diff options
Diffstat (limited to 'resources/tools/presentation/generator_plots.py')
| -rw-r--r-- | resources/tools/presentation/generator_plots.py | 2989 |
1 files changed, 1075 insertions, 1914 deletions
diff --git a/resources/tools/presentation/generator_plots.py b/resources/tools/presentation/generator_plots.py index f67945567a..89eb1c6521 100644 --- a/resources/tools/presentation/generator_plots.py +++ b/resources/tools/presentation/generator_plots.py @@ -1,4 +1,4 @@ -# Copyright (c) 2019 Cisco and/or its affiliates. +# Copyright (c) 2020 Cisco and/or its affiliates. # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at: @@ -17,25 +17,30 @@ import re import logging + +from collections import OrderedDict +from copy import deepcopy + +import hdrh.histogram +import hdrh.codec import pandas as pd import plotly.offline as ploff import plotly.graph_objs as plgo +from plotly.subplots import make_subplots from plotly.exceptions import PlotlyError -from collections import OrderedDict -from copy import deepcopy -from utils import mean, stdev +from pal_utils import mean, stdev -COLORS = ["SkyBlue", "Olive", "Purple", "Coral", "Indigo", "Pink", - "Chocolate", "Brown", "Magenta", "Cyan", "Orange", "Black", - "Violet", "Blue", "Yellow", "BurlyWood", "CadetBlue", "Crimson", - "DarkBlue", "DarkCyan", "DarkGreen", "Green", "GoldenRod", - "LightGreen", "LightSeaGreen", "LightSkyBlue", "Maroon", - "MediumSeaGreen", "SeaGreen", "LightSlateGrey"] +COLORS = [u"SkyBlue", u"Olive", u"Purple", u"Coral", u"Indigo", u"Pink", + u"Chocolate", u"Brown", u"Magenta", u"Cyan", u"Orange", u"Black", + u"Violet", u"Blue", u"Yellow", u"BurlyWood", u"CadetBlue", u"Crimson", + u"DarkBlue", u"DarkCyan", u"DarkGreen", u"Green", u"GoldenRod", + u"LightGreen", u"LightSeaGreen", u"LightSkyBlue", u"Maroon", + u"MediumSeaGreen", u"SeaGreen", u"LightSlateGrey"] -REGEX_NIC = re.compile(r'\d*ge\dp\d\D*\d*-') +REGEX_NIC = re.compile(r'(\d*ge\dp\d\D*\d*[a-z]*)-') def generate_plots(spec, data): @@ -47,22 +52,35 @@ def generate_plots(spec, data): :type data: InputData """ - logging.info("Generating the plots ...") + generator = { + u"plot_nf_reconf_box_name": plot_nf_reconf_box_name, + u"plot_perf_box_name": plot_perf_box_name, + u"plot_lat_err_bars_name": plot_lat_err_bars_name, + u"plot_tsa_name": plot_tsa_name, + u"plot_http_server_perf_box": plot_http_server_perf_box, + u"plot_nf_heatmap": plot_nf_heatmap, + u"plot_lat_hdrh_bar_name": plot_lat_hdrh_bar_name, + u"plot_lat_hdrh_percentile": plot_lat_hdrh_percentile, + u"plot_hdrh_lat_by_percentile": plot_hdrh_lat_by_percentile + } + + logging.info(u"Generating the plots ...") for index, plot in enumerate(spec.plots): try: - logging.info(" Plot nr {0}: {1}".format(index + 1, - plot.get("title", ""))) - plot["limits"] = spec.configuration["limits"] - eval(plot["algorithm"])(plot, data) - logging.info(" Done.") + logging.info(f" Plot nr {index + 1}: {plot.get(u'title', u'')}") + plot[u"limits"] = spec.configuration[u"limits"] + generator[plot[u"algorithm"]](plot, data) + logging.info(u" Done.") except NameError as err: - logging.error("Probably algorithm '{alg}' is not defined: {err}". - format(alg=plot["algorithm"], err=repr(err))) - logging.info("Done.") + logging.error( + f"Probably algorithm {plot[u'algorithm']} is not defined: " + f"{repr(err)}" + ) + logging.info(u"Done.") -def plot_service_density_reconf_box_name(plot, input_data): - """Generate the plot(s) with algorithm: plot_service_density_reconf_box_name +def plot_lat_hdrh_percentile(plot, input_data): + """Generate the plot(s) with algorithm: plot_lat_hdrh_percentile specified in the specification file. :param plot: Plot to generate. @@ -72,87 +90,102 @@ def plot_service_density_reconf_box_name(plot, input_data): """ # Transform the data - plot_title = plot.get("title", "") - logging.info(" Creating the data set for the {0} '{1}'.". - format(plot.get("type", ""), plot_title)) + plot_title = plot.get(u"title", u"") + logging.info( + f" Creating the data set for the {plot.get(u'type', u'')} " + f"{plot_title}." + ) data = input_data.filter_tests_by_name( - plot, params=["result", "parent", "tags", "type"]) - if data is None: - logging.error("No data.") + plot, params=[u"latency", u"parent", u"tags", u"type"]) + if data is None or len(data[0][0]) == 0: + logging.error(u"No data.") return + fig = plgo.Figure() + # Prepare the data for the plot - y_vals = OrderedDict() - loss = dict() - for job in data: - for build in job: - for test in build: - if y_vals.get(test["parent"], None) is None: - y_vals[test["parent"]] = list() - loss[test["parent"]] = list() - try: - y_vals[test["parent"]].append(test["result"]["time"]) - loss[test["parent"]].append(test["result"]["loss"]) - except (KeyError, TypeError): - y_vals[test["parent"]].append(None) + directions = [u"W-E", u"E-W"] + for color, test in enumerate(data[0][0]): + try: + if test[u"type"] in (u"NDRPDR",): + if u"-pdr" in plot_title.lower(): + ttype = u"PDR" + elif u"-ndr" in plot_title.lower(): + ttype = u"NDR" + else: + logging.warning(f"Invalid test type: {test[u'type']}") + continue + name = re.sub(REGEX_NIC, u"", test[u"parent"]. + replace(u'-ndrpdr', u''). + replace(u'2n1l-', u'')) + for idx, direction in enumerate( + (u"direction1", u"direction2", )): + try: + hdr_lat = test[u"latency"][ttype][direction][u"hdrh"] + # TODO: Workaround, HDRH data must be aligned to 4 + # bytes, remove when not needed. + hdr_lat += u"=" * (len(hdr_lat) % 4) + xaxis = list() + yaxis = list() + hovertext = list() + decoded = hdrh.histogram.HdrHistogram.decode(hdr_lat) + for item in decoded.get_recorded_iterator(): + percentile = item.percentile_level_iterated_to + if percentile != 100.0: + xaxis.append(100.0 / (100.0 - percentile)) + yaxis.append(item.value_iterated_to) + hovertext.append( + f"Test: {name}<br>" + f"Direction: {directions[idx]}<br>" + f"Percentile: {percentile:.5f}%<br>" + f"Latency: {item.value_iterated_to}uSec" + ) + fig.add_trace( + plgo.Scatter( + x=xaxis, + y=yaxis, + name=name, + mode=u"lines", + legendgroup=name, + showlegend=bool(idx), + line=dict( + color=COLORS[color] + ), + hovertext=hovertext, + hoverinfo=u"text" + ) + ) + except hdrh.codec.HdrLengthException as err: + logging.warning( + f"No or invalid data for HDRHistogram for the test " + f"{name}\n{err}" + ) + continue + else: + logging.warning(f"Invalid test type: {test[u'type']}") + continue + except (ValueError, KeyError) as err: + logging.warning(repr(err)) - # 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))]) + layout = deepcopy(plot[u"layout"]) - # Add plot traces - traces = list() - df = pd.DataFrame(y_vals) - df.head() - for i, col in enumerate(df.columns): - tst_name = re.sub(REGEX_NIC, "", - col.lower().replace('-ndrpdr', ''). - replace('2n1l-', '')) - tst_name = "-".join(tst_name.split("-")[3:-2]) - name = "{nr}. ({samples:02d} run{plural}, packets lost average: " \ - "{loss:.1f}) {name}".format( - nr=(i + 1), - samples=nr_of_samples[i], - plural='s' if nr_of_samples[i] > 1 else '', - name=tst_name, - loss=mean(loss[col])) - - traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]), - y=[y if y else None for y in df[col]], - name=name, - hoverinfo="x+y", - boxpoints="outliers", - whiskerwidth=0)) - try: - # Create plot - layout = deepcopy(plot["layout"]) - layout["title"] = "<b>Time Lost:</b> {0}".format(layout["title"]) - layout["yaxis"]["title"] = "<b>Implied Time Lost [s]</b>" - layout["legend"]["font"]["size"] = 14 - layout["yaxis"].pop("range") - plpl = plgo.Figure(data=traces, layout=layout) + layout[u"title"][u"text"] = \ + f"<b>Latency:</b> {plot.get(u'graph-title', u'')}" + fig[u"layout"].update(layout) + # Create plot + file_type = plot.get(u"output-file-type", u".html") + logging.info(f" Writing file {plot[u'output-file']}{file_type}.") + try: # Export Plot - file_type = plot.get("output-file-type", ".html") - logging.info(" Writing file '{0}{1}'.". - format(plot["output-file"], file_type)) - ploff.plot(plpl, show_link=False, auto_open=False, - filename='{0}{1}'.format(plot["output-file"], file_type)) + ploff.plot(fig, show_link=False, auto_open=False, + filename=f"{plot[u'output-file']}{file_type}") except PlotlyError as err: - logging.error(" Finished with error: {}". - format(repr(err).replace("\n", " "))) - return + logging.error(f" Finished with error: {repr(err)}") -def plot_performance_box_name(plot, input_data): - """Generate the plot(s) with algorithm: plot_performance_box_name +def plot_hdrh_lat_by_percentile(plot, input_data): + """Generate the plot(s) with algorithm: plot_hdrh_lat_by_percentile specified in the specification file. :param plot: Plot to generate. @@ -162,105 +195,149 @@ def plot_performance_box_name(plot, input_data): """ # Transform the data - plot_title = plot.get("title", "") - logging.info(" Creating the data set for the {0} '{1}'.". - format(plot.get("type", ""), plot_title)) - data = input_data.filter_tests_by_name( - plot, params=["throughput", "parent", "tags", "type"]) - if data is None: - logging.error("No data.") + logging.info( + f" Creating the data set for the {plot.get(u'type', u'')} " + f"{plot.get(u'title', u'')}." + ) + if plot.get(u"include", None): + data = input_data.filter_tests_by_name( + plot, + params=[u"name", u"latency", u"parent", u"tags", u"type"] + )[0][0] + elif plot.get(u"filter", None): + data = input_data.filter_data( + plot, + params=[u"name", u"latency", u"parent", u"tags", u"type"], + continue_on_error=True + )[0][0] + else: + job = list(plot[u"data"].keys())[0] + build = str(plot[u"data"][job][0]) + data = input_data.tests(job, build) + + if data is None or len(data) == 0: + logging.error(u"No data.") return - # Prepare the data for the plot - y_vals = OrderedDict() - for job in data: - for build in job: - for test in build: - if y_vals.get(test["parent"], None) is None: - y_vals[test["parent"]] = list() - try: - if test["type"] in ("NDRPDR", ): - if "-pdr" in plot_title.lower(): - y_vals[test["parent"]].\ - append(test["throughput"]["PDR"]["LOWER"]) - elif "-ndr" in plot_title.lower(): - y_vals[test["parent"]]. \ - append(test["throughput"]["NDR"]["LOWER"]) - else: - continue - elif test["type"] in ("SOAK", ): - y_vals[test["parent"]].\ - append(test["throughput"]["LOWER"]) - else: - continue - except (KeyError, TypeError): - y_vals[test["parent"]].append(None) + desc = { + u"LAT0": u"No-load.", + u"PDR10": u"Low-load, 10% PDR.", + u"PDR50": u"Mid-load, 50% PDR.", + u"PDR90": u"High-load, 90% PDR.", + u"PDR": u"Full-load, 100% PDR.", + u"NDR10": u"Low-load, 10% NDR.", + u"NDR50": u"Mid-load, 50% NDR.", + u"NDR90": u"High-load, 90% NDR.", + u"NDR": u"Full-load, 100% NDR." + } + + graphs = [ + u"LAT0", + u"PDR10", + u"PDR50", + u"PDR90" + ] - # 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))]) + file_links = plot.get(u"output-file-links", None) + target_links = plot.get(u"target-links", None) - # Add plot traces - traces = list() - df = pd.DataFrame(y_vals) - df.head() - y_max = list() - for i, col in enumerate(df.columns): - tst_name = re.sub(REGEX_NIC, "", - col.lower().replace('-ndrpdr', ''). - replace('2n1l-', '')) - name = "{nr}. ({samples:02d} run{plural}) {name}".\ - format(nr=(i + 1), - samples=nr_of_samples[i], - plural='s' if nr_of_samples[i] > 1 else '', - name=tst_name) - - 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]], - name=name, - hoverinfo="x+y", - boxpoints="outliers", - whiskerwidth=0)) + for test in data: try: - val_max = max(df[col]) - except ValueError as err: - logging.error(repr(err)) - continue - if val_max: - y_max.append(int(val_max / 1000000) + 2) + if test[u"type"] not in (u"NDRPDR",): + logging.warning(f"Invalid test type: {test[u'type']}") + continue + name = re.sub(REGEX_NIC, u"", test[u"parent"]. + replace(u'-ndrpdr', u'').replace(u'2n1l-', u'')) + try: + nic = re.search(REGEX_NIC, test[u"parent"]).group(1) + except (IndexError, AttributeError, KeyError, ValueError): + nic = u"" + name_link = f"{nic}-{test[u'name']}".replace(u'-ndrpdr', u'') + + logging.info(f" Generating the graph: {name_link}") + + fig = plgo.Figure() + layout = deepcopy(plot[u"layout"]) + + for color, graph in enumerate(graphs): + for idx, direction in enumerate((u"direction1", u"direction2")): + xaxis = [0.0, ] + yaxis = [0.0, ] + hovertext = [ + f"<b>{desc[graph]}</b><br>" + f"Direction: {(u'W-E', u'E-W')[idx % 2]}<br>" + f"Percentile: 0.0%<br>" + f"Latency: 0.0uSec" + ] + decoded = hdrh.histogram.HdrHistogram.decode( + test[u"latency"][graph][direction][u"hdrh"] + ) + for item in decoded.get_recorded_iterator(): + percentile = item.percentile_level_iterated_to + if percentile > 99.9: + continue + xaxis.append(percentile) + yaxis.append(item.value_iterated_to) + hovertext.append( + f"<b>{desc[graph]}</b><br>" + f"Direction: {(u'W-E', u'E-W')[idx % 2]}<br>" + f"Percentile: {percentile:.5f}%<br>" + f"Latency: {item.value_iterated_to}uSec" + ) + fig.add_trace( + plgo.Scatter( + x=xaxis, + y=yaxis, + name=desc[graph], + mode=u"lines", + legendgroup=desc[graph], + showlegend=bool(idx), + line=dict( + color=COLORS[color], + dash=u"solid" if idx % 2 else u"dash" + ), + hovertext=hovertext, + hoverinfo=u"text" + ) + ) + + layout[u"title"][u"text"] = f"<b>Latency:</b> {name}" + fig.update_layout(layout) + + # Create plot + file_name = f"{plot[u'output-file']}-{name_link}.html" + logging.info(f" Writing file {file_name}") - try: - # Create plot - layout = deepcopy(plot["layout"]) - if layout.get("title", None): - layout["title"] = "<b>Throughput:</b> {0}". \ - format(layout["title"]) - if y_max: - layout["yaxis"]["range"] = [0, max(y_max)] - plpl = plgo.Figure(data=traces, layout=layout) + try: + # Export Plot + ploff.plot(fig, show_link=False, auto_open=False, + filename=file_name) + # Add link to the file: + if file_links and target_links: + with open(file_links, u"a") as file_handler: + file_handler.write( + f"- `{name_link} " + f"<{target_links}/{file_name.split(u'/')[-1]}>`_\n" + ) + except FileNotFoundError as err: + logging.error( + f"Not possible to write the link to the file " + f"{file_links}\n{err}" + ) + except PlotlyError as err: + logging.error(f" Finished with error: {repr(err)}") - # Export Plot - file_type = plot.get("output-file-type", ".html") - logging.info(" Writing file '{0}{1}'.". - format(plot["output-file"], file_type)) - ploff.plot(plpl, show_link=False, auto_open=False, - filename='{0}{1}'.format(plot["output-file"], file_type)) - except PlotlyError as err: - logging.error(" Finished with error: {}". - format(repr(err).replace("\n", " "))) - return + except hdrh.codec.HdrLengthException as err: + logging.warning(repr(err)) + continue + + except (ValueError, KeyError) as err: + logging.warning(repr(err)) + continue -def plot_latency_error_bars_name(plot, input_data): - """Generate the plot(s) with algorithm: plot_latency_error_bars_name +def plot_lat_hdrh_bar_name(plot, input_data): + """Generate the plot(s) with algorithm: plot_lat_hdrh_bar_name specified in the specification file. :param plot: Plot to generate. @@ -270,171 +347,173 @@ def plot_latency_error_bars_name(plot, input_data): """ # Transform the data - plot_title = plot.get("title", "") - logging.info(" Creating the data set for the {0} '{1}'.". - format(plot.get("type", ""), plot_title)) + plot_title = plot.get(u"title", u"") + logging.info( + f" Creating the data set for the {plot.get(u'type', u'')} " + f"{plot_title}." + ) data = input_data.filter_tests_by_name( - plot, params=["latency", "parent", "tags", "type"]) - if data is None: - logging.error("No data.") + plot, params=[u"latency", u"parent", u"tags", u"type"]) + if data is None or len(data[0][0]) == 0: + logging.error(u"No data.") return # Prepare the data for the plot - y_tmp_vals = OrderedDict() - for job in data: - for build in job: - for test in build: - try: - logging.debug("test['latency']: {0}\n". - format(test["latency"])) - except ValueError as err: - logging.warning(repr(err)) - if y_tmp_vals.get(test["parent"], None) is None: - y_tmp_vals[test["parent"]] = [ - list(), # direction1, min - list(), # direction1, avg - list(), # direction1, max - list(), # direction2, min - list(), # direction2, avg - list() # direction2, max - ] - try: - if test["type"] in ("NDRPDR", ): - if "-pdr" in plot_title.lower(): - ttype = "PDR" - elif "-ndr" in plot_title.lower(): - ttype = "NDR" - else: - logging.warning("Invalid test type: {0}". - format(test["type"])) - continue - y_tmp_vals[test["parent"]][0].append( - test["latency"][ttype]["direction1"]["min"]) - y_tmp_vals[test["parent"]][1].append( - test["latency"][ttype]["direction1"]["avg"]) - y_tmp_vals[test["parent"]][2].append( - test["latency"][ttype]["direction1"]["max"]) - y_tmp_vals[test["parent"]][3].append( - test["latency"][ttype]["direction2"]["min"]) - y_tmp_vals[test["parent"]][4].append( - test["latency"][ttype]["direction2"]["avg"]) - y_tmp_vals[test["parent"]][5].append( - test["latency"][ttype]["direction2"]["max"]) - else: - logging.warning("Invalid test type: {0}". - format(test["type"])) - continue - except (KeyError, TypeError) as err: - logging.warning(repr(err)) - - x_vals = list() - y_vals = list() - y_mins = list() - y_maxs = list() - nr_of_samples = list() - for key, val in y_tmp_vals.items(): - name = re.sub(REGEX_NIC, "", key.replace('-ndrpdr', ''). - replace('2n1l-', '')) - x_vals.append(name) # 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(name) # 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) - + directions = [u"W-E", u"E-W"] + tests = list() traces = list() - annotations = list() + for idx_row, test in enumerate(data[0][0]): + try: + if test[u"type"] in (u"NDRPDR",): + if u"-pdr" in plot_title.lower(): + ttype = u"PDR" + elif u"-ndr" in plot_title.lower(): + ttype = u"NDR" + else: + logging.warning(f"Invalid test type: {test[u'type']}") + continue + name = re.sub(REGEX_NIC, u"", test[u"parent"]. + replace(u'-ndrpdr', u''). + replace(u'2n1l-', u'')) + histograms = list() + for idx_col, direction in enumerate( + (u"direction1", u"direction2", )): + try: + hdr_lat = test[u"latency"][ttype][direction][u"hdrh"] + # TODO: Workaround, HDRH data must be aligned to 4 + # bytes, remove when not needed. + hdr_lat += u"=" * (len(hdr_lat) % 4) + xaxis = list() + yaxis = list() + hovertext = list() + decoded = hdrh.histogram.HdrHistogram.decode(hdr_lat) + total_count = decoded.get_total_count() + for item in decoded.get_recorded_iterator(): + xaxis.append(item.value_iterated_to) + prob = float(item.count_added_in_this_iter_step) / \ + total_count * 100 + yaxis.append(prob) + hovertext.append( + f"Test: {name}<br>" + f"Direction: {directions[idx_col]}<br>" + f"Latency: {item.value_iterated_to}uSec<br>" + f"Probability: {prob:.2f}%<br>" + f"Percentile: " + f"{item.percentile_level_iterated_to:.2f}" + ) + marker_color = [COLORS[idx_row], ] * len(yaxis) + marker_color[xaxis.index( + decoded.get_value_at_percentile(50.0))] = u"red" + marker_color[xaxis.index( + decoded.get_value_at_percentile(90.0))] = u"red" + marker_color[xaxis.index( + decoded.get_value_at_percentile(95.0))] = u"red" + histograms.append( + plgo.Bar( + x=xaxis, + y=yaxis, + showlegend=False, + name=name, + marker={u"color": marker_color}, + hovertext=hovertext, + hoverinfo=u"text" + ) + ) + except hdrh.codec.HdrLengthException as err: + logging.warning( + f"No or invalid data for HDRHistogram for the test " + f"{name}\n{err}" + ) + continue + if len(histograms) == 2: + traces.append(histograms) + tests.append(name) + else: + logging.warning(f"Invalid test type: {test[u'type']}") + continue + except (ValueError, KeyError) as err: + logging.warning(repr(err)) - for idx in range(len(x_vals)): - if not bool(int(idx % 2)): - direction = "West-East" - else: - direction = "East-West" - hovertext = ("No. of Runs: {nr}<br>" - "Test: {test}<br>" - "Direction: {dir}<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): - hovertext += "Mean: {avg:.2f}uSec<br>".format(avg=y_vals[idx]) - if isinstance(y_mins[idx], float): - hovertext += "Min: {min:.2f}uSec".format(min=y_mins[idx]) + if not tests: + logging.warning(f"No data for {plot_title}.") + return - if isinstance(y_maxs[idx], float) and isinstance(y_vals[idx], float): - array = [y_maxs[idx] - y_vals[idx], ] - else: - array = [None, ] - if isinstance(y_mins[idx], float) and isinstance(y_vals[idx], float): - arrayminus = [y_vals[idx] - y_mins[idx], ] - else: - arrayminus = [None, ] - traces.append(plgo.Scatter( - x=[idx, ], - y=[y_vals[idx], ], - name=x_vals[idx], - legendgroup=x_vals[idx], - showlegend=bool(int(idx % 2)), - mode="markers", - error_y=dict( - type='data', - symmetric=False, - array=array, - arrayminus=arrayminus, - color=COLORS[int(idx / 2)] - ), - marker=dict( - size=10, - color=COLORS[int(idx / 2)], - ), - text=hovertext, - hoverinfo="text", - )) - annotations.append(dict( - x=idx, - y=0, - xref="x", - yref="y", - xanchor="center", - yanchor="top", - text="E-W" if bool(int(idx % 2)) else "W-E", - font=dict( - size=16, - ), - align="center", - showarrow=False - )) + fig = make_subplots( + rows=len(tests), + cols=2, + specs=[ + [{u"type": u"bar"}, {u"type": u"bar"}] for _ in range(len(tests)) + ] + ) + + layout_axes = dict( + gridcolor=u"rgb(220, 220, 220)", + linecolor=u"rgb(220, 220, 220)", + linewidth=1, + showgrid=True, + showline=True, + showticklabels=True, + tickcolor=u"rgb(220, 220, 220)", + ) + + for idx_row, test in enumerate(tests): + for idx_col in range(2): + fig.add_trace( + traces[idx_row][idx_col], + row=idx_row + 1, + col=idx_col + 1 + ) + fig.update_xaxes( + row=idx_row + 1, + col=idx_col + 1, + **layout_axes + ) + fig.update_yaxes( + row=idx_row + 1, + col=idx_col + 1, + **layout_axes + ) + layout = deepcopy(plot[u"layout"]) + + layout[u"title"][u"text"] = \ + f"<b>Latency:</b> {plot.get(u'graph-title', u'')}" + layout[u"height"] = 250 * len(tests) + 130 + + layout[u"annotations"][2][u"y"] = 1.06 - 0.008 * len(tests) + layout[u"annotations"][3][u"y"] = 1.06 - 0.008 * len(tests) + + for idx, test in enumerate(tests): + layout[u"annotations"].append({ + u"font": { + u"size": 14 + }, + u"showarrow": False, + u"text": f"<b>{test}</b>", + u"textangle": 0, + u"x": 0.5, + u"xanchor": u"center", + u"xref": u"paper", + u"y": 1.0 - float(idx) * 1.06 / len(tests), + u"yanchor": u"bottom", + u"yref": u"paper" + }) + + fig[u"layout"].update(layout) + + # Create plot + file_type = plot.get(u"output-file-type", u".html") + logging.info(f" Writing file {plot[u'output-file']}{file_type}.") try: - # Create plot - file_type = plot.get("output-file-type", ".html") - logging.info(" Writing file '{0}{1}'.". - format(plot["output-file"], file_type)) - layout = deepcopy(plot["layout"]) - if layout.get("title", None): - layout["title"] = "<b>Latency:</b> {0}".\ - format(layout["title"]) - layout["annotations"] = annotations - plpl = plgo.Figure(data=traces, layout=layout) - # Export Plot - ploff.plot(plpl, - show_link=False, auto_open=False, - filename='{0}{1}'.format(plot["output-file"], file_type)) + ploff.plot(fig, show_link=False, auto_open=False, + filename=f"{plot[u'output-file']}{file_type}") except PlotlyError as err: - logging.error(" Finished with error: {}". - format(str(err).replace("\n", " "))) - return + logging.error(f" Finished with error: {repr(err)}") -def plot_throughput_speedup_analysis_name(plot, input_data): - """Generate the plot(s) with algorithm: - plot_throughput_speedup_analysis_name +def plot_nf_reconf_box_name(plot, input_data): + """Generate the plot(s) with algorithm: plot_nf_reconf_box_name specified in the specification file. :param plot: Plot to generate. @@ -444,319 +523,93 @@ def plot_throughput_speedup_analysis_name(plot, input_data): """ # Transform the data - plot_title = plot.get("title", "") - logging.info(" Creating the data set for the {0} '{1}'.". - format(plot.get("type", ""), plot_title)) + logging.info( + f" Creating the data set for the {plot.get(u'type', u'')} " + f"{plot.get(u'title', u'')}." + ) data = input_data.filter_tests_by_name( - plot, params=["throughput", "parent", "tags", "type"]) + plot, params=[u"result", u"parent", u"tags", u"type"] + ) if data is None: - logging.error("No data.") + logging.error(u"No data.") return + # Prepare the data for the plot y_vals = OrderedDict() + loss = dict() for job in data: for build in job: for test in build: - if y_vals.get(test["parent"], None) is None: - y_vals[test["parent"]] = {"1": list(), - "2": list(), - "4": list()} + if y_vals.get(test[u"parent"], None) is None: + y_vals[test[u"parent"]] = list() + loss[test[u"parent"]] = list() try: - if test["type"] in ("NDRPDR",): - if "-pdr" in plot_title.lower(): - ttype = "PDR" - elif "-ndr" in plot_title.lower(): - ttype = "NDR" - else: - continue - if "1C" in test["tags"]: - y_vals[test["parent"]]["1"]. \ - append(test["throughput"][ttype]["LOWER"]) - elif "2C" in test["tags"]: - y_vals[test["parent"]]["2"]. \ - append(test["throughput"][ttype]["LOWER"]) - elif "4C" in test["tags"]: - y_vals[test["parent"]]["4"]. \ - append(test["throughput"][ttype]["LOWER"]) + y_vals[test[u"parent"]].append(test[u"result"][u"time"]) + loss[test[u"parent"]].append(test[u"result"][u"loss"]) except (KeyError, TypeError): - pass - - if not y_vals: - logging.warning("No data for the plot '{}'". - format(plot.get("title", ""))) - return - - y_1c_max = dict() - for test_name, test_vals in y_vals.items(): - 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, 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 - - vals = OrderedDict() - y_max = list() - nic_limit = 0 - lnk_limit = 0 - pci_limit = plot["limits"]["pci"]["pci-g3-x8"] - for test_name, test_vals in y_vals.items(): - try: - if test_vals["1"][1]: - name = re.sub(REGEX_NIC, "", test_name.replace('-ndrpdr', ''). - replace('2n1l-', '')) - vals[name] = OrderedDict() - 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]] + y_vals[test[u"parent"]].append(None) - try: - val_max = max(vals[name]["val"]) - except ValueError as err: - logging.error(repr(err)) - continue - if val_max: - y_max.append(val_max) - - 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: - limit = plot["limits"]["nic"]["x520"] - elif "x710" in test_name: - limit = plot["limits"]["nic"]["x710"] - elif "xxv710" in test_name: - limit = plot["limits"]["nic"]["xxv710"] - elif "xl710" in test_name: - limit = plot["limits"]["nic"]["xl710"] - elif "x553" in test_name: - limit = plot["limits"]["nic"]["x553"] - else: - limit = 0 - if limit > nic_limit: - nic_limit = limit - - mul = 2 if "ge2p" in test_name else 1 - if "10ge" in test_name: - limit = plot["limits"]["link"]["10ge"] * mul - elif "25ge" in test_name: - limit = plot["limits"]["link"]["25ge"] * mul - elif "40ge" in test_name: - limit = plot["limits"]["link"]["40ge"] * mul - elif "100ge" in test_name: - limit = plot["limits"]["link"]["100ge"] * mul - else: - limit = 0 - if limit > lnk_limit: - lnk_limit = limit + # 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 val in y_vals.values(): + if len(val) < max_len: + val.extend([None for _ in range(max_len - len(val))]) + # Add plot traces traces = list() - annotations = list() - x_vals = [1, 2, 4] - - # Limits: - try: - threshold = 1.1 * max(y_max) # 10% - except ValueError as err: - logging.error(err) - return - nic_limit /= 1000000.0 - traces.append(plgo.Scatter( - x=x_vals, - y=[nic_limit, ] * len(x_vals), - name="NIC: {0:.2f}Mpps".format(nic_limit), - showlegend=False, - mode="lines", - line=dict( - dash="dot", - color=COLORS[-1], - width=1), - hoverinfo="none" - )) - annotations.append(dict( - x=1, - y=nic_limit, - xref="x", - yref="y", - xanchor="left", - yanchor="bottom", - text="NIC: {0:.2f}Mpps".format(nic_limit), - font=dict( - size=14, - color=COLORS[-1], - ), - align="left", - showarrow=False - )) - y_max.append(nic_limit) - - lnk_limit /= 1000000.0 - if lnk_limit < threshold: - traces.append(plgo.Scatter( - x=x_vals, - y=[lnk_limit, ] * len(x_vals), - name="Link: {0:.2f}Mpps".format(lnk_limit), - showlegend=False, - mode="lines", - line=dict( - dash="dot", - color=COLORS[-2], - width=1), - hoverinfo="none" - )) - annotations.append(dict( - x=1, - y=lnk_limit, - xref="x", - yref="y", - xanchor="left", - yanchor="bottom", - text="Link: {0:.2f}Mpps".format(lnk_limit), - font=dict( - size=14, - color=COLORS[-2], + 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'')) + + 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]], + 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])}" ), - align="left", - showarrow=False + hoverinfo=u"y+name" )) - y_max.append(lnk_limit) - - pci_limit /= 1000000.0 - if (pci_limit < threshold and - (pci_limit < lnk_limit * 0.95 or lnk_limit > lnk_limit * 1.05)): - traces.append(plgo.Scatter( - x=x_vals, - y=[pci_limit, ] * len(x_vals), - name="PCIe: {0:.2f}Mpps".format(pci_limit), - showlegend=False, - mode="lines", - line=dict( - dash="dot", - color=COLORS[-3], - width=1), - hoverinfo="none" - )) - annotations.append(dict( - x=1, - y=pci_limit, - xref="x", - yref="y", - xanchor="left", - yanchor="bottom", - text="PCIe: {0:.2f}Mpps".format(pci_limit), - font=dict( - size=14, - color=COLORS[-3], - ), - align="left", - showarrow=False - )) - y_max.append(pci_limit) - - # Perfect and measured: - cidx = 0 - for name, val in vals.iteritems(): - hovertext = list() - try: - for idx in range(len(val["val"])): - htext = "" - if isinstance(val["val"][idx], float): - htext += "No. of Runs: {1}<br>" \ - "Mean: {0:.2f}Mpps<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 - file_type = plot.get("output-file-type", ".html") - logging.info(" Writing file '{0}{1}'.". - format(plot["output-file"], file_type)) - layout = deepcopy(plot["layout"]) - if layout.get("title", None): - layout["title"] = "<b>Speedup Multi-core:</b> {0}". \ - format(layout["title"]) - layout["yaxis"]["range"] = [0, int(max(y_max) * 1.1)] - layout["annotations"].extend(annotations) + layout = deepcopy(plot[u"layout"]) + layout[u"title"] = f"<b>Time Lost:</b> {layout[u'title']}" + layout[u"yaxis"][u"title"] = u"<b>Implied Time Lost [s]</b>" + layout[u"legend"][u"font"][u"size"] = 14 + layout[u"yaxis"].pop(u"range") plpl = plgo.Figure(data=traces, layout=layout) # Export Plot - ploff.plot(plpl, - show_link=False, auto_open=False, - filename='{0}{1}'.format(plot["output-file"], file_type)) + file_type = plot.get(u"output-file-type", u".html") + logging.info(f" Writing file {plot[u'output-file']}{file_type}.") + ploff.plot( + plpl, + show_link=False, + auto_open=False, + filename=f"{plot[u'output-file']}{file_type}" + ) except PlotlyError as err: - logging.error(" Finished with error: {}". - format(repr(err).replace("\n", " "))) + logging.error( + f" Finished with error: {repr(err)}".replace(u"\n", u" ") + ) return -def plot_performance_box(plot, input_data): - """Generate the plot(s) with algorithm: plot_performance_box +def plot_perf_box_name(plot, input_data): + """Generate the plot(s) with algorithm: plot_perf_box_name specified in the specification file. - TODO: Remove when not needed. - :param plot: Plot to generate. :param input_data: Data to process. :type plot: pandas.Series @@ -764,375 +617,133 @@ def plot_performance_box(plot, input_data): """ # Transform the data - plot_title = plot.get("title", "") - logging.info(" Creating the data set for the {0} '{1}'.". - format(plot.get("type", ""), plot_title)) - data = input_data.filter_data(plot) + logging.info( + f" Creating data set for the {plot.get(u'type', u'')} " + f"{plot.get(u'title', u'')}." + ) + data = input_data.filter_tests_by_name( + plot, params=[u"throughput", u"result", u"parent", u"tags", u"type"]) if data is None: - logging.error("No data.") + logging.error(u"No data.") return # Prepare the data for the plot - y_vals = dict() - y_tags = dict() + y_vals = OrderedDict() + test_type = u"" for job in data: for build in job: for test in build: - if y_vals.get(test["parent"], None) is None: - y_vals[test["parent"]] = list() - y_tags[test["parent"]] = test.get("tags", None) + if y_vals.get(test[u"parent"], None) is None: + y_vals[test[u"parent"]] = list() try: - if test["type"] in ("NDRPDR", ): - if "-pdr" in plot_title.lower(): - y_vals[test["parent"]].\ - append(test["throughput"]["PDR"]["LOWER"]) - elif "-ndr" in plot_title.lower(): - y_vals[test["parent"]]. \ - append(test["throughput"]["NDR"]["LOWER"]) - else: - continue - elif test["type"] in ("SOAK", ): - y_vals[test["parent"]].\ - append(test["throughput"]["LOWER"]) + if (test[u"type"] in (u"NDRPDR", ) and + u"-pdr" in plot.get(u"title", u"").lower()): + y_vals[test[u"parent"]].\ + append(test[u"throughput"][u"PDR"][u"LOWER"]) + test_type = u"NDRPDR" + elif (test[u"type"] in (u"NDRPDR", ) and + u"-ndr" in plot.get(u"title", u"").lower()): + y_vals[test[u"parent"]]. \ + append(test[u"throughput"][u"NDR"][u"LOWER"]) + test_type = u"NDRPDR" + elif test[u"type"] in (u"SOAK", ): + y_vals[test[u"parent"]].\ + append(test[u"throughput"][u"LOWER"]) + test_type = u"SOAK" + elif test[u"type"] in (u"HOSTSTACK", ): + if u"LDPRELOAD" in test[u"tags"]: + y_vals[test[u"parent"]].append( + float(test[u"result"][u"bits_per_second"]) / 1e3 + ) + elif u"VPPECHO" in test[u"tags"]: + y_vals[test[u"parent"]].append( + (float(test[u"result"][u"client"][u"tx_data"]) + * 8 / 1e3) / + ((float(test[u"result"][u"client"][u"time"]) + + float(test[u"result"][u"server"][u"time"])) / + 2) + ) + test_type = u"HOSTSTACK" else: continue except (KeyError, TypeError): - y_vals[test["parent"]].append(None) - - # Sort the tests - order = plot.get("sort", None) - if order and y_tags: - y_sorted = OrderedDict() - y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()} - for tag in order: - logging.debug(tag) - for suite, tags in y_tags_l.items(): - if "not " in tag: - tag = tag.split(" ")[-1] - if tag.lower() in tags: - continue - else: - if tag.lower() not in tags: - continue - try: - y_sorted[suite] = y_vals.pop(suite) - y_tags_l.pop(suite) - logging.debug(suite) - except KeyError as err: - logging.error("Not found: {0}".format(repr(err))) - finally: - break - else: - y_sorted = y_vals + y_vals[test[u"parent"]].append(None) # Add None to the lists with missing data max_len = 0 nr_of_samples = list() - for val in y_sorted.values(): + 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_sorted.items(): + for val in y_vals.values(): if len(val) < max_len: val.extend([None for _ in range(max_len - len(val))]) # Add plot traces traces = list() - df = pd.DataFrame(y_sorted) - df.head() + df_y = pd.DataFrame(y_vals) + df_y.head() y_max = list() - for i, col in enumerate(df.columns): - tst_name = re.sub(REGEX_NIC, "", - col.lower().replace('-ndrpdr', ''). - replace('2n1l-', '')) - name = "{nr}. ({samples:02d} run{plural}) {name}".\ - format(nr=(i + 1), - samples=nr_of_samples[i], - plural='s' if nr_of_samples[i] > 1 else '', - name=tst_name) - - 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]], - name=name, - **plot["traces"])) + 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'')) + kwargs = dict( + x=[str(i + 1) + u'.'] * len(df_y[col]), + y=[y / 1e6 if y else None for y in 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"{tst_name}" + ), + hoverinfo=u"y+name" + ) + if test_type in (u"SOAK", ): + kwargs[u"boxpoints"] = u"all" + + traces.append(plgo.Box(**kwargs)) + try: - val_max = max(df[col]) - except ValueError as err: + val_max = max(df_y[col]) + if val_max: + y_max.append(int(val_max / 1e6) + 2) + except (ValueError, TypeError) as err: logging.error(repr(err)) continue - if val_max: - y_max.append(int(val_max / 1000000) + 2) try: # Create plot - layout = deepcopy(plot["layout"]) - if layout.get("title", None): - layout["title"] = "<b>Throughput:</b> {0}". \ - format(layout["title"]) + layout = deepcopy(plot[u"layout"]) + if layout.get(u"title", None): + if test_type in (u"HOSTSTACK", ): + layout[u"title"] = f"<b>Bandwidth:</b> {layout[u'title']}" + else: + layout[u"title"] = f"<b>Throughput:</b> {layout[u'title']}" if y_max: - layout["yaxis"]["range"] = [0, max(y_max)] + layout[u"yaxis"][u"range"] = [0, max(y_max)] plpl = plgo.Figure(data=traces, layout=layout) # Export Plot - logging.info(" Writing file '{0}{1}'.". - format(plot["output-file"], plot["output-file-type"])) - ploff.plot(plpl, show_link=False, auto_open=False, - filename='{0}{1}'.format(plot["output-file"], - plot["output-file-type"])) - except PlotlyError as err: - logging.error(" Finished with error: {}". - format(repr(err).replace("\n", " "))) - return - - -def plot_soak_bars(plot, input_data): - """Generate the plot(s) with algorithm: plot_soak_bars - specified in the specification file. - - :param plot: Plot to generate. - :param input_data: Data to process. - :type plot: pandas.Series - :type input_data: InputData - """ - - # Transform the data - plot_title = plot.get("title", "") - logging.info(" Creating the data set for the {0} '{1}'.". - format(plot.get("type", ""), plot_title)) - data = input_data.filter_data(plot) - if data is None: - logging.error("No data.") - return - - # Prepare the data for the plot - y_vals = dict() - y_tags = dict() - for job in data: - for build in job: - for test in build: - if y_vals.get(test["parent"], None) is None: - y_tags[test["parent"]] = test.get("tags", None) - try: - if test["type"] in ("SOAK", ): - y_vals[test["parent"]] = test["throughput"] - else: - continue - except (KeyError, TypeError): - y_vals[test["parent"]] = dict() - - # Sort the tests - order = plot.get("sort", None) - if order and y_tags: - y_sorted = OrderedDict() - y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()} - for tag in order: - logging.debug(tag) - for suite, tags in y_tags_l.items(): - if "not " in tag: - tag = tag.split(" ")[-1] - if tag.lower() in tags: - continue - else: - if tag.lower() not in tags: - continue - try: - y_sorted[suite] = y_vals.pop(suite) - y_tags_l.pop(suite) - logging.debug(suite) - except KeyError as err: - logging.error("Not found: {0}".format(repr(err))) - finally: - break - else: - y_sorted = y_vals - - idx = 0 - y_max = 0 - traces = list() - for test_name, test_data in y_sorted.items(): - idx += 1 - name = "{nr}. {name}".\ - format(nr=idx, name=test_name.lower().replace('-soak', '')) - if len(name) > 50: - name_lst = name.split('-') - name = "" - split_name = True - for segment in name_lst: - if (len(name) + len(segment) + 1) > 50 and split_name: - name += "<br> " - split_name = False - name += segment + '-' - name = name[:-1] - - y_val = test_data.get("LOWER", None) - if y_val: - y_val /= 1000000 - if y_val > y_max: - y_max = y_val - - time = "No Information" - result = "No Information" - hovertext = ("{name}<br>" - "Packet Throughput: {val:.2f}Mpps<br>" - "Final Duration: {time}<br>" - "Result: {result}".format(name=name, - val=y_val, - time=time, - result=result)) - traces.append(plgo.Bar(x=[str(idx) + '.', ], - y=[y_val, ], - name=name, - text=hovertext, - hoverinfo="text")) - try: - # Create plot - layout = deepcopy(plot["layout"]) - if layout.get("title", None): - layout["title"] = "<b>Packet Throughput:</b> {0}". \ - format(layout["title"]) - if y_max: - layout["yaxis"]["range"] = [0, y_max + 1] - plpl = plgo.Figure(data=traces, layout=layout) - # Export Plot - logging.info(" Writing file '{0}{1}'.". - format(plot["output-file"], plot["output-file-type"])) - ploff.plot(plpl, show_link=False, auto_open=False, - filename='{0}{1}'.format(plot["output-file"], - plot["output-file-type"])) - except PlotlyError as err: - logging.error(" Finished with error: {}". - format(repr(err).replace("\n", " "))) - return - - -def plot_soak_boxes(plot, input_data): - """Generate the plot(s) with algorithm: plot_soak_boxes - specified in the specification file. - - :param plot: Plot to generate. - :param input_data: Data to process. - :type plot: pandas.Series - :type input_data: InputData - """ - - # Transform the data - plot_title = plot.get("title", "") - logging.info(" Creating the data set for the {0} '{1}'.". - format(plot.get("type", ""), plot_title)) - data = input_data.filter_data(plot) - if data is None: - logging.error("No data.") - return - - # Prepare the data for the plot - y_vals = dict() - y_tags = dict() - for job in data: - for build in job: - for test in build: - if y_vals.get(test["parent"], None) is None: - y_tags[test["parent"]] = test.get("tags", None) - try: - if test["type"] in ("SOAK", ): - y_vals[test["parent"]] = test["throughput"] - else: - continue - except (KeyError, TypeError): - y_vals[test["parent"]] = dict() - - # Sort the tests - order = plot.get("sort", None) - if order and y_tags: - y_sorted = OrderedDict() - y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()} - for tag in order: - logging.debug(tag) - for suite, tags in y_tags_l.items(): - if "not " in tag: - tag = tag.split(" ")[-1] - if tag.lower() in tags: - continue - else: - if tag.lower() not in tags: - continue - try: - y_sorted[suite] = y_vals.pop(suite) - y_tags_l.pop(suite) - logging.debug(suite) - except KeyError as err: - logging.error("Not found: {0}".format(repr(err))) - finally: - break - else: - y_sorted = y_vals - - idx = 0 - y_max = 0 - traces = list() - for test_name, test_data in y_sorted.items(): - idx += 1 - name = "{nr}. {name}".\ - format(nr=idx, name=test_name.lower().replace('-soak', ''). - replace('2n1l-', '')) - if len(name) > 55: - name_lst = name.split('-') - name = "" - split_name = True - for segment in name_lst: - if (len(name) + len(segment) + 1) > 55 and split_name: - name += "<br> " - split_name = False - name += segment + '-' - name = name[:-1] - - y_val = test_data.get("UPPER", None) - if y_val: - y_val /= 1000000 - if y_val > y_max: - y_max = y_val - - y_base = test_data.get("LOWER", None) - if y_base: - y_base /= 1000000 - - hovertext = ("Upper bound: {upper:.2f}<br>" - "Lower bound: {lower:.2f}".format(upper=y_val, - lower=y_base)) - traces.append(plgo.Bar(x=[str(idx) + '.', ], - # +0.05 to see the value in case lower == upper - y=[y_val - y_base + 0.05, ], - base=y_base, - name=name, - text=hovertext, - hoverinfo="text")) - try: - # Create plot - layout = deepcopy(plot["layout"]) - if layout.get("title", None): - layout["title"] = "<b>Throughput:</b> {0}". \ - format(layout["title"]) - if y_max: - layout["yaxis"]["range"] = [0, y_max + 1] - plpl = plgo.Figure(data=traces, layout=layout) - # Export Plot - logging.info(" Writing file '{0}{1}'.". - format(plot["output-file"], plot["output-file-type"])) - ploff.plot(plpl, show_link=False, auto_open=False, - filename='{0}{1}'.format(plot["output-file"], - plot["output-file-type"])) + logging.info(f" Writing file {plot[u'output-file']}.html.") + ploff.plot( + plpl, + show_link=False, + auto_open=False, + filename=f"{plot[u'output-file']}.html" + ) except PlotlyError as err: - logging.error(" Finished with error: {}". - format(repr(err).replace("\n", " "))) + logging.error( + f" Finished with error: {repr(err)}".replace(u"\n", u" ") + ) return -def plot_latency_error_bars(plot, input_data): - """Generate the plot(s) with algorithm: plot_latency_error_bars +def plot_lat_err_bars_name(plot, input_data): + """Generate the plot(s) with algorithm: plot_lat_err_bars_name specified in the specification file. - TODO: Remove when not needed. - :param plot: Plot to generate. :param input_data: Data to process. :type plot: pandas.Series @@ -1140,27 +751,27 @@ def plot_latency_error_bars(plot, input_data): """ # Transform the data - plot_title = plot.get("title", "") - logging.info(" Creating the data set for the {0} '{1}'.". - format(plot.get("type", ""), plot_title)) - data = input_data.filter_data(plot) + plot_title = plot.get(u"title", u"") + logging.info( + f" Creating data set for the {plot.get(u'type', u'')} {plot_title}." + ) + data = input_data.filter_tests_by_name( + plot, params=[u"latency", u"parent", u"tags", u"type"]) if data is None: - logging.error("No data.") + logging.error(u"No data.") return # Prepare the data for the plot - y_tmp_vals = dict() - y_tags = dict() + y_tmp_vals = OrderedDict() for job in data: for build in job: for test in build: try: - logging.debug("test['latency']: {0}\n". - format(test["latency"])) + logging.debug(f"test[u'latency']: {test[u'latency']}\n") except ValueError as err: logging.warning(repr(err)) - if y_tmp_vals.get(test["parent"], None) is None: - y_tmp_vals[test["parent"]] = [ + if y_tmp_vals.get(test[u"parent"], None) is None: + y_tmp_vals[test[u"parent"]] = [ list(), # direction1, min list(), # direction1, avg list(), # direction1, max @@ -1168,72 +779,42 @@ def plot_latency_error_bars(plot, input_data): list(), # direction2, avg list() # direction2, max ] - y_tags[test["parent"]] = test.get("tags", None) try: - if test["type"] in ("NDRPDR", ): - if "-pdr" in plot_title.lower(): - ttype = "PDR" - elif "-ndr" in plot_title.lower(): - ttype = "NDR" - else: - logging.warning("Invalid test type: {0}". - format(test["type"])) - continue - y_tmp_vals[test["parent"]][0].append( - test["latency"][ttype]["direction1"]["min"]) - y_tmp_vals[test["parent"]][1].append( - test["latency"][ttype]["direction1"]["avg"]) - y_tmp_vals[test["parent"]][2].append( - test["latency"][ttype]["direction1"]["max"]) - y_tmp_vals[test["parent"]][3].append( - test["latency"][ttype]["direction2"]["min"]) - y_tmp_vals[test["parent"]][4].append( - test["latency"][ttype]["direction2"]["avg"]) - y_tmp_vals[test["parent"]][5].append( - test["latency"][ttype]["direction2"]["max"]) + if test[u"type"] not in (u"NDRPDR", ): + logging.warning(f"Invalid test type: {test[u'type']}") + continue + if u"-pdr" in plot_title.lower(): + ttype = u"PDR" + elif u"-ndr" in plot_title.lower(): + ttype = u"NDR" else: - logging.warning("Invalid test type: {0}". - format(test["type"])) + logging.warning( + f"Invalid test type: {test[u'type']}" + ) continue + y_tmp_vals[test[u"parent"]][0].append( + test[u"latency"][ttype][u"direction1"][u"min"]) + y_tmp_vals[test[u"parent"]][1].append( + test[u"latency"][ttype][u"direction1"][u"avg"]) + y_tmp_vals[test[u"parent"]][2].append( + test[u"latency"][ttype][u"direction1"][u"max"]) + y_tmp_vals[test[u"parent"]][3].append( + test[u"latency"][ttype][u"direction2"][u"min"]) + y_tmp_vals[test[u"parent"]][4].append( + test[u"latency"][ttype][u"direction2"][u"avg"]) + y_tmp_vals[test[u"parent"]][5].append( + test[u"latency"][ttype][u"direction2"][u"max"]) 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: - y_sorted = OrderedDict() - y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()} - for tag in order: - logging.debug(tag) - for suite, tags in y_tags_l.items(): - if "not " in tag: - tag = tag.split(" ")[-1] - if tag.lower() in tags: - continue - else: - if tag.lower() not in tags: - continue - try: - y_sorted[suite] = y_tmp_vals.pop(suite) - y_tags_l.pop(suite) - logging.debug(suite) - except KeyError as err: - logging.error("Not found: {0}".format(repr(err))) - finally: - break - else: - y_sorted = y_tmp_vals - logging.debug("y_sorted: {0}\n".format(y_sorted)) x_vals = list() y_vals = list() y_mins = list() y_maxs = list() nr_of_samples = list() - for key, val in y_sorted.items(): - name = re.sub(REGEX_NIC, "", key.replace('-ndrpdr', ''). - replace('2n1l-', '')) + for key, val in y_tmp_vals.items(): + name = re.sub(REGEX_NIC, u"", key.replace(u'-ndrpdr', u''). + replace(u'2n1l-', u'')) x_vals.append(name) # dir 1 y_vals.append(mean(val[1]) if val[1] else None) y_mins.append(mean(val[0]) if val[0] else None) @@ -1245,30 +826,25 @@ def plot_latency_error_bars(plot, input_data): 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() - for idx in range(len(x_vals)): + for idx, _ in enumerate(x_vals): if not bool(int(idx % 2)): - direction = "West-East" + direction = u"West-East" else: - direction = "East-West" - hovertext = ("No. of Runs: {nr}<br>" - "Test: {test}<br>" - "Direction: {dir}<br>".format(test=x_vals[idx], - dir=direction, - nr=nr_of_samples[idx])) + direction = u"East-West" + hovertext = ( + f"No. of Runs: {nr_of_samples[idx]}<br>" + f"Test: {x_vals[idx]}<br>" + f"Direction: {direction}<br>" + ) if isinstance(y_maxs[idx], float): - hovertext += "Max: {max:.2f}uSec<br>".format(max=y_maxs[idx]) + hovertext += f"Max: {y_maxs[idx]:.2f}uSec<br>" if isinstance(y_vals[idx], float): - hovertext += "Mean: {avg:.2f}uSec<br>".format(avg=y_vals[idx]) + hovertext += f"Mean: {y_vals[idx]:.2f}uSec<br>" if isinstance(y_mins[idx], float): - hovertext += "Min: {min:.2f}uSec".format(min=y_mins[idx]) + hovertext += f"Min: {y_mins[idx]:.2f}uSec" if isinstance(y_maxs[idx], float) and isinstance(y_vals[idx], float): array = [y_maxs[idx] - y_vals[idx], ] @@ -1278,18 +854,15 @@ def plot_latency_error_bars(plot, input_data): arrayminus = [y_vals[idx] - y_mins[idx], ] else: arrayminus = [None, ] - logging.debug("y_vals[{1}] :{0}\n".format(y_vals[idx], idx)) - logging.debug("array :{0}\n".format(array)) - logging.debug("arrayminus :{0}\n".format(arrayminus)) traces.append(plgo.Scatter( x=[idx, ], y=[y_vals[idx], ], name=x_vals[idx], legendgroup=x_vals[idx], showlegend=bool(int(idx % 2)), - mode="markers", + mode=u"markers", error_y=dict( - type='data', + type=u"data", symmetric=False, array=array, arrayminus=arrayminus, @@ -1300,52 +873,51 @@ def plot_latency_error_bars(plot, input_data): color=COLORS[int(idx / 2)], ), text=hovertext, - hoverinfo="text", + hoverinfo=u"text", )) annotations.append(dict( x=idx, y=0, - xref="x", - yref="y", - xanchor="center", - yanchor="top", - text="E-W" if bool(int(idx % 2)) else "W-E", + xref=u"x", + yref=u"y", + xanchor=u"center", + yanchor=u"top", + text=u"E-W" if bool(int(idx % 2)) else u"W-E", font=dict( size=16, ), - align="center", + align=u"center", showarrow=False )) try: # Create plot - logging.info(" Writing file '{0}{1}'.". - format(plot["output-file"], plot["output-file-type"])) - layout = deepcopy(plot["layout"]) - if layout.get("title", None): - layout["title"] = "<b>Latency:</b> {0}".\ - format(layout["title"]) - layout["annotations"] = annotations + file_type = plot.get(u"output-file-type", u".html") + logging.info(f" Writing file {plot[u'output-file']}{file_type}.") + layout = deepcopy(plot[u"layout"]) + if layout.get(u"title", None): + layout[u"title"] = f"<b>Latency:</b> {layout[u'title']}" + layout[u"annotations"] = annotations plpl = plgo.Figure(data=traces, layout=layout) # Export Plot - ploff.plot(plpl, - show_link=False, auto_open=False, - filename='{0}{1}'.format(plot["output-file"], - plot["output-file-type"])) + ploff.plot( + plpl, + show_link=False, auto_open=False, + filename=f"{plot[u'output-file']}{file_type}" + ) except PlotlyError as err: - logging.error(" Finished with error: {}". - format(str(err).replace("\n", " "))) + logging.error( + f" Finished with error: {repr(err)}".replace(u"\n", u" ") + ) return -def plot_throughput_speedup_analysis(plot, input_data): +def plot_tsa_name(plot, input_data): """Generate the plot(s) with algorithm: - plot_throughput_speedup_analysis + plot_tsa_name specified in the specification file. - TODO: Remove when not needed. - :param plot: Plot to generate. :param input_data: Data to process. :type plot: pandas.Series @@ -1353,47 +925,51 @@ def plot_throughput_speedup_analysis(plot, input_data): """ # Transform the data - plot_title = plot.get("title", "") - logging.info(" Creating the data set for the {0} '{1}'.". - format(plot.get("type", ""), plot_title)) - data = input_data.filter_data(plot) + plot_title = plot.get(u"title", u"") + logging.info( + f" Creating data set for the {plot.get(u'type', u'')} {plot_title}." + ) + data = input_data.filter_tests_by_name( + plot, params=[u"throughput", u"parent", u"tags", u"type"]) if data is None: - logging.error("No data.") + logging.error(u"No data.") return - y_vals = dict() - y_tags = dict() + y_vals = OrderedDict() for job in data: for build in job: for test in build: - if y_vals.get(test["parent"], None) is None: - y_vals[test["parent"]] = {"1": list(), - "2": list(), - "4": list()} - y_tags[test["parent"]] = test.get("tags", None) + if y_vals.get(test[u"parent"], None) is None: + y_vals[test[u"parent"]] = { + u"1": list(), + u"2": list(), + u"4": list() + } try: - if test["type"] in ("NDRPDR",): - if "-pdr" in plot_title.lower(): - ttype = "PDR" - elif "-ndr" in plot_title.lower(): - ttype = "NDR" - else: - continue - if "1C" in test["tags"]: - y_vals[test["parent"]]["1"]. \ - append(test["throughput"][ttype]["LOWER"]) - elif "2C" in test["tags"]: - y_vals[test["parent"]]["2"]. \ - append(test["throughput"][ttype]["LOWER"]) - elif "4C" in test["tags"]: - y_vals[test["parent"]]["4"]. \ - append(test["throughput"][ttype]["LOWER"]) + if test[u"type"] not in (u"NDRPDR",): + continue + + if u"-pdr" in plot_title.lower(): + ttype = u"PDR" + elif u"-ndr" in plot_title.lower(): + ttype = u"NDR" + else: + continue + + if u"1C" in test[u"tags"]: + y_vals[test[u"parent"]][u"1"]. \ + append(test[u"throughput"][ttype][u"LOWER"]) + elif u"2C" in test[u"tags"]: + y_vals[test[u"parent"]][u"2"]. \ + append(test[u"throughput"][ttype][u"LOWER"]) + elif u"4C" in test[u"tags"]: + y_vals[test[u"parent"]][u"4"]. \ + append(test[u"throughput"][ttype][u"LOWER"]) except (KeyError, TypeError): pass if not y_vals: - logging.warning("No data for the plot '{}'". - format(plot.get("title", ""))) + logging.warning(f"No data for the plot {plot.get(u'title', u'')}") return y_1c_max = dict() @@ -1401,112 +977,99 @@ 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, len(test_val)) - ideal = avg_val / (int(key) * 1000000.0) + y_vals[test_name][key] = [avg_val, len(test_val)] + ideal = avg_val / (int(key) * 1e6) if test_name not in y_1c_max or ideal > y_1c_max[test_name]: y_1c_max[test_name] = ideal - vals = dict() + vals = OrderedDict() y_max = list() nic_limit = 0 lnk_limit = 0 - pci_limit = plot["limits"]["pci"]["pci-g3-x8"] + pci_limit = plot[u"limits"][u"pci"][u"pci-g3-x8"] for test_name, test_vals in y_vals.items(): try: - if test_vals["1"][1]: - name = re.sub(REGEX_NIC, "", test_name.replace('-ndrpdr', ''). - replace('2n1l-', '')) - 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] \ + if test_vals[u"1"][1]: + name = re.sub( + REGEX_NIC, + u"", + test_name.replace(u'-ndrpdr', u'').replace(u'2n1l-', u'') + ) + vals[name] = OrderedDict() + y_val_1 = test_vals[u"1"][0] / 1e6 + y_val_2 = test_vals[u"2"][0] / 1e6 if test_vals[u"2"][0] \ else None - y_val_4 = test_vals["4"][0] / 1000000.0 if test_vals["4"][0] \ + y_val_4 = test_vals[u"4"][0] / 1e6 if test_vals[u"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]] + vals[name][u"val"] = [y_val_1, y_val_2, y_val_4] + vals[name][u"rel"] = [1.0, None, None] + vals[name][u"ideal"] = [ + y_1c_max[test_name], + y_1c_max[test_name] * 2, + y_1c_max[test_name] * 4 + ] + vals[name][u"diff"] = [ + (y_val_1 - y_1c_max[test_name]) * 100 / y_val_1, None, None + ] + vals[name][u"count"] = [ + test_vals[u"1"][1], + test_vals[u"2"][1], + test_vals[u"4"][1] + ] try: - # val_max = max(max(vals[name]["val"], vals[name]["ideal"])) - val_max = max(vals[name]["val"]) + val_max = max(vals[name][u"val"]) except ValueError as err: - logging.error(err) + logging.error(repr(err)) continue if val_max: - # y_max.append(int((val_max / 10) + 1) * 10) y_max.append(val_max) 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 + vals[name][u"rel"][1] = round(y_val_2 / y_val_1, 2) + vals[name][u"diff"][1] = \ + (y_val_2 - vals[name][u"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 + vals[name][u"rel"][2] = round(y_val_4 / y_val_1, 2) + vals[name][u"diff"][2] = \ + (y_val_4 - vals[name][u"ideal"][2]) * 100 / y_val_4 except IndexError as err: - logging.warning("No data for '{0}'".format(test_name)) + logging.warning(f"No data for {test_name}") logging.warning(repr(err)) # Limits: - if "x520" in test_name: - limit = plot["limits"]["nic"]["x520"] - elif "x710" in test_name: - limit = plot["limits"]["nic"]["x710"] - elif "xxv710" in test_name: - limit = plot["limits"]["nic"]["xxv710"] - elif "xl710" in test_name: - limit = plot["limits"]["nic"]["xl710"] - elif "x553" in test_name: - limit = plot["limits"]["nic"]["x553"] + if u"x520" in test_name: + limit = plot[u"limits"][u"nic"][u"x520"] + elif u"x710" in test_name: + limit = plot[u"limits"][u"nic"][u"x710"] + elif u"xxv710" in test_name: + limit = plot[u"limits"][u"nic"][u"xxv710"] + elif u"xl710" in test_name: + limit = plot[u"limits"][u"nic"][u"xl710"] + elif u"x553" in test_name: + limit = plot[u"limits"][u"nic"][u"x553"] + elif u"cx556a" in test_name: + limit = plot[u"limits"][u"nic"][u"cx556a"] else: limit = 0 if limit > nic_limit: nic_limit = limit - mul = 2 if "ge2p" in test_name else 1 - if "10ge" in test_name: - limit = plot["limits"]["link"]["10ge"] * mul - elif "25ge" in test_name: - limit = plot["limits"]["link"]["25ge"] * mul - elif "40ge" in test_name: - limit = plot["limits"]["link"]["40ge"] * mul - elif "100ge" in test_name: - limit = plot["limits"]["link"]["100ge"] * mul + mul = 2 if u"ge2p" in test_name else 1 + if u"10ge" in test_name: + limit = plot[u"limits"][u"link"][u"10ge"] * mul + elif u"25ge" in test_name: + limit = plot[u"limits"][u"link"][u"25ge"] * mul + elif u"40ge" in test_name: + limit = plot[u"limits"][u"link"][u"40ge"] * mul + elif u"100ge" in test_name: + limit = plot[u"limits"][u"link"][u"100ge"] * mul else: limit = 0 if limit > lnk_limit: lnk_limit = limit - # Sort the tests - order = plot.get("sort", None) - if order and y_tags: - y_sorted = OrderedDict() - y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()} - for tag in order: - for test, tags in y_tags_l.items(): - if tag.lower() in tags: - name = re.sub(REGEX_NIC, "", - test.replace('-ndrpdr', ''). - replace('2n1l-', '')) - try: - y_sorted[name] = vals.pop(name) - y_tags_l.pop(test) - except KeyError as err: - logging.error("Not found: {0}".format(err)) - finally: - break - else: - y_sorted = vals - traces = list() annotations = list() x_vals = [1, 2, 4] @@ -1517,179 +1080,181 @@ def plot_throughput_speedup_analysis(plot, input_data): except ValueError as err: logging.error(err) return - nic_limit /= 1000000.0 - # if nic_limit < threshold: + nic_limit /= 1e6 traces.append(plgo.Scatter( x=x_vals, y=[nic_limit, ] * len(x_vals), - name="NIC: {0:.2f}Mpps".format(nic_limit), + name=f"NIC: {nic_limit:.2f}Mpps", showlegend=False, - mode="lines", + mode=u"lines", line=dict( - dash="dot", + dash=u"dot", color=COLORS[-1], width=1), - hoverinfo="none" + hoverinfo=u"none" )) annotations.append(dict( x=1, y=nic_limit, - xref="x", - yref="y", - xanchor="left", - yanchor="bottom", - text="NIC: {0:.2f}Mpps".format(nic_limit), + xref=u"x", + yref=u"y", + xanchor=u"left", + yanchor=u"bottom", + text=f"NIC: {nic_limit:.2f}Mpps", font=dict( size=14, color=COLORS[-1], ), - align="left", + align=u"left", showarrow=False )) - # y_max.append(int((nic_limit / 10) + 1) * 10) y_max.append(nic_limit) - lnk_limit /= 1000000.0 + lnk_limit /= 1e6 if lnk_limit < threshold: traces.append(plgo.Scatter( x=x_vals, y=[lnk_limit, ] * len(x_vals), - name="Link: {0:.2f}Mpps".format(lnk_limit), + name=f"Link: {lnk_limit:.2f}Mpps", showlegend=False, - mode="lines", + mode=u"lines", line=dict( - dash="dot", + dash=u"dot", color=COLORS[-2], width=1), - hoverinfo="none" + hoverinfo=u"none" )) annotations.append(dict( x=1, y=lnk_limit, - xref="x", - yref="y", - xanchor="left", - yanchor="bottom", - text="Link: {0:.2f}Mpps".format(lnk_limit), + xref=u"x", + yref=u"y", + xanchor=u"left", + yanchor=u"bottom", + text=f"Link: {lnk_limit:.2f}Mpps", font=dict( size=14, color=COLORS[-2], ), - align="left", + align=u"left", showarrow=False )) - # y_max.append(int((lnk_limit / 10) + 1) * 10) y_max.append(lnk_limit) - pci_limit /= 1000000.0 + pci_limit /= 1e6 if (pci_limit < threshold and - (pci_limit < lnk_limit * 0.95 or lnk_limit > lnk_limit * 1.05)): + (pci_limit < lnk_limit * 0.95 or lnk_limit > lnk_limit * 1.05)): traces.append(plgo.Scatter( x=x_vals, y=[pci_limit, ] * len(x_vals), - name="PCIe: {0:.2f}Mpps".format(pci_limit), + name=f"PCIe: {pci_limit:.2f}Mpps", showlegend=False, - mode="lines", + mode=u"lines", line=dict( - dash="dot", + dash=u"dot", color=COLORS[-3], width=1), - hoverinfo="none" + hoverinfo=u"none" )) annotations.append(dict( x=1, y=pci_limit, - xref="x", - yref="y", - xanchor="left", - yanchor="bottom", - text="PCIe: {0:.2f}Mpps".format(pci_limit), + xref=u"x", + yref=u"y", + xanchor=u"left", + yanchor=u"bottom", + text=f"PCIe: {pci_limit:.2f}Mpps", font=dict( size=14, color=COLORS[-3], ), - align="left", + align=u"left", showarrow=False )) - # y_max.append(int((pci_limit / 10) + 1) * 10) y_max.append(pci_limit) # Perfect and measured: cidx = 0 - for name, val in y_sorted.iteritems(): + for name, val in vals.items(): hovertext = list() try: - for idx in range(len(val["val"])): + for idx in range(len(val[u"val"])): htext = "" - if isinstance(val["val"][idx], float): - htext += "No. of Runs: {1}<br>" \ - "Mean: {0:.2f}Mpps<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]) + if isinstance(val[u"val"][idx], float): + htext += ( + f"No. of Runs: {val[u'count'][idx]}<br>" + f"Mean: {val[u'val'][idx]:.2f}Mpps<br>" + ) + if isinstance(val[u"diff"][idx], float): + htext += f"Diff: {round(val[u'diff'][idx]):.0f}%<br>" + if isinstance(val[u"rel"][idx], float): + htext += f"Speedup: {val[u'rel'][idx]:.2f}" 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" - )) + traces.append( + plgo.Scatter( + x=x_vals, + y=val[u"val"], + name=name, + legendgroup=name, + mode=u"lines+markers", + line=dict( + color=COLORS[cidx], + width=2), + marker=dict( + symbol=u"circle", + size=10 + ), + text=hovertext, + hoverinfo=u"text+name" + ) + ) + traces.append( + plgo.Scatter( + x=x_vals, + y=val[u"ideal"], + name=f"{name} perfect", + legendgroup=name, + showlegend=False, + mode=u"lines", + line=dict( + color=COLORS[cidx], + width=2, + dash=u"dash"), + text=[f"Perfect: {y:.2f}Mpps" for y in val[u"ideal"]], + hoverinfo=u"text" + ) + ) cidx += 1 except (IndexError, ValueError, KeyError) as err: - logging.warning("No data for '{0}'".format(name)) - logging.warning(repr(err)) + logging.warning(f"No data for {name}\n{repr(err)}") try: # Create plot - logging.info(" Writing file '{0}{1}'.". - format(plot["output-file"], plot["output-file-type"])) - layout = deepcopy(plot["layout"]) - if layout.get("title", None): - layout["title"] = "<b>Speedup Multi-core:</b> {0}". \ - format(layout["title"]) - # layout["yaxis"]["range"] = [0, int((max(y_max) / 10) + 1) * 10] - layout["yaxis"]["range"] = [0, int(max(y_max) * 1.1)] - layout["annotations"].extend(annotations) + file_type = plot.get(u"output-file-type", u".html") + logging.info(f" Writing file {plot[u'output-file']}{file_type}.") + layout = deepcopy(plot[u"layout"]) + if layout.get(u"title", None): + layout[u"title"] = f"<b>Speedup Multi-core:</b> {layout[u'title']}" + layout[u"yaxis"][u"range"] = [0, int(max(y_max) * 1.1)] + layout[u"annotations"].extend(annotations) plpl = plgo.Figure(data=traces, layout=layout) # Export Plot - ploff.plot(plpl, - show_link=False, auto_open=False, - filename='{0}{1}'.format(plot["output-file"], - plot["output-file-type"])) + ploff.plot( + plpl, + show_link=False, + auto_open=False, + filename=f"{plot[u'output-file']}{file_type}" + ) except PlotlyError as err: - logging.error(" Finished with error: {}". - format(str(err).replace("\n", " "))) + logging.error( + f" Finished with error: {repr(err)}".replace(u"\n", u" ") + ) return -def plot_http_server_performance_box(plot, input_data): - """Generate the plot(s) with algorithm: plot_http_server_performance_box +def plot_http_server_perf_box(plot, input_data): + """Generate the plot(s) with algorithm: plot_http_server_perf_box specified in the specification file. :param plot: Plot to generate. @@ -1699,11 +1264,13 @@ def plot_http_server_performance_box(plot, input_data): """ # Transform the data - logging.info(" Creating the data set for the {0} '{1}'.". - format(plot.get("type", ""), plot.get("title", ""))) + logging.info( + f" Creating the data set for the {plot.get(u'type', u'')} " + f"{plot.get(u'title', u'')}." + ) data = input_data.filter_data(plot) if data is None: - logging.error("No data.") + logging.error(u"No data.") return # Prepare the data for the plot @@ -1711,12 +1278,12 @@ def plot_http_server_performance_box(plot, input_data): for job in data: for build in job: for test in build: - if y_vals.get(test["name"], None) is None: - y_vals[test["name"]] = list() + if y_vals.get(test[u"name"], None) is None: + y_vals[test[u"name"]] = list() try: - y_vals[test["name"]].append(test["result"]) + y_vals[test[u"name"]].append(test[u"result"]) except (KeyError, TypeError): - y_vals[test["name"]].append(None) + y_vals[test[u"name"]].append(None) # Add None to the lists with missing data max_len = 0 @@ -1725,53 +1292,59 @@ def plot_http_server_performance_box(plot, input_data): if len(val) > max_len: max_len = len(val) nr_of_samples.append(len(val)) - for key, val in y_vals.items(): + for val in y_vals.values(): if len(val) < max_len: val.extend([None for _ in range(max_len - len(val))]) # Add plot traces traces = list() - df = pd.DataFrame(y_vals) - df.head() - for i, col in enumerate(df.columns): - name = "{nr}. ({samples:02d} run{plural}) {name}".\ - format(nr=(i + 1), - samples=nr_of_samples[i], - plural='s' if nr_of_samples[i] > 1 else '', - name=col.lower().replace('-ndrpdr', '')) + df_y = pd.DataFrame(y_vals) + df_y.head() + for i, col in enumerate(df_y.columns): + name = \ + f"{i + 1}. " \ + f"({nr_of_samples[i]:02d} " \ + f"run{u's' if nr_of_samples[i] > 1 else u''}) " \ + f"{col.lower().replace(u'-ndrpdr', u'')}" if len(name) > 50: - name_lst = name.split('-') - name = "" + name_lst = name.split(u'-') + name = u"" split_name = True for segment in name_lst: if (len(name) + len(segment) + 1) > 50 and split_name: - name += "<br> " + name += u"<br> " split_name = False - name += segment + '-' + name += segment + u'-' name = name[:-1] - traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]), - y=df[col], + traces.append(plgo.Box(x=[str(i + 1) + u'.'] * len(df_y[col]), + y=df_y[col], name=name, - **plot["traces"])) + **plot[u"traces"])) try: # Create plot - plpl = plgo.Figure(data=traces, layout=plot["layout"]) + plpl = plgo.Figure(data=traces, layout=plot[u"layout"]) # Export Plot - logging.info(" Writing file '{0}{1}'.". - format(plot["output-file"], plot["output-file-type"])) - ploff.plot(plpl, show_link=False, auto_open=False, - filename='{0}{1}'.format(plot["output-file"], - plot["output-file-type"])) + logging.info( + f" Writing file {plot[u'output-file']}" + f"{plot[u'output-file-type']}." + ) + ploff.plot( + plpl, + show_link=False, + auto_open=False, + filename=f"{plot[u'output-file']}{plot[u'output-file-type']}" + ) except PlotlyError as err: - logging.error(" Finished with error: {}". - format(str(err).replace("\n", " "))) + logging.error( + f" Finished with error: {repr(err)}".replace(u"\n", u" ") + ) return -def plot_service_density_heatmap(plot, input_data): - """Generate the plot(s) with algorithm: plot_service_density_heatmap +def plot_nf_heatmap(plot, input_data): + """Generate the plot(s) with algorithm: plot_nf_heatmap specified in the specification file. :param plot: Plot to generate. @@ -1780,729 +1353,317 @@ def plot_service_density_heatmap(plot, input_data): :type input_data: InputData """ - REGEX_CN = re.compile(r'^(\d*)R(\d*)C$') - REGEX_TEST_NAME = re.compile(r'^.*-(\d+ch|\d+pl)-' + regex_cn = re.compile(r'^(\d*)R(\d*)C$') + regex_test_name = re.compile(r'^.*-(\d+ch|\d+pl)-' r'(\d+mif|\d+vh)-' - r'(\d+vm\d+t|\d+dcr\d+t).*$') - - txt_chains = list() - txt_nodes = list() + r'(\d+vm\d+t|\d+dcr\d+t|\d+dcr\d+c).*$') vals = dict() # Transform the data - logging.info(" Creating the data set for the {0} '{1}'.". - format(plot.get("type", ""), plot.get("title", ""))) + logging.info( + f" Creating the data set for the {plot.get(u'type', u'')} " + f"{plot.get(u'title', u'')}." + ) data = input_data.filter_data(plot, continue_on_error=True) if data is None or data.empty: - logging.error("No data.") + logging.error(u"No data.") return for job in data: for build in job: for test in build: - for tag in test['tags']: - groups = re.search(REGEX_CN, tag) + for tag in test[u"tags"]: + groups = re.search(regex_cn, tag) if groups: - c = str(groups.group(1)) - n = str(groups.group(2)) + chain = str(groups.group(1)) + node = str(groups.group(2)) break else: continue - groups = re.search(REGEX_TEST_NAME, test["name"]) + groups = re.search(regex_test_name, test[u"name"]) if groups and len(groups.groups()) == 3: - hover_name = "{chain}-{vhost}-{vm}".format( - chain=str(groups.group(1)), - vhost=str(groups.group(2)), - vm=str(groups.group(3))) + hover_name = ( + f"{str(groups.group(1))}-" + f"{str(groups.group(2))}-" + f"{str(groups.group(3))}" + ) else: - hover_name = "" - if vals.get(c, None) is None: - vals[c] = dict() - if vals[c].get(n, None) is None: - vals[c][n] = dict(name=hover_name, - vals=list(), - nr=None, - mean=None, - stdev=None) + hover_name = u"" + if vals.get(chain, None) is None: + vals[chain] = dict() + if vals[chain].get(node, None) is None: + vals[chain][node] = dict( + name=hover_name, + vals=list(), + nr=None, + mean=None, + stdev=None + ) try: - if plot["include-tests"] == "MRR": - result = test["result"]["receive-rate"].avg - elif plot["include-tests"] == "PDR": - result = test["throughput"]["PDR"]["LOWER"] - elif plot["include-tests"] == "NDR": - result = test["throughput"]["NDR"]["LOWER"] + if plot[u"include-tests"] == u"MRR": + result = test[u"result"][u"receive-rate"] + elif plot[u"include-tests"] == u"PDR": + result = test[u"throughput"][u"PDR"][u"LOWER"] + elif plot[u"include-tests"] == u"NDR": + result = test[u"throughput"][u"NDR"][u"LOWER"] else: result = None except TypeError: result = None if result: - vals[c][n]["vals"].append(result) + vals[chain][node][u"vals"].append(result) if not vals: - logging.error("No data.") + logging.error(u"No data.") return - for key_c in vals.keys(): + txt_chains = list() + txt_nodes = list() + for key_c in vals: txt_chains.append(key_c) for key_n in vals[key_c].keys(): txt_nodes.append(key_n) - if vals[key_c][key_n]["vals"]: - vals[key_c][key_n]["nr"] = len(vals[key_c][key_n]["vals"]) - vals[key_c][key_n]["mean"] = \ - round(mean(vals[key_c][key_n]["vals"]) / 1000000, 1) - vals[key_c][key_n]["stdev"] = \ - round(stdev(vals[key_c][key_n]["vals"]) / 1000000, 1) + if vals[key_c][key_n][u"vals"]: + vals[key_c][key_n][u"nr"] = len(vals[key_c][key_n][u"vals"]) + vals[key_c][key_n][u"mean"] = \ + round(mean(vals[key_c][key_n][u"vals"]) / 1000000, 1) + vals[key_c][key_n][u"stdev"] = \ + round(stdev(vals[key_c][key_n][u"vals"]) / 1000000, 1) txt_nodes = list(set(txt_nodes)) - txt_chains = sorted(txt_chains, key=lambda chain: int(chain)) - txt_nodes = sorted(txt_nodes, key=lambda node: int(node)) + def sort_by_int(value): + """Makes possible to sort a list of strings which represent integers. + + :param value: Integer as a string. + :type value: str + :returns: Integer representation of input parameter 'value'. + :rtype: int + """ + return int(value) + + txt_chains = sorted(txt_chains, key=sort_by_int) + txt_nodes = sorted(txt_nodes, key=sort_by_int) chains = [i + 1 for i in range(len(txt_chains))] nodes = [i + 1 for i in range(len(txt_nodes))] data = [list() for _ in range(len(chains))] - for c in chains: - for n in nodes: + for chain in chains: + for node in nodes: try: - val = vals[txt_chains[c - 1]][txt_nodes[n - 1]]["mean"] + val = vals[txt_chains[chain - 1]][txt_nodes[node - 1]][u"mean"] except (KeyError, IndexError): val = None - data[c - 1].append(val) + data[chain - 1].append(val) - # Colorscales: - my_green = [[0.0, 'rgb(235, 249, 242)'], - [1.0, 'rgb(45, 134, 89)']] + # Color scales: + my_green = [[0.0, u"rgb(235, 249, 242)"], + [1.0, u"rgb(45, 134, 89)"]] - my_blue = [[0.0, 'rgb(236, 242, 248)'], - [1.0, 'rgb(57, 115, 172)']] + my_blue = [[0.0, u"rgb(236, 242, 248)"], + [1.0, u"rgb(57, 115, 172)"]] - my_grey = [[0.0, 'rgb(230, 230, 230)'], - [1.0, 'rgb(102, 102, 102)']] + my_grey = [[0.0, u"rgb(230, 230, 230)"], + [1.0, u"rgb(102, 102, 102)"]] hovertext = list() annotations = list() - text = ("Test: {name}<br>" - "Runs: {nr}<br>" - "Thput: {val}<br>" - "StDev: {stdev}") + text = (u"Test: {name}<br>" + u"Runs: {nr}<br>" + u"Thput: {val}<br>" + u"StDev: {stdev}") - for c in range(len(txt_chains)): + for chain, _ in enumerate(txt_chains): hover_line = list() - for n in range(len(txt_nodes)): - if data[c][n] is not None: - annotations.append(dict( - x=n+1, - y=c+1, - xref="x", - yref="y", - xanchor="center", - yanchor="middle", - text=str(data[c][n]), - font=dict( - size=14, - ), - align="center", - showarrow=False - )) + for node, _ in enumerate(txt_nodes): + if data[chain][node] is not None: + annotations.append( + dict( + x=node+1, + y=chain+1, + xref=u"x", + yref=u"y", + xanchor=u"center", + yanchor=u"middle", + text=str(data[chain][node]), + font=dict( + size=14, + ), + align=u"center", + showarrow=False + ) + ) hover_line.append(text.format( - name=vals[txt_chains[c]][txt_nodes[n]]["name"], - nr=vals[txt_chains[c]][txt_nodes[n]]["nr"], - val=data[c][n], - stdev=vals[txt_chains[c]][txt_nodes[n]]["stdev"])) + name=vals[txt_chains[chain]][txt_nodes[node]][u"name"], + nr=vals[txt_chains[chain]][txt_nodes[node]][u"nr"], + val=data[chain][node], + stdev=vals[txt_chains[chain]][txt_nodes[node]][u"stdev"])) hovertext.append(hover_line) traces = [ - plgo.Heatmap(x=nodes, - y=chains, - z=data, - colorbar=dict( - title=plot.get("z-axis", ""), - titleside="right", - titlefont=dict( - size=16 - ), - tickfont=dict( - size=16, - ), - tickformat=".1f", - yanchor="bottom", - y=-0.02, - len=0.925, - ), - showscale=True, - colorscale=my_green, - text=hovertext, - hoverinfo="text") + plgo.Heatmap( + x=nodes, + y=chains, + z=data, + colorbar=dict( + title=plot.get(u"z-axis", u""), + titleside=u"right", + titlefont=dict( + size=16 + ), + tickfont=dict( + size=16, + ), + tickformat=u".1f", + yanchor=u"bottom", + y=-0.02, + len=0.925, + ), + showscale=True, + colorscale=my_green, + text=hovertext, + hoverinfo=u"text" + ) ] for idx, item in enumerate(txt_nodes): # X-axis, numbers: - annotations.append(dict( - x=idx+1, - y=0.05, - xref="x", - yref="y", - xanchor="center", - yanchor="top", - text=item, - font=dict( - size=16, - ), - align="center", - showarrow=False - )) - for idx, item in enumerate(txt_chains): - # Y-axis, numbers: - annotations.append(dict( - x=0.35, - y=idx+1, - xref="x", - yref="y", - xanchor="right", - yanchor="middle", - text=item, - font=dict( - size=16, - ), - align="center", - showarrow=False - )) - # X-axis, title: - annotations.append(dict( - x=0.55, - y=-0.15, - xref="paper", - yref="y", - xanchor="center", - yanchor="bottom", - text=plot.get("x-axis", ""), - font=dict( - size=16, - ), - align="center", - showarrow=False - )) - # Y-axis, title: - annotations.append(dict( - x=-0.1, - y=0.5, - xref="x", - yref="paper", - xanchor="center", - yanchor="middle", - text=plot.get("y-axis", ""), - font=dict( - size=16, - ), - align="center", - textangle=270, - showarrow=False - )) - updatemenus = list([ - dict( - x=1.0, - y=0.0, - xanchor='right', - yanchor='bottom', - direction='up', - buttons=list([ - dict( - args=[{"colorscale": [my_green, ], "reversescale": False}], - label="Green", - method="update" - ), - dict( - args=[{"colorscale": [my_blue, ], "reversescale": False}], - label="Blue", - method="update" + annotations.append( + dict( + x=idx+1, + y=0.05, + xref=u"x", + yref=u"y", + xanchor=u"center", + yanchor=u"top", + text=item, + font=dict( + size=16, ), - dict( - args=[{"colorscale": [my_grey, ], "reversescale": False}], - label="Grey", - method="update" - ) - ]) + align=u"center", + showarrow=False + ) ) - ]) - - try: - layout = deepcopy(plot["layout"]) - except KeyError as err: - logging.error("Finished with error: No layout defined") - logging.error(repr(err)) - return - - layout["annotations"] = annotations - layout['updatemenus'] = updatemenus - - try: - # Create plot - plpl = plgo.Figure(data=traces, layout=layout) - - # Export Plot - logging.info(" Writing file '{0}{1}'.". - format(plot["output-file"], plot["output-file-type"])) - ploff.plot(plpl, show_link=False, auto_open=False, - filename='{0}{1}'.format(plot["output-file"], - plot["output-file-type"])) - except PlotlyError as err: - logging.error(" Finished with error: {}". - format(str(err).replace("\n", " "))) - return - - -def plot_service_density_heatmap_compare(plot, input_data): - """Generate the plot(s) with algorithm: plot_service_density_heatmap_compare - specified in the specification file. - - :param plot: Plot to generate. - :param input_data: Data to process. - :type plot: pandas.Series - :type input_data: InputData - """ - - REGEX_CN = re.compile(r'^(\d*)R(\d*)C$') - REGEX_TEST_NAME = re.compile(r'^.*-(\d+ch|\d+pl)-' - r'(\d+mif|\d+vh)-' - r'(\d+vm\d+t|\d+dcr\d+t).*$') - REGEX_THREADS = re.compile(r'^(\d+)(VM|DCR)(\d+)T$') - - txt_chains = list() - txt_nodes = list() - vals = dict() - - # Transform the data - logging.info(" Creating the data set for the {0} '{1}'.". - format(plot.get("type", ""), plot.get("title", ""))) - data = input_data.filter_data(plot, continue_on_error=True) - if data is None or data.empty: - logging.error("No data.") - return - - for job in data: - for build in job: - for test in build: - for tag in test['tags']: - groups = re.search(REGEX_CN, tag) - if groups: - c = str(groups.group(1)) - n = str(groups.group(2)) - break - else: - continue - groups = re.search(REGEX_TEST_NAME, test["name"]) - if groups and len(groups.groups()) == 3: - hover_name = "{chain}-{vhost}-{vm}".format( - chain=str(groups.group(1)), - vhost=str(groups.group(2)), - vm=str(groups.group(3))) - else: - hover_name = "" - if vals.get(c, None) is None: - vals[c] = dict() - if vals[c].get(n, None) is None: - vals[c][n] = dict(name=hover_name, - vals_r=list(), - vals_c=list(), - nr_r=None, - nr_c=None, - mean_r=None, - mean_c=None, - stdev_r=None, - stdev_c=None) - try: - if plot["include-tests"] == "MRR": - result = test["result"]["receive-rate"].avg - elif plot["include-tests"] == "PDR": - result = test["throughput"]["PDR"]["LOWER"] - elif plot["include-tests"] == "NDR": - result = test["throughput"]["NDR"]["LOWER"] - else: - result = None - except TypeError: - result = None - - if result: - for tag in test['tags']: - groups = re.search(REGEX_THREADS, tag) - if groups and len(groups.groups()) == 3: - if str(groups.group(3)) == \ - plot["reference"]["include"]: - vals[c][n]["vals_r"].append(result) - elif str(groups.group(3)) == \ - plot["compare"]["include"]: - vals[c][n]["vals_c"].append(result) - break - if not vals: - logging.error("No data.") - return - - for key_c in vals.keys(): - txt_chains.append(key_c) - for key_n in vals[key_c].keys(): - txt_nodes.append(key_n) - if vals[key_c][key_n]["vals_r"]: - vals[key_c][key_n]["nr_r"] = len(vals[key_c][key_n]["vals_r"]) - vals[key_c][key_n]["mean_r"] = \ - mean(vals[key_c][key_n]["vals_r"]) - vals[key_c][key_n]["stdev_r"] = \ - round(stdev(vals[key_c][key_n]["vals_r"]) / 1000000, 1) - if vals[key_c][key_n]["vals_c"]: - vals[key_c][key_n]["nr_c"] = len(vals[key_c][key_n]["vals_c"]) - vals[key_c][key_n]["mean_c"] = \ - mean(vals[key_c][key_n]["vals_c"]) - vals[key_c][key_n]["stdev_c"] = \ - round(stdev(vals[key_c][key_n]["vals_c"]) / 1000000, 1) - - txt_nodes = list(set(txt_nodes)) - - txt_chains = sorted(txt_chains, key=lambda chain: int(chain)) - txt_nodes = sorted(txt_nodes, key=lambda node: int(node)) - - chains = [i + 1 for i in range(len(txt_chains))] - nodes = [i + 1 for i in range(len(txt_nodes))] - - data_r = [list() for _ in range(len(chains))] - data_c = [list() for _ in range(len(chains))] - diff = [list() for _ in range(len(chains))] - for c in chains: - for n in nodes: - try: - val_r = vals[txt_chains[c - 1]][txt_nodes[n - 1]]["mean_r"] - except (KeyError, IndexError): - val_r = None - try: - val_c = vals[txt_chains[c - 1]][txt_nodes[n - 1]]["mean_c"] - except (KeyError, IndexError): - val_c = None - if val_c is not None and val_r: - val_d = (val_c - val_r) * 100 / val_r - else: - val_d = None - - if val_r is not None: - val_r = round(val_r / 1000000, 1) - data_r[c - 1].append(val_r) - if val_c is not None: - val_c = round(val_c / 1000000, 1) - data_c[c - 1].append(val_c) - if val_d is not None: - val_d = int(round(val_d, 0)) - diff[c - 1].append(val_d) - - # Colorscales: - my_green = [[0.0, 'rgb(235, 249, 242)'], - [1.0, 'rgb(45, 134, 89)']] - - my_blue = [[0.0, 'rgb(236, 242, 248)'], - [1.0, 'rgb(57, 115, 172)']] - - my_grey = [[0.0, 'rgb(230, 230, 230)'], - [1.0, 'rgb(102, 102, 102)']] - - hovertext = list() - - annotations = list() - annotations_r = list() - annotations_c = list() - annotations_diff = list() - - text = ("Test: {name}" - "<br>{title_r}: {text_r}" - "<br>{title_c}: {text_c}{text_diff}") - text_r = "Thput: {val_r}; StDev: {stdev_r}; Runs: {nr_r}" - text_c = "Thput: {val_c}; StDev: {stdev_c}; Runs: {nr_c}" - text_diff = "<br>Relative Difference {title_c} vs. {title_r}: {diff}%" - - for c in range(len(txt_chains)): - hover_line = list() - for n in range(len(txt_nodes)): - point = dict( - x=n + 1, - y=c + 1, - xref="x", - yref="y", - xanchor="center", - yanchor="middle", - text="", + for idx, item in enumerate(txt_chains): + # Y-axis, numbers: + annotations.append( + dict( + x=0.35, + y=idx+1, + xref=u"x", + yref=u"y", + xanchor=u"right", + yanchor=u"middle", + text=item, font=dict( - size=14, + size=16, ), - align="center", + align=u"center", showarrow=False ) - - point_text_r = "Not present" - point_text_c = "Not present" - point_text_diff = "" - try: - point_r = data_r[c][n] - if point_r is not None: - point_text_r = text_r.format( - val_r=point_r, - stdev_r=vals[txt_chains[c]][txt_nodes[n]]["stdev_r"], - nr_r=vals[txt_chains[c]][txt_nodes[n]]["nr_r"]) - except KeyError: - point_r = None - point["text"] = "" if point_r is None else point_r - annotations_r.append(deepcopy(point)) - - try: - point_c = data_c[c][n] - if point_c is not None: - point_text_c = text_c.format( - val_c=point_c, - stdev_c=vals[txt_chains[c]][txt_nodes[n]]["stdev_c"], - nr_c=vals[txt_chains[c]][txt_nodes[n]]["nr_c"]) - except KeyError: - point_c = None - point["text"] = "" if point_c is None else point_c - annotations_c.append(deepcopy(point)) - - try: - point_d = diff[c][n] - if point_d is not None: - point_text_diff = text_diff.format( - title_r=plot["reference"]["name"], - title_c=plot["compare"]["name"], - diff=point_d) - except KeyError: - point_d = None - point["text"] = "" if point_d is None else point_d - annotations_diff.append(deepcopy(point)) - - try: - name = vals[txt_chains[c]][txt_nodes[n]]["name"] - except KeyError: - continue - - hover_line.append(text.format( - name=name, - title_r=plot["reference"]["name"], - text_r=point_text_r, - title_c=plot["compare"]["name"], - text_c=point_text_c, - text_diff=point_text_diff - )) - - hovertext.append(hover_line) - - traces = [ - plgo.Heatmap(x=nodes, - y=chains, - z=data_r, - visible=True, - colorbar=dict( - title=plot.get("z-axis", ""), - titleside="right", - titlefont=dict( - size=16 - ), - tickfont=dict( - size=16, - ), - tickformat=".1f", - yanchor="bottom", - y=-0.02, - len=0.925, - ), - showscale=True, - colorscale=my_green, - reversescale=False, - text=hovertext, - hoverinfo="text"), - plgo.Heatmap(x=nodes, - y=chains, - z=data_c, - visible=False, - colorbar=dict( - title=plot.get("z-axis", ""), - titleside="right", - titlefont=dict( - size=16 - ), - tickfont=dict( - size=16, - ), - tickformat=".1f", - yanchor="bottom", - y=-0.02, - len=0.925, - ), - showscale=True, - colorscale=my_blue, - reversescale=False, - text=hovertext, - hoverinfo="text"), - plgo.Heatmap(x=nodes, - y=chains, - z=diff, - name="Diff", - visible=False, - colorbar=dict( - title="Relative Difference {name_c} vs. {name_r} [%]". - format(name_c=plot["compare"]["name"], - name_r=plot["reference"]["name"]), - titleside="right", - titlefont=dict( - size=16 - ), - tickfont=dict( - size=16, - ), - tickformat=".1f", - yanchor="bottom", - y=-0.02, - len=0.925, - ), - showscale=True, - colorscale=my_grey, - reversescale=False, - text=hovertext, - hoverinfo="text") - ] - - for idx, item in enumerate(txt_nodes): - # X-axis, numbers: - annotations.append(dict( - x=idx+1, - y=0.05, - xref="x", - yref="y", - xanchor="center", - yanchor="top", - text=item, + ) + # X-axis, title: + annotations.append( + dict( + x=0.55, + y=-0.15, + xref=u"paper", + yref=u"y", + xanchor=u"center", + yanchor=u"bottom", + text=plot.get(u"x-axis", u""), font=dict( size=16, ), - align="center", + align=u"center", showarrow=False - )) - for idx, item in enumerate(txt_chains): - # Y-axis, numbers: - annotations.append(dict( - x=0.35, - y=idx+1, - xref="x", - yref="y", - xanchor="right", - yanchor="middle", - text=item, + ) + ) + # Y-axis, title: + annotations.append( + dict( + x=-0.1, + y=0.5, + xref=u"x", + yref=u"paper", + xanchor=u"center", + yanchor=u"middle", + text=plot.get(u"y-axis", u""), font=dict( size=16, ), - align="center", + align=u"center", + textangle=270, showarrow=False - )) - # X-axis, title: - annotations.append(dict( - x=0.55, - y=-0.15, - xref="paper", - yref="y", - xanchor="center", - yanchor="bottom", - text=plot.get("x-axis", ""), - font=dict( - size=16, - ), - align="center", - showarrow=False - )) - # Y-axis, title: - annotations.append(dict( - x=-0.1, - y=0.5, - xref="x", - yref="paper", - xanchor="center", - yanchor="middle", - text=plot.get("y-axis", ""), - font=dict( - size=16, - ), - align="center", - textangle=270, - showarrow=False - )) + ) + ) updatemenus = list([ dict( - active=0, x=1.0, y=0.0, - xanchor='right', - yanchor='bottom', - direction='up', + xanchor=u"right", + yanchor=u"bottom", + direction=u"up", buttons=list([ dict( - label=plot["reference"]["name"], - method="update", args=[ { - "visible": [True, False, False] - }, - { - "colorscale": [my_green, ], - "reversescale": False, - "annotations": annotations + annotations_r, - }, - ] + u"colorscale": [my_green, ], + u"reversescale": False + } + ], + label=u"Green", + method=u"update" ), dict( - label=plot["compare"]["name"], - method="update", args=[ { - "visible": [False, True, False] - }, - { - "colorscale": [my_blue, ], - "reversescale": False, - "annotations": annotations + annotations_c, - }, - ] + u"colorscale": [my_blue, ], + u"reversescale": False + } + ], + label=u"Blue", + method=u"update" ), dict( - label="Diff", - method="update", args=[ { - "visible": [False, False, True] - }, - { - "colorscale": [my_grey, ], - "reversescale": False, - "annotations": annotations + annotations_diff, - }, - ] - ), + u"colorscale": [my_grey, ], + u"reversescale": False + } + ], + label=u"Grey", + method=u"update" + ) ]) ) ]) try: - layout = deepcopy(plot["layout"]) + layout = deepcopy(plot[u"layout"]) except KeyError as err: - logging.error("Finished with error: No layout defined") - logging.error(repr(err)) + logging.error(f"Finished with error: No layout defined\n{repr(err)}") return - layout["annotations"] = annotations + annotations_r - layout['updatemenus'] = updatemenus + layout[u"annotations"] = annotations + layout[u'updatemenus'] = updatemenus try: # Create plot plpl = plgo.Figure(data=traces, layout=layout) # Export Plot - logging.info(" Writing file '{0}{1}'.". - format(plot["output-file"], plot["output-file-type"])) - ploff.plot(plpl, show_link=False, auto_open=False, - filename='{0}{1}'.format(plot["output-file"], - plot["output-file-type"])) + logging.info(f" Writing file {plot[u'output-file']}.html") + ploff.plot( + plpl, + show_link=False, + auto_open=False, + filename=f"{plot[u'output-file']}.html" + ) except PlotlyError as err: - logging.error(" Finished with error: {}". - format(str(err).replace("\n", " "))) + logging.error( + f" Finished with error: {repr(err)}".replace(u"\n", u" ") + ) return |