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oestebanoesteban
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Update to use JSONFileGrabber. Fix pep8 errors
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+120
-106
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-106
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‎nipype/workflows/dmri/fsl/artifacts.py‎

Lines changed: 120 additions & 106 deletions
Original file line numberDiff line numberDiff line change
@@ -4,6 +4,7 @@
44
import os
55

66
import nipype.pipeline.engine as pe
7+
from nipype.interfaces.io import JSONFileGrabber
78
from nipype.interfaces import utility as niu
89
from nipype.interfaces import freesurfer as fs
910
from nipype.interfaces import ants
@@ -42,17 +43,19 @@ def all_fmb_pipeline(name='hmc_sdc_ecc',
4243
>>> allcorr.run() # doctest: +SKIP
4344
4445
"""
45-
inputnode = pe.Node(niu.IdentityInterface(fields=['in_file', 'in_bvec',
46-
'in_bval', 'bmap_pha', 'bmap_mag']), name='inputnode')
47-
48-
outputnode = pe.Node(niu.IdentityInterface(fields=['out_file', 'out_mask',
49-
'out_bvec']), name='outputnode')
50-
avg_b0_0 = pe.Node(niu.Function(input_names=['in_dwi', 'in_bval'],
51-
output_names=['out_file'], function=b0_average),
52-
name='b0_avg_pre')
53-
avg_b0_1 = pe.Node(niu.Function(input_names=['in_dwi', 'in_bval'],
54-
output_names=['out_file'], function=b0_average),
55-
name='b0_avg_post')
46+
inputnode = pe.Node(niu.IdentityInterface(
47+
fields=['in_file', 'in_bvec', 'in_bval', 'bmap_pha', 'bmap_mag']),
48+
name='inputnode')
49+
50+
outputnode = pe.Node(niu.IdentityInterface(
51+
fields=['out_file', 'out_mask', 'out_bvec']), name='outputnode')
52+
53+
avg_b0_0 = pe.Node(niu.Function(
54+
input_names=['in_dwi', 'in_bval'], output_names=['out_file'],
55+
function=b0_average), name='b0_avg_pre')
56+
avg_b0_1 = pe.Node(niu.Function(
57+
input_names=['in_dwi', 'in_bval'], output_names=['out_file'],
58+
function=b0_average), name='b0_avg_post')
5659
bet_dwi0 = pe.Node(fsl.BET(frac=0.3, mask=True, robust=True),
5760
name='bet_dwi_pre')
5861
bet_dwi1 = pe.Node(fsl.BET(frac=0.3, mask=True, robust=True),
@@ -128,18 +131,19 @@ def all_peb_pipeline(name='hmc_sdc_ecc',
128131
>>> allcorr.run() # doctest: +SKIP
129132
130133
"""
131-
inputnode = pe.Node(niu.IdentityInterface(fields=['in_file', 'in_bvec',
132-
'in_bval', 'alt_file']), name='inputnode')
133-
134-
outputnode = pe.Node(niu.IdentityInterface(fields=['out_file', 'out_mask',
135-
'out_bvec']), name='outputnode')
136-
137-
avg_b0_0 = pe.Node(niu.Function(input_names=['in_dwi', 'in_bval'],
138-
output_names=['out_file'], function=b0_average),
139-
name='b0_avg_pre')
140-
avg_b0_1 = pe.Node(niu.Function(input_names=['in_dwi', 'in_bval'],
141-
output_names=['out_file'], function=b0_average),
142-
name='b0_avg_post')
134+
inputnode = pe.Node(niu.IdentityInterface(
135+
fields=['in_file', 'in_bvec', 'in_bval', 'alt_file']),
136+
name='inputnode')
137+
138+
outputnode = pe.Node(niu.IdentityInterface(
139+
fields=['out_file', 'out_mask', 'out_bvec']), name='outputnode')
140+
141+
avg_b0_0 = pe.Node(niu.Function(
142+
input_names=['in_dwi', 'in_bval'], output_names=['out_file'],
143+
function=b0_average), name='b0_avg_pre')
144+
avg_b0_1 = pe.Node(niu.Function(
145+
input_names=['in_dwi', 'in_bval'], output_names=['out_file'],
146+
function=b0_average), name='b0_avg_post')
143147
bet_dwi0 = pe.Node(fsl.BET(frac=0.3, mask=True, robust=True),
144148
name='bet_dwi_pre')
145149
bet_dwi1 = pe.Node(fsl.BET(frac=0.3, mask=True, robust=True),
@@ -216,11 +220,12 @@ def all_fsl_pipeline(name='fsl_all_correct',
216220
217221
"""
218222

219-
inputnode = pe.Node(niu.IdentityInterface(fields=['in_file', 'in_bvec',
220-
'in_bval', 'alt_file']), name='inputnode')
223+
inputnode = pe.Node(niu.IdentityInterface(
224+
fields=['in_file', 'in_bvec', 'in_bval', 'alt_file']),
225+
name='inputnode')
221226

222-
outputnode = pe.Node(niu.IdentityInterface(fields=['out_file', 'out_mask',
223-
'out_bvec']), name='outputnode')
227+
outputnode = pe.Node(niu.IdentityInterface(
228+
fields=['out_file', 'out_mask', 'out_bvec']), name='outputnode')
224229

225230
def _gen_index(in_file):
226231
import numpy as np
@@ -231,20 +236,20 @@ def _gen_index(in_file):
231236
np.savetxt(out_file, np.ones((vols,)).T)
232237
return out_file
233238

234-
avg_b0_0 = pe.Node(niu.Function(input_names=['in_dwi', 'in_bval'],
235-
output_names=['out_file'], function=b0_average),
236-
name='b0_avg_pre')
239+
avg_b0_0 = pe.Node(niu.Function(
240+
input_names=['in_dwi', 'in_bval'], output_names=['out_file'],
241+
function=b0_average), name='b0_avg_pre')
237242
bet_dwi0 = pe.Node(fsl.BET(frac=0.3, mask=True, robust=True),
238243
name='bet_dwi_pre')
239244

240245
sdc = sdc_peb(epi_params=epi_params, altepi_params=altepi_params)
241246
ecc = pe.Node(fsl.Eddy(method='jac'), name='fsl_eddy')
242-
rot_bvec = pe.Node(niu.Function(input_names=['in_bvec', 'eddy_params'],
243-
output_names=['out_file'], function=eddy_rotate_bvecs),
244-
name='Rotate_Bvec')
245-
avg_b0_1 = pe.Node(niu.Function(input_names=['in_dwi', 'in_bval'],
246-
output_names=['out_file'], function=b0_average),
247-
name='b0_avg_post')
247+
rot_bvec = pe.Node(niu.Function(
248+
input_names=['in_bvec', 'eddy_params'], output_names=['out_file'],
249+
function=eddy_rotate_bvecs), name='Rotate_Bvec')
250+
avg_b0_1 = pe.Node(niu.Function(
251+
input_names=['in_dwi', 'in_bval'], output_names=['out_file'],
252+
function=b0_average), name='b0_avg_post')
248253
bet_dwi1 = pe.Node(fsl.BET(frac=0.3, mask=True, robust=True),
249254
name='bet_dwi_post')
250255

@@ -349,22 +354,22 @@ def hmc_pipeline(name='motion_correct'):
349354
# cost='mutualinfo', cost_func='mutualinfo', bins=64,
350355
schedule=get_flirt_schedule('hmc'))
351356

352-
inputnode = pe.Node(niu.IdentityInterface(fields=['in_file', 'ref_num',
353-
'in_bvec', 'in_bval', 'in_mask']), name='inputnode')
354-
split = pe.Node(niu.Function(function=hmc_split,
355-
input_names=['in_file', 'in_bval', 'ref_num'],
356-
output_names=['out_ref', 'out_mov', 'out_bval', 'volid']),
357-
name='SplitDWI')
357+
inputnode = pe.Node(niu.IdentityInterface(
358+
fields=['in_file', 'ref_num', 'in_bvec', 'in_bval', 'in_mask']),
359+
name='inputnode')
360+
split = pe.Node(niu.Function(
361+
output_names=['out_ref', 'out_mov', 'out_bval', 'volid'],
362+
input_names=['in_file', 'in_bval', 'ref_num'], function=hmc_split),
363+
name='SplitDWI')
358364
flirt = dwi_flirt(flirt_param=params)
359365
insmat = pe.Node(niu.Function(input_names=['inlist', 'volid'],
360366
output_names=['out'], function=insert_mat),
361367
name='InsertRefmat')
362-
rot_bvec = pe.Node(niu.Function(input_names=['in_bvec', 'in_matrix'],
363-
output_names=['out_file'], function=rotate_bvecs),
364-
name='Rotate_Bvec')
365-
outputnode = pe.Node(niu.IdentityInterface(fields=['out_file',
366-
'out_bvec', 'out_xfms']),
367-
name='outputnode')
368+
rot_bvec = pe.Node(niu.Function(
369+
function=rotate_bvecs, input_names=['in_bvec', 'in_matrix'],
370+
output_names=['out_file']), name='Rotate_Bvec')
371+
outputnode = pe.Node(niu.IdentityInterface(
372+
fields=['out_file', 'out_bvec', 'out_xfms']), name='outputnode')
368373

369374
wf = pe.Workflow(name=name)
370375
wf.connect([
@@ -450,14 +455,14 @@ def ecc_pipeline(name='eddy_correct'):
450455
schedule=get_flirt_schedule('ecc'))
451456
# cost='normmi', cost_func='normmi', bins=64,
452457

453-
inputnode = pe.Node(niu.IdentityInterface(fields=['in_file', 'in_bval',
454-
'in_mask', 'in_xfms']), name='inputnode')
455-
avg_b0 = pe.Node(niu.Function(input_names=['in_dwi', 'in_bval'],
456-
output_names=['out_file'], function=b0_average),
457-
name='b0_avg')
458-
pick_dws = pe.Node(niu.Function(input_names=['in_dwi', 'in_bval', 'b'],
459-
output_names=['out_file'], function=extract_bval),
460-
name='ExtractDWI')
458+
inputnode = pe.Node(niu.IdentityInterface(
459+
fields=['in_file', 'in_bval', 'in_mask', 'in_xfms']), name='inputnode')
460+
avg_b0 = pe.Node(niu.Function(
461+
input_names=['in_dwi', 'in_bval'], output_names=['out_file'],
462+
function=b0_average), name='b0_avg')
463+
pick_dws = pe.Node(niu.Function(
464+
input_names=['in_dwi', 'in_bval', 'b'], output_names=['out_file'],
465+
function=extract_bval), name='ExtractDWI')
461466
pick_dws.inputs.b = 'diff'
462467

463468
flirt = dwi_flirt(flirt_param=params, excl_nodiff=True)
@@ -468,14 +473,15 @@ def ecc_pipeline(name='eddy_correct'):
468473
name='RemoveNegative')
469474

470475
split = pe.Node(fsl.Split(dimension='t'), name='SplitDWIs')
471-
get_mat = pe.Node(niu.Function(input_names=['in_bval', 'in_xfms'],
472-
output_names=['out_files'], function=recompose_xfm),
473-
name='GatherMatrices')
474-
merge = pe.Node(niu.Function(input_names=['in_dwi', 'in_bval', 'in_corrected'],
475-
output_names=['out_file'], function=recompose_dwi), name='MergeDWIs')
476+
get_mat = pe.Node(niu.Function(
477+
input_names=['in_bval', 'in_xfms'], output_names=['out_files'],
478+
function=recompose_xfm), name='GatherMatrices')
479+
merge = pe.Node(niu.Function(
480+
input_names=['in_dwi', 'in_bval', 'in_corrected'],
481+
output_names=['out_file'], function=recompose_dwi), name='MergeDWIs')
476482

477-
outputnode = pe.Node(niu.IdentityInterface(fields=['out_file', 'out_xfms']),
478-
name='outputnode')
483+
outputnode = pe.Node(niu.IdentityInterface(
484+
fields=['out_file', 'out_xfms']), name='outputnode')
479485

480486
wf = pe.Workflow(name=name)
481487
wf.connect([
@@ -505,11 +511,7 @@ def ecc_pipeline(name='eddy_correct'):
505511

506512

507513
def sdc_fmb(name='fmb_correction',
508-
fugue_params=dict(smooth3d=2.0),
509-
bmap_params=dict(delta_te=2.46e-3),
510-
epi_params=dict(echospacing=0.77e-3,
511-
acc_factor=3,
512-
enc_dir='AP')):
514+
fugue_params=dict(smooth3d=2.0)):
513515
"""
514516
SDC stands for susceptibility distortion correction. FMB stands for
515517
fieldmap-based.
@@ -523,14 +525,6 @@ def sdc_fmb(name='fmb_correction',
523525
script in FSL `fsl_prepare_fieldmap
524526
<http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FUGUE/Guide#SIEMENS_data>`_.
525527
526-
Default settings
527-
----------------
528-
529-
>>> fugue_params=dict(smooth3d=2.0),
530-
>>> bmap_params=dict(delta_te=2.46e-3),
531-
>>> epi_params=dict(echospacing=0.77e-3,
532-
... acc_factor=3,
533-
... enc_dir='AP')
534528
535529
536530
Example
@@ -560,24 +554,35 @@ def sdc_fmb(name='fmb_correction',
560554
561555
"""
562556

563-
if epi_params['enc_dir'].upper() == 'LR':
564-
epi_params['enc_dir'] = 'x-'
557+
defaults = dict(delta_te=2.46e-3, echospacing=0.77e-3, acc_factor=3,
558+
enc_dir='AP')
565559

566-
if epi_params['enc_dir'].upper() == 'RL':
567-
epi_params['enc_dir'] = 'x'
560+
delta_te = epi_params['echospacing'] / (1.0 * epi_params['acc_factor'])
568561

569-
if epi_params['enc_dir'].upper() == 'AP':
570-
epi_params['enc_dir'] = 'y-'
562+
def _fix_enc_dir(enc_dir):
563+
enc_dir = enc_dir.lower()
564+
if enc_dir == 'lr':
565+
return 'x-'
566+
if enc_dir == 'rl':
567+
return 'x'
571568

572-
if epi_params['enc_dir'].upper() == 'PA':
573-
epi_params['enc_dir'] = 'y'
569+
if enc_dir == 'ap':
570+
return 'y-'
571+
if enc_dir == 'pa':
572+
return 'y'
573+
return enc_dir
574574

575575
inputnode = pe.Node(niu.IdentityInterface(
576-
fields=['in_file', 'in_bval', 'in_mask', 'bmap_pha', 'bmap_mag']),
577-
name='inputnode')
576+
fields=['in_file', 'in_bval', 'in_mask', 'bmap_pha', 'bmap_mag',
577+
'settings']), name='inputnode')
578+
578579
outputnode = pe.Node(niu.IdentityInterface(
579580
fields=['out_file', 'out_vsm', 'out_warp']), name='outputnode')
580-
delta_te = epi_params['echospacing'] / (1.0 * epi_params['acc_factor'])
581+
582+
r_params = pe.Node(JSONFileGrabber(), name='SettingsGrabber')
583+
eff_echo = pe.Node(niu.Function(function=_eff_t_echo,
584+
input_names=['echospacing', 'acc_factor'],
585+
output_names=['eff_echo']), name='EffEcho')
581586

582587
firstmag = pe.Node(fsl.ExtractROI(t_min=0, t_size=1), name='GetFirst')
583588
n4 = pe.Node(ants.N4BiasFieldCorrection(dimension=3), name='Bias')
@@ -591,7 +596,6 @@ def sdc_fmb(name='fmb_correction',
591596
rad2rsec = pe.Node(niu.Function(
592597
input_names=['in_file', 'delta_te'], output_names=['out_file'],
593598
function=rads2radsec), name='ToRadSec')
594-
rad2rsec.inputs.delta_te = bmap_params['delta_te']
595599

596600
avg_b0 = pe.Node(niu.Function(
597601
input_names=['in_dwi', 'in_bval'], output_names=['out_file'],
@@ -623,9 +627,9 @@ def sdc_fmb(name='fmb_correction',
623627
dimension=3, interpolation='BSpline'), name='FMp_to_B0')
624628

625629
pre_fugue = pe.Node(fsl.FUGUE(save_fmap=True), name='PreliminaryFugue')
626-
demean = pe.Node(niu.Function(input_names=['in_file', 'in_mask'],
627-
output_names=['out_file'], function=demean_image),
628-
name='DemeanFmap')
630+
demean = pe.Node(niu.Function(
631+
input_names=['in_file', 'in_mask'], output_names=['out_file'],
632+
function=demean_image), name='DemeanFmap')
629633

630634
cleanup = cleanup_edge_pipeline()
631635

@@ -635,8 +639,6 @@ def sdc_fmb(name='fmb_correction',
635639

636640
vsm = pe.Node(fsl.FUGUE(save_shift=True, **fugue_params),
637641
name="ComputeVSM")
638-
vsm.inputs.asym_se_time = bmap_params['delta_te']
639-
vsm.inputs.dwell_time = delta_te
640642

641643
split = pe.Node(fsl.Split(dimension='t'), name='SplitDWIs')
642644
merge = pe.Node(fsl.Merge(dimension='t'), name='MergeDWIs')
@@ -647,10 +649,12 @@ def sdc_fmb(name='fmb_correction',
647649
name='RemoveNegative')
648650
vsm2dfm = vsm2warp()
649651
vsm2dfm.inputs.inputnode.scaling = 1.0
650-
vsm2dfm.inputs.inputnode.enc_dir = epi_params['enc_dir']
651652

652653
wf = pe.Workflow(name=name)
653654
wf.connect([
655+
(inputnode, r_params, [('settings', 'in_file')]),
656+
(r_params, eff_echo, [('echospacing', 'echospacing'),
657+
('acc_factor', 'acc_factor')]),
654658
(inputnode, pha2rads, [('bmap_pha', 'in_file')]),
655659
(inputnode, firstmag, [('bmap_mag', 'in_file')]),
656660
(inputnode, avg_b0, [('in_file', 'in_dwi'),
@@ -661,6 +665,7 @@ def sdc_fmb(name='fmb_correction',
661665
(pha2rads, prelude, [('out_file', 'phase_file')]),
662666
(n4, prelude, [('output_image', 'magnitude_file')]),
663667
(dilate, prelude, [('out_file', 'mask_file')]),
668+
(r_params, rad2rsec, [('delta_te', 'delta_te')]),
664669
(prelude, rad2rsec, [('unwrapped_phase_file', 'in_file')]),
665670

666671
(avg_b0, fmm2b0, [('out_file', 'fixed_image')]),
@@ -683,11 +688,14 @@ def sdc_fmb(name='fmb_correction',
683688
(cleanup, addvol, [('outputnode.out_file', 'in_file')]),
684689
(inputnode, vsm, [('in_mask', 'mask_file')]),
685690
(addvol, vsm, [('out_file', 'fmap_in_file')]),
691+
(r_params, vsm, [('delta_te', 'asym_se_time')]),
692+
(eff_echo, vsm, [('eff_echo', 'dwell_time')]),
686693
(inputnode, split, [('in_file', 'in_file')]),
687694
(split, unwarp, [('out_files', 'in_file')]),
688695
(vsm, unwarp, [('shift_out_file', 'shift_in_file')]),
689696
(unwarp, thres, [('unwarped_file', 'in_file')]),
690697
(thres, merge, [('out_file', 'in_files')]),
698+
(r_params, vsm2dfm, [(('enc_dir', _fix_enc_dir), 'enc_dir')]),
691699
(merge, vsm2dfm, [('merged_file', 'inputnode.in_ref')]),
692700
(vsm, vsm2dfm, [('shift_out_file', 'inputnode.in_vsm')]),
693701
(merge, outputnode, [('merged_file', 'out_file')]),
@@ -748,11 +756,11 @@ def sdc_peb(name='peb_correction',
748756
749757
"""
750758

751-
inputnode = pe.Node(niu.IdentityInterface(fields=['in_file', 'in_bval',
752-
'in_mask', 'alt_file', 'ref_num']),
753-
name='inputnode')
754-
outputnode = pe.Node(niu.IdentityInterface(fields=['out_file', 'out_vsm',
755-
'out_warp']), name='outputnode')
759+
inputnode = pe.Node(niu.IdentityInterface(
760+
fields=['in_file', 'in_bval', 'in_mask', 'alt_file', 'ref_num']),
761+
name='inputnode')
762+
outputnode = pe.Node(niu.IdentityInterface(
763+
fields=['out_file', 'out_vsm', 'out_warp']), name='outputnode')
756764

757765
b0_ref = pe.Node(fsl.ExtractROI(t_size=1), name='b0_ref')
758766
b0_alt = pe.Node(fsl.ExtractROI(t_size=1), name='b0_alt')
@@ -826,17 +834,18 @@ def remove_bias(name='bias_correct'):
826834
>>> bias.run() # doctest: +SKIP
827835
828836
"""
829-
inputnode = pe.Node(niu.IdentityInterface(fields=['in_file', 'in_bval',
830-
'in_mask']), name='inputnode')
837+
inputnode = pe.Node(niu.IdentityInterface(
838+
fields=['in_file', 'in_bval', 'in_mask']), name='inputnode')
831839

832840
outputnode = pe.Node(niu.IdentityInterface(fields=['out_file']),
833841
name='outputnode')
834842

835-
avg_b0 = pe.Node(niu.Function(input_names=['in_dwi', 'in_bval'],
836-
output_names=['out_file'], function=b0_average),
837-
name='b0_avg')
838-
n4 = pe.Node(ants.N4BiasFieldCorrection(dimension=3,
839-
save_bias=True, bspline_fitting_distance=600), name='Bias_b0')
843+
avg_b0 = pe.Node(niu.Function(
844+
input_names=['in_dwi', 'in_bval'], output_names=['out_file'],
845+
function=b0_average), name='b0_avg')
846+
n4 = pe.Node(ants.N4BiasFieldCorrection(
847+
dimension=3, save_bias=True, bspline_fitting_distance=600),
848+
name='Bias_b0')
840849
split = pe.Node(fsl.Split(dimension='t'), name='SplitDWIs')
841850
mult = pe.MapNode(fsl.MultiImageMaths(op_string='-div %s'),
842851
iterfield=['in_file'], name='RemoveBiasOfDWIs')
@@ -860,6 +869,11 @@ def remove_bias(name='bias_correct'):
860869
return wf
861870

862871

872+
def _eff_t_echo(echospacing, acc_factor):
873+
eff_echo = echospacing / (1.0 * acc_factor)
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return eff_echo
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def _checkrnum(ref_num):
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from nipype.interfaces.base import isdefined
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if (ref_num is None) or not isdefined(ref_num):

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