#!/usr/bin/env python3
import argparse
import logging
import sys
from util.color_logger import get_logger
from util.datamodel_helper import create_db_session, load_file_in_db, save_file_as_json
logger = get_logger('merge_results')
if __name__ == "__main__":
# Parse Command-line Arguments
parser = argparse.ArgumentParser(
description='Merge benchmark results into one file',
formatter_class=lambda prog: argparse.HelpFormatter(
prog, max_help_position=30, width=120))
parser.add_argument('infile',
metavar='INFILE',
nargs="+",
type=argparse.FileType('r'),
help='file where the benchmarks are merged into')
parser.add_argument('outfile',
metavar='OUTFILE',
type=argparse.FileType('x'),
help='file where the benchmarks are merged into')
parser.add_argument(
'--database',
default='sqlite://',
type=str,
import functools
import re
import numpy
from util.color_logger import get_logger
logger = get_logger('plot')
def calculate_stat_from_array(array):
if len(array) == 0:
return {}
res_dict = {}
for type in array[0]:
tmp_arr = numpy.array([r[type] for r in array
]) # TODO: support runs with different types
tmp_mean = numpy.mean(tmp_arr)
if tmp_mean == 0:
logger.error('no correct baseline calculated for', type)
continue
res_dict[type] = {'mean': tmp_mean}
return res_dict
def preprocess(results, baseline, filter_runtime='.*', filter_benchmark='.*'):
#!/usr/bin/env python3
import argparse
import logging
import sys
from util.bench_results import BenchmarkingResults
from util.color_logger import get_logger
logger = get_logger('stats')
def log_general_stats(results):
logger.info("number of different benchmarks present: %d",
len(results.get_all_benchmark_names()))
for runtime in sorted(results.get_all_runtimes()):
logger.info('runtime "%s" has %d benchmarks', runtime,
len(list(results.get_all_benchmarks_of_runtime(runtime))))
missing_benchmarks = results.get_missing_benchmark_names(runtime)
if missing_benchmarks:
logger.warning(' missing: %s', missing_benchmarks)
if __name__ == "__main__":
# Parse Command-line Arguments
parser = argparse.ArgumentParser(
description='Evaluate benchmark results',
formatter_class=lambda prog: argparse.HelpFormatter(
prog, max_help_position=30, width=120))
import platform
import re
import subprocess
import sys
import tempfile
from datetime import datetime
from util.color_logger import get_logger
from util.console import query_yes_no
import util.datamodel as dm
from util.datamodel_helper import create_db_session, load_file_in_db, save_file_as_json,\
get_benchmark_name, get_or_create_config, get_or_create_harness, get_or_create_benchmark
logger = get_logger('bench')
try:
import psutil
psutil_imported = True
except ImportError:
psutil_imported = False
logger.warning("psutil not installed, will skip system related metadata")
BASE_DIR = os.path.abspath(os.path.join(sys.path[0], '..'))
BENCHMARK_DIR = os.path.join(BASE_DIR, 'benchmarks')
CONFIG_DIR = os.path.join(BASE_DIR, 'configs')
ENV_FILE = os.path.join(CONFIG_DIR, 'env')
#!/usr/bin/env python3
import argparse
import csv
import logging
import sys
import re
from sqlalchemy.orm import joinedload
from util.color_logger import get_logger
import util.datamodel as dm
from util.datamodel_helper import create_db_session, load_file_in_db
logger = get_logger('extract_gcov')
CSV_BENCHMARK_NAME = 'benchmark name'
CSV_FILE_NAME = 'file name'
CSV_EXECUTED_LOC = 'executed LOC'
CSV_TOTAL_LOC = 'total LOC'
def parse_gcov_output(benchmark_name, output):
lines = output.splitlines()
for i in range(0, len(lines), 3):
file_matcher = re.match("File '(.*)'", lines[i])
loc_matcher = re.match("Lines executed:(.*)% of ([0-9]*)",
lines[i + 1])
file_name = file_matcher.group(1)
if loc_matcher is None:
assert (lines[i + 1] == 'No executable lines')
import json
import re
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker, joinedload
from dateutil.parser import parse as date_parse
import util.datamodel as dm
from util.color_logger import get_logger
from util.auto_extend_list import auto_extend_list
from datetime import timezone
logger = get_logger('datamodel_helper')
def create_db_session(db_engine='sqlite://'):
logger.debug('create database session. Engine: "{}"'.format(db_engine))
engine = create_engine(db_engine)
dm.Base.metadata.bind = engine
dm.Base.metadata.create_all(engine)
DBSession = sessionmaker()
DBSession.bind = engine
return DBSession()
def get_benchmark_name(benchmark):
fixture = benchmark.get('fixture')
