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         val_max = max(df[col])
 153         if val_max:
 154             y_max.append(int(val_max / 1000000) + 1)
 155
 156     try:
 157         # Create plot
 158         layout = deepcopy(plot["layout"])
 159         if layout.get("title", None):
 160             layout["title"] = "<b>Packet Throughput:</b> {0}". \
 161                 format(layout["title"])
 162         if y_max:
 163             layout["yaxis"]["range"] = [0, max(y_max)]
 164         plpl = plgo.Figure(data=traces, layout=layout)
 165
 166         # Export Plot
 167         logging.info("    Writing file '{0}{1}'.".
 168                      format(plot["output-file"], plot["output-file-type"]))
 169         ploff.plot(plpl, show_link=False, auto_open=False,
 170                    filename='{0}{1}'.format(plot["output-file"],
 171                                             plot["output-file-type"]))
 172     except PlotlyError as err:
 173         logging.error("   Finished with error: {}".
 174                       format(str(err).replace("\n", " ")))
 175         return
 176
 177
 178 def plot_latency_error_bars(plot, input_data):
 179     """Generate the plot(s) with algorithm: plot_latency_error_bars
 180     specified in the specification file.
 181
 182     :param plot: Plot to generate.
 183     :param input_data: Data to process.
 184     :type plot: pandas.Series
 185     :type input_data: InputData
 186     """
 187
 188     # Transform the data
 189     plot_title = plot.get("title", "")
 190     logging.info("    Creating the data set for the {0} '{1}'.".
 191                  format(plot.get("type", ""), plot_title))
 192     data = input_data.filter_data(plot)
 193     if data is None:
 194         logging.error("No data.")
 195         return
 196
 197     # Prepare the data for the plot
 198     y_tmp_vals = dict()
 199     y_tags = dict()
 200     for job in data:
 201         for build in job:
 202             for test in build:
 203                 if y_tmp_vals.get(test["parent"], None) is None:
 204                     y_tmp_vals[test["parent"]] = [
 205                         list(),  # direction1, min
 206                         list(),  # direction1, avg
 207                         list(),  # direction1, max
 208                         list(),  # direction2, min
 209                         list(),  # direction2, avg
 210                         list()   # direction2, max
 211                     ]
 212                     y_tags[test["parent"]] = test.get("tags", None)
 213                 try:
 214                     if test["type"] in ("NDRPDR", ):
 215                         if "-pdr" in plot_title.lower():
 216                             ttype = "PDR"
 217                         elif "-ndr" in plot_title.lower():
 218                             ttype = "NDR"
 219                         else:
 220                             continue
 221                         y_tmp_vals[test["parent"]][0].append(
 222                             test["latency"][ttype]["direction1"]["min"])
 223                         y_tmp_vals[test["parent"]][1].append(
 224                             test["latency"][ttype]["direction1"]["avg"])
 225                         y_tmp_vals[test["parent"]][2].append(
 226                             test["latency"][ttype]["direction1"]["max"])
 227                         y_tmp_vals[test["parent"]][3].append(
 228                             test["latency"][ttype]["direction2"]["min"])
 229                         y_tmp_vals[test["parent"]][4].append(
 230                             test["latency"][ttype]["direction2"]["avg"])
 231                         y_tmp_vals[test["parent"]][5].append(
 232                             test["latency"][ttype]["direction2"]["max"])
 233                     else:
 234                         continue
 235                 except (KeyError, TypeError):
 236                     pass
 237
 238     # Sort the tests
 239     order = plot.get("sort", None)
 240     if order and y_tags:
 241         y_sorted = OrderedDict()
 242         y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()}
 243         for tag in order:
 244             for suite, tags in y_tags_l.items():
 245                 if tag.lower() in tags:
 246                     try:
 247                         y_sorted[suite] = y_tmp_vals.pop(suite)
 248                         y_tags_l.pop(suite)
 249                     except KeyError as err:
 250                         logging.error("Not found: {0}".format(err))
 251                     finally:
 252                         break
 253     else:
 254         y_sorted = y_tmp_vals
 255
 256     x_vals = list()
 257     y_vals = list()
 258     y_mins = list()
 259     y_maxs = list()
 260     for key, val in y_sorted.items():
 261         key = "-".join(key.split("-")[1:-1])
 262         x_vals.append(key)  # dir 1
 263         y_vals.append(mean(val[1]) if val[1] else None)
 264         y_mins.append(mean(val[0]) if val[0] else None)
 265         y_maxs.append(mean(val[2]) if val[2] else None)
 266         x_vals.append(key)  # dir 2
 267         y_vals.append(mean(val[4]) if val[4] else None)
 268         y_mins.append(mean(val[3]) if val[3] else None)
 269         y_maxs.append(mean(val[5]) if val[5] else None)
 270
 271     traces = list()
 272     annotations = list()
 273
 274     for idx in range(len(x_vals)):
 275         if not bool(int(idx % 2)):
 276             direction = "West - East"
 277         else:
 278             direction = "East - West"
 279         hovertext = ("Test: {test}<br>"
 280                      "Direction: {dir}<br>".format(test=x_vals[idx],
 281                                                    dir=direction))
 282         if isinstance(y_maxs[idx], float):
 283             hovertext += "Max: {max:.2f}uSec<br>".format(max=y_maxs[idx])
 284         if isinstance(y_vals[idx], float):
 285             hovertext += "Avg: {avg:.2f}uSec<br>".format(avg=y_vals[idx])
 286         if isinstance(y_mins[idx], float):
 287             hovertext += "Min: {min:.2f}uSec".format(min=y_mins[idx])
 288
 289         if isinstance(y_maxs[idx], float) and isinstance(y_vals[idx], float):
 290             array = [y_maxs[idx] - y_vals[idx], ]
 291         else:
 292             array = [None, ]
 293         if isinstance(y_mins[idx], float) and isinstance(y_vals[idx], float):
 294             arrayminus = [y_vals[idx] - y_mins[idx], ]
 295         else:
 296             arrayminus = [None, ]
 297         traces.append(plgo.Scatter(
 298             x=[idx, ],
 299             y=[y_vals[idx], ],
 300             name=x_vals[idx],
 301             legendgroup=x_vals[idx],
 302             showlegend=bool(int(idx % 2)),
 303             mode="markers",
 304             error_y=dict(
 305                 type='data',
 306                 symmetric=False,
 307                 array=array,
 308                 arrayminus=arrayminus,
 309                 color=COLORS[int(idx / 2)]
 310             ),
 311             marker=dict(
 312                 size=10,
 313                 color=COLORS[int(idx / 2)],
 314             ),
 315             text=hovertext,
 316             hoverinfo="text",
 317         ))
 318         annotations.append(dict(
 319             x=idx,
 320             y=0,
 321             xref="x",
 322             yref="y",
 323             xanchor="center",
 324             yanchor="top",
 325             text="E-W" if bool(int(idx % 2)) else "W-E",
 326             font=dict(
 327                 size=16,
 328             ),
 329             align="center",
 330             showarrow=False
 331         ))
 332
 333     try:
 334         # Create plot
 335         logging.info("    Writing file '{0}{1}'.".
 336                      format(plot["output-file"], plot["output-file-type"]))
 337         layout = deepcopy(plot["layout"])
 338         if layout.get("title", None):
 339             layout["title"] = "<b>Packet Latency:</b> {0}".\
 340                 format(layout["title"])
 341         layout["annotations"] = annotations
 342         plpl = plgo.Figure(data=traces, layout=layout)
 343
 344         # Export Plot
 345         ploff.plot(plpl,
 346                    show_link=False, auto_open=False,
 347                    filename='{0}{1}'.format(plot["output-file"],
 348                                             plot["output-file-type"]))
 349     except PlotlyError as err:
 350         logging.error("   Finished with error: {}".
 351                       format(str(err).replace("\n", " ")))
 352         return
 353
 354
 355 def plot_throughput_speedup_analysis(plot, input_data):
 356     """Generate the plot(s) with algorithm:
 357     plot_throughput_speedup_analysis
 358     specified in the specification file.
 359
 360     :param plot: Plot to generate.
 361     :param input_data: Data to process.
 362     :type plot: pandas.Series
 363     :type input_data: InputData
 364     """
 365
 366     # Transform the data
 367     plot_title = plot.get("title", "")
 368     logging.info("    Creating the data set for the {0} '{1}'.".
 369                  format(plot.get("type", ""), plot_title))
 370     data = input_data.filter_data(plot)
 371     if data is None:
 372         logging.error("No data.")
 373         return
 374
 375     y_vals = dict()
 376     y_tags = dict()
 377     for job in data:
 378         for build in job:
 379             for test in build:
 380                 if y_vals.get(test["parent"], None) is None:
 381                     y_vals[test["parent"]] = {"1": list(),
 382                                               "2": list(),
 383                                               "4": list()}
 384                     y_tags[test["parent"]] = test.get("tags", None)
 385                 try:
 386                     if test["type"] in ("NDRPDR",):
 387                         if "-pdr" in plot_title.lower():
 388                             ttype = "PDR"
 389                         elif "-ndr" in plot_title.lower():
 390                             ttype = "NDR"
 391                         else:
 392                             continue
 393                         if "1C" in test["tags"]:
 394                             y_vals[test["parent"]]["1"]. \
 395                                 append(test["throughput"][ttype]["LOWER"])
 396                         elif "2C" in test["tags"]:
 397                             y_vals[test["parent"]]["2"]. \
 398                                 append(test["throughput"][ttype]["LOWER"])
 399                         elif "4C" in test["tags"]:
 400                             y_vals[test["parent"]]["4"]. \
 401                                 append(test["throughput"][ttype]["LOWER"])
 402                 except (KeyError, TypeError):
 403                     pass
 404
 405     if not y_vals:
 406         logging.warning("No data for the plot '{}'".
 407                         format(plot.get("title", "")))
 408         return
 409
 410     y_1c_max = dict()
 411     for test_name, test_vals in y_vals.items():
 412         for key, test_val in test_vals.items():
 413             if test_val:
 414                 y_vals[test_name][key] = sum(test_val) / len(test_val)
 415                 if key == "1":
 416                     y_1c_max[test_name] = max(test_val) / 1000000.0
 417
 418     vals = dict()
 419     y_max = list()
 420     nic_limit = 0
 421     lnk_limit = 0
 422     pci_limit = plot["limits"]["pci"]["pci-g3-x8"]
 423     for test_name, test_vals in y_vals.items():
 424         if test_vals["1"]:
 425             name = "-".join(test_name.split('-')[1:-1])
 426
 427             vals[name] = dict()
 428             y_val_1 = test_vals["1"] / 1000000.0
 429             y_val_2 = test_vals["2"] / 1000000.0 if test_vals["2"] else None
 430             y_val_4 = test_vals["4"] / 1000000.0 if test_vals["4"] else None
 431
 432             vals[name]["val"] = [y_val_1, y_val_2, y_val_4]
 433             vals[name]["rel"] = [1.0, None, None]
 434             vals[name]["ideal"] = [y_1c_max[test_name],
 435                                    y_1c_max[test_name] * 2,
 436                                    y_1c_max[test_name] * 4]
 437             vals[name]["diff"] = \
 438                 [(y_val_1 - y_1c_max[test_name]) * 100 / y_val_1, None, None]
 439
 440             try:
 441                 val_max = max(max(vals[name]["val"], vals[name]["ideal"]))
 442             except ValueError as err:
 443                 logging.error(err)
 444                 continue
 445             if val_max:
 446                 y_max.append(int((val_max / 10) + 1) * 10)
 447
 448             if y_val_2:
 449                 vals[name]["rel"][1] = round(y_val_2 / y_val_1, 2)
 450                 vals[name]["diff"][1] = \
 451                     (y_val_2 - vals[name]["ideal"][1]) * 100 / y_val_2
 452             if y_val_4:
 453                 vals[name]["rel"][2] = round(y_val_4 / y_val_1, 2)
 454                 vals[name]["diff"][2] = \
 455                     (y_val_4 - vals[name]["ideal"][2]) * 100 / y_val_4
 456
 457         # Limits:
 458         if "x520" in test_name:
 459             limit = plot["limits"]["nic"]["x520"]
 460         elif "x710" in test_name:
 461             limit = plot["limits"]["nic"]["x710"]
 462         elif "xxv710" in test_name:
 463             limit = plot["limits"]["nic"]["xxv710"]
 464         elif "xl710" in test_name:
 465             limit = plot["limits"]["nic"]["xl710"]
 466         else:
 467             limit = 0
 468         if limit > nic_limit:
 469             nic_limit = limit
 470
 471         mul = 2 if "ge2p" in test_name else 1
 472         if "10ge" in test_name:
 473             limit = plot["limits"]["link"]["10ge"] * mul
 474         elif "25ge" in test_name:
 475             limit = plot["limits"]["link"]["25ge"] * mul
 476         elif "40ge" in test_name:
 477             limit = plot["limits"]["link"]["40ge"] * mul
 478         elif "100ge" in test_name:
 479             limit = plot["limits"]["link"]["100ge"] * mul
 480         else:
 481             limit = 0
 482         if limit > lnk_limit:
 483             lnk_limit = limit
 484
 485     # Sort the tests
 486     order = plot.get("sort", None)
 487     if order and y_tags:
 488         y_sorted = OrderedDict()
 489         y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()}
 490         for tag in order:
 491             for test, tags in y_tags_l.items():
 492                 if tag.lower() in tags:
 493                     name = "-".join(test.split('-')[1:-1])
 494                     try:
 495                         y_sorted[name] = vals.pop(name)
 496                         y_tags_l.pop(test)
 497                     except KeyError as err:
 498                         logging.error("Not found: {0}".format(err))
 499                     finally:
 500                         break
 501     else:
 502         y_sorted = vals
 503
 504     traces = list()
 505     annotations = list()
 506     x_vals = [1, 2, 4]
 507
 508     # Limits:
 509     try:
 510         threshold = 1.1 * max(y_max)  # 10%
 511     except ValueError as err:
 512         logging.error(err)
 513         return
 514     nic_limit /= 1000000.0
 515     if nic_limit < threshold:
 516         traces.append(plgo.Scatter(
 517             x=x_vals,
 518             y=[nic_limit, ] * len(x_vals),
 519             name="NIC: {0:.2f}Mpps".format(nic_limit),
 520             showlegend=False,
 521             mode="lines",
 522             line=dict(
 523                 dash="dot",
 524                 color=COLORS[-1],
 525                 width=1),
 526             hoverinfo="none"
 527         ))
 528         annotations.append(dict(
 529             x=1,
 530             y=nic_limit,
 531             xref="x",
 532             yref="y",
 533             xanchor="left",
 534             yanchor="bottom",
 535             text="NIC: {0:.2f}Mpps".format(nic_limit),
 536             font=dict(
 537                 size=14,
 538                 color=COLORS[-1],
 539             ),
 540             align="left",
 541             showarrow=False
 542         ))
 543         y_max.append(int((nic_limit / 10) + 1) * 10)
 544
 545     lnk_limit /= 1000000.0
 546     if lnk_limit < threshold:
 547         traces.append(plgo.Scatter(
 548             x=x_vals,
 549             y=[lnk_limit, ] * len(x_vals),
 550             name="Link: {0:.2f}Mpps".format(lnk_limit),
 551             showlegend=False,
 552             mode="lines",
 553             line=dict(
 554                 dash="dot",
 555                 color=COLORS[-2],
 556                 width=1),
 557             hoverinfo="none"
 558         ))
 559         annotations.append(dict(
 560             x=1,
 561             y=lnk_limit,
 562             xref="x",
 563             yref="y",
 564             xanchor="left",
 565             yanchor="bottom",
 566             text="Link: {0:.2f}Mpps".format(lnk_limit),
 567             font=dict(
 568                 size=14,
 569                 color=COLORS[-2],
 570             ),
 571             align="left",
 572             showarrow=False
 573         ))
 574         y_max.append(int((lnk_limit / 10) + 1) * 10)
 575
 576     pci_limit /= 1000000.0
 577     if pci_limit < threshold:
 578         traces.append(plgo.Scatter(
 579             x=x_vals,
 580             y=[pci_limit, ] * len(x_vals),
 581             name="PCIe: {0:.2f}Mpps".format(pci_limit),
 582             showlegend=False,
 583             mode="lines",
 584             line=dict(
 585                 dash="dot",
 586                 color=COLORS[-3],
 587                 width=1),
 588             hoverinfo="none"
 589         ))
 590         annotations.append(dict(
 591             x=1,
 592             y=pci_limit,
 593             xref="x",
 594             yref="y",
 595             xanchor="left",
 596             yanchor="bottom",
 597             text="PCIe: {0:.2f}Mpps".format(pci_limit),
 598             font=dict(
 599                 size=14,
 600                 color=COLORS[-3],
 601             ),
 602             align="left",
 603             showarrow=False
 604         ))
 605         y_max.append(int((pci_limit / 10) + 1) * 10)
 606
 607     # Perfect and measured:
 608     cidx = 0
 609     for name, val in y_sorted.iteritems():
 610         hovertext = list()
 611         for idx in range(len(val["val"])):
 612             htext = ""
 613             if isinstance(val["val"][idx], float):
 614                 htext += "value: {0:.2f}Mpps<br>".format(val["val"][idx])
 615             if isinstance(val["diff"][idx], float):
 616                 htext += "diff: {0:.0f}%<br>".format(round(val["diff"][idx]))
 617             if isinstance(val["rel"][idx], float):
 618                 htext += "speedup: {0:.2f}".format(val["rel"][idx])
 619             hovertext.append(htext)
 620         traces.append(plgo.Scatter(x=x_vals,
 621                                    y=val["val"],
 622                                    name=name,
 623                                    legendgroup=name,
 624                                    mode="lines+markers",
 625                                    line=dict(
 626                                        color=COLORS[cidx],
 627                                        width=2),
 628                                    marker=dict(
 629                                        symbol="circle",
 630                                        size=10
 631                                    ),
 632                                    text=hovertext,
 633                                    hoverinfo="text+name"
 634                                    ))
 635         traces.append(plgo.Scatter(x=x_vals,
 636                                    y=val["ideal"],
 637                                    name="{0} perfect".format(name),
 638                                    legendgroup=name,
 639                                    showlegend=False,
 640                                    mode="lines",
 641                                    line=dict(
 642                                        color=COLORS[cidx],
 643                                        width=2,
 644                                        dash="dash"),
 645                                    text=["perfect: {0:.2f}Mpps".format(y)
 646                                          for y in val["ideal"]],
 647                                    hoverinfo="text"
 648                                    ))
 649         cidx += 1
 650
 651     try:
 652         # Create plot
 653         logging.info("    Writing file '{0}{1}'.".
 654                      format(plot["output-file"], plot["output-file-type"]))
 655         layout = deepcopy(plot["layout"])
 656         if layout.get("title", None):
 657             layout["title"] = "<b>Speedup Multi-core:</b> {0}". \
 658                 format(layout["title"])
 659         layout["annotations"].extend(annotations)
 660         plpl = plgo.Figure(data=traces, layout=layout)
 661
 662         # Export Plot
 663         ploff.plot(plpl,
 664                    show_link=False, auto_open=False,
 665                    filename='{0}{1}'.format(plot["output-file"],
 666                                             plot["output-file-type"]))
 667     except PlotlyError as err:
 668         logging.error("   Finished with error: {}".
 669                       format(str(err).replace("\n", " ")))
 670         return
 671
 672
 673 def plot_http_server_performance_box(plot, input_data):
 674     """Generate the plot(s) with algorithm: plot_http_server_performance_box
 675     specified in the specification file.
 676
 677     :param plot: Plot to generate.
 678     :param input_data: Data to process.
 679     :type plot: pandas.Series
 680     :type input_data: InputData
 681     """
 682
 683     # Transform the data
 684     logging.info("    Creating the data set for the {0} '{1}'.".
 685                  format(plot.get("type", ""), plot.get("title", "")))
 686     data = input_data.filter_data(plot)
 687     if data is None:
 688         logging.error("No data.")
 689         return
 690
 691     # Prepare the data for the plot
 692     y_vals = dict()
 693     for job in data:
 694         for build in job:
 695             for test in build:
 696                 if y_vals.get(test["name"], None) is None:
 697                     y_vals[test["name"]] = list()
 698                 try:
 699                     y_vals[test["name"]].append(test["result"])
 700                 except (KeyError, TypeError):
 701                     y_vals[test["name"]].append(None)
 702
 703     # Add None to the lists with missing data
 704     max_len = 0
 705     for val in y_vals.values():
 706         if len(val) > max_len:
 707             max_len = len(val)
 708     for key, val in y_vals.items():
 709         if len(val) < max_len:
 710             val.extend([None for _ in range(max_len - len(val))])
 711
 712     # Add plot traces
 713     traces = list()
 714     df = pd.DataFrame(y_vals)
 715     df.head()
 716     for i, col in enumerate(df.columns):
 717         name = "{0}. {1}".format(i + 1, col.lower().replace('-cps', '').
 718                                  replace('-rps', ''))
 719         traces.append(plgo.Box(x=[str(i + 1) + '.'] * len(df[col]),
 720                                y=df[col],
 721                                name=name,
 722                                **plot["traces"]))
 723     try:
 724         # Create plot
 725         plpl = plgo.Figure(data=traces, layout=plot["layout"])
 726
 727         # Export Plot
 728         logging.info("    Writing file '{0}{1}'.".
 729                      format(plot["output-file"], plot["output-file-type"]))
 730         ploff.plot(plpl, show_link=False, auto_open=False,
 731                    filename='{0}{1}'.format(plot["output-file"],
 732                                             plot["output-file-type"]))
 733     except PlotlyError as err:
 734         logging.error("   Finished with error: {}".
 735                       format(str(err).replace("\n", " ")))
 736         return