def runProcess(queue, vehicleData, sensorData, trajPredictor, trajPredictorSettings, egoPredictor, egoPredictorSettings, truth): predTime, predID = applyPredictor(vehicleData, sensorData, 'ego', 2.5, 3.5, trajPredictor, trajPredictorSettings, egoPredictor, egoPredictorSettings) queue.put([predTime, predID, truth])
def runProcess(queue, vehicleData, sensor, sensorSettings, egoSensor, egoSensorSettings, predictor, predictorSettings, egoPredictor, egoPredictorSettings, extraInfo): sensorData = applySensor(vehicleData, 'ego', sensor, sensorSettings, egoSensor, egoSensorSettings) predTime, predID = applyPredictor(vehicleData, sensorData, 'ego', 0.5, 1.5, predictor, predictorSettings, egoPredictor, egoPredictorSettings) queue.put([predTime] + extraInfo)
def runProcess( queue, vehicleData, sensorData, trajPredictor, trajPredictorSettings, egoPredictor, egoPredictorSettings, truth ): predTime, predID = applyPredictor( vehicleData, sensorData, "ego", 2.5, 3.5, trajPredictor, trajPredictorSettings, egoPredictor, egoPredictorSettings, ) queue.put([predTime, predID, truth])
sensorFile = sensorFolder + "/" + sensorName + "/" + np.str(simIndex + 1) + ".csv" vehicleData = pd.read_table(vehicleFile, sep=",") # new data read try: sensorData = pd.read_table(sensorFile, sep=",") except ValueError: # empty file pred += [-1] predVehID += [""] continue predCollision, predictVehID = applyPredictor( vehicleData, sensorData, "ego", 2.5, 3.5, trajectoryPredictor, trajectoryPredictorSettings, egoPredictor, egoPredictorSettings, ) pred += [predCollision] predVehID += [predictVehID] thistruth = truth else: outputQueue = multiprocessing.Queue() thistruth = [] for batch in np.arange(0, nsims, batch_size): # print "- batch " + str(batch) +" / " +str(nsims) processes = []
egoPredictor = ego1Predictors[predind] egoSettings = ego1Settings[predind] pred = [] predVehID = [] for simIndex in range(nsims): inFile = vehicleFolder + "/" + simName + "/" + np.str(simIndex + 1) + ".csv" vData = pd.read_table(inFile, sep=',') sensor1Data = applySensor(vData, vehicleIDtoSeek, sensor1, sensor1Settings, egoSensor1, egoSensor1Settings) predCollision, predictVehID = applyPredictor(vData, sensor1Data, 'ego', 2.5, 3.5, trajectoryPredictor, trajectorySettings, egoPredictor, egoSettings) pred += [predCollision] predVehID += [predictVehID] result = scorePredictions(truth, truthVehID, pred, predVehID, display=False) results.add(['DSRC', trajectoryNames[predind]] + result) for predind in range(len(trajectory2Predictors)): trajectoryPredictor = trajectory2Predictors[predind] trajectorySettings = trajectory2Settings[predind]
print "- nsim: " + str(simIndex + 1) + " / " + str(nsims) vehicleFile = vehicleFolder + "/" + simName + "/" +\ np.str(simIndex+1) + ".csv" sensorFile = sensorFolder + "/" + sensorName + "/" +\ np.str(simIndex+1) + ".csv" vehicleData = pd.read_table(vehicleFile, sep=',') # new data read try: sensorData = pd.read_table(sensorFile, sep=",") except ValueError: # empty file pred += [-1] predVehID += [''] continue predCollision, predVehid = applyPredictor( vehicleData, sensorData, 'ego', 2.5, 3.5, trajectoryPredictor, trajectoryPredictorSettings, egoPredictor, egoPredictorSettings) pred += [predCollision] predVehID += [predVehid] thistruth = truth else: thistruth = [] for batch in np.arange(0, nsims, batch_size): print "- batch " + str(batch) + " / " + str(nsims) processes = [] for simIndex in range(batch, min(batch + batch_size, nsims)): vehicleFile = vehicleFolder + "/" + simName + "/" +\ np.str(simIndex+1) + ".csv" sensorFile = sensorFolder + "/" + sensorName + "/" +\
trajectoryPredictor = trajectory1Predictors[predind] trajectorySettings = trajectory1Settings[predind] egoPredictor = ego1Predictors[predind] egoSettings = ego1Settings[predind] pred = [] predVehID = [] for simIndex in range(nsims): inFile = vehicleFolder+"/"+simName+"/"+np.str(simIndex+1)+".csv" vData = pd.read_table(inFile, sep=',') sensor1Data = applySensor(vData, vehicleIDtoSeek, sensor1, sensor1Settings, egoSensor1, egoSensor1Settings) predCollision, predictVehID = applyPredictor(vData, sensor1Data, 'ego', 2.5, 3.5, trajectoryPredictor, trajectorySettings, egoPredictor, egoSettings) pred += [predCollision] predVehID += [predictVehID] result = scorePredictions(truth, truthVehID, pred, predVehID, display=False) results.add(['DSRC',trajectoryNames[predind]]+result) for predind in range(len(trajectory2Predictors)): trajectoryPredictor = trajectory2Predictors[predind] trajectorySettings = trajectory2Settings[predind] egoPredictor = ego2Predictors[predind] egoSettings = ego2Settings[predind]