+ ploff.plot(plpl, show_link=False, auto_open=False,
+ filename='{0}{1}'.format(plot["output-file"],
+ plot["output-file-type"]))
+ except PlotlyError as err:
+ logging.error(" Finished with error: {}".
+ format(repr(err).replace("\n", " ")))
+ return
+
+
+def plot_soak_bars(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_soak_bars
+ specified in the specification file.
+
+ :param plot: Plot to generate.
+ :param input_data: Data to process.
+ :type plot: pandas.Series
+ :type input_data: InputData
+ """
+
+ # Transform the data
+ plot_title = plot.get("title", "")
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(plot.get("type", ""), plot_title))
+ data = input_data.filter_data(plot)
+ if data is None:
+ logging.error("No data.")
+ return
+
+ # Prepare the data for the plot
+ y_vals = dict()
+ y_tags = dict()
+ for job in data:
+ for build in job:
+ for test in build:
+ if y_vals.get(test["parent"], None) is None:
+ y_tags[test["parent"]] = test.get("tags", None)
+ try:
+ if test["type"] in ("SOAK", ):
+ y_vals[test["parent"]] = test["throughput"]
+ else:
+ continue
+ except (KeyError, TypeError):
+ y_vals[test["parent"]] = dict()
+
+ # Sort the tests
+ order = plot.get("sort", None)
+ if order and y_tags:
+ y_sorted = OrderedDict()
+ y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()}
+ for tag in order:
+ logging.debug(tag)
+ for suite, tags in y_tags_l.items():
+ if "not " in tag:
+ tag = tag.split(" ")[-1]
+ if tag.lower() in tags:
+ continue
+ else:
+ if tag.lower() not in tags:
+ continue
+ try:
+ y_sorted[suite] = y_vals.pop(suite)
+ y_tags_l.pop(suite)
+ logging.debug(suite)
+ except KeyError as err:
+ logging.error("Not found: {0}".format(repr(err)))
+ finally:
+ break
+ else:
+ y_sorted = y_vals
+
+ idx = 0
+ y_max = 0
+ traces = list()
+ for test_name, test_data in y_sorted.items():
+ idx += 1
+ name = "{nr}. {name}".\
+ format(nr=idx, name=test_name.lower().replace('-soak', ''))
+ if len(name) > 50:
+ name_lst = name.split('-')
+ name = ""
+ split_name = True
+ for segment in name_lst:
+ if (len(name) + len(segment) + 1) > 50 and split_name:
+ name += "<br> "
+ split_name = False
+ name += segment + '-'
+ name = name[:-1]
+
+ y_val = test_data.get("LOWER", None)
+ if y_val:
+ y_val /= 1000000
+ if y_val > y_max:
+ y_max = y_val
+
+ time = "No Information"
+ result = "No Information"
+ hovertext = ("{name}<br>"
+ "Packet Throughput: {val:.2f}Mpps<br>"
+ "Final Duration: {time}<br>"
+ "Result: {result}".format(name=name,
+ val=y_val,
+ time=time,
+ result=result))
+ traces.append(plgo.Bar(x=[str(idx) + '.', ],
+ y=[y_val, ],
+ name=name,
+ text=hovertext,
+ hoverinfo="text"))
+ try:
+ # Create plot
+ layout = deepcopy(plot["layout"])
+ if layout.get("title", None):
+ layout["title"] = "<b>Packet Throughput:</b> {0}". \
+ format(layout["title"])
+ if y_max:
+ layout["yaxis"]["range"] = [0, y_max + 1]
+ plpl = plgo.Figure(data=traces, layout=layout)
+ # Export Plot
+ logging.info(" Writing file '{0}{1}'.".
+ format(plot["output-file"], plot["output-file-type"]))
+ ploff.plot(plpl, show_link=False, auto_open=False,
+ filename='{0}{1}'.format(plot["output-file"],
+ plot["output-file-type"]))
+ except PlotlyError as err:
+ logging.error(" Finished with error: {}".
+ format(repr(err).replace("\n", " ")))
+ return
+
+
+def plot_soak_boxes(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_soak_boxes
+ specified in the specification file.
+
+ :param plot: Plot to generate.
+ :param input_data: Data to process.
+ :type plot: pandas.Series
+ :type input_data: InputData
+ """
+
+ # Transform the data
+ plot_title = plot.get("title", "")
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(plot.get("type", ""), plot_title))
+ data = input_data.filter_data(plot)
+ if data is None:
+ logging.error("No data.")
+ return
+
+ # Prepare the data for the plot
+ y_vals = dict()
+ y_tags = dict()
+ for job in data:
+ for build in job:
+ for test in build:
+ if y_vals.get(test["parent"], None) is None:
+ y_tags[test["parent"]] = test.get("tags", None)
+ try:
+ if test["type"] in ("SOAK", ):
+ y_vals[test["parent"]] = test["throughput"]
+ else:
+ continue
+ except (KeyError, TypeError):
+ y_vals[test["parent"]] = dict()
+
+ # Sort the tests
+ order = plot.get("sort", None)
+ if order and y_tags:
+ y_sorted = OrderedDict()
+ y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()}
+ for tag in order:
+ logging.debug(tag)
+ for suite, tags in y_tags_l.items():
+ if "not " in tag:
+ tag = tag.split(" ")[-1]
+ if tag.lower() in tags:
+ continue
+ else:
+ if tag.lower() not in tags:
+ continue
+ try:
+ y_sorted[suite] = y_vals.pop(suite)
+ y_tags_l.pop(suite)
+ logging.debug(suite)
+ except KeyError as err:
+ logging.error("Not found: {0}".format(repr(err)))
+ finally:
+ break
+ else:
+ y_sorted = y_vals
+
+ idx = 0
+ y_max = 0
+ traces = list()
+ for test_name, test_data in y_sorted.items():
+ idx += 1
+ name = "{nr}. {name}".\
+ format(nr=idx, name=test_name.lower().replace('-soak', '').
+ replace('2n1l-', ''))
+ if len(name) > 55:
+ name_lst = name.split('-')
+ name = ""
+ split_name = True
+ for segment in name_lst:
+ if (len(name) + len(segment) + 1) > 55 and split_name:
+ name += "<br> "
+ split_name = False
+ name += segment + '-'
+ name = name[:-1]
+
+ y_val = test_data.get("UPPER", None)
+ if y_val:
+ y_val /= 1000000
+ if y_val > y_max:
+ y_max = y_val
+
+ y_base = test_data.get("LOWER", None)
+ if y_base:
+ y_base /= 1000000
+
+ hovertext = ("Upper bound: {upper:.2f}<br>"
+ "Lower bound: {lower:.2f}".format(upper=y_val,
+ lower=y_base))
+ traces.append(plgo.Bar(x=[str(idx) + '.', ],
+ # +0.05 to see the value in case lower == upper
+ y=[y_val - y_base + 0.05, ],
+ base=y_base,
+ name=name,
+ text=hovertext,
+ hoverinfo="text"))
+ try:
+ # Create plot
+ layout = deepcopy(plot["layout"])
+ if layout.get("title", None):
+ layout["title"] = "<b>Throughput:</b> {0}". \
+ format(layout["title"])
+ if y_max:
+ layout["yaxis"]["range"] = [0, y_max + 1]
+ plpl = plgo.Figure(data=traces, layout=layout)
+ # Export Plot
+ logging.info(" Writing file '{0}{1}'.".
+ format(plot["output-file"], plot["output-file-type"]))
+ ploff.plot(plpl, show_link=False, auto_open=False,
+ filename='{0}{1}'.format(plot["output-file"],
+ plot["output-file-type"]))
+ except PlotlyError as err:
+ logging.error(" Finished with error: {}".
+ format(repr(err).replace("\n", " ")))
+ return
+
+
+def plot_latency_error_bars(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_latency_error_bars
+ specified in the specification file.
+
+ TODO: Remove when not needed.
+
+ :param plot: Plot to generate.
+ :param input_data: Data to process.
+ :type plot: pandas.Series
+ :type input_data: InputData
+ """
+
+ # Transform the data
+ plot_title = plot.get("title", "")
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(plot.get("type", ""), plot_title))
+ data = input_data.filter_data(plot)
+ if data is None:
+ logging.error("No data.")
+ return
+
+ # Prepare the data for the plot
+ y_tmp_vals = dict()
+ y_tags = dict()
+ for job in data:
+ for build in job:
+ for test in build:
+ try:
+ logging.debug("test['latency']: {0}\n".
+ format(test["latency"]))
+ except ValueError as err:
+ logging.warning(repr(err))
+ if y_tmp_vals.get(test["parent"], None) is None:
+ y_tmp_vals[test["parent"]] = [
+ list(), # direction1, min
+ list(), # direction1, avg
+ list(), # direction1, max
+ list(), # direction2, min
+ list(), # direction2, avg
+ list() # direction2, max
+ ]
+ y_tags[test["parent"]] = test.get("tags", None)
+ try:
+ if test["type"] in ("NDRPDR", ):
+ if "-pdr" in plot_title.lower():
+ ttype = "PDR"
+ elif "-ndr" in plot_title.lower():
+ ttype = "NDR"
+ else:
+ logging.warning("Invalid test type: {0}".
+ format(test["type"]))
+ continue
+ y_tmp_vals[test["parent"]][0].append(
+ test["latency"][ttype]["direction1"]["min"])
+ y_tmp_vals[test["parent"]][1].append(
+ test["latency"][ttype]["direction1"]["avg"])
+ y_tmp_vals[test["parent"]][2].append(
+ test["latency"][ttype]["direction1"]["max"])
+ y_tmp_vals[test["parent"]][3].append(
+ test["latency"][ttype]["direction2"]["min"])
+ y_tmp_vals[test["parent"]][4].append(
+ test["latency"][ttype]["direction2"]["avg"])
+ y_tmp_vals[test["parent"]][5].append(
+ test["latency"][ttype]["direction2"]["max"])
+ else:
+ logging.warning("Invalid test type: {0}".
+ format(test["type"]))
+ continue
+ except (KeyError, TypeError) as err:
+ logging.warning(repr(err))
+ logging.debug("y_tmp_vals: {0}\n".format(y_tmp_vals))
+
+ # Sort the tests
+ order = plot.get("sort", None)
+ if order and y_tags:
+ y_sorted = OrderedDict()
+ y_tags_l = {s: [t.lower() for t in ts] for s, ts in y_tags.items()}
+ for tag in order:
+ logging.debug(tag)
+ for suite, tags in y_tags_l.items():
+ if "not " in tag:
+ tag = tag.split(" ")[-1]
+ if tag.lower() in tags:
+ continue
+ else:
+ if tag.lower() not in tags:
+ continue
+ try:
+ y_sorted[suite] = y_tmp_vals.pop(suite)
+ y_tags_l.pop(suite)
+ logging.debug(suite)
+ except KeyError as err:
+ logging.error("Not found: {0}".format(repr(err)))
+ finally:
+ break
+ else:
+ y_sorted = y_tmp_vals
+
+ logging.debug("y_sorted: {0}\n".format(y_sorted))
+ x_vals = list()
+ y_vals = list()
+ y_mins = list()
+ y_maxs = list()
+ nr_of_samples = list()
+ for key, val in y_sorted.items():
+ name = re.sub(REGEX_NIC, "", key.replace('-ndrpdr', '').
+ replace('2n1l-', ''))
+ x_vals.append(name) # dir 1
+ y_vals.append(mean(val[1]) if val[1] else None)
+ y_mins.append(mean(val[0]) if val[0] else None)
+ y_maxs.append(mean(val[2]) if val[2] else None)
+ nr_of_samples.append(len(val[1]) if val[1] else 0)
+ x_vals.append(name) # dir 2
+ y_vals.append(mean(val[4]) if val[4] else None)
+ y_mins.append(mean(val[3]) if val[3] else None)
+ y_maxs.append(mean(val[5]) if val[5] else None)
+ nr_of_samples.append(len(val[3]) if val[3] else 0)
+
+ logging.debug("x_vals :{0}\n".format(x_vals))
+ logging.debug("y_vals :{0}\n".format(y_vals))
+ logging.debug("y_mins :{0}\n".format(y_mins))
+ logging.debug("y_maxs :{0}\n".format(y_maxs))
+ logging.debug("nr_of_samples :{0}\n".format(nr_of_samples))
+ traces = list()
+ annotations = list()
+
+ for idx in range(len(x_vals)):
+ if not bool(int(idx % 2)):
+ direction = "West-East"
+ else:
+ direction = "East-West"
+ hovertext = ("No. of Runs: {nr}<br>"
+ "Test: {test}<br>"
+ "Direction: {dir}<br>".format(test=x_vals[idx],
+ dir=direction,
+ nr=nr_of_samples[idx]))
+ if isinstance(y_maxs[idx], float):
+ hovertext += "Max: {max:.2f}uSec<br>".format(max=y_maxs[idx])
+ if isinstance(y_vals[idx], float):
+ hovertext += "Mean: {avg:.2f}uSec<br>".format(avg=y_vals[idx])
+ if isinstance(y_mins[idx], float):
+ hovertext += "Min: {min:.2f}uSec".format(min=y_mins[idx])
+
+ if isinstance(y_maxs[idx], float) and isinstance(y_vals[idx], float):
+ array = [y_maxs[idx] - y_vals[idx], ]
+ else:
+ array = [None, ]
+ if isinstance(y_mins[idx], float) and isinstance(y_vals[idx], float):
+ arrayminus = [y_vals[idx] - y_mins[idx], ]
+ else:
+ arrayminus = [None, ]
+ logging.debug("y_vals[{1}] :{0}\n".format(y_vals[idx], idx))
+ logging.debug("array :{0}\n".format(array))
+ logging.debug("arrayminus :{0}\n".format(arrayminus))
+ traces.append(plgo.Scatter(
+ x=[idx, ],
+ y=[y_vals[idx], ],
+ name=x_vals[idx],
+ legendgroup=x_vals[idx],
+ showlegend=bool(int(idx % 2)),
+ mode="markers",
+ error_y=dict(
+ type='data',
+ symmetric=False,
+ array=array,
+ arrayminus=arrayminus,
+ color=COLORS[int(idx / 2)]
+ ),
+ marker=dict(
+ size=10,
+ color=COLORS[int(idx / 2)],
+ ),
+ text=hovertext,
+ hoverinfo="text",
+ ))
+ annotations.append(dict(
+ x=idx,
+ y=0,
+ xref="x",
+ yref="y",
+ xanchor="center",
+ yanchor="top",
+ text="E-W" if bool(int(idx % 2)) else "W-E",
+ font=dict(
+ size=16,
+ ),
+ align="center",
+ showarrow=False
+ ))
+
+ try:
+ # Create plot
+ logging.info(" Writing file '{0}{1}'.".
+ format(plot["output-file"], plot["output-file-type"]))
+ layout = deepcopy(plot["layout"])
+ if layout.get("title", None):
+ layout["title"] = "<b>Latency:</b> {0}".\
+ format(layout["title"])
+ layout["annotations"] = annotations
+ plpl = plgo.Figure(data=traces, layout=layout)