def estimateSample(self, interpolationSample, time):
estimatedSample = PredictionSample()
estimatedSample.sample.time = time
estimatedSample.sample.position = self.calculatePosition(
interpolationSample, time)
estimatedSample.velocity = deepcopy(interpolationSample.velocity)
return estimatedSample
def calcExtrapolationSample(self, currentSample, targetSample):
deltaPosition = targetSample.position - currentSample.position
deltaTime = targetSample.time - currentSample.time
invDeltaTimeVector = Vector(1 / float(deltaTime), 1 / float(deltaTime), 1 / float(deltaTime))
velocity = deltaPosition * invDeltaTimeVector
extrapolationSample = PredictionSample()
extrapolationSample.sample = deepcopy(currentSample)
extrapolationSample.velocity = velocity
return extrapolationSample
def calcExtrapolationSample(self, snapSample, targetSample):
deltaPosition = targetSample.position - snapSample.position
deltaTime = targetSample.time - snapSample.time
invDeltaTimeVector = Vector( 1 / float(deltaTime), \
1 / float(deltaTime), \
1 / float(deltaTime))
velocity = deltaPosition * invDeltaTimeVector
extrapolationSample = PredictionSample()
extrapolationSample.sample = deepcopy(snapSample)
extrapolationSample.velocity = velocity
return extrapolationSample
def findInterpolationSample(self, currentSample, targetSample):
deltaPosition = targetSample.position - \
currentSample.position
deltaTime = targetSample.time - \
currentSample.time
invDeltaTimeVector = Vector( 1 / float(deltaTime), \
1 / float(deltaTime), \
1 / float(deltaTime))
velocity = deltaPosition * invDeltaTimeVector
interpolationSample = PredictionSample()
interpolationSample.sample = deepcopy(currentSample)
interpolationSample.velocity = velocity
return interpolationSample
def findInterpolationSample(self, currentSample, targetSample):
deltaPosition = targetSample.sample.position - \
currentSample.sample.position
deltaTime = targetSample.sample.time - \
currentSample.sample.time
invDeltaTimeVector = Vector( 1 / float(deltaTime), \
1 / float(deltaTime), \
1 / float(deltaTime))
velocity = deltaPosition * invDeltaTimeVector
interpolationSample = PredictionSample()
interpolationSample.sample = deepcopy(currentSample.sample)
interpolationSample.velocity = velocity
return interpolationSample
def executeAlgorithm(self):
self.predictedData = []
for index, sample in enumerate(self.inputData):
if sample.time < self.predictionInterval:
# Set initial values
predictionSample = PredictionSample()
predictionSample.sample = copy(sample)
predictionSample.velocity = Vector()
self.predictedData.append(predictionSample)
else:
shift = index - self.predictionInterval / self.samplingInterval
# Calculate velocity
deltaPosition = self.inputData[index].position - \
self.inputData[shift].position
deltaTime = self.inputData[index].time - \
self.inputData[shift].time
invDeltaTimeVector = Vector( 1 / float(deltaTime), \
1 / float(deltaTime), \
1 / float(deltaTime))
velocity = deltaPosition * invDeltaTimeVector
# Populate data structures
predictionSample = PredictionSample()
predictionSample.sample = copy(sample)
predictionSample.velocity = velocity
self.predictedData.append(predictionSample)
def executeAlgorithm(self):
self.reconstructedSignal = []
self.reconstructedSignal.append(deepcopy(self.rawSignal[0].sample))
extrapolationSample = self.rawSignal[0]
futureExtrapolationSample = None
nextTimeToRecord = self.reconstructedSignal[0].time + 1
tempRawSignal = self.rawSignal[1:]
for index, predictionSample in enumerate(tempRawSignal):
while predictionSample.sample.time > nextTimeToRecord:
if futureExtrapolationSample != None and \
futureExtrapolationSample.sample.time == nextTimeToRecord:
extrapolationSample = futureExtrapolationSample
futureExtrapolationSample = None
self.reconstructedSignal.append(
deepcopy(extrapolationSample.sample))
else:
estimatedSample = self.estSample(extrapolationSample,
nextTimeToRecord)
self.reconstructedSignal.append(deepcopy(estimatedSample))
nextTimeToRecord += 1
lastEstimatedSample = self.reconstructedSignal[-1]
targetSample = self.calcTargetSample(predictionSample)
snapSample = self.calcSnapSample(predictionSample.sample,
lastEstimatedSample)
extrapolationSample = self.calcExtrapolationSample(
snapSample, targetSample)
futureExtrapolationSample = PredictionSample(
targetSample, predictionSample.velocity)
self.reconstructedSignal.append(deepcopy(snapSample))
nextTimeToRecord += 1
def executeAlgorithm(self):
self.reconstructedSignal = []
nextTimeToRecord = 0
timeDiff = self.rawSignal[0].sample.time % self.samplingInterval
if timeDiff == 0:
self.reconstructedSignal.append( deepcopy(self.rawSignal[0].sample) )
nextTimeToRecord = self.rawSignal[0].sample.time + \
self.samplingInterval
else:
change = self.samplingInterval - timeDiff
newSample = Sample()
newSample.time = self.rawSignal[0].sample.time + change
newSample.position = deepcopy(self.rawSignal[0].sample.position)
self.reconstructedSignal.append(newSample)
nextTimeToRecord = newSample.time + self.samplingInterval
interpolationSample = PredictionSample()
interpolationSample.sample = self.reconstructedSignal[0]
interpolationSample.velocity = self.rawSignal[0].velocity
for index, predictionSample in enumerate(self.rawSignal):
if predictionSample.sample.time == nextTimeToRecord:
estimatedSample = self.calculateEstSample(interpolationSample, \
nextTimeToRecord)
self.reconstructedSignal.append(estimatedSample)
targetSample = self.findTarget(predictionSample)
interpolationSample = self.findInterpolationSample(estimatedSample, \
targetSample)
nextTimeToRecord = nextTimeToRecord + self.samplingInterval
elif predictionSample.sample.time > nextTimeToRecord:
while predictionSample.sample.time > nextTimeToRecord:
estimatedSample = self.calculateEstSample(interpolationSample, \
nextTimeToRecord)
self.reconstructedSignal.append(estimatedSample)
nextTimeToRecord = nextTimeToRecord + self.samplingInterval
if predictionSample.sample.time == nextTimeToRecord:
estimatedSample = self.calculateEstSample(interpolationSample, \
nextTimeToRecord)
self.reconstructedSignal.append(estimatedSample)
targetSample = self.findTarget(predictionSample)
interpolationSample = self.findInterpolationSample(estimatedSample, \
targetSample)
nextTimeToRecord = nextTimeToRecord + self.samplingInterval
else:
targetSample = self.findTarget(predictionSample)
interpolationSample = self.findInterpolationSample(self.reconstructedSignal[-1], \
targetSample)
def findSnapSample(self, currentSample, estimatedSample, targetSample):
deltaPosition = targetSample.sample.position - \
currentSample.sample.position
deltaPosition.x *= self.snapLimit
deltaPosition.y *= self.snapLimit
deltaPosition.z *= self.snapLimit
snapPosition = currentSample.sample.position + deltaPosition
deltaPosition = targetSample.sample.position - snapPosition
deltaTime = targetSample.sample.time - \
currentSample.sample.time
invDeltaTimeVector = Vector( 1 / float(deltaTime), \
1 / float(deltaTime), \
1 / float(deltaTime))
velocity = deltaPosition * invDeltaTimeVector
snapSample = PredictionSample()
snapSample.sample = Sample(currentSample.sample.time, snapPosition)
snapSample.velocity = velocity
return snapSample
def findSnapSample(self, currentSample, estimatedSample, targetSample): deltaPosition = targetSample.sample.position - \ currentSample.sample.position deltaPosition.x *= self.snapLimit deltaPosition.y *= self.snapLimit deltaPosition.z *= self.snapLimit snapPosition = currentSample.sample.position + deltaPosition deltaPosition = targetSample.sample.position - snapPosition deltaTime = targetSample.sample.time - \ currentSample.sample.time invDeltaTimeVector = Vector( 1 / float(deltaTime), \ 1 / float(deltaTime), \ 1 / float(deltaTime)) velocity = deltaPosition * invDeltaTimeVector snapSample = PredictionSample() snapSample.sample = Sample(currentSample.sample.time, snapPosition) snapSample.velocity = velocity return snapSample
def executeAlgorithm(self):
self.predictedData = []
for index, sample in enumerate(self.inputData):
if sample.time < self.predictionInterval:
# Set initial values
predictionSample = PredictionSample()
predictionSample.sample = copy(sample)
predictionSample.velocity = Vector()
self.predictedData.append( predictionSample )
else:
shift = index - self.predictionInterval / self.samplingInterval
# Calculate velocity
deltaPosition = self.inputData[index].position - \
self.inputData[shift].position
deltaTime = self.inputData[index].time - \
self.inputData[shift].time
invDeltaTimeVector = Vector( 1 / float(deltaTime), \
1 / float(deltaTime), \
1 / float(deltaTime))
velocity = deltaPosition * invDeltaTimeVector
# Populate data structures
predictionSample = PredictionSample()
predictionSample.sample = copy(sample)
predictionSample.velocity = velocity
self.predictedData.append( predictionSample )
def executeAlgorithm(self): self.reconstructedSignal = [] self.reconstructedSignal.append( self.findFirstSample() ) reconstructionTime = self.reconstructedSignal[0].time + self.samplingInterval interpolationSample = PredictionSample(self.reconstructedSignal[0], self.rawSignal[0].velocity) targetSample = None for index, predictionSample in enumerate(self.rawSignal[1:]): currentTime = predictionSample.sample.time if currentTime < reconstructionTime: estimatedSample = self.estimateSample(interpolationSample, currentTime) targetSample = self.findTarget(predictionSample) interpolationSample = self.findInterpolationSample(estimatedSample, targetSample) elif currentTime == reconstructionTime: previousEstimatedSample = self.estimateSample(interpolationSample, reconstructionTime - self.samplingInterval) targetSample = self.findTarget(predictionSample) interpolationSample = self.findInterpolationSample(previousEstimatedSample, targetSample) estimatedSample = self.estimateSample(interpolationSample, reconstructionTime) self.reconstructedSignal.append(deepcopy(estimatedSample.sample)) reconstructionTime += self.samplingInterval elif currentTime > reconstructionTime: while currentTime > reconstructionTime: if targetSample != None and reconstructionTime >= targetSample.sample.time: interpolationSample = targetSample targetSample = None estimatedSample = self.estimateSample(interpolationSample, reconstructionTime) self.reconstructedSignal.append(deepcopy(estimatedSample.sample)) reconstructionTime += self.samplingInterval if currentTime < reconstructionTime: estimatedSample = self.estimateSample(interpolationSample, currentTime) targetSample = self.findTarget(predictionSample) interpolationSample = self.findInterpolationSample(estimatedSample, targetSample) elif currentTime == reconstructionTime: previousEstimatedSample = self.estimateSample(interpolationSample, reconstructionTime - self.samplingInterval) targetSample = self.findTarget(predictionSample) interpolationSample = self.findInterpolationSample(previousEstimatedSample, targetSample) estimatedSample = self.estimateSample(interpolationSample, reconstructionTime) self.reconstructedSignal.append(deepcopy(estimatedSample.sample)) reconstructionTime += self.samplingInterval
def estimateSample(self, interpolationSample, time): estimatedSample = PredictionSample() estimatedSample.sample.time = time estimatedSample.sample.position = self.calculatePosition(interpolationSample, time) estimatedSample.velocity = deepcopy(interpolationSample.velocity) return estimatedSample
