Remaining anomaly rules updated to use the new library function.

home/rules/percentile/anomaly_stationary_percent_values.py

@@ -104,16 +104,15 @@ def evaluate_rule(rule_parameters: RuleExecutionRunParameters) -> RuleExecutionR
  filtered_median_float if 0.0 not in all_extracted else 0.0,
  filtered_median_float if 100.0 not in all_extracted else 100.0)
 
- degrees_of_freedom = float(rule_parameters.configuration_parameters.degrees_of_freedom)
- tail = rule_parameters.parameters.anomaly_percent / 100.0
+ tail = rule_parameters.parameters.anomaly_percent / 100.0 / 2.0
 
  if 100.0 in all_extracted:
  threshold_upper = 100.0
  else:
- upper_median_multiples_array = [1.0 / (1.0 - readout / 100.0) for readout in extracted
-  if readout >= filtered_median_float]
- threshold_upper_multiple = detect_upper_bound_anomaly(values_above_median=upper_median_multiples_array,
- degrees_of_freedom=degrees_of_freedom, tail=tail)
+ upper_median_multiples_array = [1.0 / (1.0 - readout / 100.0) for readout in extracted]
+ threshold_upper_multiple = detect_upper_bound_anomaly(values=upper_median_multiples_array,
+  median=1.0 / (1.0 - filtered_median_float / 100.0),
+ tail=tail, parameters=rule_parameters)
 
  if threshold_upper_multiple is not None:
  threshold_upper = 100.0 - 100.0 * (1.0 / threshold_upper_multiple)
@@ -123,10 +122,10 @@ def evaluate_rule(rule_parameters: RuleExecutionRunParameters) -> RuleExecutionR
  if 0.0 in all_extracted:
  threshold_lower = 0.0
  else:
- lower_median_multiples_array = [(-1.0 / (readout / filtered_median_float)) for readout in extracted
-  if readout <= filtered_median_float]
- threshold_lower_multiple = detect_lower_bound_anomaly(values_below_median=lower_median_multiples_array,
- degrees_of_freedom=degrees_of_freedom, tail=tail)
+ lower_median_multiples_array = [(-1.0 / (readout / filtered_median_float)) for readout in extracted]
+ threshold_lower_multiple = detect_lower_bound_anomaly(values=lower_median_multiples_array,
+  median=-1.0,
+ tail=tail, parameters=rule_parameters)
 
  if threshold_lower_multiple is not None:
  threshold_lower = filtered_median_float * (-1.0 / threshold_lower_multiple)