)
text = u""
+
+ legend = (f"Legend:\n[ Last trend in Mpps | number of runs for "
+ f"last trend |")
+
+ out_file = (
+ f"{self.configs[alert[u'way']][u'output-dir']}/"
+ f"trending-regressions.txt"
+ )
+ try:
+ with open(out_file, u'w') as reg_file:
+ reg_file.write(f"{legend} regressions ]")
+ except IOError:
+ logging.error(f"Not possible to write the file {out_file}.txt.")
+
+ out_file = (
+ f"{self.configs[alert[u'way']][u'output-dir']}/"
+ f"trending-progressions.txt"
+ )
+ try:
+ with open(out_file, u'w') as reg_file:
+ reg_file.write(f"{legend} progressions ]")
+ except IOError:
+ logging.error(f"Not possible to write the file {out_file}.txt.")
+
for idx, test_set in enumerate(alert.get(u"include", list())):
test_set_short = u""
device = u""
# 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"