def updateFeatureMatrixRowWithSection(self, featureMatrix, i,
section_entry):
section = section_entry.data
featureMatrix[i, 0] = section.distance
featureMatrix[i, 1] = section.duration
featureMatrix[i, 2] = section.sensed_mode.value
# TODO: Figure out if I can get the section id from the new style sections
# featureMatrix[i, 3] = section['_id']
featureMatrix[i, 4] = easf.calOverallSectionSpeed(section)
speeds = section['speeds']
if speeds is not 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 = easf.calAccels(section)
if accels is not None and len(accels) > 0:
featureMatrix[i, 8] = np.max(accels)
else:
# They will remain zero
pass
featureMatrix[i, 9] = False
featureMatrix[i, 10] = easf.calHCR(section_entry)
featureMatrix[i, 11] = easf.calSR(section_entry)
featureMatrix[i, 12] = easf.calVCR(section_entry)
if 'start_loc' in section and section['end_loc'] != None:
startCoords = section['start_loc']['coordinates']
featureMatrix[i, 13] = startCoords[0]
featureMatrix[i, 14] = startCoords[1]
if 'end_loc' in section and section['end_loc'] != None:
endCoords = section['end_loc']['coordinates']
featureMatrix[i, 15] = endCoords[0]
featureMatrix[i, 16] = endCoords[1]
featureMatrix[i, 17] = section['start_local_dt']['hour']
featureMatrix[i, 18] = section['end_local_dt']['hour']
if (hasattr(self, "bus_cluster")):
featureMatrix[i, 19] = easf.mode_start_end_coverage(
section, self.bus_cluster, 105)
if (hasattr(self, "train_cluster")):
featureMatrix[i, 20] = easf.mode_start_end_coverage(
section, self.train_cluster, 600)
if (hasattr(self, "air_cluster")):
featureMatrix[i, 21] = easf.mode_start_end_coverage(
section, self.air_cluster, 600)
if self.last_section_done is None or self.last_section_done.data.end_ts < section_entry.data.end_ts:
self.last_section_done = section_entry
# Replace NaN and inf by zeros so that it doesn't crash later
featureMatrix[i] = np.nan_to_num(featureMatrix[i])
def updateFeatureMatrixRowWithSection(self, featureMatrix, i, section_entry):
section = section_entry.data
featureMatrix[i, 0] = section.distance
featureMatrix[i, 1] = section.duration
featureMatrix[i, 2] = section.sensed_mode.value
# TODO: Figure out if I can get the section id from the new style sections
# featureMatrix[i, 3] = section['_id']
featureMatrix[i, 4] = easf.calOverallSectionSpeed(section)
speeds = section['speeds']
if speeds is not 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 = easf.calAccels(section)
if accels is not None and len(accels) > 0:
featureMatrix[i, 8] = np.max(accels)
else:
# They will remain zero
pass
featureMatrix[i, 9] = False
featureMatrix[i, 10] = easf.calHCR(section_entry)
featureMatrix[i, 11] = easf.calSR(section_entry)
featureMatrix[i, 12] = easf.calVCR(section_entry)
if 'start_loc' in section and section['end_loc'] != None:
startCoords = section['start_loc']['coordinates']
featureMatrix[i, 13] = startCoords[0]
featureMatrix[i, 14] = startCoords[1]
if 'end_loc' in section and section['end_loc'] != None:
endCoords = section['end_loc']['coordinates']
featureMatrix[i, 15] = endCoords[0]
featureMatrix[i, 16] = endCoords[1]
featureMatrix[i, 17] = section['start_local_dt']['hour']
featureMatrix[i, 18] = section['end_local_dt']['hour']
if (hasattr(self, "bus_cluster")):
featureMatrix[i, 19] = easf.mode_start_end_coverage(section, self.bus_cluster,105)
if (hasattr(self, "train_cluster")):
featureMatrix[i, 20] = easf.mode_start_end_coverage(section, self.train_cluster,600)
if (hasattr(self, "air_cluster")):
featureMatrix[i, 21] = easf.mode_start_end_coverage(section, self.air_cluster,600)
if self.last_section_done is None or self.last_section_done.data.end_ts < section_entry.data.end_ts:
self.last_section_done = section_entry
# Replace NaN and inf by zeros so that it doesn't crash later
featureMatrix[i] = np.nan_to_num(featureMatrix[i])
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] = easf.calAvgSpeed(section)
speeds = easf.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 = easf.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] = easf.calHCR(section)
featureMatrix[i, 11] = easf.calSR(section)
featureMatrix[i, 12] = easf.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] = easf.mode_start_end_coverage(section, self.bus_cluster,105)
if (hasattr(self, "train_cluster")):
featureMatrix[i, 20] = easf.mode_start_end_coverage(section, self.train_cluster,600)
if (hasattr(self, "air_cluster")):
featureMatrix[i, 21] = easf.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])
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] = easf.calAvgSpeed(section)
speeds = easf.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 = easf.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] = easf.calHCR(section)
featureMatrix[i, 11] = easf.calSR(section)
featureMatrix[i, 12] = easf.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] = easf.mode_start_end_coverage(section, self.bus_cluster,105)
if (hasattr(self, "train_cluster")):
featureMatrix[i, 20] = easf.mode_start_end_coverage(section, self.train_cluster,600)
if (hasattr(self, "air_cluster")):
featureMatrix[i, 21] = easf.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])