resources/tools/presentation/generator_plots.py

   1 # Copyright (c) 2018 Cisco and/or its affiliates.
   2 # Licensed under the Apache License, Version 2.0 (the "License");
   3 # you may not use this file except in compliance with the License.
   4 # You may obtain a copy of the License at:
   5 #
   6 #     http://www.apache.org/licenses/LICENSE-2.0
   7 #
   8 # Unless required by applicable law or agreed to in writing, software
   9 # distributed under the License is distributed on an "AS IS" BASIS,
  10 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  11 # See the License for the specific language governing permissions and
  12 # limitations under the License.
  13
  14 """Algorithms to generate plots.
  15 """
  16
  17
  18 import logging
  19 import pandas as pd
  20 import plotly.offline as ploff
  21 import plotly.graph_objs as plgo
  22
  23 from plotly.exceptions import PlotlyError
  24 from collections import OrderedDict
  25 from copy import deepcopy
  26
  27 from utils import mean
  28
  29
  30 COLORS = ["SkyBlue", "Olive", "Purple", "Coral", "Indigo", "Pink",
  31           "Chocolate", "Brown", "Magenta", "Cyan", "Orange", "Black",
  32           "Violet", "Blue", "Yellow", "BurlyWood", "CadetBlue", "Crimson",
  33           "DarkBlue", "DarkCyan", "DarkGreen", "Green", "GoldenRod",
  34           "LightGreen", "LightSeaGreen", "LightSkyBlue", "Maroon",
  35           "MediumSeaGreen", "SeaGreen", "LightSlateGrey"]
  36
  37
  38 def generate_plots(spec, data):
  39     """Generate all plots specified in the specification file.
  40
  41     :param spec: Specification read from the specification file.
  42     :param data: Data to process.
  43     :type spec: Specification
  44     :type data: InputData
  45     """
  46
  47     logging.info("Generating the plots ...")
  48     for index, plot in enumerate(spec.plots):
  49         try:
  50             logging.info("  Plot nr {0}: {1}".format(index + 1,
  51                                                      plot.get("title", "")))
  52             plot["limits"] = spec.configuration["limits"]
  53             eval(plot["algorithm"])(plot, data)
  54             logging.info("  Done.")
  55         except NameError as err:
  56             logging.error("Probably algorithm '{alg}' is not defined: {err}".
  57                           format(alg=plot["algorithm"], err=repr(err)))
  58     logging.info("Done.")
  59
  60
  61 def plot_performance_box(plot, input_data):
  62     """Generate the plot(s) with algorithm: plot_performance_box
  63     specified in the specification file.
  64
  65     :param plot: Plot to generate.
  66     :param input_data: Data to process.
  67     :type plot: pandas.Series
  68     :type input_data: InputData
  69     """
  70
  71     # Transform the data
  72     plot_title = plot.get("title", "")
  73     logging.info("    Creating the data set for the {0} '{1}'.".
  74                  format(plot.get("type", ""), plot_title))
  75     data = input_data.filter_data(plot)
  76     if data is None:
  77         logging.error("No data.")
  78         return
  79
  80     # Prepare the data for the plot
  81     y_vals = dict()
  82     y_tags = dict()
  83     for job in data:
  84         for build in job:
  85             for test in build:
  86                 if y_vals.get(test["parent"], None) is None:
  87                     y_vals[test["parent"]] = list()
  88                     y_tags[test["parent"]] = test.get("tags", None)
  89                 try:
  90                     if test["type"] in ("NDRPDR", ):
  91                         if "-pdr" in plot_title.lower():
  92                             y_vals[test["parent"]].\
  93                                 append(test["throughput"]["PDR"]["LOWER"])
  94                         elif "-ndr" in plot_title.lower():
  95                             y_vals[test["parent"]]. \
  96                                 append(test["throughput"]["NDR"]["LOWER"])
  97                         else:
  98                             continue
  99                     else:
 100                         continue
 101                 except (KeyError, TypeError):
 102                     y_vals[test["parent"]].append(None)
 103
 104     # Sort the tests
 105     order = plot.get("sort", None)
 106     if order and y_tags:
 107         y_sorted = OrderedDict()
 108         y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()}
 109         for tag in order:
 110             logging.info(tag)
 111             for suite, tags in y_tags_l.items():
 112                 if "not " in tag:
 113                     tag = tag.split(" ")[-1]
 114                     if tag.lower() in tags:
 115                         continue
 116                 else:
 117                     if tag.lower() not in tags:
 118                         continue
 119                 try:
 120                     y_sorted[suite] = y_vals.pop(suite)
 121                     y_tags_l.pop(suite)
 122                     logging.info(suite)
 123                 except KeyError as err:
 124                     logging.error("Not found: {0}".format(err))
 125                 finally:
 126                     break
 127     else:
 128         y_sorted = y_vals
 129
 130     # Add None to the lists with missing data
 131     max_len = 0
 132     for val in y_sorted.values():
 133         if len(val) > max_len:
 134             max_len = len(val)
 135     for key, val in y_sorted.items():
 136         if len(val) < max_len:
 137             val.extend([None for _ in range(max_len - len(val))])
 138
 139     # Add plot traces
 140     traces = list()
 141     df = pd.DataFrame(y_sorted)
 142     df.head()
 143     y_max = list()
 144     for i, col in enumerate(df.columns):
 145         name = "{0}. {1}".format(i + 1, col.lower().replace('-ndrpdrdisc', '').
 146                                  replace('-ndrpdr', ''))
 147         logging.info(name)
 148         traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]),
 149                                y=[y / 1000000 if y else None for y in df[col]],
 150                                name=name,
 151                                **plot["traces"]))
 152         try:
 153             val_max = max(df[col])
 154         except ValueError as err:
 155             logging.error(err)
 156             continue
 157         if val_max:
 158             y_max.append(int(val_max / 1000000) + 1)
 159
 160     try:
 161         # Create plot
 162         layout = deepcopy(plot["layout"])
 163         if layout.get("title", None):
 164             layout["title"] = "<b>Packet Throughput:</b> {0}". \
 165                 format(layout["title"])
 166         if y_max:
 167             layout["yaxis"]["range"] = [0, max(y_max)]
 168         plpl = plgo.Figure(data=traces, layout=layout)
 169
 170         # Export Plot
 171         logging.info("    Writing file '{0}{1}'.".
 172                      format(plot["output-file"], plot["output-file-type"]))
 173         ploff.plot(plpl, show_link=False, auto_open=False,
 174                    filename='{0}{1}'.format(plot["output-file"],
 175                                             plot["output-file-type"]))
 176     except PlotlyError as err:
 177         logging.error("   Finished with error: {}".
 178                       format(str(err).replace("\n", " ")))
 179         return
 180
 181
 182 def plot_latency_error_bars(plot, input_data):
 183     """Generate the plot(s) with algorithm: plot_latency_error_bars
 184     specified in the specification file.
 185
 186     :param plot: Plot to generate.
 187     :param input_data: Data to process.
 188     :type plot: pandas.Series
 189     :type input_data: InputData
 190     """
 191
 192     # Transform the data
 193     plot_title = plot.get("title", "")
 194     logging.info("    Creating the data set for the {0} '{1}'.".
 195                  format(plot.get("type", ""), plot_title))
 196     data = input_data.filter_data(plot)
 197     if data is None:
 198         logging.error("No data.")
 199         return
 200
 201     # Prepare the data for the plot
 202     y_tmp_vals = dict()
 203     y_tags = dict()
 204     for job in data:
 205         for build in job:
 206             for test in build:
 207                 if y_tmp_vals.get(test["parent"], None) is None:
 208                     y_tmp_vals[test["parent"]] = [
 209                         list(),  # direction1, min
 210                         list(),  # direction1, avg
 211                         list(),  # direction1, max
 212                         list(),  # direction2, min
 213                         list(),  # direction2, avg
 214                         list()   # direction2, max
 215                     ]
 216                     y_tags[test["parent"]] = test.get("tags", None)
 217                 try:
 218                     if test["type"] in ("NDRPDR", ):
 219                         if "-pdr" in plot_title.lower():
 220                             ttype = "PDR"
 221                         elif "-ndr" in plot_title.lower():
 222                             ttype = "NDR"
 223                         else:
 224                             continue
 225                         y_tmp_vals[test["parent"]][0].append(
 226                             test["latency"][ttype]["direction1"]["min"])
 227                         y_tmp_vals[test["parent"]][1].append(
 228                             test["latency"][ttype]["direction1"]["avg"])
 229                         y_tmp_vals[test["parent"]][2].append(
 230                             test["latency"][ttype]["direction1"]["max"])
 231                         y_tmp_vals[test["parent"]][3].append(
 232                             test["latency"][ttype]["direction2"]["min"])
 233                         y_tmp_vals[test["parent"]][4].append(
 234                             test["latency"][ttype]["direction2"]["avg"])
 235                         y_tmp_vals[test["parent"]][5].append(
 236                             test["latency"][ttype]["direction2"]["max"])
 237                     else:
 238                         continue
 239                 except (KeyError, TypeError):
 240                     pass
 241
 242     # Sort the tests
 243     order = plot.get("sort", None)
 244     if order and y_tags:
 245         y_sorted = OrderedDict()
 246         y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()}
 247         for tag in order:
 248             logging.info(tag)
 249             for suite, tags in y_tags_l.items():
 250                 if "not " in tag:
 251                     tag = tag.split(" ")[-1]
 252                     if tag.lower() in tags:
 253                         continue
 254                 else:
 255                     if tag.lower() not in tags:
 256                         continue
 257                 try:
 258                     y_sorted[suite] = y_tmp_vals.pop(suite)
 259                     y_tags_l.pop(suite)
 260                     logging.info(suite)
 261                 except KeyError as err:
 262                     logging.error("Not found: {0}".format(err))
 263                 finally:
 264                     break
 265     else:
 266         y_sorted = y_tmp_vals
 267
 268     x_vals = list()
 269     y_vals = list()
 270     y_mins = list()
 271     y_maxs = list()
 272     for key, val in y_sorted.items():
 273         key = "-".join(key.split("-")[1:-1])
 274         x_vals.append(key)  # dir 1
 275         y_vals.append(mean(val[1]) if val[1] else None)
 276         y_mins.append(mean(val[0]) if val[0] else None)
 277         y_maxs.append(mean(val[2]) if val[2] else None)
 278         x_vals.append(key)  # dir 2
 279         y_vals.append(mean(val[4]) if val[4] else None)
 280         y_mins.append(mean(val[3]) if val[3] else None)
 281         y_maxs.append(mean(val[5]) if val[5] else None)
 282
 283     traces = list()
 284     annotations = list()
 285
 286     for idx in range(len(x_vals)):
 287         if not bool(int(idx % 2)):
 288             direction = "West - East"
 289         else:
 290             direction = "East - West"
 291         hovertext = ("Test: {test}<br>"
 292                      "Direction: {dir}<br>".format(test=x_vals[idx],
 293                                                    dir=direction))
 294         if isinstance(y_maxs[idx], float):
 295             hovertext += "Max: {max:.2f}uSec<br>".format(max=y_maxs[idx])
 296         if isinstance(y_vals[idx], float):
 297             hovertext += "Avg: {avg:.2f}uSec<br>".format(avg=y_vals[idx])
 298         if isinstance(y_mins[idx], float):
 299             hovertext += "Min: {min:.2f}uSec".format(min=y_mins[idx])
 300
 301         if isinstance(y_maxs[idx], float) and isinstance(y_vals[idx], float):
 302             array = [y_maxs[idx] - y_vals[idx], ]
 303         else:
 304             array = [None, ]
 305         if isinstance(y_mins[idx], float) and isinstance(y_vals[idx], float):
 306             arrayminus = [y_vals[idx] - y_mins[idx], ]
 307         else:
 308             arrayminus = [None, ]
 309         traces.append(plgo.Scatter(
 310             x=[idx, ],
 311             y=[y_vals[idx], ],
 312             name=x_vals[idx],
 313             legendgroup=x_vals[idx],
 314             showlegend=bool(int(idx % 2)),
 315             mode="markers",
 316             error_y=dict(
 317                 type='data',
 318                 symmetric=False,
 319                 array=array,
 320                 arrayminus=arrayminus,
 321                 color=COLORS[int(idx / 2)]
 322             ),
 323             marker=dict(
 324                 size=10,
 325                 color=COLORS[int(idx / 2)],
 326             ),
 327             text=hovertext,
 328             hoverinfo="text",
 329         ))
 330         annotations.append(dict(
 331             x=idx,
 332             y=0,
 333             xref="x",
 334             yref="y",
 335             xanchor="center",
 336             yanchor="top",
 337             text="E-W" if bool(int(idx % 2)) else "W-E",
 338             font=dict(
 339                 size=16,
 340             ),
 341             align="center",
 342             showarrow=False
 343         ))
 344
 345     try:
 346         # Create plot
 347         logging.info("    Writing file '{0}{1}'.".
 348                      format(plot["output-file"], plot["output-file-type"]))
 349         layout = deepcopy(plot["layout"])
 350         if layout.get("title", None):
 351             layout["title"] = "<b>Packet Latency:</b> {0}".\
 352                 format(layout["title"])
 353         layout["annotations"] = annotations
 354         plpl = plgo.Figure(data=traces, layout=layout)
 355
 356         # Export Plot
 357         ploff.plot(plpl,
 358                    show_link=False, auto_open=False,
 359                    filename='{0}{1}'.format(plot["output-file"],
 360                                             plot["output-file-type"]))
 361     except PlotlyError as err:
 362         logging.error("   Finished with error: {}".
 363                       format(str(err).replace("\n", " ")))
 364         return
 365
 366
 367 def plot_throughput_speedup_analysis(plot, input_data):
 368     """Generate the plot(s) with algorithm:
 369     plot_throughput_speedup_analysis
 370     specified in the specification file.
 371
 372     :param plot: Plot to generate.
 373     :param input_data: Data to process.
 374     :type plot: pandas.Series
 375     :type input_data: InputData
 376     """
 377
 378     # Transform the data
 379     plot_title = plot.get("title", "")
 380     logging.info("    Creating the data set for the {0} '{1}'.".
 381                  format(plot.get("type", ""), plot_title))
 382     data = input_data.filter_data(plot)
 383     if data is None:
 384         logging.error("No data.")
 385         return
 386
 387     y_vals = dict()
 388     y_tags = dict()
 389     for job in data:
 390         for build in job:
 391             for test in build:
 392                 if y_vals.get(test["parent"], None) is None:
 393                     y_vals[test["parent"]] = {"1": list(),
 394                                               "2": list(),
 395                                               "4": list()}
 396                     y_tags[test["parent"]] = test.get("tags", None)
 397                 try:
 398                     if test["type"] in ("NDRPDR",):
 399                         if "-pdr" in plot_title.lower():
 400                             ttype = "PDR"
 401                         elif "-ndr" in plot_title.lower():
 402                             ttype = "NDR"
 403                         else:
 404                             continue
 405                         if "1C" in test["tags"]:
 406                             y_vals[test["parent"]]["1"]. \
 407                                 append(test["throughput"][ttype]["LOWER"])
 408                         elif "2C" in test["tags"]:
 409                             y_vals[test["parent"]]["2"]. \
 410                                 append(test["throughput"][ttype]["LOWER"])
 411                         elif "4C" in test["tags"]:
 412                             y_vals[test["parent"]]["4"]. \
 413                                 append(test["throughput"][ttype]["LOWER"])
 414                 except (KeyError, TypeError):
 415                     pass
 416
 417     if not y_vals:
 418         logging.warning("No data for the plot '{}'".
 419                         format(plot.get("title", "")))
 420         return
 421
 422     y_1c_max = dict()
 423     for test_name, test_vals in y_vals.items():
 424         for key, test_val in test_vals.items():
 425             if test_val:
 426                 y_vals[test_name][key] = sum(test_val) / len(test_val)
 427                 if key == "1":
 428                     y_1c_max[test_name] = max(test_val) / 1000000.0
 429
 430     vals = dict()
 431     y_max = list()
 432     nic_limit = 0
 433     lnk_limit = 0
 434     pci_limit = plot["limits"]["pci"]["pci-g3-x8"]
 435     for test_name, test_vals in y_vals.items():
 436         if test_vals["1"]:
 437             name = "-".join(test_name.split('-')[1:-1])
 438
 439             vals[name] = dict()
 440             y_val_1 = test_vals["1"] / 1000000.0
 441             y_val_2 = test_vals["2"] / 1000000.0 if test_vals["2"] else None
 442             y_val_4 = test_vals["4"] / 1000000.0 if test_vals["4"] else None
 443
 444             vals[name]["val"] = [y_val_1, y_val_2, y_val_4]
 445             vals[name]["rel"] = [1.0, None, None]
 446             vals[name]["ideal"] = [y_1c_max[test_name],
 447                                    y_1c_max[test_name] * 2,
 448                                    y_1c_max[test_name] * 4]
 449             vals[name]["diff"] = \
 450                 [(y_val_1 - y_1c_max[test_name]) * 100 / y_val_1, None, None]
 451
 452             try:
 453                 val_max = max(max(vals[name]["val"], vals[name]["ideal"]))
 454             except ValueError as err:
 455                 logging.error(err)
 456                 continue
 457             if val_max:
 458                 y_max.append(int((val_max / 10) + 1) * 10)
 459
 460             if y_val_2:
 461                 vals[name]["rel"][1] = round(y_val_2 / y_val_1, 2)
 462                 vals[name]["diff"][1] = \
 463                     (y_val_2 - vals[name]["ideal"][1]) * 100 / y_val_2
 464             if y_val_4:
 465                 vals[name]["rel"][2] = round(y_val_4 / y_val_1, 2)
 466                 vals[name]["diff"][2] = \
 467                     (y_val_4 - vals[name]["ideal"][2]) * 100 / y_val_4
 468
 469         # Limits:
 470         if "x520" in test_name:
 471             limit = plot["limits"]["nic"]["x520"]
 472         elif "x710" in test_name:
 473             limit = plot["limits"]["nic"]["x710"]
 474         elif "xxv710" in test_name:
 475             limit = plot["limits"]["nic"]["xxv710"]
 476         elif "xl710" in test_name:
 477             limit = plot["limits"]["nic"]["xl710"]
 478         else:
 479             limit = 0
 480         if limit > nic_limit:
 481             nic_limit = limit
 482
 483         mul = 2 if "ge2p" in test_name else 1
 484         if "10ge" in test_name:
 485             limit = plot["limits"]["link"]["10ge"] * mul
 486         elif "25ge" in test_name:
 487             limit = plot["limits"]["link"]["25ge"] * mul
 488         elif "40ge" in test_name:
 489             limit = plot["limits"]["link"]["40ge"] * mul
 490         elif "100ge" in test_name:
 491             limit = plot["limits"]["link"]["100ge"] * mul
 492         else:
 493             limit = 0
 494         if limit > lnk_limit:
 495             lnk_limit = limit
 496
 497     # Sort the tests
 498     order = plot.get("sort", None)
 499     if order and y_tags:
 500         y_sorted = OrderedDict()
 501         y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()}
 502         for tag in order:
 503             for test, tags in y_tags_l.items():
 504                 if tag.lower() in tags:
 505                     name = "-".join(test.split('-')[1:-1])
 506                     try:
 507                         y_sorted[name] = vals.pop(name)
 508                         y_tags_l.pop(test)
 509                     except KeyError as err:
 510                         logging.error("Not found: {0}".format(err))
 511                     finally:
 512                         break
 513     else:
 514         y_sorted = vals
 515
 516     traces = list()
 517     annotations = list()
 518     x_vals = [1, 2, 4]
 519
 520     # Limits:
 521     try:
 522         threshold = 1.1 * max(y_max)  # 10%
 523     except ValueError as err:
 524         logging.error(err)
 525         return
 526     nic_limit /= 1000000.0
 527     if nic_limit < threshold:
 528         traces.append(plgo.Scatter(
 529             x=x_vals,
 530             y=[nic_limit, ] * len(x_vals),
 531             name="NIC: {0:.2f}Mpps".format(nic_limit),
 532             showlegend=False,
 533             mode="lines",
 534             line=dict(
 535                 dash="dot",
 536                 color=COLORS[-1],
 537                 width=1),
 538             hoverinfo="none"
 539         ))
 540         annotations.append(dict(
 541             x=1,
 542             y=nic_limit,
 543             xref="x",
 544             yref="y",
 545             xanchor="left",
 546             yanchor="bottom",
 547             text="NIC: {0:.2f}Mpps".format(nic_limit),
 548             font=dict(
 549                 size=14,
 550                 color=COLORS[-1],
 551             ),
 552             align="left",
 553             showarrow=False
 554         ))
 555         y_max.append(int((nic_limit / 10) + 1) * 10)
 556
 557     lnk_limit /= 1000000.0
 558     if lnk_limit < threshold:
 559         traces.append(plgo.Scatter(
 560             x=x_vals,
 561             y=[lnk_limit, ] * len(x_vals),
 562             name="Link: {0:.2f}Mpps".format(lnk_limit),
 563             showlegend=False,
 564             mode="lines",
 565             line=dict(
 566                 dash="dot",
 567                 color=COLORS[-2],
 568                 width=1),
 569             hoverinfo="none"
 570         ))
 571         annotations.append(dict(
 572             x=1,
 573             y=lnk_limit,
 574             xref="x",
 575             yref="y",
 576             xanchor="left",
 577             yanchor="bottom",
 578             text="Link: {0:.2f}Mpps".format(lnk_limit),
 579             font=dict(
 580                 size=14,
 581                 color=COLORS[-2],
 582             ),
 583             align="left",
 584             showarrow=False
 585         ))
 586         y_max.append(int((lnk_limit / 10) + 1) * 10)
 587
 588     pci_limit /= 1000000.0
 589     if pci_limit < threshold:
 590         traces.append(plgo.Scatter(
 591             x=x_vals,
 592             y=[pci_limit, ] * len(x_vals),
 593             name="PCIe: {0:.2f}Mpps".format(pci_limit),
 594             showlegend=False,
 595             mode="lines",
 596             line=dict(
 597                 dash="dot",
 598                 color=COLORS[-3],
 599                 width=1),
 600             hoverinfo="none"
 601         ))
 602         annotations.append(dict(
 603             x=1,
 604             y=pci_limit,
 605             xref="x",
 606             yref="y",
 607             xanchor="left",
 608             yanchor="bottom",
 609             text="PCIe: {0:.2f}Mpps".format(pci_limit),
 610             font=dict(
 611                 size=14,
 612                 color=COLORS[-3],
 613             ),
 614             align="left",
 615             showarrow=False
 616         ))
 617         y_max.append(int((pci_limit / 10) + 1) * 10)
 618
 619     # Perfect and measured:
 620     cidx = 0
 621     for name, val in y_sorted.iteritems():
 622         hovertext = list()
 623         for idx in range(len(val["val"])):
 624             htext = ""
 625             if isinstance(val["val"][idx], float):
 626                 htext += "value: {0:.2f}Mpps<br>".format(val["val"][idx])
 627             if isinstance(val["diff"][idx], float):
 628                 htext += "diff: {0:.0f}%<br>".format(round(val["diff"][idx]))
 629             if isinstance(val["rel"][idx], float):
 630                 htext += "speedup: {0:.2f}".format(val["rel"][idx])
 631             hovertext.append(htext)
 632         traces.append(plgo.Scatter(x=x_vals,
 633                                    y=val["val"],
 634                                    name=name,
 635                                    legendgroup=name,
 636                                    mode="lines+markers",
 637                                    line=dict(
 638                                        color=COLORS[cidx],
 639                                        width=2),
 640                                    marker=dict(
 641                                        symbol="circle",
 642                                        size=10
 643                                    ),
 644                                    text=hovertext,
 645                                    hoverinfo="text+name"
 646                                    ))
 647         traces.append(plgo.Scatter(x=x_vals,
 648                                    y=val["ideal"],
 649                                    name="{0} perfect".format(name),
 650                                    legendgroup=name,
 651                                    showlegend=False,
 652                                    mode="lines",
 653                                    line=dict(
 654                                        color=COLORS[cidx],
 655                                        width=2,
 656                                        dash="dash"),
 657                                    text=["perfect: {0:.2f}Mpps".format(y)
 658                                          for y in val["ideal"]],
 659                                    hoverinfo="text"
 660                                    ))
 661         cidx += 1
 662
 663     try:
 664         # Create plot
 665         logging.info("    Writing file '{0}{1}'.".
 666                      format(plot["output-file"], plot["output-file-type"]))
 667         layout = deepcopy(plot["layout"])
 668         if layout.get("title", None):
 669             layout["title"] = "<b>Speedup Multi-core:</b> {0}". \
 670                 format(layout["title"])
 671         layout["annotations"].extend(annotations)
 672         plpl = plgo.Figure(data=traces, layout=layout)
 673
 674         # Export Plot
 675         ploff.plot(plpl,
 676                    show_link=False, auto_open=False,
 677                    filename='{0}{1}'.format(plot["output-file"],
 678                                             plot["output-file-type"]))
 679     except PlotlyError as err:
 680         logging.error("   Finished with error: {}".
 681                       format(str(err).replace("\n", " ")))
 682         return
 683
 684
 685 def plot_http_server_performance_box(plot, input_data):
 686     """Generate the plot(s) with algorithm: plot_http_server_performance_box
 687     specified in the specification file.
 688
 689     :param plot: Plot to generate.
 690     :param input_data: Data to process.
 691     :type plot: pandas.Series
 692     :type input_data: InputData
 693     """
 694
 695     # Transform the data
 696     logging.info("    Creating the data set for the {0} '{1}'.".
 697                  format(plot.get("type", ""), plot.get("title", "")))
 698     data = input_data.filter_data(plot)
 699     if data is None:
 700         logging.error("No data.")
 701         return
 702
 703     # Prepare the data for the plot
 704     y_vals = dict()
 705     for job in data:
 706         for build in job:
 707             for test in build:
 708                 if y_vals.get(test["name"], None) is None:
 709                     y_vals[test["name"]] = list()
 710                 try:
 711                     y_vals[test["name"]].append(test["result"])
 712                 except (KeyError, TypeError):
 713                     y_vals[test["name"]].append(None)
 714
 715     # Add None to the lists with missing data
 716     max_len = 0
 717     for val in y_vals.values():
 718         if len(val) > max_len:
 719             max_len = len(val)
 720     for key, val in y_vals.items():
 721         if len(val) < max_len:
 722             val.extend([None for _ in range(max_len - len(val))])
 723
 724     # Add plot traces
 725     traces = list()
 726     df = pd.DataFrame(y_vals)
 727     df.head()
 728     for i, col in enumerate(df.columns):
 729         name = "{0}. {1}".format(i + 1, col.lower().replace('-cps', '').
 730                                  replace('-rps', ''))
 731         traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]),
 732                                y=df[col],
 733                                name=name,
 734                                **plot["traces"]))
 735     try:
 736         # Create plot
 737         plpl = plgo.Figure(data=traces, layout=plot["layout"])
 738
 739         # Export Plot
 740         logging.info("    Writing file '{0}{1}'.".
 741                      format(plot["output-file"], plot["output-file-type"]))
 742         ploff.plot(plpl, show_link=False, auto_open=False,
 743                    filename='{0}{1}'.format(plot["output-file"],
 744                                             plot["output-file-type"]))
 745     except PlotlyError as err:
 746         logging.error("   Finished with error: {}".
 747                       format(str(err).replace("\n", " ")))
 748         return