def getRandom() : return randint(0,15) startValue = 0.0 data = 'false' orderflag = 0 while True : data = serverflag.parseHtml() print data if data == 'true' : #distance = getRandom(); distance = sensor.getDistance() print distance if initialvalue.isIntialNotSet(): #if startValue == 0: startValue = distance #startValue = 15.0 initialvalue.setInitialValue(startValue) else: startValue = initialvalue.getInitialValue() percnt = ((startValue-distance)/startValue)*100 print percnt
def generateFeedback(javaFiles, traceFiles, pathToProjectFolder, traceDir, verbose=False, main_config = dict()):
#generate the feedback
#INPUT
#javaFiles - Tuple of submitted and reference dicts
#Each map maps the class file dir to the java file
#traceFiles - Tuple of submitted and reference trace files
#submittedTraceFiles - Dict mapping test case # to username to absolute trace file location on disk
#referenceTraceFiles - Dict mapping test case # to username to absolute trace file location on disk
#OUTPUT
#feedback - Dict mapping username to feedback
print("Generating Feedback", flush=True)
submittedTraceFiles, referenceTraceFiles = traceFiles
submittedJavaFiles, referenceJavaFiles = javaFiles
editDistanceMapping = {}
feedback = {}
submittedPathDict = dict()
referencePathDict = dict()
for testcase in submittedTraceFiles:
print(" Evaluating on Test Case %d"%(testcase), flush=True)
for submittedPath in submittedTraceFiles[testcase]:
submittedPathDict[submittedPath] = True
if not submittedPath in editDistanceMapping:
editDistanceMapping[submittedPath] = {}
submittedFileName = submittedTraceFiles[testcase][submittedPath]
submittedFullPath = os.path.join(submittedPath,submittedFileName)
print(" Evaluating: %s"%(getName(submittedPath)), flush=True)
for referencePath in referenceTraceFiles[testcase]:
referencePathDict[referencePath] = True
referenceFileName = referenceTraceFiles[testcase][referencePath]
referenceFullPath = os.path.join(referencePath,referenceFileName)
distanceVector = Distance.getDistance(traceDir, submittedFullPath, referenceFullPath, submittedJavaFiles[submittedPath], referenceJavaFiles[referencePath], main_config)
if not referencePath in editDistanceMapping[submittedPath]:
distList = list()
distList.append(distanceVector)
editDistanceMapping[submittedPath][referencePath] = (np.array(distanceVector), distList)
else:
oldDist, distList = editDistanceMapping[submittedPath][referencePath]
distList.append(distanceVector)
editDistanceMapping[submittedPath][referencePath] = (oldDist+np.array(distanceVector), distList)
#normalize the vectors and convert to a magnitude distance
for submittedPath in editDistanceMapping.keys():
editDistanceMapping[submittedPath] = normalize(editDistanceMapping[submittedPath], verbose)
#output the editDistanceMapping csv file
submittedPaths = list(submittedPathDict.keys())
referencePaths = list(referencePathDict.keys())
csvStr = " "
#add the reference program labels accross the top
for rPath in referencePaths:
csvStr += "," + rPath
csvStr += "\n"
#loop through the rows, printing the labels on the left side first
for sPath in submittedPaths:
csvStr += sPath
for rPath in referencePaths:
csvStr += "," + str(editDistanceMapping[sPath][rPath][0])
csvStr += "\n"
mappingCsvFile = open('editDistanceMappting.csv', 'wt', encoding='utf-8')
mappingCsvFile.write(csvStr)
for submittedPath in editDistanceMapping:
minPath = ""
minDistance = 1000000000
for referencePath in editDistanceMapping[submittedPath]:
if editDistanceMapping[submittedPath][referencePath][0] < minDistance:
if(verbose):
print("Distance: " + str(submittedPath) + " => " + str(referencePath) + ": " + str(editDistanceMapping[submittedPath][referencePath]))
minDistance, distList = editDistanceMapping[submittedPath][referencePath]
minPath = referencePath
feedback[submittedPath] = (minPath, minDistance, distList)
for user in feedback:
print(getName(user) + " " + readResults(feedback[user][0]))
print("Finished Generating Feedback")
return feedback
import time
# Modul als Klasse schreiben ???
import Distance
import MotorFunctions as Motor
# Soll-Distanz in [cm]
maxDistance = 30
# Geschwindigkeit des Autos
speed = 0
Motor.initMotor()
Distance.initPins()
Distance.getDistance()
Motor.maxVelocity = 30
Motor.changeVelocity(int(speed))
input("Press Enter to continue >> ")
try:
while True:
# Ermittle Entfernung zum Hindernis
dist = Distance.getDistance()
t = time.time()
time.sleep(0.01)
# Ignoriere ungültige Messungen
if dist == None:
continue
Skript um Entfernungsmessungen und Motorgeschwindigkeit zu kombinieren
in Abhängigkeit der relativen Geschwindigkeit zum vorausfahrenen Fahrzeug
"""
import time
# Modul als Klasse schreiben ???
import Distance
import MotorFunctions as Motor
# Konstante zur Anpassung des Tastgrads
x = 1
Motor.initMotor()
Distance.initPins()
Distance.getDistance()
Motor.maxVelocity = 30
Motor.changeVelocity(int(0))
input("Press Enter to continue >> ")
try:
while True:
# Entfernungsmessungen
dist1 = Distance.getDistance()
t1 = time.time()
time.sleep(0.01)
dist2 = Distance.getDistance()
t2 = time.time()
if dist1 == None or dist2 == None:
