1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
|
#!/usr/bin/env python
# -*- python -*-
# Author: Pearu Peterson
# Created: May 2010
# flake8: noqa
import os
description_template = '''
DimensionX: %(DimensionX)s
DimensionY: %(DimensionY)s
DimensionZ: %(DimensionZ)s
VoxelSizeX: %(VoxelSizeX)s
VoxelSizeY: %(VoxelSizeY)s
VoxelSizeZ: %(VoxelSizeZ)s
NofStacks: 1
RotationAngle: %(RotationAngle)s
PixelTime: %(PixelTime)s
ENTRY_OBJECTIVE: %(Objective)s
Objective: %(Objective)s
ExcitationWavelength: %(ExcitationWavelength)s
MicroscopeType: %(MicroscopeType)s
ChannelName: %(ChannelName)s
OriginalFile: %(OriginalFile)s
'''
def runner(parser, options, args):
if not hasattr(parser, 'runner'):
options.output_path = None
assert not args, repr(args)
if options.input_path is None:
parser.error('Expected --input-path but got nothing')
input_path = options.input_path
output_path = options.output_path
if output_path is None:
b, e = os.path.splitext(input_path)
b = os.path.basename(b)
output_path = b + '_%(channel_name)s_%(slice)s.tif'
from libtiff.tiff import TIFFfile, TIFFimage
tiff = TIFFfile(input_path)
samples, sample_names = tiff.get_samples()
description = []
for ifd in tiff.IFD:
s = ifd.get('ImageDescription')
if s is not None:
description.append(s.value.tobytes())
init_description = '\n'.join(description)
samples_list, names_list = tiff.get_samples()
while samples_list:
samples = samples_list.pop()
if options.slice is not None:
exec('samples = samples[%s]' % (options.slice))
name = names_list.pop()
if tiff.is_lsm:
voxel_sizes = [tiff.lsmentry[
'VoxelSize' + x][0] for x in 'XYZ'] # m
# us, integration is >=70% of # the pixel time
pixel_time = tiff.lsminfo.get(
'track pixel time')[0]
rotation = tiff.lsminfo.get('recording rotation')[0] # deg
objective = tiff.lsminfo.get(
'recording objective')[0] # objective description
excitation_wavelength = tiff.lsminfo.get(
'illumination channel wavelength')[0] # nm
description = description_template % (dict(
DimensionX=samples.shape[2],
DimensionY=samples.shape[1],
DimensionZ=samples.shape[0],
VoxelSizeX=voxel_sizes[0],
VoxelSizeY=voxel_sizes[1],
VoxelSizeZ=voxel_sizes[2],
RotationAngle=rotation,
PixelTime=pixel_time,
Objective=objective,
MicroscopeType='confocal',
OriginalFile=os.path.abspath(input_path),
ExcitationWavelength=excitation_wavelength,
ChannelName=name,
)) + init_description
description += '\n'+tiff.lsminfo.tostr(short=True)
else:
description = init_description
tif = TIFFimage(samples, description=description)
fn = output_path % dict(channel_name=name, slice=options.slice)
tif.write_file(fn, compression=getattr(options, 'compression', 'none'))
return
def main():
from optparse import OptionParser
from libtiff.script_options import set_convert_options
parser = OptionParser()
set_convert_options(parser)
if hasattr(parser, 'runner'):
parser.runner = runner
options, args = parser.parse_args()
runner(parser, options, args)
return
if __name__ == '__main__':
main()
|
