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])