-
Notifications
You must be signed in to change notification settings - Fork 51
/
itk.py
328 lines (273 loc) · 11.2 KB
/
itk.py
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
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
#
# Copyright 2021 The NiPreps Developers <nipreps@gmail.com>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# We support and encourage derived works from this project, please read
# about our expectations at
#
# https://www.nipreps.org/community/licensing/
#
"""ITK files handling."""
import os
from mimetypes import guess_type
from tempfile import TemporaryDirectory
from nipype import logging
from nipype.utils.filemanip import fname_presuffix
from nipype.interfaces.base import (
traits,
TraitedSpec,
BaseInterfaceInputSpec,
File,
InputMultiObject,
OutputMultiObject,
SimpleInterface,
)
from .fixes import _FixTraitApplyTransformsInputSpec
LOGGER = logging.getLogger("nipype.interface")
class _MCFLIRT2ITKInputSpec(BaseInterfaceInputSpec):
in_files = InputMultiObject(
File(exists=True), mandatory=True, desc="list of MAT files from MCFLIRT"
)
in_reference = File(
exists=True, mandatory=True, desc="input image for spatial reference"
)
in_source = File(exists=True, mandatory=True, desc="input image for spatial source")
num_threads = traits.Int(
1, usedefault=True, nohash=True, desc="number of parallel processes"
)
class _MCFLIRT2ITKOutputSpec(TraitedSpec):
out_file = File(desc="the output ITKTransform file")
class MCFLIRT2ITK(SimpleInterface):
"""Convert a list of MAT files from MCFLIRT into an ITK Transform file."""
input_spec = _MCFLIRT2ITKInputSpec
output_spec = _MCFLIRT2ITKOutputSpec
def _run_interface(self, runtime):
num_threads = self.inputs.num_threads
if num_threads < 1:
num_threads = None
with TemporaryDirectory(prefix="tmp-", dir=runtime.cwd) as tmp_folder:
# Inputs are ready to run in parallel
if num_threads is None or num_threads > 1:
from concurrent.futures import ThreadPoolExecutor
with ThreadPoolExecutor(max_workers=num_threads) as pool:
itk_outs = list(
pool.map(
_mat2itk,
[
(
in_mat,
self.inputs.in_reference,
self.inputs.in_source,
i,
tmp_folder,
)
for i, in_mat in enumerate(self.inputs.in_files)
],
)
)
else:
itk_outs = [
_mat2itk(
(
in_mat,
self.inputs.in_reference,
self.inputs.in_source,
i,
tmp_folder,
)
)
for i, in_mat in enumerate(self.inputs.in_files)
]
# Compose the collated ITK transform file and write
tfms = "#Insight Transform File V1.0\n" + "".join(
[el[1] for el in sorted(itk_outs)]
)
self._results["out_file"] = os.path.join(runtime.cwd, "mat2itk.txt")
with open(self._results["out_file"], "w") as f:
f.write(tfms)
return runtime
class _MultiApplyTransformsInputSpec(_FixTraitApplyTransformsInputSpec):
input_image = InputMultiObject(
File(exists=True),
mandatory=True,
desc="input time-series as a list of volumes after splitting"
" through the fourth dimension",
)
num_threads = traits.Int(
1, usedefault=True, nohash=True, desc="number of parallel processes"
)
save_cmd = traits.Bool(
True, usedefault=True, desc="write a log of command lines that were applied"
)
copy_dtype = traits.Bool(
False, usedefault=True, desc="copy dtype from inputs to outputs"
)
class _MultiApplyTransformsOutputSpec(TraitedSpec):
out_files = OutputMultiObject(File(), desc="the output ITKTransform file")
log_cmdline = File(desc="a list of command lines used to apply transforms")
class MultiApplyTransforms(SimpleInterface):
"""Apply the corresponding list of input transforms."""
input_spec = _MultiApplyTransformsInputSpec
output_spec = _MultiApplyTransformsOutputSpec
def _run_interface(self, runtime):
# Get all inputs from the ApplyTransforms object
ifargs = self.inputs.get()
# Extract number of input images and transforms
in_files = ifargs.pop("input_image")
num_files = len(in_files)
transforms = ifargs.pop("transforms")
# Get number of parallel jobs
num_threads = ifargs.pop("num_threads")
save_cmd = ifargs.pop("save_cmd")
# Remove certain keys
for key in ["environ", "ignore_exception", "terminal_output", "output_image"]:
ifargs.pop(key, None)
# Get a temp folder ready
tmp_folder = TemporaryDirectory(prefix="tmp-", dir=runtime.cwd)
xfms_list = _arrange_xfms(transforms, num_files, tmp_folder)
if len(xfms_list) != num_files:
raise ValueError(
"Number of files and entries in the transforms list do not match"
)
# Inputs are ready to run in parallel
if num_threads < 1:
num_threads = None
if num_threads == 1:
out_files = [
_applytfms((in_file, in_xfm, ifargs, i, runtime.cwd))
for i, (in_file, in_xfm) in enumerate(zip(in_files, xfms_list))
]
else:
from concurrent.futures import ThreadPoolExecutor
with ThreadPoolExecutor(max_workers=num_threads) as pool:
out_files = list(
pool.map(
_applytfms,
[
(in_file, in_xfm, ifargs, i, runtime.cwd)
for i, (in_file, in_xfm) in enumerate(
zip(in_files, xfms_list)
)
],
)
)
tmp_folder.cleanup()
# Collect output file names, after sorting by index
self._results["out_files"] = [el[0] for el in out_files]
if save_cmd:
self._results["log_cmdline"] = os.path.join(runtime.cwd, "command.txt")
with open(self._results["log_cmdline"], "w") as cmdfile:
print("\n-------\n".join([el[1] for el in out_files]), file=cmdfile)
return runtime
def _mat2itk(args):
from nipype.interfaces.c3 import C3dAffineTool
from nipype.utils.filemanip import fname_presuffix
in_file, in_ref, in_src, index, newpath = args
# Generate a temporal file name
out_file = fname_presuffix(in_file, suffix="_itk-%05d.txt" % index, newpath=newpath)
# Run c3d_affine_tool
C3dAffineTool(
transform_file=in_file,
reference_file=in_ref,
source_file=in_src,
fsl2ras=True,
itk_transform=out_file,
resource_monitor=False,
).run()
transform = "#Transform %d\n" % index
with open(out_file) as itkfh:
transform += "".join(itkfh.readlines()[2:])
return (index, transform)
def _applytfms(args):
"""
Applies ANTs' antsApplyTransforms to the input image.
All inputs are zipped in one tuple to make it digestible by
multiprocessing's map
"""
import nibabel as nb
from nipype.utils.filemanip import fname_presuffix
from niworkflows.interfaces.fixes import FixHeaderApplyTransforms as ApplyTransforms
in_file, in_xform, ifargs, index, newpath = args
out_file = fname_presuffix(
in_file, suffix="_xform-%05d" % index, newpath=newpath, use_ext=True
)
copy_dtype = ifargs.pop("copy_dtype", False)
xfm = ApplyTransforms(
input_image=in_file, transforms=in_xform, output_image=out_file, **ifargs
)
xfm.terminal_output = "allatonce"
xfm.resource_monitor = False
runtime = xfm.run().runtime
if copy_dtype:
nii = nb.load(out_file, mmap=False)
in_dtype = nb.load(in_file).get_data_dtype()
# Overwrite only iff dtypes don't match
if in_dtype != nii.get_data_dtype():
nii.set_data_dtype(in_dtype)
nii.to_filename(out_file)
return (out_file, runtime.cmdline)
def _arrange_xfms(transforms, num_files, tmp_folder):
"""
Convenience method to arrange the list of transforms that should be applied
to each input file
"""
base_xform = ["#Insight Transform File V1.0", "#Transform 0"]
# Initialize the transforms matrix
xfms_T = []
for i, tf_file in enumerate(transforms):
if tf_file == "identity":
xfms_T.append([tf_file] * num_files)
continue
# If it is a deformation field, copy to the tfs_matrix directly
if guess_type(tf_file)[0] != "text/plain":
xfms_T.append([tf_file] * num_files)
continue
with open(tf_file) as tf_fh:
tfdata = tf_fh.read().strip()
# If it is not an ITK transform file, copy to the tfs_matrix directly
if not tfdata.startswith("#Insight Transform File"):
xfms_T.append([tf_file] * num_files)
continue
# Count number of transforms in ITK transform file
nxforms = tfdata.count("#Transform")
# Remove first line
tfdata = tfdata.split("\n")[1:]
# If it is a ITK transform file with only 1 xform, copy to the tfs_matrix directly
if nxforms == 1:
xfms_T.append([tf_file] * num_files)
continue
if nxforms != num_files:
raise RuntimeError(
"Number of transforms (%d) found in the ITK file does not match"
" the number of input image files (%d)." % (nxforms, num_files)
)
# At this point splitting transforms will be necessary, generate a base name
out_base = fname_presuffix(
tf_file, suffix="_pos-%03d_xfm-{:05d}" % i, newpath=tmp_folder.name
).format
# Split combined ITK transforms file
split_xfms = []
for xform_i in range(nxforms):
# Find start token to extract
startidx = tfdata.index("#Transform %d" % xform_i)
next_xform = base_xform + tfdata[startidx + 1:startidx + 4] + [""]
xfm_file = out_base(xform_i)
with open(xfm_file, "w") as out_xfm:
out_xfm.write("\n".join(next_xform))
split_xfms.append(xfm_file)
xfms_T.append(split_xfms)
# Transpose back (only Python 3)
return list(map(list, zip(*xfms_T)))