def scaleData(self):
tempData = []
for sample in self.rawData:
newSample = Sample()
newSample.time = sample.time
newSample.position = (sample.position + self.scalingFactorA)
newSample.position.x = newSample.position.x * self.scalingFactorB.x
newSample.position.y = newSample.position.y * self.scalingFactorB.y
newSample.position.z = newSample.position.z * self.scalingFactorB.z
newSample.position = newSample.position - Vector(1, 1, 1)
tempData.append(newSample)
self.rawData = tempData
def scaleData(self):
tempData = []
for sample in self.rawData:
newSample = Sample()
newSample.time = sample.time
newSample.position = ( sample.position + self.scalingFactorA )
newSample.position.x = newSample.position.x * self.scalingFactorB.x
newSample.position.y = newSample.position.y * self.scalingFactorB.y
newSample.position.z = newSample.position.z * self.scalingFactorB.z
newSample.position = newSample.position - Vector(1,1,1)
tempData.append(newSample)
self.rawData = tempData
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
for index, predictionSample in enumerate(self.rawSignal):
if predictionSample.sample.time == nextTimeToRecord:
self.reconstructedSignal.append( deepcopy(predictionSample.sample) )
nextTimeToRecord = nextTimeToRecord + self.samplingInterval
elif predictionSample.sample.time > nextTimeToRecord:
while predictionSample.sample.time > nextTimeToRecord:
deltaTime = nextTimeToRecord - self.rawSignal[index-1].sample.time
deltaTimeVector = Vector(deltaTime, deltaTime, deltaTime)
deltaPosition = self.rawSignal[index-1].velocity * deltaTimeVector
newPosition = self.rawSignal[index-1].sample.position + deltaPosition
newSample = Sample(nextTimeToRecord, newPosition)
self.reconstructedSignal.append( newSample )
nextTimeToRecord = nextTimeToRecord + self.samplingInterval
if predictionSample.sample.time == nextTimeToRecord:
self.reconstructedSignal.append( deepcopy(predictionSample.sample) )
nextTimeToRecord = nextTimeToRecord + self.samplingInterval
def calculateEstSample(self, interpolationSample, currentTime):
estimatedSample = Sample()
estimatedSample.time = currentTime
estimatedSample.position = self.calculateEstPosition(interpolationSample, currentTime)
return estimatedSample
def findFirstSample(self):
timeDiff = self.rawSignal[0].sample.time % self.samplingInterval
if timeDiff == 0:
return deepcopy(self.rawSignal[0].sample)
else:
change = self.samplingInterval - timeDiff
newSample = Sample()
newSample.time = self.rawSignal[0].sample.time + change
newSample.position = deepcopy(self.rawSignal[0].sample.position)
return newSample
def findFirstSample(self):
timeDiff = self.rawSignal[0].sample.time % self.samplingInterval
if timeDiff == 0:
return deepcopy(self.rawSignal[0].sample)
else:
change = self.samplingInterval - timeDiff
newSample = Sample()
newSample.time = self.rawSignal[0].sample.time + change
newSample.position = deepcopy(self.rawSignal[0].sample.position)
return newSample
def shiftData(self):
tempData = []
firstTime = self.rawData[0].time
for sample in self.rawData:
if sample.time >= firstTime:
newSample = Sample()
newSample.time = sample.time - firstTime + ( 10 * self.numberOfPaddingSamples)
newSample.position = copy( sample.position )
tempData.append(newSample)
self.rawData = tempData
def shiftData(self):
tempData = []
firstTime = self.rawData[0].time
for sample in self.rawData:
if sample.time >= firstTime:
newSample = Sample()
newSample.time = sample.time - firstTime + (
10 * self.numberOfPaddingSamples)
newSample.position = copy(sample.position)
tempData.append(newSample)
self.rawData = tempData
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)
