# Copyright 2013 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import collections
from metrics import Metric
from telemetry.core import bitmap
from telemetry.value import scalar
class SpeedIndexMetric(Metric):
"""The speed index metric is one way of measuring page load speed.
It is meant to approximate user perception of page load speed, and it
is based on the amount of time that it takes to paint to the visual
portion of the screen. It includes paint events that occur after the
onload event, and it doesn't include time loading things off-screen.
This speed index metric is based on WebPageTest.org (WPT).
For more info see: http://goo.gl/e7AH5l
"""
def __init__(self):
super(SpeedIndexMetric, self).__init__()
self._impl = None
@classmethod
def CustomizeBrowserOptions(cls, options):
options.AppendExtraBrowserArgs('--disable-infobars')
def Start(self, _, tab):
"""Start recording events.
This method should be called in the WillNavigateToPage method of
a PageTest, so that all the events can be captured. If it's called
in DidNavigateToPage, that will be too late.
"""
self._impl = (VideoSpeedIndexImpl() if tab.video_capture_supported else
PaintRectSpeedIndexImpl())
self._impl.Start(tab)
def Stop(self, _, tab):
"""Stop timeline recording."""
assert self._impl, 'Must call Start() before Stop()'
assert self.IsFinished(tab), 'Must wait for IsFinished() before Stop()'
self._impl.Stop(tab)
# Optional argument chart_name is not in base class Metric.
# pylint: disable=W0221
def AddResults(self, tab, results, chart_name=None):
"""Calculate the speed index and add it to the results."""
index = self._impl.CalculateSpeedIndex(tab)
# Release the tab so that it can be disconnected.
self._impl = None
results.AddValue(scalar.ScalarValue(
results.current_page, '%s.speed_index' % chart_name, 'ms', index))
def IsFinished(self, tab):
"""Decide whether the timeline recording should be stopped.
When the timeline recording is stopped determines which paint events
are used in the speed index metric calculation. In general, the recording
should continue if there has just been some data received, because
this suggests that painting may continue.
A page may repeatedly request resources in an infinite loop; a timeout
should be placed in any measurement that uses this metric, e.g.:
def IsDone():
return self._speedindex.IsFinished(tab)
util.WaitFor(IsDone, 60)
Returns:
True if 2 seconds have passed since last resource received, false
otherwise.
"""
return tab.HasReachedQuiescence()
class SpeedIndexImpl(object):
def Start(self, tab):
raise NotImplementedError()
def Stop(self, tab):
raise NotImplementedError()
def GetTimeCompletenessList(self, tab):
"""Returns a list of time to visual completeness tuples.
In the WPT PHP implementation, this is also called 'visual progress'.
"""
raise NotImplementedError()
def CalculateSpeedIndex(self, tab):
"""Calculate the speed index.
The speed index number conceptually represents the number of milliseconds
that the page was "visually incomplete". If the page were 0% complete for
1000 ms, then the score would be 1000; if it were 0% complete for 100 ms
then 90% complete (ie 10% incomplete) for 900 ms, then the score would be
1.0*100 + 0.1*900 = 190.
Returns:
A single number, milliseconds of visual incompleteness.
"""
time_completeness_list = self.GetTimeCompletenessList(tab)
prev_completeness = 0.0
speed_index = 0.0
prev_time = time_completeness_list[0][0]
for time, completeness in time_completeness_list:
# Add the incemental value for the interval just before this event.
elapsed_time = time - prev_time
incompleteness = (1.0 - prev_completeness)
speed_index += elapsed_time * incompleteness
# Update variables for next iteration.
prev_completeness = completeness
prev_time = time
return int(speed_index)
class VideoSpeedIndexImpl(SpeedIndexImpl):
def __init__(self):
super(VideoSpeedIndexImpl, self).__init__()
self._time_completeness_list = None
def Start(self, tab):
assert tab.video_capture_supported
# Blank out the current page so it doesn't count towards the new page's
# completeness.
tab.Highlight(bitmap.WHITE)
# TODO(tonyg): Bitrate is arbitrary here. Experiment with screen capture
# overhead vs. speed index accuracy and set the bitrate appropriately.
tab.StartVideoCapture(min_bitrate_mbps=4)
def Stop(self, tab):
# Ignore white because Chrome may blank out the page during load and we want
# that to count as 0% complete. Relying on this fact, we also blank out the
# previous page to white. The tolerance of 8 experimentally does well with
# video capture at 4mbps. We should keep this as low as possible with
# supported video compression settings.
video_capture = tab.StopVideoCapture()
histograms = [(time, bmp.ColorHistogram(ignore_color=bitmap.WHITE,
tolerance=8))
for time, bmp in video_capture.GetVideoFrameIter()]
start_histogram = histograms[0][1]
final_histogram = histograms[-1][1]
total_distance = start_histogram.Distance(final_histogram)
def FrameProgress(histogram):
if total_distance == 0:
if histogram.Distance(final_histogram) == 0:
return 1.0
else:
return 0.0
return 1 - histogram.Distance(final_histogram) / total_distance
self._time_completeness_list = [(time, FrameProgress(hist))
for time, hist in histograms]
def GetTimeCompletenessList(self, tab):
assert self._time_completeness_list, 'Must call Stop() first.'
return self._time_completeness_list
class PaintRectSpeedIndexImpl(SpeedIndexImpl):
def __init__(self):
super(PaintRectSpeedIndexImpl, self).__init__()
def Start(self, tab):
tab.StartTimelineRecording()
def Stop(self, tab):
tab.StopTimelineRecording()
def GetTimeCompletenessList(self, tab):
events = tab.timeline_model.GetAllEvents()
viewport = self._GetViewportSize(tab)
paint_events = self._IncludedPaintEvents(events)
time_area_dict = self._TimeAreaDict(paint_events, viewport)
total_area = sum(time_area_dict.values())
assert total_area > 0.0, 'Total paint event area must be greater than 0.'
completeness = 0.0
time_completeness_list = []
# TODO(tonyg): This sets the start time to the start of the first paint
# event. That can't be correct. The start time should be navigationStart.
# Since the previous screen is not cleared at navigationStart, we should
# probably assume the completeness is 0 until the first paint and add the
# time of navigationStart as the start. We need to confirm what WPT does.
time_completeness_list.append(
(tab.timeline_model.GetAllEvents()[0].start, completeness))
for time, area in sorted(time_area_dict.items()):
completeness += float(area) / total_area
# Visual progress is rounded to the nearest percentage point as in WPT.
time_completeness_list.append((time, round(completeness, 2)))
return time_completeness_list
def _GetViewportSize(self, tab):
"""Returns dimensions of the viewport."""
return tab.EvaluateJavaScript('[ window.innerWidth, window.innerHeight ]')
def _IncludedPaintEvents(self, events):
"""Get all events that are counted in the calculation of the speed index.
There's one category of paint event that's filtered out: paint events
that occur before the first 'ResourceReceiveResponse' and 'Layout' events.
Previously in the WPT speed index, paint events that contain children paint
events were also filtered out.
"""
def FirstLayoutTime(events):
"""Get the start time of the first layout after a resource received."""
has_received_response = False
for event in events:
if event.name == 'ResourceReceiveResponse':
has_received_response = True
elif has_received_response and event.name == 'Layout':
return event.start
assert False, 'There were no layout events after resource receive events.'
first_layout_time = FirstLayoutTime(events)
paint_events = [e for e in events
if e.start >= first_layout_time and e.name == 'Paint']
return paint_events
def _TimeAreaDict(self, paint_events, viewport):
"""Make a dict from time to adjusted area value for events at that time.
The adjusted area value of each paint event is determined by how many paint
events cover the same rectangle, and whether it's a full-window paint event.
"Adjusted area" can also be thought of as "points" of visual completeness --
each rectangle has a certain number of points and these points are
distributed amongst the paint events that paint that rectangle.
Args:
paint_events: A list of paint events
viewport: A tuple (width, height) of the window.
Returns:
A dictionary of times of each paint event (in milliseconds) to the
adjusted area that the paint event is worth.
"""
width, height = viewport
fullscreen_area = width * height
def ClippedArea(rectangle):
"""Returns rectangle area clipped to viewport size."""
_, x0, y0, x1, y1 = rectangle
clipped_width = max(0, min(width, x1) - max(0, x0))
clipped_height = max(0, min(height, y1) - max(0, y0))
return clipped_width * clipped_height
grouped = self._GroupEventByRectangle(paint_events)
event_area_dict = collections.defaultdict(int)
for rectangle, events in grouped.items():
# The area points for each rectangle are divided up among the paint
# events in that rectangle.
area = ClippedArea(rectangle)
update_count = len(events)
adjusted_area = float(area) / update_count
# Paint events for the largest-area rectangle are counted as 50%.
if area == fullscreen_area:
adjusted_area /= 2
for event in events:
# The end time for an event is used for that event's time.
event_time = event.end
event_area_dict[event_time] += adjusted_area
return event_area_dict
def _GetRectangle(self, paint_event):
"""Get the specific rectangle on the screen for a paint event.
Each paint event belongs to a frame (as in html or