Comments (3)
edit:
I guess this is the culprit
sample = self._tracker.get_frame()
t1 = time.time()
# put the sample in the Queue
queue.put(sample)
# release the Threading Lock
self._lock.release()
# Update the newest frame
self._newestframe = copy.deepcopy(sample)
# Calculate the clock difference
self._clockdiff = sample['time'] - t1
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I still have no idea about that 'time', but I managed to convert the timestamp from string format into unix timestamp format :)
thanks to this:
http://stackoverflow.com/questions/26161156/python-converting-string-to-timestamp-with-microseconds
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To provide some general information on this:
The way gaze recordings and events in an experiment are generally compared and matched is NOT through comparing timestamps. The ideal way is to use the log
function of the EyeTracker
class at the moment that your experiment changes, for example directly after calling the show
function of a Display
object. In this way, there is a log message in the gaze data file at the time of your screen update.
The reason for this, is that clocks on different devices do not necessarily run at the same pace. In other words: There is a drift in the difference between the two clocks. This means a direct comparison of the timestamps on both devices is not necessarily valid.
As for the trackertime
, this is what the device (or the computer running the server that talks to the device) reports as its timestamps. They are useful, because the device is where your gaze data comes from. Timestamps in tracker time are thus the most precise indication of what gaze behaviour happened when. With the EyeTracker.log
function, you can add a trigger/event/message (different people use different terms) to your eye data file, which will then also be assigned a timestamp in tracker time.
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