UTI: Small fixes and improvements

Change-Id: Iff83f4340beb51edbfcba230b60b175ac8c2d6ad
Signed-off-by: Tibor Frank <tifrank@cisco.com>

diff --git a/resources/tools/dash/app/pal/report/graphs.py b/resources/tools/dash/app/pal/report/graphs.py
index 0543193..76aa8b7 100644 (file)
--- 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 150b705..8950558 100644 (file)
--- 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 c21e4b3..d632820 100644 (file)
--- 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 = \