Ruben Brunk | 370e243 | 2014-10-14 18:33:23 -0700 | [diff] [blame] | 1 | # Copyright 2014 The Android Open Source Project |
| 2 | # |
| 3 | # Licensed under the Apache License, Version 2.0 (the "License"); |
| 4 | # you may not use this file except in compliance with the License. |
| 5 | # You may obtain a copy of the License at |
| 6 | # |
| 7 | # http://www.apache.org/licenses/LICENSE-2.0 |
| 8 | # |
| 9 | # Unless required by applicable law or agreed to in writing, software |
| 10 | # distributed under the License is distributed on an "AS IS" BASIS, |
| 11 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| 12 | # See the License for the specific language governing permissions and |
| 13 | # limitations under the License. |
| 14 | |
| 15 | import its.image |
| 16 | import its.caps |
| 17 | import its.device |
| 18 | import its.objects |
| 19 | import its.target |
| 20 | import time |
| 21 | import pylab |
| 22 | import os.path |
| 23 | import matplotlib |
| 24 | import matplotlib.pyplot |
| 25 | import numpy |
| 26 | |
| 27 | def main(): |
| 28 | """Test if the gyro has stable output when device is stationary. |
| 29 | """ |
| 30 | NAME = os.path.basename(__file__).split(".")[0] |
| 31 | |
| 32 | # Number of samples averaged together, in the plot. |
| 33 | N = 20 |
| 34 | |
| 35 | # Pass/fail thresholds for gyro drift |
| 36 | MEAN_THRESH = 0.01 |
| 37 | VAR_THRESH = 0.001 |
| 38 | |
| 39 | with its.device.ItsSession() as cam: |
| 40 | props = cam.get_camera_properties() |
| 41 | # Only run test if the appropriate caps are claimed. |
Chien-Yu Chen | bad96ca | 2014-10-20 17:30:56 -0700 | [diff] [blame] | 42 | its.caps.skip_unless(its.caps.sensor_fusion(props)) |
Ruben Brunk | 370e243 | 2014-10-14 18:33:23 -0700 | [diff] [blame] | 43 | |
| 44 | print "Collecting gyro events" |
| 45 | cam.start_sensor_events() |
| 46 | time.sleep(5) |
| 47 | gyro_events = cam.get_sensor_events()["gyro"] |
| 48 | |
| 49 | nevents = (len(gyro_events) / N) * N |
| 50 | gyro_events = gyro_events[:nevents] |
| 51 | times = numpy.array([(e["time"] - gyro_events[0]["time"])/1000000000.0 |
| 52 | for e in gyro_events]) |
| 53 | xs = numpy.array([e["x"] for e in gyro_events]) |
| 54 | ys = numpy.array([e["y"] for e in gyro_events]) |
| 55 | zs = numpy.array([e["z"] for e in gyro_events]) |
| 56 | |
| 57 | # Group samples into size-N groups and average each together, to get rid |
Chien-Yu Chen | 34fa85d | 2014-10-22 16:58:08 -0700 | [diff] [blame] | 58 | # of individual random spikes in the data. |
Ruben Brunk | 370e243 | 2014-10-14 18:33:23 -0700 | [diff] [blame] | 59 | times = times[N/2::N] |
| 60 | xs = xs.reshape(nevents/N, N).mean(1) |
| 61 | ys = ys.reshape(nevents/N, N).mean(1) |
| 62 | zs = zs.reshape(nevents/N, N).mean(1) |
| 63 | |
| 64 | pylab.plot(times, xs, 'r', label="x") |
| 65 | pylab.plot(times, ys, 'g', label="y") |
| 66 | pylab.plot(times, zs, 'b', label="z") |
| 67 | pylab.xlabel("Time (seconds)") |
| 68 | pylab.ylabel("Gyro readings (mean of %d samples)"%(N)) |
| 69 | pylab.legend() |
| 70 | matplotlib.pyplot.savefig("%s_plot.png" % (NAME)) |
| 71 | |
| 72 | for samples in [xs,ys,zs]: |
| 73 | assert(samples.mean() < MEAN_THRESH) |
| 74 | assert(numpy.var(samples) < VAR_THRESH) |
| 75 | |
| 76 | if __name__ == '__main__': |
| 77 | main() |
| 78 | |