# Evaluate result:
if anomaly_classifications:
- legend_str = (f"Legend:\n[ Last trend in Mpps/Mcps | number of runs for"
- f" last trend | ")
result = u"PASS"
for job_name, job_data in anomaly_classifications.items():
data = []
if classification in (u"regression", u"outlier"):
result = u"FAIL"
-
- txt_file.write(f"\n{legend_str}regression in percentage ]")
-
file_name = \
f"{spec.cpta[u'output-file']}/progressions-{job_name}.txt"
with open(file_name, u'w') as txt_file:
ltc = line.split("|")[4]
txt_file.write(f"{tst_name} [ {trend}M | "
f"#{number} | {ltc}% ]\n")
-
- txt_file.write(f"\n{legend_str}progression in percentage ]")
else:
result = u"FAIL"