def test_magnitude_empty(self):
ds = DataStream(None, None, data=[])
self.assertIsInstance(ds, DataStream)
m = magnitude(normalize(ds))
self.assertIsInstance(m, DataStream)
self.assertEqual(len(m.data), 0)
def test_magnitude(self):
self.assertIsInstance(self.ds, DataStream)
self.assertEqual(len(self.ds.datapoints), self.size)
m = magnitude(normalize(self.ds))
self.assertIsInstance(m, DataStream)
for sample in m.datapoints:
self.assertAlmostEqual(sample.sample,
0.12295653034492039,
delta=1e-6)
def test_normalize(self):
self.assertIsInstance(self.ds, DataStream)
self.assertEqual(len(self.ds.datapoints), self.size)
n = normalize(self.ds)
self.assertIsInstance(n, DataStream)
for dp in n.datapoints:
self.assertAlmostEqual(np.linalg.norm(dp.sample),
0.1713970501312247,
delta=1e-6)
def accelerometer_features(accel: DataStream,
window_length: float = 10.0,
activity_threshold: float = 0.21,
percentile_low: int = 1,
percentile_high: int = 99):
"""
References:
Figure 3: http://www.cs.memphis.edu/~santosh/Papers/Timing-JIT-UbiComp-2014.pdf
:param percentile_high:
:param percentile_low:
:param accel:
:param window_length:
:param activity_threshold:
:return:
"""
accelerometer_magnitude = magnitude(normalize(accel))
accelerometer_win_mag_deviations_data = []
for key, data in window(accelerometer_magnitude.data,
window_length).items():
accelerometer_win_mag_deviations_data.append(
window_std_dev(data, key[0]))
accelerometer_win_mag_deviations = DataStream.from_datastream([accel])
accelerometer_win_mag_deviations.data = accelerometer_win_mag_deviations_data
am_values = np.array([dp.sample for dp in accelerometer_magnitude.data])
low_limit = np.percentile(am_values, percentile_low)
high_limit = np.percentile(am_values, percentile_high)
range = high_limit - low_limit
#print (range)
#print (low_limit + activity_threshold * range)
#print (accelerometer_win_mag_deviations_data)
accel_activity_data = []
for dp in accelerometer_win_mag_deviations_data:
comparison = dp.sample > (low_limit + activity_threshold * range)
accel_activity_data.append(
DataPoint.from_tuple(dp.start_time, comparison))
accel_activity = DataStream.from_datastream([accel])
accel_activity.data = accel_activity_data
return accelerometer_magnitude, accelerometer_win_mag_deviations, accel_activity
def test_magnitude(self):
self.assertIsInstance(self.accel, DataStream)
m = magnitude(normalize(self.accel))
self.assertIsInstance(m, DataStream)
def test_normalize(self):
self.assertIsInstance(self.accel, DataStream)
n = normalize(self.accel)
self.assertIsInstance(n, DataStream)