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_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)