|  | # Copyright 2017 The Chromium OS Authors. All rights reserved. | 
|  | # Use of this source code is governed by a BSD-style license that can be | 
|  | # found in the LICENSE file. | 
|  | """Helper functions to parse result collected from device""" | 
|  |  | 
|  | from __future__ import print_function | 
|  | from fix_skia_results import _TransformBenchmarks | 
|  |  | 
|  | import json | 
|  |  | 
|  | def normalize(bench, dict_list): | 
|  | bench_base = { | 
|  | 'Panorama': 1, | 
|  | 'Dex2oat': 1, | 
|  | 'Hwui': 10000, | 
|  | 'Skia': 1, | 
|  | 'Synthmark': 1, | 
|  | 'Binder': 0.001 | 
|  | } | 
|  | result_dict = dict_list[0] | 
|  | for key in result_dict: | 
|  | result_dict[key] = result_dict[key] / bench_base[bench] | 
|  | return [result_dict] | 
|  |  | 
|  |  | 
|  | # Functions to parse benchmark result for data collection. | 
|  | def parse_Panorama(bench, fin): | 
|  | result_dict = {} | 
|  | for line in fin: | 
|  | words = line.split() | 
|  | if 'elapsed' in words: | 
|  | #TODO: Need to restructure the embedded word counts. | 
|  | result_dict['total_time_s'] = float(words[3]) | 
|  | result_dict['retval'] = 0 | 
|  | return normalize(bench, [result_dict]) | 
|  | raise ValueError('You passed the right type of thing, ' | 
|  | 'but it didn\'t have the expected contents.') | 
|  |  | 
|  |  | 
|  | def parse_Synthmark(bench, fin): | 
|  | result_dict = {} | 
|  | accum = 0 | 
|  | cnt = 0 | 
|  | for line in fin: | 
|  | words = line.split() | 
|  | if 'normalized' in words: | 
|  | #TODO: Need to restructure the embedded word counts. | 
|  | accum += float(words[-1]) | 
|  | cnt += 1 | 
|  | if accum != 0: | 
|  | result_dict['total_voices'] = accum / cnt | 
|  | result_dict['retval'] = 0 | 
|  | return normalize(bench, [result_dict]) | 
|  | raise ValueError('You passed the right type of thing, ' | 
|  | 'but it didn\'t have the expected contents.') | 
|  |  | 
|  |  | 
|  | def parse_Binder(bench, fin): | 
|  | result_dict = {} | 
|  | accum = 0 | 
|  | cnt = 0 | 
|  | for line in fin: | 
|  | words = line.split() | 
|  | for word in words: | 
|  | if 'average' in word: | 
|  | #TODO: Need to restructure the embedded word counts. | 
|  | accum += float(word[8:-2]) | 
|  | cnt += 1 | 
|  | if accum != 0: | 
|  | result_dict['avg_time_ms'] = accum / cnt | 
|  | result_dict['retval'] = 0 | 
|  | return normalize(bench, [result_dict]) | 
|  | raise ValueError('You passed the right type of thing, ' | 
|  | 'but it didn\'t have the expected contents.') | 
|  |  | 
|  |  | 
|  | def parse_Dex2oat(bench, fin): | 
|  | result_dict = {} | 
|  | cnt = 0 | 
|  | for line in fin: | 
|  | words = line.split() | 
|  | if 'elapsed' in words: | 
|  | cnt += 1 | 
|  | #TODO: Need to restructure the embedded word counts. | 
|  | if cnt == 1: | 
|  | # First 'elapsed' time is for microbench 'Chrome' | 
|  | result_dict['chrome_s'] = float(words[3]) | 
|  | elif cnt == 2: | 
|  | # Second 'elapsed' time is for microbench 'Camera' | 
|  | result_dict['camera_s'] = float(words[3]) | 
|  |  | 
|  | result_dict['retval'] = 0 | 
|  | # Two results found, return | 
|  | return normalize(bench, [result_dict]) | 
|  | raise ValueError('You passed the right type of thing, ' | 
|  | 'but it didn\'t have the expected contents.') | 
|  |  | 
|  |  | 
|  | def parse_Hwui(bench, fin): | 
|  | result_dict = {} | 
|  | for line in fin: | 
|  | words = line.split() | 
|  | if 'elapsed' in words: | 
|  | #TODO: Need to restructure the embedded word counts. | 
|  | result_dict['total_time_s'] = float(words[3]) | 
|  | result_dict['retval'] = 0 | 
|  | return normalize(bench, [result_dict]) | 
|  | raise ValueError('You passed the right type of thing, ' | 
|  | 'but it didn\'t have the expected contents.') | 
|  |  | 
|  |  | 
|  | def parse_Skia(bench, fin): | 
|  | obj = json.load(fin) | 
|  | return normalize(bench, _TransformBenchmarks(obj)) |