_create_test_name(test).replace("-ndrpdr", "-pdr"),
x_axis[_get_rindex(anomalies, "regression")]
))
- else: # mrr
- tst_data = tst_data.dropna(
- subset=["result_receive_rate_rate_avg", ]
- )
+ else: # mrr, hoststack, soak
+ if "soak" in test:
+ val = "result_critical_rate_lower_rate_value"
+ elif "hoststack" in test:
+ val = "result_rate_value"
+ else: # mrr
+ val = "result_receive_rate_rate_avg"
+ tst_data = tst_data.dropna(subset=[val, ])
if tst_data.empty:
continue
x_axis = tst_data["start_time"].tolist()
try:
anomalies, _, _ = classify_anomalies({
- k: v for k, v in zip(
- x_axis,
- tst_data["result_receive_rate_rate_avg"].\
- tolist()
- )
+ k: v for k, v in zip(x_axis, tst_data[val].tolist())
})
except ValueError:
continue