This directory contains a simple python script for visualizing the behavior of the WindowOrientationListener. PREREQUISITES ------------- 1. Python 2.6 2. numpy 3. matplotlib eg. sudo apt-get install python-numpy python-matplotlib USAGE ----- The tool works by scaping the debug log output from WindowOrientationListener for interesting data and then plotting it. 1. Plug in the device. Ensure that it is the only device plugged in since this script is of very little brain and will get confused otherwise. 2. Enable the Window Orientation Listener debugging data log. adb shell setprop debug.orientation.log true adb shell stop adb shell start 3. Run "orientationplot.py". WHAT IT ALL MEANS ----------------- The tool displays several time series graphs that plot the output of the WindowOrientationListener. Here you can see the raw accelerometer data, filtered accelerometer data, measured tilt and orientation angle, confidence intervals for the proposed orientation and accelerometer latency. Things to look for: 1. Ensure the filtering is not too aggressive. If the filter cut-off frequency is less than about 1Hz, then the filtered accelorometer data becomes too smooth and the latency for orientation detection goes up. One way to observe this is by holding the device vertically in one orientation then sharply turning it 90 degrees to a different orientation. Compared the rapid changes in the raw accelerometer data with the smoothed out filtered data. If the filtering is too aggressive, the filter response may lag by hundreds of milliseconds. 2. Ensure that there is an appropriate gap between adjacent orientation angles for hysteresis. Try holding the device in one orientation and slowly turning it 90 degrees. Note that the confidence intervals will all drop to 0 at some point in between the two orientations; that is the gap. The gap should be observed between all adjacent pairs of orientations when turning the device in either direction. Next try holding the device in one orientation and rapidly turning it end over end to a midpoint about 45 degrees between two opposing orientations. There should be no gap observed initially. The algorithm should pick one of the orientations and settle into it (since it is obviously quite different from the original orientation of the device). However, once it settles, the confidence values should start trending to 0 again because the measured orientation angle is now within the gap between the new orientation and the adjacent orientation. In other words, the hysteresis gap applies only when the measured orientation angle (say, 45 degrees) is between the current orientation's ideal angle (say, 0 degrees) and an adjacent orientation's ideal angle (say, 90 degrees). 3. Accelerometer jitter. The accelerometer latency graph displays the interval between sensor events as reported by the SensorEvent.timestamp field. It should be a fairly constant 60ms. If the latency jumps around wildly or greatly exceeds 60ms then there is a problem with the accelerometer or the sensor manager. 4. The orientation angle is not measured when the tilt is too close to 90 or -90 degrees (refer to MAX_TILT constant). Consequently, you should expect there to be no data. Likewise, all dependent calculations are suppressed in this case so there will be no orientation proposal either. 5. Each orientation has its own bound on allowable tilt angles. It's a good idea to verify that these limits are being enforced by gradually varying the tilt of the device until it is inside/outside the limit for each orientation. 6. Orientation changes should be significantly harder when the device is held overhead. People reading on tablets in bed often have their head turned a little to the side, or they hold the device loosely so its orientation can be a bit unusual. The tilt is a good indicator of whether the device is overhead.