bands = [0.0, 1, 2, 50.0]
weights = [1, 0]
# Simulate the transmission and part of the reconstruction
startTimeTotal = time.time()
testData = []
staticJumps = [ [ [], [], [] ],
[ [], [], [] ],
[ [], [], [] ],
[ [], [], [] ] ]
for inputFile in inputFiles:
simulationData = sim.simulateTransmission(inputFile, logDir, predictionInterval,
samplingInterval, heartbeat, drThreshold,
delay, jitter, packetLoss)
simNumber = inputFile.split('/')[-2][-1]
snapReconstruction = sim.simulateSnapRecon(simulationData[4], logDir, simNumber, samplingInterval)[0]
snapLimitReconstruction = sim.simulateSnapLimitRecon(simulationData[4], logDir, simNumber, samplingInterval,
interpolationType, closeThreshold, snapLimit)[0]
convergedReconstruction = sim.simulateLinearConvergence(simulationData[4], logDir, simNumber, samplingInterval,
interpolationType, closeThreshold)[0]
testData.append([simulationData[0], simulationData[4], snapReconstruction,
snapLimitReconstruction, convergedReconstruction])
# Find intra-sample jump
threshold = 0
spacing = 1
jumpDataSets = []
jumpDataSets.append( sim.findDistanceBetweenSamples(simulationData[0], threshold, spacing) )
jumpDataSets.append( sim.findDistanceBetweenSamples(snapReconstruction, threshold, spacing) )
jumpDataSets.append( sim.findDistanceBetweenSamples(snapLimitReconstruction, threshold, spacing) )
jumpDataSets.append( sim.findDistanceBetweenSamples(convergedReconstruction, threshold, spacing) )
errors = [] deltaInput = [] deltaSnap = [] deltaConverge = [] # Simulate the transmission simulationData = sim.simulateTransmission(inputFile, logDir, predictionInterval, samplingInterval, heartbeat, drThreshold, delay, jitter, packetLoss) inputData = simulationData[0] deltaInput = sim.findDistanceBetweenSamples(inputData, jumpThreshold, spacing) for reconThreshold in reconThresholds: convergeTxData = sim.simulateLinearConvergence(simulationData[4], logDir, "_ex1", samplingInterval, interpolationType, reconThreshold) snapRxData = sim.simulateSnapRecon(simulationData[4], logDir, "_ex1", samplingInterval) errors.append( sim.findDistanceError(inputData, convergeTxData[0]) ) deltaSnap.append( sim.findDistanceBetweenSamples(snapRxData, jumpThreshold, spacing) ) deltaConverge.append( sim.findDistanceBetweenSamples(convergeTxData, jumpThreshold, spacing) ) # Prepare the data for plotting temp = [] for error in errors: temp.append( scipy.stats.mean(error) ) errors = temp #pylab.figure(1) #pylab.plot(reconThresholds, errors) pylab.figure(2) n, bins, patches = pylab.hist(deltaInput, 50)
