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]
