+++ /dev/null
-# Copyright (c) 2019 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:
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""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 (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.
-If number of tests does not match, or there was a regression,
-this script votes -1 (by exiting with code 1), otherwise it votes +1 (exit 0).
-"""
-
-import json
-import sys
-
-from jumpavg.BitCountingMetadataFactory import BitCountingMetadataFactory
-from jumpavg.BitCountingClassifier import BitCountingClassifier
-
-
-def hack(value_list):
- """Return middle two quartiles, hoping to reduce influence of outliers.
-
- Currently "middle two" is "all", but that can change in future.
-
- :param value_list: List to pick subset from.
- :type value_list: list of float
- :returns: New list containing middle values.
- :rtype: list of float
- """
- tmp = sorted(value_list)
- eight = len(tmp) / 8
- ret = tmp[3*eight:-eight]
- return tmp # ret
-
-
-iteration = -1
-parent_iterations = list()
-current_iterations = list()
-num_tests = None
-while 1:
- iteration += 1
- parent_lines = list()
- current_lines = list()
- filename = f"csit_parent/{iteration}/results.txt"
- try:
- with open(filename) as parent_file:
- parent_lines = parent_file.readlines()
- except IOError:
- break
- num_lines = len(parent_lines)
- filename = f"csit_current/{iteration}/results.txt"
- with open(filename) as current_file:
- current_lines = current_file.readlines()
- if num_lines != len(current_lines):
- print(f"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(
- f"Number of tests does not match previous at iteration {iteration}"
- )
- sys.exit(1)
- parent_iterations.append(parent_lines)
- current_iterations.append(current_lines)
-classifier = BitCountingClassifier()
-exit_code = 0
-for test_index in range(num_tests):
- val_max = 1.0
- parent_values = list()
- current_values = list()
- for iteration_index in range(len(parent_iterations)):
- parent_values.extend(
- json.loads(parent_iterations[iteration_index][test_index])
- )
- current_values.extend(
- json.loads(current_iterations[iteration_index][test_index])
- )
- print(f"Time-ordered MRR values for parent build: {parent_values}")
- print(f"Time-ordered MRR values for current build: {current_values}")
- parent_values = hack(parent_values)
- current_values = hack(current_values)
- parent_max = BitCountingMetadataFactory.find_max_value(parent_values)
- current_max = BitCountingMetadataFactory.find_max_value(current_values)
- val_max = max(val_max, parent_max, current_max)
- factory = BitCountingMetadataFactory(val_max)
- parent_stats = factory.from_data(parent_values)
- current_factory = BitCountingMetadataFactory(val_max, parent_stats.avg)
- current_stats = current_factory.from_data(current_values)
- both_stats = factory.from_data(parent_values + current_values)
- print(f"Value-ordered MRR values for parent build: {parent_values}")
- print(f"Value-ordered MRR values for current build: {current_values}")
- difference = (current_stats.avg - parent_stats.avg) / parent_stats.avg
- print(f"Difference of averages relative to parent: {100 * difference}%")
- print(f"Jumpavg representation of parent group: {parent_stats}")
- print(f"Jumpavg representation of current group: {current_stats}")
- print(f"Jumpavg representation of both as one group: {both_stats}")
- bits = parent_stats.bits + current_stats.bits - both_stats.bits
- compared = u"longer" if bits >= 0 else u"shorter"
- print(
- f"Separate groups are {compared} than single group by {abs(bits)} bits"
- )
- classified_list = classifier.classify([parent_stats, current_stats])
- if len(classified_list) < 2:
- print(f"Test test_index {test_index}: normal (no anomaly)")
- continue
- anomaly = classified_list[1].metadata.classification
- if anomaly == u"regression":
- print(f"Test test_index {test_index}: anomaly regression")
- exit_code = 1
- continue
- print(f"Test test_index {test_index}: anomaly {anomaly}")
-print(f"Exit code {exit_code}")
-sys.exit(exit_code)
Code Review / csit.git / blobdiff