- idx = len(classification_lst) - 1
- while idx:
- if classification_lst[idx] == classification:
- break
- idx -= 1
-
- trend = round(float(trend_lst[-2]) / 1000000, 2) \
- if not isnan(trend_lst[-2]) else ''
- sample = round(float(sample_lst[idx]) / 1000000, 2) \
- if not isnan(sample_lst[idx]) else ''
- rel_change = rel_change_lst[idx] \
- if rel_change_lst[idx] is not None else ''
+ if classification == "normal":
+ index = len(classification_lst) - 1
+ else:
+ tmp_classification = "outlier" if classification == "failure" \
+ else classification
+ for idx in range(first_idx, len(classification_lst)):
+ if classification_lst[idx] == tmp_classification:
+ index = idx
+ break
+ for idx in range(index+1, len(classification_lst)):
+ if classification_lst[idx] == tmp_classification:
+ if rel_change_lst[idx] > rel_change_lst[index]:
+ index = idx
+
+ # if "regression" in classification_lst[first_idx:]:
+ # classification = "regression"
+ # elif "outlier" in classification_lst[first_idx:]:
+ # classification = "outlier"
+ # elif "progression" in classification_lst[first_idx:]:
+ # classification = "progression"
+ # elif "normal" in classification_lst[first_idx:]:
+ # classification = "normal"
+ # else:
+ # classification = None
+ #
+ # nr_outliers = 0
+ # consecutive_outliers = 0
+ # failure = False
+ # for item in classification_lst[first_idx:]:
+ # if item == "outlier":
+ # nr_outliers += 1
+ # consecutive_outliers += 1
+ # if consecutive_outliers == 3:
+ # failure = True
+ # else:
+ # consecutive_outliers = 0
+ #
+ # idx = len(classification_lst) - 1
+ # while idx:
+ # if classification_lst[idx] == classification:
+ # break
+ # idx -= 1
+ #
+ # if failure:
+ # classification = "failure"
+ # elif classification == "outlier":
+ # classification = "normal"
+
+ trend = round(float(median_lst[-1]) / 1000000, 2) \
+ if not isnan(median_lst[-1]) else ''
+ sample = round(float(sample_lst[index]) / 1000000, 2) \
+ if not isnan(sample_lst[index]) else ''
+ rel_change = rel_change_lst[index] \
+ if rel_change_lst[index] is not None else ''