X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fgenerator_tables.py;h=a5a8824dc91ea6e5d8470e46671a8c9cc4934931;hp=dc61adbfe2187912aa428aee2e3e9297f2c0f8ca;hb=29035746be0145db942832b55555b695da2323d7;hpb=2036f500644bf34aebfd3456278d0efd0b9ab79f diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py index dc61adbfe2..a5a8824dc9 100644 --- a/resources/tools/presentation/generator_tables.py +++ b/resources/tools/presentation/generator_tables.py @@ -18,11 +18,13 @@ import logging import csv import prettytable +import pandas as pd from string import replace +from math import isnan from errors import PresentationError -from utils import mean, stdev, relative_change, remove_outliers +from utils import mean, stdev, relative_change, remove_outliers, find_outliers def generate_tables(spec, data): @@ -401,17 +403,17 @@ def table_performance_comparison(table, input_data): for tst_name in tbl_dict.keys(): item = [tbl_dict[tst_name]["name"], ] if tbl_dict[tst_name]["ref-data"]: - item.append(round(mean(remove_outliers( - tbl_dict[tst_name]["ref-data"], 2)) / 1000000, 2)) - item.append(round(stdev(remove_outliers( - tbl_dict[tst_name]["ref-data"], 2)) / 1000000, 2)) + data_t = remove_outliers(tbl_dict[tst_name]["ref-data"], + table["outlier-const"]) + item.append(round(mean(data_t) / 1000000, 2)) + item.append(round(stdev(data_t) / 1000000, 2)) else: item.extend([None, None]) if tbl_dict[tst_name]["cmp-data"]: - item.append(round(mean(remove_outliers( - tbl_dict[tst_name]["cmp-data"], 2)) / 1000000, 2)) - item.append(round(stdev(remove_outliers( - tbl_dict[tst_name]["cmp-data"], 2)) / 1000000, 2)) + data_t = remove_outliers(tbl_dict[tst_name]["cmp-data"], + table["outlier-const"]) + item.append(round(mean(data_t) / 1000000, 2)) + item.append(round(stdev(data_t) / 1000000, 2)) else: item.extend([None, None]) if item[1] is not None and item[3] is not None: @@ -438,7 +440,7 @@ def table_performance_comparison(table, input_data): table["output-file-ext"]) ] for file_name in tbl_names: - logging.info(" Writing file: '{}'".format(file_name)) + logging.info(" Writing file: '{0}'".format(file_name)) with open(file_name, "w") as file_handler: file_handler.write(header_str) for test in tbl_lst: @@ -459,7 +461,7 @@ def table_performance_comparison(table, input_data): for i, txt_name in enumerate(tbl_names_txt): txt_table = None - logging.info(" Writing file: '{}'".format(txt_name)) + logging.info(" Writing file: '{0}'".format(txt_name)) with open(tbl_names[i], 'rb') as csv_file: csv_content = csv.reader(csv_file, delimiter=',', quotechar='"') for row in csv_content: @@ -467,6 +469,7 @@ def table_performance_comparison(table, input_data): txt_table = prettytable.PrettyTable(row) else: txt_table.add_row(row) + txt_table.align["Test case"] = "l" with open(txt_name, "w") as txt_file: txt_file.write(str(txt_table)) @@ -480,7 +483,7 @@ def table_performance_comparison(table, input_data): output_file = "{0}-ndr-1t1c-top{1}".format(table["output-file"], table["output-file-ext"]) - logging.info(" Writing file: '{}'".format(output_file)) + logging.info(" Writing file: '{0}'".format(output_file)) with open(output_file, "w") as out_file: out_file.write(header_str) for i, line in enumerate(lines[1:]): @@ -490,7 +493,7 @@ def table_performance_comparison(table, input_data): output_file = "{0}-ndr-1t1c-bottom{1}".format(table["output-file"], table["output-file-ext"]) - logging.info(" Writing file: '{}'".format(output_file)) + logging.info(" Writing file: '{0}'".format(output_file)) with open(output_file, "w") as out_file: out_file.write(header_str) for i, line in enumerate(lines[-1:0:-1]): @@ -507,7 +510,7 @@ def table_performance_comparison(table, input_data): output_file = "{0}-pdr-1t1c-top{1}".format(table["output-file"], table["output-file-ext"]) - logging.info(" Writing file: '{}'".format(output_file)) + logging.info(" Writing file: '{0}'".format(output_file)) with open(output_file, "w") as out_file: out_file.write(header_str) for i, line in enumerate(lines[1:]): @@ -517,10 +520,122 @@ def table_performance_comparison(table, input_data): output_file = "{0}-pdr-1t1c-bottom{1}".format(table["output-file"], table["output-file-ext"]) - logging.info(" Writing file: '{}'".format(output_file)) + logging.info(" Writing file: '{0}'".format(output_file)) with open(output_file, "w") as out_file: out_file.write(header_str) for i, line in enumerate(lines[-1:0:-1]): if i == table["nr-of-tests-shown"]: break out_file.write(line) + + +def table_performance_trending_dashboard(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 + data = input_data.filter_data(table) + + # Prepare the header of the tables + header = ["Test case", + "Thput trend [Mpps]", + "Anomaly [Mpps]", + "Change [%]", + "Classification"] + header_str = ",".join(header) + "\n" + + # 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(): + if tbl_dict.get(tst_name, None) is None: + name = "{0}-{1}".format(tst_data["parent"].split("-")[0], + "-".join(tst_data["name"]. + split("-")[1:])) + tbl_dict[tst_name] = {"name": name, + "data": list()} + try: + tbl_dict[tst_name]["data"]. \ + append(tst_data["result"]["throughput"]) + except (TypeError, KeyError): + pass # No data in output.xml for this test + + tbl_lst = list() + for tst_name in tbl_dict.keys(): + if len(tbl_dict[tst_name]["data"]) > 2: + pd_data = pd.Series(tbl_dict[tst_name]["data"]) + win_size = pd_data.size \ + if pd_data.size < table["window"] else table["window"] + # Test name: + name = tbl_dict[tst_name]["name"] + # Throughput trend: + trend = list(pd_data.rolling(window=win_size, min_periods=2). + median())[-2] + # Anomaly: + t_data, _ = find_outliers(pd_data) + last = list(t_data)[-1] + t_stdev = list(t_data.rolling(window=win_size, min_periods=2). + std())[-2] + if isnan(last): + classification = "outlier" + last = list(pd_data)[-1] + elif last < (trend - 3 * t_stdev): + classification = "regression" + elif last > (trend + 3 * t_stdev): + classification = "progression" + else: + classification = "normal" + + if not isnan(last) and not isnan(trend) and trend != 0: + # Change: + change = round(float(last - trend) / 1000000, 2) + # Relative change: + rel_change = int(relative_change(float(trend), float(last))) + + tbl_lst.append([name, + round(float(trend) / 1000000, 2), + last, + rel_change, + classification]) + + # Sort the table according to the relative change + # tbl_lst.sort(key=lambda rel: rel[-2], reverse=True) + + # Sort the table according to the classification + tbl_sorted = list() + for classification in ("regression", "outlier", "progression", "normal"): + tbl_tmp = [item for item in tbl_lst if item[4] == classification] + tbl_tmp.sort(key=lambda rel: rel[0]) + tbl_sorted.extend(tbl_tmp) + + file_name = "{0}.{1}".format(table["output-file"], table["output-file-ext"]) + + logging.info(" Writing file: '{0}'".format(file_name)) + with open(file_name, "w") as file_handler: + file_handler.write(header_str) + for test in tbl_sorted: + file_handler.write(",".join([str(item) for item in test]) + '\n') + + txt_file_name = "{0}.txt".format(table["output-file"]) + txt_table = None + logging.info(" Writing file: '{0}'".format(txt_file_name)) + with open(file_name, 'rb') as csv_file: + csv_content = csv.reader(csv_file, delimiter=',', quotechar='"') + for row in csv_content: + if txt_table is None: + txt_table = prettytable.PrettyTable(row) + else: + txt_table.add_row(row) + txt_table.align["Test case"] = "l" + with open(txt_file_name, "w") as txt_file: + txt_file.write(str(txt_table))