def openTiff(self, filename):
Tiff = tifffile.TiffFile(str(filename))
A = Tiff.asarray()
Tiff.close()
axes = [tifffile.AXES_LABELS[ax] for ax in Tiff.series[0].axes]
if set(axes) == set(['series', 'height',
'width']): # single channel, multi-volume
target_axes = ['series', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
return A
def loadTiff_Display(self):
t = time()
g.m.statusBar().showMessage("Loading movie...")
if self.axes == 'IYX':
#single channel (stk?)
startPage = 0
endPage = self.nPages
stepSize = 1
volume = 0
series = list(range(startPage+volume, endPage+volume, stepSize))
#for stk? file (axes == 'IYX')
Page_series = tifffile.imread(self.fileName,key=series)
print(Page_series.shape)
self.displayWindow_0 = Window(Page_series, 'Loaded from pages - channel 0')
elif self.axes == 'TZCYX':
#multi-sweep (micromanager)
volNum = shape[1]
#2-channel - get channels serperately
#for micromanager file (axes == 'TZCYX')
with tifffile.TiffFile(self.fileName) as tif:
initiated_0 = False
initiated_1 = False
for page in tif.pages:
#print('ChannelIndex',page.tags.micromanager_metadata.value.ChannelIndex)
#print('ImageNumber',page.tags.micromanager_metadata.value.ImageNumber)
g.m.statusBar().showMessage("Loading movie...(Image #:{})".format(page.tags.micromanager_metadata.value.ImageNumber))
if page.tags.micromanager_metadata.value.ChannelIndex == 0 and int(page.tags.micromanager_metadata.value.ImageNumber)%volNum == 0:
image_0 = page.asarray()
if initiated_0 == False:
stack_0 = image_0
initiated_0 = True
else:
stack_0 = np.dstack((stack_0, image_0))
if page.tags.micromanager_metadata.value.ChannelIndex == 1 and int(page.tags.micromanager_metadata.value.ImageNumber)%volNum == 0:
image_1 = page.asarray()
if initiated_1 == False:
stack_1 = image_1
initiated_1 = True
else:
stack_1 = np.dstack((stack_1, image_1))
print(stack_0.shape)
print(stack_1.shape)
stackAxes = ['y','x','t']
target_axes = ['t', 'y', 'x']
perm = get_permutation_tuple(stackAxes, target_axes)
stack_0 = np.transpose(stack_0, perm)
stack_1 = np.transpose(stack_1, perm)
stack_0.shape
stack_1.shape
self.displayWindow_0 = Window(stack_0,'Loaded Page series - channel 0')
self.displayWindow_1 = Window(stack_1,'Loaded Page series - channel 1')
elif self.axes == 'ZCYX':
#single-sweep (micromanager)
#2-channel
with tifffile.TiffFile(self.fileName) as tif:
axes = [tifffile.AXES_LABELS[ax] for ax in tif.series[0].axes]
print(axes)
initiated_0 = False
initiated_1 = False
for page in tif.pages:
##print('ChannelIndex',page.tags.micromanager_metadata.value.ChannelIndex)
##print('ImageNumber',page.tags.micromanager_metadata.value.ImageNumber)
g.m.statusBar().showMessage("Loading movie...(Image #:{})".format(page.tags.micromanager_metadata.value.ImageNumber))
if page.tags.micromanager_metadata.value.ChannelIndex == 0:
image_0 = page.asarray()
if initiated_0 == False:
stack_0 = image_0
initiated_0 = True
else:
stack_0 = np.dstack((stack_0, image_0))
if page.tags.micromanager_metadata.value.ChannelIndex == 1:
image_1 = page.asarray()
if initiated_1 == False:
stack_1 = image_1
initiated_1 = True
else:
stack_1 = np.dstack((stack_1, image_1))
tif.close()
print(stack_0.shape)
print(stack_1.shape)
stackAxes = ['y','x','t']
target_axes = ['t', 'y', 'x']
perm = get_permutation_tuple(stackAxes, target_axes)
stack_0 = np.transpose(stack_0, perm)
stack_1 = np.transpose(stack_1, perm)
stack_0.shape
stack_1.shape
self.displayWindow_0 = Window(stack_0,'Loaded from pages - channel 0')
self.displayWindow_1 = Window(stack_1,'Loaded from pages - channel 1')
elif self.axes == 'TZYX':
#single-sweep (micromanager)
#2-channel
with tifffile.TiffFile(self.fileName) as tif:
axes = [tifffile.AXES_LABELS[ax] for ax in tif.series[0].axes]
print(axes)
initiated_0 = False
initiated_1 = False
print('ok')
for page in tif.pages:
##print('ChannelIndex',page.tags.micromanager_metadata.value.ChannelIndex)
print('ImageNumber',page.tags.micromanager_metadata.value.ImageNumber)
g.m.statusBar().showMessage("Loading movie...(Image #:{})".format(page.tags.micromanager_metadata.value.ImageNumber))
if page.tags.micromanager_metadata.value.ChannelIndex == 0:
image_0 = page.asarray()
if initiated_0 == False:
stack_0 = image_0
initiated_0 = True
else:
stack_0 = np.dstack((stack_0, image_0))
if page.tags.micromanager_metadata.value.ChannelIndex == 1:
image_1 = page.asarray()
if initiated_1 == False:
stack_1 = image_1
initiated_1 = True
else:
stack_1 = np.dstack((stack_1, image_1))
tif.close()
print(stack_0.shape)
print(stack_1.shape)
stackAxes = ['y','x','t']
target_axes = ['t', 'y', 'x']
perm = get_permutation_tuple(stackAxes, target_axes)
stack_0 = np.transpose(stack_0, perm)
stack_1 = np.transpose(stack_1, perm)
stack_0.shape
stack_1.shape
self.displayWindow_0 = Window(stack_0,'Loaded from pages - channel 0')
self.displayWindow_1 = Window(stack_1,'Loaded from pages - channel 1')
else:
g.m.statusBar().showMessage("No Movie Generated")
return
g.m.statusBar().showMessage("Successfully generated movie ({} s)".format(round(time() - t)))
return
def openTiff(filename):
Tiff = tifffile.TiffFile(str(filename))
A = Tiff.asarray()
B = []
C = []
Tiff.close()
axes = [tifffile.AXES_LABELS[ax] for ax in Tiff.series[0].axes]
print(axes)
if set(axes) == set(['time', 'depth', 'height',
'width']): # single channel, multi-volume
target_axes = ['time', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nScans, nFrames, x, y = A.shape
A = A.reshape(nScans * nFrames, x, y)
#newWindow = Window(A,'Loaded Tiff')
elif set(axes) == set(['series', 'height',
'width']): # single channel, single-volume
target_axes = ['series', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
A = A.reshape(nFrames, x, y)
#newWindow = Window(A,'Loaded Tiff')
elif set(axes) == set(['time', 'height',
'width']): # single channel, single-volume
target_axes = ['time', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
A = A.reshape(nFrames, x, y)
#newWindow = Window(A,'Loaded Tiff')
elif set(axes) == set(['time', 'depth', 'channel', 'height',
'width']): # multi-channel, multi-volume
target_axes = ['channel', 'time', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
n1Scans, n1Frames, x1, y1 = B.shape
n2Scans, n2Frames, x2, y2 = C.shape
B = B.reshape(n1Scans * n1Frames, x1, y1)
C = C.reshape(n2Scans * n2Frames, x2, y2)
#channel_1 = Window(B,'Channel 1')
#channel_2 = Window(C,'Channel 2')
elif set(axes) == set(['depth', 'channel', 'height',
'width']): # multi-channel, single volume
target_axes = ['channel', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
#channel_1 = Window(B,'Channel 1')
#channel_2 = Window(C,'Channel 2')
elif set(axes) == set(['time', 'channel', 'height',
'width']): # multi-channel, single volume
target_axes = ['channel', 'time', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
#channel_1 = Window(B,'Channel 1')
#channel_2 = Window(C,'Channel 2')
return A, B, C
def openTiff(self, filename):
Tiff = tifffile.TiffFile(str(filename))
A = Tiff.asarray()
Tiff.close()
axes = [tifffile.AXES_LABELS[ax] for ax in Tiff.series[0].axes]
print(axes)
if set(axes) == set(['time', 'depth', 'height', 'width']): # single channel, multi-volume
target_axes = ['time', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nScans, nFrames, x, y = A.shape
#interleaved = np.zeros((nScans*nFrames,x,y))
#
#z = 0
#for i in np.arange(nFrames):
# for j in np.arange(nScans):
# interleaved[z] = A[j%nScans][i]
# z = z +1
#newWindow = Window(interleaved,'Loaded Tiff')
A = A.reshape(nScans*nFrames,x,y)
newWindow = Window(A,'Loaded Tiff')
elif set(axes) == set(['series', 'height', 'width']): # single channel, single-volume
target_axes = ['series', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
A = A.reshape(nFrames,x,y)
newWindow = Window(A,'Loaded Tiff')
elif set(axes) == set(['depth', 'height', 'width']): # single channel, single-volume
target_axes = ['depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
A = A.reshape(nFrames,x,y)
newWindow = Window(A,'Loaded Tiff')
elif set(axes) == set(['time', 'height', 'width']): # single channel, single-volume
target_axes = ['time', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
A = A.reshape(nFrames,x,y)
newWindow = Window(A,'Loaded Tiff')
elif set(axes) == set(['time', 'depth', 'channel', 'height', 'width']): # multi-channel, multi-volume
target_axes = ['channel','time','depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
n1Scans, n1Frames, x1, y1 = B.shape
n2Scans, n2Frames, x2, y2 = C.shape
B = B.reshape(n1Scans*n1Frames,x1,y1)
C = C.reshape(n2Scans*n2Frames,x2,y2)
channel_1 = Window(B,'Channel 1')
channel_2 = Window(C,'Channel 2')
#clear A array to reduce memory use
A = np.zeros((2,2))
elif set(axes) == set(['depth', 'channel', 'height', 'width']): # multi-channel, single volume
target_axes = ['channel','depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
channel_1 = Window(B,'Channel 1')
channel_2 = Window(C,'Channel 2')
#clear A array to reduce memory use
A = np.zeros((2,2))
elif set(axes) == set(['time', 'channel', 'height', 'width']): # multi-channel, single volume
target_axes = ['channel','time', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
channel_1 = Window(B,'Channel 1')
channel_2 = Window(C,'Channel 2')
#clear A array to reduce memory use
A = np.zeros((2,2))
def openTiff(self, filename):
Tiff = tifffile.TiffFile(str(filename))
A = Tiff.asarray()
Tiff.close()
axes = [tifffile.AXES_LABELS[ax] for ax in Tiff.series[0].axes]
if set(axes) == set(['time', 'depth', 'height',
'width']): # single channel, multi-volume
target_axes = ['time', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nScans, nFrames, x, y = A.shape
A = A.reshape(nScans * nFrames, x, y)
#newWindow = Window(A,'Loaded Tiff')
return A, None
elif set(axes) == set(['series', 'height',
'width']): # single channel, single-volume
target_axes = ['series', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
A = A.reshape(nFrames, x, y)
#newWindow = Window(A,'Loaded Tiff')
return A, None
elif set(axes) == set(['time', 'height',
'width']): # single channel, single-volume
target_axes = ['time', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
A = A.reshape(nFrames, x, y)
#newWindow = Window(A,'Loaded Tiff')
return A, None
elif set(axes) == set(['time', 'depth', 'channel', 'height',
'width']): # multi-channel, multi-volume
target_axes = ['channel', 'time', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
n1Scans, n1Frames, x1, y1 = B.shape
n2Scans, n2Frames, x2, y2 = C.shape
B = B.reshape(n1Scans * n1Frames, x1, y1)
C = C.reshape(n2Scans * n2Frames, x2, y2)
#channel_1 = Window(B,'Channel 1')
#channel_2 = Window(C,'Channel 2')
#clear A array to reduce memory use
A = np.zeros((2, 2))
return B, C
elif set(axes) == set(['depth', 'channel', 'height',
'width']): # multi-channel, single volume
target_axes = ['channel', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
#channel_1 = Window(B,'Channel 1')
#channel_2 = Window(C,'Channel 2')
#clear A array to reduce memory use
A = np.zeros((2, 2))
return B, C
elif set(axes) == set(['time', 'channel', 'height',
'width']): # multi-channel, single volume
target_axes = ['channel', 'time', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
nChannels, nFrames, x, y = A.shape
n1Frames, x1, y1 = B.shape
n2Frames, x2, y2 = C.shape
#uncomment to display original
#self.channel_1 = Window(B,'Channel 1')
#self.channel_2 = Window(B,'Channel 2')
#clear A array to reduce memory use
A = np.zeros((2, 2))
return B, C
from flika.utils.io import tifffile from flika.process.file_ import get_permutation_tuple filename = r"C:\Users\George\Dropbox\UCI\multiColor\2bin_200slices_0.11slicestep_2sweep_MMStack_Pos0.ome.tif" Tiff = tifffile.TiffFile(str(filename)) A = Tiff.asarray() Tiff.close() axes = [tifffile.AXES_LABELS[ax] for ax in Tiff.series[0].axes] target_axes = ['channel','time','depth', 'width', 'height'] perm = get_permutation_tuple(axes, target_axes) A = np.transpose(A, perm) B = A[0] C = A[1] n1Scans, n1Frames, x1, y1 = B.shape n2Scans, n2Frames, x2, y2 = C.shape B = B.reshape(n1Scans*n1Frames,x1,y1) C = C.reshape(n2Scans*n2Frames,x2,y2) channel_1 = Window(B,'Channel 1') channel_2 = Window(C,'Channel 2')
def openTiff(self, filename):
ext = os.path.splitext(filename)[-1]
if ext in ['.tif', '.tiff', 'stk']:
Tiff = tifffile.TiffFile(str(filename))
A = Tiff.asarray()
Tiff.close()
axes = [tifffile.AXES_LABELS[ax] for ax in Tiff.series[0].axes]
elif ext == '.czi':
#import czifile
czi = CziFile(filename)
A = czi.asarray()
czi.close()
axes = [ax for ax in czi.axes]
##remove axes length ==1
#get shape
shape = A.shape
#squeeze array to remove length ==1
A = A.squeeze()
#remove axis length 1 labels
toRemove = []
for n, i in enumerate(shape):
if i == 1:
toRemove.append(n)
delete_multiple_element(axes, toRemove)
#convert labels to tiff format
for n, i in enumerate(axes):
if i == 'T':
axes[n] = 'time'
elif i == 'C':
axes[n] = 'channel'
elif i == 'Y':
axes[n] = 'height'
elif i == 'X':
axes[n] = 'width'
elif i == 'Z':
axes[n] = 'depth'
else:
msg = "Could not open. Filetype for '{}' not recognized".format(
filename)
g.alert(msg)
if filename in g.settings['recent_files']:
g.settings['recent_files'].remove(filename)
# make_recent_menu()
return
print(axes)
if set(axes) == set(['time', 'depth', 'height',
'width']): # single channel, multi-volume
target_axes = ['time', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nScans, nFrames, x, y = A.shape
#interleaved = np.zeros((nScans*nFrames,x,y))
#
#z = 0
#for i in np.arange(nFrames):
# for j in np.arange(nScans):
# interleaved[z] = A[j%nScans][i]
# z = z +1
#newWindow = Window(interleaved,'Loaded Tiff')
A = A.reshape(nScans * nFrames, x, y)
newWindow = Window(A, 'Loaded Tiff')
elif set(axes) == set(['series', 'height',
'width']): # single channel, single-volume
target_axes = ['series', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
A = A.reshape(nFrames, x, y)
newWindow = Window(A, 'Loaded Tiff')
elif set(axes) == set(['time', 'height',
'width']): # single channel, single-volume
target_axes = ['time', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
A = A.reshape(nFrames, x, y)
newWindow = Window(A, 'Loaded Tiff')
elif set(axes) == set(['time', 'depth', 'channel', 'height',
'width']): # multi-channel, multi-volume
target_axes = ['channel', 'time', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
n1Scans, n1Frames, x1, y1 = B.shape
n2Scans, n2Frames, x2, y2 = C.shape
B = B.reshape(n1Scans * n1Frames, x1, y1)
C = C.reshape(n2Scans * n2Frames, x2, y2)
channel_1 = Window(B, 'Channel 1')
channel_2 = Window(C, 'Channel 2')
#clear A array to reduce memory use
A = np.zeros((2, 2))
elif set(axes) == set(['depth', 'channel', 'height',
'width']): # multi-channel, single volume
target_axes = ['channel', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
channel_1 = Window(B, 'Channel 1')
channel_2 = Window(C, 'Channel 2')
#clear A array to reduce memory use
A = np.zeros((2, 2))
elif set(axes) == set(['time', 'channel', 'height',
'width']): # multi-channel, single volume
target_axes = ['channel', 'time', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
channel_1 = Window(B, 'Channel 1')
channel_2 = Window(C, 'Channel 2')
#clear A array to reduce memory use
A = np.zeros((2, 2))
def openTiff(self, filename):
Tiff = tifffile.TiffFile(str(filename))
A = Tiff.asarray()
Tiff.close()
axes = [tifffile.AXES_LABELS[ax] for ax in Tiff.series[0].axes]
print(axes)
if set(axes) == set(['time', 'depth', 'height',
'width']): # single channel, multi-volume
target_axes = ['time', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nScans, nFrames, x, y = A.shape
self.channel1_array = A.reshape(nScans * nFrames, x, y)
#newWindow = Window(self.channel1_array,'Loaded Tiff')
nFrames, x, y = self.channel1_array.shape
self.nChannels = 1
self.nVolumes = nScans
self.nFrames = nFrames
self.sclicesPerVolume = int(self.nFrames / self.nVolumes)
#clear A array to reduce memory use
A = np.zeros((2, 2))
return
elif set(axes) == set(['series', 'height',
'width']): # single channel, single-volume
target_axes = ['series', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
self.channel1_array = A.reshape(nFrames, x, y)
#uncomment to display original
#newWindow = Window(self.channel1_array,'Loaded Tiff')
self.nChannels = 1
self.nVolumes = 1
self.nFrames = nFrames
self.sclicesPerVolume = int(self.nFrames / self.nVolumes)
#clear A array to reduce memory use
A = np.zeros((2, 2))
return
elif set(axes) == set(['time', 'height',
'width']): # single channel, single-volume
target_axes = ['time', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
self.channel1_array = A.reshape(nFrames, x, y)
#uncomment to display original
#newWindow = Window(self.channel1_array,'Loaded Tiff')
self.nChannels = 1
self.nVolumes = 1
self.nFrames = nFrames
self.sclicesPerVolume = int(self.nFrames / self.nVolumes)
#clear A array to reduce memory use
A = np.zeros((2, 2))
return
elif set(axes) == set(['time', 'depth', 'channel', 'height',
'width']): # multi-channel, multi-volume
target_axes = ['channel', 'time', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
self.channel1_array = A[0]
self.channel2_array = A[1]
nChannels, nScans, nFrames, x, y = A.shape
n1Scans, n1Frames, x1, y1 = self.channel1_array.shape
n2Scans, n2Frames, x2, y2 = self.channel2_array.shape
self.channel1_array = self.channel1_array.reshape(
n1Scans * n1Frames, x1, y1)
self.channel2_array = self.channel2_array.reshape(
n2Scans * n2Frames, x2, y2)
n1Frames, x1, y1 = self.channel1_array.shape
n2Frames, x2, y2 = self.channel2_array.shape
#uncomment to display original
#self.channel_1 = Window(self.channel1_array,'Channel 1')
#self.channel_2 = Window(self.channel2_array,'Channel 2')
#original shape before splitting channel
self.nChannels = nChannels
self.nVolumes = nScans
self.nFrames = n1Frames
self.sclicesPerVolume = int(self.nFrames / self.nVolumes)
#clear A array to reduce memory use
A = np.zeros((2, 2))
return
elif set(axes) == set(['depth', 'channel', 'height',
'width']): # multi-channel, single volume
target_axes = ['channel', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
self.channel1_array = A[0]
self.channel2_array = A[1]
nChannels, nFrames, x, y = A.shape
n1Frames, x1, y1 = self.channel1_array.shape
n2Frames, x2, y2 = self.channel2_array.shape
#uncomment to display original
#self.channel_1 = Window(self.channel1_array,'Channel 1')
#self.channel_2 = Window(self.channel2_array,'Channel 2')
#original shape before splitting channel
self.nChannels = nChannels
self.nVolumes = 1
self.nFrames = n1Frames
self.sclicesPerVolume = int(self.nFrames / self.nVolumes)
#clear A array to reduce memory use
A = np.zeros((2, 2))
return
elif set(axes) == set(['time', 'channel', 'height',
'width']): # multi-channel, single volume
target_axes = ['channel', 'time', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
self.channel1_array = A[0]
self.channel2_array = A[1]
nChannels, nFrames, x, y = A.shape
n1Frames, x1, y1 = self.channel1_array.shape
n2Frames, x2, y2 = self.channel2_array.shape
#uncomment to display original
#self.channel_1 = Window(self.channel1_array,'Channel 1')
#self.channel_2 = Window(self.channel2_array,'Channel 2')
#original shape before splitting channel
self.nChannels = nChannels
self.nVolumes = 1
self.nFrames = n1Frames
self.sclicesPerVolume = int(self.nFrames / self.nVolumes)
#clear A array to reduce memory use
A = np.zeros((2, 2))
return
elif set(axes) == set(['depth', 'height',
'width']): # single channel, single-volume
target_axes = ['depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
self.channel1_array = A.reshape(nFrames, x, y)
#uncomment to display original
#newWindow = Window(self.channel1_array,'Loaded Tiff')
self.nChannels = 1
self.nVolumes = 1
self.nFrames = nFrames
self.sclicesPerVolume = int(self.nFrames / self.nVolumes)
#clear A array to reduce memory use
A = np.zeros((2, 2))
return
else:
print('tif axes header not recognized')
self.errorFlag = True
#clear A array to reduce memory use
A = np.zeros((2, 2))
return
def openTiff(self, filename):
Tiff = tifffile.TiffFile(str(filename))
A = Tiff.asarray()
Tiff.close()
axes = [tifffile.AXES_LABELS[ax] for ax in Tiff.series[0].axes]
if set(axes) == set(['time', 'depth', 'height', 'width']): # single channel, multi-volume
target_axes = ['time', 'depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nScans, nFrames, x, y = A.shape
A = A.reshape(nScans*nFrames,x,y)
newWindow = Window(A,'Loaded Tiff')
self.nChannels = 1
self.nVolumes = nScans
self.nFrames = nFrames
return
elif set(axes) == set(['series', 'height', 'width']): # single channel, single-volume
target_axes = ['series', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
A = A.reshape(nFrames,x,y)
newWindow = Window(A,'Loaded Tiff')
self.nChannels = 1
self.nVolumes = 1
self.nFrames = nFrames
return
elif set(axes) == set(['time', 'height', 'width']): # single channel, single-volume
target_axes = ['time', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
nFrames, x, y = A.shape
A = A.reshape(nFrames,x,y)
newWindow = Window(A,'Loaded Tiff')
self.nChannels = 1
self.nVolumes = 1
self.nFrames = nFrames
return
elif set(axes) == set(['time', 'depth', 'channel', 'height', 'width']): # multi-channel, multi-volume
target_axes = ['channel','time','depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
nChannels, nScans, nFrames, x, y = A.shape
n1Scans, n1Frames, x1, y1 = B.shape
n2Scans, n2Frames, x2, y2 = C.shape
B = B.reshape(n1Scans*n1Frames,x1,y1)
C = C.reshape(n2Scans*n2Frames,x2,y2)
self.channel_1 = Window(B,'Channel 1')
self.channel_2 = Window(C,'Channel 2')
#original shape before splitting channel
self.nChannels = nChannels
self.nVolumes = nScans
self.nFrames = nFrames
return
elif set(axes) == set(['depth', 'channel', 'height', 'width']): # multi-channel, single volume
target_axes = ['channel','depth', 'width', 'height']
perm = get_permutation_tuple(axes, target_axes)
A = np.transpose(A, perm)
B = A[0]
C = A[1]
nChannels, nFrames, x, y = A.shape
n1Frames, x1, y1 = B.shape
n2Frames, x2, y2 = C.shape
self.channel_1 = Window(B,'Channel 1')
self.channel_2 = Window(C,'Channel 2')
#original shape before splitting channel
self.nChannels = nChannels
self.nVolumes = 1
self.nFrames = nFrames
return