X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fgenerator_plots.py;h=7298babe537f0b43a6e4fcabd5f9bbc03e3d6d20;hp=dd0093941508e6bfcd742bf41e72481fdae8ad00;hb=0c02e000ae58474120246c484cf5458a76510288;hpb=826d80373dbd20bc1feac2403e9cade9e5633336

diff --git a/resources/tools/presentation/generator_plots.py b/resources/tools/presentation/generator_plots.py
index dd00939415..7298babe53 100644
--- a/resources/tools/presentation/generator_plots.py
+++ b/resources/tools/presentation/generator_plots.py
@@ -61,6 +61,9 @@ COLORS = (
 
 REGEX_NIC = re.compile(r'(\d*ge\dp\d\D*\d*[a-z]*)-')
 
+# This value depends on latency stream rate (9001 pps) and duration (5s).
+PERCENTILE_MAX = 99.9995
+
 
 def generate_plots(spec, data):
     """Generate all plots specified in the specification file.
@@ -189,8 +192,6 @@ def plot_hdrh_lat_by_percentile(plot, input_data):
 
                     for item in decoded.get_recorded_iterator():
                         percentile = item.percentile_level_iterated_to
-                        if percentile > 99.9999999:
-                            continue
                         xaxis.append(previous_x)
                         yaxis.append(item.value_iterated_to)
                         hovertext.append(
@@ -335,7 +336,6 @@ def plot_hdrh_lat_by_percentile_x_log(plot, input_data):
 
             fig = plgo.Figure()
             layout = deepcopy(plot[u"layout"])
-            xaxis_max = 0
 
             for color, graph in enumerate(graphs):
                 for idx, direction in enumerate((u"direction1", u"direction2")):
@@ -355,9 +355,11 @@ def plot_hdrh_lat_by_percentile_x_log(plot, input_data):
                         continue
 
                     for item in decoded.get_recorded_iterator():
+                        # The real value is "percentile".
+                        # For 100%, we cut that down to "x_perc" to avoid
+                        # infinity.
                         percentile = item.percentile_level_iterated_to
-                        if percentile > 99.9999999:
-                            continue
+                        x_perc = min(percentile, PERCENTILE_MAX)
                         xaxis.append(previous_x)
                         yaxis.append(item.value_iterated_to)
                         hovertext.append(
@@ -366,7 +368,7 @@ def plot_hdrh_lat_by_percentile_x_log(plot, input_data):
                             f"Percentile: {prev_perc:.5f}-{percentile:.5f}%<br>"
                             f"Latency: {item.value_iterated_to}uSec"
                         )
-                        next_x = 100.0 / (100.0 - percentile)
+                        next_x = 100.0 / (100.0 - x_perc)
                         xaxis.append(next_x)
                         yaxis.append(item.value_iterated_to)
                         hovertext.append(
@@ -394,11 +396,9 @@ def plot_hdrh_lat_by_percentile_x_log(plot, input_data):
                             hoverinfo=u"text"
                         )
                     )
-                    xaxis_max = max(xaxis) if xaxis_max < max(
-                        xaxis) else xaxis_max
 
             layout[u"title"][u"text"] = f"<b>Latency:</b> {name}"
-            layout[u"xaxis"][u"range"] = [0, int(log(xaxis_max, 10)) + 1]
+            layout[u"xaxis"][u"range"] = [0, 5.302]
             fig.update_layout(layout)
 
             # Create plot
@@ -486,19 +486,21 @@ def plot_nf_reconf_box_name(plot, input_data):
     df_y = pd.DataFrame(y_vals)
     df_y.head()
     for i, col in enumerate(df_y.columns):
+
         tst_name = re.sub(REGEX_NIC, u"",
-                          col.lower().replace(u'-ndrpdr', u'').
-                          replace(u'2n1l-', u''))
+                          col.lower().replace(u'-reconf', u'').
+                          replace(u'2n1l-', u'').replace(u'2n-', u'').
+                          replace(u'-testpmd', u''))
 
         traces.append(plgo.Box(
             x=[str(i + 1) + u'.'] * len(df_y[col]),
-            y=[y if y else None for y in df_y[col]],
+            y=df_y[col],
             name=(
                 f"{i + 1}. "
                 f"({nr_of_samples[i]:02d} "
                 f"run{u's' if nr_of_samples[i] > 1 else u''}, "
                 f"packets lost average: {mean(loss[col]):.1f}) "
-                f"{u'-'.join(tst_name.split(u'-')[3:-2])}"
+                f"{u'-'.join(tst_name.split(u'-')[2:])}"
             ),
             hoverinfo=u"y+name"
         ))