+++ /dev/null
-# Copyright (c) 2019 Cisco and/or its affiliates.
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at:
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""Algorithms to generate plots.
-"""
-
-
-import re
-import logging
-import pandas as pd
-import plotly.offline as ploff
-import plotly.graph_objs as plgo
-
-from plotly.exceptions import PlotlyError
-from collections import OrderedDict
-from copy import deepcopy
-
-from utils import mean, 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"]
-
-REGEX_NIC = re.compile(r'\d*ge\dp\d\D*\d*-')
-
-
-def generate_plots(spec, data):
- """Generate all plots specified in the specification file.
-
- :param spec: Specification read from the specification file.
- :param data: Data to process.
- :type spec: Specification
- :type data: InputData
- """
-
- logging.info("Generating the plots ...")
- for index, plot in enumerate(spec.plots):
- try:
- logging.info(" Plot nr {0}: {1}".format(index + 1,
- plot.get("title", "")))
- plot["limits"] = spec.configuration["limits"]
- eval(plot["algorithm"])(plot, data)
- logging.info(" Done.")
- except NameError as err:
- logging.error("Probably algorithm '{alg}' is not defined: {err}".
- format(alg=plot["algorithm"], err=repr(err)))
- logging.info("Done.")
-
-
-def plot_performance_box(plot, input_data):
- """Generate the plot(s) with algorithm: plot_performance_box
- specified in the specification file.
-
- :param plot: Plot to generate.
- :param input_data: Data to process.
- :type plot: pandas.Series
- :type input_data: InputData
- """
-
- # Transform the data
- plot_title = plot.get("title", "")
- logging.info(" Creating the data set for the {0} '{1}'.".
- format(plot.get("type", ""), plot_title))
- data = input_data.filter_data(plot)
- if data is None:
- logging.error("No data.")
- return
-
- # Prepare the data for the plot
- y_vals = dict()
- y_tags = dict()
- for job in data:
- for build in job:
- for test in build:
- if y_vals.get(test["parent"], None) is None:
- y_vals[test["parent"]] = list()
- y_tags[test["parent"]] = test.get("tags", None)
- try:
- if test["type"] in ("NDRPDR", ):
- if "-pdr" in plot_title.lower():
- y_vals[test["parent"]].\
- append(test["throughput"]["PDR"]["LOWER"])
- elif "-ndr" in plot_title.lower():
- y_vals[test["parent"]]. \
- append(test["throughput"]["NDR"]["LOWER"])
- else:
- continue
- else:
- continue
- except (KeyError, TypeError):
- y_vals[test["parent"]].append(None)
-
- # Sort the tests
- order = plot.get("sort", None)
- if order and y_tags:
- y_sorted = OrderedDict()
- y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()}
- for tag in order:
- logging.debug(tag)
- for suite, tags in y_tags_l.items():
- if "not " in tag:
- tag = tag.split(" ")[-1]
- if tag.lower() in tags:
- continue
- else:
- if tag.lower() not in tags:
- continue
- try:
- y_sorted[suite] = y_vals.pop(suite)
- y_tags_l.pop(suite)
- logging.debug(suite)
- except KeyError as err:
- logging.error("Not found: {0}".format(repr(err)))
- finally:
- break
- else:
- y_sorted = y_vals
-
- # Add None to the lists with missing data
- max_len = 0
- nr_of_samples = list()
- for val in y_sorted.values():
- if len(val) > max_len:
- max_len = len(val)
- nr_of_samples.append(len(val))
- for key, val in y_sorted.items():
- if len(val) < max_len:
- val.extend([None for _ in range(max_len - len(val))])
-
- # Add plot traces
- traces = list()
- df = pd.DataFrame(y_sorted)
- df.head()
- y_max = list()
- for i, col in enumerate(df.columns):
- 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) + 1)
-
- try:
- # Create plot
- layout = deepcopy(plot["layout"])
- if layout.get("title", None):
- layout["title"] = "<b>Throughput:</b> {0}". \
- format(layout["title"])
- if y_max:
- layout["yaxis"]["range"] = [0, max(y_max)]
- plpl = plgo.Figure(data=traces, layout=layout)
-
- # Export Plot
- logging.info(" Writing file '{0}{1}'.".
- format(plot["output-file"], plot["output-file-type"]))
- ploff.plot(plpl, show_link=False, auto_open=False,
- filename='{0}{1}'.format(plot["output-file"],
- plot["output-file-type"]))
- except PlotlyError as err:
- logging.error(" Finished with error: {}".
- format(repr(err).replace("\n", " ")))
- return
-
-
-def plot_soak_bars(plot, input_data):
- """Generate the plot(s) with algorithm: plot_soak_bars
- specified in the specification file.
-
- :param plot: Plot to generate.
- :param input_data: Data to process.
- :type plot: pandas.Series
- :type input_data: InputData
- """
-
- # Transform the data
- plot_title = plot.get("title", "")
- logging.info(" Creating the data set for the {0} '{1}'.".
- format(plot.get("type", ""), plot_title))
- data = input_data.filter_data(plot)
- if data is None:
- logging.error("No data.")
- return
-
- # Prepare the data for the plot
- y_vals = dict()
- y_tags = dict()
- for job in data:
- for build in job:
- for test in build:
- if y_vals.get(test["parent"], None) is None:
- y_tags[test["parent"]] = test.get("tags", None)
- try:
- if test["type"] in ("SOAK", ):
- y_vals[test["parent"]] = test["throughput"]
- else:
- continue
- except (KeyError, TypeError):
- y_vals[test["parent"]] = dict()
-
- # Sort the tests
- order = plot.get("sort", None)
- if order and y_tags:
- y_sorted = OrderedDict()
- y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()}
- for tag in order:
- logging.debug(tag)
- for suite, tags in y_tags_l.items():
- if "not " in tag:
- tag = tag.split(" ")[-1]
- if tag.lower() in tags:
- continue
- else:
- if tag.lower() not in tags:
- continue
- try:
- y_sorted[suite] = y_vals.pop(suite)
- y_tags_l.pop(suite)
- logging.debug(suite)
- except KeyError as err:
- logging.error("Not found: {0}".format(repr(err)))
- finally:
- break
- else:
- y_sorted = y_vals
-
- idx = 0
- y_max = 0
- traces = list()
- for test_name, test_data in y_sorted.items():
- idx += 1
- name = "{nr}. {name}".\
- format(nr=idx, name=test_name.lower().replace('-soak', ''))
- if len(name) > 50:
- name_lst = name.split('-')
- name = ""
- split_name = True
- for segment in name_lst:
- if (len(name) + len(segment) + 1) > 50 and split_name:
- name += "<br> "
- split_name = False
- name += segment + '-'
- name = name[:-1]
-
- y_val = test_data.get("LOWER", None)
- if y_val:
- y_val /= 1000000
- if y_val > y_max:
- y_max = y_val
-
- time = "No Information"
- result = "No Information"
- hovertext = ("{name}<br>"
- "Packet Throughput: {val:.2f}Mpps<br>"
- "Final Duration: {time}<br>"
- "Result: {result}".format(name=name,
- val=y_val,
- time=time,
- result=result))
- traces.append(plgo.Bar(x=[str(idx) + '.', ],
- y=[y_val, ],
- name=name,
- text=hovertext,
- hoverinfo="text"))
- try:
- # Create plot
- layout = deepcopy(plot["layout"])
- if layout.get("title", None):
- layout["title"] = "<b>Packet Throughput:</b> {0}". \
- format(layout["title"])
- if y_max:
- layout["yaxis"]["range"] = [0, y_max + 1]
- plpl = plgo.Figure(data=traces, layout=layout)
- # Export Plot
- logging.info(" Writing file '{0}{1}'.".
- format(plot["output-file"], plot["output-file-type"]))
- ploff.plot(plpl, show_link=False, auto_open=False,
- filename='{0}{1}'.format(plot["output-file"],
- plot["output-file-type"]))
- except PlotlyError as err:
- logging.error(" Finished with error: {}".
- format(repr(err).replace("\n", " ")))
- return
-
-
-def plot_soak_boxes(plot, input_data):
- """Generate the plot(s) with algorithm: plot_soak_boxes
- specified in the specification file.
-
- :param plot: Plot to generate.
- :param input_data: Data to process.
- :type plot: pandas.Series
- :type input_data: InputData
- """
-
- # Transform the data
- plot_title = plot.get("title", "")
- logging.info(" Creating the data set for the {0} '{1}'.".
- format(plot.get("type", ""), plot_title))
- data = input_data.filter_data(plot)
- if data is None:
- logging.error("No data.")
- return
-
- # Prepare the data for the plot
- y_vals = dict()
- y_tags = dict()
- for job in data:
- for build in job:
- for test in build:
- if y_vals.get(test["parent"], None) is None:
- y_tags[test["parent"]] = test.get("tags", None)
- try:
- if test["type"] in ("SOAK", ):
- y_vals[test["parent"]] = test["throughput"]
- else:
- continue
- except (KeyError, TypeError):
- y_vals[test["parent"]] = dict()
-
- # Sort the tests
- order = plot.get("sort", None)
- if order and y_tags:
- y_sorted = OrderedDict()
- y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()}
- for tag in order:
- logging.debug(tag)
- for suite, tags in y_tags_l.items():
- if "not " in tag:
- tag = tag.split(" ")[-1]
- if tag.lower() in tags:
- continue
- else:
- if tag.lower() not in tags:
- continue
- try:
- y_sorted[suite] = y_vals.pop(suite)
- y_tags_l.pop(suite)
- logging.debug(suite)
- except KeyError as err:
- logging.error("Not found: {0}".format(repr(err)))
- finally:
- break
- else:
- y_sorted = y_vals
-
- idx = 0
- y_max = 0
- traces = list()
- for test_name, test_data in y_sorted.items():
- idx += 1
- name = "{nr}. {name}".\
- format(nr=idx, name=test_name.lower().replace('-soak', '').
- replace('2n1l-', ''))
- if len(name) > 55:
- name_lst = name.split('-')
- name = ""
- split_name = True
- for segment in name_lst:
- if (len(name) + len(segment) + 1) > 55 and split_name:
- name += "<br> "
- split_name = False
- name += segment + '-'
- name = name[:-1]
-
- y_val = test_data.get("UPPER", None)
- if y_val:
- y_val /= 1000000
- if y_val > y_max:
- y_max = y_val
-
- y_base = test_data.get("LOWER", None)
- if y_base:
- y_base /= 1000000
-
- hovertext = ("Upper bound: {upper:.2f}<br>"
- "Lower bound: {lower:.2f}".format(upper=y_val,
- lower=y_base))
- traces.append(plgo.Bar(x=[str(idx) + '.', ],
- # +0.05 to see the value in case lower == upper
- y=[y_val - y_base + 0.05, ],
- base=y_base,
- name=name,
- text=hovertext,
- hoverinfo="text"))
- try:
- # Create plot
- layout = deepcopy(plot["layout"])
- if layout.get("title", None):
- layout["title"] = "<b>Throughput:</b> {0}". \
- format(layout["title"])
- if y_max:
- layout["yaxis"]["range"] = [0, y_max + 1]
- plpl = plgo.Figure(data=traces, layout=layout)
- # Export Plot
- logging.info(" Writing file '{0}{1}'.".
- format(plot["output-file"], plot["output-file-type"]))
- ploff.plot(plpl, show_link=False, auto_open=False,
- filename='{0}{1}'.format(plot["output-file"],
- plot["output-file-type"]))
- except PlotlyError as err:
- logging.error(" Finished with error: {}".
- format(repr(err).replace("\n", " ")))
- return
-
-
-def plot_latency_error_bars(plot, input_data):
- """Generate the plot(s) with algorithm: plot_latency_error_bars
- specified in the specification file.
-
- :param plot: Plot to generate.
- :param input_data: Data to process.
- :type plot: pandas.Series
- :type input_data: InputData
- """
-
- # Transform the data
- plot_title = plot.get("title", "")
- logging.info(" Creating the data set for the {0} '{1}'.".
- format(plot.get("type", ""), plot_title))
- data = input_data.filter_data(plot)
- if data is None:
- logging.error("No data.")
- return
-
- # Prepare the data for the plot
- y_tmp_vals = dict()
- y_tags = dict()
- for job in data:
- for build in job:
- for test in build:
- try:
- logging.debug("test['latency']: {0}\n".
- format(test["latency"]))
- except ValueError as err:
- logging.warning(repr(err))
- if y_tmp_vals.get(test["parent"], None) is None:
- y_tmp_vals[test["parent"]] = [
- list(), # direction1, min
- list(), # direction1, avg
- list(), # direction1, max
- list(), # direction2, min
- list(), # direction2, avg
- list() # direction2, max
- ]
- y_tags[test["parent"]] = test.get("tags", None)
- try:
- if test["type"] in ("NDRPDR", ):
- if "-pdr" in plot_title.lower():
- ttype = "PDR"
- elif "-ndr" in plot_title.lower():
- ttype = "NDR"
- else:
- logging.warning("Invalid test type: {0}".
- format(test["type"]))
- continue
- y_tmp_vals[test["parent"]][0].append(
- test["latency"][ttype]["direction1"]["min"])
- y_tmp_vals[test["parent"]][1].append(
- test["latency"][ttype]["direction1"]["avg"])
- y_tmp_vals[test["parent"]][2].append(
- test["latency"][ttype]["direction1"]["max"])
- y_tmp_vals[test["parent"]][3].append(
- test["latency"][ttype]["direction2"]["min"])
- y_tmp_vals[test["parent"]][4].append(
- test["latency"][ttype]["direction2"]["avg"])
- y_tmp_vals[test["parent"]][5].append(
- test["latency"][ttype]["direction2"]["max"])
- else:
- logging.warning("Invalid test type: {0}".
- format(test["type"]))
- continue
- except (KeyError, TypeError) as err:
- logging.warning(repr(err))
- logging.debug("y_tmp_vals: {0}\n".format(y_tmp_vals))
-
- # Sort the tests
- order = plot.get("sort", None)
- if order and y_tags:
- y_sorted = OrderedDict()
- y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()}
- for tag in order:
- logging.debug(tag)
- for suite, tags in y_tags_l.items():
- if "not " in tag:
- tag = tag.split(" ")[-1]
- if tag.lower() in tags:
- continue
- else:
- if tag.lower() not in tags:
- continue
- try:
- y_sorted[suite] = y_tmp_vals.pop(suite)
- y_tags_l.pop(suite)
- logging.debug(suite)
- except KeyError as err:
- logging.error("Not found: {0}".format(repr(err)))
- finally:
- break
- else:
- y_sorted = y_tmp_vals
-
- logging.debug("y_sorted: {0}\n".format(y_sorted))
- x_vals = list()
- y_vals = list()
- y_mins = list()
- y_maxs = list()
- nr_of_samples = list()
- for key, val in y_sorted.items():
- name = 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}<br>"
- "Test: {test}<br>"
- "Direction: {dir}<br>".format(test=x_vals[idx],
- dir=direction,
- nr=nr_of_samples[idx]))
- if isinstance(y_maxs[idx], float):
- hovertext += "Max: {max:.2f}uSec<br>".format(max=y_maxs[idx])
- if isinstance(y_vals[idx], float):
- hovertext += "Mean: {avg:.2f}uSec<br>".format(avg=y_vals[idx])
- if isinstance(y_mins[idx], float):
- hovertext += "Min: {min:.2f}uSec".format(min=y_mins[idx])
-
- if 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"] = "<b>Latency:</b> {0}".\
- format(layout["title"])
- layout["annotations"] = annotations
- plpl = plgo.Figure(data=traces, layout=layout)
-
- # Export Plot
- ploff.plot(plpl,
- show_link=False, auto_open=False,
- filename='{0}{1}'.format(plot["output-file"],
- plot["output-file-type"]))
- except PlotlyError as err:
- logging.error(" Finished with error: {}".
- format(str(err).replace("\n", " ")))
- return
-
-
-def plot_throughput_speedup_analysis(plot, input_data):
- """Generate the plot(s) with algorithm:
- plot_throughput_speedup_analysis
- specified in the specification file.
-
- :param plot: Plot to generate.
- :param input_data: Data to process.
- :type plot: pandas.Series
- :type input_data: InputData
- """
-
- # Transform the data
- plot_title = plot.get("title", "")
- logging.info(" Creating the data set for the {0} '{1}'.".
- format(plot.get("type", ""), plot_title))
- data = input_data.filter_data(plot)
- if data is None:
- logging.error("No data.")
- return
-
- y_vals = dict()
- y_tags = dict()
- for job in data:
- for build in job:
- for test in build:
- if y_vals.get(test["parent"], None) is None:
- y_vals[test["parent"]] = {"1": list(),
- "2": list(),
- "4": list()}
- y_tags[test["parent"]] = test.get("tags", None)
- try:
- if test["type"] in ("NDRPDR",):
- if "-pdr" in plot_title.lower():
- ttype = "PDR"
- elif "-ndr" in plot_title.lower():
- ttype = "NDR"
- else:
- continue
- if "1C" in test["tags"]:
- y_vals[test["parent"]]["1"]. \
- append(test["throughput"][ttype]["LOWER"])
- elif "2C" in test["tags"]:
- y_vals[test["parent"]]["2"]. \
- append(test["throughput"][ttype]["LOWER"])
- elif "4C" in test["tags"]:
- y_vals[test["parent"]]["4"]. \
- append(test["throughput"][ttype]["LOWER"])
- except (KeyError, TypeError):
- pass
-
- if not y_vals:
- logging.warning("No data for the plot '{}'".
- format(plot.get("title", "")))
- return
-
- y_1c_max = dict()
- for test_name, test_vals in y_vals.items():
- for key, test_val in test_vals.items():
- if test_val:
- avg_val = sum(test_val) / len(test_val)
- y_vals[test_name][key] = (avg_val, len(test_val))
- ideal = avg_val / (int(key) * 1000000.0)
- if test_name not in y_1c_max or ideal > y_1c_max[test_name]:
- y_1c_max[test_name] = ideal
-
- vals = dict()
- y_max = list()
- nic_limit = 0
- lnk_limit = 0
- pci_limit = plot["limits"]["pci"]["pci-g3-x8"]
- for test_name, test_vals in y_vals.items():
- try:
- if test_vals["1"][1]:
- name = 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}<br>" \
- "Mean: {0:.2f}Mpps<br>".format(val["val"][idx],
- val["count"][idx])
- if isinstance(val["diff"][idx], float):
- htext += "Diff: {0:.0f}%<br>".format(round(val["diff"][idx]))
- if isinstance(val["rel"][idx], float):
- htext += "Speedup: {0:.2f}".format(val["rel"][idx])
- hovertext.append(htext)
- traces.append(plgo.Scatter(x=x_vals,
- y=val["val"],
- name=name,
- legendgroup=name,
- mode="lines+markers",
- line=dict(
- color=COLORS[cidx],
- width=2),
- marker=dict(
- symbol="circle",
- size=10
- ),
- text=hovertext,
- hoverinfo="text+name"
- ))
- traces.append(plgo.Scatter(x=x_vals,
- y=val["ideal"],
- name="{0} perfect".format(name),
- legendgroup=name,
- showlegend=False,
- mode="lines",
- line=dict(
- color=COLORS[cidx],
- width=2,
- dash="dash"),
- text=["Perfect: {0:.2f}Mpps".format(y)
- for y in val["ideal"]],
- hoverinfo="text"
- ))
- cidx += 1
- except (IndexError, ValueError, KeyError) as err:
- logging.warning("No data for '{0}'".format(name))
- logging.warning(repr(err))
-
- try:
- # Create plot
- logging.info(" Writing file '{0}{1}'.".
- format(plot["output-file"], plot["output-file-type"]))
- layout = deepcopy(plot["layout"])
- if layout.get("title", None):
- layout["title"] = "<b>Speedup Multi-core:</b> {0}". \
- format(layout["title"])
- # layout["yaxis"]["range"] = [0, int((max(y_max) / 10) + 1) * 10]
- layout["yaxis"]["range"] = [0, int(max(y_max) * 1.1)]
- layout["annotations"].extend(annotations)
- 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 += "<br> "
- 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$')
- REGEX_TEST_NAME = re.compile(r'^.*-(\d+vhost|\d+memif)-'
- r'(\d+chain|\d+pipe)-'
- r'(\d+vm|\d+dcr|\d+drc).*$')
-
- 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 = "{vhost}-{chain}-{vm}".format(
- vhost=str(groups.group(1)),
- chain=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"]
- else:
- result = None
- except TypeError:
- result = None
-
- if result:
- vals[c][n]["vals"].append(result)
-
- 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"]:
- 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)
- 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 = [list() for _ in range(len(chains))]
- for c in chains:
- for n in nodes:
- try:
- val = vals[txt_chains[c - 1]][txt_nodes[n - 1]]["mean"]
- except (KeyError, IndexError):
- val = None
- data[c - 1].append(val)
-
- # 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()
-
- text = ("Test: {name}<br>"
- "Runs: {nr}<br>"
- "Thput: {val}<br>"
- "StDev: {stdev}")
-
- for c in range(len(txt_chains)):
- hover_line = list()
- for n in range(len(txt_nodes)):
- if data[c][n] is not None:
- annotations.append(dict(
- x=n+1,
- y=c+1,
- xref="x",
- yref="y",
- xanchor="center",
- yanchor="middle",
- text=str(data[c][n]),
- font=dict(
- size=14,
- ),
- align="center",
- showarrow=False
- ))
- hover_line.append(text.format(
- name=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"]))
- 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")
- ]
-
- 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"
- ),
- dict(
- args=[{"colorscale": [my_grey, ], "reversescale": False}],
- label="Grey",
- method="update"
- )
- ])
- )
- ])
-
- try:
- layout = deepcopy(plot["layout"])
- except KeyError as err:
- logging.error("Finished with error: No layout defined")
- logging.error(repr(err))
- return
-
- layout["annotations"] = annotations
- layout['updatemenus'] = updatemenus
-
- try:
- # Create plot
- plpl = plgo.Figure(data=traces, layout=layout)
-
- # Export Plot
- logging.info(" Writing file '{0}{1}'.".
- format(plot["output-file"], plot["output-file-type"]))
- ploff.plot(plpl, show_link=False, auto_open=False,
- filename='{0}{1}'.format(plot["output-file"],
- plot["output-file-type"]))
- except PlotlyError as err:
- logging.error(" Finished with error: {}".
- format(str(err).replace("\n", " ")))
- return
-
-
-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$')
- REGEX_TEST_NAME = re.compile(r'^.*-(\d+ch|\d+pl)-'
- r'(\d+vh|\d+mif)-'
- r'(\d+vm|\d+dcr).*$')
- 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_c"].append(result)
- elif str(groups.group(3)) == \
- plot["compare"]["include"]:
- vals[c][n]["vals_r"].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"] = \
- round(mean(vals[key_c][key_n]["vals_r"]) / 1000000, 1)
- 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"] = \
- round(mean(vals[key_c][key_n]["vals_c"]) / 1000000, 1)
- 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
- data_r[c - 1].append(val_r)
- try:
- val_c = vals[txt_chains[c - 1]][txt_nodes[n - 1]]["mean_c"]
- except (KeyError, IndexError):
- val_c = None
- data_c[c - 1].append(val_c)
-
- if val_c is not None and val_r:
- diff[c - 1].append(round((val_c - val_r) * 100 / val_r, 1))
- else:
- diff[c - 1].append(None)
-
- # Colorscales:
- my_green = [[0.0, 'rgb(235, 249, 242)'],
- [1.0, 'rgb(45, 134, 89)']]
-
- my_blue = [[0.0, 'rgb(236, 242, 248)'],
- [1.0, 'rgb(57, 115, 172)']]
-
- my_grey = [[0.0, 'rgb(230, 230, 230)'],
- [1.0, 'rgb(102, 102, 102)']]
-
- hovertext = list()
-
- annotations = list()
- annotations_r = list()
- annotations_c = list()
- annotations_diff = list()
-
- text = ("Test: {name}"
- "<br>{title_r}: {text_r}"
- "<br>{title_c}: {text_c}{text_diff}")
- text_r = "Thput: {val_r}; StDev: {stdev_r}; Runs: {nr_r}"
- text_c = "Thput: {val_c}; StDev: {stdev_c}; Runs: {nr_c}"
- text_diff = "<br>Relative Difference {title_c} vs. {title_r}: {diff}%"
-
- for c in range(len(txt_chains)):
- hover_line = list()
- for n in range(len(txt_nodes)):
- if data_r[c][n] is not None:
- data_point = dict(
- x=n+1,
- y=c+1,
- xref="x",
- yref="y",
- xanchor="center",
- yanchor="middle",
- text=str(data_r[c][n]) if data_r[c][n] is not None else "",
- font=dict(
- size=14,
- ),
- align="center",
- showarrow=False
- )
- annotations_r.append(deepcopy(data_point))
- data_point["text"] = str(data_c[c][n]) \
- if data_c[c][n] is not None else ""
- annotations_c.append(deepcopy(data_point))
- data_point["text"] = str(diff[c][n]) \
- if diff[c][n] is not None else ""
- annotations_diff.append(deepcopy(data_point))
-
- hover_line.append(text.format(
- name=vals[txt_chains[c]][txt_nodes[n]]["name"],
- title_r=plot["reference"]["name"],
- text_r=text_r.format(
- val_r=data_r[c][n],
- stdev_r=vals[txt_chains[c]][txt_nodes[n]]["stdev_r"],
- nr_r=vals[txt_chains[c]][txt_nodes[n]]["nr_r"]
- ) if data_r[c][n] is not None else "Test Failed",
- title_c=plot["compare"]["name"],
- text_c=text_c.format(
- val_c=data_c[c][n],
- stdev_c = vals[txt_chains[c]][txt_nodes[n]]["stdev_c"],
- nr_c=vals[txt_chains[c]][txt_nodes[n]]["nr_c"]
- ) if data_c[c][n] is not None else "Test Failed",
- text_diff=text_diff.format(
- diff=diff[c][n]
- ) if diff[c][n] is not None else ""
- ))
-
- 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 [%]",
- 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,
- 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(
- active=0,
- x=1.0,
- y=0.0,
- xanchor='right',
- yanchor='bottom',
- direction='up',
- buttons=list([
- dict(
- label=plot["reference"]["name"],
- method="update",
- args=[
- {
- "visible": [True, False, False]
- },
- {
- "colorscale": [my_green, ],
- "reversescale": False,
- "annotations": annotations + annotations_r,
- },
- ]
- ),
- dict(
- label=plot["compare"]["name"],
- method="update",
- args=[
- {
- "visible": [False, True, False]
- },
- {
- "colorscale": [my_blue, ],
- "reversescale": False,
- "annotations": annotations + annotations_c,
- },
- ]
- ),
- dict(
- label="Diff",
- method="update",
- args=[
- {
- "visible": [False, False, True]
- },
- {
- "colorscale": [my_grey, ],
- "reversescale": False,
- "annotations": annotations + annotations_diff,
- },
- ]
- ),
- ])
- )
- ])
-
- 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 + annotations_r
- 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
Code Review / csit.git / blobdiff