Change-Id: Iff83f4340beb51edbfcba230b60b175ac8c2d6ad
Signed-off-by: Tibor Frank <tifrank@cisco.com>
if normalize else 1.0
if itm["testtype"] == "mrr":
y_data_raw = itm_data[_VALUE[itm["testtype"]]].to_list()[0]
if normalize else 1.0
if itm["testtype"] == "mrr":
y_data_raw = itm_data[_VALUE[itm["testtype"]]].to_list()[0]
- y_data = [y * norm_factor for y in y_data_raw]
+ y_data = [(y * norm_factor) for y in y_data_raw]
if len(y_data) > 0:
y_tput_max = \
max(y_data) if max(y_data) > y_tput_max else y_tput_max
else:
y_data_raw = itm_data[_VALUE[itm["testtype"]]].to_list()
if len(y_data) > 0:
y_tput_max = \
max(y_data) if max(y_data) > y_tput_max else y_tput_max
else:
y_data_raw = itm_data[_VALUE[itm["testtype"]]].to_list()
- y_data = [y * norm_factor for y in y_data_raw]
+ y_data = [(y * norm_factor) for y in y_data_raw]
if y_data:
y_tput_max = \
max(y_data) if max(y_data) > y_tput_max else y_tput_max
if y_data:
y_tput_max = \
max(y_data) if max(y_data) > y_tput_max else y_tput_max
if itm["testtype"] == "pdr":
y_lat_row = itm_data[_VALUE["pdr-lat"]].to_list()
if itm["testtype"] == "pdr":
y_lat_row = itm_data[_VALUE["pdr-lat"]].to_list()
- y_lat = [y * norm_factor for y in y_lat_row]
+ y_lat = [(y / norm_factor) for y in y_lat_row]
if y_lat:
y_lat_max = max(y_lat) if max(y_lat) > y_lat_max else y_lat_max
nr_of_samples = len(y_lat)
if y_lat:
y_lat_max = max(y_lat) if max(y_lat) > y_lat_max else y_lat_max
nr_of_samples = len(y_lat)
return list()
x_axis = df["start_time"].tolist()
return list()
x_axis = df["start_time"].tolist()
- y_data = [itm * norm_factor for itm in df[_VALUE[ttype]].tolist()]
+ if ttype == "pdr-lat":
+ y_data = [(itm / norm_factor) for itm in df[_VALUE[ttype]].tolist()]
+ else:
+ y_data = [(itm * norm_factor) for itm in df[_VALUE[ttype]].tolist()]
anomalies, trend_avg, trend_stdev = _classify_anomalies(
{k: v for k, v in zip(x_axis, y_data)}
anomalies, trend_avg, trend_stdev = _classify_anomalies(
{k: v for k, v in zip(x_axis, y_data)}
hover = list()
customdata = list()
hover = list()
customdata = list()
- for _, row in df.iterrows():
+ for idx, (_, row) in enumerate(df.iterrows()):
d_type = "trex" if row["dut_type"] == "none" else row["dut_type"]
hover_itm = (
f"date: {row['start_time'].strftime('%Y-%m-%d %H:%M:%S')}<br>"
d_type = "trex" if row["dut_type"] == "none" else row["dut_type"]
hover_itm = (
f"date: {row['start_time'].strftime('%Y-%m-%d %H:%M:%S')}<br>"
- f"<prop> [{row[_UNIT[ttype]]}]: {row[_VALUE[ttype]]:,.0f}<br>"
+ f"<prop> [{row[_UNIT[ttype]]}]: {y_data[idx]:,.0f}<br>"
f"<stdev>"
f"{d_type}-ref: {row['dut_version']}<br>"
f"csit-ref: {row['job']}/{row['build']}<br>"
f"<stdev>"
f"{d_type}-ref: {row['dut_version']}<br>"
f"csit-ref: {row['job']}/{row['build']}<br>"
row_card_sel_tests = self.STYLE_ENABLED
row_btns_sel_tests = self.STYLE_ENABLED
row_card_sel_tests = self.STYLE_ENABLED
row_btns_sel_tests = self.STYLE_ENABLED
- if trigger_id in ("btn-ctrl-add", "url", "dpr-period"
+ if trigger_id in ("btn-ctrl-add", "url", "dpr-period",
"btn-sel-remove", "cl-ctrl-normalize"):
if store_sel:
row_fig_tput, row_fig_lat, row_btn_dwnld = \
"btn-sel-remove", "cl-ctrl-normalize"):
if store_sel:
row_fig_tput, row_fig_lat, row_btn_dwnld = \