def import_data_fn(self):
deltat= 1000/float(self.text_1)
#pickle.dump(tif.asarray(), open('extra.p',"wb"))
ab = self.tif.asarray().astype(np.float64)
print('shape',ab.shape)
scanObject(filename,par_obj,[deltat,float(self.text_2)/1000000],ab,0,0);
win_obj.bleachCorr1 = False
win_obj.bleachCorr2 = False
win_obj.label.generateList()
self.win_obj.image_status_text.showMessage("Correlating carpet: File " +str(self.win_obj.file_import.file_index+1)+' of '+str(self.win_obj.file_import.file_list.__len__()))
self.win_obj.app.processEvents()
if win_obj.last_in_list == False:
print ('moving to next file')
win_obj.file_import.load_next_file()
else:
print( 'finished with all files')
win_obj.file_import.post_initial_import()
def import_data_fn(self):
deltat= 1000/float(self.text_1)
data_array = tif_fn.imread(str(filename),key=0)
scanObject(filename,par_obj,[deltat,float(self.text_2)/1000000],data_array,0,0);
win_obj.bleachCorr1 = False
win_obj.bleachCorr2 = False
win_obj.DeltatEdit.setText(str(deltat));
win_obj.label.generateList()
self.win_obj.image_status_text.showMessage("Correlating carpet: File " +str(self.win_obj.file_import.file_index+1)+' of '+str(self.win_obj.file_import.file_list.__len__()))
self.win_obj.app.processEvents()
if win_obj.last_in_list == False:
print( 'moving to next file')
win_obj.file_import.load_next_file()
else:
print ('finished with all files')
win_obj.file_import.post_initial_import()
def import_data_fn(self):
"""Populates the scannning FCS software with the data."""
self.imDataDesc[7] = self.stack_ind['name']
self.imDataDesc[6] = float(self.text_2) / 1000000
self.imDataDesc[3] = self.stack_ind['size']
self.imDataDesc[4] = [1.0 / float(self.text_1)]
self.imDataDesc[2] = ['Red']
scanObject(self.stack_ind['title'], self.par_obj, self.imDataDesc,
self.stack_ind['image'].astype(np.float64), 0, 0)
self.win_obj.bleachCorr1 = False
self.win_obj.bleachCorr2 = False
self.win_obj.label.generateList()
self.par_obj.objectRef[-1].cb.setChecked(True)
self.par_obj.objectRef[-1].plotOn = True
self.win_obj.image_status_text.showMessage(
"Correlating carpet: " + str(self.ind) + " of " +
str(self.selList.__len__()) + ". File " +
str(self.win_obj.file_import.file_index + 1) + ' of ' +
str(self.win_obj.file_import.file_list.__len__()))
if self.ind < self.selList.__len__():
self.ind = self.ind + 1
if self.ind == self.selList.__len__():
self.win_obj.last_in_file = True
self.next_index(self.ind - 1)
else:
self.win_obj.app.processEvents()
#Is it the last file in the list
if self.win_obj.last_in_list == False:
print('moving to next file')
self.win_obj.file_import.load_next_file()
else:
print('finished with all files')
self.win_obj.file_import.post_initial_import()
def import_lif_sing(self, selList):
"""Loads the individual lif raw data in to the scanning software"""
self.imDataStore = []
self.imDataDesc = []
count_loaded = 0
#Memory reading happens once.
while True:
#Unpacks header for pixel encoding memory.
try:
struct.unpack('i', self.f.read(4))[0]
except:
break
struct.unpack('i', self.f.read(4))[0]
self.f.read(1)
if platform.system() == 'Darwin':
memSize = struct.unpack('l', self.f.read(8))[0]
elif platform.system() == 'Windows':
memSize = struct.unpack('l', self.f.read(4))[0]
memSize2 = struct.unpack('l', self.f.read(4))[0]
else:
memSize = struct.unpack('l', self.f.read(8))[0]
self.f.read(1)
c = struct.unpack('i', self.f.read(4))[0]
memDesc = bytearray()
for i in range(0, c * 2):
memDesc.extend(bytes(self.f.read(1)))
#print struct.unpack('i', f.read(4))[0]
#Read a memory block of the correct size.
#imBinData = self.f.read(memSize)
memDesc = memDesc.translate(None, b'\x00').decode("utf-8")
#loadImBool = (memDesc in memId )
loadImBool = False
#Catch data if it happens to be in array
for b in selList:
#print memDesc+' '+temp[0]
if self.meta_array[b]['memid'] == memDesc:
loadImBool = True
bytesInc = self.meta_array[b]['bytesinc']
count_loaded += 1
self.win_obj.image_status_text.showMessage(
"Processing carpet: " + str(count_loaded) + " of " +
str(selList.__len__()) + ". From file: " +
str(self.win_obj.file_import.file_num + 1) + " of " +
str(self.win_obj.file_import.file_list.__len__()) +
".")
self.win_obj.app.processEvents()
break
#If memDesc and temp are in list.
if memSize > 0 and loadImBool == True:
#This is where the actual data is read in.
imBinData = self.f.read(memSize)
if bytesInc == 1:
imData = [0] * imBinData.__len__()
for iv in range(0, imBinData.__len__(), 1):
byteData = struct.unpack('B', imBinData[iv:iv + 1])[0]
imData[iv] = byteData
if bytesInc == 2:
imData = [0] * int(imBinData.__len__() / 2)
cc = 0
for iv in range(0, imBinData.__len__(), 2):
byteData = struct.unpack('H', imBinData[iv:iv + 2])[0]
imData[cc] = byteData
cc = cc + 1
self.imDataStore.append(imData)
self.imDataDesc.append(self.meta_array[b])
else:
if count_loaded == selList.__len__():
break
footer = self.f.tell()
self.f.seek(footer + memSize)
s = []
self.f.close()
self.win_obj.update_correlation_parameters()
self.parObj.total_sub_files = self.imDataDesc.__len__()
for i in range(self.imDataDesc.__len__()):
self.parObj.file_sub = i
self.win_obj.image_status_text.showMessage(
"Correlating carpet: " + str(i + 1) + " of " +
str(self.imDataDesc.__len__()) + ". From file: " +
str(self.win_obj.file_import.file_num + 1) + " of " +
str(self.win_obj.file_import.file_list.__len__()) + ".")
self.win_obj.fit_obj.app.processEvents()
s.append(
scanObject(self.fname, self.parObj, self.imDataDesc[i],
self.imDataStore[i], 0, 0))
self.win_obj.bleachCorr1 = False
self.win_obj.bleachCorr2 = False
self.win_obj.label.generateList()
self.win_obj.image_status_text.showMessage("Data plotted.")