path = u"_tmp/src/vpp_performance_tests/comparisons/"
else:
path = u"_tmp/src/dpdk_performance_tests/comparisons/"
+ logging.info(f" Writing the HTML file to {path}{file_name}.rst")
with open(f"{path}{file_name}.rst", u"wt") as rst_file:
rst_file.write(
u"\n"
f'src="../..{out_file_name.replace(u"_build", u"")}_in.html">'
f'</iframe>\n\n'
)
+
if legend:
- rst_file.write(legend[1:].replace(u"\n", u" |br| "))
+ try:
+ itm_lst = legend[1:-2].split(u"\n")
+ rst_file.write(
+ f"{itm_lst[0]}\n\n- " + u'\n- '.join(itm_lst[1:]) + u"\n\n"
+ )
+ except IndexError as err:
+ logging.error(f"Legend cannot be written to html file\n{err}")
if footnote:
- rst_file.write(footnote.replace(u"\n", u" |br| ")[1:])
+ try:
+ itm_lst = footnote[1:].split(u"\n")
+ rst_file.write(
+ f"{itm_lst[0]}\n\n- " + u'\n- '.join(itm_lst[1:]) + u"\n\n"
+ )
+ except IndexError as err:
+ logging.error(f"Footnote cannot be written to html file\n{err}")
def table_soak_vs_ndr(table, input_data):
f"Percentage change calculated for mean values.\n"
u"Stdev(Diff): "
u"Standard deviation of percentage change calculated for mean "
- u"values.\n"
- u":END"
+ u"values."
)
except (AttributeError, KeyError) as err:
logging.error(f"The model is invalid, missing parameter: {repr(err)}")
tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
# Generate csv tables:
- csv_file = f"{table[u'output-file']}.csv"
- with open(csv_file, u"wt") as file_handler:
+ csv_file_name = f"{table[u'output-file']}.csv"
+ with open(csv_file_name, u"wt") as file_handler:
file_handler.write(header_str)
for test in tbl_lst:
file_handler.write(u";".join([str(item) for item in test]) + u"\n")
convert_csv_to_pretty_txt(
- csv_file, f"{table[u'output-file']}.txt", delimiter=u";"
+ csv_file_name, f"{table[u'output-file']}.txt", delimiter=u";"
)
- with open(f"{table[u'output-file']}.txt", u'a') as txt_file:
- txt_file.write(legend)
+ with open(f"{table[u'output-file']}.txt", u'a') as file_handler:
+ file_handler.write(legend)
# Generate html table:
_tpc_generate_html_table(
]
header_str = u",".join(header) + u"\n"
+ incl_tests = table.get(u"include-tests", u"MRR")
+
# Prepare data to the table:
tbl_dict = dict()
for job, builds in table[u"data"].items():
u"data": OrderedDict()
}
try:
- tbl_dict[tst_name][u"data"][str(build)] = \
- tst_data[u"result"][u"receive-rate"]
+ if incl_tests == u"MRR":
+ tbl_dict[tst_name][u"data"][str(build)] = \
+ tst_data[u"result"][u"receive-rate"]
+ elif incl_tests == u"NDR":
+ tbl_dict[tst_name][u"data"][str(build)] = \
+ tst_data[u"throughput"][u"NDR"][u"LOWER"]
+ elif incl_tests == u"PDR":
+ tbl_dict[tst_name][u"data"][str(build)] = \
+ tst_data[u"throughput"][u"PDR"][u"LOWER"]
except (TypeError, KeyError):
pass # No data in output.xml for this test
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"])
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])
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",
u"stdev": tst_data[u"stdev"]
}
+ if not tbl_dict:
+ logging.warning(f"No data for table {table.get(u'title', u'')}!")
+ return
+
tbl_lst = list()
for tst_data in tbl_dict.values():
row = [tst_data[u"name"], ]
if comparisons:
for row in tbl_lst:
new_row = deepcopy(row)
- add_to_tbl = False
for comp in comparisons:
ref_itm = row[int(comp[u"reference"])]
if ref_itm is None and \
ref_itm[u"mean"], cmp_itm[u"mean"],
ref_itm[u"stdev"], cmp_itm[u"stdev"]
)
- new_row.append(
- {
+ if delta is None:
+ break
+ else:
+ new_row.append({
u"mean": delta * 1e6,
u"stdev": d_stdev * 1e6
- }
- )
- add_to_tbl = True
+ })
else:
- new_row.append(None)
- if add_to_tbl:
+ break
+ else:
tbl_cmp_lst.append(new_row)
- tbl_cmp_lst.sort(key=lambda rel: rel[0], reverse=False)
- tbl_cmp_lst.sort(key=lambda rel: rel[-1][u'mean'], reverse=True)
+ try:
+ tbl_cmp_lst.sort(key=lambda rel: rel[0], reverse=False)
+ tbl_cmp_lst.sort(key=lambda rel: rel[-1][u'mean'], reverse=True)
+ except TypeError as err:
+ logging.warning(f"Empty data element in table\n{tbl_cmp_lst}\n{err}")
rcas = list()
rca_in = table.get(u"rca", None)
for line in tbl_cmp_lst:
row = [line[0], ]
for idx, itm in enumerate(line[1:]):
- if itm is None:
+ if itm is None or not isinstance(itm, dict) or\
+ itm.get(u'mean', None) is None or \
+ itm.get(u'stdev', None) is None:
row.append(u"NT")
row.append(u"NT")
else:
legend = u"\n" + u"\n".join(legend_lst) + u"\n"
footnote = u""
- for rca in rcas:
- footnote += f"\n{rca[u'title']}:\n"
- footnote += rca[u"data"].get(u"footnote", u"")
+ if rcas:
+ footnote += u"\nRCA:\n"
+ for rca in rcas:
+ footnote += rca[u"data"].get(u"footnote", u"")
- csv_file = f"{table[u'output-file']}-csv.csv"
- with open(csv_file, u"wt", encoding='utf-8') as file_handler:
+ csv_file_name = f"{table[u'output-file']}-csv.csv"
+ with open(csv_file_name, u"wt", encoding='utf-8') as file_handler:
file_handler.write(
u",".join([f'"{itm}"' for itm in header_csv]) + u"\n"
)
for line in tbl_cmp_lst:
row = [line[0], ]
for idx, itm in enumerate(line[1:]):
- if itm is None:
+ if itm is None or not isinstance(itm, dict) or \
+ itm.get(u'mean', None) is None or \
+ itm.get(u'stdev', None) is None:
new_itm = u"NT"
else:
if idx < len(cols):
header.extend([rca[u"title"] for rca in rcas])
# Generate csv tables:
- csv_file = f"{table[u'output-file']}.csv"
- with open(csv_file, u"wt", encoding='utf-8') as file_handler:
+ csv_file_name = f"{table[u'output-file']}.csv"
+ logging.info(f" Writing the file {csv_file_name}")
+ with open(csv_file_name, u"wt", encoding='utf-8') as file_handler:
file_handler.write(u";".join(header) + u"\n")
for test in tbl_final:
file_handler.write(u";".join([str(item) for item in test]) + u"\n")
# Generate txt table:
txt_file_name = f"{table[u'output-file']}.txt"
- convert_csv_to_pretty_txt(csv_file, txt_file_name, delimiter=u";")
+ logging.info(f" Writing the file {txt_file_name}")
+ convert_csv_to_pretty_txt(csv_file_name, txt_file_name, delimiter=u";")
- with open(txt_file_name, u'a', encoding='utf-8') as txt_file:
- txt_file.write(legend)
- txt_file.write(footnote)
- if legend or footnote:
- txt_file.write(u"\n:END")
+ with open(txt_file_name, u'a', encoding='utf-8') as file_handler:
+ file_handler.write(legend)
+ file_handler.write(footnote)
# Generate html table:
_tpc_generate_html_table(
)
header = [
- [u"Version"],
- [u"Date", ],
- [u"Build", ],
- [u"Testbed", ]
+ [u"VPP Version", ],
+ [u"Start Timestamp", ],
+ [u"CSIT Build", ],
+ [u"CSIT Testbed", ]
]
tbl_dict = dict()
idx = 0
idx_cmp = cmp.get(u"compare", None)
if idx_ref is None or idx_cmp is None:
continue
- header[0].append(f"Diff{idx + 1}")
- header[1].append(header[0][idx_ref - idx - 1])
- header[2].append(u"vs")
- header[3].append(header[0][idx_cmp - idx - 1])
+ header[0].append(
+ f"Diff({header[0][idx_ref - idx].split(u'~')[-1]} vs "
+ f"{header[0][idx_cmp - idx].split(u'~')[-1]})"
+ )
+ header[1].append(u"")
+ header[2].append(u"")
+ header[3].append(u"")
for tst_name, tst_data in tbl_dict.items():
if not cmp_dict.get(tst_name, None):
cmp_dict[tst_name] = list()
tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
# Generate csv table:
- csv_file = f"{table[u'output-file']}.csv"
- with open(csv_file, u"wt", encoding='utf-8') as file_handler:
+ csv_file_name = f"{table[u'output-file']}.csv"
+ logging.info(f" Writing the file {csv_file_name}")
+ with open(csv_file_name, u"wt", encoding='utf-8') as file_handler:
for hdr in header:
file_handler.write(u",".join(hdr) + u"\n")
for test in tbl_lst:
]
) + u"\n")
- txt_file = f"{table[u'output-file']}.txt"
- convert_csv_to_pretty_txt(csv_file, txt_file, delimiter=u",")
+ txt_file_name = f"{table[u'output-file']}.txt"
+ logging.info(f" Writing the file {txt_file_name}")
+ convert_csv_to_pretty_txt(csv_file_name, txt_file_name, delimiter=u",")
# Reorganize header in txt table
txt_table = list()
- with open(txt_file, u"rt", encoding='utf-8') as file_handler:
+ with open(txt_file_name, u"rt", encoding='utf-8') as file_handler:
for line in file_handler:
txt_table.append(line)
try:
txt_table.insert(5, txt_table.pop(2))
- with open(txt_file, u"wt", encoding='utf-8') as file_handler:
+ with open(txt_file_name, u"wt", encoding='utf-8') as file_handler:
file_handler.writelines(txt_table)
except IndexError:
pass
Code Review / csit.git / blobdiff