X-Git-Url: https://gerrit.fd.io/r/gitweb?a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fgenerator_plots.py;h=b6a393968d331bb3562e564bec984f492a11dd6c;hb=7dc45304cd2e4e877c7c5b1885d242c3977e9245;hp=dda519600835121b1ee05f74b9f4b560a1d7a8ad;hpb=cbfa26dc0f5334bcd367c161b4eaad342355bbde;p=csit.git diff --git a/resources/tools/presentation/generator_plots.py b/resources/tools/presentation/generator_plots.py index dda5196008..b6a393968d 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: @@ -21,10 +21,13 @@ 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 pal_utils import mean, stdev @@ -37,7 +40,7 @@ COLORS = [u"SkyBlue", u"Olive", u"Purple", u"Coral", u"Indigo", u"Pink", 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): @@ -55,7 +58,10 @@ def generate_plots(spec, data): 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_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 ...") @@ -73,6 +79,439 @@ def generate_plots(spec, data): logging.info(u"Done.") +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. + :param input_data: Data to process. + :type plot: pandas.Series + :type input_data: InputData + """ + + # Transform the data + 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=[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 + 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}
" + f"Direction: {directions[idx]}
" + f"Percentile: {percentile:.5f}%
" + 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)) + + layout = deepcopy(plot[u"layout"]) + + layout[u"title"][u"text"] = \ + f"Latency: {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 + ploff.plot(fig, show_link=False, auto_open=False, + filename=f"{plot[u'output-file']}{file_type}") + except PlotlyError as err: + logging.error(f" Finished with error: {repr(err)}") + + +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. + :param input_data: Data to process. + :type plot: pandas.Series + :type input_data: InputData + """ + + # Transform the 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"latency", u"throughput", u"parent", u"tags", u"type"] + )[0][0] + elif plot.get(u"filter", None): + data = input_data.filter_data( + plot, + params=[u"latency", u"throughput", u"parent", u"tags", u"type"], + continue_on_error=True + ) + 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 + + 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" + ] + + file_links = plot.get(u"output-file-links", None) + target_links = plot.get(u"target-links", None) + + for test in data: + try: + 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"{desc[graph]}
" + f"Direction: {(u'W-E', u'E-W')[idx % 2]}
" + f"Percentile: 0.0%
" + 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"{desc[graph]}
" + f"Direction: {(u'W-E', u'E-W')[idx % 2]}
" + f"Percentile: {percentile:.5f}%
" + 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"Latency: {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: + # 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 fw: + fw.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)}") + + except hdrh.codec.HdrLengthException as err: + logging.warning(repr(err)) + continue + + except (ValueError, KeyError) as err: + logging.warning(repr(err)) + continue + + +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. + :param input_data: Data to process. + :type plot: pandas.Series + :type input_data: InputData + """ + + # Transform the data + 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=[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 + directions = [u"W-E", u"E-W"] + tests = list() + traces = 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}
" + f"Direction: {directions[idx_col]}
" + f"Latency: {item.value_iterated_to}uSec
" + f"Probability: {prob:.2f}%
" + 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)) + + if not tests: + logging.warning(f"No data for {plot_title}.") + return + + 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"Latency: {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"{test}", + 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: + # Export Plot + ploff.plot(fig, show_link=False, auto_open=False, + filename=f"{plot[u'output-file']}{file_type}") + except PlotlyError as err: + logging.error(f" Finished with error: {repr(err)}") + + 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. @@ -1190,15 +1629,12 @@ def plot_nf_heatmap(plot, input_data): plpl = plgo.Figure(data=traces, layout=layout) # Export Plot - logging.info( - f" Writing file {plot[u'output-file']}" - f"{plot[u'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']}{plot[u'output-file-type']}" + filename=f"{plot[u'output-file']}.html" ) except PlotlyError as err: logging.error(