def main():
if len(sys.argv) <= 1:
print "Usage: monkeyrunner DroidReplayer.py TRACE_PATH"
print "The trace must be generated from getevent -lt [EVDEV]"
return 1
print "Replay started"
pl = Pipeline()
pl.addStep(dtm.TextFileLineReader(sys.argv[1]))
pl.addStep(dtm.RawTraceParser())
pl.addStep(dtm.MultiTouchTypeAParser())
pl.addStep(dtm.RelativeTimingConverter())
dev = EMonkeyDevice()
pl.addStep(dtm.DeviceAdjuster(dev))
pl.addStep(dtm.FingerDecomposer())
pl.addStep(GestureReplayEventWrapper())
# this step might be necessary for a tablet
# pl.addStep(dtm.TrailScaler(0.8,0.8))
# pl.addStep(dtm.TimeScaler(0.25))
# trouble maker
# pl.addStep(TroubleInjector())
#replayers = [MonkeyHelperReplayer(dev), TroubleReplayer(dev)]
#pl.addStep(CompositeReplayer(replayers))
pl.addStep(MonkeyHelperReplayer(dev))
pl.addStep(dtm.GenericPrinter())
pl.execute()
print "Replay finished"
def main():
if len(sys.argv) <= 1:
print "Usage: monkeyrunner DroidReplayer.py TRACE_PATH"
print "The trace must be generated from getevent -lt [EVDEV]"
return 1
print "Replay started"
pl = Pipeline()
pl.addStep(dtm.TextFileLineReader(sys.argv[1]))
pl.addStep(dtm.RawTraceParser())
pl.addStep(dtm.MultiTouchTypeAParser())
pl.addStep(dtm.RelativeTimingConverter())
dev = EMonkeyDevice()
pl.addStep(dtm.DeviceAdjuster(dev))
pl.addStep(dtm.FingerDecomposer())
pl.addStep(GestureReplayEventWrapper())
# this step might be necessary for a tablet
# pl.addStep(dtm.TrailScaler(0.8,0.8))
# pl.addStep(dtm.TimeScaler(0.25))
# trouble maker
# pl.addStep(TroubleInjector())
#replayers = [MonkeyHelperReplayer(dev), TroubleReplayer(dev)]
#pl.addStep(CompositeReplayer(replayers))
pl.addStep(MonkeyHelperReplayer(dev))
pl.addStep(dtm.GenericPrinter())
pl.execute()
print "Replay finished"
def main():
# capture three samples and automatically scrolls five times
SAMPLE_COUNT = 3
REPEAT_COUNT = 5
print "learning the pace of scrolling"
pl = Pipeline()
reader = LiveGeteventReader()
pl.addStep(reader)
pl.addStep(dtm.RawTraceParser())
pl.addStep(dtm.MultiTouchTypeAParser())
pl.addStep(dtm.RelativeTimingConverter())
pl.addStep(dtm.FingerDecomposer())
learner = AutoScrollingLearner(reader, SAMPLE_COUNT)
pl.addStep(learner)
pl.execute()
(waitTime, xdelta, ydelta, duration, pointCount) = learner.getSpeedAndDelta()
print "User scrolling parameters learned"
device = EMonkeyDevice()
(xmiddle, ymiddle) = (device.displayWidth / 2, device.displayHeight / 2)
start = (xmiddle - xdelta / 2, ymiddle - ydelta / 2)
end = (xmiddle + xdelta / 2, ymiddle + ydelta / 2)
for _ in range(REPEAT_COUNT):
device.sleep(waitTime)
device.drag(start, end, duration, pointCount)
print 'done'
def main():
# capture three samples and automatically scrolls five times
SAMPLE_COUNT = 3
REPEAT_COUNT = 5
print "learning the pace of scrolling"
pl = Pipeline()
reader = LiveGeteventReader()
pl.addStep(reader)
pl.addStep(dtm.RawTraceParser())
pl.addStep(dtm.MultiTouchTypeAParser())
pl.addStep(dtm.RelativeTimingConverter())
pl.addStep(dtm.FingerDecomposer())
learner = AutoScrollingLearner(reader, SAMPLE_COUNT)
pl.addStep(learner)
pl.execute()
(waitTime, xdelta, ydelta, duration,
pointCount) = learner.getSpeedAndDelta()
print "User scrolling parameters learned"
device = EMonkeyDevice()
(xmiddle, ymiddle) = (device.displayWidth / 2, device.displayHeight / 2)
start = (xmiddle - xdelta / 2, ymiddle - ydelta / 2)
end = (xmiddle + xdelta / 2, ymiddle + ydelta / 2)
for _ in range(REPEAT_COUNT):
device.sleep(waitTime)
device.drag(start, end, duration, pointCount)
print 'done'
def main():
print "Replay started"
pl = Pipeline()
pl.addStep(EventGenerator(interval=3000, number=1000))
pl.addStep(TroubleInjector())
dev = dm.getDevice()
pl.addStep(TroubleReplayer(dev))
pl.execute()
print "Replay finished"
def main():
print "Replay started"
pl = Pipeline()
pl.addStep(EventGenerator(interval=3000,number=1000))
pl.addStep(TroubleInjector())
dev = dm.getDevice()
pl.addStep(TroubleReplayer(dev))
pl.execute()
print "Replay finished"
begin_time = cur_time()
rand.seed(seed_)
for iter_ in range(iterations):
print('Computing iteration %d of %d, time=%f.' %
(iter_ + 1, iterations, (cur_time() - begin_time) / 60))
data = getExperimentsFromParameterRanges(
methodNames_parameters, list_of_splits, list_of_systemCounts,
list_of_entityCounts, list_of_signValues, list_of_cutoffs,
system_id_rank, totalRanks, bootstrapSize)
pipe = Pipeline([computeSwapRate],
nr_threads=nr_threads,
update_interval=100,
verbose=verbose)
pipe.execute(
data,
f_result_handler=experiment_results.handleExperimentResult,
chunksize=10,
pool=pool)
print('Done computing ASL rate and swap method. Time: %f\n' %
((cur_time() - begin_time) / 60))
if useErrTie:
print(
'Computing Error and Tie rate'
) #computes: error and tie rate, relRate, signRate (without replacement)
begin_time = cur_time()
rand.seed(seed_)
for iter_ in range(iterations):
print('Computing iteration %d of %d, time=%f.' %
(iter_ + 1, iterations, (cur_time() - begin_time) / 60))
data = getExperimentsFromParameterRanges(