diff options
Diffstat (limited to 'resources/tools/presentation/generator_plots.py')
| -rw-r--r-- | resources/tools/presentation/generator_plots.py | 188 |
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, |