def is_bad(r):
if settings.param.sustained_median.trigger < r.result.confidence:
test_param = nvl(settings.param.test[literal_field(r.Talos.Test.name)], settings.param.suite[literal_field(r.Talos.Test.suite)])
if test_param == None:
return True
if test_param.disable:
return False
if test_param.better == "higher":
diff = -r.diff
elif test_param.better == "lower":
diff = r.diff
else:
diff = abs(r.diff) # DEFAULT = ANY DIRECTION IS BAD
if test_param.min_regression:
if unicode(test_param.min_regression.strip()[-1]) == "%":
min_diff = Math.abs(r.past_stats.mean * float(test_param.min_regression.strip()[:-1]) / 100.0)
else:
min_diff = Math.abs(float(test_param.min_regression))
else:
min_diff = Math.abs(r.past_stats.mean * 0.01)
if diff > min_diff:
return True
return False
def is_bad(r):
if settings.param.sustained_median.trigger < r.result.confidence:
test_param = settings.param.test[literal_field(r.B2G.Test.name)]
if test_param == None:
return True
if test_param.better == "higher":
diff = -r.diff
else:
diff = r.diff
if unicode(test_param.min_regression.strip()[-1]) == "%":
min_diff = Math.abs(r.past_stats.mean * float(test_param.min_regression.strip()[:-1]) / 100.0)
else:
min_diff = Math.abs(float(test_param.min_regression))
if diff > min_diff:
return True
return False