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Fix: effect label #55

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Merged
sarusso merged 1 commit into from
Dec 2, 2025
Merged

Fix: effect label #55

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52 changes: 26 additions & 26 deletions ats/tests/test_evaluators.py
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Original file line number Diff line number Diff line change
Expand Up @@ -61,7 +61,7 @@ def test_evaluate_anomaly_detector(self):
def test_evaluate_anomaly_det_on_spiked_synth_timeseries(self):

spiked_humi_temp_generator = HumiTempTimeseriesGenerator()
timeseries_df = spiked_humi_temp_generator.generate(anomalies=['spike_uv'],effects=[])
timeseries_df = spiked_humi_temp_generator.generate(include_effect_label=True, anomalies=['spike_uv'],effects=[])
# Generated DataFrame:
# Timestamp temperature humidity anomaly_label effect_label
# ...
Expand Down Expand Up @@ -102,7 +102,7 @@ def test_evaluate_anomaly_det_on_spiked_synth_timeseries(self):
def test_evaluate_anomaly_det_on_step_synth_timeseries(self):

step_humi_temp_generator = HumiTempTimeseriesGenerator()
timeseries_df = step_humi_temp_generator.generate(anomalies=['step_uv'],effects=[])
timeseries_df = step_humi_temp_generator.generate(include_effect_label=True, anomalies=['step_uv'],effects=[])
# Generated DataFrame:
# Timestamp temperature humidity anomaly_label effect_label
# ...
Expand All @@ -127,7 +127,7 @@ def test_evaluate_anomaly_det_on_step_synth_timeseries(self):

def test_evaluate_anomaly_det_on_synth_not_anomalous_timeseries(self):
humi_temp_generator = HumiTempTimeseriesGenerator()
timeseries_df = humi_temp_generator.generate(anomalies=[],effects=[])
timeseries_df = humi_temp_generator.generate(include_effect_label=True, anomalies=[],effects=[])
# Generated DataFrame:
# Timestamp temperature humidity anomaly_label effect_label
# ...
Expand Down Expand Up @@ -171,7 +171,7 @@ def test_evaluation_details(self):

def test_evaluation_details_on_synth_spiked_timeseries(self):
spiked_humi_temp_generator = HumiTempTimeseriesGenerator()
timeseries_df = spiked_humi_temp_generator.generate(anomalies=['spike_uv'],effects=[])
timeseries_df = spiked_humi_temp_generator.generate(include_effect_label=True, anomalies=['spike_uv'],effects=[])
min_max_anomaly_detector = MinMaxAnomalyDetector()
f_timeseries_df,anomaly_labels = _format_for_anomaly_detector(timeseries_df,synthetic=True)
evaluated_ts_df = min_max_anomaly_detector.apply(f_timeseries_df)
Expand All @@ -187,7 +187,7 @@ def test_evaluation_details_on_synth_spiked_timeseries(self):

def test_evaluation_details_on_synth_step_timeseries(self):
step_humi_temp_generator = HumiTempTimeseriesGenerator()
timeseries_df = step_humi_temp_generator.generate(anomalies=['step_uv'],effects=[])
timeseries_df = step_humi_temp_generator.generate(include_effect_label=True, anomalies=['step_uv'],effects=[])

min_max_anomaly_detector = MinMaxAnomalyDetector()
f_timeseries_df,anomaly_labels = _format_for_anomaly_detector(timeseries_df,synthetic=True)
Expand All @@ -208,7 +208,7 @@ def test_evaluation_details_on_synth_step_timeseries(self):

def test_evaluation_details_on_synth_not_anomalous_timeseries(self):
humi_temp_generator = HumiTempTimeseriesGenerator()
timeseries_df = humi_temp_generator.generate(anomalies=[],effects=[])
timeseries_df = humi_temp_generator.generate(include_effect_label=True, anomalies=[],effects=[])

min_max_anomaly_detector = MinMaxAnomalyDetector()
f_timeseries_df,anomaly_labels = _format_for_anomaly_detector(timeseries_df,synthetic=True)
Expand All @@ -225,8 +225,8 @@ def test_evaluation_details_on_synth_not_anomalous_timeseries(self):

def test_get_model_output(self):
humi_temp_generator = HumiTempTimeseriesGenerator()
humitemp_series1 = humi_temp_generator.generate(anomalies=[],effects=[])
humitemp_series2 = humi_temp_generator.generate(anomalies=[],effects=['noise'])
humitemp_series1 = humi_temp_generator.generate(include_effect_label=True, anomalies=[],effects=[])
humitemp_series2 = humi_temp_generator.generate(include_effect_label=True, anomalies=[],effects=['noise'])
format_humitemp_series1,anomalies1 = _format_for_anomaly_detector(humitemp_series1,synthetic=True)
format_humitemp_series2,anomalies2 = _format_for_anomaly_detector(humitemp_series2,synthetic=True)
min_max = MinMaxAnomalyDetector()
Expand Down Expand Up @@ -303,8 +303,8 @@ def test_evaluate_point_granularity(self):
effects = []
# series with 2880 data points
series_generator = HumiTempTimeseriesGenerator()
series1 = series_generator.generate(anomalies=anomalies,effects=effects)
series2 = series_generator.generate(anomalies=anomalies,effects=effects)
series1 = series_generator.generate(include_effect_label=True, anomalies=anomalies,effects=effects)
series2 = series_generator.generate(include_effect_label=True, anomalies=anomalies,effects=effects)
dataset = [series1,series2]
evaluator = Evaluator(test_data=dataset)
minmax1 = MinMaxAnomalyDetector()
Expand Down Expand Up @@ -332,8 +332,8 @@ def test_evaluate_variable_granularity(self):
effects = []
# series with 2880 data points
series_generator = HumiTempTimeseriesGenerator()
series1 = series_generator.generate(anomalies=anomalies,effects=effects)
series2 = series_generator.generate(anomalies=anomalies,effects=effects)
series1 = series_generator.generate(include_effect_label=True, anomalies=anomalies,effects=effects)
series2 = series_generator.generate(include_effect_label=True, anomalies=anomalies,effects=effects)
dataset = [series1,series2]
evaluator = Evaluator(test_data=dataset)
minmax1 = MinMaxAnomalyDetector()
Expand Down Expand Up @@ -362,9 +362,9 @@ def test_evaluate_series_granularity(self):
effects = []
series_generator = HumiTempTimeseriesGenerator()
# series1 will be a true anomaly for the minmax
series1 = series_generator.generate(anomalies=anomalies,effects=effects)
series1 = series_generator.generate(include_effect_label=True, anomalies=anomalies,effects=effects)
# series2 will be a false positive for minmax (it sees always 2 anomalous data points for each variable)
series2 = series_generator.generate(anomalies=[],effects=effects)
series2 = series_generator.generate(include_effect_label=True, anomalies=[],effects=effects)
dataset = [series1,series2]
evaluator = Evaluator(test_data=dataset)
minmax1 = MinMaxAnomalyDetector()
Expand Down Expand Up @@ -392,9 +392,9 @@ def test_series_granularity_eval_with_non_detected_anomalies(self):
effects = []
series_generator = HumiTempTimeseriesGenerator()
# series1 will be a true anomaly for the minmax
series1 = series_generator.generate(anomalies=['step_uv'],effects=effects)
series1 = series_generator.generate(include_effect_label=True, anomalies=['step_uv'],effects=effects)
# series2 will be a false positive for minmax (it sees always 2 anomalous data points for each variable)
series2 = series_generator.generate(anomalies=['pattern_uv'],effects=effects)
series2 = series_generator.generate(include_effect_label=True, anomalies=['pattern_uv'],effects=effects)
dataset = [series1,series2]
evaluator = Evaluator(test_data=dataset)
minmax1 = MinMaxAnomalyDetector()
Expand All @@ -421,7 +421,7 @@ def test_series_granularity_eval_with_non_detected_anomalies(self):
def test_raised_error_evaluation_series_granularity(self):
anomalies = ['step_uv','spike_uv']
series_generator = HumiTempTimeseriesGenerator()
series = series_generator.generate(anomalies=anomalies)
series = series_generator.generate(include_effect_label=True, anomalies=anomalies)
dataset = [series]
minmax = MinMaxAnomalyDetector()
evaluator = Evaluator(test_data=dataset)
Expand All @@ -432,8 +432,8 @@ def test_raised_error_evaluation_series_granularity(self):

def test_copy_dataset(self):
series_generator = HumiTempTimeseriesGenerator()
series1 = series_generator.generate(effects=['noise'])
series2 = series_generator.generate(effects=['noise'])
series1 = series_generator.generate(include_effect_label=True, effects=['noise'])
series2 = series_generator.generate(include_effect_label=True, effects=['noise'])
dataset = [series1,series2]
evaluator = Evaluator(test_data=dataset)
minmax1 = MinMaxAnomalyDetector()
Expand All @@ -448,7 +448,7 @@ def test_copy_dataset(self):

def test_variable_granularity_evaluation(self):
series_generator = HumiTempTimeseriesGenerator()
series = series_generator.generate(anomalies=['step_uv'])
series = series_generator.generate(include_effect_label=True, anomalies=['step_uv'])
minmax = MinMaxAnomalyDetector()
formatted_series,anomaly_labels = _format_for_anomaly_detector(series,synthetic=True)
flagged_series = minmax.apply(formatted_series)
Expand All @@ -463,7 +463,7 @@ def test_variable_granularity_evaluation(self):

def test_point_granularity_evaluation(self):
series_generator = HumiTempTimeseriesGenerator()
series = series_generator.generate(anomalies=['step_uv'])
series = series_generator.generate(include_effect_label=True, anomalies=['step_uv'])
minmax = MinMaxAnomalyDetector()
formatted_series,anomaly_labels = _format_for_anomaly_detector(series,synthetic=True)
flagged_series = minmax.apply(formatted_series)
Expand All @@ -478,7 +478,7 @@ def test_point_granularity_evaluation(self):

def test_series_granularity_evaluation(self):
series_generator = HumiTempTimeseriesGenerator()
series = series_generator.generate(anomalies=['step_uv'])
series = series_generator.generate(include_effect_label=True, anomalies=['step_uv'])
minmax = MinMaxAnomalyDetector()
formatted_series,anomaly_labels = _format_for_anomaly_detector(series,synthetic=True)
flagged_series = minmax.apply(formatted_series)
Expand All @@ -489,7 +489,7 @@ def test_series_granularity_evaluation(self):
self.assertEqual(len(evaluation_result),1)
self.assertAlmostEqual(evaluation_result['step_uv'],1)

series1 = series_generator.generate(anomalies=[])
series1 = series_generator.generate(include_effect_label=True, anomalies=[])
minmax1 = MinMaxAnomalyDetector()
formatted_series1,anomaly_labels1 = _format_for_anomaly_detector(series1,synthetic=True)
flagged_series1 = minmax.apply(formatted_series1)
Expand All @@ -501,7 +501,7 @@ def test_series_granularity_evaluation(self):
# }

try:
series2 = series_generator.generate(anomalies=['spike_uv','step_uv'])
series2 = series_generator.generate(include_effect_label=True, anomalies=['spike_uv','step_uv'])
formatted_series2,anomaly_labels2 = _format_for_anomaly_detector(series2,synthetic=True)
flagged_series2 = minmax.apply(formatted_series2)
evaluation_result2 = _series_granularity_evaluation(flagged_series2,anomaly_labels2)
Expand All @@ -513,9 +513,9 @@ def test_double_evaluator(self):
effects = []
series_generator = HumiTempTimeseriesGenerator()
# series1 will be a true anomaly for the minmax
series1 = series_generator.generate(anomalies=anomalies,effects=effects)
series1 = series_generator.generate(include_effect_label=True, anomalies=anomalies,effects=effects)
# series2 will be a false positive for minmax (it sees always 2 anomalous data points for each variable)
series2 = series_generator.generate(anomalies=[],effects=effects)
series2 = series_generator.generate(include_effect_label=True, anomalies=[],effects=effects)
dataset = [series1,series2]
evaluator = Evaluator(test_data=dataset)
minmax1 = MinMaxAnomalyDetector()
Expand Down
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