigingSurrogate()
metamodel.model = Simple()
metamodel.recorder = DumbRecorder()
simple = Simple()
cases = []
metamodel.a = 1.
metamodel.b = 2.
metamodel.train_next = True
metamodel.run()
inputs = [('meta2.a',metamodel.a),('meta2.b',metamodel.b)]
outputs = [('meta2.c',metamodel.c.mu),('meta2.d',metamodel.d.mu)]
cases.append(Case(inputs=inputs,outputs=outputs))
metamodel.a = 3.
metamodel.b = 5.
metamodel.train_next = True
metamodel.run()
inputs = [('meta2.a',metamodel.a),('meta2.b',metamodel.b)]
outputs = [('meta2.c',metamodel.c.mu),('meta2.d',metamodel.d.mu)]
cases.append(Case(inputs=inputs,outputs=outputs))
case_iter = ListCaseIterator(cases)
metamodel2 = MetaModel()
metamodel2.name = 'meta2'
metamodel2.default_surrogate = KrigingSurrogate()
metamodel2.model = Simple()
metamodel2.recorder = DumbRecorder()
metamodel2.warm_start_data = case_iter
metamodel2.a = simple.a = 1
metamodel2.b = simple.b = 2
metamodel.train_next = True
metamodel2.run()
simple.run()
self.assertEqual(metamodel2.c.getvalue(), 3.)
self.assertEqual(metamodel2.d.getvalue(), -1.)
self.assertEqual(metamodel2.c.getvalue(), simple.c)
self.assertEqual(metamodel2.d.getvalue(), simple.d)
def test_reset_training_data_event(self):
metamodel = MetaModel()
metamodel.name = 'meta'
metamodel.surrogate = {'default':KrigingSurrogate()}
metamodel.model = Simple()
metamodel.recorder = DumbRecorder()
simple = Simple()
metamodel.a = 1.
metamodel.b = 2.
metamodel.train_next = True
metamodel.run()
metamodel.a = 2.
metamodel.b = 3.
metamodel.train_next = True
metamodel.run()
def test_reset_training_data_event(self):
metamodel = MetaModel()
metamodel.name = 'meta'
metamodel.surrogate = {'default': KrigingSurrogate()}
metamodel.model = Simple()
metamodel.recorder = DumbRecorder()
simple = Simple()
metamodel.a = 1.
metamodel.b = 2.
metamodel.train_next = True
metamodel.run()
metamodel.a = 2.
metamodel.b = 3.
metamodel.train_next = True
metamodel.run()
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()
metamodel.a = simple.a = 1.0
metamodel.b = simple.b = 2.0
metamodel.train_next = True
simple.run()
metamodel.run()
metamodel.a = simple.a = 3.0
metamodel.b = simple.b = 4.0
metamodel.train_next = True
simple.run()
metamodel.run()
self.assertTrue(isinstance(metamodel.d, NormalDistribution))
self.assertTrue(isinstance(metamodel.c, float))
def test_default_execute(self):
metamodel = MetaModel()
metamodel.name = "meta"
metamodel.surrogate = {"default": KrigingSurrogate()}
metamodel.model = Simple()
metamodel.recorder = DumbRecorder()
simple = Simple()
metamodel.a = simple.a = 1.0
metamodel.b = simple.b = 2.0
metamodel.train_next = True
simple.run()
metamodel.run()
metamodel.a = simple.a = 1.0
metamodel.b = simple.b = 2.0
metamodel.train_next = True
simple.run()
metamodel.run()
self.assertEqual(metamodel.c.getvalue(), 3.0)
self.assertEqual(metamodel.d.getvalue(), -1.0)
self.assertEqual(metamodel.c.getvalue(), simple.c)
self.assertEqual(metamodel.d.getvalue(), simple.d)
