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eval_methods.py
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eval_methods.py
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import numpy as np
def adjust_predicts(predict, label, delay=7):
"""
Calculate adjusted predict labels.
This function is from AIOps Challenge, KPI Anomaly Detection Competition,
https://github.com/iopsai/iops/blob/master/evaluation/evaluation.py
"""
splits = np.where(label[1:] != label[:-1])[0] + 1
is_anomaly = label[0] == 1
new_predict = np.array(predict)
pos = 0
for sp in splits:
if is_anomaly:
if 1 in predict[pos:min(pos + delay + 1, sp)]:
new_predict[pos: sp] = 1
else:
new_predict[pos: sp] = 0
is_anomaly = not is_anomaly
pos = sp
sp = len(label)
if is_anomaly: # anomaly in the end
if 1 in predict[pos: min(pos + delay + 1, sp)]:
new_predict[pos: sp] = 1
else:
new_predict[pos: sp] = 0
return new_predict