X-Git-Url: https://gerrit.fd.io/r/gitweb?a=blobdiff_plain;f=resources%2Ftools%2Fscripts%2Fcompare_perpatch.py;h=1f8a1cf89250bb79abdbd59af2c5e7a4a8394474;hb=d465d9fba33a323703a2bf40c499d74d0f017091;hp=cc9ffd89923e7a5abd7e0fdd8afb45d397665889;hpb=7db6faf25da39820d321222f7f8fcb191585add9;p=csit.git diff --git a/resources/tools/scripts/compare_perpatch.py b/resources/tools/scripts/compare_perpatch.py index cc9ffd8992..1f8a1cf892 100644 --- a/resources/tools/scripts/compare_perpatch.py +++ b/resources/tools/scripts/compare_perpatch.py @@ -14,7 +14,7 @@ """Script for determining whether per-patch perf test votes -1. This script assumes there exist two text files with processed BMRR results, -located at hardcoded relative paths, having several lines +located at hardcoded relative paths (subdirs thereof), having several lines of json-parseable lists of float values, corresponding to testcase results. This script then uses jumpavg library to determine whether there was a regression, progression or no change for each testcase. @@ -38,32 +38,62 @@ def hack(value_list): :rtype: list of float """ tmp = sorted(value_list) - quarter = len(tmp) / 4 - ret = tmp[quarter:-quarter] + eight = len(tmp) / 8 + ret = tmp[3*eight:-eight] return ret -parent_lines = list() -new_lines = list() -with open("csit_parent/results.txt") as parent_file: - parent_lines = parent_file.readlines() -with open("csit_new/results.txt") as new_file: - new_lines = new_file.readlines() -if len(parent_lines) != len(new_lines): - print "Number of passed tests does not match!" - sys.exit(1) +iteration = -1 +parent_iterations = list() +new_iterations = list() +num_tests = None +while 1: + iteration += 1 + parent_lines = list() + new_lines = list() + filename = "csit_parent/{iter}/results.txt".format(iter=iteration) + try: + with open(filename) as parent_file: + parent_lines = parent_file.readlines() + except IOError: + break + num_lines = len(parent_lines) + filename = "csit_new/{iter}/results.txt".format(iter=iteration) + with open(filename) as new_file: + new_lines = new_file.readlines() + if num_lines != len(new_lines): + print "Number of tests does not match within iteration", iteration + sys.exit(1) + if num_tests is None: + num_tests = num_lines + elif num_tests != num_lines: + print "Number of tests does not match previous at iteration", iteration + sys.exit(1) + parent_iterations.append(parent_lines) + new_iterations.append(new_lines) classifier = BitCountingClassifier() -num_tests = len(parent_lines) exit_code = 0 -for index in range(num_tests): - parent_values = hack(json.loads(parent_lines[index])) - new_values = hack(json.loads(new_lines[index])) +for test_index in range(num_tests): + val_max = 1.0 + parent_values = list() + new_values = list() + for iteration_index in range(len(parent_iterations)): + parent_values.extend( + json.loads(parent_iterations[iteration_index][test_index])) + new_values.extend( + json.loads(new_iterations[iteration_index][test_index])) + print "TRACE pre-hack parent: {p}".format(p=parent_values) + print "TRACE pre-hack new: {n}".format(n=new_values) + parent_values = hack(parent_values) + new_values = hack(new_values) parent_max = BitCountingMetadataFactory.find_max_value(parent_values) new_max = BitCountingMetadataFactory.find_max_value(new_values) - cmax = max(parent_max, new_max) - factory = BitCountingMetadataFactory(cmax) + val_max = max(val_max, parent_max, new_max) + factory = BitCountingMetadataFactory(val_max) parent_stats = factory.from_data(parent_values) - factory = BitCountingMetadataFactory(cmax, parent_stats.avg) - new_stats = factory.from_data(new_values) + new_factory = BitCountingMetadataFactory(val_max, parent_stats.avg) + new_stats = new_factory.from_data(new_values) + print "TRACE parent: {p}".format(p=parent_values) + print "TRACE new: {n}".format(n=new_values) print "DEBUG parent: {p}".format(p=parent_stats) print "DEBUG new: {n}".format(n=new_stats) common_max = max(parent_stats.avg, new_stats.avg) @@ -71,15 +101,16 @@ for index in range(num_tests): print "DEBUG difference: {d}%".format(d=100 * difference) classified_list = classifier.classify([parent_stats, new_stats]) if len(classified_list) < 2: - print "Test index {index}: normal (no anomaly)".format( - index=index) + print "Test test_index {test_index}: normal (no anomaly)".format( + test_index=test_index) continue anomaly = classified_list[1].metadata.classification if anomaly == "regression": - print "Test index {index}: anomaly regression".format(index=index) + print "Test test_index {test_index}: anomaly regression".format( + test_index=test_index) exit_code = 1 continue - print "Test index {index}: anomaly {anomaly}".format( - index=index, anomaly=anomaly) + print "Test test_index {test_index}: anomaly {anomaly}".format( + test_index=test_index, anomaly=anomaly) print "DEBUG exit code {code}".format(code=exit_code) sys.exit(exit_code)