def testFirstAccel(self):
self.assertAlmostEqual(calAccels(self.walkSegment)[0],
0.01626,
places=3) # 33 secs
self.assertAlmostEqual(calAccels(self.bikeSegment)[0], 0.05,
places=4) # 25 secs
self.assertAlmostEqual(calAccels(self.trainSegment)[0],
0.02339,
places=4) # 17 secs
self.assertAlmostEqual(calAccels(self.carSegment)[0],
0.02810,
places=4) # 20 secs
def testSecondAccel(self):
self.assertAlmostEqual(calAccels(self.walkSegment)[1],
-0.00114,
places=4) # 52 secs
self.assertAlmostEqual(calAccels(self.bikeSegment)[1],
0.00442,
places=4) # 181 secs
self.assertAlmostEqual(calAccels(self.trainSegment)[1],
0.24863,
places=3) # 21 secs
self.assertAlmostEqual(calAccels(self.carSegment)[1],
-0.01574,
places=4) # 19 secs
def updateFeatureMatrixRowWithSection(self, featureMatrix, i, section):
featureMatrix[i, 0] = section['distance']
featureMatrix[i,
1] = (section['section_end_datetime'] -
section['section_start_datetime']).total_seconds()
# Deal with unknown modes like "airplane"
try:
featureMatrix[i, 2] = section['mode']
except ValueError:
featureMatrix[i, 2] = 0
featureMatrix[i, 3] = section['section_id']
featureMatrix[i, 4] = calAvgSpeed(section)
speeds = calSpeeds(section)
if speeds != None:
featureMatrix[i, 5] = np.mean(speeds)
featureMatrix[i, 6] = np.std(speeds)
featureMatrix[i, 7] = np.max(speeds)
else:
# They will remain zero
pass
accels = calAccels(section)
if accels != None and len(accels) > 0:
featureMatrix[i, 8] = np.max(accels)
else:
# They will remain zero
pass
featureMatrix[i,
9] = ('commute'
in section) and (section['commute'] == 'to'
or section['commute'] == 'from')
featureMatrix[i, 10] = calHCR(section)
featureMatrix[i, 11] = calSR(section)
featureMatrix[i, 12] = calVCR(section)
if 'section_start_point' in section and section[
'section_start_point'] != None:
startCoords = section['section_start_point']['coordinates']
featureMatrix[i, 13] = startCoords[0]
featureMatrix[i, 14] = startCoords[1]
if 'section_end_point' in section and section[
'section_end_point'] != None:
endCoords = section['section_end_point']['coordinates']
featureMatrix[i, 15] = endCoords[0]
featureMatrix[i, 16] = endCoords[1]
featureMatrix[i, 17] = section['section_start_datetime'].time().hour
featureMatrix[i, 18] = section['section_end_datetime'].time().hour
featureMatrix[i, 19] = mode_start_end_coverage(section,
self.bus_cluster, 105)
featureMatrix[i, 20] = mode_start_end_coverage(section,
self.train_cluster, 600)
def updateFeatureMatrixRowWithSection(self, featureMatrix, i, section):
featureMatrix[i, 0] = section['distance']
featureMatrix[i, 1] = (section['section_end_datetime'] - section['section_start_datetime']).total_seconds()
# Deal with unknown modes like "airplane"
try:
featureMatrix[i, 2] = section['mode']
except ValueError:
featureMatrix[i, 2] = 0
featureMatrix[i, 3] = section['section_id']
featureMatrix[i, 4] = calAvgSpeed(section)
speeds = calSpeeds(section)
if speeds != None and len(speeds) > 0:
featureMatrix[i, 5] = np.mean(speeds)
featureMatrix[i, 6] = np.std(speeds)
featureMatrix[i, 7] = np.max(speeds)
else:
# They will remain zero
pass
accels = calAccels(section)
if accels != None and len(accels) > 0:
featureMatrix[i, 8] = np.max(accels)
else:
# They will remain zero
pass
featureMatrix[i, 9] = ('commute' in section) and (section['commute'] == 'to' or section['commute'] == 'from')
featureMatrix[i, 10] = calHCR(section)
featureMatrix[i, 11] = calSR(section)
featureMatrix[i, 12] = calVCR(section)
if 'section_start_point' in section and section['section_start_point'] != None:
startCoords = section['section_start_point']['coordinates']
featureMatrix[i, 13] = startCoords[0]
featureMatrix[i, 14] = startCoords[1]
if 'section_end_point' in section and section['section_end_point'] != None:
endCoords = section['section_end_point']['coordinates']
featureMatrix[i, 15] = endCoords[0]
featureMatrix[i, 16] = endCoords[1]
featureMatrix[i, 17] = section['section_start_datetime'].time().hour
featureMatrix[i, 18] = section['section_end_datetime'].time().hour
if (hasattr(self, "bus_cluster")):
featureMatrix[i, 19] = mode_start_end_coverage(section, self.bus_cluster,105)
if (hasattr(self, "train_cluster")):
featureMatrix[i, 20] = mode_start_end_coverage(section, self.train_cluster,600)
if (hasattr(self, "air_cluster")):
featureMatrix[i, 21] = mode_start_end_coverage(section, self.air_cluster,600)
# Replace NaN and inf by zeros so that it doesn't crash later
featureMatrix[i] = np.nan_to_num(featureMatrix[i])