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