X-Git-Url: https://gerrit.fd.io/r/gitweb?a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fgenerator_plots.py;h=89eb1c6521444858d1172a5236712247282d7be5;hb=79f5ba9bf7656972dd988508eff9465562dde42c;hp=e7a50fc0491b39386e5ae16974f2c6f55168ced4;hpb=c26ab619b300e6bf38c447c0600a5739ca46e27b;p=csit.git
diff --git a/resources/tools/presentation/generator_plots.py b/resources/tools/presentation/generator_plots.py
index e7a50fc049..89eb1c6521 100644
--- a/resources/tools/presentation/generator_plots.py
+++ b/resources/tools/presentation/generator_plots.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2019 Cisco and/or its affiliates.
+# Copyright (c) 2020 Cisco and/or its affiliates.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at:
@@ -40,7 +40,7 @@ COLORS = [u"SkyBlue", u"Olive", u"Purple", u"Coral", u"Indigo", u"Pink",
u"LightGreen", u"LightSeaGreen", u"LightSkyBlue", u"Maroon",
u"MediumSeaGreen", u"SeaGreen", u"LightSlateGrey"]
-REGEX_NIC = re.compile(r'\d*ge\dp\d\D*\d*-')
+REGEX_NIC = re.compile(r'(\d*ge\dp\d\D*\d*[a-z]*)-')
def generate_plots(spec, data):
@@ -60,7 +60,8 @@ def generate_plots(spec, data):
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_lat_hdrh_percentile": plot_lat_hdrh_percentile,
+ u"plot_hdrh_lat_by_percentile": plot_hdrh_lat_by_percentile
}
logging.info(u"Generating the plots ...")
@@ -116,8 +117,7 @@ def plot_lat_hdrh_percentile(plot, input_data):
continue
name = re.sub(REGEX_NIC, u"", test[u"parent"].
replace(u'-ndrpdr', u'').
- replace(u'2n1l-', u'').
- replace(u'avf-', u''))
+ replace(u'2n1l-', u''))
for idx, direction in enumerate(
(u"direction1", u"direction2", )):
try:
@@ -184,6 +184,158 @@ def plot_lat_hdrh_percentile(plot, input_data):
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.
+
+ :param plot: Plot to generate.
+ :param input_data: Data to process.
+ :type plot: pandas.Series
+ :type input_data: InputData
+ """
+
+ # Transform the data
+ logging.info(
+ f" Creating the data set for the {plot.get(u'type', u'')} "
+ f"{plot.get(u'title', u'')}."
+ )
+ if plot.get(u"include", None):
+ data = input_data.filter_tests_by_name(
+ plot,
+ params=[u"name", u"latency", u"parent", u"tags", u"type"]
+ )[0][0]
+ elif plot.get(u"filter", None):
+ data = input_data.filter_data(
+ plot,
+ params=[u"name", u"latency", u"parent", u"tags", u"type"],
+ continue_on_error=True
+ )[0][0]
+ else:
+ job = list(plot[u"data"].keys())[0]
+ build = str(plot[u"data"][job][0])
+ data = input_data.tests(job, build)
+
+ if data is None or len(data) == 0:
+ logging.error(u"No data.")
+ return
+
+ desc = {
+ u"LAT0": u"No-load.",
+ u"PDR10": u"Low-load, 10% PDR.",
+ u"PDR50": u"Mid-load, 50% PDR.",
+ u"PDR90": u"High-load, 90% PDR.",
+ u"PDR": u"Full-load, 100% PDR.",
+ u"NDR10": u"Low-load, 10% NDR.",
+ u"NDR50": u"Mid-load, 50% NDR.",
+ u"NDR90": u"High-load, 90% NDR.",
+ u"NDR": u"Full-load, 100% NDR."
+ }
+
+ graphs = [
+ u"LAT0",
+ u"PDR10",
+ u"PDR50",
+ u"PDR90"
+ ]
+
+ file_links = plot.get(u"output-file-links", None)
+ target_links = plot.get(u"target-links", None)
+
+ for test in data:
+ try:
+ if test[u"type"] not in (u"NDRPDR",):
+ 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''))
+ try:
+ nic = re.search(REGEX_NIC, test[u"parent"]).group(1)
+ except (IndexError, AttributeError, KeyError, ValueError):
+ nic = u""
+ name_link = f"{nic}-{test[u'name']}".replace(u'-ndrpdr', u'')
+
+ logging.info(f" Generating the graph: {name_link}")
+
+ fig = plgo.Figure()
+ layout = deepcopy(plot[u"layout"])
+
+ for color, graph in enumerate(graphs):
+ for idx, direction in enumerate((u"direction1", u"direction2")):
+ xaxis = [0.0, ]
+ yaxis = [0.0, ]
+ hovertext = [
+ f"{desc[graph]}
"
+ f"Direction: {(u'W-E', u'E-W')[idx % 2]}
"
+ f"Percentile: 0.0%
"
+ f"Latency: 0.0uSec"
+ ]
+ decoded = hdrh.histogram.HdrHistogram.decode(
+ test[u"latency"][graph][direction][u"hdrh"]
+ )
+ for item in decoded.get_recorded_iterator():
+ percentile = item.percentile_level_iterated_to
+ if percentile > 99.9:
+ continue
+ xaxis.append(percentile)
+ yaxis.append(item.value_iterated_to)
+ hovertext.append(
+ f"{desc[graph]}
"
+ f"Direction: {(u'W-E', u'E-W')[idx % 2]}
"
+ f"Percentile: {percentile:.5f}%
"
+ f"Latency: {item.value_iterated_to}uSec"
+ )
+ fig.add_trace(
+ plgo.Scatter(
+ x=xaxis,
+ y=yaxis,
+ name=desc[graph],
+ mode=u"lines",
+ legendgroup=desc[graph],
+ showlegend=bool(idx),
+ line=dict(
+ color=COLORS[color],
+ dash=u"solid" if idx % 2 else u"dash"
+ ),
+ hovertext=hovertext,
+ hoverinfo=u"text"
+ )
+ )
+
+ layout[u"title"][u"text"] = f"Latency: {name}"
+ fig.update_layout(layout)
+
+ # Create plot
+ file_name = f"{plot[u'output-file']}-{name_link}.html"
+ logging.info(f" Writing file {file_name}")
+
+ try:
+ # Export Plot
+ ploff.plot(fig, show_link=False, auto_open=False,
+ filename=file_name)
+ # Add link to the file:
+ if file_links and target_links:
+ with open(file_links, u"a") as file_handler:
+ file_handler.write(
+ f"- `{name_link} "
+ f"<{target_links}/{file_name.split(u'/')[-1]}>`_\n"
+ )
+ except FileNotFoundError as err:
+ logging.error(
+ f"Not possible to write the link to the file "
+ f"{file_links}\n{err}"
+ )
+ except PlotlyError as err:
+ logging.error(f" Finished with error: {repr(err)}")
+
+ except hdrh.codec.HdrLengthException as err:
+ logging.warning(repr(err))
+ continue
+
+ except (ValueError, KeyError) as err:
+ logging.warning(repr(err))
+ 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.
@@ -222,8 +374,7 @@ def plot_lat_hdrh_bar_name(plot, input_data):
continue
name = re.sub(REGEX_NIC, u"", test[u"parent"].
replace(u'-ndrpdr', u'').
- replace(u'2n1l-', u'').
- replace(u'avf-', u''))
+ replace(u'2n1l-', u''))
histograms = list()
for idx_col, direction in enumerate(
(u"direction1", u"direction2", )):
@@ -416,7 +567,7 @@ def plot_nf_reconf_box_name(plot, input_data):
for i, col in enumerate(df_y.columns):
tst_name = re.sub(REGEX_NIC, u"",
col.lower().replace(u'-ndrpdr', u'').
- replace(u'2n1l-', u'').replace(u'avf-', u''))
+ replace(u'2n1l-', u''))
traces.append(plgo.Box(
x=[str(i + 1) + u'.'] * len(df_y[col]),
@@ -471,13 +622,14 @@ def plot_perf_box_name(plot, input_data):
f"{plot.get(u'title', u'')}."
)
data = input_data.filter_tests_by_name(
- plot, params=[u"throughput", u"parent", u"tags", u"type"])
+ plot, params=[u"throughput", u"result", u"parent", u"tags", u"type"])
if data is None:
logging.error(u"No data.")
return
# Prepare the data for the plot
y_vals = OrderedDict()
+ test_type = u""
for job in data:
for build in job:
for test in build:
@@ -488,13 +640,30 @@ def plot_perf_box_name(plot, input_data):
u"-pdr" in plot.get(u"title", u"").lower()):
y_vals[test[u"parent"]].\
append(test[u"throughput"][u"PDR"][u"LOWER"])
+ test_type = u"NDRPDR"
elif (test[u"type"] in (u"NDRPDR", ) and
u"-ndr" in plot.get(u"title", u"").lower()):
y_vals[test[u"parent"]]. \
append(test[u"throughput"][u"NDR"][u"LOWER"])
+ test_type = u"NDRPDR"
elif test[u"type"] in (u"SOAK", ):
y_vals[test[u"parent"]].\
append(test[u"throughput"][u"LOWER"])
+ test_type = u"SOAK"
+ elif test[u"type"] in (u"HOSTSTACK", ):
+ if u"LDPRELOAD" in test[u"tags"]:
+ y_vals[test[u"parent"]].append(
+ float(test[u"result"][u"bits_per_second"]) / 1e3
+ )
+ elif u"VPPECHO" in test[u"tags"]:
+ y_vals[test[u"parent"]].append(
+ (float(test[u"result"][u"client"][u"tx_data"])
+ * 8 / 1e3) /
+ ((float(test[u"result"][u"client"][u"time"]) +
+ float(test[u"result"][u"server"][u"time"])) /
+ 2)
+ )
+ test_type = u"HOSTSTACK"
else:
continue
except (KeyError, TypeError):
@@ -519,24 +688,27 @@ def plot_perf_box_name(plot, input_data):
for i, col in enumerate(df_y.columns):
tst_name = re.sub(REGEX_NIC, u"",
col.lower().replace(u'-ndrpdr', u'').
- replace(u'2n1l-', u'').replace(u'avf-', u''))
- traces.append(
- plgo.Box(
- x=[str(i + 1) + u'.'] * len(df_y[col]),
- y=[y / 1000000 if y else None for y in df_y[col]],
- name=(
- f"{i + 1}. "
- f"({nr_of_samples[i]:02d} "
- f"run{u's' if nr_of_samples[i] > 1 else u''}) "
- f"{tst_name}"
- ),
- hoverinfo=u"y+name"
- )
+ replace(u'2n1l-', u''))
+ kwargs = dict(
+ x=[str(i + 1) + u'.'] * len(df_y[col]),
+ y=[y / 1e6 if y else None for y in df_y[col]],
+ name=(
+ f"{i + 1}. "
+ f"({nr_of_samples[i]:02d} "
+ f"run{u's' if nr_of_samples[i] > 1 else u''}) "
+ f"{tst_name}"
+ ),
+ hoverinfo=u"y+name"
)
+ if test_type in (u"SOAK", ):
+ kwargs[u"boxpoints"] = u"all"
+
+ traces.append(plgo.Box(**kwargs))
+
try:
val_max = max(df_y[col])
if val_max:
- y_max.append(int(val_max / 1000000) + 2)
+ y_max.append(int(val_max / 1e6) + 2)
except (ValueError, TypeError) as err:
logging.error(repr(err))
continue
@@ -545,7 +717,10 @@ def plot_perf_box_name(plot, input_data):
# Create plot
layout = deepcopy(plot[u"layout"])
if layout.get(u"title", None):
- layout[u"title"] = f"Throughput: {layout[u'title']}"
+ if test_type in (u"HOSTSTACK", ):
+ layout[u"title"] = f"Bandwidth: {layout[u'title']}"
+ else:
+ layout[u"title"] = f"Throughput: {layout[u'title']}"
if y_max:
layout[u"yaxis"][u"range"] = [0, max(y_max)]
plpl = plgo.Figure(data=traces, layout=layout)
@@ -639,7 +814,7 @@ def plot_lat_err_bars_name(plot, input_data):
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'').replace(u'avf-', 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)
@@ -803,7 +978,7 @@ def plot_tsa_name(plot, input_data):
if test_val:
avg_val = sum(test_val) / len(test_val)
y_vals[test_name][key] = [avg_val, len(test_val)]
- ideal = avg_val / (int(key) * 1000000.0)
+ ideal = avg_val / (int(key) * 1e6)
if test_name not in y_1c_max or ideal > y_1c_max[test_name]:
y_1c_max[test_name] = ideal
@@ -818,14 +993,13 @@ def plot_tsa_name(plot, input_data):
name = re.sub(
REGEX_NIC,
u"",
- test_name.replace(u'-ndrpdr', u'').replace(u'2n1l-', u'').
- replace(u'avf-', u'')
+ test_name.replace(u'-ndrpdr', u'').replace(u'2n1l-', u'')
)
vals[name] = OrderedDict()
- y_val_1 = test_vals[u"1"][0] / 1000000.0
- y_val_2 = test_vals[u"2"][0] / 1000000.0 if test_vals[u"2"][0] \
+ y_val_1 = test_vals[u"1"][0] / 1e6
+ y_val_2 = test_vals[u"2"][0] / 1e6 if test_vals[u"2"][0] \
else None
- y_val_4 = test_vals[u"4"][0] / 1000000.0 if test_vals[u"4"][0] \
+ y_val_4 = test_vals[u"4"][0] / 1e6 if test_vals[u"4"][0] \
else None
vals[name][u"val"] = [y_val_1, y_val_2, y_val_4]
@@ -875,6 +1049,8 @@ def plot_tsa_name(plot, input_data):
limit = plot[u"limits"][u"nic"][u"xl710"]
elif u"x553" in test_name:
limit = plot[u"limits"][u"nic"][u"x553"]
+ elif u"cx556a" in test_name:
+ limit = plot[u"limits"][u"nic"][u"cx556a"]
else:
limit = 0
if limit > nic_limit:
@@ -904,7 +1080,7 @@ def plot_tsa_name(plot, input_data):
except ValueError as err:
logging.error(err)
return
- nic_limit /= 1000000.0
+ nic_limit /= 1e6
traces.append(plgo.Scatter(
x=x_vals,
y=[nic_limit, ] * len(x_vals),
@@ -934,7 +1110,7 @@ def plot_tsa_name(plot, input_data):
))
y_max.append(nic_limit)
- lnk_limit /= 1000000.0
+ lnk_limit /= 1e6
if lnk_limit < threshold:
traces.append(plgo.Scatter(
x=x_vals,
@@ -965,7 +1141,7 @@ def plot_tsa_name(plot, input_data):
))
y_max.append(lnk_limit)
- pci_limit /= 1000000.0
+ pci_limit /= 1e6
if (pci_limit < threshold and
(pci_limit < lnk_limit * 0.95 or lnk_limit > lnk_limit * 1.05)):
traces.append(plgo.Scatter(
@@ -1180,7 +1356,7 @@ def plot_nf_heatmap(plot, input_data):
regex_cn = re.compile(r'^(\d*)R(\d*)C$')
regex_test_name = re.compile(r'^.*-(\d+ch|\d+pl)-'
r'(\d+mif|\d+vh)-'
- r'(\d+vm\d+t|\d+dcr\d+t).*$')
+ r'(\d+vm\d+t|\d+dcr\d+t|\d+dcr\d+c).*$')
vals = dict()
# Transform the data
@@ -1479,15 +1655,12 @@ def plot_nf_heatmap(plot, input_data):
plpl = plgo.Figure(data=traces, layout=layout)
# Export Plot
- logging.info(
- f" Writing file {plot[u'output-file']}"
- f"{plot[u'output-file-type']}."
- )
+ logging.info(f" Writing file {plot[u'output-file']}.html")
ploff.plot(
plpl,
show_link=False,
auto_open=False,
- filename=f"{plot[u'output-file']}{plot[u'output-file-type']}"
+ filename=f"{plot[u'output-file']}.html"
)
except PlotlyError as err:
logging.error(