if plot.get(u"include", None):
data = input_data.filter_tests_by_name(
plot,
- params=[u"latency", u"throughput", u"parent", u"tags", u"type"]
+ 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"latency", u"throughput", u"parent", u"tags", u"type"],
+ 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])
filename=file_name)
# Add link to the file:
if file_links and target_links:
- with open(file_links, u"a") as fw:
- fw.write(
+ with open(file_links, u"a") as file_handler:
+ file_handler.write(
f"- `{name_link} "
f"<{target_links}/{file_name.split(u'/')[-1]}>`_\n"
)
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:
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):
tst_name = re.sub(REGEX_NIC, u"",
col.lower().replace(u'-ndrpdr', u'').
replace(u'2n1l-', 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"
- )
+ 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
# Create plot
layout = deepcopy(plot[u"layout"])
if layout.get(u"title", None):
- layout[u"title"] = f"<b>Throughput:</b> {layout[u'title']}"
+ if test_type in (u"HOSTSTACK", ):
+ layout[u"title"] = f"<b>Bandwidth:</b> {layout[u'title']}"
+ else:
+ layout[u"title"] = f"<b>Throughput:</b> {layout[u'title']}"
if y_max:
layout[u"yaxis"][u"range"] = [0, max(y_max)]
plpl = plgo.Figure(data=traces, layout=layout)
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
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]
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:
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),
))
y_max.append(nic_limit)
- lnk_limit /= 1000000.0
+ lnk_limit /= 1e6
if lnk_limit < threshold:
traces.append(plgo.Scatter(
x=x_vals,
))
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(
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