def transmitData(inputFile, logDir, predictionInterval, samplingInterval,
heartbeat, drThreshold, delay, jitter, packetLoss):
# Import data
print "Importing data..."
importer = Importer()
rawInputData = importer.getInputData(inputFile, samplingInterval)
exportData(logDir + "RawInputData.txt", rawInputData)
# Filtering input data
print "Filtering data..."
samplingFreq = int(1e3 / samplingInterval)
taps = 80
bands = [0.0, 10, 11, 50.0]
weights = [1, 0]
coefficients = scipy.signal.remez(taps, bands, weights, Hz=samplingFreq)
gain = 1.0 / sum(coefficients)
filteredInputData = filterData(rawInputData, logDir, "cc",
samplingInterval, coefficients)[0]
filteredInputData = amplifyData(filteredInputData, gain)
exportData(logDir + "FilteredInputData.txt", filteredInputData)
# Create the prediction vectors
print "Creating the prediction vectors..."
predictor = DRPredictor()
predictedData = predictor.getPredictedData(filteredInputData,
predictionInterval,
samplingInterval)
exportData(logDir + "PredictionData.txt", predictedData)
# Run the transmission algorithm
print "Simulating the transmission algorithm..."
transmitter = DRTransmitter(heartbeat)
drTxPackets = transmitter.getTransmittedPackets(drThreshold, predictedData)
exportData(logDir + "DRTxPackets.txt", drTxPackets)
# Simulate the transmission of the packets
print "Simulating the network..."
network = Network()
drRxPackets = network.getReceivedPackets(drTxPackets, delay, jitter,
packetLoss)
exportData(logDir + "DRRxPackets.txt", drRxPackets)
# Receive the packets
print "Receiving the packets..."
receiver = Receiver()
drRxFilteredPackets = receiver.getFilteredData(drRxPackets)
exportData(logDir + "DRRxData.txt", drRxFilteredPackets)
return [
rawInputData, filteredInputData, predictedData, drTxPackets,
drRxPackets, drRxFilteredPackets
]
def transmitData(inputFile, logDir, predictionInterval, samplingInterval,
heartbeat, drThreshold, delay, jitter, packetLoss):
# Import data
print "Importing data..."
importer = Importer()
rawInputData = importer.getInputData(inputFile, samplingInterval)
exportData(logDir + "RawInputData.txt", rawInputData)
# Filtering input data
print "Filtering data..."
samplingFreq = int(1e3/samplingInterval)
taps = 80
bands = [0.0, 10, 11, 50.0]
weights = [1, 0]
coefficients = scipy.signal.remez(taps, bands, weights, Hz=samplingFreq)
gain = 1.0 / sum(coefficients)
filteredInputData = filterData(rawInputData, logDir, "cc", samplingInterval, coefficients)[0]
filteredInputData = amplifyData(filteredInputData, gain)
exportData(logDir + "FilteredInputData.txt", filteredInputData)
# Create the prediction vectors
print "Creating the prediction vectors..."
predictor = DRPredictor()
predictedData = predictor.getPredictedData(filteredInputData, predictionInterval, samplingInterval)
exportData(logDir + "PredictionData.txt", predictedData)
# Run the transmission algorithm
print "Simulating the transmission algorithm..."
transmitter = DRTransmitter(heartbeat)
drTxPackets = transmitter.getTransmittedPackets(drThreshold, predictedData)
exportData(logDir + "DRTxPackets.txt", drTxPackets)
# Simulate the transmission of the packets
print "Simulating the network..."
network = Network()
drRxPackets = network.getReceivedPackets(drTxPackets, delay, jitter, packetLoss)
exportData(logDir + "DRRxPackets.txt", drRxPackets)
# Receive the packets
print "Receiving the packets..."
receiver = Receiver()
drRxFilteredPackets = receiver.getFilteredData(drRxPackets)
exportData(logDir + "DRRxData.txt", drRxFilteredPackets)
return [rawInputData, filteredInputData, predictedData, drTxPackets,
drRxPackets, drRxFilteredPackets]
predictedData = predictor.getPredictedData(inputData, predictionInterval, samplingInterval) # Run the transmission algorithm print "Simulating the transmission algorithm..." transmitter = DRTransmitter(heartbeat) DRTxPackets = transmitter.getTransmittedPackets(threshold, predictedData) # Simulate the transmission of the packets print "Simulating the network..." network = Network() DRRxPackets = network.getReceivedPackets(DRTxPackets, delay, jitter, packetLoss) # Receive the packets print "Receiving the packets..." receiver = Receiver() DRRxData = receiver.getFilteredData(DRRxPackets) # Reconstruct the transmitted and received data print "Reconstructing the signals..." reconstructor = SnapReconstructor() DRTxData = reconstructor.getReconstructedSignal(DRTxPackets, samplingInterval) DRRxReconData = reconstructor.getReconstructedSignal(DRRxData, samplingInterval) # Split data into components inputTime = range(0, len(inputData) * samplingInterval, samplingInterval) x = [] y = [] z = [] transmittedTime = [] txX = [] txY = []
else:
stepFunc.append(Sample(i, 1, 1, 1))
predictor = DRPredictor()
predictedData = predictor.getPredictedData(stepFunc, predictionInterval,
samplingInterval)
s.exportData(logDir + "PredictionData.txt", predictedData)
transmitter = DRTransmitter(heartbeat)
drTxPackets = transmitter.getTransmittedPackets(.9, predictedData)
s.exportData(logDir + "TransmittedData.txt", drTxPackets)
network = Network()
drRxPackets = network.getReceivedPackets(drTxPackets, delay, jitter,
packetLoss)
s.exportData(logDir + "ReceivedData.txt", drRxPackets)
receiver = Receiver()
drRxFilteredPackets = receiver.getFilteredData(drRxPackets)
s.exportData(logDir + "FilteredData.txt", drRxFilteredPackets)
convergedData = s.convergeData(drRxFilteredPackets, logDir, "-",
samplingInterval, interpolationType,
reconstructionThreshold)[0]
iData = [[]] * 4
cData = [[]] * 4
iData[0], iData[1], iData[2], iData[3] = s.splitData(stepFunc)
cData[0], cData[1], cData[2], cData[3] = s.splitData(convergedData)
pylab.figure(1)
pylab.plot(iData[0], iData[1], 'k-', cData[0], cData[1], 'b-')
pylab.axis([0, 2000, -.1, 1.8])
if i < 200: stepFunc.append( Sample(i, 0, 0, 0) ) else: stepFunc.append( Sample(i, 1, 1, 1) ) predictor = DRPredictor() predictedData = predictor.getPredictedData(stepFunc, predictionInterval, samplingInterval) s.exportData(logDir + "PredictionData.txt", predictedData) transmitter = DRTransmitter(heartbeat) drTxPackets = transmitter.getTransmittedPackets(.9, predictedData) s.exportData(logDir + "TransmittedData.txt", drTxPackets) network = Network() drRxPackets = network.getReceivedPackets(drTxPackets, delay, jitter, packetLoss) s.exportData(logDir + "ReceivedData.txt", drRxPackets) receiver = Receiver() drRxFilteredPackets = receiver.getFilteredData(drRxPackets) s.exportData(logDir + "FilteredData.txt", drRxFilteredPackets) convergedData = s.convergeData(drRxFilteredPackets, logDir, "-", samplingInterval, interpolationType, reconstructionThreshold)[0] iData = [ [] ] * 4 cData = [ [] ] * 4 iData[0], iData[1], iData[2], iData[3] = s.splitData(stepFunc) cData[0], cData[1], cData[2], cData[3] = s.splitData(convergedData) pylab.figure(1) pylab.plot(iData[0], iData[1], 'k-', cData[0], cData[1], 'b-') pylab.axis([ 0, 2000, -.1, 1.8 ]) pylab.show()
