diff --git a/tods/tests/detection_algorithm/test_AutoRegODetect.py b/tods/tests/detection_algorithm/test_AutoRegODetect.py index ee7d9e8..e282b59 100644 --- a/tods/tests/detection_algorithm/test_AutoRegODetect.py +++ b/tods/tests/detection_algorithm/test_AutoRegODetect.py @@ -31,7 +31,7 @@ class AutoRegODetectTestCase(unittest.TestCase): self.y_train = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]) self.X_test = d3m_dataframe({'data': [3., 4., 8.6, 13.4, 22.5, 17, 19.2, 36.1, 127, -23, 59.2]}, columns=['data'], generate_metadata=True) - self.y_test = np.array([0, 0, 0, 0, 0, 0, 0, 0, 1]) + self.y_test = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0]) @@ -70,7 +70,7 @@ class AutoRegODetectTestCase(unittest.TestCase): 'dimension': { 'name': 'rows', 'semantic_types': ['https://metadata.datadrivendiscovery.org/types/TabularRow'], - 'length': 9, + 'length': 11, }, }, }, { @@ -87,21 +87,21 @@ class AutoRegODetectTestCase(unittest.TestCase): 'metadata': { 'name': 'AutoRegODetector0_0', 'semantic_types': ['https://metadata.datadrivendiscovery.org/types/Attribute'], - 'structural_type': 'numpy.int64', + 'structural_type': 'numpy.float64', }, }, { 'selector': ['__ALL_ELEMENTS__', 1], 'metadata': { 'name': 'AutoRegODetector0_1', 'semantic_types': ['https://metadata.datadrivendiscovery.org/types/Attribute'], - 'structural_type': 'numpy.int64', + 'structural_type': 'numpy.float64', }, }, { 'selector': ['__ALL_ELEMENTS__', 2], 'metadata': { 'name': 'AutoRegODetector0_2', 'semantic_types': ['https://metadata.datadrivendiscovery.org/types/Attribute'], - 'structural_type': 'numpy.int64', + 'structural_type': 'numpy.float64', }, }]) diff --git a/tods/tests/detection_algorithm/test_LSTMODetector.py b/tods/tests/detection_algorithm/test_LSTMODetector.py index e6de1c9..812f4f1 100644 --- a/tods/tests/detection_algorithm/test_LSTMODetector.py +++ b/tods/tests/detection_algorithm/test_LSTMODetector.py @@ -30,7 +30,7 @@ class LSTMODTestCase(unittest.TestCase): self.y_train = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]) self.X_test = d3m_dataframe({'data': [3., 4., 8.6, 13.4, 22.5, 17, 19.2, 36.1, 127, -23, 59.2]}, columns=['data'], generate_metadata=True) - self.y_test = np.array([0, 0, 0, 0, 0, 0, 0, 0, 1, 0]) + self.y_test = np.array([0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0]) @@ -66,7 +66,7 @@ class LSTMODTestCase(unittest.TestCase): 'dimension': { 'name': 'rows', 'semantic_types': ['https://metadata.datadrivendiscovery.org/types/TabularRow'], - 'length': 10, + 'length': 11, }, }, }, {