def runAnalysis(self):
#get params
windowSize = self.getValue('windowSize')
averageSize = self.getValue('averageSize')
#get data window
dataWindow = self.getValue('analysisWindow')
#get image array
A = dataWindow.image
#get array shape
frames, height, width = A.shape
#print(A.shape)
#plot roi in center
if dataWindow.currentROI == None:
centerROI = makeROI('rectangle',
[[10, 10], [height - 20, width - 20]],
window=dataWindow)
else:
centerROI = dataWindow.currentROI
#plot roi average trace
plot = centerROI.plot()
#get trace data
trace = centerROI.getTrace()
#define function to get moving average from trace
def moving_average(x, n=windowSize):
return np.convolve(x, np.ones((n, )) / n, mode='valid')
#get trace moving average
movingAverage = moving_average(trace, n=windowSize)
#set moving average values <= 0 to 0.0000001
movingAverage[movingAverage <= 0] = 0.0000001
#add moving average trace to plot
plot.p1.plot(movingAverage, pen=(1, 3), symbol=None)
#identify peak of trace
peakFrame = np.argmax(movingAverage)
#plot peak
plot.p1.plot(np.array([peakFrame]),
np.array([movingAverage[peakFrame]]),
pen=None,
symbol='o',
symbolSize=20)
#average frames around peak
start = int(peakFrame - averageSize / 2)
end = int(peakFrame + averageSize / 2)
#prevent indexing from reaching past ends of trace
if start < 0:
start = 0
if end > frames:
end = frames
#get peak images
averageImages = A[start:end]
#display average stack
#averageImageStack_Win = Window(averageImages, 'Peak Images')
#average peak images
averageImage = np.mean(averageImages, axis=0)
#display average
#averageImage_Win = Window(averageImage,'Averaged Peak Images')
#make stack of averaged images
scaleImage_stack = np.ones_like(A)
scaleImage_stack = scaleImage_stack * averageImage
scaleImage_stack = scaleImage_stack[int(windowSize /
2):-(int(windowSize / 2) - 1)]
#scale moving average 0 -> 1
scale = movingAverage / max(movingAverage)
#scale averaged image stack
scaleImage_stack = np.multiply(scaleImage_stack, scale[:, None, None])
#show scale images
#scaleWindow = Window(scaleImage_stack,'Scaled Average Images')
#subtract scaled average from original stack
A_subtract = np.zeros_like(A)
A_subtract[int(windowSize / 2):-(int(windowSize / 2) - 1)] = (
A[int(windowSize / 2):-(int(windowSize / 2) - 1)] -
scaleImage_stack)
#show subtracted image stack
subtractWindow = Window(A_subtract, 'Subtracted Images')
filename = r"C:\Users\g_dic\OneDrive\Desktop\trial_2_Cal520_cip3.tif"
#filename = r"C:\Users\g_dic\OneDrive\Desktop\2021_02_05_KRAP_800ms001.tif"
windowSize = 100
#averageSize = 100
#open file in window
dataWindow = open_file(filename)
#get image array
A = dataWindow.imageArray()
#get array shape
frames, height, width = A.shape
#plot roi in center
centerROI = makeROI('rectangle', [[10, 10], [height - 20, width - 20]],
window=dataWindow)
#plot roi average trace
plot = centerROI.plot()
#get trace data
trace = centerROI.getTrace()
#define function to get moving average from trace
def moving_average(x, n=windowSize):
return np.convolve(x, np.ones((n, )) / n, mode='valid')
#get trace moving average
movingAverage = moving_average(trace, n=windowSize)
def autodetectFlash(self):
rangeStart = self.getValue('flashRangeStart')
rangeEnd = self.getValue('flashRangeEnd')
windowSize = self.getValue('windowSize')
showAverage = self.getValue('showAverage')
useROI = self.getValue('useROI')
#get data window
dataWindow = self.getValue('window')
#get image array
A = dataWindow.image
#get array shape
frames, height, width = A.shape
#plot roi in center
if useROI:
if dataWindow.currentROI == None:
print('No ROI detected: generating center ROI')
centerROI = makeROI('rectangle',
[[10, 10], [height - 20, width - 20]],
window=dataWindow)
else:
centerROI = dataWindow.currentROI
else:
centerROI = makeROI('rectangle',
[[10, 10], [height - 20, width - 20]],
window=dataWindow)
#plot roi average trace
if showAverage:
plot = centerROI.plot()
#get trace data
trace = centerROI.getTrace()
#define function to get moving average from trace
def moving_average(x, n=windowSize):
return np.convolve(x, np.ones((n, )) / n, mode='valid')
#get trace moving average
movingAverage = moving_average(trace, n=windowSize)
#set moving average values <= 0 to 0.0000001
movingAverage[movingAverage <= 0] = 0.0000001
#add moving average trace to plot
if showAverage:
plot.p1.plot(movingAverage, pen=(1, 3), symbol=None)
#identify peak of trace - first frame of flash
flashStart = rangeStart + np.argmax(movingAverage[rangeStart:rangeEnd])
#identify 1st drop after peak - end of flash
flashEnd = flashStart + np.argmin(movingAverage[flashStart:rangeEnd])
#plot flash start and end
if showAverage:
plot.p1.plot(np.array([flashStart]),
np.array([movingAverage[flashStart]]),
pen=None,
symbol='o',
symbolSize=20)
plot.p1.plot(np.array([flashEnd]),
np.array([movingAverage[flashEnd]]),
pen=None,
symbol='o',
symbolSize=20)
#remove center ROI
if showAverage == False:
centerROI.delete()
return flashStart, flashEnd