blob: c8af55d978ce46b72bcaa3d7c90398303f9a7dbc [file] [log] [blame]
# Copyright (c) 2014 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.
# Compute the touchpad drag latency
# This script computed the touch drag-latency given an evtest log and a
# Quickstep log that were collected while moving a finger at a fixed speed
# back and forth over the laser beam on the pad. It generates the numeric
# calculations (in seconds) as well as an image that visualizes the data
# for debugging purposes. This image is useful if the results are surprising,
# as it will often make it very obvious what the issue was.
# Usage:
# 1.) Align the Quickstep laser horizontally across the device. Make sure
# that the beam is low across the surface and squarely centered on the
# receiever.
# 2.) Begin evtest log collection while nothing is touching the device.
# evtest > evtest_log.txt
# 3.) Move a single finger at a constant speed back and forth over the laser
# on the pad at least 20 times. A robot will be able to produce more
# consistent results than a hand.
# 4.) Save a copy of the Quickstep log by accessing its "laser" sysfs entry
# find / -name 'laser'
# cat $the_file_you_found_above > quickstep_log.txt
# 5.) Crunch the numbers by passing both file names to this script
# python evtest_log.txt quickstep_log.txt
import commands
import json
import numpy as np
import re
import sys
from collections import namedtuple
import ppm
FingerPosition = namedtuple('FingerPosition', ['timestamp', 'x', 'y'])
LaserCrossing = namedtuple('LaserCrossing', ['timestamp', 'direction'])
def get_evtest_timestamp(line):
return float(line.split(',')[0].split(' ')[-1])
def get_evtest_value(line):
return int(line.split(' ')[-1])
def get_finger_positions(filename):
""" Parse the finger positions out of an evtest log
This only works with a single contact.
Returns a list of FingerPosition objects
log = open(filename, 'r')
if not log:
return None
points = []
fingers = {}
curr_id = -1
last_x = last_y = 0
for line in log:
if not line.startswith('Event: '):
if 'ABS_MT_TRACKING_ID' in line:
curr_id = get_evtest_value(line)
if not fingers.get(curr_id, None):
fingers[curr_id] = {}
elif 'ABS_MT_POSITION_X' in line:
fingers[curr_id]['x'] = get_evtest_value(line)
elif 'ABS_MT_POSITION_Y' in line:
fingers[curr_id]['y'] = get_evtest_value(line)
elif 'SYN' in line and curr_id != -1 and curr_id in fingers:
t = get_evtest_timestamp(line)
last_x = x = fingers[curr_id].get('x', last_x)
last_y = y = fingers[curr_id].get('y', last_y)
points.append(FingerPosition(t, x, y))
return points
def get_laser_crossings(filename):
""" Parse out the laser crossing events from a Quickstep log
Returns a list of LaserCrossing events
QUICKSTEP_LOG_REGEX = '^\s*([\d.]+)\s+(\d)\s*$'
status, raw_log = commands.getstatusoutput('cat %s' % filename)
if status:
return None
laser_crossings = []
for line in raw_log.splitlines():
matches = re.match(QUICKSTEP_LOG_REGEX, line)
if matches and len(matches.groups()) == 2:
timestamp = float(
direction = int(
laser_crossings.append(LaserCrossing(timestamp, direction))
return laser_crossings
def clip_timeframes(positions, laser_crossings):
""" Clip both lists of events so they only contain events that occurred
during the period of time that *both* logs were being generated.
Returns the clipped lists
if not positions or not laser_crossings:
return [], []
touchpad_start = positions[0].timestamp
touchpad_end = positions[-1].timestamp
laser_start = laser_crossings[0].timestamp
laser_end = laser_crossings[-1].timestamp
positions = [p for p in positions
if (p.timestamp <= laser_end and p.timestamp >= laser_start)]
laser_crossings = [q for q in laser_crossings
if (q.timestamp <= touchpad_end and
q.timestamp >= touchpad_start)]
return positions, laser_crossings
def get_laser_crossing_points(positions, laser_crossings):
""" Find the touchpad readings at the moment the laser was crossed for each
laser crossing event. Since the timestamps will not likely line up
perfectly, the exact position is interpolated between the two positions
read before and after the laser was crossed.
Returns a list of TouchpadPosition events
crossing_points = []
for crossing in laser_crossings:
for i, position in enumerate(positions):
if i == 0:
if position.timestamp > crossing.timestamp:
# interpolate, since they won't line up perfectly
time_gap = (position.timestamp - positions[i - 1].timestamp)
before_weight = ((position.timestamp - crossing.timestamp) /
after_weight = 1.0 - before_weight
(positions[i - 1].x * before_weight +
position.x * after_weight),
(positions[i - 1].y * before_weight +
position.y * after_weight)
return crossing_points
def estimate_laser_line(laser_crossings):
""" Estimate the position of the line defined by the laser on the pad
Given the touchpad readings on either side of the line that were generated
at the moment the laser was crossed, you can fit a line to them and
discover where the line is inbetween then.
Returns a np.poly1d representation of the line
line = np.poly1d(np.polyfit([x for t, x, y in laser_crossings],
[y for t, x, y in laser_crossings],
return line
def which_side(line, coords):
""" Indicates which side of a line a given point lies on """
distance = line(coords.x) - coords.y
if abs(distance) <= 2: return 0
elif distance > 0: return 1
else: return -1
def get_touchpad_crossing_points(positions, line):
""" Find the touchpad readings of where it finally crossed the line formed
by the laser. These are the points that the user would see, and are likely
delayed somewhat, which is what we will try to measure.
Returns a list of TouchpadPosition events along the line
last_side = which_side(line, positions[0])
points = []
for i, position in enumerate(positions):
current_side = which_side(line, position)
if current_side != last_side and last_side != 0:
last_side = current_side
return points
def compute_latency(line_positions, laser_positions):
""" Measure how much time passed between the laser being triggered and the
touchpad reporting an event passed the line.
Returns a list of floats corresponding to the latency for each crossing
latencies = []
for (probe_timestamp, _, _), (laser_timestamp, _, _) \
in zip(line_positions, laser_positions):
latencies.append(probe_timestamp - laser_timestamp)
return latencies
def measure_latencies(finger_positions, laser_crossings, filename=None):
positions, laser_crossings = \
clip_timeframes(finger_positions, laser_crossings)
if not positions or not laser_crossings:
print 'ERROR: There are no overlapping events in the input'
return []
# Find the points where the laser was crossed
laser_crossing_points = \
get_laser_crossing_points(positions, laser_crossings)
# Separate those points of two "lines" (the laser essentially defines two)
laser_crossing_points0 = [p for i, p in enumerate(laser_crossing_points)
if int((i + 1) / 2) % 2 == 0]
laser_crossing_points1 = [p for i, p in enumerate(laser_crossing_points)
if int((i + 1) / 2) % 2 == 1]
# Fit a line to them to estimate where the actual laser is
line0 = estimate_laser_line(laser_crossing_points0)
line1 = estimate_laser_line(laser_crossing_points1)
# Find the touchpad positions where the probe actually crossed the "line"
touchpad_crossing_points0 = get_touchpad_crossing_points(positions, line0)
touchpad_crossing_points1 = get_touchpad_crossing_points(positions, line1)
# Actually do the timings against the ideal line
latencies0 = compute_latency(touchpad_crossing_points0,
latencies1 = compute_latency(touchpad_crossing_points1,
if filename:
# Draw everything, and make a picture of the data for debugging
maxx = max([x for t, x, y in positions])
maxy = max([y for t, x, y in positions])
img = ppm.Image(maxx + 50, maxy + 50)
last_x, last_y = None, None
for t, x, y in positions:
img.Circle((x, y), ppm.BLACK, radius=2)
if not last_x is None:
img.Line((last_x, last_y), (x, y), ppm.BLACK)
last_x, last_y = x, y
for t, x, y in touchpad_crossing_points0:
img.Circle((x, y), ppm.BLACK, radius=6)
for t, x, y in touchpad_crossing_points1:
img.Circle((x, y), ppm.BLACK, radius=6)
for i, (t, x, y) in enumerate(laser_crossing_points):
img.Circle((x, y), ppm.BLACK, radius=6)
for i, (t, x, y) in enumerate(laser_crossing_points0):
img.Circle((x, y), ppm.MAGENTA if i % 2 else ppm.RED)
for i, (t, x, y) in enumerate(laser_crossing_points1):
img.Circle((x, y), ppm.YELLOW if i % 2 else ppm.CYAN)
img.Line((0, line0(0)), (maxx + 50, line0(maxx + 50)), ppm.BLUE)
img.Line((0, line1(0)), (maxx + 50, line1(maxx + 50)), ppm.GREEN)
return latencies0 + latencies1
def main(evtest_log_filename, quickstep_log_filename):
positions = get_finger_positions(evtest_log_filename)
laser_crossings = get_laser_crossings(quickstep_log_filename)
latencies = measure_latencies(positions, laser_crossings, 'out.ppm')
if not latencies:
print 'ERROR: Unable to compute any latencies'
# Display the results
print 'Average', 'Maximum', 'Minimum'
print np.average(latencies), max(latencies), min(latencies)
if __name__ == '__main__':
if len(sys.argv) != 3:
print 'Usage: %s evtest_log.txt quickstep_log.txt' % sys.argv[0]
evtest_log_filename = sys.argv[1]
quickstep_log_filename = sys.argv[2]
main(evtest_log_filename, quickstep_log_filename)