X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fgenerator_plots.py;h=05f525c96af4318d8b486f4a73efebd9d0787b2e;hp=3e5da63c9e53a651d221f3d0cb4cba6ee2d99330;hb=ef5c30213bb28824a55f4ebbcade6410ee8d2461;hpb=e2d15edc355f0c70df578dde0495f8ffd85d8c12
diff --git a/resources/tools/presentation/generator_plots.py b/resources/tools/presentation/generator_plots.py
index 3e5da63c9e..05f525c96a 100644
--- a/resources/tools/presentation/generator_plots.py
+++ b/resources/tools/presentation/generator_plots.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2019 Cisco and/or its affiliates.
+# Copyright (c) 2020 Cisco and/or its affiliates.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at:
@@ -17,25 +17,49 @@
import re
import logging
+
+import hdrh.histogram
+import hdrh.codec
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 math import log
-from utils import mean, stdev
-
-
-COLORS = ["SkyBlue", "Olive", "Purple", "Coral", "Indigo", "Pink",
- "Chocolate", "Brown", "Magenta", "Cyan", "Orange", "Black",
- "Violet", "Blue", "Yellow", "BurlyWood", "CadetBlue", "Crimson",
- "DarkBlue", "DarkCyan", "DarkGreen", "Green", "GoldenRod",
- "LightGreen", "LightSeaGreen", "LightSkyBlue", "Maroon",
- "MediumSeaGreen", "SeaGreen", "LightSlateGrey"]
+from plotly.exceptions import PlotlyError
-REGEX_NIC = re.compile(r'\d*ge\dp\d\D*\d*-')
+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"
+)
+
+REGEX_NIC = re.compile(r'(\d*ge\dp\d\D*\d*[a-z]*)-')
def generate_plots(spec, data):
@@ -47,22 +71,33 @@ 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
+ }
+
+ logging.info(u"Generating the plots ...")
for index, plot in enumerate(spec.plots):
try:
- logging.info(" Plot nr {0}: {1}".format(index + 1,
- plot.get("title", "")))
- plot["limits"] = spec.configuration["limits"]
- eval(plot["algorithm"])(plot, data)
- logging.info(" Done.")
+ logging.info(f" Plot nr {index + 1}: {plot.get(u'title', u'')}")
+ plot[u"limits"] = spec.configuration[u"limits"]
+ generator[plot[u"algorithm"]](plot, data)
+ logging.info(u" Done.")
except NameError as err:
- logging.error("Probably algorithm '{alg}' is not defined: {err}".
- format(alg=plot["algorithm"], err=repr(err)))
- logging.info("Done.")
+ logging.error(
+ f"Probably algorithm {plot[u'algorithm']} is not defined: "
+ f"{repr(err)}"
+ )
+ logging.info(u"Done.")
-def plot_service_density_reconf_box_name(plot, input_data):
- """Generate the plot(s) with algorithm: plot_service_density_reconf_box_name
+def plot_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.
@@ -72,98 +107,309 @@ def plot_service_density_reconf_box_name(plot, input_data):
"""
# Transform the data
- plot_title = plot.get("title", "")
- logging.info(" Creating the data set for the {0} '{1}'.".
- format(plot.get("type", ""), plot_title))
- data = input_data.filter_tests_by_name(
- plot, params=["result", "parent", "tags", "type"])
- if data is None:
- logging.error("No data.")
+ logging.info(
+ f" Creating the data set for the {plot.get(u'type', u'')} "
+ f"{plot.get(u'title', u'')}."
+ )
+ if plot.get(u"include", None):
+ data = input_data.filter_tests_by_name(
+ plot,
+ params=[u"name", u"latency", u"parent", u"tags", u"type"]
+ )[0][0]
+ elif plot.get(u"filter", None):
+ data = input_data.filter_data(
+ plot,
+ params=[u"name", u"latency", u"parent", u"tags", u"type"],
+ continue_on_error=True
+ )[0][0]
+ else:
+ job = list(plot[u"data"].keys())[0]
+ build = str(plot[u"data"][job][0])
+ data = input_data.tests(job, build)
+
+ if data is None or len(data) == 0:
+ logging.error(u"No data.")
return
- # Prepare the data for the plot
- y_vals = OrderedDict()
- loss = dict()
- for job in data:
- for build in job:
- for test in build:
- if y_vals.get(test["parent"], None) is None:
- y_vals[test["parent"]] = list()
- loss[test["parent"]] = list()
- try:
- y_vals[test["parent"]].append(test["result"]["time"])
- loss[test["parent"]].append(test["result"]["loss"])
- except (KeyError, TypeError):
- y_vals[test["parent"]].append(None)
+ desc = {
+ u"LAT0": u"No-load.",
+ u"PDR10": u"Low-load, 10% PDR.",
+ u"PDR50": u"Mid-load, 50% PDR.",
+ u"PDR90": u"High-load, 90% PDR.",
+ u"PDR": u"Full-load, 100% PDR.",
+ u"NDR10": u"Low-load, 10% NDR.",
+ u"NDR50": u"Mid-load, 50% NDR.",
+ u"NDR90": u"High-load, 90% NDR.",
+ u"NDR": u"Full-load, 100% NDR."
+ }
+
+ graphs = [
+ u"LAT0",
+ u"PDR10",
+ u"PDR50",
+ u"PDR90"
+ ]
- # Add None to the lists with missing data
- max_len = 0
- nr_of_samples = list()
- for val in y_vals.values():
- if len(val) > max_len:
- max_len = len(val)
- nr_of_samples.append(len(val))
- for key, val in y_vals.items():
- if len(val) < max_len:
- val.extend([None for _ in range(max_len - len(val))])
+ file_links = plot.get(u"output-file-links", None)
+ target_links = plot.get(u"target-links", None)
- # Add plot traces
- traces = list()
- df = pd.DataFrame(y_vals)
- df.head()
- y_max = list()
- for i, col in enumerate(df.columns):
- tst_name = re.sub(REGEX_NIC, "",
- col.lower().replace('-ndrpdr', '').
- replace('2n1l-', ''))
- tst_name = "-".join(tst_name.split("-")[3:-2])
- name = "{nr}. ({samples:02d} run{plural}, avg pkt loss: {loss:.1f}, " \
- "stdev: {stdev:.2f}) {name}".format(
- nr=(i + 1),
- samples=nr_of_samples[i],
- plural='s' if nr_of_samples[i] > 1 else '',
- name=tst_name,
- loss=mean(loss[col]) / 1000000,
- stdev=stdev(loss[col]) / 1000000)
-
- traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]),
- y=[y if y else None for y in df[col]],
- name=name,
- hoverinfo="x+y",
- boxpoints="outliers",
- whiskerwidth=0))
+ for test in data:
try:
- val_max = max(df[col])
- except ValueError as err:
- logging.error(repr(err))
+ 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 = 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
+ if percentile > 99.9999999:
+ 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"dash" if idx % 2 else u"solid"
+ ),
+ 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 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
- if val_max:
- y_max.append(int(val_max) + 1)
- try:
- # Create plot
- layout = deepcopy(plot["layout"])
- layout["title"] = "Time Lost: {0}".format(layout["title"])
- layout["yaxis"]["title"] = "Implied Time Lost [s]"
- layout["legend"]["font"]["size"] = 14
- if y_max:
- layout["yaxis"]["range"] = [0, max(y_max)]
- plpl = plgo.Figure(data=traces, layout=layout)
+ except (ValueError, KeyError) as err:
+ logging.warning(repr(err))
+ continue
- # Export Plot
- file_type = plot.get("output-file-type", ".html")
- logging.info(" Writing file '{0}{1}'.".
- format(plot["output-file"], file_type))
- ploff.plot(plpl, show_link=False, auto_open=False,
- filename='{0}{1}'.format(plot["output-file"], file_type))
- except PlotlyError as err:
- logging.error(" Finished with error: {}".
- format(repr(err).replace("\n", " ")))
+
+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"])
+ xaxis_max = 0
+
+ for color, graph in enumerate(graphs):
+ for idx, direction in enumerate((u"direction1", u"direction2")):
+ 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
+ if percentile > 99.9999999:
+ continue
+ xaxis.append(100.0 / (100.0 - 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=not(bool(idx)),
+ line=dict(
+ color=COLORS[color],
+ dash=u"dash" if idx % 2 else u"solid"
+ ),
+ hovertext=hovertext,
+ hoverinfo=u"text"
+ )
+ )
+ xaxis_max = max(xaxis) if xaxis_max < max(
+ xaxis) else xaxis_max
+
+ layout[u"title"][u"text"] = f"Latency: {name}"
+ layout[u"xaxis"][u"range"] = [0, int(log(xaxis_max, 10)) + 1]
+ 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_performance_box_name(plot, input_data):
- """Generate the plot(s) with algorithm: plot_performance_box_name
+
+def plot_nf_reconf_box_name(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_nf_reconf_box_name
specified in the specification file.
:param plot: Plot to generate.
@@ -173,39 +419,31 @@ def plot_performance_box_name(plot, input_data):
"""
# Transform the data
- plot_title = plot.get("title", "")
- logging.info(" Creating the data set for the {0} '{1}'.".
- format(plot.get("type", ""), plot_title))
+ logging.info(
+ f" Creating the data set for the {plot.get(u'type', u'')} "
+ f"{plot.get(u'title', u'')}."
+ )
data = input_data.filter_tests_by_name(
- plot, params=["throughput", "parent", "tags", "type"])
+ plot, params=[u"result", u"parent", u"tags", u"type"]
+ )
if data is None:
- logging.error("No data.")
+ logging.error(u"No data.")
return
# Prepare the data for the plot
y_vals = OrderedDict()
+ loss = dict()
for job in data:
for build in job:
for test in build:
- if y_vals.get(test["parent"], None) is None:
- y_vals[test["parent"]] = list()
+ if y_vals.get(test[u"parent"], None) is None:
+ y_vals[test[u"parent"]] = list()
+ loss[test[u"parent"]] = list()
try:
- if test["type"] in ("NDRPDR", ):
- if "-pdr" in plot_title.lower():
- y_vals[test["parent"]].\
- append(test["throughput"]["PDR"]["LOWER"])
- elif "-ndr" in plot_title.lower():
- y_vals[test["parent"]]. \
- append(test["throughput"]["NDR"]["LOWER"])
- else:
- continue
- elif test["type"] in ("SOAK", ):
- y_vals[test["parent"]].\
- append(test["throughput"]["LOWER"])
- else:
- continue
+ 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["parent"]].append(None)
+ y_vals[test[u"parent"]].append(None)
# Add None to the lists with missing data
max_len = 0
@@ -214,64 +452,58 @@ def plot_performance_box_name(plot, input_data):
if len(val) > max_len:
max_len = len(val)
nr_of_samples.append(len(val))
- for key, val in y_vals.items():
+ for val in y_vals.values():
if len(val) < max_len:
val.extend([None for _ in range(max_len - len(val))])
# Add plot traces
traces = list()
- df = pd.DataFrame(y_vals)
- df.head()
- y_max = list()
- for i, col in enumerate(df.columns):
- tst_name = re.sub(REGEX_NIC, "",
- col.lower().replace('-ndrpdr', '').
- replace('2n1l-', ''))
- name = "{nr}. ({samples:02d} run{plural}) {name}".\
- format(nr=(i + 1),
- samples=nr_of_samples[i],
- plural='s' if nr_of_samples[i] > 1 else '',
- name=tst_name)
-
- logging.debug(name)
- traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]),
- y=[y / 1000000 if y else None for y in df[col]],
- name=name,
- hoverinfo="x+y",
- boxpoints="outliers",
- whiskerwidth=0))
- try:
- val_max = max(df[col])
- except ValueError as err:
- logging.error(repr(err))
- continue
- if val_max:
- y_max.append(int(val_max / 1000000) + 2)
-
+ df_y = pd.DataFrame(y_vals)
+ df_y.head()
+ for i, col in enumerate(df_y.columns):
+ tst_name = re.sub(REGEX_NIC, u"",
+ col.lower().replace(u'-ndrpdr', u'').
+ replace(u'2n1l-', u''))
+
+ traces.append(plgo.Box(
+ x=[str(i + 1) + u'.'] * len(df_y[col]),
+ y=[y if y else None for y in df_y[col]],
+ name=(
+ f"{i + 1}. "
+ f"({nr_of_samples[i]:02d} "
+ f"run{u's' if nr_of_samples[i] > 1 else u''}, "
+ f"packets lost average: {mean(loss[col]):.1f}) "
+ f"{u'-'.join(tst_name.split(u'-')[3:-2])}"
+ ),
+ hoverinfo=u"y+name"
+ ))
try:
# Create plot
- layout = deepcopy(plot["layout"])
- if layout.get("title", None):
- layout["title"] = "Throughput: {0}". \
- format(layout["title"])
- if y_max:
- layout["yaxis"]["range"] = [0, max(y_max)]
+ layout = deepcopy(plot[u"layout"])
+ layout[u"title"] = f"Time Lost: {layout[u'title']}"
+ layout[u"yaxis"][u"title"] = u"Effective Blocked Time [s]"
+ layout[u"legend"][u"font"][u"size"] = 14
+ layout[u"yaxis"].pop(u"range")
plpl = plgo.Figure(data=traces, layout=layout)
# Export Plot
- file_type = plot.get("output-file-type", ".html")
- logging.info(" Writing file '{0}{1}'.".
- format(plot["output-file"], file_type))
- ploff.plot(plpl, show_link=False, auto_open=False,
- filename='{0}{1}'.format(plot["output-file"], file_type))
+ file_type = plot.get(u"output-file-type", u".html")
+ logging.info(f" Writing file {plot[u'output-file']}{file_type}.")
+ ploff.plot(
+ plpl,
+ show_link=False,
+ auto_open=False,
+ filename=f"{plot[u'output-file']}{file_type}"
+ )
except PlotlyError as err:
- logging.error(" Finished with error: {}".
- format(repr(err).replace("\n", " ")))
+ logging.error(
+ f" Finished with error: {repr(err)}".replace(u"\n", u" ")
+ )
return
-def plot_latency_error_bars_name(plot, input_data):
- """Generate the plot(s) with algorithm: plot_latency_error_bars_name
+def plot_perf_box_name(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_perf_box_name
specified in the specification file.
:param plot: Plot to generate.
@@ -281,171 +513,165 @@ def plot_latency_error_bars_name(plot, input_data):
"""
# Transform the data
- plot_title = plot.get("title", "")
- logging.info(" Creating the data set for the {0} '{1}'.".
- format(plot.get("type", ""), plot_title))
+ 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=["latency", "parent", "tags", "type"])
+ plot,
+ params=[u"throughput", u"gbps", u"result", u"parent", u"tags", u"type"])
if data is None:
- logging.error("No data.")
+ logging.error(u"No data.")
return
# Prepare the data for the plot
- y_tmp_vals = OrderedDict()
- for job in data:
- for build in job:
- for test in build:
- try:
- logging.debug("test['latency']: {0}\n".
- format(test["latency"]))
- except ValueError as err:
- logging.warning(repr(err))
- if y_tmp_vals.get(test["parent"], None) is None:
- y_tmp_vals[test["parent"]] = [
- list(), # direction1, min
- list(), # direction1, avg
- list(), # direction1, max
- list(), # direction2, min
- list(), # direction2, avg
- list() # direction2, max
- ]
- try:
- if test["type"] in ("NDRPDR", ):
- if "-pdr" in plot_title.lower():
- ttype = "PDR"
- elif "-ndr" in plot_title.lower():
- ttype = "NDR"
+ plot_title = plot.get(u"title", u"").lower()
+
+ if u"-gbps" in plot_title:
+ value = u"gbps"
+ multiplier = 1e6
+ else:
+ value = u"throughput"
+ multiplier = 1.0
+ 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"NDRPDR", u"CPS"):
+ test_type = test[u"type"]
+
+ if u"-pdr" in plot_title:
+ ttype = u"PDR"
+ elif u"-ndr" in plot_title:
+ ttype = u"NDR"
+ else:
+ raise RuntimeError(
+ u"Wrong title. No information about test "
+ u"type. Add '-ndr' or '-pdr' to the test "
+ u"title."
+ )
+
+ y_vals[test[u"parent"]].append(
+ test[value][ttype][u"LOWER"] * multiplier
+ )
+
+ elif test[u"type"] in (u"SOAK",):
+ y_vals[test[u"parent"]]. \
+ append(test[u"throughput"][u"LOWER"])
+ test_type = u"SOAK"
+
+ elif test[u"type"] in (u"HOSTSTACK",):
+ if u"LDPRELOAD" in test[u"tags"]:
+ y_vals[test[u"parent"]].append(
+ float(
+ test[u"result"][u"bits_per_second"]
+ ) / 1e3
+ )
+ elif u"VPPECHO" in test[u"tags"]:
+ y_vals[test[u"parent"]].append(
+ (float(
+ test[u"result"][u"client"][u"tx_data"]
+ ) * 8 / 1e3) /
+ ((float(
+ test[u"result"][u"client"][u"time"]
+ ) +
+ float(
+ test[u"result"][u"server"][u"time"])
+ ) / 2)
+ )
+ test_type = u"HOSTSTACK"
+
else:
- logging.warning("Invalid test type: {0}".
- format(test["type"]))
continue
- y_tmp_vals[test["parent"]][0].append(
- test["latency"][ttype]["direction1"]["min"])
- y_tmp_vals[test["parent"]][1].append(
- test["latency"][ttype]["direction1"]["avg"])
- y_tmp_vals[test["parent"]][2].append(
- test["latency"][ttype]["direction1"]["max"])
- y_tmp_vals[test["parent"]][3].append(
- test["latency"][ttype]["direction2"]["min"])
- y_tmp_vals[test["parent"]][4].append(
- test["latency"][ttype]["direction2"]["avg"])
- y_tmp_vals[test["parent"]][5].append(
- test["latency"][ttype]["direction2"]["max"])
- else:
- logging.warning("Invalid test type: {0}".
- format(test["type"]))
- continue
- except (KeyError, TypeError) as err:
- logging.warning(repr(err))
- x_vals = list()
- y_vals = list()
- y_mins = list()
- y_maxs = list()
+ 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 key, val in y_tmp_vals.items():
- name = re.sub(REGEX_NIC, "", key.replace('-ndrpdr', '').
- replace('2n1l-', ''))
- x_vals.append(name) # dir 1
- y_vals.append(mean(val[1]) if val[1] else None)
- y_mins.append(mean(val[0]) if val[0] else None)
- y_maxs.append(mean(val[2]) if val[2] else None)
- nr_of_samples.append(len(val[1]) if val[1] else 0)
- x_vals.append(name) # dir 2
- y_vals.append(mean(val[4]) if val[4] else None)
- y_mins.append(mean(val[3]) if val[3] else None)
- y_maxs.append(mean(val[5]) if val[5] else None)
- nr_of_samples.append(len(val[3]) if val[3] else 0)
+ for val in y_vals.values():
+ if len(val) > max_len:
+ max_len = len(val)
+ nr_of_samples.append(len(val))
+ for val in y_vals.values():
+ if len(val) < max_len:
+ val.extend([None for _ in range(max_len - len(val))])
+ # Add plot traces
traces = list()
- annotations = list()
-
- 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, ]
- 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,
+ df_y = pd.DataFrame(y_vals)
+ df_y.head()
+ y_max = list()
+ for i, col in enumerate(df_y.columns):
+ tst_name = re.sub(REGEX_NIC, u"",
+ col.lower().replace(u'-ndrpdr', u'').
+ replace(u'2n1l-', u''))
+ kwargs = dict(
+ x=[str(i + 1) + u'.'] * len(df_y[col]),
+ y=[y / 1e6 if y else None for y in df_y[col]],
+ name=(
+ f"{i + 1}. "
+ f"({nr_of_samples[i]:02d} "
+ f"run{u's' if nr_of_samples[i] > 1 else u''}) "
+ f"{tst_name}"
),
- align="center",
- showarrow=False
- ))
+ 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) + 2)
+ except (ValueError, TypeError) as err:
+ logging.error(repr(err))
+ continue
try:
# Create plot
- file_type = plot.get("output-file-type", ".html")
- logging.info(" Writing file '{0}{1}'.".
- format(plot["output-file"], file_type))
- layout = deepcopy(plot["layout"])
- if layout.get("title", None):
- layout["title"] = "Latency: {0}".\
- format(layout["title"])
- layout["annotations"] = annotations
+ layout = deepcopy(plot[u"layout"])
+ if layout.get(u"title", None):
+ if test_type in (u"HOSTSTACK", ):
+ layout[u"title"] = f"Bandwidth: {layout[u'title']}"
+ elif test_type in (u"CPS", ):
+ layout[u"title"] = f"CPS: {layout[u'title']}"
+ else:
+ layout[u"title"] = f"Throughput: {layout[u'title']}"
+ if y_max:
+ layout[u"yaxis"][u"range"] = [0, max(y_max)]
plpl = plgo.Figure(data=traces, layout=layout)
# Export Plot
- ploff.plot(plpl,
- show_link=False, auto_open=False,
- filename='{0}{1}'.format(plot["output-file"], file_type))
+ 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_throughput_speedup_analysis_name(plot, input_data):
+def plot_tsa_name(plot, input_data):
"""Generate the plot(s) with algorithm:
- plot_throughput_speedup_analysis_name
+ plot_tsa_name
specified in the specification file.
:param plot: Plot to generate.
@@ -455,46 +681,70 @@ def plot_throughput_speedup_analysis_name(plot, input_data):
"""
# Transform the data
- plot_title = plot.get("title", "")
- logging.info(" Creating the data set for the {0} '{1}'.".
- format(plot.get("type", ""), plot_title))
+ 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=["throughput", "parent", "tags", "type"])
+ 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
+ plot_title = plot_title.lower()
+
+ 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_vals = OrderedDict()
- for job in data:
- for build in job:
- for test in build:
- if y_vals.get(test["parent"], None) is None:
- y_vals[test["parent"]] = {"1": list(),
- "2": list(),
- "4": list()}
- 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
+ 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
+
+ if u"-pdr" in plot_title:
+ ttype = u"PDR"
+ elif u"-ndr" in plot_title:
+ ttype = u"NDR"
+ else:
+ continue
+
+ if u"1C" in test[u"tags"]:
+ y_vals[test[u"parent"]][u"1"].append(
+ test[value][ttype][u"LOWER"] * multiplier
+ )
+ elif u"2C" in test[u"tags"]:
+ y_vals[test[u"parent"]][u"2"].append(
+ test[value][ttype][u"LOWER"] * multiplier
+ )
+ elif u"4C" in test[u"tags"]:
+ y_vals[test[u"parent"]][u"4"].append(
+ test[value][ttype][u"LOWER"] * multiplier
+ )
+ except (KeyError, TypeError):
+ pass
if not y_vals:
- logging.warning("No data for the plot '{}'".
- format(plot.get("title", "")))
+ logging.warning(f"No data for the plot {plot.get(u'title', u'')}")
return
y_1c_max = dict()
@@ -502,8 +752,8 @@ def plot_throughput_speedup_analysis_name(plot, input_data):
for key, test_val in test_vals.items():
if test_val:
avg_val = sum(test_val) / len(test_val)
- y_vals[test_name][key] = (avg_val, len(test_val))
- ideal = avg_val / (int(key) * 1000000.0)
+ y_vals[test_name][key] = [avg_val, len(test_val)]
+ ideal = avg_val / (int(key) * 1e6)
if test_name not in y_1c_max or ideal > y_1c_max[test_name]:
y_1c_max[test_name] = ideal
@@ -511,32 +761,40 @@ def plot_throughput_speedup_analysis_name(plot, input_data):
y_max = list()
nic_limit = 0
lnk_limit = 0
- pci_limit = plot["limits"]["pci"]["pci-g3-x8"]
+ pci_limit = 0
for test_name, test_vals in y_vals.items():
try:
- if test_vals["1"][1]:
- name = re.sub(REGEX_NIC, "", test_name.replace('-ndrpdr', '').
- replace('2n1l-', ''))
+ 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["1"][0] / 1000000.0
- y_val_2 = test_vals["2"][0] / 1000000.0 if test_vals["2"][0] \
+ y_val_1 = test_vals[u"1"][0] / 1e6
+ y_val_2 = test_vals[u"2"][0] / 1e6 if test_vals[u"2"][0] \
else None
- y_val_4 = test_vals["4"][0] / 1000000.0 if test_vals["4"][0] \
+ y_val_4 = test_vals[u"4"][0] / 1e6 if test_vals[u"4"][0] \
else None
- vals[name]["val"] = [y_val_1, y_val_2, y_val_4]
- vals[name]["rel"] = [1.0, None, None]
- vals[name]["ideal"] = [y_1c_max[test_name],
- y_1c_max[test_name] * 2,
- y_1c_max[test_name] * 4]
- vals[name]["diff"] = [(y_val_1 - y_1c_max[test_name]) * 100 /
- y_val_1, None, None]
- vals[name]["count"] = [test_vals["1"][1],
- test_vals["2"][1],
- test_vals["4"][1]]
+ vals[name][u"val"] = [y_val_1, y_val_2, y_val_4]
+ vals[name][u"rel"] = [1.0, None, None]
+ vals[name][u"ideal"] = [
+ y_1c_max[test_name],
+ y_1c_max[test_name] * 2,
+ y_1c_max[test_name] * 4
+ ]
+ vals[name][u"diff"] = [
+ (y_val_1 - y_1c_max[test_name]) * 100 / y_val_1, None, None
+ ]
+ vals[name][u"count"] = [
+ test_vals[u"1"][1],
+ test_vals[u"2"][1],
+ test_vals[u"4"][1]
+ ]
try:
- val_max = max(vals[name]["val"])
+ val_max = max(vals[name][u"val"])
except ValueError as err:
logging.error(repr(err))
continue
@@ -544,230 +802,238 @@ def plot_throughput_speedup_analysis_name(plot, input_data):
y_max.append(val_max)
if y_val_2:
- vals[name]["rel"][1] = round(y_val_2 / y_val_1, 2)
- vals[name]["diff"][1] = \
- (y_val_2 - vals[name]["ideal"][1]) * 100 / y_val_2
+ vals[name][u"rel"][1] = round(y_val_2 / y_val_1, 2)
+ vals[name][u"diff"][1] = \
+ (y_val_2 - vals[name][u"ideal"][1]) * 100 / y_val_2
if y_val_4:
- vals[name]["rel"][2] = round(y_val_4 / y_val_1, 2)
- vals[name]["diff"][2] = \
- (y_val_4 - vals[name]["ideal"][2]) * 100 / y_val_4
+ vals[name][u"rel"][2] = round(y_val_4 / y_val_1, 2)
+ vals[name][u"diff"][2] = \
+ (y_val_4 - vals[name][u"ideal"][2]) * 100 / y_val_4
except IndexError as err:
- logging.warning("No data for '{0}'".format(test_name))
+ logging.warning(f"No data for {test_name}")
logging.warning(repr(err))
# Limits:
- if "x520" in test_name:
- limit = plot["limits"]["nic"]["x520"]
- elif "x710" in test_name:
- limit = plot["limits"]["nic"]["x710"]
- elif "xxv710" in test_name:
- limit = plot["limits"]["nic"]["xxv710"]
- elif "xl710" in test_name:
- limit = plot["limits"]["nic"]["xl710"]
- elif "x553" in test_name:
- limit = plot["limits"]["nic"]["x553"]
+ if u"x520" in test_name:
+ limit = plot[u"limits"][u"nic"][u"x520"]
+ elif u"x710" in test_name:
+ limit = plot[u"limits"][u"nic"][u"x710"]
+ elif u"xxv710" in test_name:
+ limit = plot[u"limits"][u"nic"][u"xxv710"]
+ elif u"xl710" in test_name:
+ limit = plot[u"limits"][u"nic"][u"xl710"]
+ elif u"x553" in test_name:
+ limit = plot[u"limits"][u"nic"][u"x553"]
+ elif u"cx556a" in test_name:
+ limit = plot[u"limits"][u"nic"][u"cx556a"]
else:
limit = 0
if limit > nic_limit:
nic_limit = limit
- mul = 2 if "ge2p" in test_name else 1
- if "10ge" in test_name:
- limit = plot["limits"]["link"]["10ge"] * mul
- elif "25ge" in test_name:
- limit = plot["limits"]["link"]["25ge"] * mul
- elif "40ge" in test_name:
- limit = plot["limits"]["link"]["40ge"] * mul
- elif "100ge" in test_name:
- limit = plot["limits"]["link"]["100ge"] * mul
+ mul = 2 if u"ge2p" in test_name else 1
+ if u"10ge" in test_name:
+ limit = plot[u"limits"][u"link"][u"10ge"] * mul
+ elif u"25ge" in test_name:
+ limit = plot[u"limits"][u"link"][u"25ge"] * mul
+ elif u"40ge" in test_name:
+ limit = plot[u"limits"][u"link"][u"40ge"] * mul
+ elif u"100ge" in test_name:
+ limit = plot[u"limits"][u"link"][u"100ge"] * mul
else:
limit = 0
if limit > lnk_limit:
lnk_limit = limit
+ 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:
- try:
- threshold = 1.1 * max(y_max) # 10%
- except ValueError as err:
- logging.error(err)
- return
- nic_limit /= 1000000.0
- traces.append(plgo.Scatter(
- x=x_vals,
- y=[nic_limit, ] * len(x_vals),
- name="NIC: {0:.2f}Mpps".format(nic_limit),
- showlegend=False,
- mode="lines",
- line=dict(
- dash="dot",
- color=COLORS[-1],
- width=1),
- hoverinfo="none"
- ))
- annotations.append(dict(
- x=1,
- y=nic_limit,
- xref="x",
- yref="y",
- xanchor="left",
- yanchor="bottom",
- text="NIC: {0:.2f}Mpps".format(nic_limit),
- font=dict(
- size=14,
- color=COLORS[-1],
- ),
- align="left",
- showarrow=False
- ))
- y_max.append(nic_limit)
-
- lnk_limit /= 1000000.0
- if lnk_limit < threshold:
- traces.append(plgo.Scatter(
- x=x_vals,
- y=[lnk_limit, ] * len(x_vals),
- name="Link: {0:.2f}Mpps".format(lnk_limit),
- showlegend=False,
- mode="lines",
- line=dict(
- dash="dot",
- color=COLORS[-2],
- width=1),
- hoverinfo="none"
- ))
- annotations.append(dict(
- x=1,
- y=lnk_limit,
- xref="x",
- yref="y",
- xanchor="left",
- yanchor="bottom",
- text="Link: {0:.2f}Mpps".format(lnk_limit),
- font=dict(
- size=14,
- color=COLORS[-2],
- ),
- align="left",
- showarrow=False
- ))
- y_max.append(lnk_limit)
-
- pci_limit /= 1000000.0
- if (pci_limit < threshold and
- (pci_limit < lnk_limit * 0.95 or lnk_limit > lnk_limit * 1.05)):
- traces.append(plgo.Scatter(
- x=x_vals,
- y=[pci_limit, ] * len(x_vals),
- name="PCIe: {0:.2f}Mpps".format(pci_limit),
- showlegend=False,
- mode="lines",
- line=dict(
- dash="dot",
- color=COLORS[-3],
- width=1),
- hoverinfo="none"
- ))
- annotations.append(dict(
- x=1,
- y=pci_limit,
- xref="x",
- yref="y",
- xanchor="left",
- yanchor="bottom",
- text="PCIe: {0:.2f}Mpps".format(pci_limit),
- font=dict(
- size=14,
- color=COLORS[-3],
- ),
- align="left",
- showarrow=False
- ))
- y_max.append(pci_limit)
+ 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.iteritems():
+ for name, val in vals.items():
hovertext = list()
try:
- for idx in range(len(val["val"])):
+ for idx in range(len(val[u"val"])):
htext = ""
- if isinstance(val["val"][idx], float):
- htext += "No. of Runs: {1}
" \
- "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])
+ if isinstance(val[u"val"][idx], float):
+ htext += (
+ f"No. of Runs: {val[u'count'][idx]}
"
+ f"Mean: {val[u'val'][idx]:.2f}{h_unit}
"
+ )
+ if isinstance(val[u"diff"][idx], float):
+ htext += f"Diff: {round(val[u'diff'][idx]):.0f}%
"
+ if isinstance(val[u"rel"][idx], float):
+ htext += f"Speedup: {val[u'rel'][idx]:.2f}"
hovertext.append(htext)
- traces.append(plgo.Scatter(x=x_vals,
- y=val["val"],
- name=name,
- legendgroup=name,
- mode="lines+markers",
- line=dict(
- color=COLORS[cidx],
- width=2),
- marker=dict(
- symbol="circle",
- size=10
- ),
- text=hovertext,
- hoverinfo="text+name"
- ))
- traces.append(plgo.Scatter(x=x_vals,
- y=val["ideal"],
- name="{0} perfect".format(name),
- legendgroup=name,
- showlegend=False,
- mode="lines",
- line=dict(
- color=COLORS[cidx],
- width=2,
- dash="dash"),
- text=["Perfect: {0:.2f}Mpps".format(y)
- for y in val["ideal"]],
- hoverinfo="text"
- ))
+ traces.append(
+ plgo.Scatter(
+ x=x_vals,
+ y=val[u"val"],
+ name=name,
+ legendgroup=name,
+ mode=u"lines+markers",
+ line=dict(
+ color=COLORS[cidx],
+ width=2),
+ marker=dict(
+ symbol=u"circle",
+ size=10
+ ),
+ text=hovertext,
+ hoverinfo=u"text+name"
+ )
+ )
+ traces.append(
+ plgo.Scatter(
+ x=x_vals,
+ y=val[u"ideal"],
+ name=f"{name} perfect",
+ legendgroup=name,
+ showlegend=False,
+ mode=u"lines",
+ line=dict(
+ color=COLORS[cidx],
+ width=2,
+ dash=u"dash"),
+ text=[f"Perfect: {y:.2f}Mpps" for y in val[u"ideal"]],
+ hoverinfo=u"text"
+ )
+ )
cidx += 1
except (IndexError, ValueError, KeyError) as err:
- logging.warning("No data for '{0}'".format(name))
- logging.warning(repr(err))
+ logging.warning(f"No data for {name}\n{repr(err)}")
try:
# Create plot
- file_type = plot.get("output-file-type", ".html")
- logging.info(" Writing file '{0}{1}'.".
- format(plot["output-file"], file_type))
- layout = deepcopy(plot["layout"])
- if layout.get("title", None):
- layout["title"] = "Speedup Multi-core: {0}". \
- format(layout["title"])
- layout["yaxis"]["range"] = [0, int(max(y_max) * 1.1)]
- layout["annotations"].extend(annotations)
+ file_type = plot.get(u"output-file-type", u".html")
+ logging.info(f" Writing file {plot[u'output-file']}{file_type}.")
+ layout = deepcopy(plot[u"layout"])
+ if layout.get(u"title", None):
+ layout[u"title"] = f"Speedup Multi-core: {layout[u'title']}"
+ layout[u"yaxis"][u"range"] = [0, int(max(y_max) * 1.1)]
+ layout[u"annotations"].extend(annotations)
plpl = plgo.Figure(data=traces, layout=layout)
# Export Plot
- ploff.plot(plpl,
- show_link=False, auto_open=False,
- filename='{0}{1}'.format(plot["output-file"], file_type))
+ ploff.plot(
+ plpl,
+ show_link=False,
+ auto_open=False,
+ filename=f"{plot[u'output-file']}{file_type}"
+ )
except PlotlyError as err:
- logging.error(" Finished with error: {}".
- format(repr(err).replace("\n", " ")))
+ logging.error(
+ f" Finished with error: {repr(err)}".replace(u"\n", u" ")
+ )
return
-def plot_performance_box(plot, input_data):
- """Generate the plot(s) with algorithm: plot_performance_box
+def plot_http_server_perf_box(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_http_server_perf_box
specified in the specification file.
- TODO: Remove when not needed.
-
:param plot: Plot to generate.
:param input_data: Data to process.
:type plot: pandas.Series
@@ -775,130 +1041,87 @@ def plot_performance_box(plot, input_data):
"""
# Transform the data
- plot_title = plot.get("title", "")
- logging.info(" Creating the data set for the {0} '{1}'.".
- format(plot.get("type", ""), plot_title))
+ 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
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)
+ if y_vals.get(test[u"name"], None) is None:
+ y_vals[test[u"name"]] = list()
try:
- if test["type"] in ("NDRPDR", ):
- if "-pdr" in plot_title.lower():
- y_vals[test["parent"]].\
- append(test["throughput"]["PDR"]["LOWER"])
- elif "-ndr" in plot_title.lower():
- y_vals[test["parent"]]. \
- append(test["throughput"]["NDR"]["LOWER"])
- else:
- continue
- elif test["type"] in ("SOAK", ):
- y_vals[test["parent"]].\
- append(test["throughput"]["LOWER"])
- else:
- continue
+ y_vals[test[u"name"]].append(test[u"result"])
except (KeyError, TypeError):
- y_vals[test["parent"]].append(None)
-
- # Sort the tests
- order = plot.get("sort", None)
- if order and y_tags:
- y_sorted = OrderedDict()
- y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()}
- for tag in order:
- logging.debug(tag)
- for suite, tags in y_tags_l.items():
- if "not " in tag:
- tag = tag.split(" ")[-1]
- if tag.lower() in tags:
- continue
- else:
- if tag.lower() not in tags:
- continue
- try:
- y_sorted[suite] = y_vals.pop(suite)
- y_tags_l.pop(suite)
- logging.debug(suite)
- except KeyError as err:
- logging.error("Not found: {0}".format(repr(err)))
- finally:
- break
- else:
- y_sorted = y_vals
+ y_vals[test[u"name"]].append(None)
# Add None to the lists with missing data
max_len = 0
nr_of_samples = list()
- for val in y_sorted.values():
+ for val in y_vals.values():
if len(val) > max_len:
max_len = len(val)
nr_of_samples.append(len(val))
- for key, val in y_sorted.items():
+ for val in y_vals.values():
if len(val) < max_len:
val.extend([None for _ in range(max_len - len(val))])
# Add plot traces
traces = list()
- df = pd.DataFrame(y_sorted)
- df.head()
- y_max = list()
- for i, col in enumerate(df.columns):
- tst_name = re.sub(REGEX_NIC, "",
- col.lower().replace('-ndrpdr', '').
- replace('2n1l-', ''))
- name = "{nr}. ({samples:02d} run{plural}) {name}".\
- format(nr=(i + 1),
- samples=nr_of_samples[i],
- plural='s' if nr_of_samples[i] > 1 else '',
- name=tst_name)
-
- logging.debug(name)
- traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]),
- y=[y / 1000000 if y else None for y in df[col]],
- name=name,
- **plot["traces"]))
- try:
- val_max = max(df[col])
- except ValueError as err:
- logging.error(repr(err))
- continue
- if val_max:
- y_max.append(int(val_max / 1000000) + 2)
+ 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"
"
+ 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[u"traces"]))
try:
# Create plot
- layout = deepcopy(plot["layout"])
- if layout.get("title", None):
- layout["title"] = "Throughput: {0}". \
- format(layout["title"])
- if y_max:
- layout["yaxis"]["range"] = [0, max(y_max)]
- plpl = plgo.Figure(data=traces, layout=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(repr(err).replace("\n", " ")))
+ logging.error(
+ f" Finished with error: {repr(err)}".replace(u"\n", u" ")
+ )
return
-def plot_soak_bars(plot, input_data):
- """Generate the plot(s) with algorithm: plot_soak_bars
+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.
@@ -907,1613 +1130,317 @@ def plot_soak_bars(plot, input_data):
:type input_data: InputData
"""
+ regex_cn = re.compile(r'^(\d*)R(\d*)C$')
+ regex_test_name = re.compile(r'^.*-(\d+ch|\d+pl)-'
+ r'(\d+mif|\d+vh)-'
+ r'(\d+vm\d+t|\d+dcr\d+t|\d+dcr\d+c).*$')
+ vals = dict()
+
# 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.")
+ logging.info(
+ f" Creating the data set for the {plot.get(u'type', u'')} "
+ f"{plot.get(u'title', u'')}."
+ )
+ data = input_data.filter_data(plot, continue_on_error=True)
+ if data is None or data.empty:
+ logging.error(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_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
+ 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:
- if tag.lower() not in tags:
- continue
+ 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:
- 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', '').
- replace('2n1l-', ''))
- if len(name) > 55:
- name_lst = name.split('-')
- name = ""
- split_name = True
- for segment in name_lst:
- if (len(name) + len(segment) + 1) > 55 and split_name:
- name += "
"
- split_name = False
- name += segment + '-'
- name = name[:-1]
-
- y_val = test_data.get("UPPER", None)
- if y_val:
- y_val /= 1000000
- if y_val > y_max:
- y_max = y_val
-
- y_base = test_data.get("LOWER", None)
- if y_base:
- y_base /= 1000000
-
- hovertext = ("Upper bound: {upper:.2f}
"
- "Lower bound: {lower:.2f}".format(upper=y_val,
- lower=y_base))
- traces.append(plgo.Bar(x=[str(idx) + '.', ],
- # +0.05 to see the value in case lower == upper
- y=[y_val - y_base + 0.05, ],
- base=y_base,
- name=name,
- text=hovertext,
- hoverinfo="text"))
- try:
- # Create plot
- layout = deepcopy(plot["layout"])
- if layout.get("title", None):
- layout["title"] = "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_latency_error_bars(plot, input_data):
- """Generate the plot(s) with algorithm: plot_latency_error_bars
- specified in the specification file.
-
- TODO: Remove when not needed.
-
- :param plot: Plot to generate.
- :param input_data: Data to process.
- :type plot: pandas.Series
- :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 = re.sub(REGEX_NIC, "", key.replace('-ndrpdr', '').
- replace('2n1l-', ''))
- x_vals.append(name) # dir 1
- y_vals.append(mean(val[1]) if val[1] else None)
- y_mins.append(mean(val[0]) if val[0] else None)
- y_maxs.append(mean(val[2]) if val[2] else None)
- nr_of_samples.append(len(val[1]) if val[1] else 0)
- x_vals.append(name) # dir 2
- y_vals.append(mean(val[4]) if val[4] else None)
- y_mins.append(mean(val[3]) if val[3] else None)
- y_maxs.append(mean(val[5]) if val[5] else None)
- nr_of_samples.append(len(val[3]) if val[3] else 0)
-
- 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"] = "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.
-
- TODO: Remove when not needed.
-
- :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 = re.sub(REGEX_NIC, "", test_name.replace('-ndrpdr', '').
- replace('2n1l-', ''))
- vals[name] = dict()
- y_val_1 = test_vals["1"][0] / 1000000.0
- y_val_2 = test_vals["2"][0] / 1000000.0 if test_vals["2"][0] \
- 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"]))
- val_max = max(vals[name]["val"])
- except ValueError as err:
- logging.error(err)
- continue
- if val_max:
- # y_max.append(int((val_max / 10) + 1) * 10)
- y_max.append(val_max)
-
- if y_val_2:
- vals[name]["rel"][1] = round(y_val_2 / y_val_1, 2)
- vals[name]["diff"][1] = \
- (y_val_2 - vals[name]["ideal"][1]) * 100 / y_val_2
- 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 = re.sub(REGEX_NIC, "",
- test.replace('-ndrpdr', '').
- replace('2n1l-', ''))
- try:
- y_sorted[name] = vals.pop(name)
- y_tags_l.pop(test)
- except KeyError as err:
- logging.error("Not found: {0}".format(err))
- finally:
- break
- else:
- y_sorted = vals
-
- traces = list()
- annotations = list()
- x_vals = [1, 2, 4]
-
- # 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)
- y_max.append(nic_limit)
-
- lnk_limit /= 1000000.0
- if lnk_limit < threshold:
- traces.append(plgo.Scatter(
- x=x_vals,
- y=[lnk_limit, ] * len(x_vals),
- name="Link: {0:.2f}Mpps".format(lnk_limit),
- showlegend=False,
- mode="lines",
- line=dict(
- dash="dot",
- color=COLORS[-2],
- width=1),
- hoverinfo="none"
- ))
- annotations.append(dict(
- x=1,
- y=lnk_limit,
- xref="x",
- yref="y",
- xanchor="left",
- yanchor="bottom",
- text="Link: {0:.2f}Mpps".format(lnk_limit),
- font=dict(
- size=14,
- color=COLORS[-2],
- ),
- align="left",
- showarrow=False
- ))
- # y_max.append(int((lnk_limit / 10) + 1) * 10)
- y_max.append(lnk_limit)
-
- pci_limit /= 1000000.0
- if (pci_limit < threshold and
- (pci_limit < lnk_limit * 0.95 or lnk_limit > lnk_limit * 1.05)):
- traces.append(plgo.Scatter(
- x=x_vals,
- y=[pci_limit, ] * len(x_vals),
- name="PCIe: {0:.2f}Mpps".format(pci_limit),
- showlegend=False,
- mode="lines",
- line=dict(
- dash="dot",
- color=COLORS[-3],
- width=1),
- hoverinfo="none"
- ))
- annotations.append(dict(
- x=1,
- y=pci_limit,
- xref="x",
- yref="y",
- xanchor="left",
- yanchor="bottom",
- text="PCIe: {0:.2f}Mpps".format(pci_limit),
- font=dict(
- size=14,
- color=COLORS[-3],
- ),
- align="left",
- showarrow=False
- ))
- # y_max.append(int((pci_limit / 10) + 1) * 10)
- y_max.append(pci_limit)
-
- # 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["yaxis"]["range"] = [0, int((max(y_max) / 10) + 1) * 10]
- layout["yaxis"]["range"] = [0, int(max(y_max) * 1.1)]
- 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
- """
-
- REGEX_CN = re.compile(r'^(\d*)R(\d*)C$')
- REGEX_TEST_NAME = re.compile(r'^.*-(\d+ch|\d+pl)-'
- r'(\d+mif|\d+vh)-'
- r'(\d+vm\d+t|\d+dcr\d+t).*$')
-
- txt_chains = list()
- txt_nodes = list()
- vals = dict()
-
- # Transform the data
- logging.info(" Creating the data set for the {0} '{1}'.".
- format(plot.get("type", ""), plot.get("title", "")))
- data = input_data.filter_data(plot, continue_on_error=True)
- if data is None or data.empty:
- logging.error("No data.")
- return
-
- for job in data:
- for build in job:
- for test in build:
- for tag in test['tags']:
- groups = re.search(REGEX_CN, tag)
- if groups:
- c = str(groups.group(1))
- n = str(groups.group(2))
- break
- else:
- continue
- groups = re.search(REGEX_TEST_NAME, test["name"])
- if groups and len(groups.groups()) == 3:
- hover_name = "{chain}-{vhost}-{vm}".format(
- chain=str(groups.group(1)),
- vhost=str(groups.group(2)),
- vm=str(groups.group(3)))
- else:
- hover_name = ""
- if vals.get(c, None) is None:
- vals[c] = dict()
- if vals[c].get(n, None) is None:
- vals[c][n] = dict(name=hover_name,
- vals=list(),
- nr=None,
- mean=None,
- stdev=None)
- try:
- if plot["include-tests"] == "MRR":
- result = test["result"]["receive-rate"].avg
- elif plot["include-tests"] == "PDR":
- result = test["throughput"]["PDR"]["LOWER"]
- elif plot["include-tests"] == "NDR":
- result = test["throughput"]["NDR"]["LOWER"]
+ if plot[u"include-tests"] == u"MRR":
+ result = test[u"result"][u"receive-rate"]
+ elif plot[u"include-tests"] == u"PDR":
+ result = test[u"throughput"][u"PDR"][u"LOWER"]
+ elif plot[u"include-tests"] == u"NDR":
+ result = test[u"throughput"][u"NDR"][u"LOWER"]
else:
result = None
except TypeError:
result = None
if result:
- vals[c][n]["vals"].append(result)
+ vals[chain][node][u"vals"].append(result)
if not vals:
- logging.error("No data.")
+ logging.error(u"No data.")
return
- for key_c in vals.keys():
+ txt_chains = list()
+ txt_nodes = list()
+ for key_c in vals:
txt_chains.append(key_c)
for key_n in vals[key_c].keys():
txt_nodes.append(key_n)
- if vals[key_c][key_n]["vals"]:
- vals[key_c][key_n]["nr"] = len(vals[key_c][key_n]["vals"])
- vals[key_c][key_n]["mean"] = \
- round(mean(vals[key_c][key_n]["vals"]) / 1000000, 1)
- vals[key_c][key_n]["stdev"] = \
- round(stdev(vals[key_c][key_n]["vals"]) / 1000000, 1)
+ if vals[key_c][key_n][u"vals"]:
+ vals[key_c][key_n][u"nr"] = len(vals[key_c][key_n][u"vals"])
+ vals[key_c][key_n][u"mean"] = \
+ round(mean(vals[key_c][key_n][u"vals"]) / 1000000, 1)
+ vals[key_c][key_n][u"stdev"] = \
+ round(stdev(vals[key_c][key_n][u"vals"]) / 1000000, 1)
txt_nodes = list(set(txt_nodes))
- txt_chains = sorted(txt_chains, key=lambda chain: int(chain))
- txt_nodes = sorted(txt_nodes, key=lambda node: int(node))
+ def sort_by_int(value):
+ """Makes possible to sort a list of strings which represent integers.
+
+ :param value: Integer as a string.
+ :type value: str
+ :returns: Integer representation of input parameter 'value'.
+ :rtype: int
+ """
+ return int(value)
+
+ txt_chains = sorted(txt_chains, key=sort_by_int)
+ txt_nodes = sorted(txt_nodes, key=sort_by_int)
chains = [i + 1 for i in range(len(txt_chains))]
nodes = [i + 1 for i in range(len(txt_nodes))]
data = [list() for _ in range(len(chains))]
- for c in chains:
- for n in nodes:
+ for chain in chains:
+ for node in nodes:
try:
- val = vals[txt_chains[c - 1]][txt_nodes[n - 1]]["mean"]
+ val = vals[txt_chains[chain - 1]][txt_nodes[node - 1]][u"mean"]
except (KeyError, IndexError):
val = None
- data[c - 1].append(val)
+ data[chain - 1].append(val)
- # Colorscales:
- my_green = [[0.0, 'rgb(235, 249, 242)'],
- [1.0, 'rgb(45, 134, 89)']]
+ # Color scales:
+ my_green = [[0.0, u"rgb(235, 249, 242)"],
+ [1.0, u"rgb(45, 134, 89)"]]
- my_blue = [[0.0, 'rgb(236, 242, 248)'],
- [1.0, 'rgb(57, 115, 172)']]
+ my_blue = [[0.0, u"rgb(236, 242, 248)"],
+ [1.0, u"rgb(57, 115, 172)"]]
- my_grey = [[0.0, 'rgb(230, 230, 230)'],
- [1.0, 'rgb(102, 102, 102)']]
+ my_grey = [[0.0, u"rgb(230, 230, 230)"],
+ [1.0, u"rgb(102, 102, 102)"]]
hovertext = list()
annotations = list()
- text = ("Test: {name}
"
- "Runs: {nr}
"
- "Thput: {val}
"
- "StDev: {stdev}")
+ text = (u"Test: {name}
"
+ u"Runs: {nr}
"
+ u"Thput: {val}
"
+ u"StDev: {stdev}")
- for c in range(len(txt_chains)):
+ for chain, _ in enumerate(txt_chains):
hover_line = list()
- for n in range(len(txt_nodes)):
- if data[c][n] is not None:
- annotations.append(dict(
- x=n+1,
- y=c+1,
- xref="x",
- yref="y",
- xanchor="center",
- yanchor="middle",
- text=str(data[c][n]),
- font=dict(
- size=14,
- ),
- align="center",
- showarrow=False
- ))
+ for node, _ in enumerate(txt_nodes):
+ if data[chain][node] is not None:
+ annotations.append(
+ dict(
+ x=node+1,
+ y=chain+1,
+ xref=u"x",
+ yref=u"y",
+ xanchor=u"center",
+ yanchor=u"middle",
+ text=str(data[chain][node]),
+ font=dict(
+ size=14,
+ ),
+ align=u"center",
+ showarrow=False
+ )
+ )
hover_line.append(text.format(
- name=vals[txt_chains[c]][txt_nodes[n]]["name"],
- nr=vals[txt_chains[c]][txt_nodes[n]]["nr"],
- val=data[c][n],
- stdev=vals[txt_chains[c]][txt_nodes[n]]["stdev"]))
+ name=vals[txt_chains[chain]][txt_nodes[node]][u"name"],
+ nr=vals[txt_chains[chain]][txt_nodes[node]][u"nr"],
+ val=data[chain][node],
+ stdev=vals[txt_chains[chain]][txt_nodes[node]][u"stdev"]))
hovertext.append(hover_line)
traces = [
- plgo.Heatmap(x=nodes,
- y=chains,
- z=data,
- colorbar=dict(
- title=plot.get("z-axis", ""),
- titleside="right",
- titlefont=dict(
- size=16
- ),
- tickfont=dict(
- size=16,
- ),
- tickformat=".1f",
- yanchor="bottom",
- y=-0.02,
- len=0.925,
- ),
- showscale=True,
- colorscale=my_green,
- text=hovertext,
- hoverinfo="text")
+ plgo.Heatmap(
+ x=nodes,
+ y=chains,
+ z=data,
+ colorbar=dict(
+ title=plot.get(u"z-axis", u""),
+ titleside=u"right",
+ titlefont=dict(
+ size=16
+ ),
+ tickfont=dict(
+ size=16,
+ ),
+ tickformat=u".1f",
+ yanchor=u"bottom",
+ y=-0.02,
+ len=0.925,
+ ),
+ showscale=True,
+ colorscale=my_green,
+ text=hovertext,
+ hoverinfo=u"text"
+ )
]
for idx, item in enumerate(txt_nodes):
# X-axis, numbers:
- annotations.append(dict(
- x=idx+1,
- y=0.05,
- xref="x",
- yref="y",
- xanchor="center",
- yanchor="top",
- text=item,
- font=dict(
- size=16,
- ),
- align="center",
- showarrow=False
- ))
- for idx, item in enumerate(txt_chains):
- # Y-axis, numbers:
- annotations.append(dict(
- x=0.35,
- y=idx+1,
- xref="x",
- yref="y",
- xanchor="right",
- yanchor="middle",
- text=item,
- font=dict(
- size=16,
- ),
- align="center",
- showarrow=False
- ))
- # X-axis, title:
- annotations.append(dict(
- x=0.55,
- y=-0.15,
- xref="paper",
- yref="y",
- xanchor="center",
- yanchor="bottom",
- text=plot.get("x-axis", ""),
- font=dict(
- size=16,
- ),
- align="center",
- showarrow=False
- ))
- # Y-axis, title:
- annotations.append(dict(
- x=-0.1,
- y=0.5,
- xref="x",
- yref="paper",
- xanchor="center",
- yanchor="middle",
- text=plot.get("y-axis", ""),
- font=dict(
- size=16,
- ),
- align="center",
- textangle=270,
- showarrow=False
- ))
- updatemenus = list([
- dict(
- x=1.0,
- y=0.0,
- xanchor='right',
- yanchor='bottom',
- direction='up',
- buttons=list([
- dict(
- args=[{"colorscale": [my_green, ], "reversescale": False}],
- label="Green",
- method="update"
- ),
- dict(
- args=[{"colorscale": [my_blue, ], "reversescale": False}],
- label="Blue",
- method="update"
+ annotations.append(
+ dict(
+ x=idx+1,
+ y=0.05,
+ xref=u"x",
+ yref=u"y",
+ xanchor=u"center",
+ yanchor=u"top",
+ text=item,
+ font=dict(
+ size=16,
),
- dict(
- args=[{"colorscale": [my_grey, ], "reversescale": False}],
- label="Grey",
- method="update"
- )
- ])
+ align=u"center",
+ showarrow=False
+ )
)
- ])
-
- try:
- layout = deepcopy(plot["layout"])
- except KeyError as err:
- logging.error("Finished with error: No layout defined")
- logging.error(repr(err))
- return
-
- layout["annotations"] = annotations
- layout['updatemenus'] = updatemenus
-
- try:
- # Create plot
- plpl = plgo.Figure(data=traces, layout=layout)
-
- # Export Plot
- logging.info(" Writing file '{0}{1}'.".
- format(plot["output-file"], plot["output-file-type"]))
- ploff.plot(plpl, show_link=False, auto_open=False,
- filename='{0}{1}'.format(plot["output-file"],
- plot["output-file-type"]))
- except PlotlyError as err:
- logging.error(" Finished with error: {}".
- format(str(err).replace("\n", " ")))
- return
-
-
-def plot_service_density_heatmap_compare(plot, input_data):
- """Generate the plot(s) with algorithm: plot_service_density_heatmap_compare
- specified in the specification file.
-
- :param plot: Plot to generate.
- :param input_data: Data to process.
- :type plot: pandas.Series
- :type input_data: InputData
- """
-
- REGEX_CN = re.compile(r'^(\d*)R(\d*)C$')
- REGEX_TEST_NAME = re.compile(r'^.*-(\d+ch|\d+pl)-'
- r'(\d+mif|\d+vh)-'
- r'(\d+vm\d+t|\d+dcr\d+t).*$')
- REGEX_THREADS = re.compile(r'^(\d+)(VM|DCR)(\d+)T$')
-
- txt_chains = list()
- txt_nodes = list()
- vals = dict()
-
- # Transform the data
- logging.info(" Creating the data set for the {0} '{1}'.".
- format(plot.get("type", ""), plot.get("title", "")))
- data = input_data.filter_data(plot, continue_on_error=True)
- if data is None or data.empty:
- logging.error("No data.")
- return
-
- for job in data:
- for build in job:
- for test in build:
- for tag in test['tags']:
- groups = re.search(REGEX_CN, tag)
- if groups:
- c = str(groups.group(1))
- n = str(groups.group(2))
- break
- else:
- continue
- groups = re.search(REGEX_TEST_NAME, test["name"])
- if groups and len(groups.groups()) == 3:
- hover_name = "{chain}-{vhost}-{vm}".format(
- chain=str(groups.group(1)),
- vhost=str(groups.group(2)),
- vm=str(groups.group(3)))
- else:
- hover_name = ""
- if vals.get(c, None) is None:
- vals[c] = dict()
- if vals[c].get(n, None) is None:
- vals[c][n] = dict(name=hover_name,
- vals_r=list(),
- vals_c=list(),
- nr_r=None,
- nr_c=None,
- mean_r=None,
- mean_c=None,
- stdev_r=None,
- stdev_c=None)
- try:
- if plot["include-tests"] == "MRR":
- result = test["result"]["receive-rate"].avg
- elif plot["include-tests"] == "PDR":
- result = test["throughput"]["PDR"]["LOWER"]
- elif plot["include-tests"] == "NDR":
- result = test["throughput"]["NDR"]["LOWER"]
- else:
- result = None
- except TypeError:
- result = None
-
- if result:
- for tag in test['tags']:
- groups = re.search(REGEX_THREADS, tag)
- if groups and len(groups.groups()) == 3:
- if str(groups.group(3)) == \
- plot["reference"]["include"]:
- vals[c][n]["vals_r"].append(result)
- elif str(groups.group(3)) == \
- plot["compare"]["include"]:
- vals[c][n]["vals_c"].append(result)
- break
- if not vals:
- logging.error("No data.")
- return
-
- for key_c in vals.keys():
- txt_chains.append(key_c)
- for key_n in vals[key_c].keys():
- txt_nodes.append(key_n)
- if vals[key_c][key_n]["vals_r"]:
- vals[key_c][key_n]["nr_r"] = len(vals[key_c][key_n]["vals_r"])
- vals[key_c][key_n]["mean_r"] = \
- mean(vals[key_c][key_n]["vals_r"])
- vals[key_c][key_n]["stdev_r"] = \
- round(stdev(vals[key_c][key_n]["vals_r"]) / 1000000, 1)
- if vals[key_c][key_n]["vals_c"]:
- vals[key_c][key_n]["nr_c"] = len(vals[key_c][key_n]["vals_c"])
- vals[key_c][key_n]["mean_c"] = \
- mean(vals[key_c][key_n]["vals_c"])
- vals[key_c][key_n]["stdev_c"] = \
- round(stdev(vals[key_c][key_n]["vals_c"]) / 1000000, 1)
-
- txt_nodes = list(set(txt_nodes))
-
- txt_chains = sorted(txt_chains, key=lambda chain: int(chain))
- txt_nodes = sorted(txt_nodes, key=lambda node: int(node))
-
- chains = [i + 1 for i in range(len(txt_chains))]
- nodes = [i + 1 for i in range(len(txt_nodes))]
-
- data_r = [list() for _ in range(len(chains))]
- data_c = [list() for _ in range(len(chains))]
- diff = [list() for _ in range(len(chains))]
- for c in chains:
- for n in nodes:
- try:
- val_r = vals[txt_chains[c - 1]][txt_nodes[n - 1]]["mean_r"]
- except (KeyError, IndexError):
- val_r = None
- try:
- val_c = vals[txt_chains[c - 1]][txt_nodes[n - 1]]["mean_c"]
- except (KeyError, IndexError):
- val_c = None
- if val_c is not None and val_r:
- val_d = (val_c - val_r) * 100 / val_r
- else:
- val_d = None
-
- if val_r is not None:
- val_r = round(val_r / 1000000, 1)
- data_r[c - 1].append(val_r)
- if val_c is not None:
- val_c = round(val_c / 1000000, 1)
- data_c[c - 1].append(val_c)
- if val_d is not None:
- val_d = int(round(val_d, 0))
- diff[c - 1].append(val_d)
-
- # Colorscales:
- my_green = [[0.0, 'rgb(235, 249, 242)'],
- [1.0, 'rgb(45, 134, 89)']]
-
- my_blue = [[0.0, 'rgb(236, 242, 248)'],
- [1.0, 'rgb(57, 115, 172)']]
-
- my_grey = [[0.0, 'rgb(230, 230, 230)'],
- [1.0, 'rgb(102, 102, 102)']]
-
- hovertext = list()
-
- annotations = list()
- annotations_r = list()
- annotations_c = list()
- annotations_diff = list()
-
- text = ("Test: {name}"
- "
{title_r}: {text_r}"
- "
{title_c}: {text_c}{text_diff}")
- text_r = "Thput: {val_r}; StDev: {stdev_r}; Runs: {nr_r}"
- text_c = "Thput: {val_c}; StDev: {stdev_c}; Runs: {nr_c}"
- text_diff = "
Relative Difference {title_c} vs. {title_r}: {diff}%"
-
- for c in range(len(txt_chains)):
- hover_line = list()
- for n in range(len(txt_nodes)):
- point = dict(
- x=n + 1,
- y=c + 1,
- xref="x",
- yref="y",
- xanchor="center",
- yanchor="middle",
- text="",
+ for idx, item in enumerate(txt_chains):
+ # Y-axis, numbers:
+ annotations.append(
+ dict(
+ x=0.35,
+ y=idx+1,
+ xref=u"x",
+ yref=u"y",
+ xanchor=u"right",
+ yanchor=u"middle",
+ text=item,
font=dict(
- size=14,
+ size=16,
),
- align="center",
+ align=u"center",
showarrow=False
)
-
- point_text_r = "Not present"
- point_text_c = "Not present"
- point_text_diff = ""
- try:
- point_r = data_r[c][n]
- if point_r is not None:
- point_text_r = text_r.format(
- val_r=point_r,
- stdev_r=vals[txt_chains[c]][txt_nodes[n]]["stdev_r"],
- nr_r=vals[txt_chains[c]][txt_nodes[n]]["nr_r"])
- except KeyError:
- point_r = None
- point["text"] = "" if point_r is None else point_r
- annotations_r.append(deepcopy(point))
-
- try:
- point_c = data_c[c][n]
- if point_c is not None:
- point_text_c = text_c.format(
- val_c=point_c,
- stdev_c=vals[txt_chains[c]][txt_nodes[n]]["stdev_c"],
- nr_c=vals[txt_chains[c]][txt_nodes[n]]["nr_c"])
- except KeyError:
- point_c = None
- point["text"] = "" if point_c is None else point_c
- annotations_c.append(deepcopy(point))
-
- try:
- point_d = diff[c][n]
- if point_d is not None:
- point_text_diff = text_diff.format(
- title_r=plot["reference"]["name"],
- title_c=plot["compare"]["name"],
- diff=point_d)
- except KeyError:
- point_d = None
- point["text"] = "" if point_d is None else point_d
- annotations_diff.append(deepcopy(point))
-
- try:
- name = vals[txt_chains[c]][txt_nodes[n]]["name"]
- except KeyError:
- continue
-
- hover_line.append(text.format(
- name=name,
- title_r=plot["reference"]["name"],
- text_r=point_text_r,
- title_c=plot["compare"]["name"],
- text_c=point_text_c,
- text_diff=point_text_diff
- ))
-
- hovertext.append(hover_line)
-
- traces = [
- plgo.Heatmap(x=nodes,
- y=chains,
- z=data_r,
- visible=True,
- colorbar=dict(
- title=plot.get("z-axis", ""),
- titleside="right",
- titlefont=dict(
- size=16
- ),
- tickfont=dict(
- size=16,
- ),
- tickformat=".1f",
- yanchor="bottom",
- y=-0.02,
- len=0.925,
- ),
- showscale=True,
- colorscale=my_green,
- reversescale=False,
- text=hovertext,
- hoverinfo="text"),
- plgo.Heatmap(x=nodes,
- y=chains,
- z=data_c,
- visible=False,
- colorbar=dict(
- title=plot.get("z-axis", ""),
- titleside="right",
- titlefont=dict(
- size=16
- ),
- tickfont=dict(
- size=16,
- ),
- tickformat=".1f",
- yanchor="bottom",
- y=-0.02,
- len=0.925,
- ),
- showscale=True,
- colorscale=my_blue,
- reversescale=False,
- text=hovertext,
- hoverinfo="text"),
- plgo.Heatmap(x=nodes,
- y=chains,
- z=diff,
- name="Diff",
- visible=False,
- colorbar=dict(
- title="Relative Difference {name_c} vs. {name_r} [%]".
- format(name_c=plot["compare"]["name"],
- name_r=plot["reference"]["name"]),
- titleside="right",
- titlefont=dict(
- size=16
- ),
- tickfont=dict(
- size=16,
- ),
- tickformat=".1f",
- yanchor="bottom",
- y=-0.02,
- len=0.925,
- ),
- showscale=True,
- colorscale=my_grey,
- reversescale=False,
- text=hovertext,
- hoverinfo="text")
- ]
-
- for idx, item in enumerate(txt_nodes):
- # X-axis, numbers:
- annotations.append(dict(
- x=idx+1,
- y=0.05,
- xref="x",
- yref="y",
- xanchor="center",
- yanchor="top",
- text=item,
+ )
+ # X-axis, title:
+ annotations.append(
+ dict(
+ x=0.55,
+ y=-0.15,
+ xref=u"paper",
+ yref=u"y",
+ xanchor=u"center",
+ yanchor=u"bottom",
+ text=plot.get(u"x-axis", u""),
font=dict(
size=16,
),
- align="center",
+ align=u"center",
showarrow=False
- ))
- for idx, item in enumerate(txt_chains):
- # Y-axis, numbers:
- annotations.append(dict(
- x=0.35,
- y=idx+1,
- xref="x",
- yref="y",
- xanchor="right",
- yanchor="middle",
- text=item,
+ )
+ )
+ # Y-axis, title:
+ annotations.append(
+ dict(
+ x=-0.1,
+ y=0.5,
+ xref=u"x",
+ yref=u"paper",
+ xanchor=u"center",
+ yanchor=u"middle",
+ text=plot.get(u"y-axis", u""),
font=dict(
size=16,
),
- align="center",
+ align=u"center",
+ textangle=270,
showarrow=False
- ))
- # X-axis, title:
- annotations.append(dict(
- x=0.55,
- y=-0.15,
- xref="paper",
- yref="y",
- xanchor="center",
- yanchor="bottom",
- text=plot.get("x-axis", ""),
- font=dict(
- size=16,
- ),
- align="center",
- showarrow=False
- ))
- # Y-axis, title:
- annotations.append(dict(
- x=-0.1,
- y=0.5,
- xref="x",
- yref="paper",
- xanchor="center",
- yanchor="middle",
- text=plot.get("y-axis", ""),
- font=dict(
- size=16,
- ),
- align="center",
- textangle=270,
- showarrow=False
- ))
+ )
+ )
updatemenus = list([
dict(
- active=0,
x=1.0,
y=0.0,
- xanchor='right',
- yanchor='bottom',
- direction='up',
+ xanchor=u"right",
+ yanchor=u"bottom",
+ direction=u"up",
buttons=list([
dict(
- label=plot["reference"]["name"],
- method="update",
args=[
{
- "visible": [True, False, False]
- },
- {
- "colorscale": [my_green, ],
- "reversescale": False,
- "annotations": annotations + annotations_r,
- },
- ]
+ u"colorscale": [my_green, ],
+ u"reversescale": False
+ }
+ ],
+ label=u"Green",
+ method=u"update"
),
dict(
- label=plot["compare"]["name"],
- method="update",
args=[
{
- "visible": [False, True, False]
- },
- {
- "colorscale": [my_blue, ],
- "reversescale": False,
- "annotations": annotations + annotations_c,
- },
- ]
+ u"colorscale": [my_blue, ],
+ u"reversescale": False
+ }
+ ],
+ label=u"Blue",
+ method=u"update"
),
dict(
- label="Diff",
- method="update",
args=[
{
- "visible": [False, False, True]
- },
- {
- "colorscale": [my_grey, ],
- "reversescale": False,
- "annotations": annotations + annotations_diff,
- },
- ]
- ),
+ u"colorscale": [my_grey, ],
+ u"reversescale": False
+ }
+ ],
+ label=u"Grey",
+ method=u"update"
+ )
])
)
])
try:
- layout = deepcopy(plot["layout"])
+ layout = deepcopy(plot[u"layout"])
except KeyError as err:
- logging.error("Finished with error: No layout defined")
- logging.error(repr(err))
+ logging.error(f"Finished with error: No layout defined\n{repr(err)}")
return
- layout["annotations"] = annotations + annotations_r
- layout['updatemenus'] = updatemenus
+ layout[u"annotations"] = annotations
+ layout[u'updatemenus'] = updatemenus
try:
# Create plot
plpl = plgo.Figure(data=traces, layout=layout)
# Export Plot
- logging.info(" Writing file '{0}{1}'.".
- format(plot["output-file"], plot["output-file-type"]))
- ploff.plot(plpl, show_link=False, auto_open=False,
- filename='{0}{1}'.format(plot["output-file"],
- plot["output-file-type"]))
+ logging.info(f" Writing file {plot[u'output-file']}.html")
+ ploff.plot(
+ plpl,
+ show_link=False,
+ auto_open=False,
+ filename=f"{plot[u'output-file']}.html"
+ )
except PlotlyError as err:
- logging.error(" Finished with error: {}".
- format(str(err).replace("\n", " ")))
+ logging.error(
+ f" Finished with error: {repr(err)}".replace(u"\n", u" ")
+ )
return