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-rw-r--r--resources/tools/presentation/generator_cpta.py52
-rw-r--r--resources/tools/presentation/generator_plots.py458
-rw-r--r--resources/tools/presentation/generator_tables.py8
-rw-r--r--resources/tools/presentation/input_data_parser.py12
-rw-r--r--resources/tools/presentation/pal_utils.py10
-rw-r--r--resources/tools/presentation/specification_CPTA.yaml8
-rw-r--r--resources/tools/presentation/specification_parser.py2
7 files changed, 56 insertions, 494 deletions
diff --git a/resources/tools/presentation/generator_cpta.py b/resources/tools/presentation/generator_cpta.py
index 511800a988..a308f64e2e 100644
--- a/resources/tools/presentation/generator_cpta.py
+++ b/resources/tools/presentation/generator_cpta.py
@@ -146,7 +146,7 @@ def generate_cpta(spec, data):
def _generate_trending_traces(in_data, job_name, build_info,
- show_trend_line=True, name=u"", color=u""):
+ name=u"", color=u""):
"""Generate the trending traces:
- samples,
- outliers, regress, progress
@@ -155,13 +155,11 @@ def _generate_trending_traces(in_data, job_name, build_info,
:param in_data: Full data set.
:param job_name: The name of job which generated the data.
:param build_info: Information about the builds.
- :param show_trend_line: Show moving median (trending plot).
:param name: Name of the plot
:param color: Name of the color for the plot.
:type in_data: OrderedDict
:type job_name: str
:type build_info: dict
- :type show_trend_line: bool
:type name: str
:type color: str
:returns: Generated traces (list) and the evaluated result.
@@ -183,7 +181,7 @@ def _generate_trending_traces(in_data, job_name, build_info,
str_key = str(key)
date = build_info[job_name][str_key][0]
hover_str = (u"date: {date}<br>"
- u"value [Mpps]: {value:.3f}<br>"
+ u"average [Mpps]: {value:.3f}<br>"
u"stdev [Mpps]: {stdev:.3f}<br>"
u"{sut}-ref: {build}<br>"
u"csit-ref: mrr-{period}-build-{build_nr}<br>"
@@ -216,8 +214,9 @@ def _generate_trending_traces(in_data, job_name, build_info,
for key, value in zip(xaxis, data_y_pps):
data_pd[key] = value
- anomaly_classification, avgs_pps = classify_anomalies(data_pd)
+ anomaly_classification, avgs_pps, stdevs_pps = classify_anomalies(data_pd)
avgs_mpps = [avg_pps / 1e6 for avg_pps in avgs_pps]
+ stdevs_mpps = [stdev_pps / 1e6 for stdev_pps in stdevs_pps]
anomalies = OrderedDict()
anomalies_colors = list()
@@ -258,23 +257,30 @@ def _generate_trending_traces(in_data, job_name, build_info,
)
traces = [trace_samples, ]
- if show_trend_line:
- trace_trend = plgo.Scatter(
- x=xaxis,
- y=avgs_mpps,
- mode=u"lines",
- line={
- u"shape": u"linear",
- u"width": 1,
- u"color": color,
- },
- showlegend=False,
- legendgroup=name,
- name=f"{name}",
- text=[f"trend [Mpps]: {avg:.3f}" for avg in avgs_mpps],
- hoverinfo=u"text+name"
+ trend_hover_text = list()
+ for idx in range(len(data_x)):
+ trend_hover_str = (
+ f"trend [Mpps]: {avgs_mpps[idx]:.3f}<br>"
+ f"stdev [Mpps]: {stdevs_mpps[idx]:.3f}"
)
- traces.append(trace_trend)
+ trend_hover_text.append(trend_hover_str)
+
+ trace_trend = plgo.Scatter(
+ x=xaxis,
+ y=avgs_mpps,
+ mode=u"lines",
+ line={
+ u"shape": u"linear",
+ u"width": 1,
+ u"color": color,
+ },
+ showlegend=False,
+ legendgroup=name,
+ name=f"{name}",
+ text=trend_hover_text,
+ hoverinfo=u"text+name"
+ )
+ traces.append(trace_trend)
trace_anomalies = plgo.Scatter(
x=list(anomalies.keys()),
@@ -354,8 +360,8 @@ def _generate_all_charts(spec, input_data):
# Transform the data
logging.info(
- f" Creating the data set for the {graph.get(u'type', u'')} "
- f"{graph.get(u'title', u'')}."
+ f" Creating the data set for the {graph.get(u'type', u'')} "
+ f"{graph.get(u'title', u'')}."
)
if graph.get(u"include", None):
diff --git a/resources/tools/presentation/generator_plots.py b/resources/tools/presentation/generator_plots.py
index 89eb1c6521..c1e5bed893 100644
--- a/resources/tools/presentation/generator_plots.py
+++ b/resources/tools/presentation/generator_plots.py
@@ -27,7 +27,6 @@ import pandas as pd
import plotly.offline as ploff
import plotly.graph_objs as plgo
-from plotly.subplots import make_subplots
from plotly.exceptions import PlotlyError
from pal_utils import mean, stdev
@@ -55,12 +54,9 @@ def generate_plots(spec, data):
generator = {
u"plot_nf_reconf_box_name": plot_nf_reconf_box_name,
u"plot_perf_box_name": plot_perf_box_name,
- u"plot_lat_err_bars_name": plot_lat_err_bars_name,
u"plot_tsa_name": plot_tsa_name,
u"plot_http_server_perf_box": plot_http_server_perf_box,
u"plot_nf_heatmap": plot_nf_heatmap,
- u"plot_lat_hdrh_bar_name": plot_lat_hdrh_bar_name,
- u"plot_lat_hdrh_percentile": plot_lat_hdrh_percentile,
u"plot_hdrh_lat_by_percentile": plot_hdrh_lat_by_percentile
}
@@ -79,111 +75,6 @@ def generate_plots(spec, data):
logging.info(u"Done.")
-def plot_lat_hdrh_percentile(plot, input_data):
- """Generate the plot(s) with algorithm: plot_lat_hdrh_percentile
- 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(u"title", u"")
- logging.info(
- f" Creating the data set for the {plot.get(u'type', u'')} "
- f"{plot_title}."
- )
- data = input_data.filter_tests_by_name(
- plot, params=[u"latency", u"parent", u"tags", u"type"])
- if data is None or len(data[0][0]) == 0:
- logging.error(u"No data.")
- return
-
- fig = plgo.Figure()
-
- # Prepare the data for the plot
- directions = [u"W-E", u"E-W"]
- for color, test in enumerate(data[0][0]):
- try:
- if test[u"type"] in (u"NDRPDR",):
- 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
- name = re.sub(REGEX_NIC, u"", test[u"parent"].
- replace(u'-ndrpdr', u'').
- replace(u'2n1l-', u''))
- for idx, direction in enumerate(
- (u"direction1", u"direction2", )):
- try:
- hdr_lat = test[u"latency"][ttype][direction][u"hdrh"]
- # TODO: Workaround, HDRH data must be aligned to 4
- # bytes, remove when not needed.
- hdr_lat += u"=" * (len(hdr_lat) % 4)
- xaxis = list()
- yaxis = list()
- hovertext = list()
- decoded = hdrh.histogram.HdrHistogram.decode(hdr_lat)
- for item in decoded.get_recorded_iterator():
- percentile = item.percentile_level_iterated_to
- if percentile != 100.0:
- xaxis.append(100.0 / (100.0 - percentile))
- yaxis.append(item.value_iterated_to)
- hovertext.append(
- f"Test: {name}<br>"
- f"Direction: {directions[idx]}<br>"
- f"Percentile: {percentile:.5f}%<br>"
- f"Latency: {item.value_iterated_to}uSec"
- )
- fig.add_trace(
- plgo.Scatter(
- x=xaxis,
- y=yaxis,
- name=name,
- mode=u"lines",
- legendgroup=name,
- showlegend=bool(idx),
- line=dict(
- color=COLORS[color]
- ),
- hovertext=hovertext,
- hoverinfo=u"text"
- )
- )
- except hdrh.codec.HdrLengthException as err:
- logging.warning(
- f"No or invalid data for HDRHistogram for the test "
- f"{name}\n{err}"
- )
- continue
- else:
- logging.warning(f"Invalid test type: {test[u'type']}")
- continue
- except (ValueError, KeyError) as err:
- logging.warning(repr(err))
-
- layout = deepcopy(plot[u"layout"])
-
- layout[u"title"][u"text"] = \
- f"<b>Latency:</b> {plot.get(u'graph-title', u'')}"
- fig[u"layout"].update(layout)
-
- # Create plot
- file_type = plot.get(u"output-file-type", u".html")
- logging.info(f" Writing file {plot[u'output-file']}{file_type}.")
- try:
- # Export Plot
- ploff.plot(fig, show_link=False, auto_open=False,
- filename=f"{plot[u'output-file']}{file_type}")
- except PlotlyError as err:
- logging.error(f" Finished with error: {repr(err)}")
-
-
def plot_hdrh_lat_by_percentile(plot, input_data):
"""Generate the plot(s) with algorithm: plot_hdrh_lat_by_percentile
specified in the specification file.
@@ -336,182 +227,6 @@ def plot_hdrh_lat_by_percentile(plot, input_data):
continue
-def plot_lat_hdrh_bar_name(plot, input_data):
- """Generate the plot(s) with algorithm: plot_lat_hdrh_bar_name
- 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(u"title", u"")
- logging.info(
- f" Creating the data set for the {plot.get(u'type', u'')} "
- f"{plot_title}."
- )
- data = input_data.filter_tests_by_name(
- plot, params=[u"latency", u"parent", u"tags", u"type"])
- if data is None or len(data[0][0]) == 0:
- logging.error(u"No data.")
- return
-
- # Prepare the data for the plot
- directions = [u"W-E", u"E-W"]
- tests = list()
- traces = list()
- for idx_row, test in enumerate(data[0][0]):
- try:
- if test[u"type"] in (u"NDRPDR",):
- 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
- name = re.sub(REGEX_NIC, u"", test[u"parent"].
- replace(u'-ndrpdr', u'').
- replace(u'2n1l-', u''))
- histograms = list()
- for idx_col, direction in enumerate(
- (u"direction1", u"direction2", )):
- try:
- hdr_lat = test[u"latency"][ttype][direction][u"hdrh"]
- # TODO: Workaround, HDRH data must be aligned to 4
- # bytes, remove when not needed.
- hdr_lat += u"=" * (len(hdr_lat) % 4)
- xaxis = list()
- yaxis = list()
- hovertext = list()
- decoded = hdrh.histogram.HdrHistogram.decode(hdr_lat)
- total_count = decoded.get_total_count()
- for item in decoded.get_recorded_iterator():
- xaxis.append(item.value_iterated_to)
- prob = float(item.count_added_in_this_iter_step) / \
- total_count * 100
- yaxis.append(prob)
- hovertext.append(
- f"Test: {name}<br>"
- f"Direction: {directions[idx_col]}<br>"
- f"Latency: {item.value_iterated_to}uSec<br>"
- f"Probability: {prob:.2f}%<br>"
- f"Percentile: "
- f"{item.percentile_level_iterated_to:.2f}"
- )
- marker_color = [COLORS[idx_row], ] * len(yaxis)
- marker_color[xaxis.index(
- decoded.get_value_at_percentile(50.0))] = u"red"
- marker_color[xaxis.index(
- decoded.get_value_at_percentile(90.0))] = u"red"
- marker_color[xaxis.index(
- decoded.get_value_at_percentile(95.0))] = u"red"
- histograms.append(
- plgo.Bar(
- x=xaxis,
- y=yaxis,
- showlegend=False,
- name=name,
- marker={u"color": marker_color},
- hovertext=hovertext,
- hoverinfo=u"text"
- )
- )
- except hdrh.codec.HdrLengthException as err:
- logging.warning(
- f"No or invalid data for HDRHistogram for the test "
- f"{name}\n{err}"
- )
- continue
- if len(histograms) == 2:
- traces.append(histograms)
- tests.append(name)
- else:
- logging.warning(f"Invalid test type: {test[u'type']}")
- continue
- except (ValueError, KeyError) as err:
- logging.warning(repr(err))
-
- if not tests:
- logging.warning(f"No data for {plot_title}.")
- return
-
- fig = make_subplots(
- rows=len(tests),
- cols=2,
- specs=[
- [{u"type": u"bar"}, {u"type": u"bar"}] for _ in range(len(tests))
- ]
- )
-
- layout_axes = dict(
- gridcolor=u"rgb(220, 220, 220)",
- linecolor=u"rgb(220, 220, 220)",
- linewidth=1,
- showgrid=True,
- showline=True,
- showticklabels=True,
- tickcolor=u"rgb(220, 220, 220)",
- )
-
- for idx_row, test in enumerate(tests):
- for idx_col in range(2):
- fig.add_trace(
- traces[idx_row][idx_col],
- row=idx_row + 1,
- col=idx_col + 1
- )
- fig.update_xaxes(
- row=idx_row + 1,
- col=idx_col + 1,
- **layout_axes
- )
- fig.update_yaxes(
- row=idx_row + 1,
- col=idx_col + 1,
- **layout_axes
- )
-
- layout = deepcopy(plot[u"layout"])
-
- layout[u"title"][u"text"] = \
- f"<b>Latency:</b> {plot.get(u'graph-title', u'')}"
- layout[u"height"] = 250 * len(tests) + 130
-
- layout[u"annotations"][2][u"y"] = 1.06 - 0.008 * len(tests)
- layout[u"annotations"][3][u"y"] = 1.06 - 0.008 * len(tests)
-
- for idx, test in enumerate(tests):
- layout[u"annotations"].append({
- u"font": {
- u"size": 14
- },
- u"showarrow": False,
- u"text": f"<b>{test}</b>",
- u"textangle": 0,
- u"x": 0.5,
- u"xanchor": u"center",
- u"xref": u"paper",
- u"y": 1.0 - float(idx) * 1.06 / len(tests),
- u"yanchor": u"bottom",
- u"yref": u"paper"
- })
-
- fig[u"layout"].update(layout)
-
- # Create plot
- file_type = plot.get(u"output-file-type", u".html")
- logging.info(f" Writing file {plot[u'output-file']}{file_type}.")
- try:
- # Export Plot
- ploff.plot(fig, show_link=False, auto_open=False,
- filename=f"{plot[u'output-file']}{file_type}")
- except PlotlyError as err:
- logging.error(f" Finished with error: {repr(err)}")
-
-
def plot_nf_reconf_box_name(plot, input_data):
"""Generate the plot(s) with algorithm: plot_nf_reconf_box_name
specified in the specification file.
@@ -740,179 +455,6 @@ def plot_perf_box_name(plot, input_data):
return
-def plot_lat_err_bars_name(plot, input_data):
- """Generate the plot(s) with algorithm: plot_lat_err_bars_name
- 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(u"title", u"")
- logging.info(
- f" Creating data set for the {plot.get(u'type', u'')} {plot_title}."
- )
- data = input_data.filter_tests_by_name(
- plot, params=[u"latency", u"parent", u"tags", u"type"])
- if data is None:
- logging.error(u"No data.")
- return
-
- # 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
- ))
-
- try:
- # Create plot
- file_type = plot.get(u"output-file-type", u".html")
- logging.info(f" Writing file {plot[u'output-file']}{file_type}.")
- layout = deepcopy(plot[u"layout"])
- if layout.get(u"title", None):
- layout[u"title"] = f"<b>Latency:</b> {layout[u'title']}"
- layout[u"annotations"] = annotations
- plpl = plgo.Figure(data=traces, layout=layout)
-
- # Export Plot
- ploff.plot(
- plpl,
- show_link=False, auto_open=False,
- filename=f"{plot[u'output-file']}{file_type}"
- )
- except PlotlyError as err:
- logging.error(
- f" Finished with error: {repr(err)}".replace(u"\n", u" ")
- )
- return
-
-
def plot_tsa_name(plot, input_data):
"""Generate the plot(s) with algorithm:
plot_tsa_name
diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py
index 08c9d55305..33cd763dca 100644
--- a/resources/tools/presentation/generator_tables.py
+++ b/resources/tools/presentation/generator_tables.py
@@ -866,7 +866,7 @@ def table_perf_trending_dash(table, input_data):
if len(data_t) < 2:
continue
- classification_lst, avgs = classify_anomalies(data_t)
+ classification_lst, avgs, _ = classify_anomalies(data_t)
win_size = min(len(data_t), table[u"window"])
long_win_size = min(len(data_t), table[u"long-trend-window"])
@@ -903,8 +903,8 @@ def table_perf_trending_dash(table, input_data):
round(last_avg / 1e6, 2),
rel_change_last,
rel_change_long,
- classification_lst[-win_size:].count(u"regression"),
- classification_lst[-win_size:].count(u"progression")])
+ classification_lst[-win_size+1:].count(u"regression"),
+ classification_lst[-win_size+1:].count(u"progression")])
tbl_lst.sort(key=lambda rel: rel[0])
@@ -1155,7 +1155,7 @@ def table_perf_trending_dash_html(table, input_data):
attrib=dict(align=u"left" if c_idx == 0 else u"center")
)
# Name:
- if c_idx == 0:
+ if c_idx == 0 and table.get(u"add-links", True):
ref = ET.SubElement(
tdata,
u"a",
diff --git a/resources/tools/presentation/input_data_parser.py b/resources/tools/presentation/input_data_parser.py
index 27db6a84d8..fc640875ce 100644
--- a/resources/tools/presentation/input_data_parser.py
+++ b/resources/tools/presentation/input_data_parser.py
@@ -1454,17 +1454,17 @@ class InputData:
do_repeat -= 1
if not success:
logging.error(
- f"It is not possible to download the input data file from the "
- f"job {job}, build {build[u'build']}, or it is damaged. "
- f"Skipped."
+ f"It is not possible to download the input data file from the "
+ f"job {job}, build {build[u'build']}, or it is damaged. "
+ f"Skipped."
)
if success:
logging.info(f" Processing data from build {build[u'build']}")
data = self._parse_tests(job, build)
if data is None:
logging.error(
- f"Input data file from the job {job}, build "
- f"{build[u'build']} is damaged. Skipped."
+ f"Input data file from the job {job}, build "
+ f"{build[u'build']} is damaged. Skipped."
)
else:
state = u"processed"
@@ -1592,7 +1592,7 @@ class InputData:
self._cfg.add_build(job, build)
logging.info(f"Processing {job}: {build_nr:2d}: {local_file}")
- data = self._parse_tests(job, build, list())
+ data = self._parse_tests(job, build)
if data is None:
raise PresentationError(
f"Error occurred while parsing the file {local_file}"
diff --git a/resources/tools/presentation/pal_utils.py b/resources/tools/presentation/pal_utils.py
index 98d5837989..86a6679918 100644
--- a/resources/tools/presentation/pal_utils.py
+++ b/resources/tools/presentation/pal_utils.py
@@ -262,7 +262,7 @@ def classify_anomalies(data):
:param data: Full data set with unavailable samples replaced by nan.
:type data: OrderedDict
:returns: Classification and trend values
- :rtype: 2-tuple, list of strings and list of floats
+ :rtype: 3-tuple, list of strings, list of floats and list of floats
"""
# Nan means something went wrong.
# Use 0.0 to cause that being reported as a severe regression.
@@ -273,13 +273,16 @@ def classify_anomalies(data):
group_list.reverse() # Just to use .pop() for FIFO.
classification = []
avgs = []
+ stdevs = []
active_group = None
values_left = 0
avg = 0.0
+ stdv = 0.0
for sample in data.values():
if np.isnan(sample):
classification.append(u"outlier")
avgs.append(sample)
+ stdevs.append(sample)
continue
if values_left < 1 or active_group is None:
values_left = 0
@@ -287,14 +290,17 @@ def classify_anomalies(data):
active_group = group_list.pop()
values_left = len(active_group.run_list)
avg = active_group.stats.avg
+ stdv = active_group.stats.stdev
classification.append(active_group.comment)
avgs.append(avg)
+ stdevs.append(stdv)
values_left -= 1
continue
classification.append(u"normal")
avgs.append(avg)
+ stdevs.append(stdv)
values_left -= 1
- return classification, avgs
+ return classification, avgs, stdevs
def convert_csv_to_pretty_txt(csv_file_name, txt_file_name, delimiter=u","):
diff --git a/resources/tools/presentation/specification_CPTA.yaml b/resources/tools/presentation/specification_CPTA.yaml
index 6f8dee1bef..5eb45e6336 100644
--- a/resources/tools/presentation/specification_CPTA.yaml
+++ b/resources/tools/presentation/specification_CPTA.yaml
@@ -915,6 +915,7 @@
input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-1t1c-3n-hsw-ndr.csv"
output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-1t1c-3n-hsw-ndr.rst"
testbed: "3n-hsw"
+ add-links: False
-
type: "table"
@@ -923,6 +924,7 @@
input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-1t1c-3n-hsw-pdr.csv"
output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-1t1c-3n-hsw-pdr.rst"
testbed: "3n-hsw"
+ add-links: False
# 3n-skx
-
@@ -964,6 +966,7 @@
input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-3n-skx-ndr.csv"
output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-3n-skx-ndr.rst"
testbed: "3n-skx"
+ add-links: False
-
type: "table"
@@ -972,6 +975,7 @@
input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-3n-skx-pdr.csv"
output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-3n-skx-pdr.rst"
testbed: "3n-skx"
+ add-links: False
# 2n-skx
-
@@ -1013,6 +1017,7 @@
input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-skx-ndr.csv"
output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-skx-ndr.rst"
testbed: "2n-skx"
+ add-links: False
-
type: "table"
@@ -1021,6 +1026,7 @@
input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-skx-pdr.csv"
output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-skx-pdr.rst"
testbed: "2n-skx"
+ add-links: False
# 2n-clx
-
@@ -1062,6 +1068,7 @@
input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-clx-ndr.csv"
output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-clx-ndr.rst"
testbed: "2n-clx"
+ add-links: False
-
type: "table"
@@ -1070,6 +1077,7 @@
input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-clx-pdr.csv"
output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-clx-pdr.rst"
testbed: "2n-clx"
+ add-links: False
-
type: "table"
diff --git a/resources/tools/presentation/specification_parser.py b/resources/tools/presentation/specification_parser.py
index 302ce037ab..37b26eb0d5 100644
--- a/resources/tools/presentation/specification_parser.py
+++ b/resources/tools/presentation/specification_parser.py
@@ -535,7 +535,7 @@ class Specification:
except ValueError:
# defined as a range <start, build_type>
build_end = self._get_build_number(job, build_end)
- builds = [x for x in range(builds[u"start"], build_end + 1)]
+ builds = list(range(builds[u"start"], build_end + 1))
if max_builds and max_builds < len(builds):
builds = builds[-max_builds:]
if reverse: