-# 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:
from numpy import nan, isnan
-from pal_utils import mean, stdev, relative_change, classify_anomalies, \
+from pal_utils import mean, stdev, classify_anomalies, \
convert_csv_to_pretty_txt, relative_change_stdev
-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_tables(spec, data):
"""
generator = {
- u"table_details": table_details,
u"table_merged_details": table_merged_details,
u"table_perf_comparison": table_perf_comparison,
u"table_perf_comparison_nic": table_perf_comparison_nic,
u"table_perf_trending_dash_html": table_perf_trending_dash_html,
u"table_last_failed_tests": table_last_failed_tests,
u"table_failed_tests": table_failed_tests,
- u"table_failed_tests_html": table_failed_tests_html
+ u"table_failed_tests_html": table_failed_tests_html,
+ u"table_oper_data_html": table_oper_data_html
}
logging.info(u"Generating the tables ...")
logging.info(u"Done.")
-def table_details(table, input_data):
- """Generate the table(s) with algorithm: table_detailed_test_results
+def table_oper_data_html(table, input_data):
+ """Generate the table(s) with algorithm: html_table_oper_data
specified in the specification file.
:param table: Table to generate.
"""
logging.info(f" Generating the table {table.get(u'title', u'')} ...")
-
# Transform the data
logging.info(
f" Creating the data set for the {table.get(u'type', u'')} "
f"{table.get(u'title', u'')}."
)
- data = input_data.filter_data(table)
+ data = input_data.filter_data(
+ table,
+ params=[u"name", u"parent", u"show-run", u"type"],
+ continue_on_error=True
+ )
+ if data.empty:
+ return
+ data = input_data.merge_data(data)
- # Prepare the header of the tables
- header = list()
- for column in table[u"columns"]:
- header.append(
- u'"{0}"'.format(str(column[u"title"]).replace(u'"', u'""'))
+ sort_tests = table.get(u"sort", None)
+ if sort_tests:
+ args = dict(
+ inplace=True,
+ ascending=(sort_tests == u"ascending")
)
+ data.sort_index(**args)
- # Generate the data for the table according to the model in the table
- # specification
- job = list(table[u"data"].keys())[0]
- build = str(table[u"data"][job][0])
- try:
- suites = input_data.suites(job, build)
- except KeyError:
- logging.error(
- u" No data available. The table will not be generated."
- )
+ suites = input_data.filter_data(
+ table,
+ continue_on_error=True,
+ data_set=u"suites"
+ )
+ if suites.empty:
return
+ suites = input_data.merge_data(suites)
- for suite in suites.values:
- # Generate data
- suite_name = suite[u"name"]
- table_lst = list()
- for test in data[job][build].keys():
- if data[job][build][test][u"parent"] not in suite_name:
+ def _generate_html_table(tst_data):
+ """Generate an HTML table with operational data for the given test.
+
+ :param tst_data: Test data to be used to generate the table.
+ :type tst_data: pandas.Series
+ :returns: HTML table with operational data.
+ :rtype: str
+ """
+
+ colors = {
+ u"header": u"#7eade7",
+ u"empty": u"#ffffff",
+ u"body": (u"#e9f1fb", u"#d4e4f7")
+ }
+
+ tbl = ET.Element(u"table", attrib=dict(width=u"100%", border=u"0"))
+
+ trow = ET.SubElement(tbl, u"tr", attrib=dict(bgcolor=colors[u"header"]))
+ thead = ET.SubElement(
+ trow, u"th", attrib=dict(align=u"left", colspan=u"6")
+ )
+ thead.text = tst_data[u"name"]
+
+ trow = ET.SubElement(tbl, u"tr", attrib=dict(bgcolor=colors[u"empty"]))
+ thead = ET.SubElement(
+ trow, u"th", attrib=dict(align=u"left", colspan=u"6")
+ )
+ thead.text = u"\t"
+
+ if tst_data.get(u"show-run", u"No Data") == u"No Data":
+ trow = ET.SubElement(
+ tbl, u"tr", attrib=dict(bgcolor=colors[u"header"])
+ )
+ tcol = ET.SubElement(
+ trow, u"td", attrib=dict(align=u"left", colspan=u"6")
+ )
+ tcol.text = u"No Data"
+
+ trow = ET.SubElement(
+ tbl, u"tr", attrib=dict(bgcolor=colors[u"empty"])
+ )
+ thead = ET.SubElement(
+ trow, u"th", attrib=dict(align=u"left", colspan=u"6")
+ )
+ font = ET.SubElement(
+ thead, u"font", attrib=dict(size=u"12px", color=u"#ffffff")
+ )
+ font.text = u"."
+ return str(ET.tostring(tbl, encoding=u"unicode"))
+
+ tbl_hdr = (
+ u"Name",
+ u"Nr of Vectors",
+ u"Nr of Packets",
+ u"Suspends",
+ u"Cycles per Packet",
+ u"Average Vector Size"
+ )
+
+ for dut_data in tst_data[u"show-run"].values():
+ trow = ET.SubElement(
+ tbl, u"tr", attrib=dict(bgcolor=colors[u"header"])
+ )
+ tcol = ET.SubElement(
+ trow, u"td", attrib=dict(align=u"left", colspan=u"6")
+ )
+ if dut_data.get(u"threads", None) is None:
+ tcol.text = u"No Data"
continue
- row_lst = list()
- for column in table[u"columns"]:
- try:
- col_data = str(data[job][build][test][column[
- u"data"].split(" ")[1]]).replace(u'"', u'""')
- if column[u"data"].split(u" ")[1] in \
- (u"conf-history", u"show-run"):
- col_data = col_data.replace(u" |br| ", u"", 1)
- col_data = f" |prein| {col_data[:-5]} |preout| "
- row_lst.append(f'"{col_data}"')
- except KeyError:
- row_lst.append(u"No data")
- table_lst.append(row_lst)
- # Write the data to file
- if table_lst:
- file_name = (
- f"{table[u'output-file']}_{suite_name}"
- f"{table[u'output-file-ext']}"
+ bold = ET.SubElement(tcol, u"b")
+ bold.text = (
+ f"Host IP: {dut_data.get(u'host', '')}, "
+ f"Socket: {dut_data.get(u'socket', '')}"
)
- logging.info(f" Writing file: {file_name}")
- with open(file_name, u"wt") as file_handler:
- file_handler.write(u",".join(header) + u"\n")
- for item in table_lst:
- file_handler.write(u",".join(item) + u"\n")
+ trow = ET.SubElement(
+ tbl, u"tr", attrib=dict(bgcolor=colors[u"empty"])
+ )
+ thead = ET.SubElement(
+ trow, u"th", attrib=dict(align=u"left", colspan=u"6")
+ )
+ thead.text = u"\t"
+
+ for thread_nr, thread in dut_data[u"threads"].items():
+ trow = ET.SubElement(
+ tbl, u"tr", attrib=dict(bgcolor=colors[u"header"])
+ )
+ tcol = ET.SubElement(
+ trow, u"td", attrib=dict(align=u"left", colspan=u"6")
+ )
+ bold = ET.SubElement(tcol, u"b")
+ bold.text = u"main" if thread_nr == 0 else f"worker_{thread_nr}"
+ trow = ET.SubElement(
+ tbl, u"tr", attrib=dict(bgcolor=colors[u"header"])
+ )
+ for idx, col in enumerate(tbl_hdr):
+ tcol = ET.SubElement(
+ trow, u"td",
+ attrib=dict(align=u"right" if idx else u"left")
+ )
+ font = ET.SubElement(
+ tcol, u"font", attrib=dict(size=u"2")
+ )
+ bold = ET.SubElement(font, u"b")
+ bold.text = col
+ for row_nr, row in enumerate(thread):
+ trow = ET.SubElement(
+ tbl, u"tr",
+ attrib=dict(bgcolor=colors[u"body"][row_nr % 2])
+ )
+ for idx, col in enumerate(row):
+ tcol = ET.SubElement(
+ trow, u"td",
+ attrib=dict(align=u"right" if idx else u"left")
+ )
+ font = ET.SubElement(
+ tcol, u"font", attrib=dict(size=u"2")
+ )
+ if isinstance(col, float):
+ font.text = f"{col:.2f}"
+ else:
+ font.text = str(col)
+ trow = ET.SubElement(
+ tbl, u"tr", attrib=dict(bgcolor=colors[u"empty"])
+ )
+ thead = ET.SubElement(
+ trow, u"th", attrib=dict(align=u"left", colspan=u"6")
+ )
+ thead.text = u"\t"
+
+ trow = ET.SubElement(tbl, u"tr", attrib=dict(bgcolor=colors[u"empty"]))
+ thead = ET.SubElement(
+ trow, u"th", attrib=dict(align=u"left", colspan=u"6")
+ )
+ font = ET.SubElement(
+ thead, u"font", attrib=dict(size=u"12px", color=u"#ffffff")
+ )
+ font.text = u"."
+
+ return str(ET.tostring(tbl, encoding=u"unicode"))
+ for suite in suites.values:
+ html_table = str()
+ for test_data in data.values:
+ if test_data[u"parent"] not in suite[u"name"]:
+ continue
+ html_table += _generate_html_table(test_data)
+ if not html_table:
+ continue
+ try:
+ file_name = f"{table[u'output-file']}{suite[u'name']}.rst"
+ with open(f"{file_name}", u'w') as html_file:
+ logging.info(f" Writing file: {file_name}")
+ html_file.write(u".. raw:: html\n\n\t")
+ html_file.write(html_table)
+ html_file.write(u"\n\t<p><br><br></p>\n")
+ except KeyError:
+ logging.warning(u"The output file is not defined.")
+ return
logging.info(u" Done.")
"""
logging.info(f" Generating the table {table.get(u'title', u'')} ...")
+
# Transform the data
logging.info(
f" Creating the data set for the {table.get(u'type', u'')} "
)
data = input_data.filter_data(table, continue_on_error=True)
data = input_data.merge_data(data)
- data.sort_index(inplace=True)
- logging.info(
- f" Creating the data set for the {table.get(u'type', u'')} "
- f"{table.get(u'title', u'')}."
- )
+ sort_tests = table.get(u"sort", None)
+ if sort_tests:
+ args = dict(
+ inplace=True,
+ ascending=(sort_tests == u"ascending")
+ )
+ data.sort_index(**args)
+
suites = input_data.filter_data(
table, continue_on_error=True, data_set=u"suites")
suites = input_data.merge_data(suites)
try:
col_data = str(data[test][column[
u"data"].split(u" ")[1]]).replace(u'"', u'""')
+ # Do not include tests with "Test Failed" in test message
+ if u"Test Failed" in col_data:
+ continue
col_data = col_data.replace(
u"No Data", u"Not Captured "
)
- if column[u"data"].split(u" ")[1] in \
- (u"conf-history", u"show-run"):
+ if column[u"data"].split(u" ")[1] in (u"name", ):
+ if len(col_data) > 30:
+ col_data_lst = col_data.split(u"-")
+ half = int(len(col_data_lst) / 2)
+ col_data = f"{u'-'.join(col_data_lst[:half])}" \
+ f"- |br| " \
+ f"{u'-'.join(col_data_lst[half:])}"
+ col_data = f" |prein| {col_data} |preout| "
+ elif column[u"data"].split(u" ")[1] in (u"msg", ):
+ # Temporary solution: remove NDR results from message:
+ if bool(table.get(u'remove-ndr', False)):
+ try:
+ col_data = col_data.split(u" |br| ", 1)[1]
+ except IndexError:
+ pass
+ col_data = f" |prein| {col_data} |preout| "
+ elif column[u"data"].split(u" ")[1] in \
+ (u"conf-history", u"show-run"):
col_data = col_data.replace(u" |br| ", u"", 1)
col_data = f" |prein| {col_data[:-5]} |preout| "
row_lst.append(f'"{col_data}"')
except KeyError:
row_lst.append(u'"Not captured"')
- table_lst.append(row_lst)
+ if len(row_lst) == len(table[u"columns"]):
+ table_lst.append(row_lst)
# Write the data to file
if table_lst:
- file_name = (
- f"{table[u'output-file']}_{suite_name}"
- f"{table[u'output-file-ext']}"
- )
+ separator = u"" if table[u'output-file'].endswith(u"/") else u"_"
+ file_name = f"{table[u'output-file']}{separator}{suite_name}.csv"
logging.info(f" Writing file: {file_name}")
with open(file_name, u"wt") as file_handler:
file_handler.write(u",".join(header) + u"\n")
:rtype: list
"""
-
tbl_new = list()
tbl_see = list()
tbl_delta = list()
# Sort the tables:
tbl_new.sort(key=lambda rel: rel[0], reverse=False)
tbl_see.sort(key=lambda rel: rel[0], reverse=False)
- tbl_see.sort(key=lambda rel: rel[-1], reverse=False)
- tbl_delta.sort(key=lambda rel: rel[-1], reverse=True)
+ tbl_see.sort(key=lambda rel: rel[-2], reverse=False)
+ tbl_delta.sort(key=lambda rel: rel[0], reverse=False)
+ tbl_delta.sort(key=lambda rel: rel[-2], reverse=True)
# Put the tables together:
table = list()
- table.extend(tbl_new)
+ # We do not want "New in CSIT":
+ # table.extend(tbl_new)
table.extend(tbl_see)
table.extend(tbl_delta)
xanchor=u"left",
y=1.045,
yanchor=u"top",
- active=len(menu_items) - 1,
+ active=len(menu_items) - 2,
buttons=list(buttons)
)
],
f"{table[u'reference'][u'title']} Stdev [Mpps]",
f"{table[u'compare'][u'title']} {hdr_param} [Mpps]",
f"{table[u'compare'][u'title']} Stdev [Mpps]",
- u"Delta [%]"
+ u"Delta [%]",
+ u"Stdev of delta [%]"
]
)
header_str = u",".join(header) + u"\n"
for build in builds:
for tst_name, tst_data in data[job][str(build)].items():
tst_name_mod = _tpc_modify_test_name(tst_name)
- if u"across topologies" in table[u"title"].lower():
+ if (u"across topologies" in table[u"title"].lower() or
+ (u" 3n-" in table[u"title"].lower() and
+ u" 2n-" in table[u"title"].lower())):
tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
if tbl_dict.get(tst_name_mod, None) is None:
groups = re.search(REGEX_NIC, tst_data[u"parent"])
for build in builds:
for tst_name, tst_data in rpl_data[job][str(build)].items():
tst_name_mod = _tpc_modify_test_name(tst_name)
- if u"across topologies" in table[u"title"].lower():
+ if (u"across topologies" in table[u"title"].lower() or
+ (u" 3n-" in table[u"title"].lower() and
+ u" 2n-" in table[u"title"].lower())):
tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
if tbl_dict.get(tst_name_mod, None) is None:
name = \
for build in builds:
for tst_name, tst_data in data[job][str(build)].items():
tst_name_mod = _tpc_modify_test_name(tst_name)
- if u"across topologies" in table[u"title"].lower():
+ if (u"across topologies" in table[u"title"].lower() or
+ (u" 3n-" in table[u"title"].lower() and
+ u" 2n-" in table[u"title"].lower())):
tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
if tbl_dict.get(tst_name_mod, None) is None:
groups = re.search(REGEX_NIC, tst_data[u"parent"])
for build in builds:
for tst_name, tst_data in rpl_data[job][str(build)].items():
tst_name_mod = _tpc_modify_test_name(tst_name)
- if u"across topologies" in table[u"title"].lower():
+ if (u"across topologies" in table[u"title"].lower() or
+ (u" 3n-" in table[u"title"].lower() and
+ u" 2n-" in table[u"title"].lower())):
tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
if tbl_dict.get(tst_name_mod, None) is None:
name = \
for build in builds:
for tst_name, tst_data in data[job][str(build)].items():
tst_name_mod = _tpc_modify_test_name(tst_name)
- if u"across topologies" in table[u"title"].lower():
+ if (u"across topologies" in table[u"title"].lower() or
+ (u" 3n-" in table[u"title"].lower() and
+ u" 2n-" in table[u"title"].lower())):
tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
if tbl_dict.get(tst_name_mod, None) is None:
continue
item.extend([u"Not tested", u"Not tested"])
else:
item.extend([u"Not tested", u"Not tested"])
- data_t = tbl_dict[tst_name][u"ref-data"]
- if data_t:
- item.append(round(mean(data_t) / 1000000, 2))
- item.append(round(stdev(data_t) / 1000000, 2))
+ data_r = tbl_dict[tst_name][u"ref-data"]
+ if data_r:
+ data_r_mean = mean(data_r)
+ item.append(round(data_r_mean / 1000000, 2))
+ data_r_stdev = stdev(data_r)
+ item.append(round(data_r_stdev / 1000000, 2))
else:
+ data_r_mean = None
+ data_r_stdev = None
item.extend([u"Not tested", u"Not tested"])
- data_t = tbl_dict[tst_name][u"cmp-data"]
- if data_t:
- item.append(round(mean(data_t) / 1000000, 2))
- item.append(round(stdev(data_t) / 1000000, 2))
+ data_c = tbl_dict[tst_name][u"cmp-data"]
+ if data_c:
+ data_c_mean = mean(data_c)
+ item.append(round(data_c_mean / 1000000, 2))
+ data_c_stdev = stdev(data_c)
+ item.append(round(data_c_stdev / 1000000, 2))
else:
+ data_c_mean = None
+ data_c_stdev = None
item.extend([u"Not tested", u"Not tested"])
if item[-2] == u"Not tested":
pass
elif item[-4] == u"Not tested":
item.append(u"New in CSIT-2001")
+ item.append(u"New in CSIT-2001")
# elif topo == u"2n-skx" and u"dot1q" in tbl_dict[tst_name][u"name"]:
# item.append(u"See footnote [1]")
# footnote = True
- elif item[-4] != 0:
- item.append(int(relative_change(float(item[-4]), float(item[-2]))))
- if (len(item) == len(header)) and (item[-3] != u"Not tested"):
+ elif data_r_mean and data_c_mean:
+ delta, d_stdev = relative_change_stdev(
+ data_r_mean, data_c_mean, data_r_stdev, data_c_stdev
+ )
+ item.append(round(delta))
+ item.append(round(d_stdev))
+ if (len(item) == len(header)) and (item[-4] != u"Not tested"):
tbl_lst.append(item)
tbl_lst = _tpc_sort_table(tbl_lst)
f"{table[u'reference'][u'title']} Stdev [Mpps]",
f"{table[u'compare'][u'title']} {hdr_param} [Mpps]",
f"{table[u'compare'][u'title']} Stdev [Mpps]",
- u"Delta [%]"
+ u"Delta [%]",
+ u"Stdev of delta [%]"
]
)
header_str = u",".join(header) + u"\n"
if table[u"reference"][u"nic"] not in tst_data[u"tags"]:
continue
tst_name_mod = _tpc_modify_test_name(tst_name)
- if u"across topologies" in table[u"title"].lower():
+ if (u"across topologies" in table[u"title"].lower() or
+ (u" 3n-" in table[u"title"].lower() and
+ u" 2n-" in table[u"title"].lower())):
tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
if tbl_dict.get(tst_name_mod, None) is None:
name = f"{u'-'.join(tst_data[u'name'].split(u'-')[:-1])}"
if table[u"reference"][u"nic"] not in tst_data[u"tags"]:
continue
tst_name_mod = _tpc_modify_test_name(tst_name)
- if u"across topologies" in table[u"title"].lower():
+ if (u"across topologies" in table[u"title"].lower() or
+ (u" 3n-" in table[u"title"].lower() and
+ u" 2n-" in table[u"title"].lower())):
tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
if tbl_dict.get(tst_name_mod, None) is None:
name = \
if table[u"compare"][u"nic"] not in tst_data[u"tags"]:
continue
tst_name_mod = _tpc_modify_test_name(tst_name)
- if u"across topologies" in table[u"title"].lower():
+ if (u"across topologies" in table[u"title"].lower() or
+ (u" 3n-" in table[u"title"].lower() and
+ u" 2n-" in table[u"title"].lower())):
tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
if tbl_dict.get(tst_name_mod, None) is None:
name = f"{u'-'.join(tst_data[u'name'].split(u'-')[:-1])}"
if table[u"compare"][u"nic"] not in tst_data[u"tags"]:
continue
tst_name_mod = _tpc_modify_test_name(tst_name)
- if u"across topologies" in table[u"title"].lower():
+ if (u"across topologies" in table[u"title"].lower() or
+ (u" 3n-" in table[u"title"].lower() and
+ u" 2n-" in table[u"title"].lower())):
tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
if tbl_dict.get(tst_name_mod, None) is None:
name = \
if item[u"nic"] not in tst_data[u"tags"]:
continue
tst_name_mod = _tpc_modify_test_name(tst_name)
- if u"across topologies" in table[u"title"].lower():
+ if (u"across topologies" in table[u"title"].lower() or
+ (u" 3n-" in table[u"title"].lower() and
+ u" 2n-" in table[u"title"].lower())):
tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
if tbl_dict.get(tst_name_mod, None) is None:
continue
item.extend([u"Not tested", u"Not tested"])
else:
item.extend([u"Not tested", u"Not tested"])
- data_t = tbl_dict[tst_name][u"ref-data"]
- if data_t:
- item.append(round(mean(data_t) / 1000000, 2))
- item.append(round(stdev(data_t) / 1000000, 2))
+ data_r = tbl_dict[tst_name][u"ref-data"]
+ if data_r:
+ data_r_mean = mean(data_r)
+ item.append(round(data_r_mean / 1000000, 2))
+ data_r_stdev = stdev(data_r)
+ item.append(round(data_r_stdev / 1000000, 2))
else:
+ data_r_mean = None
+ data_r_stdev = None
item.extend([u"Not tested", u"Not tested"])
- data_t = tbl_dict[tst_name][u"cmp-data"]
- if data_t:
- item.append(round(mean(data_t) / 1000000, 2))
- item.append(round(stdev(data_t) / 1000000, 2))
+ data_c = tbl_dict[tst_name][u"cmp-data"]
+ if data_c:
+ data_c_mean = mean(data_c)
+ item.append(round(data_c_mean / 1000000, 2))
+ data_c_stdev = stdev(data_c)
+ item.append(round(data_c_stdev / 1000000, 2))
else:
+ data_c_mean = None
+ data_c_stdev = None
item.extend([u"Not tested", u"Not tested"])
if item[-2] == u"Not tested":
pass
elif item[-4] == u"Not tested":
item.append(u"New in CSIT-2001")
+ item.append(u"New in CSIT-2001")
# elif topo == u"2n-skx" and u"dot1q" in tbl_dict[tst_name][u"name"]:
# item.append(u"See footnote [1]")
# footnote = True
- elif item[-4] != 0:
- item.append(int(relative_change(float(item[-4]), float(item[-2]))))
- if (len(item) == len(header)) and (item[-3] != u"Not tested"):
+ elif data_r_mean and data_c_mean:
+ delta, d_stdev = relative_change_stdev(
+ data_r_mean, data_c_mean, data_r_stdev, data_c_stdev
+ )
+ item.append(round(delta))
+ item.append(round(d_stdev))
+ if (len(item) == len(header)) and (item[-4] != u"Not tested"):
tbl_lst.append(item)
tbl_lst = _tpc_sort_table(tbl_lst)
f"{table[u'reference'][u'title']} Stdev [Mpps]",
f"{table[u'compare'][u'title']} {hdr_param} [Mpps]",
f"{table[u'compare'][u'title']} Stdev [Mpps]",
- u"Delta [%]"
+ u"Delta [%]",
+ u"Stdev of delta [%]"
]
)
u"cmp-data": list()
}
try:
- result = None
if table[u"include-tests"] == u"MRR":
result = tst_data[u"result"][u"receive-rate"]
elif table[u"include-tests"] == u"PDR":
tbl_lst = list()
for tst_name in tbl_dict:
item = [tbl_dict[tst_name][u"name"], ]
- data_t = tbl_dict[tst_name][u"ref-data"]
- if data_t:
- item.append(round(mean(data_t) / 1000000, 2))
- item.append(round(stdev(data_t) / 1000000, 2))
+ data_r = tbl_dict[tst_name][u"ref-data"]
+ if data_r:
+ data_r_mean = mean(data_r)
+ item.append(round(data_r_mean / 1000000, 2))
+ data_r_stdev = stdev(data_r)
+ item.append(round(data_r_stdev / 1000000, 2))
else:
+ data_r_mean = None
+ data_r_stdev = None
item.extend([None, None])
- data_t = tbl_dict[tst_name][u"cmp-data"]
- if data_t:
- item.append(round(mean(data_t) / 1000000, 2))
- item.append(round(stdev(data_t) / 1000000, 2))
+ data_c = tbl_dict[tst_name][u"cmp-data"]
+ if data_c:
+ data_c_mean = mean(data_c)
+ item.append(round(data_c_mean / 1000000, 2))
+ data_c_stdev = stdev(data_c)
+ item.append(round(data_c_stdev / 1000000, 2))
else:
+ data_c_mean = None
+ data_c_stdev = None
item.extend([None, None])
- if item[-4] is not None and item[-2] is not None and item[-4] != 0:
- item.append(int(relative_change(float(item[-4]), float(item[-2]))))
- if len(item) == len(header):
+ if data_r_mean and data_c_mean:
+ delta, d_stdev = relative_change_stdev(
+ data_r_mean, data_c_mean, data_r_stdev, data_c_stdev
+ )
+ item.append(round(delta))
+ item.append(round(d_stdev))
tbl_lst.append(item)
# Sort the table according to the relative change
f"{table[u'reference'][u'title']} Stdev [Mpps]",
f"{table[u'compare'][u'title']} Thput [Mpps]",
f"{table[u'compare'][u'title']} Stdev [Mpps]",
- u"Delta [%]", u"Stdev of delta [%]"
+ u"Delta [%]",
+ u"Stdev of delta [%]"
]
header_str = u",".join(header) + u"\n"
except (AttributeError, KeyError) as err:
if data_r_mean and data_c_mean:
delta, d_stdev = relative_change_stdev(
data_r_mean, data_c_mean, data_r_stdev, data_c_stdev)
- item.append(round(delta, 2))
- item.append(round(d_stdev, 2))
+ item.append(round(delta))
+ item.append(round(d_stdev))
tbl_lst.append(item)
# Sort the table according to the relative change
elif u"dnv" in testbed or u"tsh" in testbed:
driver = u"ixgbe"
else:
- driver = u"i40e"
+ driver = u"dpdk"
if u"acl" in test_name or \
u"macip" in test_name or \