-# Copyright (c) 2019 Cisco and/or its affiliates.
+# Copyright (c) 2021 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 xml.etree import ElementTree as ET
from datetime import datetime as dt
from datetime import timedelta
+from copy import deepcopy
+from json import loads
import plotly.graph_objects as go
import plotly.offline as ploff
import pandas as pd
from numpy import nan, isnan
+from yaml import load, FullLoader, YAMLError
-from pal_utils import mean, stdev, relative_change, classify_anomalies, \
- convert_csv_to_pretty_txt, relative_change_stdev
+from pal_utils import mean, stdev, classify_anomalies, \
+ convert_csv_to_pretty_txt, relative_change_stdev, relative_change
-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_nics_comparison": table_nics_comparison,
u"table_soak_vs_ndr": table_soak_vs_ndr,
u"table_perf_trending_dash": table_perf_trending_dash,
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,
+ u"table_comparison": table_comparison,
+ u"table_weekly_comparison": table_weekly_comparison
}
logging.info(u"Generating the tables ...")
for table in spec.tables:
try:
+ if table[u"algorithm"] == u"table_weekly_comparison":
+ table[u"testbeds"] = spec.environment.get(u"testbeds", None)
generator[table[u"algorithm"]](table, data)
except NameError as err:
logging.error(
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"telemetry-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"telemetry-show-run", None) is None or \
+ isinstance(tst_data[u"telemetry-show-run"], str):
+ 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"telemetry-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"runtime", 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']}"
+ runtime = dict()
+ for item in dut_data[u"runtime"].get(u"data", tuple()):
+ tid = int(item[u"labels"][u"thread_id"])
+ if runtime.get(tid, None) is None:
+ runtime[tid] = dict()
+ gnode = item[u"labels"][u"graph_node"]
+ if runtime[tid].get(gnode, None) is None:
+ runtime[tid][gnode] = dict()
+ try:
+ runtime[tid][gnode][item[u"name"]] = float(item[u"value"])
+ except ValueError:
+ runtime[tid][gnode][item[u"name"]] = item[u"value"]
+
+ threads = dict({idx: list() for idx in range(len(runtime))})
+ for idx, run_data in runtime.items():
+ for gnode, gdata in run_data.items():
+ if gdata[u"vectors"] > 0:
+ clocks = gdata[u"clocks"] / gdata[u"vectors"]
+ elif gdata[u"calls"] > 0:
+ clocks = gdata[u"clocks"] / gdata[u"calls"]
+ elif gdata[u"suspends"] > 0:
+ clocks = gdata[u"clocks"] / gdata[u"suspends"]
+ else:
+ clocks = 0.0
+ if gdata[u"calls"] > 0:
+ vectors_call = gdata[u"vectors"] / gdata[u"calls"]
+ else:
+ vectors_call = 0.0
+ if int(gdata[u"calls"]) + int(gdata[u"vectors"]) + \
+ int(gdata[u"suspends"]):
+ threads[idx].append([
+ gnode,
+ int(gdata[u"calls"]),
+ int(gdata[u"vectors"]),
+ int(gdata[u"suspends"]),
+ clocks,
+ vectors_call
+ ])
+
+ 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 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)
suite_name = suite[u"name"]
table_lst = list()
for test in data.keys():
- if data[test][u"parent"] not in suite_name:
+ if data[test][u"status"] != u"PASS" or \
+ data[test][u"parent"] not in suite_name:
continue
row_lst = list()
for column in table[u"columns"]:
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"):
- col_data = col_data.replace(u" |br| ", u"", 1)
+ 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"\n", 1)[1]
+ except IndexError:
+ pass
+ col_data = col_data.replace(u'\n', u' |br| ').\
+ replace(u'\r', u'').replace(u'"', u"'")
+ col_data = f" |prein| {col_data} |preout| "
+ elif column[u"data"].split(u" ")[1] in (u"conf-history", ):
+ col_data = col_data.replace(u'\n', u' |br| ')
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")
logging.info(u" Done.")
-def _tpc_modify_test_name(test_name):
+def _tpc_modify_test_name(test_name, ignore_nic=False):
"""Modify a test name by replacing its parts.
:param test_name: Test name to be modified.
+ :param ignore_nic: If True, NIC is removed from TC name.
:type test_name: str
+ :type ignore_nic: bool
:returns: Modified test name.
:rtype: str
"""
test_name_mod = test_name.\
- replace(u"-ndrpdrdisc", u""). \
replace(u"-ndrpdr", u"").\
- replace(u"-pdrdisc", u""). \
- replace(u"-ndrdisc", u"").\
- replace(u"-pdr", u""). \
- replace(u"-ndr", u""). \
replace(u"1t1c", u"1c").\
replace(u"2t1c", u"1c"). \
replace(u"2t2c", u"2c").\
replace(u"4t4c", u"4c").\
replace(u"8t4c", u"4c")
- return re.sub(REGEX_NIC, u"", test_name_mod)
+ if ignore_nic:
+ return re.sub(REGEX_NIC, u"", test_name_mod)
+ return test_name_mod
def _tpc_modify_displayed_test_name(test_name):
"""Insert src data to the target structure.
:param target: Target structure where the data is placed.
- :param src: Source data to be placed into the target stucture.
+ :param src: Source data to be placed into the target structure.
:param include_tests: Which results will be included (MRR, NDR, PDR).
:type target: list
:type src: dict
"""
try:
if include_tests == u"MRR":
- target.append(src[u"result"][u"receive-rate"])
+ target[u"mean"] = src[u"result"][u"receive-rate"]
+ target[u"stdev"] = src[u"result"][u"receive-stdev"]
elif include_tests == u"PDR":
- target.append(src[u"throughput"][u"PDR"][u"LOWER"])
+ target[u"data"].append(src[u"throughput"][u"PDR"][u"LOWER"])
elif include_tests == u"NDR":
- target.append(src[u"throughput"][u"NDR"][u"LOWER"])
+ target[u"data"].append(src[u"throughput"][u"NDR"][u"LOWER"])
except (KeyError, TypeError):
pass
-def _tpc_sort_table(table):
- """Sort the table this way:
-
- 1. Put "New in CSIT-XXXX" at the first place.
- 2. Put "See footnote" at the second place.
- 3. Sort the rest by "Delta".
-
- :param table: Table to sort.
- :type table: list
- :returns: Sorted table.
- :rtype: list
- """
-
-
- tbl_new = list()
- tbl_see = list()
- tbl_delta = list()
- for item in table:
- if isinstance(item[-1], str):
- if u"New in CSIT" in item[-1]:
- tbl_new.append(item)
- elif u"See footnote" in item[-1]:
- tbl_see.append(item)
- else:
- tbl_delta.append(item)
-
- # 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)
-
- # Put the tables together:
- table = list()
- table.extend(tbl_new)
- table.extend(tbl_see)
- table.extend(tbl_delta)
-
- return table
-
-
-def _tpc_generate_html_table(header, data, output_file_name):
+def _tpc_generate_html_table(header, data, out_file_name, legend=u"",
+ footnote=u"", sort_data=True, title=u"",
+ generate_rst=True):
"""Generate html table from input data with simple sorting possibility.
:param header: Table header.
:param data: Input data to be included in the table. It is a list of lists.
Inner lists are rows in the table. All inner lists must be of the same
length. The length of these lists must be the same as the length of the
- header.
- :param output_file_name: The name (relative or full path) where the
- generated html table is written.
- :type header: list
- :type data: list of lists
- :type output_file_name: str
- """
-
- df_data = pd.DataFrame(data, columns=header)
-
- df_sorted = [df_data.sort_values(
- by=[key, header[0]], ascending=[True, True]
- if key != header[0] else [False, True]) for key in header]
- df_sorted_rev = [df_data.sort_values(
- by=[key, header[0]], ascending=[False, True]
- if key != header[0] else [True, True]) for key in header]
- df_sorted.extend(df_sorted_rev)
-
- fill_color = [[u"#d4e4f7" if idx % 2 else u"#e9f1fb"
- for idx in range(len(df_data))]]
- table_header = dict(
- values=[f"<b>{item}</b>" for item in header],
- fill_color=u"#7eade7",
- align=[u"left", u"center"]
- )
-
- fig = go.Figure()
-
- for table in df_sorted:
- columns = [table.get(col) for col in header]
- fig.add_trace(
- go.Table(
- columnwidth=[30, 10],
- header=table_header,
- cells=dict(
- values=columns,
- fill_color=fill_color,
- align=[u"left", u"right"]
- )
- )
- )
-
- buttons = list()
- menu_items = [f"<b>{itm}</b> (ascending)" for itm in header]
- menu_items_rev = [f"<b>{itm}</b> (descending)" for itm in header]
- menu_items.extend(menu_items_rev)
- for idx, hdr in enumerate(menu_items):
- visible = [False, ] * len(menu_items)
- visible[idx] = True
- buttons.append(
- dict(
- label=hdr.replace(u" [Mpps]", u""),
- method=u"update",
- args=[{u"visible": visible}],
- )
- )
-
- fig.update_layout(
- updatemenus=[
- go.layout.Updatemenu(
- type=u"dropdown",
- direction=u"down",
- x=0.03,
- xanchor=u"left",
- y=1.045,
- yanchor=u"top",
- active=len(menu_items) - 1,
- buttons=list(buttons)
- )
- ],
- annotations=[
- go.layout.Annotation(
- text=u"<b>Sort by:</b>",
- x=0,
- xref=u"paper",
- y=1.035,
- yref=u"paper",
- align=u"left",
- showarrow=False
- )
- ]
- )
-
- ploff.plot(fig, show_link=False, auto_open=False, filename=output_file_name)
-
-
-def table_perf_comparison(table, input_data):
- """Generate the table(s) with algorithm: table_perf_comparison
- specified in the specification file.
-
- :param table: Table to generate.
- :param input_data: Data to process.
- :type table: pandas.Series
- :type input_data: InputData
- """
-
- 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, continue_on_error=True)
-
- # Prepare the header of the tables
- try:
- header = [u"Test case", ]
-
- if table[u"include-tests"] == u"MRR":
- hdr_param = u"Rec Rate"
- else:
- hdr_param = u"Thput"
-
- history = table.get(u"history", list())
- for item in history:
- header.extend(
- [
- f"{item[u'title']} {hdr_param} [Mpps]",
- f"{item[u'title']} Stdev [Mpps]"
- ]
- )
- header.extend(
- [
- f"{table[u'reference'][u'title']} {hdr_param} [Mpps]",
- 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 [%]"
- ]
- )
- header_str = u",".join(header) + u"\n"
- except (AttributeError, KeyError) as err:
- logging.error(f"The model is invalid, missing parameter: {repr(err)}")
- return
-
- # Prepare data to the table:
- tbl_dict = dict()
- # topo = ""
- for job, builds in table[u"reference"][u"data"].items():
- # topo = u"2n-skx" if u"2n-skx" in job else u""
- 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():
- 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"])
- nic = groups.group(0) if groups else u""
- name = \
- f"{nic}-{u'-'.join(tst_data[u'name'].split(u'-')[:-1])}"
- if u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- _tpc_insert_data(target=tbl_dict[tst_name_mod][u"ref-data"],
- src=tst_data,
- include_tests=table[u"include-tests"])
-
- replacement = table[u"reference"].get(u"data-replacement", None)
- if replacement:
- create_new_list = True
- rpl_data = input_data.filter_data(
- table, data=replacement, continue_on_error=True)
- for job, builds in replacement.items():
- 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():
- 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 u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- if create_new_list:
- create_new_list = False
- tbl_dict[tst_name_mod][u"ref-data"] = list()
-
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"ref-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- for job, builds in table[u"compare"][u"data"].items():
- 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():
- 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"])
- nic = groups.group(0) if groups else u""
- name = \
- f"{nic}-{u'-'.join(tst_data[u'name'].split(u'-')[:-1])}"
- if u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"cmp-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- replacement = table[u"compare"].get(u"data-replacement", None)
- if replacement:
- create_new_list = True
- rpl_data = input_data.filter_data(
- table, data=replacement, continue_on_error=True)
- for job, builds in replacement.items():
- 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():
- 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 u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- if create_new_list:
- create_new_list = False
- tbl_dict[tst_name_mod][u"cmp-data"] = list()
-
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"cmp-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- for item in history:
- for job, builds in item[u"data"].items():
- 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():
- tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
- if tbl_dict.get(tst_name_mod, None) is None:
- continue
- if tbl_dict[tst_name_mod].get(u"history", None) is None:
- tbl_dict[tst_name_mod][u"history"] = OrderedDict()
- if tbl_dict[tst_name_mod][u"history"].\
- get(item[u"title"], None) is None:
- tbl_dict[tst_name_mod][u"history"][item[
- u"title"]] = list()
- try:
- if table[u"include-tests"] == u"MRR":
- res = tst_data[u"result"][u"receive-rate"]
- elif table[u"include-tests"] == u"PDR":
- res = tst_data[u"throughput"][u"PDR"][u"LOWER"]
- elif table[u"include-tests"] == u"NDR":
- res = tst_data[u"throughput"][u"NDR"][u"LOWER"]
- else:
- continue
- tbl_dict[tst_name_mod][u"history"][item[u"title"]].\
- append(res)
- except (TypeError, KeyError):
- pass
-
- tbl_lst = list()
- footnote = False
- for tst_name in tbl_dict:
- item = [tbl_dict[tst_name][u"name"], ]
- if history:
- if tbl_dict[tst_name].get(u"history", None) is not None:
- for hist_data in tbl_dict[tst_name][u"history"].values():
- if hist_data:
- item.append(round(mean(hist_data) / 1000000, 2))
- item.append(round(stdev(hist_data) / 1000000, 2))
- else:
- 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))
- else:
- 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))
- else:
- 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")
- # 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"):
- tbl_lst.append(item)
-
- tbl_lst = _tpc_sort_table(tbl_lst)
-
- # Generate csv tables:
- csv_file = f"{table[u'output-file']}.csv"
- with open(csv_file, 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")
-
- txt_file_name = f"{table[u'output-file']}.txt"
- convert_csv_to_pretty_txt(csv_file, txt_file_name)
-
- if footnote:
- with open(txt_file_name, u'a') as txt_file:
- txt_file.writelines([
- u"\nFootnotes:\n",
- u"[1] CSIT-1908 changed test methodology of dot1q tests in "
- u"2-node testbeds, dot1q encapsulation is now used on both "
- u"links of SUT.\n",
- u" Previously dot1q was used only on a single link with the "
- u"other link carrying untagged Ethernet frames. This changes "
- u"results\n",
- u" in slightly lower throughput in CSIT-1908 for these "
- u"tests. See release notes."
- ])
-
- # Generate html table:
- _tpc_generate_html_table(header, tbl_lst, f"{table[u'output-file']}.html")
-
-
-def table_perf_comparison_nic(table, input_data):
- """Generate the table(s) with algorithm: table_perf_comparison
- specified in the specification file.
-
- :param table: Table to generate.
- :param input_data: Data to process.
- :type table: pandas.Series
- :type input_data: InputData
- """
-
- 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, continue_on_error=True)
-
- # Prepare the header of the tables
- try:
- header = [u"Test case", ]
-
- if table[u"include-tests"] == u"MRR":
- hdr_param = u"Rec Rate"
- else:
- hdr_param = u"Thput"
-
- history = table.get(u"history", list())
- for item in history:
- header.extend(
- [
- f"{item[u'title']} {hdr_param} [Mpps]",
- f"{item[u'title']} Stdev [Mpps]"
- ]
- )
- header.extend(
- [
- f"{table[u'reference'][u'title']} {hdr_param} [Mpps]",
- 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 [%]"
- ]
- )
- header_str = u",".join(header) + u"\n"
- except (AttributeError, KeyError) as err:
- logging.error(f"The model is invalid, missing parameter: {repr(err)}")
- return
-
- # Prepare data to the table:
- tbl_dict = dict()
- # topo = u""
- for job, builds in table[u"reference"][u"data"].items():
- # topo = u"2n-skx" if u"2n-skx" in job else u""
- for build in builds:
- for tst_name, tst_data in data[job][str(build)].items():
- 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():
- 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 u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"ref-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- replacement = table[u"reference"].get(u"data-replacement", None)
- if replacement:
- create_new_list = True
- rpl_data = input_data.filter_data(
- table, data=replacement, continue_on_error=True)
- for job, builds in replacement.items():
- for build in builds:
- for tst_name, tst_data in rpl_data[job][str(build)].items():
- 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():
- 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 u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- if create_new_list:
- create_new_list = False
- tbl_dict[tst_name_mod][u"ref-data"] = list()
-
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"ref-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- for job, builds in table[u"compare"][u"data"].items():
- for build in builds:
- for tst_name, tst_data in data[job][str(build)].items():
- 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():
- 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 u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"cmp-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- replacement = table[u"compare"].get(u"data-replacement", None)
- if replacement:
- create_new_list = True
- rpl_data = input_data.filter_data(
- table, data=replacement, continue_on_error=True)
- for job, builds in replacement.items():
- for build in builds:
- for tst_name, tst_data in rpl_data[job][str(build)].items():
- 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():
- 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 u"across testbeds" in table[u"title"].lower() or \
- u"across topologies" in table[u"title"].lower():
- name = _tpc_modify_displayed_test_name(name)
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"ref-data": list(),
- u"cmp-data": list()
- }
- if create_new_list:
- create_new_list = False
- tbl_dict[tst_name_mod][u"cmp-data"] = list()
-
- _tpc_insert_data(
- target=tbl_dict[tst_name_mod][u"cmp-data"],
- src=tst_data,
- include_tests=table[u"include-tests"]
- )
-
- for item in history:
- for job, builds in item[u"data"].items():
- for build in builds:
- for tst_name, tst_data in data[job][str(build)].items():
- 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():
- tst_name_mod = tst_name_mod.replace(u"2n1l-", u"")
- if tbl_dict.get(tst_name_mod, None) is None:
- continue
- if tbl_dict[tst_name_mod].get(u"history", None) is None:
- tbl_dict[tst_name_mod][u"history"] = OrderedDict()
- if tbl_dict[tst_name_mod][u"history"].\
- get(item[u"title"], None) is None:
- tbl_dict[tst_name_mod][u"history"][item[
- u"title"]] = list()
- try:
- if table[u"include-tests"] == u"MRR":
- res = tst_data[u"result"][u"receive-rate"]
- elif table[u"include-tests"] == u"PDR":
- res = tst_data[u"throughput"][u"PDR"][u"LOWER"]
- elif table[u"include-tests"] == u"NDR":
- res = tst_data[u"throughput"][u"NDR"][u"LOWER"]
- else:
- continue
- tbl_dict[tst_name_mod][u"history"][item[u"title"]].\
- append(res)
- except (TypeError, KeyError):
- pass
-
- tbl_lst = list()
- footnote = False
- for tst_name in tbl_dict:
- item = [tbl_dict[tst_name][u"name"], ]
- if history:
- if tbl_dict[tst_name].get(u"history", None) is not None:
- for hist_data in tbl_dict[tst_name][u"history"].values():
- if hist_data:
- item.append(round(mean(hist_data) / 1000000, 2))
- item.append(round(stdev(hist_data) / 1000000, 2))
- else:
- 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))
- else:
- 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))
- else:
- 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")
- # 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"):
- tbl_lst.append(item)
-
- tbl_lst = _tpc_sort_table(tbl_lst)
-
- # Generate csv tables:
- csv_file = f"{table[u'output-file']}.csv"
- with open(csv_file, 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")
-
- txt_file_name = f"{table[u'output-file']}.txt"
- convert_csv_to_pretty_txt(csv_file, txt_file_name)
-
- if footnote:
- with open(txt_file_name, u'a') as txt_file:
- txt_file.writelines([
- u"\nFootnotes:\n",
- u"[1] CSIT-1908 changed test methodology of dot1q tests in "
- u"2-node testbeds, dot1q encapsulation is now used on both "
- u"links of SUT.\n",
- u" Previously dot1q was used only on a single link with the "
- u"other link carrying untagged Ethernet frames. This changes "
- u"results\n",
- u" in slightly lower throughput in CSIT-1908 for these "
- u"tests. See release notes."
- ])
-
- # Generate html table:
- _tpc_generate_html_table(header, tbl_lst, f"{table[u'output-file']}.html")
-
-
-def table_nics_comparison(table, input_data):
- """Generate the table(s) with algorithm: table_nics_comparison
- specified in the specification file.
-
- :param table: Table to generate.
- :param input_data: Data to process.
- :type table: pandas.Series
- :type input_data: InputData
- """
-
- 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, continue_on_error=True)
+ header.
+ :param out_file_name: The name (relative or full path) where the
+ generated html table is written.
+ :param legend: The legend to display below the table.
+ :param footnote: The footnote to display below the table (and legend).
+ :param sort_data: If True the data sorting is enabled.
+ :param title: The table (and file) title.
+ :param generate_rst: If True, wrapping rst file is generated.
+ :type header: list
+ :type data: list of lists
+ :type out_file_name: str
+ :type legend: str
+ :type footnote: str
+ :type sort_data: bool
+ :type title: str
+ :type generate_rst: bool
+ """
- # Prepare the header of the tables
try:
- header = [u"Test case", ]
+ idx = header.index(u"Test Case")
+ except ValueError:
+ idx = 0
+ params = {
+ u"align-hdr": (
+ [u"left", u"right"],
+ [u"left", u"left", u"right"],
+ [u"left", u"left", u"left", u"right"]
+ ),
+ u"align-itm": (
+ [u"left", u"right"],
+ [u"left", u"left", u"right"],
+ [u"left", u"left", u"left", u"right"]
+ ),
+ u"width": ([15, 9], [4, 24, 10], [4, 4, 32, 10])
+ }
- if table[u"include-tests"] == u"MRR":
- hdr_param = u"Rec Rate"
- else:
- hdr_param = u"Thput"
+ df_data = pd.DataFrame(data, columns=header)
- header.extend(
- [
- f"{table[u'reference'][u'title']} {hdr_param} [Mpps]",
- 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 [%]"
- ]
+ if sort_data:
+ df_sorted = [df_data.sort_values(
+ by=[key, header[idx]], ascending=[True, True]
+ if key != header[idx] else [False, True]) for key in header]
+ df_sorted_rev = [df_data.sort_values(
+ by=[key, header[idx]], ascending=[False, True]
+ if key != header[idx] else [True, True]) for key in header]
+ df_sorted.extend(df_sorted_rev)
+ else:
+ df_sorted = df_data
+
+ fill_color = [[u"#d4e4f7" if idx % 2 else u"#e9f1fb"
+ for idx in range(len(df_data))]]
+ table_header = dict(
+ values=[f"<b>{item.replace(u',', u',<br>')}</b>" for item in header],
+ fill_color=u"#7eade7",
+ align=params[u"align-hdr"][idx],
+ font=dict(
+ family=u"Courier New",
+ size=12
)
+ )
- except (AttributeError, KeyError) as err:
- logging.error(f"The model is invalid, missing parameter: {repr(err)}")
- return
+ fig = go.Figure()
- # Prepare data to the table:
- tbl_dict = dict()
- for job, builds in table[u"data"].items():
- 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 tbl_dict.get(tst_name_mod, None) is None:
- name = u"-".join(tst_data[u"name"].split(u"-")[:-1])
- tbl_dict[tst_name_mod] = {
- u"name": name,
- u"ref-data": list(),
- 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":
- result = tst_data[u"throughput"][u"PDR"][u"LOWER"]
- elif table[u"include-tests"] == u"NDR":
- result = tst_data[u"throughput"][u"NDR"][u"LOWER"]
- else:
- continue
+ if sort_data:
+ for table in df_sorted:
+ columns = [table.get(col) for col in header]
+ fig.add_trace(
+ go.Table(
+ columnwidth=params[u"width"][idx],
+ header=table_header,
+ cells=dict(
+ values=columns,
+ fill_color=fill_color,
+ align=params[u"align-itm"][idx],
+ font=dict(
+ family=u"Courier New",
+ size=12
+ )
+ )
+ )
+ )
- if result and \
- table[u"reference"][u"nic"] in tst_data[u"tags"]:
- tbl_dict[tst_name_mod][u"ref-data"].append(result)
- elif result and \
- table[u"compare"][u"nic"] in tst_data[u"tags"]:
- tbl_dict[tst_name_mod][u"cmp-data"].append(result)
- except (TypeError, KeyError) as err:
- logging.debug(f"No data for {tst_name}\n{repr(err)}")
- # No data in output.xml for this test
+ buttons = list()
+ menu_items = [f"<b>{itm}</b> (ascending)" for itm in header]
+ menu_items.extend([f"<b>{itm}</b> (descending)" for itm in header])
+ for idx, hdr in enumerate(menu_items):
+ visible = [False, ] * len(menu_items)
+ visible[idx] = True
+ buttons.append(
+ dict(
+ label=hdr.replace(u" [Mpps]", u""),
+ method=u"update",
+ args=[{u"visible": visible}],
+ )
+ )
- 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))
- else:
- 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))
- else:
- 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):
- tbl_lst.append(item)
+ fig.update_layout(
+ updatemenus=[
+ go.layout.Updatemenu(
+ type=u"dropdown",
+ direction=u"down",
+ x=0.0,
+ xanchor=u"left",
+ y=1.002,
+ yanchor=u"bottom",
+ active=len(menu_items) - 1,
+ buttons=list(buttons)
+ )
+ ],
+ )
+ else:
+ fig.add_trace(
+ go.Table(
+ columnwidth=params[u"width"][idx],
+ header=table_header,
+ cells=dict(
+ values=[df_sorted.get(col) for col in header],
+ fill_color=fill_color,
+ align=params[u"align-itm"][idx],
+ font=dict(
+ family=u"Courier New",
+ size=12
+ )
+ )
+ )
+ )
- # Sort the table according to the relative change
- tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
+ ploff.plot(
+ fig,
+ show_link=False,
+ auto_open=False,
+ filename=f"{out_file_name}_in.html"
+ )
- # Generate csv tables:
- with open(f"{table[u'output-file']}.csv", u"wt") as file_handler:
- file_handler.write(u",".join(header) + u"\n")
- for test in tbl_lst:
- file_handler.write(u",".join([str(item) for item in test]) + u"\n")
+ if not generate_rst:
+ return
- convert_csv_to_pretty_txt(f"{table[u'output-file']}.csv",
- f"{table[u'output-file']}.txt")
+ file_name = out_file_name.split(u"/")[-1]
+ if u"vpp" in out_file_name:
+ 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"
+ u".. |br| raw:: html\n\n <br />\n\n\n"
+ u".. |prein| raw:: html\n\n <pre>\n\n\n"
+ u".. |preout| raw:: html\n\n </pre>\n\n"
+ )
+ if title:
+ rst_file.write(f"{title}\n")
+ rst_file.write(f"{u'`' * len(title)}\n\n")
+ rst_file.write(
+ u".. raw:: html\n\n"
+ f' <iframe frameborder="0" scrolling="no" '
+ f'width="1600" height="1200" '
+ f'src="../..{out_file_name.replace(u"_build", u"")}_in.html">'
+ f'</iframe>\n\n'
+ )
- # Generate html table:
- _tpc_generate_html_table(header, tbl_lst, f"{table[u'output-file']}.html")
+ if legend:
+ 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:
+ 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):
# Prepare the header of the table
try:
header = [
- u"Test case",
- f"{table[u'reference'][u'title']} Thput [Mpps]",
- 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"Test Case",
+ f"Avg({table[u'reference'][u'title']})",
+ f"Stdev({table[u'reference'][u'title']})",
+ f"Avg({table[u'compare'][u'title']})",
+ f"Stdev{table[u'compare'][u'title']})",
+ u"Diff",
+ u"Stdev(Diff)"
]
- header_str = u",".join(header) + u"\n"
+ header_str = u";".join(header) + u"\n"
+ legend = (
+ u"\nLegend:\n"
+ f"Avg({table[u'reference'][u'title']}): "
+ f"Mean value of {table[u'reference'][u'title']} [Mpps] computed "
+ f"from a series of runs of the listed tests.\n"
+ f"Stdev({table[u'reference'][u'title']}): "
+ f"Standard deviation value of {table[u'reference'][u'title']} "
+ f"[Mpps] computed from a series of runs of the listed tests.\n"
+ f"Avg({table[u'compare'][u'title']}): "
+ f"Mean value of {table[u'compare'][u'title']} [Mpps] computed from "
+ f"a series of runs of the listed tests.\n"
+ f"Stdev({table[u'compare'][u'title']}): "
+ f"Standard deviation value of {table[u'compare'][u'title']} [Mpps] "
+ f"computed from a series of runs of the listed tests.\n"
+ f"Diff({table[u'reference'][u'title']},"
+ f"{table[u'compare'][u'title']}): "
+ f"Percentage change calculated for mean values.\n"
+ u"Stdev(Diff): "
+ u"Standard deviation of percentage change calculated for mean "
+ u"values."
+ )
except (AttributeError, KeyError) as err:
logging.error(f"The model is invalid, missing parameter: {repr(err)}")
return
if tst_data[u"type"] not in (u"NDRPDR", u"MRR", u"BMRR"):
continue
if table[u"include-tests"] == u"MRR":
- result = tst_data[u"result"][u"receive-rate"]
+ result = (tst_data[u"result"][u"receive-rate"],
+ tst_data[u"result"][u"receive-stdev"])
elif table[u"include-tests"] == u"PDR":
result = \
tst_data[u"throughput"][u"PDR"][u"LOWER"]
item = [tbl_dict[tst_name][u"name"], ]
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))
+ if table[u"include-tests"] == u"MRR":
+ data_r_mean = data_r[0][0]
+ data_r_stdev = data_r[0][1]
+ else:
+ data_r_mean = mean(data_r)
+ data_r_stdev = stdev(data_r)
+ item.append(round(data_r_mean / 1e6, 1))
+ item.append(round(data_r_stdev / 1e6, 1))
else:
data_r_mean = None
data_r_stdev = None
item.extend([None, None])
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))
+ if table[u"include-tests"] == u"MRR":
+ data_c_mean = data_c[0][0]
+ data_c_stdev = data_c[0][1]
+ else:
+ data_c_mean = mean(data_c)
+ data_c_stdev = stdev(data_c)
+ item.append(round(data_c_mean / 1e6, 1))
+ item.append(round(data_c_stdev / 1e6, 1))
else:
data_c_mean = None
data_c_stdev = None
item.extend([None, None])
- if data_r_mean and data_c_mean:
+ if data_r_mean is not None and data_c_mean is not None:
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))
+ try:
+ item.append(round(delta))
+ except ValueError:
+ item.append(delta)
+ try:
+ item.append(round(d_stdev))
+ except ValueError:
+ item.append(d_stdev)
tbl_lst.append(item)
# Sort the table according to the relative change
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")
+ 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")
+ convert_csv_to_pretty_txt(
+ csv_file_name, f"{table[u'output-file']}.txt", delimiter=u";"
+ )
+ 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, tbl_lst, f"{table[u'output-file']}.html")
+ _tpc_generate_html_table(
+ header,
+ tbl_lst,
+ table[u'output-file'],
+ legend=legend,
+ title=table.get(u"title", u"")
+ )
def table_perf_trending_dash(table, input_data):
]
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)
+ try:
+ classification_lst, avgs, _ = classify_anomalies(data_t)
+ except ValueError as err:
+ logging.info(f"{err} Skipping")
+ return
win_size = min(len(data_t), table[u"window"])
long_win_size = min(len(data_t), table[u"long-trend-window"])
rel_change_last = nan
else:
rel_change_last = round(
- ((last_avg - avg_week_ago) / avg_week_ago) * 100, 2)
+ ((last_avg - avg_week_ago) / avg_week_ago) * 1e2, 2)
if isnan(max_long_avg) or isnan(last_avg) or max_long_avg == 0.0:
rel_change_long = nan
else:
rel_change_long = round(
- ((last_avg - max_long_avg) / max_long_avg) * 100, 2)
+ ((last_avg - max_long_avg) / max_long_avg) * 1e2, 2)
if classification_lst:
if isnan(rel_change_last) and isnan(rel_change_long):
continue
tbl_lst.append(
[tbl_dict[tst_name][u"name"],
- round(last_avg / 1000000, 2),
+ 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])
+ tbl_lst.sort(key=lambda rel: rel[3])
+ tbl_lst.sort(key=lambda rel: rel[2])
tbl_sorted = list()
for nrr in range(table[u"window"], -1, -1):
tbl_reg = [item for item in tbl_lst if item[4] == nrr]
for nrp in range(table[u"window"], -1, -1):
tbl_out = [item for item in tbl_reg if item[5] == nrp]
- tbl_out.sort(key=lambda rel: rel[2])
tbl_sorted.extend(tbl_out)
file_name = f"{table[u'output-file']}{table[u'output-file-ext']}"
nic = u"vic1385"
elif u"x553" in test_name:
nic = u"x553"
+ elif u"cx556" in test_name or u"cx556a" in test_name:
+ nic = u"cx556a"
else:
nic = u""
if u"1t1c" in test_name or \
(u"-1c-" in test_name and
- testbed in (u"3n-hsw", u"3n-tsh", u"2n-dnv", u"3n-dnv")):
+ testbed in (u"3n-hsw", u"3n-tsh", u"2n-dnv", u"3n-dnv", u"2n-tx2")):
cores = u"1t1c"
elif u"2t2c" in test_name or \
(u"-2c-" in test_name and
- testbed in (u"3n-hsw", u"3n-tsh", u"2n-dnv", u"3n-dnv")):
+ testbed in (u"3n-hsw", u"3n-tsh", u"2n-dnv", u"3n-dnv", u"2n-tx2")):
cores = u"2t2c"
elif u"4t4c" in test_name or \
(u"-4c-" in test_name and
- testbed in (u"3n-hsw", u"3n-tsh", u"2n-dnv", u"3n-dnv")):
+ testbed in (u"3n-hsw", u"3n-tsh", u"2n-dnv", u"3n-dnv", u"2n-tx2")):
cores = u"4t4c"
elif u"2t1c" in test_name or \
(u"-1c-" in test_name and
- testbed in (u"2n-skx", u"3n-skx")):
+ testbed in (u"2n-skx", u"3n-skx", u"2n-clx", u"2n-zn2")):
cores = u"2t1c"
- elif u"4t2c" in test_name:
+ elif u"4t2c" in test_name or \
+ (u"-2c-" in test_name and
+ testbed in (u"2n-skx", u"3n-skx", u"2n-clx", u"2n-zn2")):
cores = u"4t2c"
- elif u"8t4c" in test_name:
+ elif u"8t4c" in test_name or \
+ (u"-4c-" in test_name and
+ testbed in (u"2n-skx", u"3n-skx", u"2n-clx", u"2n-zn2")):
cores = u"8t4c"
else:
cores = u""
driver = u"l3fwd"
elif u"avf" in test_name:
driver = u"avf"
+ elif u"rdma" in test_name:
+ driver = u"rdma"
elif u"dnv" in testbed or u"tsh" in testbed:
driver = u"ixgbe"
else:
- driver = u"i40e"
-
- if u"acl" in test_name or \
- u"macip" in test_name or \
- u"nat" in test_name or \
- u"policer" in test_name or \
- u"cop" in test_name:
+ driver = u"dpdk"
+
+ if u"macip-iacl1s" in test_name:
+ bsf = u"features-macip-iacl1"
+ elif u"macip-iacl10s" in test_name:
+ bsf = u"features-macip-iacl10"
+ elif u"macip-iacl50s" in test_name:
+ bsf = u"features-macip-iacl50"
+ elif u"iacl1s" in test_name:
+ bsf = u"features-iacl1"
+ elif u"iacl10s" in test_name:
+ bsf = u"features-iacl10"
+ elif u"iacl50s" in test_name:
+ bsf = u"features-iacl50"
+ elif u"oacl1s" in test_name:
+ bsf = u"features-oacl1"
+ elif u"oacl10s" in test_name:
+ bsf = u"features-oacl10"
+ elif u"oacl50s" in test_name:
+ bsf = u"features-oacl50"
+ elif u"nat44det" in test_name:
+ bsf = u"nat44det-bidir"
+ elif u"nat44ed" in test_name and u"udir" in test_name:
+ bsf = u"nat44ed-udir"
+ elif u"-cps" in test_name and u"ethip4udp" in test_name:
+ bsf = u"udp-cps"
+ elif u"-cps" in test_name and u"ethip4tcp" in test_name:
+ bsf = u"tcp-cps"
+ elif u"-pps" in test_name and u"ethip4udp" in test_name:
+ bsf = u"udp-pps"
+ elif u"-pps" in test_name and u"ethip4tcp" in test_name:
+ bsf = u"tcp-pps"
+ elif u"-tput" in test_name and u"ethip4udp" in test_name:
+ bsf = u"udp-tput"
+ elif u"-tput" in test_name and u"ethip4tcp" in test_name:
+ bsf = u"tcp-tput"
+ elif u"udpsrcscale" in test_name:
+ bsf = u"features-udp"
+ elif u"iacl" in test_name:
+ bsf = u"features"
+ elif u"policer" in test_name:
+ bsf = u"features"
+ elif u"adl" in test_name:
+ bsf = u"features"
+ elif u"cop" in test_name:
+ bsf = u"features"
+ elif u"nat" in test_name:
+ bsf = u"features"
+ elif u"macip" in test_name:
bsf = u"features"
elif u"scale" in test_name:
bsf = u"scale"
if u"114b" in test_name and u"vhost" in test_name:
domain = u"vts"
+ elif u"nat44" in test_name or u"-pps" in test_name or u"-cps" in test_name:
+ domain = u"nat44"
+ if u"nat44det" in test_name:
+ domain += u"-det-bidir"
+ else:
+ domain += u"-ed"
+ if u"udir" in test_name:
+ domain += u"-unidir"
+ elif u"-ethip4udp-" in test_name:
+ domain += u"-udp"
+ elif u"-ethip4tcp-" in test_name:
+ domain += u"-tcp"
+ if u"-cps" in test_name:
+ domain += u"-cps"
+ elif u"-pps" in test_name:
+ domain += u"-pps"
+ elif u"-tput" in test_name:
+ domain += u"-tput"
elif u"testpmd" in test_name or u"l3fwd" in test_name:
domain = u"dpdk"
elif u"memif" in test_name:
bsf += u"-hw"
elif u"ethip4vxlan" in test_name:
domain = u"ip4_tunnels"
+ elif u"ethip4udpgeneve" in test_name:
+ domain = u"ip4_tunnels"
elif u"ip4base" in test_name or u"ip4scale" in test_name:
domain = u"ip4"
elif u"ip6base" in test_name or u"ip6scale" in test_name:
if not table.get(u"testbed", None):
logging.error(
f"The testbed is not defined for the table "
- f"{table.get(u'title', u'')}."
+ f"{table.get(u'title', u'')}. Skipping."
+ )
+ return
+
+ test_type = table.get(u"test-type", u"MRR")
+ if test_type not in (u"MRR", u"NDR", u"PDR"):
+ logging.error(
+ f"Test type {table.get(u'test-type', u'MRR')} is not defined. "
+ f"Skipping."
)
return
+ if test_type in (u"NDR", u"PDR"):
+ lnk_dir = u"../ndrpdr_trending/"
+ lnk_sufix = f"-{test_type.lower()}"
+ else:
+ lnk_dir = u"../trending/"
+ lnk_sufix = u""
+
logging.info(f" Generating the table {table.get(u'title', u'')} ...")
try:
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",
attrib=dict(
- href=f"../trending/"
- f"{_generate_url(table.get(u'testbed', ''), item)}"
+ href=f"{lnk_dir}"
+ f"{_generate_url(table.get(u'testbed', ''), item)}"
+ f"{lnk_sufix}"
)
)
ref.text = item
build = str(build)
try:
version = input_data.metadata(job, build).get(u"version", u"")
+ duration = \
+ input_data.metadata(job, build).get(u"elapsedtime", u"")
except KeyError:
logging.error(f"Data for {job}: {build} is not present.")
return
continue
nic = groups.group(0)
failed_tests.append(f"{nic}-{tst_data[u'name']}")
- tbl_list.append(str(passed))
- tbl_list.append(str(failed))
+ tbl_list.append(passed)
+ tbl_list.append(failed)
+ tbl_list.append(duration)
tbl_list.extend(failed_tests)
file_name = f"{table[u'output-file']}{table[u'output-file-ext']}"
logging.info(f" Writing file: {file_name}")
with open(file_name, u"wt") as file_handler:
for test in tbl_list:
- file_handler.write(test + u'\n')
+ file_handler.write(f"{test}\n")
def table_failed_tests(table, input_data):
)
data = input_data.filter_data(table, continue_on_error=True)
+ test_type = u"MRR"
+ if u"NDRPDR" in table.get(u"filter", list()):
+ test_type = u"NDRPDR"
+
# Prepare the header of the tables
header = [
u"Test Case",
fails_last_csit = val[3]
if fails_nr:
max_fails = fails_nr if fails_nr > max_fails else max_fails
- tbl_lst.append(
- [
- tst_data[u"name"],
- fails_nr,
- fails_last_date,
- fails_last_vpp,
- f"mrr-daily-build-{fails_last_csit}"
- ]
- )
+ tbl_lst.append([
+ tst_data[u"name"],
+ fails_nr,
+ fails_last_date,
+ fails_last_vpp,
+ f"{u'mrr-daily' if test_type == u'MRR' else u'ndrpdr-weekly'}"
+ f"-build-{fails_last_csit}"
+ ])
tbl_lst.sort(key=lambda rel: rel[2], reverse=True)
tbl_sorted = list()
if not table.get(u"testbed", None):
logging.error(
f"The testbed is not defined for the table "
- f"{table.get(u'title', u'')}."
+ f"{table.get(u'title', u'')}. Skipping."
+ )
+ return
+
+ test_type = table.get(u"test-type", u"MRR")
+ if test_type not in (u"MRR", u"NDR", u"PDR", u"NDRPDR"):
+ logging.error(
+ f"Test type {table.get(u'test-type', u'MRR')} is not defined. "
+ f"Skipping."
)
return
+ if test_type in (u"NDRPDR", u"NDR", u"PDR"):
+ lnk_dir = u"../ndrpdr_trending/"
+ lnk_sufix = u"-pdr"
+ else:
+ lnk_dir = u"../trending/"
+ lnk_sufix = u""
+
logging.info(f" Generating the table {table.get(u'title', u'')} ...")
try:
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",
attrib=dict(
- href=f"../trending/"
- f"{_generate_url(table.get(u'testbed', ''), item)}"
+ href=f"{lnk_dir}"
+ f"{_generate_url(table.get(u'testbed', ''), item)}"
+ f"{lnk_sufix}"
)
)
ref.text = item
except KeyError:
logging.warning(u"The output file is not defined.")
return
+
+
+def table_comparison(table, input_data):
+ """Generate the table(s) with algorithm: table_comparison
+ specified in the specification file.
+
+ :param table: Table to generate.
+ :param input_data: Data to process.
+ :type table: pandas.Series
+ :type input_data: InputData
+ """
+ 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'')}."
+ )
+
+ columns = table.get(u"columns", None)
+ if not columns:
+ logging.error(
+ f"No columns specified for {table.get(u'title', u'')}. Skipping."
+ )
+ return
+
+ cols = list()
+ for idx, col in enumerate(columns):
+ if col.get(u"data-set", None) is None:
+ logging.warning(f"No data for column {col.get(u'title', u'')}")
+ continue
+ tag = col.get(u"tag", None)
+ data = input_data.filter_data(
+ table,
+ params=[u"throughput", u"result", u"name", u"parent", u"tags"],
+ data=col[u"data-set"],
+ continue_on_error=True
+ )
+ col_data = {
+ u"title": col.get(u"title", f"Column{idx}"),
+ u"data": dict()
+ }
+ for builds in data.values:
+ for build in builds:
+ for tst_name, tst_data in build.items():
+ if tag and tag not in tst_data[u"tags"]:
+ continue
+ tst_name_mod = \
+ _tpc_modify_test_name(tst_name, ignore_nic=True).\
+ replace(u"2n1l-", u"")
+ if col_data[u"data"].get(tst_name_mod, None) is None:
+ name = tst_data[u'name'].rsplit(u'-', 1)[0]
+ if u"across testbeds" in table[u"title"].lower() or \
+ u"across topologies" in table[u"title"].lower():
+ name = _tpc_modify_displayed_test_name(name)
+ col_data[u"data"][tst_name_mod] = {
+ u"name": name,
+ u"replace": True,
+ u"data": list(),
+ u"mean": None,
+ u"stdev": None
+ }
+ _tpc_insert_data(
+ target=col_data[u"data"][tst_name_mod],
+ src=tst_data,
+ include_tests=table[u"include-tests"]
+ )
+
+ replacement = col.get(u"data-replacement", None)
+ if replacement:
+ rpl_data = input_data.filter_data(
+ table,
+ params=[u"throughput", u"result", u"name", u"parent", u"tags"],
+ data=replacement,
+ continue_on_error=True
+ )
+ for builds in rpl_data.values:
+ for build in builds:
+ for tst_name, tst_data in build.items():
+ if tag and tag not in tst_data[u"tags"]:
+ continue
+ tst_name_mod = \
+ _tpc_modify_test_name(tst_name, ignore_nic=True).\
+ replace(u"2n1l-", u"")
+ if col_data[u"data"].get(tst_name_mod, None) is None:
+ name = tst_data[u'name'].rsplit(u'-', 1)[0]
+ if u"across testbeds" in table[u"title"].lower() \
+ or u"across topologies" in \
+ table[u"title"].lower():
+ name = _tpc_modify_displayed_test_name(name)
+ col_data[u"data"][tst_name_mod] = {
+ u"name": name,
+ u"replace": False,
+ u"data": list(),
+ u"mean": None,
+ u"stdev": None
+ }
+ if col_data[u"data"][tst_name_mod][u"replace"]:
+ col_data[u"data"][tst_name_mod][u"replace"] = False
+ col_data[u"data"][tst_name_mod][u"data"] = list()
+ _tpc_insert_data(
+ target=col_data[u"data"][tst_name_mod],
+ src=tst_data,
+ include_tests=table[u"include-tests"]
+ )
+
+ if table[u"include-tests"] in (u"NDR", u"PDR"):
+ for tst_name, tst_data in col_data[u"data"].items():
+ if tst_data[u"data"]:
+ tst_data[u"mean"] = mean(tst_data[u"data"])
+ tst_data[u"stdev"] = stdev(tst_data[u"data"])
+
+ cols.append(col_data)
+
+ tbl_dict = dict()
+ for col in cols:
+ for tst_name, tst_data in col[u"data"].items():
+ if tbl_dict.get(tst_name, None) is None:
+ tbl_dict[tst_name] = {
+ "name": tst_data[u"name"]
+ }
+ tbl_dict[tst_name][col[u"title"]] = {
+ u"mean": tst_data[u"mean"],
+ 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"], ]
+ for col in cols:
+ row.append(tst_data.get(col[u"title"], None))
+ tbl_lst.append(row)
+
+ comparisons = table.get(u"comparisons", None)
+ rcas = list()
+ if comparisons and isinstance(comparisons, list):
+ for idx, comp in enumerate(comparisons):
+ try:
+ col_ref = int(comp[u"reference"])
+ col_cmp = int(comp[u"compare"])
+ except KeyError:
+ logging.warning(u"Comparison: No references defined! Skipping.")
+ comparisons.pop(idx)
+ continue
+ if not (0 < col_ref <= len(cols) and 0 < col_cmp <= len(cols) or
+ col_ref == col_cmp):
+ logging.warning(f"Wrong values of reference={col_ref} "
+ f"and/or compare={col_cmp}. Skipping.")
+ comparisons.pop(idx)
+ continue
+ rca_file_name = comp.get(u"rca-file", None)
+ if rca_file_name:
+ try:
+ with open(rca_file_name, u"r") as file_handler:
+ rcas.append(
+ {
+ u"title": f"RCA{idx + 1}",
+ u"data": load(file_handler, Loader=FullLoader)
+ }
+ )
+ except (YAMLError, IOError) as err:
+ logging.warning(
+ f"The RCA file {rca_file_name} does not exist or "
+ f"it is corrupted!"
+ )
+ logging.debug(repr(err))
+ rcas.append(None)
+ else:
+ rcas.append(None)
+ else:
+ comparisons = None
+
+ tbl_cmp_lst = list()
+ if comparisons:
+ for row in tbl_lst:
+ new_row = deepcopy(row)
+ for comp in comparisons:
+ ref_itm = row[int(comp[u"reference"])]
+ if ref_itm is None and \
+ comp.get(u"reference-alt", None) is not None:
+ ref_itm = row[int(comp[u"reference-alt"])]
+ cmp_itm = row[int(comp[u"compare"])]
+ if ref_itm is not None and cmp_itm is not None and \
+ ref_itm[u"mean"] is not None and \
+ cmp_itm[u"mean"] is not None and \
+ ref_itm[u"stdev"] is not None and \
+ cmp_itm[u"stdev"] is not None:
+ delta, d_stdev = relative_change_stdev(
+ ref_itm[u"mean"], cmp_itm[u"mean"],
+ ref_itm[u"stdev"], cmp_itm[u"stdev"]
+ )
+ if delta is None:
+ break
+ new_row.append({
+ u"mean": delta * 1e6,
+ u"stdev": d_stdev * 1e6
+ })
+ else:
+ break
+ else:
+ tbl_cmp_lst.append(new_row)
+
+ 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}")
+
+ tbl_for_csv = list()
+ for line in tbl_cmp_lst:
+ row = [line[0], ]
+ for idx, itm in enumerate(line[1:]):
+ 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:
+ row.append(round(float(itm[u'mean']) / 1e6, 3))
+ row.append(round(float(itm[u'stdev']) / 1e6, 3))
+ for rca in rcas:
+ if rca is None:
+ continue
+ rca_nr = rca[u"data"].get(row[0], u"-")
+ row.append(f"[{rca_nr}]" if rca_nr != u"-" else u"-")
+ tbl_for_csv.append(row)
+
+ header_csv = [u"Test Case", ]
+ for col in cols:
+ header_csv.append(f"Avg({col[u'title']})")
+ header_csv.append(f"Stdev({col[u'title']})")
+ for comp in comparisons:
+ header_csv.append(
+ f"Avg({comp.get(u'title', u'')})"
+ )
+ header_csv.append(
+ f"Stdev({comp.get(u'title', u'')})"
+ )
+ for rca in rcas:
+ if rca:
+ header_csv.append(rca[u"title"])
+
+ legend_lst = table.get(u"legend", None)
+ if legend_lst is None:
+ legend = u""
+ else:
+ legend = u"\n" + u"\n".join(legend_lst) + u"\n"
+
+ footnote = u""
+ if rcas and any(rcas):
+ footnote += u"\nRoot Cause Analysis:\n"
+ for rca in rcas:
+ if rca:
+ footnote += f"{rca[u'data'].get(u'footnote', u'')}\n"
+
+ 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 test in tbl_for_csv:
+ file_handler.write(
+ u",".join([f'"{item}"' for item in test]) + u"\n"
+ )
+ if legend_lst:
+ for item in legend_lst:
+ file_handler.write(f'"{item}"\n')
+ if footnote:
+ for itm in footnote.split(u"\n"):
+ file_handler.write(f'"{itm}"\n')
+
+ tbl_tmp = list()
+ max_lens = [0, ] * len(tbl_cmp_lst[0])
+ for line in tbl_cmp_lst:
+ row = [line[0], ]
+ for idx, itm in enumerate(line[1:]):
+ 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):
+ new_itm = (
+ f"{round(float(itm[u'mean']) / 1e6, 1)} "
+ f"\u00B1{round(float(itm[u'stdev']) / 1e6, 1)}".
+ replace(u"nan", u"NaN")
+ )
+ else:
+ new_itm = (
+ f"{round(float(itm[u'mean']) / 1e6, 1):+} "
+ f"\u00B1{round(float(itm[u'stdev']) / 1e6, 1)}".
+ replace(u"nan", u"NaN")
+ )
+ if len(new_itm.rsplit(u" ", 1)[-1]) > max_lens[idx]:
+ max_lens[idx] = len(new_itm.rsplit(u" ", 1)[-1])
+ row.append(new_itm)
+
+ tbl_tmp.append(row)
+
+ header = [u"Test Case", ]
+ header.extend([col[u"title"] for col in cols])
+ header.extend([comp.get(u"title", u"") for comp in comparisons])
+
+ tbl_final = list()
+ for line in tbl_tmp:
+ row = [line[0], ]
+ for idx, itm in enumerate(line[1:]):
+ if itm in (u"NT", u"NaN"):
+ row.append(itm)
+ continue
+ itm_lst = itm.rsplit(u"\u00B1", 1)
+ itm_lst[-1] = \
+ f"{u' ' * (max_lens[idx] - len(itm_lst[-1]))}{itm_lst[-1]}"
+ itm_str = u"\u00B1".join(itm_lst)
+
+ if idx >= len(cols):
+ # Diffs
+ rca = rcas[idx - len(cols)]
+ if rca:
+ # Add rcas to diffs
+ rca_nr = rca[u"data"].get(row[0], None)
+ if rca_nr:
+ hdr_len = len(header[idx + 1]) - 1
+ if hdr_len < 19:
+ hdr_len = 19
+ rca_nr = f"[{rca_nr}]"
+ itm_str = (
+ f"{u' ' * (4 - len(rca_nr))}{rca_nr}"
+ f"{u' ' * (hdr_len - 4 - len(itm_str))}"
+ f"{itm_str}"
+ )
+ row.append(itm_str)
+ tbl_final.append(row)
+
+ # Generate csv tables:
+ 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"
+ 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 file_handler:
+ file_handler.write(legend)
+ file_handler.write(footnote)
+
+ # Generate html table:
+ _tpc_generate_html_table(
+ header,
+ tbl_final,
+ table[u'output-file'],
+ legend=legend,
+ footnote=footnote,
+ sort_data=False,
+ title=table.get(u"title", u"")
+ )
+
+
+def table_weekly_comparison(table, in_data):
+ """Generate the table(s) with algorithm: table_weekly_comparison
+ specified in the specification file.
+
+ :param table: Table to generate.
+ :param in_data: Data to process.
+ :type table: pandas.Series
+ :type in_data: InputData
+ """
+ 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'')}."
+ )
+
+ incl_tests = table.get(u"include-tests", None)
+ if incl_tests not in (u"NDR", u"PDR"):
+ logging.error(f"Wrong tests to include specified ({incl_tests}).")
+ return
+
+ nr_cols = table.get(u"nr-of-data-columns", None)
+ if not nr_cols or nr_cols < 2:
+ logging.error(
+ f"No columns specified for {table.get(u'title', u'')}. Skipping."
+ )
+ return
+
+ data = in_data.filter_data(
+ table,
+ params=[u"throughput", u"result", u"name", u"parent", u"tags"],
+ continue_on_error=True
+ )
+
+ header = [
+ [u"VPP Version", ],
+ [u"Start Timestamp", ],
+ [u"CSIT Build", ],
+ [u"CSIT Testbed", ]
+ ]
+ tbl_dict = dict()
+ idx = 0
+ tb_tbl = table.get(u"testbeds", None)
+ for job_name, job_data in data.items():
+ for build_nr, build in job_data.items():
+ if idx >= nr_cols:
+ break
+ if build.empty:
+ continue
+
+ tb_ip = in_data.metadata(job_name, build_nr).get(u"testbed", u"")
+ if tb_ip and tb_tbl:
+ testbed = tb_tbl.get(tb_ip, u"")
+ else:
+ testbed = u""
+ header[2].insert(1, build_nr)
+ header[3].insert(1, testbed)
+ header[1].insert(
+ 1, in_data.metadata(job_name, build_nr).get(u"generated", u"")
+ )
+ header[0].insert(
+ 1, in_data.metadata(job_name, build_nr).get(u"version", u"")
+ )
+
+ for tst_name, tst_data in build.items():
+ tst_name_mod = \
+ _tpc_modify_test_name(tst_name).replace(u"2n1l-", u"")
+ if not tbl_dict.get(tst_name_mod, None):
+ tbl_dict[tst_name_mod] = dict(
+ name=tst_data[u'name'].rsplit(u'-', 1)[0],
+ )
+ try:
+ tbl_dict[tst_name_mod][-idx - 1] = \
+ tst_data[u"throughput"][incl_tests][u"LOWER"]
+ except (TypeError, IndexError, KeyError, ValueError):
+ pass
+ idx += 1
+
+ if idx < nr_cols:
+ logging.error(u"Not enough data to build the table! Skipping")
+ return
+
+ cmp_dict = dict()
+ for idx, cmp in enumerate(table.get(u"comparisons", list())):
+ idx_ref = cmp.get(u"reference", None)
+ idx_cmp = cmp.get(u"compare", None)
+ if idx_ref is None or idx_cmp is None:
+ continue
+ 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()
+ ref_data = tst_data.get(idx_ref, None)
+ cmp_data = tst_data.get(idx_cmp, None)
+ if ref_data is None or cmp_data is None:
+ cmp_dict[tst_name].append(float(u'nan'))
+ else:
+ cmp_dict[tst_name].append(
+ relative_change(ref_data, cmp_data)
+ )
+
+ tbl_lst_none = list()
+ tbl_lst = list()
+ for tst_name, tst_data in tbl_dict.items():
+ itm_lst = [tst_data[u"name"], ]
+ for idx in range(nr_cols):
+ item = tst_data.get(-idx - 1, None)
+ if item is None:
+ itm_lst.insert(1, None)
+ else:
+ itm_lst.insert(1, round(item / 1e6, 1))
+ itm_lst.extend(
+ [
+ None if itm is None else round(itm, 1)
+ for itm in cmp_dict[tst_name]
+ ]
+ )
+ if str(itm_lst[-1]) == u"nan" or itm_lst[-1] is None:
+ tbl_lst_none.append(itm_lst)
+ else:
+ tbl_lst.append(itm_lst)
+
+ tbl_lst_none.sort(key=lambda rel: rel[0], reverse=False)
+ tbl_lst.sort(key=lambda rel: rel[0], reverse=False)
+ tbl_lst.sort(key=lambda rel: rel[-1], reverse=False)
+ tbl_lst.extend(tbl_lst_none)
+
+ # Generate csv table:
+ 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:
+ file_handler.write(u",".join(
+ [
+ str(item).replace(u"None", u"-").replace(u"nan", u"-").
+ replace(u"null", u"-") for item in test
+ ]
+ ) + u"\n")
+
+ 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_name, u"rt", encoding='utf-8') as file_handler:
+ for line in list(file_handler):
+ txt_table.append(line)
+ try:
+ txt_table.insert(5, txt_table.pop(2))
+ with open(txt_file_name, u"wt", encoding='utf-8') as file_handler:
+ file_handler.writelines(txt_table)
+ except IndexError:
+ pass
+
+ # Generate html table:
+ hdr_html = [
+ u"<br>".join(row) for row in zip(*header)
+ ]
+ _tpc_generate_html_table(
+ hdr_html,
+ tbl_lst,
+ table[u'output-file'],
+ sort_data=True,
+ title=table.get(u"title", u""),
+ generate_rst=False
+ )
Code Review / csit.git / blobdiff