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-rw-r--r--resources/tools/dash/app/pal/report/graphs.py6
-rw-r--r--resources/tools/dash/app/pal/trending/graphs.py9
-rw-r--r--resources/tools/dash/app/pal/trending/layout.py2
3 files changed, 10 insertions, 7 deletions
diff --git a/resources/tools/dash/app/pal/report/graphs.py b/resources/tools/dash/app/pal/report/graphs.py
index 0543193d99..76aa8b7793 100644
--- a/resources/tools/dash/app/pal/report/graphs.py
+++ b/resources/tools/dash/app/pal/report/graphs.py
@@ -186,13 +186,13 @@ def graph_iterative(data: pd.DataFrame, sel:dict, layout: dict,
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()
- 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
@@ -215,7 +215,7 @@ def graph_iterative(data: pd.DataFrame, sel:dict, layout: dict,
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)
diff --git a/resources/tools/dash/app/pal/trending/graphs.py b/resources/tools/dash/app/pal/trending/graphs.py
index 150b7056ba..8950558166 100644
--- a/resources/tools/dash/app/pal/trending/graphs.py
+++ b/resources/tools/dash/app/pal/trending/graphs.py
@@ -237,7 +237,10 @@ def _generate_trending_traces(ttype: str, name: str, df: pd.DataFrame,
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)}
@@ -245,11 +248,11 @@ def _generate_trending_traces(ttype: str, name: str, df: pd.DataFrame,
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>"
- 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>"
diff --git a/resources/tools/dash/app/pal/trending/layout.py b/resources/tools/dash/app/pal/trending/layout.py
index c21e4b3c2e..d632820b99 100644
--- a/resources/tools/dash/app/pal/trending/layout.py
+++ b/resources/tools/dash/app/pal/trending/layout.py
@@ -1213,7 +1213,7 @@ class Layout:
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 = \