X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fgenerator_plots.py;h=28490074736304185bb0b080e43524a40536e14b;hp=ca1cd9bdf687bde2d10b7bdb83a0bf0618fd4773;hb=HEAD;hpb=7f83ed570d3cd7ec18f2a7ea3c8c3badd0368099 diff --git a/resources/tools/presentation/generator_plots.py b/resources/tools/presentation/generator_plots.py deleted file mode 100644 index ca1cd9bdf6..0000000000 --- a/resources/tools/presentation/generator_plots.py +++ /dev/null @@ -1,1326 +0,0 @@ -# Copyright (c) 2019 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: -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -"""Algorithms to generate plots. -""" - - -import logging -import pandas as pd -import plotly.offline as ploff -import plotly.graph_objs as plgo - -from plotly.exceptions import PlotlyError -from collections import OrderedDict -from copy import deepcopy - -from utils import mean - - -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"] - - -def generate_plots(spec, data): - """Generate all plots specified in the specification file. - - :param spec: Specification read from the specification file. - :param data: Data to process. - :type spec: Specification - :type data: InputData - """ - - logging.info("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.") - except NameError as err: - logging.error("Probably algorithm '{alg}' is not defined: {err}". - format(alg=plot["algorithm"], err=repr(err))) - logging.info("Done.") - - -def plot_performance_box(plot, input_data): - """Generate the plot(s) with algorithm: plot_performance_box - 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_vals[test["parent"]] = list() - y_tags[test["parent"]] = test.get("tags", None) - 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 - 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 - - # Add None to the lists with missing data - max_len = 0 - nr_of_samples = list() - for val in y_sorted.values(): - if len(val) > max_len: - max_len = len(val) - nr_of_samples.append(len(val)) - for key, val in y_sorted.items(): - if len(val) < max_len: - val.extend([None for _ in range(max_len - len(val))]) - - # Add plot traces - traces = list() - df = pd.DataFrame(y_sorted) - df.head() - y_max = list() - 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', '')) - 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 += "
" - split_name = False - name += segment + '-' - name = name[:-1] - - 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"])) - 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) + 1) - - try: - # Create plot - layout = deepcopy(plot["layout"]) - if layout.get("title", None): - layout["title"] = "Packet Throughput: {0}". \ - format(layout["title"]) - if y_max: - layout["yaxis"]["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 += "
" - 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}
" - "Packet Throughput: {val:.2f}Mpps
" - "Final Duration: {time}
" - "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"] = "Packet Throughput: {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', '')) - 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 += "
" - 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 = ("{name}
" - "Upper bound: {upper:.2f}Mpps
" - "Lower bound: {lower:.2f}Mpps".format(name=name, - 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"] = "Soak Tests: {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_latency_error_bars(plot, input_data): - """Generate the plot(s) with algorithm: plot_latency_error_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_tmp_vals = dict() - y_tags = dict() - 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 - ] - 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"]) - else: - logging.warning("Invalid test type: {0}". - format(test["type"])) - continue - 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 = "-".join(key.split("-")[1:-1]) - 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 += "
" - split_name = False - name += segment + '-' - name = name[:-1] - 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) - - 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)): - if not bool(int(idx % 2)): - direction = "West-East" - else: - direction = "East-West" - hovertext = ("No. of Runs: {nr}
" - "Test: {test}
" - "Direction: {dir}
".format(test=x_vals[idx], - dir=direction, - nr=nr_of_samples[idx])) - if isinstance(y_maxs[idx], float): - hovertext += "Max: {max:.2f}uSec
".format(max=y_maxs[idx]) - if isinstance(y_vals[idx], float): - hovertext += "Mean: {avg:.2f}uSec
".format(avg=y_vals[idx]) - if isinstance(y_mins[idx], float): - hovertext += "Min: {min:.2f}uSec".format(min=y_mins[idx]) - - 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, ] - 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", - 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 - )) - - 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"] = "Packet Latency: {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"], - plot["output-file-type"])) - except PlotlyError as err: - logging.error(" Finished with error: {}". - format(str(err).replace("\n", " "))) - return - - -def plot_throughput_speedup_analysis(plot, input_data): - """Generate the plot(s) with algorithm: - plot_throughput_speedup_analysis - 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 - - 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_vals[test["parent"]] = {"1": list(), - "2": list(), - "4": list()} - 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: - 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"]) - 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 = dict() - 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 = "-".join(test_name.split('-')[1:-1]) - 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 += "
" - split_name = False - name += segment + '-' - name = name[:-1] - - vals[name] = dict() - y_val_1 = test_vals["1"][0] / 1000000.0 - y_val_2 = test_vals["2"][0] / 1000000.0 if test_vals["2"][0] \ - else None - y_val_4 = test_vals["4"][0] / 1000000.0 if test_vals["4"][0] \ - else None - - vals[name]["val"] = [y_val_1, y_val_2, y_val_4] - vals[name]["rel"] = [1.0, None, None] - vals[name]["ideal"] = [y_1c_max[test_name], - y_1c_max[test_name] * 2, - y_1c_max[test_name] * 4] - vals[name]["diff"] = [(y_val_1 - y_1c_max[test_name]) * 100 / - y_val_1, None, None] - vals[name]["count"] = [test_vals["1"][1], - test_vals["2"][1], - test_vals["4"][1]] - - try: - val_max = max(max(vals[name]["val"], vals[name]["ideal"])) - except ValueError as err: - logging.error(err) - continue - if val_max: - y_max.append(int((val_max / 10) + 1) * 10) - - if y_val_2: - vals[name]["rel"][1] = round(y_val_2 / y_val_1, 2) - vals[name]["diff"][1] = \ - (y_val_2 - vals[name]["ideal"][1]) * 100 / y_val_2 - if y_val_4: - vals[name]["rel"][2] = round(y_val_4 / y_val_1, 2) - vals[name]["diff"][2] = \ - (y_val_4 - vals[name]["ideal"][2]) * 100 / y_val_4 - except IndexError as err: - logging.warning("No data for '{0}'".format(test_name)) - logging.warning(repr(err)) - - # Limits: - if "x520" in test_name: - 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 - - # 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 = "-".join(test.split('-')[1:-1]) - 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] - - # Limits: - try: - threshold = 1.1 * max(y_max) # 10% - except ValueError as err: - logging.error(err) - return - nic_limit /= 1000000.0 - if nic_limit < threshold: - 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(int((nic_limit / 10) + 1) * 10) - - 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], - ), - align="left", - showarrow=False - )) - y_max.append(int((lnk_limit / 10) + 1) * 10) - - pci_limit /= 1000000.0 - if pci_limit < threshold: - 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(int((pci_limit / 10) + 1) * 10) - - # Perfect and measured: - cidx = 0 - for name, val in y_sorted.iteritems(): - hovertext = list() - try: - for idx in range(len(val["val"])): - htext = "" - if isinstance(val["val"][idx], float): - htext += "No. of Runs: {1}
" \ - "Mean: {0:.2f}Mpps
".format(val["val"][idx], - val["count"][idx]) - if isinstance(val["diff"][idx], float): - htext += "Diff: {0:.0f}%
".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 - 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"] = "Speedup Multi-core: {0}". \ - format(layout["title"]) - layout["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"])) - except PlotlyError as err: - logging.error(" Finished with error: {}". - format(str(err).replace("\n", " "))) - return - - -def plot_http_server_performance_box(plot, input_data): - """Generate the plot(s) with algorithm: plot_http_server_performance_box - 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 - logging.info(" Creating the data set for the {0} '{1}'.". - format(plot.get("type", ""), plot.get("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() - 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() - try: - y_vals[test["name"]].append(test["result"]) - except (KeyError, TypeError): - y_vals[test["name"]].append(None) - - # 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))]) - - # 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', '')) - 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 += "
" - split_name = False - name += segment + '-' - name = name[:-1] - - traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]), - y=df[col], - name=name, - **plot["traces"])) - try: - # Create plot - plpl = plgo.Figure(data=traces, layout=plot["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(plot, input_data): - """Generate the plot(s) with algorithm: plot_service_density_heatmap - specified in the specification file. - - :param plot: Plot to generate. - :param input_data: Data to process. - :type plot: pandas.Series - :type input_data: InputData - """ - - # Example data in Mpps - txt_chains = ['1', '2', '4', '6', '8', '10'] - txt_nodes = ['1', '2', '4', '6', '8', '10'] - chains = [i + 1 for i in range(len(txt_chains))] - nodes = [i + 1 for i in range(len(txt_nodes))] - data = [ - [6.3, 6.3, 6.3, 6.4, 6.5, 6.4], - [5.8, 5.6, 5.6, 5.6, 5.5, None], - [5.6, 5.5, 5.3, None, None, None], - [5.4, 5.3, None, None, None, None], - [5.4, 5.2, None, None, None, None], - [5.3, None, None, None, None, None] - ] - - hovertext = list() - annotations = list() - - text = "{name}" - - for c in range(len(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 - )) - hover_line.append(text.format(name="Testcase Name")) - hovertext.append(hover_line) - - traces = [ - plgo.Heatmap(x=nodes, - y=chains, - z=data, - colorbar=dict( - title="Packet Throughput [Mpps]", - titleside="right", - titlefont=dict( - size=14 - ), - ), - showscale=True, - colorscale="Reds", - text=hovertext, - hoverinfo="text") - ] - - for idx, item in enumerate(txt_nodes): - annotations.append(dict( - x=idx+1, - y=0, - 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): - annotations.append(dict( - x=0.3, - y=idx+1, - xref="x", - yref="y", - xanchor="right", - yanchor="middle", - text=item, - font=dict( - size=16, - ), - align="center", - showarrow=False - )) - # X-axis: - annotations.append(dict( - x=0.55, - y=1.05, - xref="paper", - yref="paper", - xanchor="center", - yanchor="middle", - text="No. of Network Functions per Service Instance", - font=dict( - size=16, - ), - align="center", - showarrow=False - )) - # Y-axis: - annotations.append(dict( - x=-0.04, - y=0.5, - xref="paper", - yref="paper", - xanchor="center", - yanchor="middle", - text="No. of Service Instances", - 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": "Reds", "reversescale": False}], - label="Red", - method="update" - ), - dict( - args=[{"colorscale": "Blues", "reversescale": True}], - label="Blue", - method="update" - ), - dict( - args=[{"colorscale": "Greys", "reversescale": True}], - label="Grey", - method="update" - ), - dict( - args=[{"colorscale": "Greens", "reversescale": True}], - label="Green", - method="update" - ), - dict( - args=[{"colorscale": "RdBu", "reversescale": False}], - label="RedBlue", - method="update" - ), - dict( - args=[{"colorscale": "Picnic", "reversescale": False}], - label="Picnic", - method="update" - ), - dict( - args=[{"colorscale": "Rainbow", "reversescale": False}], - label="Rainbow", - method="update" - ), - dict( - args=[{"colorscale": "Portland", "reversescale": False}], - label="Portland", - method="update" - ), - dict( - args=[{"colorscale": "Jet", "reversescale": False}], - label="Jet", - method="update" - ), - dict( - args=[{"colorscale": "Hot", "reversescale": True}], - label="Hot", - method="update" - ), - dict( - args=[{"colorscale": "Blackbody", "reversescale": True}], - label="Blackbody", - method="update" - ), - dict( - args=[{"colorscale": "Earth", "reversescale": True}], - label="Earth", - method="update" - ), - dict( - args=[{"colorscale": "Electric", "reversescale": True}], - label="Electric", - method="update" - ), - dict( - args=[{"colorscale": "Viridis", "reversescale": True}], - label="Viridis", - method="update" - ), - dict( - args=[{"colorscale": "Cividis", "reversescale": True}], - label="Cividis", - method="update" - ), - ]) - ) - ]) - - 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