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authorTibor Frank <tifrank@cisco.com>2019-01-18 13:19:01 +0100
committerTibor Frank <tifrank@cisco.com>2019-01-21 11:52:03 +0000
commitbec963c7d97302d7a0e41d38a5eec1ff5e518067 (patch)
treee8e345578f2f609104cd9f5fd296cdd4af06fdbe /resources/tools/presentation/generator_tables.py
parentd7a10b0bb4133a32884079a146b6876506b99054 (diff)
CSIT-1395: Create comparison tables for NICs
Change-Id: Ib8583041a0d16a6242160b4f51eae973ef33504f Signed-off-by: Tibor Frank <tifrank@cisco.com>
Diffstat (limited to 'resources/tools/presentation/generator_tables.py')
-rw-r--r--resources/tools/presentation/generator_tables.py117
1 files changed, 114 insertions, 3 deletions
diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py
index f6537af93e..41dfb9429d 100644
--- a/resources/tools/presentation/generator_tables.py
+++ b/resources/tools/presentation/generator_tables.py
@@ -245,9 +245,10 @@ def table_performance_comparison(table, input_data):
if "across topologies" in table["title"].lower():
tst_name_mod = tst_name_mod.replace("2n1l-", "")
if tbl_dict.get(tst_name_mod, None) is None:
- name = "{0}-{1}".format(tst_data["parent"].split("-")[0],
- "-".join(tst_data["name"].
- split("-")[:-1]))
+ groups = re.search(REGEX_NIC, tst_data["parent"])
+ nic = groups.group(0) if groups else ""
+ name = "{0}-{1}".format(nic, "-".join(tst_data["name"].
+ split("-")[:-1]))
if "across testbeds" in table["title"].lower() or \
"across topologies" in table["title"].lower():
name = name.\
@@ -412,6 +413,116 @@ def table_performance_comparison(table, input_data):
convert_csv_to_pretty_txt(csv_file, "{0}.txt".format(table["output-file"]))
+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(" Generating the table {0} ...".
+ format(table.get("title", "")))
+
+ # Transform the data
+ logging.info(" Creating the data set for the {0} '{1}'.".
+ format(table.get("type", ""), table.get("title", "")))
+ data = input_data.filter_data(table, continue_on_error=True)
+
+ # Prepare the header of the tables
+ try:
+ header = ["Test case", ]
+
+ if table["include-tests"] == "MRR":
+ hdr_param = "Receive Rate"
+ else:
+ hdr_param = "Throughput"
+
+ header.extend(
+ ["{0} {1} [Mpps]".format(table["reference"]["title"], hdr_param),
+ "{0} Stdev [Mpps]".format(table["reference"]["title"]),
+ "{0} {1} [Mpps]".format(table["compare"]["title"], hdr_param),
+ "{0} Stdev [Mpps]".format(table["compare"]["title"]),
+ "Delta [%]"])
+ header_str = ",".join(header) + "\n"
+ except (AttributeError, KeyError) as err:
+ logging.error("The model is invalid, missing parameter: {0}".
+ format(err))
+ return
+
+ # Prepare data to the table:
+ tbl_dict = dict()
+ for job, builds in table["data"].items():
+ for build in builds:
+ for tst_name, tst_data in data[job][str(build)].iteritems():
+ tst_name_mod = tst_name.replace("-ndrpdrdisc", "").\
+ replace("-ndrpdr", "").replace("-pdrdisc", "").\
+ replace("-ndrdisc", "").replace("-pdr", "").\
+ replace("-ndr", "").\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ tst_name_mod = re.sub(REGEX_NIC, "", tst_name_mod)
+ if tbl_dict.get(tst_name_mod, None) is None:
+ name = "-".join(tst_data["name"].split("-")[:-1])
+ tbl_dict[tst_name_mod] = {"name": name,
+ "ref-data": list(),
+ "cmp-data": list()}
+ try:
+ if table["include-tests"] == "MRR":
+ result = tst_data["result"]["receive-rate"].avg
+ elif table["include-tests"] == "PDR":
+ result = tst_data["throughput"]["PDR"]["LOWER"]
+ elif table["include-tests"] == "NDR":
+ result = tst_data["throughput"]["NDR"]["LOWER"]
+ else:
+ result = None
+
+ if result:
+ if table["reference"]["nic"] in tst_data["tags"]:
+ tbl_dict[tst_name_mod]["ref-data"].append(result)
+ elif table["compare"]["nic"] in tst_data["tags"]:
+ tbl_dict[tst_name_mod]["cmp-data"].append(result)
+ except (TypeError, KeyError) as err:
+ logging.warning("No data for {0}".format(tst_name))
+ logging.warning(repr(err))
+ # No data in output.xml for this test
+
+ tbl_lst = list()
+ for tst_name in tbl_dict.keys():
+ item = [tbl_dict[tst_name]["name"], ]
+ data_t = tbl_dict[tst_name]["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]["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)
+
+ # Sort the table according to the relative change
+ tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)
+
+ # Generate csv tables:
+ csv_file = "{0}.csv".format(table["output-file"])
+ with open(csv_file, "w") as file_handler:
+ file_handler.write(header_str)
+ for test in tbl_lst:
+ file_handler.write(",".join([str(item) for item in test]) + "\n")
+
+ convert_csv_to_pretty_txt(csv_file, "{0}.txt".format(table["output-file"]))
+
+
def table_performance_trending_dashboard(table, input_data):
"""Generate the table(s) with algorithm:
table_performance_trending_dashboard