logging.error(" Finished with error: {}".
format(str(err).replace("\n", " ")))
return
+
+
+def plot_service_density_heatmap_compare(plot, input_data):
+ """Generate the plot(s) with algorithm: plot_service_density_heatmap_compare
+ specified in the specification file.
+
+ :param plot: Plot to generate.
+ :param input_data: Data to process.
+ :type plot: pandas.Series
+ :type input_data: InputData
+ """
+
+ REGEX_CN = re.compile(r'^(\d*)R(\d*)C$')
+ REGEX_TEST_NAME = re.compile(r'^.*-(\d+ch|\d+pl)-'
+ r'(\d+vh|\d+mif)-'
+ r'(\d+vm|\d+dcr).*$')
+ REGEX_THREADS = re.compile(r'^(\d+)(VM|DCR)(\d+)T$')
+
+ txt_chains = list()
+ txt_nodes = list()
+ vals = dict()
+
+ # Transform the data
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(plot.get("type", ""), plot.get("title", "")))
+ data = input_data.filter_data(plot, continue_on_error=True)
+ if data is None or data.empty:
+ logging.error("No data.")
+ return
+
+ for job in data:
+ for build in job:
+ for test in build:
+ for tag in test['tags']:
+ groups = re.search(REGEX_CN, tag)
+ if groups:
+ c = str(groups.group(1))
+ n = str(groups.group(2))
+ break
+ else:
+ continue
+ groups = re.search(REGEX_TEST_NAME, test["name"])
+ if groups and len(groups.groups()) == 3:
+ hover_name = "{chain}-{vhost}-{vm}".format(
+ chain=str(groups.group(1)),
+ vhost=str(groups.group(2)),
+ vm=str(groups.group(3)))
+ else:
+ hover_name = ""
+ if vals.get(c, None) is None:
+ vals[c] = dict()
+ if vals[c].get(n, None) is None:
+ vals[c][n] = dict(name=hover_name,
+ vals_r=list(),
+ vals_c=list(),
+ nr_r=None,
+ nr_c=None,
+ mean_r=None,
+ mean_c=None,
+ stdev_r=None,
+ stdev_c=None)
+ try:
+ if plot["include-tests"] == "MRR":
+ result = test["result"]["receive-rate"].avg
+ elif plot["include-tests"] == "PDR":
+ result = test["throughput"]["PDR"]["LOWER"]
+ elif plot["include-tests"] == "NDR":
+ result = test["throughput"]["NDR"]["LOWER"]
+ else:
+ result = None
+ except TypeError:
+ result = None
+
+ if result:
+ for tag in test['tags']:
+ groups = re.search(REGEX_THREADS, tag)
+ if groups and len(groups.groups()) == 3:
+ if str(groups.group(3)) == \
+ plot["reference"]["include"]:
+ vals[c][n]["vals_c"].append(result)
+ elif str(groups.group(3)) == \
+ plot["compare"]["include"]:
+ vals[c][n]["vals_r"].append(result)
+ break
+ if not vals:
+ logging.error("No data.")
+ return
+
+ for key_c in vals.keys():
+ txt_chains.append(key_c)
+ for key_n in vals[key_c].keys():
+ txt_nodes.append(key_n)
+ if vals[key_c][key_n]["vals_r"]:
+ vals[key_c][key_n]["nr_r"] = len(vals[key_c][key_n]["vals_r"])
+ vals[key_c][key_n]["mean_r"] = \
+ round(mean(vals[key_c][key_n]["vals_r"]) / 1000000, 1)
+ vals[key_c][key_n]["stdev_r"] = \
+ round(stdev(vals[key_c][key_n]["vals_r"]) / 1000000, 1)
+ if vals[key_c][key_n]["vals_c"]:
+ vals[key_c][key_n]["nr_c"] = len(vals[key_c][key_n]["vals_c"])
+ vals[key_c][key_n]["mean_c"] = \
+ round(mean(vals[key_c][key_n]["vals_c"]) / 1000000, 1)
+ vals[key_c][key_n]["stdev_c"] = \
+ round(stdev(vals[key_c][key_n]["vals_c"]) / 1000000, 1)
+
+ txt_nodes = list(set(txt_nodes))
+
+ txt_chains = sorted(txt_chains, key=lambda chain: int(chain))
+ txt_nodes = sorted(txt_nodes, key=lambda node: int(node))
+
+ chains = [i + 1 for i in range(len(txt_chains))]
+ nodes = [i + 1 for i in range(len(txt_nodes))]
+
+ data_r = [list() for _ in range(len(chains))]
+ data_c = [list() for _ in range(len(chains))]
+ diff = [list() for _ in range(len(chains))]
+ for c in chains:
+ for n in nodes:
+ try:
+ val_r = vals[txt_chains[c - 1]][txt_nodes[n - 1]]["mean_r"]
+ except (KeyError, IndexError):
+ val_r = None
+ data_r[c - 1].append(val_r)
+ try:
+ val_c = vals[txt_chains[c - 1]][txt_nodes[n - 1]]["mean_c"]
+ except (KeyError, IndexError):
+ val_c = None
+ data_c[c - 1].append(val_c)
+
+ if val_c is not None and val_r:
+ diff[c - 1].append(round((val_c - val_r) * 100 / val_r, 1))
+ else:
+ diff[c - 1].append(None)
+
+ # Colorscales:
+ my_green = [[0.0, 'rgb(235, 249, 242)'],
+ [1.0, 'rgb(45, 134, 89)']]
+
+ my_blue = [[0.0, 'rgb(236, 242, 248)'],
+ [1.0, 'rgb(57, 115, 172)']]
+
+ my_grey = [[0.0, 'rgb(230, 230, 230)'],
+ [1.0, 'rgb(102, 102, 102)']]
+
+ hovertext = list()
+
+ annotations = list()
+ annotations_r = list()
+ annotations_c = list()
+ annotations_diff = list()
+
+ text = ("Test: {name}"
+ "<br>{title_r}: {text_r}"
+ "<br>{title_c}: {text_c}{text_diff}")
+ text_r = "Thput: {val_r}; StDev: {stdev_r}; Runs: {nr_r}"
+ text_c = "Thput: {val_c}; StDev: {stdev_c}; Runs: {nr_c}"
+ text_diff = "<br>Relative Difference {title_c} vs. {title_r}: {diff}%"
+
+ for c in range(len(txt_chains)):
+ hover_line = list()
+ for n in range(len(txt_nodes)):
+ if data_r[c][n] is not None:
+ data_point = dict(
+ x=n+1,
+ y=c+1,
+ xref="x",
+ yref="y",
+ xanchor="center",
+ yanchor="middle",
+ text=str(data_r[c][n]) if data_r[c][n] is not None else "",
+ font=dict(
+ size=14,
+ ),
+ align="center",
+ showarrow=False
+ )
+ annotations_r.append(deepcopy(data_point))
+ data_point["text"] = str(data_c[c][n]) \
+ if data_c[c][n] is not None else ""
+ annotations_c.append(deepcopy(data_point))
+ data_point["text"] = str(diff[c][n]) \
+ if diff[c][n] is not None else ""
+ annotations_diff.append(deepcopy(data_point))
+
+ hover_line.append(text.format(
+ name=vals[txt_chains[c]][txt_nodes[n]]["name"],
+ title_r=plot["reference"]["name"],
+ text_r=text_r.format(
+ val_r=data_r[c][n],
+ stdev_r=vals[txt_chains[c]][txt_nodes[n]]["stdev_r"],
+ nr_r=vals[txt_chains[c]][txt_nodes[n]]["nr_r"]
+ ) if data_r[c][n] is not None else "Test Failed",
+ title_c=plot["compare"]["name"],
+ text_c=text_c.format(
+ val_c=data_c[c][n],
+ stdev_c = vals[txt_chains[c]][txt_nodes[n]]["stdev_c"],
+ nr_c=vals[txt_chains[c]][txt_nodes[n]]["nr_c"]
+ ) if data_c[c][n] is not None else "Test Failed",
+ text_diff=text_diff.format(
+ diff=diff[c][n]
+ ) if diff[c][n] is not None else ""
+ ))
+
+ hovertext.append(hover_line)
+
+ traces = [
+ plgo.Heatmap(x=nodes,
+ y=chains,
+ z=data_r,
+ visible=True,
+ colorbar=dict(
+ title=plot.get("z-axis", ""),
+ titleside="right",
+ titlefont=dict(
+ size=16
+ ),
+ tickfont=dict(
+ size=16,
+ ),
+ tickformat=".1f",
+ yanchor="bottom",
+ y=-0.02,
+ len=0.925,
+ ),
+ showscale=True,
+ colorscale=my_green,
+ reversescale=False,
+ text=hovertext,
+ hoverinfo="text"),
+ plgo.Heatmap(x=nodes,
+ y=chains,
+ z=data_c,
+ visible=False,
+ colorbar=dict(
+ title=plot.get("z-axis", ""),
+ titleside="right",
+ titlefont=dict(
+ size=16
+ ),
+ tickfont=dict(
+ size=16,
+ ),
+ tickformat=".1f",
+ yanchor="bottom",
+ y=-0.02,
+ len=0.925,
+ ),
+ showscale=True,
+ colorscale=my_blue,
+ reversescale=False,
+ text=hovertext,
+ hoverinfo="text"),
+ plgo.Heatmap(x=nodes,
+ y=chains,
+ z=diff,
+ name="Diff",
+ visible=False,
+ colorbar=dict(
+ title="Relative difference [%]",
+ titleside="right",
+ titlefont=dict(
+ size=16
+ ),
+ tickfont=dict(
+ size=16,
+ ),
+ tickformat=".1f",
+ yanchor="bottom",
+ y=-0.02,
+ len=0.925,
+ ),
+ showscale=True,
+ colorscale=my_grey,
+ reversescale=False,
+ text=hovertext,
+ hoverinfo="text")
+ ]
+
+ for idx, item in enumerate(txt_nodes):
+ # X-axis, numbers:
+ annotations.append(dict(
+ x=idx+1,
+ y=0.05,
+ xref="x",
+ yref="y",
+ xanchor="center",
+ yanchor="top",
+ text=item,
+ font=dict(
+ size=16,
+ ),
+ align="center",
+ showarrow=False
+ ))
+ for idx, item in enumerate(txt_chains):
+ # Y-axis, numbers:
+ annotations.append(dict(
+ x=0.35,
+ y=idx+1,
+ xref="x",
+ yref="y",
+ xanchor="right",
+ yanchor="middle",
+ text=item,
+ font=dict(
+ size=16,
+ ),
+ align="center",
+ showarrow=False
+ ))
+ # X-axis, title:
+ annotations.append(dict(
+ x=0.55,
+ y=-0.15,
+ xref="paper",
+ yref="y",
+ xanchor="center",
+ yanchor="bottom",
+ text=plot.get("x-axis", ""),
+ font=dict(
+ size=16,
+ ),
+ align="center",
+ showarrow=False
+ ))
+ # Y-axis, title:
+ annotations.append(dict(
+ x=-0.1,
+ y=0.5,
+ xref="x",
+ yref="paper",
+ xanchor="center",
+ yanchor="middle",
+ text=plot.get("y-axis", ""),
+ font=dict(
+ size=16,
+ ),
+ align="center",
+ textangle=270,
+ showarrow=False
+ ))
+ updatemenus = list([
+ dict(
+ active=0,
+ x=1.0,
+ y=0.0,
+ xanchor='right',
+ yanchor='bottom',
+ direction='up',
+ buttons=list([
+ dict(
+ label=plot["reference"]["name"],
+ method="update",
+ args=[
+ {
+ "visible": [True, False, False]
+ },
+ {
+ "colorscale": [my_green, ],
+ "reversescale": False,
+ "annotations": annotations + annotations_r,
+ },
+ ]
+ ),
+ dict(
+ label=plot["compare"]["name"],
+ method="update",
+ args=[
+ {
+ "visible": [False, True, False]
+ },
+ {
+ "colorscale": [my_blue, ],
+ "reversescale": False,
+ "annotations": annotations + annotations_c,
+ },
+ ]
+ ),
+ dict(
+ label="Diff",
+ method="update",
+ args=[
+ {
+ "visible": [False, False, True]
+ },
+ {
+ "colorscale": [my_grey, ],
+ "reversescale": False,
+ "annotations": annotations + annotations_diff,
+ },
+ ]
+ ),
+ ])
+ )
+ ])
+
+ try:
+ layout = deepcopy(plot["layout"])
+ except KeyError as err:
+ logging.error("Finished with error: No layout defined")
+ logging.error(repr(err))
+ return
+
+ layout["annotations"] = annotations + annotations_r
+ layout['updatemenus'] = updatemenus
+
+ try:
+ # Create plot
+ 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(str(err).replace("\n", " ")))
+ return
Code Review / csit.git / blobdiff