def runMainLoop(self, directory): #setup directory for correlated traces dataFolderDirectory = directory #create arrays that contain all the .trc files for both chan 1 and chan 2 (Separate) globPathNameChanOne = dataFolderDirectory + '/C1*.trc' globPathNameChanTwo = dataFolderDirectory + '/C2*.trc' fileArrayOne = glob.glob(globPathNameChanOne) fileArrayTwo = glob.glob(globPathNameChanTwo) #setup to progress through entire array of .trc files numTraces = len(fileArrayOne) fileArrayIndex = 0 #perform a while loop to progress through the individual correlated trace measurements while (fileArrayIndex < numTraces): #extract data from .trc files associated with the current index counter into arrays of data fileChanOne = fileArrayOne[fileArrayIndex] fileChanTwo = fileArrayTwo[fileArrayIndex] timeAxis = lecroyparser.ScopeData(fileChanOne).x dataChanOne = lecroyparser.ScopeData(fileChanOne).y dataChanTwo = lecroyparser.ScopeData(fileChanTwo).y if fileArrayIndex == 0: sumChanOne = dataChanOne[0:self.numSamples] sumChanTwo = dataChanTwo[0:self.numSamples] else: sumChanOne += dataChanOne[0:self.numSamples] sumChanTwo += dataChanTwo[0:self.numSamples] if (fileArrayIndex % updateEveryXTraces == 0) : updatePlotsFlag = True else: updatePlotsFlag = False #process correlated channels as desired #show user what traces look like self.plotBothChannels(dataChanOne, dataChanTwo, updatePlotsFlag) #go into the ringing range and add that fourier component to an ongoign sum self.addNewTraceRinging(dataChanTwo, updatePlotsFlag, dataChanOne, fileArrayIndex) #process the current traces to add their hits to the growing histograms self.addToHistograms(dataChanOne, dataChanTwo, updatePlotsFlag) #increment the file array index to proceed to the next trace fileArrayIndex += 1 if updatePlotsFlag : plt.plot(self.timeAxis, sumChanOne) plt.plot(self.timeAxis, sumChanTwo) plt.xlim([0, 1e-7]) plt.draw() #plt.waitforbuttonpress() plt.pause(0.1) return self.energyHistogramOne, self.energyVector
def getHeaderBytesTimes(fname):
data = lecroyparser.ScopeData(fname)
nvals = len(data.y)
f = open(fname, 'br')
buf = f.read()
f.close()
nseek = int(len(buf) - 2 * nvals)
return (nseek, nvals, data.x)
def get_channel(self, channel='C1'):
# read channel data
if (self.scope):
cmd = self.scope.write('{0}:WF? DATA1'.format(channel))
trc = self.scope.read_raw()
newFile = open("filename.txt", "wb")
newFile.write(trc)
time.sleep(2)
data = lecroyparser.ScopeData('filename.txt')
return [data.x, data.y]
else:
return None
def readInDataFromFolderWithTime():
global fileArrayIndex
fileNameNow = fileArray[fileArrayIndex]
dataNow = lecroyparser.ScopeData(fileNameNow)
fileArrayIndex += 1
return dataNow.y, dataNow.x
def runMainLoop(self, directory):
#setup directory for correlated traces
dataFolderDirectory = directory
#create arrays that contain all the .trc files for both chan 1 and chan 2 (Separate)
globPathNameChanOne = dataFolderDirectory + '/C1*.trc'
globPathNameChanTwo = dataFolderDirectory + '/C2*.trc'
fileArrayOne = glob.glob(globPathNameChanOne)
fileArrayTwo = glob.glob(globPathNameChanTwo)
#setup to progress through entire array of .trc files
numTraces = len(fileArrayOne)
freqCutoffLow = 0
freqCutoffHigh = 400
freqSamplesToKeep = freqCutoffHigh - freqCutoffLow
fileArrayIndex = 0
traceStrengths = np.zeros(numTraces)
ringingStrengths = np.zeros(numTraces)
amplitudesSpans = np.zeros(numTraces)
#perform a while loop to progress through the individual correlated trace measurements
while (fileArrayIndex < numTraces):
#extract data from .trc files associated with the current index counter into arrays of data
fileChanOne = fileArrayOne[fileArrayIndex]
fileChanTwo = fileArrayTwo[fileArrayIndex]
timeAxis = lecroyparser.ScopeData(fileChanOne).x
timeAxis = timeAxis * 1e9
dataChanOne = lecroyparser.ScopeData(fileChanOne).y
dataChanTwo = lecroyparser.ScopeData(fileChanTwo).y
if fileArrayIndex == 0:
#create frequency axis
numSamples = timeAxis.size
self.freqAxis = Fs* np.linspace(0, numSamples-1, numSamples) / numSamples
spectralMap = np.zeros((numTraces, freqSamplesToKeep))
triggerStrength = np.sum(dataChanTwo)
ampSpan = np.amax(dataChanOne) - np.amin(dataChanOne)
chanOneSpectral = fft(dataChanOne)
absFFT = np.absolute(chanOneSpectral)
powerSpectrum = np.square(absFFT)
traceStrengths[fileArrayIndex] = -1*triggerStrength*0.025
spectralMap[fileArrayIndex, :] = powerSpectrum[freqCutoffLow:freqCutoffHigh]
ringingStrengths[fileArrayIndex] = np.sum(powerSpectrum[freqCutoffLow:freqCutoffHigh])
amplitudesSpans[fileArrayIndex] = ampSpan
if False and ((fileArrayIndex % updateEveryXTraces) == 0):
#clear previous lines
linesOld = self.axisTracesHigh.lines
for i in range(len(linesOld)):
lineToDel = linesOld.pop(0)
del lineToDel
linesOld = self.axisTracesLow.lines
for i in range(len(linesOld)):
lineToDel = linesOld.pop(0)
del lineToDel
plt.sca(self.axisTracesHigh)
plt.plot(timeAxis, dataChanTwo, c='tab:blue')
plt.xticks(fontsize=26)
plt.yticks(fontsize=26)
# self.axisTracesHigh.set_xlim((25e-9, 1e-7))
plt.sca(self.axisTracesLow)
plt.plot(timeAxis, 1000*dataChanOne, c='tab:orange')
plt.xticks(fontsize=26)
plt.yticks(fontsize=26)
# self.axisTracesLow.set_xlim((25e-9, 1e-7))
plt.draw()
linesOld = self.axisPowerSpectrum.lines
for i in range(len(linesOld)):
lineToDel = linesOld.pop(0)
del lineToDel
plt.figure(self.figHandleFourier.number)
plt.plot(self.freqAxis/1e9, powerSpectrum)
plt.xticks(fontsize=26)
plt.yticks(fontsize=26)
plt.draw()
plt.pause(0.001)
# plt.waitforbuttonpress()
breakpoint()
#increment the file array index to proceed to the next trace
fileArrayIndex += 1
sortKeys = np.argsort(traceStrengths)
sortedSpectralMap = spectralMap[sortKeys, :]
# breakpoint()
heatMapHandle = plt.figure(figsize=(9,6))
heatMapHandle.add_axes([0.2, 0.2, 0.7, 0.7])
temp = np.linspace(0, numTraces-1, numTraces)
tempFreq = self.freqAxis[freqCutoffLow:freqCutoffHigh]
plt.pcolormesh(tempFreq*1e-9, temp, np.log(sortedSpectralMap), shading='auto', vmin=-1, vmax=2.5)
plt.colorbar()
plt.xlim(freqLimits)
plt.title("Tracking log(Spectral Power)", fontsize=30)
plt.xlabel("Frequency (GHz)", fontsize=30)
plt.ylabel("Unique Measurements\n", fontsize=30)
plt.yticks([], fontsize=26)
plt.xticks(freqTicks, fontsize=26)
plt.draw()
plt.figure(figHandleRingStrength.number)
scatNow = plt.scatter(traceStrengths, ringingStrengths, s=1)
scatterList.append(scatNow)
plt.draw()
plt.pause(0.001)
def _set_orderOfMagnitude(self, range):
"""Over-riding this to avoid having orderOfMagnitude reset elsewhere"""
self.orderOfMagnitude = self._order_of_mag
if len(sys.argv) < 2:
print("Usage: %s <filename>", sys.argv[0])
path = sys.argv[1]
c2path = path.replace("C3--Trace", "C2--Trace")
c3path = path.replace("C2--Trace", "C3--Trace")
print(c2path)
print(c3path)
c2 = lecroyparser.ScopeData(c2path)
c3 = lecroyparser.ScopeData(c3path)
fig, ax1 = plt.subplots()
color = 'tab:red'
ax1.set_xlabel('Time in s', fontsize=fontsize)
ax1.set_ylabel('EM-Signal (Volt)', color=color, fontsize=fontsize)
ax1.plot(c2.x, c2.y, color=color)
ax1.tick_params(axis='y', labelcolor=color)
ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis
color = 'tab:blue'
ax2.set_ylabel('Volt', color=color,
fontsize=fontsize) # we already handled the x-label with ax1
plt.xticks([i*1e-9 for i in range(0,3600,500)],fontsize=fontsize)
plt.yticks([i*0.01 for i in range(-10,8,2)],fontsize=fontsize)
if len(sys.argv) < 2:
print("Usage: %s <path>",sys.argv[0])
prefix = sys.argv[1]
if prefix[-1] != "/":
prefix += "/"
for i in range(15,-1,-1):
numstr = str(i)
while len(numstr) < 5:
numstr = "0"+numstr
curpath = prefix + "C2--Trace--"+numstr+".trc"
print(curpath)
data = lecroyparser.ScopeData(curpath)
plt.plot(data.x,data.y)
plt.xlabel('Time in s', fontsize=fontsize)
plt.ylabel('EM-Signal (Volt)', fontsize=fontsize)
title = "Multiple block decryptions"
plt.title(title, fontsize=fontsize)
plt.show()
def parse_file(datafile: str, vendor: str) -> object:
if vendor == 'lecroy':
data = lecroyparser.ScopeData(datafile)
if vendor == 'tek':
data = tek.ScopeData(datafile)
return data
