def __resize_batch_helper(item,
inputfolder,
outputfolder,
order=1,
append_resolution_to_filename=True,
**kwargs_to_ignore):
inputfile, voxel_size = item
metadata = Metadata()
metadata.set_voxel_size(voxel_size)
stack = Stack(filename=inputfolder + inputfile)
zoom = np.array(stack.metadata['Voxel size arr']) / np.array(
metadata['Voxel size arr'])
stack.resize(zoom=zoom, order=order)
stack.metadata.set_voxel_size(metadata['Voxel size arr'])
path = os.path.dirname(inputfile)
strres = str(metadata['Voxel size']).replace(' ', ' ').replace(
' ', ' ').replace('[ ', '[').replace(' ', '_')
if path == '':
if append_resolution_to_filename:
outputname = outputfolder + inputfile[:
-4] + '_voxel_size_' + strres + '.tif'
else:
outputname = outputfolder + path + 'voxel_size_' + strres + '/' + inputfile.split(
'/')[-1]
else:
outputname = outputfolder + path + '_voxel_size_' + strres + '/' + inputfile.split(
'/')[-1]
stack.save(outputname)
stack.metadata.save(outputname[:-4] + '.csv')
def __generate_stacks_batch_helper(item, outputfolder, input_voxel_size,
stack_size_microns, **kwargs_to_ignore):
filename, params = item
if not outputfolder.endswith('/'):
outputfolder += '/'
stack = Stack(input_voxel_size=input_voxel_size,
stack_size=stack_size_microns,
cell_params=params)
stack.save(outputfolder + filename[:-4] + '.tif')
stack.metadata['StackID'] = filename[:-4].split('_')[-1]
stack.metadata.save(outputfolder + filename[:-4] + '.csv')
def __convolve_batch_helper(item, inputfolder, psffolder, outputfolder,
**kwargs_to_ignore):
inputfile, psffile = item
stack = Stack(filename=inputfolder + inputfile)
psf = PSF(filename=psffolder + psffile)
stack.convolve(psf)
stack.save(outputfolder + psffile[:-4] + '/' + inputfile)
for c in ['PSF sigma xy um', 'PSF aspect ratio']:
stack.metadata[c] = psf.metadata[c]
stack.metadata.save(outputfolder + psffile[:-4] + '/' + inputfile[:-4] +
'.csv')
psf.save(outputfolder + psffile)
psf.metadata.save(outputfolder + psffile[:-4] + '.csv')
def __add_noise_batch_helper(item, inputfolder, outputfolder,
**kwargs_to_ignore):
inputfile, kind, snr = item
stack = Stack(filename=inputfolder + inputfile)
path = os.path.dirname(inputfile)
if 'isPSF' not in stack.metadata.index or str(
stack.metadata['isPSF']) == 'False':
stack.add_noise(kind=kind, snr=snr)
if path == '':
outputname = outputfolder + inputfile
else:
outputname = outputfolder + path + '_noise'
snr = np.array([snr]).flatten()
kind = np.array([kind]).flatten()
if len(snr) == 1:
snr = np.array([snr[0]] * len(kind))
for i, k in enumerate(kind):
outputname = outputname + '_' + k + '_snr=' + str(snr[i])
outputname = outputname + '/' + inputfile.split('/')[-1]
stack.save(outputname)
stack.metadata.save(outputname[:-4] + '.csv')