def calibrateScanMirror(appObj):
DebugLog.log("calibrateScanMirror")
appObj.tabWidget.setCurrentIndex(7)
appObj.doneFlag = False
appObj.isCollecting = True
appObj.JSOsaveDispersion_pushButton.setEnabled(True)
appObj.JSOloadDispersion_pushButton.setEnabled(False)
if not appObj.oct_hw.IsOCTTestingMode(): # prepare to get new data
from DAQHardware import DAQHardware
daq = DAQHardware()
audioHW=appObj.audioHW
mirrorDriver = appObj.mirrorDriver
chanNames = [mirrorDriver.X_daqChan, mirrorDriver.Y_daqChan]
trigChan = audioHW.daqTrigChanIn #use the audio trigger to start the scan
outputRate = mirrorDriver.DAQoutputRate
while appObj.doneFlag == False: # keep running until the button is turned off
scanParams = appObj.getScanParams()
# create scan pattern to drive the mirrors
mode=appObj.scanShape_comboBox.currentIndex()
print('mode',mode)
if mode==0: # create a spiral scan using fast (resonant) scanning
Vmaxx=mirrorDriver.voltRange[1] # maximum voltage for MEMS mirror for x-axis
Vmaxy=mirrorDriver.voltRange[1] # maximum voltage for MEMS mirror for y-axis
xAdjust = 1
yAdjust = scanParams.skewResonant
phaseShift = scanParams.phaseAdjust
fr = mirrorDriver.resonantFreq # angular scan rate (frequency of one rotation - resonant frequency)
fv = scanParams.volScanFreq # plotParam scan frequency, which scans in and then out, which is actually two volumes
DebugLog.log("freq of one rotation (fr)= %d; scan frequency (fv)= %d" % (fr, fv))
diameter = scanParams.length
voltsPerMM = mirrorDriver.voltsPerMillimeterResonant
A1=(Vmaxx/2)/xAdjust
A2=(Vmaxy/2)/yAdjust
A3=voltsPerMM*diameter/2
A=np.min([A1,A2,A3])
fs=mirrorDriver.DAQoutputRate # galvo output sampling rate
t=np.arange(0,np.around(fs/fv))*1/fs # t is the array of times for the DAQ output to the mirrors
r=1/2*(1-np.cos(2*np.pi*fv*t))
x=xAdjust*A*r*np.cos(2*np.pi*fr*t) # x and y are the coordinates of the laser at each point in time
y=yAdjust*A*r*np.sin(2*np.pi*fr*t+phaseShift*np.pi/180)
mirrorOut= np.vstack((x,y))
elif mode==1: # create a square scan using slow parameters
Vmaxx=mirrorDriver.voltRange[1] # maximum voltage for MEMS mirror for x-axis
Vmaxy=mirrorDriver.voltRange[1] # maximum voltage for MEMS mirror for y-axis
xAdjust = 1
yAdjust = scanParams.skewNonResonant
diameter = scanParams.length
voltsPerMMX = mirrorDriver.voltsPerMillimeter*xAdjust
voltsPerMMY = mirrorDriver.voltsPerMillimeter*yAdjust
if ((diameter/2)*voltsPerMMX)>Vmaxx:
diameter=2*Vmaxx/voltsPerMMX
if ((diameter/2)*voltsPerMMY)>Vmaxy:
diameter=2*Vmaxy/voltsPerMMY
freq = appObj.cal_freq_dblSpinBox.value()
if freq>mirrorDriver.LPFcutoff: # can't go faster than the maximum scan rate
appObj.cal_freq_dblSpinBox.setValue(mirrorDriver.LPFcutoff)
fs=mirrorDriver.DAQoutputRate # galvo output sampling rate
t1=np.arange(0,np.around(fs/freq))*1/fs
n=np.around(t1.shape[0]/4)-1 # number of points in each 4th of the cycle (reduce by 1 to make it easy to shorten t1)
t=t1[0:4*n] # t is the array of times for the DAQ output to the mirrors
cornerX=(diameter/2)*voltsPerMMX # voltage at each corner of the square
cornerY=(diameter/2)*voltsPerMMY # voltage at each corner of the square
# x and y are the coordinates of the laser at each point in time
x=np.zeros(t.shape)
y=np.zeros(t.shape)
x[0:n]=np.linspace(-cornerX,cornerX,n)
y[0:n]=-cornerY
x[n:2*n]=cornerX
y[n:2*n]=np.linspace(-cornerY,cornerY,n)
x[2*n:3*n]=np.linspace(cornerX,-cornerX,n)
y[2*n:3*n]=cornerY
x[3*n:4*n]=-cornerX
y[3*n:4*n]=np.linspace(cornerY,-cornerY,n)
mirrorOut1= np.vstack((x,y))
if mirrorDriver.MEMS==True:
mirrorOut=scipy.signal.filtfilt(mirrorDriver.b_filt,mirrorDriver.a_filt,mirrorOut1)
else:
mirrorOut=mirrorOut1
# plot mirror commands to GUI
pl = appObj.JSOmisc_plot1
npts = mirrorOut.shape[1]
t = np.linspace(0, npts/outputRate, npts)
pl.clear()
pl.plot(t, mirrorOut[0, :], pen='b')
pl.plot(t, mirrorOut[1, :], pen='r')
labelStyle = appObj.xLblStyle
pl.setLabel('bottom', 'Time', 's', **labelStyle)
labelStyle = appObj.yLblStyle
pl.setLabel('left', 'Output', 'V', **labelStyle)
pl2=appObj.JSOmisc_plot2
pl2.clear()
pl2.plot(mirrorOut[0, :],mirrorOut[1, :], pen='b')
labelStyle = appObj.xLblStyle
pl2.setLabel('bottom', 'X galvo', 'V', **labelStyle)
labelStyle = appObj.yLblStyle
pl2.setLabel('left', 'Y galvo', 'V', **labelStyle)
if not appObj.oct_hw.IsDAQTestingMode():
# setup the analog output DAQ device
daq.setupAnalogOutput(chanNames, trigChan, outputRate, mirrorOut.transpose())
daq.startAnalogOutput()
#start trigger and wait for output to finish
daq.sendDigTrig(audioHW.daqTrigChanOut)
daq.waitDoneOutput(timeout=3, stopAndClear=True)
QtGui.QApplication.processEvents() # check for GUI events
else:
appObj.doneFlag = True # just run one time through if in test mode
appObj.CalibrateScanMirror_pushButton.setChecked(False)
# when testing is over, set the mirror position to (0,0)
if not appObj.oct_hw.IsDAQTestingMode():
chanNames = [mirrorDriver.X_daqChan, mirrorDriver.Y_daqChan]
data = np.zeros(2)
daq.writeValues(chanNames, data)
appObj.JSOsaveDispersion_pushButton.setEnabled(False)
appObj.JSOloadDispersion_pushButton.setEnabled(True)
appObj.isCollecting = False
appObj.finishCollection()
def runJSOraw(appObj):
DebugLog.log("runJSOraw")
try:
appObj.tabWidget.setCurrentIndex(7)
appObj.doneFlag = False
appObj.isCollecting = True
appObj.JSOsaveDispersion_pushButton.setEnabled(True)
appObj.JSOloadDispersion_pushButton.setEnabled(False)
dispData = appObj.dispData # this class holds all the dispersion compensation data
if dispData is None:
dispData = Dispersion.DispersionData()
laserSweepFreq=appObj.octSetupInfo.getTriggerRate()
mirrorDriver = appObj.mirrorDriver
if not appObj.oct_hw.IsOCTTestingMode(): # prepare to get new data
# set the mirror position to (0,0)
chanNames = [mirrorDriver.X_daqChan, mirrorDriver.Y_daqChan]
data = np.zeros(2)
from DAQHardware import DAQHardware
daq = DAQHardware()
daq.writeValues(chanNames, data)
else:
appObj.savedDataBuffer.loadData(appObj)
peakXPos=np.array([0],dtype=int)
peakYPos=np.array([0],dtype=float)
peakXPos1=np.array([0],dtype=int)
peakYPos1=np.array([0],dtype=float)
while appObj.doneFlag == False:
# read data analysis settings from the GUI
numTrigs=appObj.numTrig.value()
dispData.requestedSamplesPerTrig=appObj.requestedSamplesPerTrig.value()
dispData.startSample=appObj.startSample.value()
dispData.endSample=appObj.endSample.value()
dispData.numKlinPts=appObj.numKlinPts.value()
dispData.Klin=np.zeros(dispData.numKlinPts)
dispData.numShiftPts=appObj.numShiftPts.value()
dispData.filterWidth=appObj.filterWidth.value()
dispData.mziFilter=appObj.mziFilter.value()
dispData.magWin_LPfilterCutoff=appObj.dispMagWindowFilter.value()
dispData.PDfilterCutoffs=[0,0]
dispData.dispCode=appObj.dispersionCompAlgorithm_comboBox.currentIndex()
dispData.dispMode=appObj.dispersionCompAlgorithm_comboBox.currentText()
# Get data using one of several methods
if appObj.oct_hw.IsOCTTestingMode():
ch0_data,ch1_data=getSavedRawData(numTrigs,dispData.requestedSamplesPerTrig,appObj.savedDataBuffer)
else:
ch0_data,ch1_data=getNewRawData(numTrigs,dispData.requestedSamplesPerTrig,appObj)
if appObj.saveData_checkBox.isChecked()==True: # save data to disk for later use if desired
fileName='Mirror_Raw'
dataToSave = (ch0_data, ch1_data)
appObj.savedDataBuffer.saveData(appObj,dataToSave,fileName)
appObj.saveData_checkBox.setChecked(False)
# delay the MZI to account for it having a shorter optical path than the sample/reference arm path, then calculate k0 as the MZI phase
pdData,mziData,actualSamplesPerTrig=channelShift(ch0_data,ch1_data,dispData)
textString='Actual samples per trigger: {actualSamplesPerTrig}'.format(actualSamplesPerTrig=actualSamplesPerTrig)
appObj.actualSamplesPerTrig_label.setText(textString)
import time
t1 = time.time()
mzi_hilbert, mzi_mag, mzi_ph, k0 = processMZI(mziData, dispData)
mzi_proc_time = time.time() - t1
print("MZI processing time = %0.4f ms" % (mzi_proc_time*1000))
# Adjust the k0 curves so that the unwrapping all starts at the same phase
appObj.k0_plot_3.clear()
appObj.k0_plot_4.clear()
appObj.k0_plot_5.clear()
t1 = time.time()
k0Cleaned=cleank0(k0,dispData)
k0clean_time = time.time() - t1
print("k0 cleaning time = %0.4f ms" % (k0clean_time*1000))
for i in range(numTrigs):
appObj.k0_plot_3.plot(k0[i,:2*dispData.startSample], pen=(i,numTrigs))
startMZIdata1=k0[:,dispData.startSample]
appObj.k0_plot_4.plot(startMZIdata1, pen='r')
startMZIdata2=k0Cleaned[:,dispData.startSample]
appObj.k0_plot_4.plot(startMZIdata2, pen='b')
for i in range(numTrigs):
appObj.k0_plot_5.plot(k0Cleaned[i,:2*dispData.startSample], pen=(i,numTrigs))
k0=k0Cleaned
# Interpolate the PD data based upon the MZI data and calculate the a-lines before dispersion compensation
t1 = time.time()
pd_interpRaw, klin = processPD(pdData, k0, dispData)
interpPD_time = time.time() - t1
print("Interp PD time = %0.4f ms" % (interpPD_time*1000))
dispData.Klin=klin
pd_fftNoInterp, alineMagNoInterp, alinePhaseNoInterp = calculateAline(pdData[:,dispData.startSample:dispData.endSample])
t1 = time.time()
pd_fftRaw, alineMagRaw, alinePhaseRaw = calculateAline(pd_interpRaw)
alineCalc_time = time.time() - t1
print("Aline calc time = %0.4f ms" % (alineCalc_time*1000))
# find the mirror in the a-line to determine the filter settings, and then perform the dispersion compensatsion
rangePeak1=[100, 900]
alineAve1=np.average(alineMagRaw,axis=0)
peakXPos1[0]=np.argmax(alineAve1[rangePeak1[0]:rangePeak1[1]])+rangePeak1[0]
peakYPos1[0]=alineAve1[peakXPos1[0]]
width=dispData.filterWidth*(rangePeak1[1]-rangePeak1[0])/2
dispData.PDfilterCutoffs[0]=(peakXPos1[0]+width)/2048
dispData.PDfilterCutoffs[1]=(peakXPos1[0]-width)/2048
dispersionCorrection(pd_interpRaw,dispData)
appObj.dispData=dispData #store the local variable in the overall class so that it can be saved when the save button is pressed
# now correct the data using dispersion compensation and then process the a-lines
pd_interpDispComp = dispData.magWin * pd_interpRaw * (np.cos(-1*dispData.phaseCorr) + 1j * np.sin(-1*dispData.phaseCorr))
pd_fftDispComp, alineMagDispComp, alinePhaseDispComp = calculateAline(pd_interpDispComp)
#scale k0 and the MZI to the same range to plot them so they overlap
k0Ripple= scipy.signal.detrend(k0[0,500:700],axis=-1)
k0RippleNorm=k0Ripple/k0Ripple.max()
mziDataRipple= scipy.signal.detrend(mziData[0,500:700],axis=-1)
mziDataNorm=mziDataRipple/mziDataRipple.max()
# Find the peak of the A-line within a range and calculate the phase noise
rangePeak=[100, 900]
alineAve=np.average(alineMagDispComp,axis=0)
peakXPos[0]=np.argmax(alineAve[rangePeak[0]:rangePeak[1]])+rangePeak[0]
peakYPos[0]=alineAve[peakXPos[0]]
t=np.arange(numTrigs)/laserSweepFreq
phaseNoiseTD=np.unwrap(alinePhaseDispComp[:,peakXPos[0]])
phaseNoiseTD=phaseNoiseTD-np.mean(phaseNoiseTD)
phaseNoiseTD=phaseNoiseTD*1310e-9/(4*np.pi*1.32)
phaseNoiseFFT = np.abs(np.fft.rfft(phaseNoiseTD))/(numTrigs/2)
# phaseNoiseFD = 20*np.log10(np.abs(phaseNoiseFFT))
freq = np.fft.rfftfreq(numTrigs)*laserSweepFreq
# Clear all of the plots
appObj.mzi_plot_2.clear()
appObj.pd_plot_2.clear()
appObj.mzi_mag_plot_2.clear()
appObj.mzi_phase_plot_2.clear()
appObj.k0_plot_2.clear()
appObj.interp_pdRaw_plot.clear()
appObj.interp_pdDispComp_plot.clear()
appObj.alineNoInterp_plot.clear()
appObj.alineRaw_plot.clear()
appObj.alineDispComp_plot.clear()
appObj.phaseNoiseTD_plot.clear()
appObj.phaseNoiseFD_plot.clear()
appObj.dispWnfcMag_plot.clear()
appObj.dispWnfcPh_plot.clear()
# Plot all the data
if appObj.plotFirstOnly_checkBox.isChecked()==True:
i=0
appObj.pd_plot_2.plot(pdData[i,:], pen='r')
appObj.mzi_plot_2.plot(mziData[i,:], pen='r')
appObj.mzi_mag_plot_2.plot(mzi_mag[i,:], pen='r')
appObj.k0_plot_2.plot(k0[i,:], pen='r')
sampleNum=np.linspace(dispData.startSample,dispData.endSample,dispData.numKlinPts)
appObj.k0_plot_2.plot(sampleNum,klin, pen='b')
appObj.interp_pdRaw_plot.plot(pd_interpRaw[i,:], pen='r')
appObj.interp_pdDispComp_plot.plot(np.abs(pd_interpDispComp[i,:]), pen='r')
appObj.alineNoInterp_plot.plot(alineMagNoInterp[i,:], pen='r')
appObj.alineRaw_plot.plot(alineMagRaw[i,:], pen='r')
appObj.alineDispComp_plot.plot(alineMagDispComp[i,:], pen='r')
else:
# limit plotting to first 10 or so triggers, otherwise this will freeze up
nTrigs = min((numTrigs, 10))
for i in range(nTrigs):
pen=(i,nTrigs)
appObj.pd_plot_2.plot(pdData[i,:], pen=pen)
appObj.mzi_plot_2.plot(mziData[i,:], pen=pen)
appObj.mzi_mag_plot_2.plot(mzi_mag[i,:], pen=pen)
appObj.mzi_phase_plot_2.plot(mzi_ph[i,:], pen=pen)
appObj.k0_plot_2.plot(k0[i,:], pen=pen)
appObj.interp_pdRaw_plot.plot(pd_interpRaw[i,:], pen=pen)
appObj.interp_pdDispComp_plot.plot(np.abs(pd_interpDispComp[i,:]), pen=pen)
appObj.alineNoInterp_plot.plot(alineMagNoInterp[i,:], pen=pen)
appObj.alineRaw_plot.plot(alineMagRaw[i,:], pen=pen)
appObj.alineDispComp_plot.plot(alineMagDispComp[i,:], pen=pen)
appObj.alineRaw_plot.plot(peakXPos1,peakYPos1, pen=None, symbolBrush='k', symbolPen='b')
appObj.alineDispComp_plot.plot(peakXPos,peakYPos, pen=None, symbolBrush='k', symbolPen='b')
appObj.phaseNoiseTD_plot.plot(t,phaseNoiseTD, pen='r')
appObj.phaseNoiseFD_plot.plot(freq,phaseNoiseFFT, pen='r')
appObj.mzi_phase_plot_2.plot(mziDataNorm, pen='b')
appObj.mzi_phase_plot_2.plot(k0RippleNorm, pen='r')
# if you want to align the pd and the Mzi data
# plotPDPhase.plot(pdData[0,:], pen='r')
# plotPDPhase.plot(mziData[0,:], pen='b')
appObj.dispWnfcMag_plot.plot(dispData.magWin, pen='b')
appObj.dispWnfcPh_plot.plot(dispData.phaseCorr, pen='b')
# plot filter cutoff ranges on the raw Aline plot
yy=[np.min(alineMagRaw[0,:]),np.max(alineMagRaw[0,:])]
xx0=[alineMagRaw.shape[1]*dispData.PDfilterCutoffs[0],alineMagRaw.shape[1]*dispData.PDfilterCutoffs[0]]
xx1=[alineMagRaw.shape[1]*dispData.PDfilterCutoffs[1],alineMagRaw.shape[1]*dispData.PDfilterCutoffs[1]]
appObj.alineRaw_plot.plot(xx0,yy, pen='b')
appObj.alineRaw_plot.plot(xx1,yy, pen='b')
# # Now create a bscan image from the 1 aline, but sweep the shift value between the mzi and pd to see what works best
# nShift=201
# bscan=np.zeros([nShift, alineMag.shape[0]])
# for i in range(nShift):
# shift=i-(nShift-1)/2
# if shift<0:
# mzi_data_temp=mzi_data[-1*shift:]
# pd_data_temp=pd_data[0:mzi_data_temp.shape[0]]
# # print(mzi_data_temp.shape,pd_data_temp.shape)
# elif shift>0:
# pd_data_temp=pd_data[shift:]
# mzi_data_temp=mzi_data[0:pd_data_temp.shape[0]]
# # print(mzi_data_temp.shape,pd_data_temp.shape)
# elif shift==0:
# pd_data_temp=pd_data
# mzi_data_temp=mzi_data
#
# mzi_hilbert, mzi_mag, mzi_ph, k0 = processMZI(mzi_data_temp)
# pd_interpRaw, pd_interpHanning, pd_fft, alineMag, alinePhase, klin = processPD(pd_data_temp, k0, klin_idx, numklinpts)
# bscan[i,:]=alineMag
#
# pl = self.bscan_plot
# pl.setImage(bscan)
# print('alineMagDispComp ',alineMagDispComp.shape)
if ~np.all(np.isnan(alineMagDispComp)): # only make the bscan plot if there is data to show (this prevents an error from occurring)
appObj.bscan_plot.setImage(alineMagDispComp)
QtGui.QApplication.processEvents() # check for GUI events
except:
traceback.print_exc(file=sys.stdout)
QtGui.QMessageBox.critical (appObj, "Error", "Error during scan. Check command line output for details")
appObj.JSOsaveDispersion_pushButton.setEnabled(False)
appObj.JSOloadDispersion_pushButton.setEnabled(True)
appObj.isCollecting = False
QtGui.QApplication.processEvents() # check for GUI events
appObj.finishCollection()
def runDispersion(appObj):
DebugLog.log("runDispersion")
appObj.tabWidget.setCurrentIndex(5)
appObj.doneFlag = False
appObj.isCollecting = True
# trigRate = octfpga.GetTriggerRate()
mirrorDriver = appObj.mirrorDriver
# set the mirror position to (0,0)
chanNames = [mirrorDriver.X_daqChan, mirrorDriver.Y_daqChan]
data = np.zeros(2)
if not appObj.oct_hw.IsDAQTestingMode():
from DAQHardware import DAQHardware
daq = DAQHardware()
daq.writeValues(chanNames, data)
pd_background = None
fpgaOpts = appObj.oct_hw.fpgaOpts
numklinpts = fpgaOpts.numKlinPts
if fpgaOpts.InterpDownsample > 0:
numklinpts = numklinpts // 2
# keep looping until we are signlaed to stop by GUI (flag set in appObj)
try:
frameNum = 0
saveDirInit = False
testDataDir = os.path.join(appObj.basePath, 'exampledata', 'Dispersion')
dispData = DispersionData(fpgaOpts)
klin = None # initialze klin to None so it will be computed first iteration
savedFPGADisp = False
while not appObj.doneFlag:
# setup and grab the OCT data - this will also fire the mirror output
numTrigs = appObj.disp_numTrigs_spinBox.value()
processMode = OCTCommon.ProcessMode(appObj.processMode_comboBox.currentIndex())
# get proessing optiosn from GUI
PD_LP_fc = appObj.disp_pd_lpfilter_cutoff_dblSpinBox.value()
PD_HP_fc = appObj.disp_pd_hpfilter_cutoff_dblSpinBox.value()
PDfiltCutoffs = [PD_LP_fc, PD_HP_fc]
magWin_LPfilterCutoff = appObj.disp_magwin_lpfilter_cutoff_dblSpinBox.value()
dispData.mziFilter = appObj.mziFilter.value()
dispData.magWin_LPfilterCutoff = magWin_LPfilterCutoff
dispData.PDfilterCutoffs = PDfiltCutoffs
collectBG = appObj.disp_collectBG_pushButton.isChecked()
pd_background = dispData.phDiode_background
if processMode == OCTCommon.ProcessMode.FPGA:
if appObj.oct_hw.IsOCTTestingMode():
pd_data = OCTCommon.loadRawData(testDataDir, frameNum % 19, dataType=1)
numklinpts = 1400
else:
err, pd_data = appObj.oct_hw.AcquireOCTDataInterpPD(numTrigs)
DebugLog.log("runDispersion(): AcquireOCTDataInterpPD() err = %d" % err)
# process the data
dispData = processData(pd_data, dispData, numklinpts, PDfiltCutoffs, magWin_LPfilterCutoff, pd_background, collectBG)
elif processMode == OCTCommon.ProcessMode.SOFTWARE:
if appObj.oct_hw.IsOCTTestingMode():
ch0_data,ch1_data=JSOraw.getSavedRawData(numTrigs,appObj.dispData.requestedSamplesPerTrig,appObj.savedDataBuffer)
else:
# def AcquireOCTDataRaw(self, numTriggers, samplesPerTrig=-1, Ch0Shift=-1, startTrigOffset=0):
samplesPerTrig = fpgaOpts.SamplesPerTrig*2 + fpgaOpts.Ch0Shift*2
err, ch0_data,ch1_data = appObj.oct_hw.AcquireOCTDataRaw(numTrigs, samplesPerTrig)
pdData,mziData,actualSamplesPerTrig = JSOraw.channelShift(ch0_data,ch1_data,dispData) # shift the two channels to account for delays in the sample data compared to the MZI data
mzi_hilbert, mzi_mag, mzi_ph, k0 = JSOraw.processMZI(mziData, dispData) # calculate k0 from the phase of the MZI data
k0Cleaned = JSOraw.cleank0(k0, dispData) # Adjust the k0 curves so that the unwrapping all starts at the same phase
pd_data, klin = JSOraw.processPD(pdData, k0Cleaned, dispData, klin) # Interpolate the PD data based upon the MZI data
dispData.Klin = klin
dispData = processUniqueDispersion(pd_data, dispData, pd_background, collectBG)
else:
QtGui.QMessageBox.critical (appObj, "Error", "Unsuppoted processing mode for current hardware")
# plot the data
plotDispData(appObj, dispData, PDfiltCutoffs)
if appObj.getSaveState():
dispFilePath = saveDispersionData(dispData, appObj.settingsPath)
saveOpts = appObj.getSaveOpts()
if saveOpts.saveRaw:
if not saveDirInit:
saveDir = OCTCommon.initSaveDir(saveOpts, 'Dispersion')
saveDirInit = True
OCTCommon.saveRawData(pd_data, saveDir, frameNum, dataType=1)
if processMode == OCTCommon.ProcessMode.FPGA:
appObj.dispDataFPGA = dispData
dispFilePathFPGA = dispFilePath
savedFPGADisp = True
else:
appObj.dispData = dispData
frameNum += 1
QtGui.QApplication.processEvents() # check for GUI events, particularly the "done" flag
if savedFPGADisp:
DebugLog.log("runDispersion(): loading dispersion file into FPGA")
appObj.loadDispersionIntoFPGA(dispFilePathFPGA, appObj.oct_hw.fpgaOpts)
except Exception as ex:
# raise ex
traceback.print_exc(file=sys.stdout)
QtGui.QMessageBox.critical (appObj, "Error", "Error during scan. Check command line output for details")
finally:
appObj.isCollecting = False
QtGui.QApplication.processEvents() # check for GUI events
appObj.finishCollection()
