class SklearnModelTest(TestCase):
def setUp(self):
data_matrix = [[1, 2, 3, "a"], [2, 3, 2, "b"], [3, 2, 1, "a"],
[5, 5, 1, "c"], [2, 2, 2, "a"]]
self.dataset = Dataset(data_matrix)
self.settings = AbstractSettings({})
self.parameter_set = ParameterSet({})
self.dependent_variable = DatasetVariable(0)
self.independent_variables = [
DatasetVariable(1),
DatasetVariable(2),
DatasetVariable(3)
]
self.sklearn_model = SklearnModel(self.settings, self.parameter_set,
self.dependent_variable,
self.independent_variables)
def test_categorical_independent_variables(self):
independent_variable_data = self.sklearn_model.get_independent_variable_data(
self.dataset)
self.assertEqual(5, len(independent_variable_data))
num_categories = len(independent_variable_data[0])
self.assertEqual(5, num_categories)
def test_dependent_variable_data(self):
dependent_variable_data = self.sklearn_model.get_dependent_variable_data(
self.dataset)
self.assertEqual(5, len(dependent_variable_data))
self.assertListEqual([1, 2, 3, 5, 2], dependent_variable_data)
def test_training_and_predicting_using_ols_regression(self):
ols_regression = OLSLinearRegression(self.settings, self.parameter_set,
self.dependent_variable,
self.independent_variables)
for training_dataset, test_dataset in self.dataset.crossfold_partitions(
2):
trained_model = ols_regression.train(training_dataset)
predicted_result = trained_model.predict(test_dataset)
self.assertEqual(test_dataset.num_rows, len(predicted_result))
class SklearnModelTest(TestCase):
def setUp(self):
data_matrix = [
[1,2,3,"a"],
[2,3,2,"b"],
[3,2,1,"a"],
[5,5,1,"c"],
[2,2,2,"a"]]
self.dataset = Dataset(data_matrix)
self.settings = AbstractSettings({})
self.parameter_set = ParameterSet({})
self.dependent_variable = DatasetVariable(0)
self.independent_variables = [DatasetVariable(1), DatasetVariable(2), DatasetVariable(3)]
self.sklearn_model = SklearnModel(self.settings, self.parameter_set, self.dependent_variable, self.independent_variables)
def test_categorical_independent_variables(self):
independent_variable_data = self.sklearn_model.get_independent_variable_data(self.dataset)
self.assertEqual(5, len(independent_variable_data))
num_categories = len(independent_variable_data[0])
self.assertEqual(5, num_categories)
def test_dependent_variable_data(self):
dependent_variable_data = self.sklearn_model.get_dependent_variable_data(self.dataset)
self.assertEqual(5, len(dependent_variable_data))
self.assertListEqual([1,2,3,5,2], dependent_variable_data)
def test_training_and_predicting_using_ols_regression(self):
ols_regression = OLSLinearRegression(self.settings, self.parameter_set, self.dependent_variable, self.independent_variables)
for training_dataset, test_dataset in self.dataset.crossfold_partitions(2):
trained_model = ols_regression.train(training_dataset)
predicted_result = trained_model.predict(test_dataset)
self.assertEqual(test_dataset.num_rows, len(predicted_result))
class DatasetTest(TestCase):
def setUp(self):
data_matrix = [[0, "detective", "book"], [1, "pablo", "escobar"],
[2, "african", "queen"], [3, "applause", "movie"]]
headers = ["number", "string", "another_string"]
self.dataset = Dataset(data_matrix, headers)
def test_data_types_and_categories_when_initializing_dataset(self):
self.assertEqual(3, len(self.dataset.data_types))
self.assertEqual("integer", self.dataset.data_types[0].data_type)
self.assertEqual("string", self.dataset.data_types[1].data_type)
self.assertEqual("string", self.dataset.data_types[2].data_type)
self.assertEqual(4, len(self.dataset.data_types[1].categories))
self.assertTrue(self.dataset.data_types[1].in_categories("detective"))
self.assertTrue(self.dataset.data_types[1].in_categories("pablo"))
self.assertTrue(self.dataset.data_types[1].in_categories("african"))
self.assertTrue(self.dataset.data_types[1].in_categories("applause"))
self.assertEqual(4, len(self.dataset.data_types[2].categories))
self.assertTrue(self.dataset.data_types[2].in_categories("book"))
self.assertTrue(self.dataset.data_types[2].in_categories("escobar"))
self.assertTrue(self.dataset.data_types[2].in_categories("queen"))
self.assertTrue(self.dataset.data_types[2].in_categories("movie"))
def test_getting_independent_variables(self):
dependent_variable_index = DatasetVariable(0)
dependent_variable_header = DatasetVariable("number")
independent_variables = self.dataset.get_independent_variables(
dependent_variable_index)
self.assertEqual(2, len(independent_variables))
for variable in independent_variables:
self.assertIn(variable.variable, ["string", "another_string"])
independent_variables = self.dataset.get_independent_variables(
dependent_variable_header)
self.assertEqual(2, len(independent_variables))
for variable in independent_variables:
self.assertIn(variable.variable, ["string", "another_string"])
def test_crossfold_partitions(self):
past_test_datasets = []
for training_dataset, test_dataset in self.dataset.crossfold_partitions(
4):
self.assertEqual(3, training_dataset.num_rows)
self.assertEqual(1, test_dataset.num_rows)
self.assertNotIn(test_dataset.get(0, 0), past_test_datasets)
self.assertListEqual(["number", "string", "another_string"],
training_dataset.headers)
self.assertListEqual(["number", "string", "another_string"],
test_dataset.headers)
past_test_datasets.append(test_dataset.get(0, 0))
for training_dataset, test_dataset in self.dataset.crossfold_partitions(
2):
self.assertEqual(2, training_dataset.num_rows)
self.assertEqual(2, test_dataset.num_rows)
self.assertListEqual(["number", "string", "another_string"],
training_dataset.headers)
self.assertListEqual(["number", "string", "another_string"],
test_dataset.headers)
def test_get_filtered_matrix(self):
variables = [DatasetVariable(0), DatasetVariable("string")]
filtered_matrix = self.dataset.get_filtered_matrix(variables)
self.assertEqual(4, len(filtered_matrix))
for i in xrange(len(filtered_matrix)):
self.assertEqual(2, len(filtered_matrix[i]))
self.assertListEqual([0, "detective"], filtered_matrix[0])
self.assertListEqual([1, "pablo"], filtered_matrix[1])
self.assertListEqual([2, "african"], filtered_matrix[2])
self.assertListEqual([3, "applause"], filtered_matrix[3])
def test_getting_filtered_matrix_with_no_variables(self):
variables = []
with self.assertRaises(ValueError):
filtered_matrix = self.dataset.get_filtered_matrix(variables)