- # Prepare the data for the plot
- y_tmp_vals = OrderedDict()
- for job in data:
- for build in job:
- for test in build:
- try:
- logging.debug(f"test[u'latency']: {test[u'latency']}\n")
- except ValueError as err:
- logging.warning(repr(err))
- if y_tmp_vals.get(test[u"parent"], None) is None:
- y_tmp_vals[test[u"parent"]] = [
- list(), # direction1, min
- list(), # direction1, avg
- list(), # direction1, max
- list(), # direction2, min
- list(), # direction2, avg
- list() # direction2, max
- ]
- try:
- if test[u"type"] not in (u"NDRPDR", ):
- logging.warning(f"Invalid test type: {test[u'type']}")
- continue
- if u"-pdr" in plot_title.lower():
- ttype = u"PDR"
- elif u"-ndr" in plot_title.lower():
- ttype = u"NDR"
- else:
- logging.warning(
- f"Invalid test type: {test[u'type']}"
- )
- continue
- y_tmp_vals[test[u"parent"]][0].append(
- test[u"latency"][ttype][u"direction1"][u"min"])
- y_tmp_vals[test[u"parent"]][1].append(
- test[u"latency"][ttype][u"direction1"][u"avg"])
- y_tmp_vals[test[u"parent"]][2].append(
- test[u"latency"][ttype][u"direction1"][u"max"])
- y_tmp_vals[test[u"parent"]][3].append(
- test[u"latency"][ttype][u"direction2"][u"min"])
- y_tmp_vals[test[u"parent"]][4].append(
- test[u"latency"][ttype][u"direction2"][u"avg"])
- y_tmp_vals[test[u"parent"]][5].append(
- test[u"latency"][ttype][u"direction2"][u"max"])
- except (KeyError, TypeError) as err:
- logging.warning(repr(err))
-
- x_vals = list()
- y_vals = list()
- y_mins = list()
- y_maxs = list()
- nr_of_samples = list()
- for key, val in y_tmp_vals.items():
- name = re.sub(REGEX_NIC, u"", key.replace(u'-ndrpdr', u'').
- replace(u'2n1l-', u''))
- 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)
-
- traces = list()
- annotations = list()
-
- for idx, _ in enumerate(x_vals):
- if not bool(int(idx % 2)):
- direction = u"West-East"
- else:
- direction = u"East-West"
- hovertext = (
- f"No. of Runs: {nr_of_samples[idx]}<br>"
- f"Test: {x_vals[idx]}<br>"
- f"Direction: {direction}<br>"
- )
- if isinstance(y_maxs[idx], float):
- hovertext += f"Max: {y_maxs[idx]:.2f}uSec<br>"
- if isinstance(y_vals[idx], float):
- hovertext += f"Mean: {y_vals[idx]:.2f}uSec<br>"
- if isinstance(y_mins[idx], float):
- hovertext += f"Min: {y_mins[idx]:.2f}uSec"
-
- 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, ]
- traces.append(plgo.Scatter(
- x=[idx, ],
- y=[y_vals[idx], ],
- name=x_vals[idx],
- legendgroup=x_vals[idx],
- showlegend=bool(int(idx % 2)),
- mode=u"markers",
- error_y=dict(
- type=u"data",
- symmetric=False,
- array=array,
- arrayminus=arrayminus,
- color=COLORS[int(idx / 2)]
- ),
- marker=dict(
- size=10,
- color=COLORS[int(idx / 2)],
- ),
- text=hovertext,
- hoverinfo=u"text",
- ))
- annotations.append(dict(
- x=idx,
- y=0,
- xref=u"x",
- yref=u"y",
- xanchor=u"center",
- yanchor=u"top",
- text=u"E-W" if bool(int(idx % 2)) else u"W-E",
- font=dict(
- size=16,
- ),
- align=u"center",
- showarrow=False
- ))
+ for core in plot.get(u"core", tuple()):
+ # Prepare the data for the plot
+ data_x = list()
+ data_names = list()
+ data_y = list()
+ data_y_max = list()
+ idx = 1
+ for item in plot.get(u"include", tuple()):
+ reg_ex = re.compile(str(item.format(core=core)).lower())
+ for job in data:
+ for build in job:
+ for test_id, test in build.iteritems():
+ if not re.match(reg_ex, str(test_id).lower()):
+ continue
+ try:
+ data_x.append(idx)
+ name = re.sub(
+ REGEX_NIC, u'', test[u'parent'].lower().
+ replace(u'-mrr', u'').replace(u'2n1l-', u'')
+ )
+ data_y.append(test[u"result"][u"samples"])
+ data_names.append(
+ f"{idx}."
+ f"({len(data_y[-1]):02d} "
+ f"run{u's' if len(data_y[-1]) > 1 else u''}) "
+ f"{name}"
+ )
+ data_y_max.append(max(data_y[-1]))
+ idx += 1
+ except (KeyError, TypeError):
+ pass
+
+ # Add plot traces
+ traces = list()
+ for idx, x_item in enumerate(data_x):
+ kwargs = dict(
+ y=data_y[idx],
+ name=data_names[idx],
+ hoverinfo=u"y+name"
+ )
+ box_points = plot.get(u"boxpoints", u"all")
+ if box_points in (u"all", u"outliers", u"suspectedoutliers", False):
+ kwargs[u"boxpoints"] = box_points
+ kwargs["jitter"] = 0.3
+ traces.append(plgo.Box(**kwargs))