def updateMasks(self):
"""Binarization of image. """
self.gaussSigma = np.float(self.main.sigmaEdit.text()) / self.pxSize
thr = np.float(self.main.intThresEdit.text())
if self.main.testData:
self.blocksInputS = [
ndi.gaussian_filter(b, self.gaussSigma)
for b in self.blocksInput
]
self.blocksInputS = np.array(self.blocksInputS)
self.meanS = np.mean(self.blocksInputS, (1, 2))
self.stdS = np.std(self.blocksInputS, (1, 2))
thresholds = self.meanS + thr * self.stdS
thresholds = thresholds.reshape(np.prod(self.n), 1, 1)
mask = self.blocksInputS < thresholds
self.blocksMask = np.array([
bI < np.mean(bI) + thr * np.std(bI) for bI in self.blocksInputS
])
self.mask = tools.unblockshaped(mask, *self.inputData.shape)
self.inputDataS = tools.unblockshaped(self.blocksInputS,
*self.shape)
else:
self.inputDataS = ndi.gaussian_filter(self.inputData,
self.gaussSigma)
self.blocksInputS = tools.blockshaped(self.inputDataS,
*self.nblocks)
self.meanS = np.mean(self.inputDataS)
self.stdS = np.std(self.inputDataS)
self.mask = self.inputDataS < self.meanS + thr * self.stdS
self.blocksMask = tools.blockshaped(self.mask, *self.nblocks)
self.showImS = np.fliplr(np.transpose(self.inputDataS))
self.showMask = np.fliplr(np.transpose(self.mask))
self.selectedMask = self.roi.getArrayRegion(self.showMask,
self.inputImg).astype(bool)
def buildData(technique=None, pxSize=None, mag=None):
print("Test image creation script started...")
if technique is None:
te = input('STED or STORM? STED=1, STORM=2 ')
if te == '1':
technique = 'STED'
elif te == '2':
technique = 'STORM'
mag = float(input('Enter super-resolved image magnification '))
else:
print('Invalid answer')
pxSize = float(input('Enter px size in nm '))
subimgPxSize = int(np.round(1000/pxSize))
folder = os.getcwd()
nRings = 0
nNoRings = 0
try:
fig, ax = plt.subplots()
fig.set_size_inches(12, 16, forward=True)
loadOutput = loadData(os.getcwd(), ax, subimgPxSize, technique, mag)
folder, blocks, dataShape, fileShape, n = loadOutput
plt.show(block=False)
# this array will be the output
testData = np.zeros(blocks.shape, dtype=blocks.dtype)
maxRings = int(0.5*len(blocks))
maxNoRings = maxRings
listRings, listNoRings = selectBlocks(maxRings, maxRings)
lR = len(listRings)
testData[nRings:nRings + lR] = blocks[listRings]
nRings += lR
lNR = len(listNoRings)
nRBlocks = blocks[listNoRings]
testData[maxRings + nNoRings:maxRings + nNoRings + lNR] = nRBlocks
nNoRings += lNR
plt.close()
ans = ''
while ans not in ['y', 'n']:
ans = input('Keep working? [y/n] ')
keepWorking = ans == 'y'
except OSError:
keepWorking = False
while keepWorking:
try:
fig, ax = plt.subplots()
fig.set_size_inches(12, 18, forward=True)
folder, blocks, dd, ee, ff = loadData(folder, ax, subimgPxSize,
technique, mag)
plt.show(block=False)
needRings = maxRings - nRings
needNoRings = maxNoRings - nNoRings
listRings, listNoRings = selectBlocks(needRings, needNoRings)
listRings = listRings[:needRings]
listNoRings = listNoRings[:needNoRings]
lR = len(listRings)
testData[nRings:nRings + lR] = blocks[listRings]
nRings += lR
lNR = len(listNoRings)
nRBlocks = blocks[listNoRings]
testData[maxRings + nNoRings:maxRings + nNoRings + lNR] = nRBlocks
nNoRings += lNR
plt.close()
ans = ''
while ans not in ['y', 'n']:
ans = input('Keep working? [y/n] ')
keepWorking = ans == 'y'
except OSError:
print('No file selected!')
testData = tools.unblockshaped(testData, *dataShape)
if technique == 'STORM':
crop = int(3*mag)
newTestData = np.zeros(fileShape, testData.dtype)
newTestData[crop:crop + n[0]*subimgPxSize,
crop:crop + n[1]*subimgPxSize] = testData
plotWithGrid(testData, ax, subimgPxSize)
plt.show()
tiff.imsave('testdata.tif', newTestData)
else:
plotWithGrid(testData, ax, subimgPxSize)
plt.show()
tiff.imsave('testdata.tif', testData)