diff --git a/spark/jobs/metrics/drift_calculator.py b/spark/jobs/metrics/drift_calculator.py index 41ed4243..71166a38 100644 --- a/spark/jobs/metrics/drift_calculator.py +++ b/spark/jobs/metrics/drift_calculator.py @@ -5,6 +5,7 @@ from metrics.psi import PSI from models.current_dataset import CurrentDataset from models.reference_dataset import ReferenceDataset +from utils.models import FieldTypes class DriftCalculator: @@ -30,6 +31,7 @@ def calculate_drift( for column in categorical_features: feature_dict_to_append = { "feature_name": column, + "field_type": FieldTypes.categorical.value, "drift_calc": { "type": "CHI2", }, @@ -55,45 +57,18 @@ def calculate_drift( for column in float_features: feature_dict_to_append = { "feature_name": column, - "drift_calc": {}, + "field_type": FieldTypes.numerical.value, + "drift_calc": { + "type": "KS", + }, } - unique_values_ref = ( - reference_dataset.reference.select(column) - .distinct() - .rdd.flatMap(lambda x: x) - .collect() + result_tmp = ks.test(column, column) + feature_dict_to_append["drift_calc"]["value"] = float( + result_tmp["ks_statistic"] ) - unique_values_cur = ( - current_dataset.current.select(column) - .distinct() - .rdd.flatMap(lambda x: x) - .collect() + feature_dict_to_append["drift_calc"]["has_drift"] = bool( + result_tmp["ks_statistic"] > result_tmp["critical_value"] ) - unique_values_refcur = unique_values_ref + unique_values_cur - lookup = set() - unique_values_tot = [ - x - for x in unique_values_refcur - if x is not None and x not in lookup and lookup.add(x) is None - ] - if len(unique_values_tot) < 15: - feature_dict_to_append["drift_calc"]["type"] = "CHI2" - result_tmp = chi2.test_goodness_fit(column, column) - feature_dict_to_append["drift_calc"]["value"] = float( - result_tmp["pValue"] - ) - feature_dict_to_append["drift_calc"]["has_drift"] = bool( - result_tmp["pValue"] <= 0.05 - ) - else: - feature_dict_to_append["drift_calc"]["type"] = "KS" - result_tmp = ks.test(column, column) - feature_dict_to_append["drift_calc"]["value"] = float( - result_tmp["ks_statistic"] - ) - feature_dict_to_append["drift_calc"]["has_drift"] = bool( - result_tmp["ks_statistic"] > result_tmp["critical_value"] - ) drift_result["feature_metrics"].append(feature_dict_to_append) int_features = [ @@ -107,46 +82,18 @@ def calculate_drift( for column in int_features: feature_dict_to_append = { "feature_name": column, - "drift_calc": {}, + "field_type": FieldTypes.numerical.value, + "drift_calc": { + "type": "PSI", + }, } - unique_values_ref = ( - reference_dataset.reference.select(column) - .distinct() - .rdd.flatMap(lambda x: x) - .collect() + result_tmp = psi_obj.calculate_psi(column) + feature_dict_to_append["drift_calc"]["value"] = float( + result_tmp["psi_value"] ) - unique_values_cur = ( - current_dataset.current.select(column) - .distinct() - .rdd.flatMap(lambda x: x) - .collect() + feature_dict_to_append["drift_calc"]["has_drift"] = bool( + result_tmp["psi_value"] >= 0.1 ) - unique_values_refcur = unique_values_ref + unique_values_cur - lookup = set() - unique_values_tot = [ - x - for x in unique_values_refcur - if x is not None and x not in lookup and lookup.add(x) is None - ] - if len(unique_values_tot) < 15: - feature_dict_to_append["drift_calc"]["type"] = "CHI2" - feature_dict_to_append["drift_calc"]["type"] = "CHI2" - result_tmp = chi2.test_goodness_fit(column, column) - feature_dict_to_append["drift_calc"]["value"] = float( - result_tmp["pValue"] - ) - feature_dict_to_append["drift_calc"]["has_drift"] = bool( - result_tmp["pValue"] <= 0.05 - ) - else: - feature_dict_to_append["drift_calc"]["type"] = "PSI" - result_tmp = psi_obj.calculate_psi(column) - feature_dict_to_append["drift_calc"]["value"] = float( - result_tmp["psi_value"] - ) - feature_dict_to_append["drift_calc"]["has_drift"] = bool( - result_tmp["psi_value"] >= 0.1 - ) drift_result["feature_metrics"].append(feature_dict_to_append) return drift_result diff --git a/spark/tests/drift_calculator_test.py b/spark/tests/drift_calculator_test.py index a752ae18..7bf21cb0 100644 --- a/spark/tests/drift_calculator_test.py +++ b/spark/tests/drift_calculator_test.py @@ -577,7 +577,7 @@ def test_drift_phone(spark_fixture, drift_dataset_phone): field_type=FieldTypes.categorical, ), ColumnDefinition( - name="num_cores", type=SupportedTypes.int, field_type=FieldTypes.numerical + name="num_cores", type=SupportedTypes.int, field_type=FieldTypes.categorical ), ColumnDefinition( name="processor_speed", @@ -592,7 +592,7 @@ def test_drift_phone(spark_fixture, drift_dataset_phone): ColumnDefinition( name="fast_charging_available", type=SupportedTypes.int, - field_type=FieldTypes.numerical, + field_type=FieldTypes.categorical, ), ColumnDefinition( name="fast_charging", @@ -602,12 +602,12 @@ def test_drift_phone(spark_fixture, drift_dataset_phone): ColumnDefinition( name="ram_capacity", type=SupportedTypes.int, - field_type=FieldTypes.numerical, + field_type=FieldTypes.categorical, ), ColumnDefinition( name="internal_memory", type=SupportedTypes.int, - field_type=FieldTypes.numerical, + field_type=FieldTypes.categorical, ), ColumnDefinition( name="screen_size", @@ -622,12 +622,12 @@ def test_drift_phone(spark_fixture, drift_dataset_phone): ColumnDefinition( name="num_rear_cameras", type=SupportedTypes.int, - field_type=FieldTypes.numerical, + field_type=FieldTypes.categorical, ), ColumnDefinition( name="num_front_cameras", type=SupportedTypes.int, - field_type=FieldTypes.numerical, + field_type=FieldTypes.categorical, ), ColumnDefinition( name="os", type=SupportedTypes.string, field_type=FieldTypes.categorical @@ -645,22 +645,22 @@ def test_drift_phone(spark_fixture, drift_dataset_phone): ColumnDefinition( name="extended_memory_available", type=SupportedTypes.int, - field_type=FieldTypes.numerical, + field_type=FieldTypes.categorical, ), ColumnDefinition( name="extended_upto", type=SupportedTypes.float, - field_type=FieldTypes.numerical, + field_type=FieldTypes.categorical, ), ColumnDefinition( name="resolution_width", type=SupportedTypes.int, - field_type=FieldTypes.numerical, + field_type=FieldTypes.categorical, ), ColumnDefinition( name="resolution_height", type=SupportedTypes.int, - field_type=FieldTypes.numerical, + field_type=FieldTypes.categorical, ), ] model = ModelOut( diff --git a/spark/tests/results/drift_calculator_results.py b/spark/tests/results/drift_calculator_results.py index 0a8f5d13..e47f23a5 100644 --- a/spark/tests/results/drift_calculator_results.py +++ b/spark/tests/results/drift_calculator_results.py @@ -2,10 +2,12 @@ "feature_metrics": [ { "feature_name": "cat1", + "field_type": "categorical", "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { "feature_name": "cat2", + "field_type": "categorical", "drift_calc": { "type": "CHI2", "value": 2.5396285894708634e-10, @@ -14,11 +16,13 @@ }, { "feature_name": "num1", - "drift_calc": {"type": "CHI2", "value": 0.0, "has_drift": True}, + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.9, "has_drift": True}, }, { "feature_name": "num2", - "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.3, "has_drift": False}, }, ] } @@ -27,6 +31,7 @@ "feature_metrics": [ { "feature_name": "cat1", + "field_type": "categorical", "drift_calc": { "type": "CHI2", "value": 0.7788007830714049, @@ -35,6 +40,7 @@ }, { "feature_name": "cat2", + "field_type": "categorical", "drift_calc": { "type": "CHI2", "value": 0.007660761135179449, @@ -43,15 +49,13 @@ }, { "feature_name": "num1", - "drift_calc": {"type": "CHI2", "value": 0.0, "has_drift": True}, + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.75, "has_drift": False}, }, { "feature_name": "num2", - "drift_calc": { - "type": "CHI2", - "value": 0.4158801869955079, - "has_drift": False, - }, + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.7, "has_drift": False}, }, ] } @@ -60,19 +64,23 @@ "feature_metrics": [ { "feature_name": "cat1", + "field_type": "categorical", "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { "feature_name": "bool1", + "field_type": "categorical", "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { "feature_name": "num1", - "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.4, "has_drift": False}, }, { "feature_name": "num2", - "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.3, "has_drift": False}, }, ] } @@ -81,6 +89,7 @@ "feature_metrics": [ { "feature_name": "cat1", + "field_type": "categorical", "drift_calc": { "type": "CHI2", "value": 0.7074036474040617, @@ -89,6 +98,7 @@ }, { "feature_name": "cat2", + "field_type": "categorical", "drift_calc": { "type": "CHI2", "value": 1.3668274623882378e-07, @@ -97,47 +107,22 @@ }, { "feature_name": "num1", - "drift_calc": {"type": "CHI2", "value": 0.0, "has_drift": True}, + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.9230769231, "has_drift": True}, }, { "feature_name": "num2", - "drift_calc": { - "type": "CHI2", - "value": 0.9282493523958153, - "has_drift": False, - }, + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.5384615385, "has_drift": False}, }, ] } test_drift_bike_res = { "feature_metrics": [ - { - "feature_name": "weathersit", - "drift_calc": { - "type": "CHI2", - "value": 0.5328493415823949, - "has_drift": False, - }, - }, - { - "feature_name": "temp", - "drift_calc": {"type": "KS", "value": 0.5259741552, "has_drift": True}, - }, - { - "feature_name": "atemp", - "drift_calc": {"type": "KS", "value": 0.5322880465, "has_drift": True}, - }, - { - "feature_name": "hum", - "drift_calc": {"type": "KS", "value": 0.2230727748, "has_drift": True}, - }, - { - "feature_name": "windspeed", - "drift_calc": {"type": "KS", "value": 0.2180156245, "has_drift": True}, - }, { "feature_name": "season", + "field_type": "categorical", "drift_calc": { "type": "CHI2", "value": 1.5727996539817032e-36, @@ -146,6 +131,7 @@ }, { "feature_name": "yr", + "field_type": "categorical", "drift_calc": { "type": "CHI2", "value": 1.3270931223367946e-23, @@ -154,6 +140,7 @@ }, { "feature_name": "mnth", + "field_type": "categorical", "drift_calc": { "type": "CHI2", "value": 1.1116581506687278e-44, @@ -162,6 +149,7 @@ }, { "feature_name": "holiday", + "field_type": "categorical", "drift_calc": { "type": "CHI2", "value": 0.6115640463654775, @@ -170,6 +158,7 @@ }, { "feature_name": "weekday", + "field_type": "categorical", "drift_calc": { "type": "CHI2", "value": 0.9998169413361089, @@ -178,12 +167,38 @@ }, { "feature_name": "workingday", + "field_type": "categorical", "drift_calc": { "type": "CHI2", "value": 0.730645812540401, "has_drift": False, }, }, + { + "feature_name": "weathersit", + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.6219091927, "has_drift": True}, + }, + { + "feature_name": "temp", + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.5259741552, "has_drift": True}, + }, + { + "feature_name": "atemp", + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.5322880465, "has_drift": True}, + }, + { + "feature_name": "hum", + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.2230727748, "has_drift": True}, + }, + { + "feature_name": "windspeed", + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.2180156245, "has_drift": True}, + }, ] } @@ -191,14 +206,17 @@ "feature_metrics": [ { "feature_name": "brand_name", + "field_type": "categorical", "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { "feature_name": "model", + "field_type": "categorical", "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { "feature_name": "has_5g", + "field_type": "categorical", "drift_calc": { "type": "CHI2", "value": 0.652356328876868, @@ -207,103 +225,126 @@ }, { "feature_name": "has_nfc", + "field_type": "categorical", "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { "feature_name": "has_ir_blaster", + "field_type": "categorical", "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { "feature_name": "processor_brand", + "field_type": "categorical", "drift_calc": {"type": "CHI2", "value": 0.0, "has_drift": True}, }, { - "feature_name": "os", + "feature_name": "num_cores", + "field_type": "categorical", "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { - "feature_name": "rating", - "drift_calc": {"type": "KS", "value": 0.9989795918, "has_drift": True}, - }, - { - "feature_name": "processor_speed", - "drift_calc": {"type": "KS", "value": 0.1541282799, "has_drift": True}, + "feature_name": "fast_charging_available", + "field_type": "categorical", + "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { - "feature_name": "fast_charging", - "drift_calc": {"type": "KS", "value": 0.196941691, "has_drift": True}, + "feature_name": "ram_capacity", + "field_type": "categorical", + "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { - "feature_name": "screen_size", - "drift_calc": {"type": "KS", "value": 0.119877551, "has_drift": True}, + "feature_name": "internal_memory", + "field_type": "categorical", + "drift_calc": { + "type": "CHI2", + "value": 0.9999999710826085, + "has_drift": False, + }, }, { - "feature_name": "primary_camera_rear", - "drift_calc": {"type": "KS", "value": 0.3382259475, "has_drift": True}, + "feature_name": "num_rear_cameras", + "field_type": "categorical", + "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { - "feature_name": "primary_camera_front", - "drift_calc": {"type": "KS", "value": 0.3139650146, "has_drift": True}, + "feature_name": "num_front_cameras", + "field_type": "categorical", + "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { - "feature_name": "extended_upto", + "feature_name": "os", + "field_type": "categorical", "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { - "feature_name": "price", - "drift_calc": {"type": "PSI", "value": 0.0, "has_drift": False}, + "feature_name": "extended_memory_available", + "field_type": "categorical", + "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { - "feature_name": "num_cores", + "feature_name": "extended_upto", + "field_type": "categorical", "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { - "feature_name": "battery_capacity", - "drift_calc": {"type": "PSI", "value": 0.0, "has_drift": False}, + "feature_name": "resolution_width", + "field_type": "categorical", + "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { - "feature_name": "fast_charging_available", + "feature_name": "resolution_height", + "field_type": "categorical", "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, }, { - "feature_name": "ram_capacity", - "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, + "feature_name": "rating", + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.9989795918, "has_drift": True}, }, { - "feature_name": "internal_memory", - "drift_calc": { - "type": "CHI2", - "value": 0.9999999710826085, - "has_drift": False, - }, + "feature_name": "processor_speed", + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.1541282799, "has_drift": True}, }, { - "feature_name": "refresh_rate", - "drift_calc": { - "type": "CHI2", - "value": 0.9997690818736329, - "has_drift": False, - }, + "feature_name": "fast_charging", + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.196941691, "has_drift": True}, }, { - "feature_name": "num_rear_cameras", - "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, + "feature_name": "screen_size", + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.119877551, "has_drift": True}, }, { - "feature_name": "num_front_cameras", - "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, + "feature_name": "primary_camera_rear", + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.3382259475, "has_drift": True}, }, { - "feature_name": "extended_memory_available", - "drift_calc": {"type": "CHI2", "value": 1.0, "has_drift": False}, + "feature_name": "primary_camera_front", + "field_type": "numerical", + "drift_calc": {"type": "KS", "value": 0.3139650146, "has_drift": True}, }, { - "feature_name": "resolution_width", + "feature_name": "price", + "field_type": "numerical", "drift_calc": {"type": "PSI", "value": 0.0, "has_drift": False}, }, { - "feature_name": "resolution_height", + "feature_name": "battery_capacity", + "field_type": "numerical", "drift_calc": {"type": "PSI", "value": 0.0, "has_drift": False}, }, + { + "feature_name": "refresh_rate", + "field_type": "numerical", + "drift_calc": { + "type": "PSI", + "value": 0.00011810925171709961, + "has_drift": False, + }, + }, ] } diff --git a/spark/tests/results/jobs_results.py b/spark/tests/results/jobs_results.py index 181e9cbb..1faf52e3 100644 --- a/spark/tests/results/jobs_results.py +++ b/spark/tests/results/jobs_results.py @@ -2,7 +2,7 @@ "MODEL_QUALITY": '{"global_metrics":{"f1":0.949532986436427,"accuracy":0.9495798319327731,"weighted_precision":0.9496219540447758,"weighted_recall":0.9495798319327731,"weighted_true_positive_rate":0.9495798319327731,"weighted_false_positive_rate":0.053168331611734364,"weighted_f_measure":0.949532986436427,"true_positive_rate":0.9618320610687023,"false_positive_rate":0.06542056074766354,"precision":0.9473684210526315,"recall":0.9618320610687023,"f_measure":0.9545454545454546,"true_positive_count":126,"false_positive_count":7,"true_negative_count":100,"false_negative_count":5,"area_under_roc":0.43144039380751953,"area_under_pr":0.4811982176119641,"log_loss":0.23320784540174666},"grouped_metrics":{"f1":[{"timestamp":"2024-06-16 00:00:00","value":0.8967032967032967},{"timestamp":"2024-06-16 01:00:00","value":0.9148148148148147},{"timestamp":"2024-06-16 02:00:00","value":1.0},{"timestamp":"2024-06-16 03:00:00","value":1.0},{"timestamp":"2024-06-16 04:00:00","value":0.9327300150829563},{"timestamp":"2024-06-16 05:00:00","value":0.8461538461538463},{"timestamp":"2024-06-16 06:00:00","value":1.0},{"timestamp":"2024-06-16 07:00:00","value":0.9229813664596275},{"timestamp":"2024-06-16 08:00:00","value":0.9180952380952382},{"timestamp":"2024-06-16 09:00:00","value":0.9251700680272108},{"timestamp":"2024-06-16 10:00:00","value":1.0},{"timestamp":"2024-06-16 11:00:00","value":1.0},{"timestamp":"2024-06-16 12:00:00","value":0.9210658622423328},{"timestamp":"2024-06-16 13:00:00","value":0.9240093240093239},{"timestamp":"2024-06-16 14:00:00","value":1.0},{"timestamp":"2024-06-16 15:00:00","value":1.0},{"timestamp":"2024-06-16 16:00:00","value":1.0},{"timestamp":"2024-06-16 17:00:00","value":0.8181818181818182},{"timestamp":"2024-06-16 18:00:00","value":1.0},{"timestamp":"2024-06-16 19:00:00","value":1.0}],"accuracy":[{"timestamp":"2024-06-16 00:00:00","value":0.9},{"timestamp":"2024-06-16 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- "DRIFT": 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+ "DRIFT": 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} test_bc_joined_reference_res = { @@ -15,7 +15,7 @@ "STATISTICS": '{"n_variables":7,"n_observations":10,"missing_cells":3,"missing_cells_perc":4.285714285714286,"duplicate_rows":0,"duplicate_rows_perc":0.0,"numeric":2,"categorical":4,"datetime":1}', "DATA_QUALITY": 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'{"feature_metrics":[{"feature_name":"Sex","drift_calc":{"type":"CHI2","value":0.424235775426858,"has_drift":false}},{"feature_name":"pred_id","drift_calc":{"type":"CHI2","value":0.0,"has_drift":true}},{"feature_name":"Length","drift_calc":{"type":"KS","value":0.025363836,"has_drift":false}},{"feature_name":"Diameter","drift_calc":{"type":"KS","value":0.0323309349,"has_drift":true}},{"feature_name":"Height","drift_calc":{"type":"KS","value":0.0657365912,"has_drift":true}},{"feature_name":"Whole_weight","drift_calc":{"type":"KS","value":0.006636604,"has_drift":false}},{"feature_name":"Shucked_weight","drift_calc":{"type":"KS","value":0.0078291138,"has_drift":false}},{"feature_name":"Viscera_weight","drift_calc":{"type":"KS","value":0.0088653421,"has_drift":false}},{"feature_name":"Shell_weight","drift_calc":{"type":"KS","value":0.0130853067,"has_drift":false}}]}', + "DRIFT": '{"feature_metrics":[{"feature_name":"Sex","field_type":"categorical","drift_calc":{"type":"CHI2","value":0.424235775426858,"has_drift":false}},{"feature_name":"pred_id","field_type":"categorical","drift_calc":{"type":"CHI2","value":0.0,"has_drift":true}},{"feature_name":"Length","field_type":"numerical","drift_calc":{"type":"KS","value":0.025363836,"has_drift":false}},{"feature_name":"Diameter","field_type":"numerical","drift_calc":{"type":"KS","value":0.0323309349,"has_drift":true}},{"feature_name":"Height","field_type":"numerical","drift_calc":{"type":"KS","value":0.0657365912,"has_drift":true}},{"feature_name":"Whole_weight","field_type":"numerical","drift_calc":{"type":"KS","value":0.006636604,"has_drift":false}},{"feature_name":"Shucked_weight","field_type":"numerical","drift_calc":{"type":"KS","value":0.0078291138,"has_drift":false}},{"feature_name":"Viscera_weight","field_type":"numerical","drift_calc":{"type":"KS","value":0.0088653421,"has_drift":false}},{"feature_name":"Shell_weight","field_type":"numerical","drift_calc":{"type":"KS","value":0.0130853067,"has_drift":false}}]}', } test_reg_abalone_reference_res = {