+ if history:
+ for item in history:
+ for job, builds in item["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")
+ 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:
+ continue
+ if tbl_dict[tst_name_mod].get("history", None) is None:
+ tbl_dict[tst_name_mod]["history"] = OrderedDict()
+ if tbl_dict[tst_name_mod]["history"].get(item["title"],
+ None) is None:
+ tbl_dict[tst_name_mod]["history"][item["title"]] = \
+ list()
+ try:
+ # TODO: Re-work when NDRPDRDISC tests are not used
+ if table["include-tests"] == "MRR":
+ tbl_dict[tst_name_mod]["history"][item["title"
+ ]].append(tst_data["result"]["receive-rate"].
+ avg)
+ elif table["include-tests"] == "PDR":
+ if tst_data["type"] == "PDR":
+ tbl_dict[tst_name_mod]["history"][
+ item["title"]].\
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["history"][item[
+ "title"]].append(tst_data["throughput"][
+ "PDR"]["LOWER"])
+ elif table["include-tests"] == "NDR":
+ if tst_data["type"] == "NDR":
+ tbl_dict[tst_name_mod]["history"][
+ item["title"]].\
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["history"][item[
+ "title"]].append(tst_data["throughput"][
+ "NDR"]["LOWER"])
+ else:
+ continue
+ except (TypeError, KeyError):
+ pass
+
+ tbl_lst = list()
+ footnote = False
+ for tst_name in tbl_dict.keys():
+ item = [tbl_dict[tst_name]["name"], ]
+ if history:
+ if tbl_dict[tst_name].get("history", None) is not None:
+ for hist_data in tbl_dict[tst_name]["history"].values():
+ if hist_data:
+ item.append(round(mean(hist_data) / 1000000, 2))
+ item.append(round(stdev(hist_data) / 1000000, 2))
+ else:
+ item.extend(["Not tested", "Not tested"])
+ else:
+ item.extend(["Not tested", "Not tested"])
+ 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(["Not tested", "Not tested"])
+ 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(["Not tested", "Not tested"])
+ if item[-2] == "Not tested":
+ pass
+ elif item[-4] == "Not tested":
+ item.append("New in CSIT-1908")
+ elif topo == "2n-skx" and "dot1q" in tbl_dict[tst_name]["name"]:
+ item.append("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] != "Not tested"):
+ 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")
+
+ txt_file_name = "{0}.txt".format(table["output-file"])
+ convert_csv_to_pretty_txt(csv_file, txt_file_name)
+
+ if footnote:
+ with open(txt_file_name, 'a') as txt_file:
+ txt_file.writelines([
+ "\nFootnotes:\n",
+ "[1] CSIT-1908 changed test methodology of dot1q tests in "
+ "2n-skx testbeds, dot1q encapsulation is now used on both "
+ "links of SUT.\n",
+ " Previously dot1q was used only on a single link with the "
+ "other link carrying untagged Ethernet frames. This change "
+ "results\n",
+ " in slightly lower throughput in CSIT-1908 for these "
+ "tests. See release notes."
+ ])
+
+
+def table_performance_comparison_nic(table, input_data):
+ """Generate the table(s) with algorithm: table_performance_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 = "Rec Rate"
+ else:
+ hdr_param = "Thput"
+
+ history = table.get("history", None)
+ if history:
+ for item in history:
+ header.extend(
+ ["{0} {1} [Mpps]".format(item["title"], hdr_param),
+ "{0} Stdev [Mpps]".format(item["title"])])
+ 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["reference"]["data"].items():
+ topo = "2n-skx" if "2n-skx" in job else ""
+ for build in builds:
+ for tst_name, tst_data in data[job][str(build)].iteritems():
+ if table["reference"]["nic"] not in tst_data["tags"]:
+ continue
+ 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 "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}".format("-".join(tst_data["name"].
+ split("-")[:-1]))
+ if "across testbeds" in table["title"].lower() or \
+ "across topologies" in table["title"].lower():
+ name = name.\
+ replace("1t1c", "1c").replace("2t1c", "1c").\
+ replace("2t2c", "2c").replace("4t2c", "2c").\
+ replace("4t4c", "4c").replace("8t4c", "4c")
+ tbl_dict[tst_name_mod] = {"name": name,
+ "ref-data": list(),
+ "cmp-data": list()}
+ try:
+ # TODO: Re-work when NDRPDRDISC tests are not used
+ if table["include-tests"] == "MRR":
+ tbl_dict[tst_name_mod]["ref-data"]. \
+ append(tst_data["result"]["receive-rate"].avg)
+ elif table["include-tests"] == "PDR":
+ if tst_data["type"] == "PDR":
+ tbl_dict[tst_name_mod]["ref-data"]. \
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["ref-data"].append(
+ tst_data["throughput"]["PDR"]["LOWER"])
+ elif table["include-tests"] == "NDR":
+ if tst_data["type"] == "NDR":
+ tbl_dict[tst_name_mod]["ref-data"]. \
+ append(tst_data["throughput"]["value"])
+ elif tst_data["type"] == "NDRPDR":
+ tbl_dict[tst_name_mod]["ref-data"].append(
+ tst_data["throughput"]["NDR"]["LOWER"])
+ else:
+ continue
Code Review / csit.git / blobdiff