Chromium Code Reviews| Index: tools/android/customtabs_benchmark/scripts/customtabs_benchmark.py |
| diff --git a/tools/android/customtabs_benchmark/scripts/customtabs_benchmark.py b/tools/android/customtabs_benchmark/scripts/customtabs_benchmark.py |
| index bd141fac28fce7a3bef5ddbbf8162cb48fd90742..1811c6dab30a48cb5662dab9ec8ff3006faeaea9 100755 |
| --- a/tools/android/customtabs_benchmark/scripts/customtabs_benchmark.py |
| +++ b/tools/android/customtabs_benchmark/scripts/customtabs_benchmark.py |
| @@ -41,7 +41,7 @@ _INVALID_VALUE = -1 |
| # Command line arguments for Chrome. |
| -_CHROME_ARGS = [ |
| +CHROME_ARGS = [ |
| # Disable backgound network requests that may pollute WPR archive, pollute |
| # HTTP cache generation, and introduce noise in loading performance. |
| '--disable-background-networking', |
| @@ -133,11 +133,10 @@ def RunOnce(device, url, warmup, speculation_mode, delay_to_may_launch_url, |
| return match.group(1) if match is not None else None |
| -Result = collections.namedtuple('Result', ['warmup', 'speculation_mode', |
| - 'delay_to_may_launch_url', |
| - 'delay_to_launch_url', |
| - 'commit', 'plt', |
| - 'first_contentful_paint']) |
| +RESULT_FIELDS = ('warmup', 'speculation_mode', 'delay_to_may_launch_url', |
| + 'delay_to_launch_url', 'commit', 'plt', |
| + 'first_contentful_paint') |
| +Result = collections.namedtuple('Result', RESULT_FIELDS) |
| def ParseResult(result_line): |
| @@ -181,7 +180,7 @@ def LoopOnDevice(device, configs, output_filename, wpr_archive_path=None, |
| try: |
| while should_stop is None or not should_stop.is_set(): |
| config = configs[random.randint(0, len(configs) - 1)] |
| - chrome_args = _CHROME_ARGS + wpr_attributes.chrome_args |
| + chrome_args = CHROME_ARGS + wpr_attributes.chrome_args |
| if config['speculation_mode'] == 'no_state_prefetch': |
| # NoStatePrefetch is enabled through an experiment. |
| chrome_args.extend([ |
| @@ -218,7 +217,7 @@ def ProcessOutput(filename): |
| A numpy structured array. |
| """ |
| import numpy as np |
| - data = np.genfromtxt(filename, delimiter=',') |
| + data = np.genfromtxt(filename, delimiter=',', skip_header=1) |
|
pasko
2016/12/14 19:38:33
is this function going to be used somewhere?
The
Benoit L
2016/12/16 14:27:00
It is used for the analysis.
Acknowledged.
|
| result = np.array(np.zeros(len(data)), |
| dtype=[('warmup', bool), ('speculation_mode', np.int32), |
| ('delay_to_may_launch_url', np.int32), |