-# Copyright (c) 2018 Cisco and/or its affiliates.
+# Copyright (c) 2021 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:
"""
+import re
import logging
+
+from collections import OrderedDict
+from datetime import datetime
+from copy import deepcopy
+from math import log
+
+import hdrh.histogram
+import hdrh.codec
import pandas as pd
import plotly.offline as ploff
import plotly.graph_objs as plgo
+import plotly.exceptions as plerr
from plotly.exceptions import PlotlyError
-from collections import OrderedDict
-from copy import deepcopy
-from utils import mean
+from pal_utils import mean, stdev
+
+COLORS = (
+ u"#1A1110",
+ u"#DA2647",
+ u"#214FC6",
+ u"#01786F",
+ u"#BD8260",
+ u"#FFD12A",
+ u"#A6E7FF",
+ u"#738276",
+ u"#C95A49",
+ u"#FC5A8D",
+ u"#CEC8EF",
+ u"#391285",
+ u"#6F2DA8",
+ u"#FF878D",
+ u"#45A27D",
+ u"#FFD0B9",
+ u"#FD5240",
+ u"#DB91EF",
+ u"#44D7A8",
+ u"#4F86F7",
+ u"#84DE02",
+ u"#FFCFF1",
+ u"#614051"
+)
-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"]
+REGEX_NIC = re.compile(r'(\d*ge\dp\d\D*\d*[a-z]*)-')
+
+# This value depends on latency stream rate (9001 pps) and duration (5s).
+# Keep it slightly higher to ensure rounding errors to not remove tick mark.
+PERCENTILE_MAX = 99.999501
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_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_hdrh_lat_by_percentile": plot_hdrh_lat_by_percentile,
+ u"plot_hdrh_lat_by_percentile_x_log": plot_hdrh_lat_by_percentile_x_log,
+ u"plot_mrr_box_name": plot_mrr_box_name,
+ u"plot_ndrpdr_box_name": plot_ndrpdr_box_name,
+ u"plot_statistics": plot_statistics
+ }
+
+ 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.environment[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_statistics(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_statistics
+ specified in the specification file.
+
+ :param plot: Plot to generate.
+ :param input_data: Data to process.
+ :type plot: pandas.Series
+ :type input_data: InputData
+ """
+
+ data_x = list()
+ data_y_pass = list()
+ data_y_fail = list()
+ data_y_duration = list()
+ hover_text = list()
+ hover_str = (
+ u"date: {date}<br>"
+ u"passed: {passed}<br>"
+ u"failed: {failed}<br>"
+ u"duration: {duration}<br>"
+ u"{sut}-ref: {build}<br>"
+ u"csit-ref: {test}-{period}-build-{build_nr}<br>"
+ u"testbed: {testbed}"
+ )
+ for job, builds in plot[u"data"].items():
+ for build_nr in builds:
+ try:
+ meta = input_data.metadata(job, str(build_nr))
+ generated = meta[u"generated"]
+ date = datetime(
+ int(generated[0:4]),
+ int(generated[4:6]),
+ int(generated[6:8]),
+ int(generated[9:11]),
+ int(generated[12:])
+ )
+ d_y_pass = meta[u"tests_passed"]
+ d_y_fail = meta[u"tests_failed"]
+ minutes = meta[u"elapsedtime"] // 60000
+ duration = f"{(minutes // 60):02d}:{(minutes % 60):02d}"
+ version = meta[u"version"]
+ except (KeyError, IndexError, ValueError, AttributeError):
+ continue
+ data_x.append(date)
+ data_y_pass.append(d_y_pass)
+ data_y_fail.append(d_y_fail)
+ data_y_duration.append(minutes)
+ hover_text.append(hover_str.format(
+ date=date,
+ passed=d_y_pass,
+ failed=d_y_fail,
+ duration=duration,
+ sut=u"vpp" if u"vpp" in job else u"dpdk",
+ build=version,
+ test=u"mrr" if u"mrr" in job else u"ndrpdr",
+ period=u"daily" if u"daily" in job else u"weekly",
+ build_nr=build_nr,
+ testbed=meta[u"testbed"]
+ ))
+
+ traces = [
+ plgo.Bar(
+ x=data_x,
+ y=data_y_pass,
+ name=u"Passed",
+ text=hover_text,
+ hoverinfo=u"text"
+ ),
+ plgo.Bar(
+ x=data_x,
+ y=data_y_fail,
+ name=u"Failed",
+ text=hover_text,
+ hoverinfo=u"text"),
+ plgo.Scatter(
+ x=data_x,
+ y=data_y_duration,
+ name=u"Duration",
+ yaxis=u"y2",
+ text=hover_text,
+ hoverinfo=u"text"
+ )
+ ]
+ name_file = f"{plot[u'output-file']}.html"
-def plot_performance_box(plot, input_data):
- """Generate the plot(s) with algorithm: plot_performance_box
+ logging.info(f" Writing the file {name_file}")
+ plpl = plgo.Figure(data=traces, layout=plot[u"layout"])
+ tickvals = [0, (max(data_y_duration) // 60) * 60]
+ step = tickvals[1] / 5
+ for i in range(5):
+ tickvals.append(int(tickvals[0] + step * (i + 1)))
+ plpl.update_layout(
+ yaxis2=dict(
+ title=u"Duration [hh:mm]",
+ anchor=u"x",
+ overlaying=u"y",
+ side=u"right",
+ rangemode="tozero",
+ tickmode=u"array",
+ tickvals=tickvals,
+ ticktext=[f"{(val // 60):02d}:{(val % 60):02d}" for val in tickvals]
+ )
+ )
+ plpl.update_layout(barmode=u"stack")
+ try:
+ ploff.plot(
+ plpl,
+ show_link=False,
+ auto_open=False,
+ filename=name_file
+ )
+ except plerr.PlotlyEmptyDataError:
+ logging.warning(u"No data for the plot. Skipped.")
+
+
+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.
"""
# 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 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
+
+ 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")):
+ previous_x = 0.0
+ xaxis = list()
+ yaxis = list()
+ hovertext = list()
+ try:
+ decoded = hdrh.histogram.HdrHistogram.decode(
+ test[u"latency"][graph][direction][u"hdrh"]
+ )
+ except hdrh.codec.HdrLengthException:
+ logging.warning(
+ f"No data for direction {(u'W-E', u'E-W')[idx % 2]}"
+ )
+ continue
+
+ for item in decoded.get_recorded_iterator():
+ percentile = item.percentile_level_iterated_to
+ xaxis.append(previous_x)
+ 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: "
+ f"{previous_x:.5f}-{percentile:.5f}%<br>"
+ f"Latency: {item.value_iterated_to}uSec"
+ )
+ 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: "
+ f"{previous_x:.5f}-{percentile:.5f}%<br>"
+ f"Latency: {item.value_iterated_to}uSec"
+ )
+ previous_x = percentile
+ 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",
+ width=1 if idx % 2 else 2
+ ),
+ 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:
+ # 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)}")
+
+ except hdrh.codec.HdrLengthException as err:
+ logging.warning(repr(err))
+ continue
+
+ except (ValueError, KeyError) as err:
+ logging.warning(repr(err))
+ continue
+
+
+def plot_hdrh_lat_by_percentile_x_log(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_hdrh_lat_by_percentile_x_log
+ 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"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
+
+ 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")):
+ previous_x = 0.0
+ prev_perc = 0.0
+ xaxis = list()
+ yaxis = list()
+ hovertext = list()
+ try:
+ decoded = hdrh.histogram.HdrHistogram.decode(
+ test[u"latency"][graph][direction][u"hdrh"]
+ )
+ except (hdrh.codec.HdrLengthException, TypeError):
+ logging.warning(
+ f"No data for direction {(u'W-E', u'E-W')[idx % 2]}"
+ )
+ continue
+
+ for item in decoded.get_recorded_iterator():
+ # The real value is "percentile".
+ # For 100%, we cut that down to "x_perc" to avoid
+ # infinity.
+ percentile = item.percentile_level_iterated_to
+ x_perc = min(percentile, PERCENTILE_MAX)
+ xaxis.append(previous_x)
+ 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: {prev_perc:.5f}-{percentile:.5f}%<br>"
+ f"Latency: {item.value_iterated_to}uSec"
+ )
+ next_x = 100.0 / (100.0 - x_perc)
+ xaxis.append(next_x)
+ 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: {prev_perc:.5f}-{percentile:.5f}%<br>"
+ f"Latency: {item.value_iterated_to}uSec"
+ )
+ previous_x = next_x
+ prev_perc = percentile
+ fig.add_trace(
+ plgo.Scatter(
+ x=xaxis,
+ y=yaxis,
+ name=desc[graph],
+ mode=u"lines",
+ legendgroup=desc[graph],
+ showlegend=not(bool(idx)),
+ line=dict(
+ color=COLORS[color],
+ dash=u"solid",
+ width=1 if idx % 2 else 2
+ ),
+ hovertext=hovertext,
+ hoverinfo=u"text"
+ )
+ )
+
+ layout[u"title"][u"text"] = f"<b>Latency:</b> {name}"
+ x_max = log(100.0 / (100.0 - PERCENTILE_MAX), 10)
+ layout[u"xaxis"][u"range"] = [0, x_max]
+ 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 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)}")
+
+ except hdrh.codec.HdrLengthException as err:
+ logging.warning(repr(err))
+ continue
+
+ except (ValueError, KeyError) as err:
+ logging.warning(repr(err))
+ continue
+
+
+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.
+ :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'')}."
+ )
+ data = input_data.filter_tests_by_name(
+ plot, params=[u"result", u"parent", u"tags", u"type"]
+ )
if data is None:
- logging.error("No data.")
+ logging.error(u"No data.")
+ return
+
+ for core in plot.get(u"core", tuple()):
+ # Prepare the data for the plot
+ y_vals = OrderedDict()
+ loss = dict()
+ for item in plot.get(u"include", tuple()):
+ reg_ex = re.compile(str(item.format(core=core)).lower())
+ for job in data:
+ for build in job:
+ for test_id, test in build.iteritems():
+ if not re.match(reg_ex, str(test_id).lower()):
+ continue
+ if y_vals.get(test[u"parent"], None) is None:
+ y_vals[test[u"parent"]] = list()
+ loss[test[u"parent"]] = list()
+ try:
+ y_vals[test[u"parent"]].append(
+ test[u"result"][u"time"]
+ )
+ loss[test[u"parent"]].append(
+ test[u"result"][u"loss"]
+ )
+ except (KeyError, TypeError):
+ 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_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()
+ 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'-reconf', u'').replace(u'2n1l-', u'').
+ replace(u'2n-', u'').replace(u'-testpmd', u'')
+ )
+ traces.append(plgo.Box(
+ x=[str(i + 1) + u'.'] * len(df_y[col]),
+ y=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'-')[2:])}"
+ ),
+ hoverinfo=u"y+name"
+ ))
+ try:
+ # Create plot
+ layout = deepcopy(plot[u"layout"])
+ layout[u"title"] = f"<b>Time Lost:</b> {layout[u'title']}"
+ layout[u"yaxis"][u"title"] = u"<b>Effective Blocked Time [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
+ file_name = f"{plot[u'output-file'].format(core=core)}.html"
+ logging.info(f" Writing file {file_name}")
+ ploff.plot(
+ plpl,
+ show_link=False,
+ auto_open=False,
+ filename=file_name
+ )
+ except PlotlyError as err:
+ logging.error(
+ f" Finished with error: {repr(err)}".replace(u"\n", u" ")
+ )
+
+
+def plot_perf_box_name(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_perf_box_name
+ specified in the specification file.
+
+ Use only for soak and hoststack tests.
+
+ :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 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"gbps", u"result", u"parent", u"tags", u"type"])
+ if data is None:
+ logging.error(u"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"])
+ y_vals = OrderedDict()
+ test_type = u""
+
+ for item in plot.get(u"include", tuple()):
+ reg_ex = re.compile(str(item).lower())
+ for job in data:
+ for build in job:
+ for test_id, test in build.iteritems():
+ if not re.match(reg_ex, str(test_id).lower()):
+ continue
+ if y_vals.get(test[u"parent"], None) is None:
+ y_vals[test[u"parent"]] = list()
+ try:
+ if 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"
+
+ elif test[u"type"] in (u"LDP_NGINX",):
+ if u"TCP_CPS" in test[u"tags"]:
+ test_type = u"VSAP_CPS"
+ y_vals[test[u"parent"]].append(
+ test[u"result"][u"cps"]
+ )
+ elif u"TCP_RPS" in test[u"tags"]:
+ test_type = u"VSAP_RPS"
+ y_vals[test[u"parent"]].append(
+ test[u"result"][u"rps"]
+ )
+ else:
+ continue
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.info(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.info(suite)
- except KeyError as err:
- logging.error("Not found: {0}".format(err))
- finally:
- break
- else:
- y_sorted = y_vals
+
+ except (KeyError, TypeError):
+ y_vals[test[u"parent"]].append(None)
# Add None to the lists with missing data
max_len = 0
- for val in y_sorted.values():
+ nr_of_samples = list()
+ for val in y_vals.values():
if len(val) > max_len:
max_len = len(val)
- for key, val in y_sorted.items():
+ 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()
- 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):
- name = "{0}. {1}".format(i + 1, col.lower().replace('-ndrpdrdisc', '').
- replace('-ndrpdr', ''))
- logging.info(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"]))
- val_max = max(df[col])
- if val_max:
- y_max.append(int(val_max / 1000000) + 1)
+ 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''))
+ if test_type in (u"VSAP_CPS", u"VSAP_RPS"):
+ data_y = [y if y else None for y in df_y[col]]
+ else:
+ data_y = [y / 1e6 if y else None for y in df_y[col]]
+ kwargs = dict(
+ x=[str(i + 1) + u'.'] * len(df_y[col]),
+ y=data_y,
+ 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_y[col])
+ if val_max:
+ y_max.append(int(val_max / 1e6))
+ except (ValueError, TypeError) as err:
+ logging.error(repr(err))
+ continue
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, max(y_max)]
+ 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']}"
+ elif test_type == u"VSAP_CPS":
+ layout[u"title"] = f"<b>CPS:</b> {layout[u'title']}"
+ layout[u"yaxis"][u"title"] = u"<b>Connection Rate [cps]</b>"
+ elif test_type == u"VSAP_RPS":
+ layout[u"title"] = f"<b>RPS:</b> {layout[u'title']}"
+ layout[u"yaxis"][u"title"] = u"<b>Connection Rate [rps]</b>"
+ else:
+ layout[u"title"] = f"<b>Tput:</b> {layout[u'title']}"
+ if y_max and max(y_max) > 1:
+ layout[u"yaxis"][u"range"] = [0, max(y_max) + 2]
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
-def plot_latency_error_bars(plot, input_data):
- """Generate the plot(s) with algorithm: plot_latency_error_bars
+def plot_ndrpdr_box_name(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_ndrpdr_box_name
specified in the specification file.
:param plot: Plot to generate.
"""
# 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"gbps", 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()
- for job in data:
- for build in job:
- for test in build:
- 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)
+ if u"-gbps" in plot.get(u"title", u"").lower():
+ value = u"gbps"
+ multiplier = 1e6
+ else:
+ value = u"throughput"
+ multiplier = 1.0
+
+ test_type = u""
+
+ for ttype in plot.get(u"test-type", (u"ndr", u"pdr")):
+ for core in plot.get(u"core", tuple()):
+ # Prepare the data for the plot
+ data_x = list()
+ data_y = OrderedDict()
+ data_y_max = list()
+ idx = 1
+ for item in plot.get(u"include", tuple()):
+ reg_ex = re.compile(str(item.format(core=core)).lower())
+ for job in data:
+ for build in job:
+ for test_id, test in build.iteritems():
+ if not re.match(reg_ex, str(test_id).lower()):
+ continue
+ if data_y.get(test[u"parent"], None) is None:
+ data_y[test[u"parent"]] = list()
+ test_type = test[u"type"]
+ data_x.append(idx)
+ idx += 1
+ try:
+ data_y[test[u"parent"]].append(
+ test[value][ttype.upper()][u"LOWER"] *
+ multiplier
+ )
+ except (KeyError, TypeError):
+ pass
+
+ # Add plot traces
+ traces = list()
+ for idx, (key, vals) in enumerate(data_y.items()):
+ name = re.sub(
+ REGEX_NIC, u'', key.lower().replace(u'-ndrpdr', u'').
+ replace(u'2n1l-', u'')
+ )
+ traces.append(
+ plgo.Box(
+ x=[data_x[idx], ] * len(data_x),
+ y=[y / 1e6 if y else None for y in vals],
+ name=(
+ f"{idx+1}."
+ f"({len(vals):02d} "
+ f"run"
+ f"{u's' if len(vals) > 1 else u''}) "
+ f"{name}"
+ ),
+ hoverinfo=u"y+name"
+ )
+ )
try:
- if test["type"] in ("NDRPDR", ):
- if "-pdr" in plot_title.lower():
- ttype = "PDR"
- elif "-ndr" in plot_title.lower():
- ttype = "NDR"
- else:
- 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"])
+ data_y_max.append(max(vals))
+ except ValueError as err:
+ logging.warning(f"No values to use.\n{err!r}")
+ try:
+ # Create plot
+ layout = deepcopy(plot[u"layout"])
+ if layout.get(u"title", None):
+ layout[u"title"] = \
+ layout[u'title'].format(core=core, test_type=ttype)
+ if test_type in (u"CPS", ):
+ layout[u"title"] = f"<b>CPS:</b> {layout[u'title']}"
else:
- continue
- except (KeyError, TypeError):
- pass
-
- # 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 suite, tags in y_tags_l.items():
- if tag.lower() in tags:
- try:
- y_sorted[suite] = y_tmp_vals.pop(suite)
- y_tags_l.pop(suite)
- except KeyError as err:
- logging.error("Not found: {0}".format(err))
- finally:
- break
- else:
- y_sorted = y_tmp_vals
-
- x_vals = list()
- y_vals = list()
- y_mins = list()
- y_maxs = list()
- for key, val in y_sorted.items():
- key = "-".join(key.split("-")[1:-1])
- x_vals.append(key) # dir 1
- y_vals.append(mean(val[1]) if val[1] else None)
- y_mins.append(mean(val[0]) if val[0] else None)
- y_maxs.append(mean(val[2]) if val[2] else None)
- x_vals.append(key) # dir 2
- y_vals.append(mean(val[4]) if val[4] else None)
- y_mins.append(mean(val[3]) if val[3] else None)
- y_maxs.append(mean(val[5]) if val[5] else None)
+ layout[u"title"] = \
+ f"<b>Tput:</b> {layout[u'title']}"
+ if data_y_max:
+ layout[u"yaxis"][u"range"] = [0, max(data_y_max) / 1e6 + 1]
+ plpl = plgo.Figure(data=traces, layout=layout)
- traces = list()
- annotations = list()
+ # Export Plot
+ file_name = (
+ f"{plot[u'output-file'].format(core=core, test_type=ttype)}"
+ f".html"
+ )
+ logging.info(f" Writing file {file_name}")
+ ploff.plot(
+ plpl,
+ show_link=False,
+ auto_open=False,
+ filename=file_name
+ )
+ except PlotlyError as err:
+ logging.error(
+ f" Finished with error: {repr(err)}".replace(u"\n", u" ")
+ )
- for idx in range(len(x_vals)):
- if not bool(int(idx % 2)):
- direction = "West - East"
- else:
- direction = "East - West"
- hovertext = ("Test: {test}<br>"
- "Direction: {dir}<br>".format(test=x_vals[idx],
- dir=direction))
- if isinstance(y_maxs[idx], float):
- hovertext += "Max: {max:.2f}uSec<br>".format(max=y_maxs[idx])
- if isinstance(y_vals[idx], float):
- hovertext += "Avg: {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 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
- ))
- 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>Packet Latency:</b> {0}".\
- format(layout["title"])
- layout["annotations"] = annotations
- plpl = plgo.Figure(data=traces, layout=layout)
+def plot_mrr_box_name(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_mrr_box_name
+ specified in the specification file.
- # 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", " ")))
+ :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 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"result", u"parent", u"tags", u"type"]
+ )
+ if data is None:
+ logging.error(u"No data.")
return
+ for core in plot.get(u"core", tuple()):
+ # Prepare the data for the plot
+ data_x = list()
+ data_names = list()
+ data_y = list()
+ data_y_max = list()
+ idx = 1
+ for item in plot.get(u"include", tuple()):
+ reg_ex = re.compile(str(item.format(core=core)).lower())
+ for job in data:
+ for build in job:
+ for test_id, test in build.iteritems():
+ if not re.match(reg_ex, str(test_id).lower()):
+ continue
+ try:
+ data_x.append(idx)
+ name = re.sub(
+ REGEX_NIC, u'', test[u'parent'].lower().
+ replace(u'-mrr', u'').replace(u'2n1l-', u'')
+ )
+ data_y.append(test[u"result"][u"samples"])
+ data_names.append(
+ f"{idx}."
+ f"({len(data_y[-1]):02d} "
+ f"run{u's' if len(data_y[-1]) > 1 else u''}) "
+ f"{name}"
+ )
+ data_y_max.append(max(data_y[-1]))
+ idx += 1
+ except (KeyError, TypeError):
+ pass
+
+ # Add plot traces
+ traces = list()
+ for idx, x_item in enumerate(data_x):
+ traces.append(
+ plgo.Box(
+ x=[x_item, ] * len(data_y[idx]),
+ y=data_y[idx],
+ name=data_names[idx],
+ hoverinfo=u"y+name"
+ )
+ )
+
+ try:
+ # Create plot
+ layout = deepcopy(plot[u"layout"])
+ if layout.get(u"title", None):
+ layout[u"title"] = (
+ f"<b>Tput:</b> {layout[u'title'].format(core=core)}"
+ )
+ if data_y_max:
+ layout[u"yaxis"][u"range"] = [0, max(data_y_max) + 1]
+ plpl = plgo.Figure(data=traces, layout=layout)
-def plot_throughput_speedup_analysis(plot, input_data):
+ # Export Plot
+ file_name = f"{plot[u'output-file'].format(core=core)}.html"
+ logging.info(f" Writing file {file_name}")
+ ploff.plot(
+ plpl,
+ show_link=False,
+ auto_open=False,
+ filename=file_name
+ )
+ except PlotlyError as err:
+ logging.error(
+ f" Finished with error: {repr(err)}".replace(u"\n", u" ")
+ )
+
+
+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.
:param plot: Plot to generate.
"""
# 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"gbps", 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()
- 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
+ plot_title = plot_title.lower()
- if not y_vals:
- logging.warning("No data for the plot '{}'".
- format(plot.get("title", "")))
- return
+ if u"-gbps" in plot_title:
+ value = u"gbps"
+ h_unit = u"Gbps"
+ multiplier = 1e6
+ else:
+ value = u"throughput"
+ h_unit = u"Mpps"
+ multiplier = 1.0
- y_1c_max = dict()
- for test_name, test_vals in y_vals.items():
- for key, test_val in test_vals.items():
- if test_val:
- y_vals[test_name][key] = sum(test_val) / len(test_val)
- if key == "1":
- y_1c_max[test_name] = max(test_val) / 1000000.0
+ for ttype in plot.get(u"test-type", (u"ndr", u"pdr")):
+ y_vals = OrderedDict()
+ for item in plot.get(u"include", tuple()):
+ reg_ex = re.compile(str(item).lower())
+ for job in data:
+ for build in job:
+ for test_id, test in build.iteritems():
+ if re.match(reg_ex, str(test_id).lower()):
+ 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[u"type"] not in (u"NDRPDR", u"CPS"):
+ continue
- 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():
- if test_vals["1"]:
- name = "-".join(test_name.split('-')[1:-1])
-
- vals[name] = dict()
- y_val_1 = test_vals["1"] / 1000000.0
- y_val_2 = test_vals["2"] / 1000000.0 if test_vals["2"] else None
- y_val_4 = test_vals["4"] / 1000000.0 if test_vals["4"] else None
-
- vals[name]["val"] = [y_val_1, y_val_2, y_val_4]
- vals[name]["rel"] = [1.0, None, None]
- vals[name]["ideal"] = [y_1c_max[test_name],
- y_1c_max[test_name] * 2,
- y_1c_max[test_name] * 4]
- vals[name]["diff"] = \
- [(y_val_1 - y_1c_max[test_name]) * 100 / y_val_1, None, None]
+ if u"1C" in test[u"tags"]:
+ y_vals[test[u"parent"]][u"1"].append(
+ test[value][ttype.upper()][u"LOWER"] *
+ multiplier
+ )
+ elif u"2C" in test[u"tags"]:
+ y_vals[test[u"parent"]][u"2"].append(
+ test[value][ttype.upper()][u"LOWER"] *
+ multiplier
+ )
+ elif u"4C" in test[u"tags"]:
+ y_vals[test[u"parent"]][u"4"].append(
+ test[value][ttype.upper()][u"LOWER"] *
+ multiplier
+ )
+ except (KeyError, TypeError):
+ pass
+
+ if not y_vals:
+ logging.warning(f"No data for the plot {plot.get(u'title', u'')}")
+ 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) * 1e6)
+ 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 = 0
+ for test_name, test_vals in y_vals.items():
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 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[u"4"][0] / 1e6 if test_vals[u"4"][0] \
+ else None
- 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
+ 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]
+ ]
- # 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"]
- 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
+ val_max = max(vals[name][u"val"])
+ except ValueError as err:
+ logging.error(repr(err))
+ continue
+ if val_max:
+ y_max.append(val_max)
- traces = list()
- annotations = list()
- x_vals = [1, 2, 4]
+ if 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][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(f"No data for {test_name}")
+ logging.warning(repr(err))
- # 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()
- for idx in range(len(val["val"])):
- htext = ""
- if isinstance(val["val"][idx], float):
- htext += "value: {0:.2f}Mpps<br>".format(val["val"][idx])
- if isinstance(val["diff"][idx], float):
- htext += "diff: {0:.0f}%<br>".format(round(val["diff"][idx]))
- if isinstance(val["rel"][idx], float):
- htext += "speedup: {0:.2f}".format(val["rel"][idx])
- hovertext.append(htext)
- traces.append(plgo.Scatter(x=x_vals,
- y=val["val"],
- name=name,
- legendgroup=name,
- mode="lines+markers",
- line=dict(
- color=COLORS[cidx],
- width=2),
- marker=dict(
- symbol="circle",
- size=10
- ),
- text=hovertext,
- hoverinfo="text+name"
- ))
- traces.append(plgo.Scatter(x=x_vals,
- y=val["ideal"],
- name="{0} perfect".format(name),
- legendgroup=name,
- showlegend=False,
- mode="lines",
- line=dict(
- color=COLORS[cidx],
- width=2,
- dash="dash"),
- text=["perfect: {0:.2f}Mpps".format(y)
- for y in val["ideal"]],
- hoverinfo="text"
- ))
- cidx += 1
+ # Limits:
+ 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"]
+ elif u"e810cq" in test_name:
+ limit = plot[u"limits"][u"nic"][u"e810cq"]
+ else:
+ limit = 0
+ if limit > nic_limit:
+ nic_limit = limit
- 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["annotations"].extend(annotations)
- plpl = plgo.Figure(data=traces, layout=layout)
+ 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
- # 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
+ if u"cx556a" in test_name:
+ limit = plot[u"limits"][u"pci"][u"pci-g3-x8"]
+ else:
+ limit = plot[u"limits"][u"pci"][u"pci-g3-x16"]
+ if limit > pci_limit:
+ pci_limit = limit
+
+ traces = list()
+ annotations = list()
+ x_vals = [1, 2, 4]
+
+ # Limits:
+ if u"-gbps" not in plot_title and u"-cps-" not in plot_title:
+ nic_limit /= 1e6
+ lnk_limit /= 1e6
+ pci_limit /= 1e6
+ min_limit = min((nic_limit, lnk_limit, pci_limit))
+ if nic_limit == min_limit:
+ traces.append(plgo.Scatter(
+ x=x_vals,
+ y=[nic_limit, ] * len(x_vals),
+ name=f"NIC: {nic_limit:.2f}Mpps",
+ showlegend=False,
+ mode=u"lines",
+ line=dict(
+ dash=u"dot",
+ color=COLORS[-1],
+ width=1),
+ hoverinfo=u"none"
+ ))
+ annotations.append(dict(
+ x=1,
+ y=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=u"left",
+ showarrow=False
+ ))
+ y_max.append(nic_limit)
+ elif lnk_limit == min_limit:
+ traces.append(plgo.Scatter(
+ x=x_vals,
+ y=[lnk_limit, ] * len(x_vals),
+ name=f"Link: {lnk_limit:.2f}Mpps",
+ showlegend=False,
+ mode=u"lines",
+ line=dict(
+ dash=u"dot",
+ color=COLORS[-1],
+ width=1),
+ hoverinfo=u"none"
+ ))
+ annotations.append(dict(
+ x=1,
+ y=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[-1],
+ ),
+ align=u"left",
+ showarrow=False
+ ))
+ y_max.append(lnk_limit)
+ elif pci_limit == min_limit:
+ traces.append(plgo.Scatter(
+ x=x_vals,
+ y=[pci_limit, ] * len(x_vals),
+ name=f"PCIe: {pci_limit:.2f}Mpps",
+ showlegend=False,
+ mode=u"lines",
+ line=dict(
+ dash=u"dot",
+ color=COLORS[-1],
+ width=1),
+ hoverinfo=u"none"
+ ))
+ annotations.append(dict(
+ x=1,
+ y=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[-1],
+ ),
+ align=u"left",
+ showarrow=False
+ ))
+ y_max.append(pci_limit)
+
+ # Perfect and measured:
+ cidx = 0
+ for name, val in vals.items():
+ hovertext = list()
+ try:
+ for idx in range(len(val[u"val"])):
+ htext = ""
+ if isinstance(val[u"val"][idx], float):
+ htext += (
+ f"No. of Runs: {val[u'count'][idx]}<br>"
+ f"Mean: {val[u'val'][idx]:.2f}{h_unit}<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[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(f"No data for {name}\n{repr(err)}")
+
+ try:
+ # Create plot
+ file_name = f"{plot[u'output-file'].format(test_type=ttype)}.html"
+ logging.info(f" Writing file {file_name}")
+ layout = deepcopy(plot[u"layout"])
+ if layout.get(u"title", None):
+ layout[u"title"] = (
+ f"<b>Speedup Multi-core:</b> "
+ f"{layout[u'title'].format(test_type=ttype)}"
+ )
+ 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=file_name
+ )
+ except PlotlyError as err:
+ logging.error(
+ f" Finished with error: {repr(err)}".replace(u"\n", u" ")
+ )
-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.
"""
# 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
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
+ nr_of_samples = list()
for val in y_vals.values():
if len(val) > max_len:
max_len = len(val)
- for key, val in y_vals.items():
+ 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()
- df = pd.DataFrame(y_vals)
- df.head()
- for i, col in enumerate(df.columns):
- name = "{0}. {1}".format(i + 1, col.lower().replace('-cps', '').
- replace('-rps', ''))
- traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]),
- y=df[col],
+ 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(u'-')
+ name = u""
+ split_name = True
+ for segment in name_lst:
+ if (len(name) + len(segment) + 1) > 50 and split_name:
+ name += u"<br> "
+ split_name = False
+ name += segment + u'-'
+ name = name[:-1]
+
+ 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_nf_heatmap(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_nf_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
+ """
+
+ 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)
+
+ regex_cn = re.compile(r'^(\d*)R(\d*)C$')
+ regex_test_name = re.compile(r'^.*-(\d+ch|\d+pl)-'
+ r'(\d+mif|\d+vh)-'
+ r'(\d+vm\d+t|\d+dcr\d+t|\d+dcr\d+c).*$')
+ vals = dict()
+
+ # Transform the data
+ logging.info(
+ f" Creating the data set for the {plot.get(u'type', u'')} "
+ f"{plot.get(u'title', u'')}."
+ )
+ in_data = input_data.filter_tests_by_name(
+ plot,
+ continue_on_error=True,
+ params=[u"throughput", u"result", u"name", u"tags", u"type"]
+ )
+ if in_data is None or in_data.empty:
+ logging.error(u"No data.")
+ return
+
+ for ttype in plot.get(u"test-type", (u"ndr", u"pdr")):
+ for core in plot.get(u"core", tuple()):
+ for item in plot.get(u"include", tuple()):
+ reg_ex = re.compile(str(item.format(core=core)).lower())
+ for job in in_data:
+ for build in job:
+ for test_id, test in build.iteritems():
+ if not re.match(reg_ex, str(test_id).lower()):
+ continue
+ for tag in test[u"tags"]:
+ groups = re.search(regex_cn, tag)
+ if groups:
+ chain = str(groups.group(1))
+ node = str(groups.group(2))
+ break
+ else:
+ continue
+ groups = re.search(regex_test_name, test[u"name"])
+ if groups and len(groups.groups()) == 3:
+ hover_name = (
+ f"{str(groups.group(1))}-"
+ f"{str(groups.group(2))}-"
+ f"{str(groups.group(3))}"
+ )
+ else:
+ 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 ttype == u"mrr":
+ result = test[u"result"][u"receive-rate"]
+ elif ttype == u"pdr":
+ result = \
+ test[u"throughput"][u"PDR"][u"LOWER"]
+ elif ttype == u"ndr":
+ result = \
+ test[u"throughput"][u"NDR"][u"LOWER"]
+ else:
+ result = None
+ except TypeError:
+ result = None
+
+ if result:
+ vals[chain][node][u"vals"].append(result)
+
+ if not vals:
+ logging.error(u"No data.")
+ return
+
+ 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][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"]) / 1e6, 1)
+ vals[key_c][key_n][u"stdev"] = \
+ round(stdev(vals[key_c][key_n][u"vals"]) / 1e6, 1)
+ txt_nodes = list(set(txt_nodes))
+
+ 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 chain in chains:
+ for node in nodes:
+ try:
+ val = vals[txt_chains[chain - 1]] \
+ [txt_nodes[node - 1]][u"mean"]
+ except (KeyError, IndexError):
+ val = None
+ data[chain - 1].append(val)
+
+ # Color scales:
+ my_green = [[0.0, u"rgb(235, 249, 242)"],
+ [1.0, u"rgb(45, 134, 89)"]]
+
+ my_blue = [[0.0, u"rgb(236, 242, 248)"],
+ [1.0, u"rgb(57, 115, 172)"]]
+
+ my_grey = [[0.0, u"rgb(230, 230, 230)"],
+ [1.0, u"rgb(102, 102, 102)"]]
+
+ hovertext = list()
+ annotations = list()
+
+ text = (u"Test: {name}<br>"
+ u"Runs: {nr}<br>"
+ u"Thput: {val}<br>"
+ u"StDev: {stdev}")
+
+ for chain, _ in enumerate(txt_chains):
+ hover_line = list()
+ 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[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(u"z-axis", u"{test_type}").
+ format(test_type=ttype.upper()),
+ 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=u"x",
+ yref=u"y",
+ xanchor=u"center",
+ yanchor=u"top",
+ text=item,
+ font=dict(
+ size=16,
+ ),
+ 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=u"x",
+ yref=u"y",
+ xanchor=u"right",
+ yanchor=u"middle",
+ text=item,
+ font=dict(
+ size=16,
+ ),
+ align=u"center",
+ showarrow=False
+ )
+ )
+ # 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=u"center",
+ showarrow=False
+ )
+ )
+ # 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=u"center",
+ textangle=270,
+ showarrow=False
+ )
+ )
+ updatemenus = list([
+ dict(
+ x=1.0,
+ y=0.0,
+ xanchor=u"right",
+ yanchor=u"bottom",
+ direction=u"up",
+ buttons=list([
+ dict(
+ args=[
+ {
+ u"colorscale": [my_green, ],
+ u"reversescale": False
+ }
+ ],
+ label=u"Green",
+ method=u"update"
+ ),
+ dict(
+ args=[
+ {
+ u"colorscale": [my_blue, ],
+ u"reversescale": False
+ }
+ ],
+ label=u"Blue",
+ method=u"update"
+ ),
+ dict(
+ args=[
+ {
+ u"colorscale": [my_grey, ],
+ u"reversescale": False
+ }
+ ],
+ label=u"Grey",
+ method=u"update"
+ )
+ ])
+ )
+ ])
+
+ try:
+ layout = deepcopy(plot[u"layout"])
+ except KeyError as err:
+ logging.error(
+ f"Finished with error: No layout defined\n{repr(err)}"
+ )
+ return
+
+ layout[u"annotations"] = annotations
+ layout[u'updatemenus'] = updatemenus
+ if layout.get(u"title", None):
+ layout[u"title"] = layout[u'title'].replace(u"test_type", ttype)
+
+ try:
+ # Create plot
+ plpl = plgo.Figure(data=traces, layout=layout)
+
+ # Export Plot
+ file_name = (
+ f"{plot[u'output-file'].format(core=core, test_type=ttype)}"
+ f".html"
+ )
+ logging.info(f" Writing file {file_name}")
+ ploff.plot(
+ plpl,
+ show_link=False,
+ auto_open=False,
+ filename=file_name
+ )
+ except PlotlyError as err:
+ logging.error(
+ f" Finished with error: {repr(err)}".replace(u"\n", u" ")
+ )
Code Review / csit.git / blobdiff