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
u"Average Vector Size"
)
- for dut_data in tst_data[u"show-run"].values:
+ for dut_data in tst_data[u"show-run"].values():
trow = ET.SubElement(
tbl, u"tr", attrib=dict(bgcolor=colors[u"header"])
)
if not html_table:
continue
try:
- file_name = f"{table[u'output-file']}_{suite[u'name']}.rst"
+ 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")
"""
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"{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"):
+ (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}"')
# Write the data to file
if table_lst:
- file_name = f"{table[u'output-file']}_{suite_name}.csv"
+ 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()
# 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)
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"
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 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]))))
+ 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, 2))
+ item.append(round(d_stdev, 2))
if (len(item) == len(header)) and (item[-3] != u"Not tested"):
tbl_lst.append(item)
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"
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 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]))))
+ 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, 2))
+ item.append(round(d_stdev, 2))
if (len(item) == len(header)) and (item[-3] != u"Not tested"):
tbl_lst.append(item)
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, 2))
+ item.append(round(d_stdev, 2))
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: