def test_create_duplicate_kmeans_model(self): model_name = str(uuid.uuid1()).replace('-', '_') ta.KMeansModel(name=model_name) self.assertTrue(model_name in ta.get_model_names(), model_name + " should be in the list of models") # try to create another model with the same name (we expect an exception) with self.assertRaises(Exception): ta.KMeansModel(name=model_name)
def test_duplicate_model_rename(self): model_name1 = str(uuid.uuid1()).replace('-', '_') model_name2 = str(uuid.uuid1()).replace('-', '_') graph_name = str(uuid.uuid1()).replace('-', '_') frame_name = str(uuid.uuid1()).replace('-', '_') # Create models, graph, and frame to test with model1 = ta.KMeansModel(name=model_name1) model2 = ta.KMeansModel(name=model_name2) ta.Graph(name=graph_name) ta.Frame(name=frame_name) # After creating models, check that models with each name exists on the server self.assertTrue(model_name1 in ta.get_model_names(), model_name1 + " should exist in list of models") self.assertTrue(model_name2 in ta.get_model_names(), model_name2 + " should exist in list of models") # Try to rename model2 to have the same name as model1 (we expect an exception here) with self.assertRaises(Exception): model2.name = model_name1 # Both model names should still exist on the server self.assertTrue(model_name1 in ta.get_model_names(), model_name1 + " should still exist in list of models") self.assertTrue(model_name2 in ta.get_model_names(), model_name2 + " should still exist in list of models") # Try to rename model1 to have the same name as the graph (we expect an exception here) with self.assertRaises(Exception): model1.name = graph_name # model1 and the graph should still exist on the server self.assertTrue( model_name1 in ta.get_model_names(), model_name1 + " should still exist in the list of models") self.assertTrue( graph_name in ta.get_graph_names(), graph_name + " should still exist in the list of graphs") # Try to rename model1 to have the same name as the frame (we expect an exception here) with self.assertRaises(Exception): model1.name = frame_name # model1 and the frame should still exist on the server self.assertTrue( model_name1 in ta.get_model_names(), model_name1 + " should still exist in the list of models") self.assertTrue( frame_name in ta.get_frame_names(), frame_name + " should still exist in the list of frames")
def test_model(self): print "Initialize KMeansModel object with name" k1 = ta.KMeansModel(name='smoke_kmeans_model') name = k1.name print "Initialize KMeansModel object" k2 = ta.KMeansModel() print "Initialize LogisticRegressionModel object with name" l1 = ta.LogisticRegressionModel(name='myLogisticRegressionModel1') print "Initialize LogisticRegressionModel object" l2 = ta.LogisticRegressionModel() print "Initialize NaiveBayesModel object" n = ta.NaiveBayesModel()
def test_model(self): print "Initialize KMeansModel object" k = ta.KMeansModel() print "Initialize LogisticRegressionModel object" l = ta.LogisticRegressionModel() print "Initialize NaiveBayesModel object" n = ta.NaiveBayesModel()
def test_drop_model_by_object(self): model_name = str(uuid.uuid1()).replace('-','_') # Create model and verify that it's in the get_model_names() list model = ta.KMeansModel(name=model_name) self.assertTrue(model_name in ta.get_model_names(), model_name + " should exist in the list of models") # Drop model using the model object self.assertEqual(1, ta.drop_models(model), "drop_models() should have deleted one model.") self.assertFalse(model_name in ta.get_model_names(), model_name + " should not exist in the list of models")
def test_generic_drop_by_name(self): model_name = str(uuid.uuid1()).replace('-','_') ta.KMeansModel(name=model_name) self.assertTrue(model_name in ta.get_model_names(), model_name + " should exist in the list of model names") # drop() item by name self.assertEqual(1, ta.drop(model_name), "drop() should have deleted one item") # check that the model no longer exists self.assertFalse(model_name in ta.get_model_names(), model_name + " should not exist in the list of models")
def test_create_kmeans_model_with_duplicte_graph_name(self): graph_name = str(uuid.uuid1()).replace('-', '_') # Create graph ta.Graph(name=graph_name) self.assertTrue(graph_name in ta.get_graph_names(), graph_name + " should be in the list of graphs") # Try to create a model with the same name as the graph (we expect an exception) with self.assertRaises(Exception): ta.KMeansModel(name=graph_name)
def test_create_kmeans_model_with_duplicte_frame_name(self): frame_name = str(uuid.uuid1()).replace('-', '_') # Create frame ta.Frame(name=frame_name) self.assertTrue(frame_name in ta.get_frame_names(), frame_name + " should be in the list of frames") # Try to create model with the same name as the frame (we expect an exception) with self.assertRaises(Exception): ta.KMeansModel(name=frame_name)
def test_kmeans_train_publish(self): frame = ta.Frame( ta.UploadRows( [[2, "ab"], [1, "cd"], [7, "ef"], [1, "gh"], [9, "ij"], [2, "kl"], [0, "mn"], [6, "op"], [5, "qr"]], [("data", ta.float64), ("name", str)])) model = ta.KMeansModel() train_output = model.train(frame, ["data"], [1], 3) self.assertTrue( train_output.has_key('within_set_sum_of_squared_error')) model.publish()
def test_generic_drop_by_object(self): model_name = str(uuid.uuid1()).replace('-','_') model = ta.KMeansModel(name=model_name) # Check that the model we just created now exists self.assertTrue(model_name in ta.get_model_names(), model_name + " should exist in the list of model names") # drop by entity self.assertEqual(1, ta.drop(model), "drop() should have deleted one item") # check that the model no longer exists self.assertFalse(model_name in ta.get_model_names(), model_name + " should not exist in the list of models")
def test_model_rename(self): model_name = str(uuid.uuid1()).replace('-', '_') new_model_name = str(uuid.uuid1()).replace('-', '_') model = ta.KMeansModel(name=model_name) self.assertTrue(model_name in ta.get_model_names(), model_name + " should be in the list of models") model.name = new_model_name self.assertTrue(new_model_name in ta.get_model_names(), new_model_name + " should be in list of models") self.assertFalse(model_name in ta.get_model_names(), model_name + " shoule not be in list of models")
def testKMeans(self): print "define csv file" csv = ta.CsvFile("/datasets/KMeansTestFile.csv", schema=[('data', ta.float64), ('name', str)], skip_header_lines=1) print "create frame" frame = ta.Frame(csv) print "Initializing a KMeansModel object" k = ta.KMeansModel(name='myKMeansModel') print "Training the model on the Frame" k.train(frame, ['data'], [2.0])
def testKMeans(self): """basic KMeans train + piggyback model last_read_date""" print "define csv file" csv = ta.CsvFile("/datasets/KMeansTestFile.csv", schema= [('data', ta.float64), ('name', str)], skip_header_lines=1) print "create frame" frame = ta.Frame(csv) print "Initializing a KMeansModel object" k = ta.KMeansModel(name='myKMeansModel') t0 = k.last_read_date t1 = k.last_read_date #print "t0=%s" % t0.isoformat() self.assertEqual(t0, t1) print "Training the model on the Frame" k.train(frame,['data'],[2.0]) t2 = k.last_read_date self.assertLess(t1, t2)