CSIT-1354: Show number of used samples in graphs in report

Change-Id: Ica3bd5bff2e7d24994d1e92bf91d218794a0cdfb
Signed-off-by: Tibor Frank <tifrank@cisco.com>
(cherry picked from commit e7a7dd493624179fff9417b55e41cc58b36805d2)

1 files changed, 110 insertions, 78 deletions

diff --git a/resources/tools/presentation/generator_plots.py b/resources/tools/presentation/generator_plots.py
index 628ea534ee..0f660999dd 100644
--- a/resources/tools/presentation/generator_plots.py
+++ b/resources/tools/presentation/generator_plots.py
@@ -129,9 +129,11 @@ def plot_performance_box(plot, input_data):
 
     # Add None to the lists with missing data
     max_len = 0
+    nr_of_samples = list()
     for val in y_sorted.values():
         if len(val) > max_len:
             max_len = len(val)
+        nr_of_samples.append(len(val))
     for key, val in y_sorted.items():
         if len(val) < max_len:
             val.extend([None for _ in range(max_len - len(val))])
@@ -142,8 +144,11 @@ def plot_performance_box(plot, input_data):
     df.head()
     y_max = list()
     for i, col in enumerate(df.columns):
-        name = "{0}. {1}".format(i + 1, col.lower().replace('-ndrpdrdisc', '').
-                                 replace('-ndrpdr', ''))
+        name = "{0}. {1} ({2} run{3})".\
+            format(i + 1,
+                   col.lower().replace('-ndrpdr', ''),
+                   nr_of_samples[i],
+                   's' if nr_of_samples[i] > 1 else '')
         logging.debug(name)
         traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]),
                                y=[y / 1000000 if y else None for y in df[col]],
@@ -248,6 +253,7 @@ def plot_latency_error_bars(plot, input_data):
                 except (KeyError, TypeError) as err:
                     logging.warning(repr(err))
     logging.debug("y_tmp_vals: {0}\n".format(y_tmp_vals))
+
     # Sort the tests
     order = plot.get("sort", None)
     if order and y_tags:
@@ -279,21 +285,25 @@ def plot_latency_error_bars(plot, input_data):
     y_vals = list()
     y_mins = list()
     y_maxs = list()
+    nr_of_samples = list()
     for key, val in y_sorted.items():
         key = "-".join(key.split("-")[1:-1])
         x_vals.append(key)  # dir 1
         y_vals.append(mean(val[1]) if val[1] else None)
         y_mins.append(mean(val[0]) if val[0] else None)
         y_maxs.append(mean(val[2]) if val[2] else None)
+        nr_of_samples.append(len(val[1]) if val[1] else 0)
         x_vals.append(key)  # dir 2
         y_vals.append(mean(val[4]) if val[4] else None)
         y_mins.append(mean(val[3]) if val[3] else None)
         y_maxs.append(mean(val[5]) if val[5] else None)
+        nr_of_samples.append(len(val[3]) if val[3] else 0)
 
     logging.debug("x_vals :{0}\n".format(x_vals))
     logging.debug("y_vals :{0}\n".format(y_vals))
     logging.debug("y_mins :{0}\n".format(y_mins))
     logging.debug("y_maxs :{0}\n".format(y_maxs))
+    logging.debug("nr_of_samples :{0}\n".format(nr_of_samples))
     traces = list()
     annotations = list()
 
@@ -303,8 +313,10 @@ def plot_latency_error_bars(plot, input_data):
         else:
             direction = "East - West"
         hovertext = ("Test: {test}<br>"
-                     "Direction: {dir}<br>".format(test=x_vals[idx],
-                                                   dir=direction))
+                     "Direction: {dir}<br>"
+                     "No. of Runs: {nr}<br>".format(test=x_vals[idx],
+                                                    dir=direction,
+                                                    nr=nr_of_samples[idx]))
         if isinstance(y_maxs[idx], float):
             hovertext += "Max: {max:.2f}uSec<br>".format(max=y_maxs[idx])
         if isinstance(y_vals[idx], float):
@@ -441,7 +453,7 @@ def plot_throughput_speedup_analysis(plot, input_data):
         for key, test_val in test_vals.items():
             if test_val:
                 avg_val = sum(test_val) / len(test_val)
-                y_vals[test_name][key] =  avg_val
+                y_vals[test_name][key] = (avg_val, len(test_val))
                 ideal = avg_val / (int(key) * 1000000.0)
                 if test_name not in y_1c_max or ideal > y_1c_max[test_name]:
                     y_1c_max[test_name] = ideal
@@ -452,38 +464,47 @@ def plot_throughput_speedup_analysis(plot, input_data):
     lnk_limit = 0
     pci_limit = plot["limits"]["pci"]["pci-g3-x8"]
     for test_name, test_vals in y_vals.items():
-        if test_vals["1"]:
-            name = "-".join(test_name.split('-')[1:-1])
-
-            vals[name] = dict()
-            y_val_1 = test_vals["1"] / 1000000.0
-            y_val_2 = test_vals["2"] / 1000000.0 if test_vals["2"] else None
-            y_val_4 = test_vals["4"] / 1000000.0 if test_vals["4"] else None
-
-            vals[name]["val"] = [y_val_1, y_val_2, y_val_4]
-            vals[name]["rel"] = [1.0, None, None]
-            vals[name]["ideal"] = [y_1c_max[test_name],
-                                   y_1c_max[test_name] * 2,
-                                   y_1c_max[test_name] * 4]
-            vals[name]["diff"] = \
-                [(y_val_1 - y_1c_max[test_name]) * 100 / y_val_1, None, None]
-
-            try:
-                val_max = max(max(vals[name]["val"], vals[name]["ideal"]))
-            except ValueError as err:
-                logging.error(err)
-                continue
-            if val_max:
-                y_max.append(int((val_max / 10) + 1) * 10)
-
-            if y_val_2:
-                vals[name]["rel"][1] = round(y_val_2 / y_val_1, 2)
-                vals[name]["diff"][1] = \
-                    (y_val_2 - vals[name]["ideal"][1]) * 100 / y_val_2
-            if y_val_4:
-                vals[name]["rel"][2] = round(y_val_4 / y_val_1, 2)
-                vals[name]["diff"][2] = \
-                    (y_val_4 - vals[name]["ideal"][2]) * 100 / y_val_4
+        try:
+            if test_vals["1"][1]:
+                name = "-".join(test_name.split('-')[1:-1])
+
+                vals[name] = dict()
+                y_val_1 = test_vals["1"][0] / 1000000.0
+                y_val_2 = test_vals["2"][0] / 1000000.0 if test_vals["2"][0] \
+                    else None
+                y_val_4 = test_vals["4"][0] / 1000000.0 if test_vals["4"][0] \
+                    else None
+
+                vals[name]["val"] = [y_val_1, y_val_2, y_val_4]
+                vals[name]["rel"] = [1.0, None, None]
+                vals[name]["ideal"] = [y_1c_max[test_name],
+                                       y_1c_max[test_name] * 2,
+                                       y_1c_max[test_name] * 4]
+                vals[name]["diff"] = [(y_val_1 - y_1c_max[test_name]) * 100 /
+                                      y_val_1, None, None]
+                vals[name]["count"] = [test_vals["1"][1],
+                                       test_vals["2"][1],
+                                       test_vals["4"][1]]
+
+                try:
+                    val_max = max(max(vals[name]["val"], vals[name]["ideal"]))
+                except ValueError as err:
+                    logging.error(err)
+                    continue
+                if val_max:
+                    y_max.append(int((val_max / 10) + 1) * 10)
+
+                if y_val_2:
+                    vals[name]["rel"][1] = round(y_val_2 / y_val_1, 2)
+                    vals[name]["diff"][1] = \
+                        (y_val_2 - vals[name]["ideal"][1]) * 100 / y_val_2
+                if y_val_4:
+                    vals[name]["rel"][2] = round(y_val_4 / y_val_1, 2)
+                    vals[name]["diff"][2] = \
+                        (y_val_4 - vals[name]["ideal"][2]) * 100 / y_val_4
+        except IndexError as err:
+            logging.warning("No data for '{0}'".format(test_name))
+            logging.warning(repr(err))
 
         # Limits:
         if "x520" in test_name:
@@ -639,45 +660,51 @@ def plot_throughput_speedup_analysis(plot, input_data):
     cidx = 0
     for name, val in y_sorted.iteritems():
         hovertext = list()
-        for idx in range(len(val["val"])):
-            htext = ""
-            if isinstance(val["val"][idx], float):
-                htext += "value: {0:.2f}Mpps<br>".format(val["val"][idx])
-            if isinstance(val["diff"][idx], float):
-                htext += "diff: {0:.0f}%<br>".format(round(val["diff"][idx]))
-            if isinstance(val["rel"][idx], float):
-                htext += "speedup: {0:.2f}".format(val["rel"][idx])
-            hovertext.append(htext)
-        traces.append(plgo.Scatter(x=x_vals,
-                                   y=val["val"],
-                                   name=name,
-                                   legendgroup=name,
-                                   mode="lines+markers",
-                                   line=dict(
-                                       color=COLORS[cidx],
-                                       width=2),
-                                   marker=dict(
-                                       symbol="circle",
-                                       size=10
-                                   ),
-                                   text=hovertext,
-                                   hoverinfo="text+name"
-                                   ))
-        traces.append(plgo.Scatter(x=x_vals,
-                                   y=val["ideal"],
-                                   name="{0} perfect".format(name),
-                                   legendgroup=name,
-                                   showlegend=False,
-                                   mode="lines",
-                                   line=dict(
-                                       color=COLORS[cidx],
-                                       width=2,
-                                       dash="dash"),
-                                   text=["perfect: {0:.2f}Mpps".format(y)
-                                         for y in val["ideal"]],
-                                   hoverinfo="text"
-                                   ))
-        cidx += 1
+        try:
+            for idx in range(len(val["val"])):
+                htext = ""
+                if isinstance(val["val"][idx], float):
+                    htext += "Value: {0:.2f}Mpps<br>" \
+                             "No. of Runs: {1}<br>".format(val["val"][idx],
+                                                        val["count"][idx])
+                if isinstance(val["diff"][idx], float):
+                    htext += "Diff: {0:.0f}%<br>".format(round(val["diff"][idx]))
+                if isinstance(val["rel"][idx], float):
+                    htext += "Speedup: {0:.2f}".format(val["rel"][idx])
+                hovertext.append(htext)
+            traces.append(plgo.Scatter(x=x_vals,
+                                       y=val["val"],
+                                       name=name,
+                                       legendgroup=name,
+                                       mode="lines+markers",
+                                       line=dict(
+                                           color=COLORS[cidx],
+                                           width=2),
+                                       marker=dict(
+                                           symbol="circle",
+                                           size=10
+                                       ),
+                                       text=hovertext,
+                                       hoverinfo="text+name"
+                                       ))
+            traces.append(plgo.Scatter(x=x_vals,
+                                       y=val["ideal"],
+                                       name="{0} perfect".format(name),
+                                       legendgroup=name,
+                                       showlegend=False,
+                                       mode="lines",
+                                       line=dict(
+                                           color=COLORS[cidx],
+                                           width=2,
+                                           dash="dash"),
+                                       text=["perfect: {0:.2f}Mpps".format(y)
+                                             for y in val["ideal"]],
+                                       hoverinfo="text"
+                                       ))
+            cidx += 1
+        except (IndexError, ValueError, KeyError) as err:
+            logging.warning("No data for '{0}'".format(name))
+            logging.warning(repr(err))
 
     try:
         # Create plot
@@ -733,9 +760,11 @@ def plot_http_server_performance_box(plot, input_data):
 
     # Add None to the lists with missing data
     max_len = 0
+    nr_of_samples = list()
     for val in y_vals.values():
         if len(val) > max_len:
             max_len = len(val)
+        nr_of_samples.append(len(val))
     for key, val in y_vals.items():
         if len(val) < max_len:
             val.extend([None for _ in range(max_len - len(val))])
@@ -745,8 +774,11 @@ def plot_http_server_performance_box(plot, input_data):
     df = pd.DataFrame(y_vals)
     df.head()
     for i, col in enumerate(df.columns):
-        name = "{0}. {1}".format(i + 1, col.lower().replace('-cps', '').
-                                 replace('-rps', ''))
+        name = "{0}. {1} ({2} run{3})".\
+            format(i + 1,
+                   col.lower().replace('-cps', '').replace('-rps', ''),
+                   nr_of_samples[i],
+                   's' if nr_of_samples[i] > 1 else '')
         traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]),
                                y=df[col],
                                name=name,