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Jul 28, 2017
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ENH: Subclass RobustTemplate from FSCommandOpenMP #2130

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954f3b3
ENH: Subclass RobustTemplate from FSCommandOpenMP
effigies Jul 26, 2017
7df150f
STY: Style cleanup
effigies Jul 26, 2017
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91 changes: 53 additions & 38 deletions nipype/interfaces/freesurfer/longitudinal.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,55 +13,66 @@
from __future__ import print_function, division, unicode_literals, absolute_import

import os
#import itertools

from ... import logging
from ..base import (TraitedSpec, File, traits,
InputMultiPath, OutputMultiPath, isdefined)
from .base import FSCommand, FSTraitedSpec
from .base import (FSCommand, FSTraitedSpec, FSCommandOpenMP,
FSTraitedSpecOpenMP)

__docformat__ = 'restructuredtext'
iflogger = logging.getLogger('interface')


class RobustTemplateInputSpec(FSTraitedSpec):
class RobustTemplateInputSpec(FSTraitedSpecOpenMP):
# required
in_files = InputMultiPath(File(exists=True), mandatory=True, argstr='--mov %s',
desc='input movable volumes to be aligned to common mean/median template')
in_files = InputMultiPath(
File(exists=True), mandatory=True, argstr='--mov %s',
desc='input movable volumes to be aligned to common mean/median '
'template')
out_file = File('mri_robust_template_out.mgz', mandatory=True,
usedefault=True, argstr='--template %s',
desc='output template volume (final mean/median image)')
auto_detect_sensitivity = traits.Bool(argstr='--satit', xor=['outlier_sensitivity'], mandatory=True,
desc='auto-detect good sensitivity (recommended for head or full brain scans)')
outlier_sensitivity = traits.Float(argstr='--sat %.4f', xor=['auto_detect_sensitivity'], mandatory=True,
desc='set outlier sensitivity manually (e.g. "--sat 4.685" ). Higher values mean ' +
'less sensitivity.')
auto_detect_sensitivity = traits.Bool(
argstr='--satit', xor=['outlier_sensitivity'], mandatory=True,
desc='auto-detect good sensitivity (recommended for head or full '
'brain scans)')
outlier_sensitivity = traits.Float(
argstr='--sat %.4f', xor=['auto_detect_sensitivity'], mandatory=True,
desc='set outlier sensitivity manually (e.g. "--sat 4.685" ). Higher '
'values mean less sensitivity.')
# optional
transform_outputs = InputMultiPath(File(exists=False),
argstr='--lta %s',
desc='output xforms to template (for each input)')
intensity_scaling = traits.Bool(default_value=False,
argstr='--iscale',
desc='allow also intensity scaling (default off)')
scaled_intensity_outputs = InputMultiPath(File(exists=False),
argstr='--iscaleout %s',
desc='final intensity scales (will activate --iscale)')
subsample_threshold = traits.Int(argstr='--subsample %d',
desc='subsample if dim > # on all axes (default no subs.)')
average_metric = traits.Enum('median', 'mean', argstr='--average %d',
desc='construct template from: 0 Mean, 1 Median (default)')
initial_timepoint = traits.Int(argstr='--inittp %d',
desc='use TP# for spacial init (default random), 0: no init')
fixed_timepoint = traits.Bool(default_value=False, argstr='--fixtp',
desc='map everthing to init TP# (init TP is not resampled)')
no_iteration = traits.Bool(default_value=False, argstr='--noit',
desc='do not iterate, just create first template')
initial_transforms = InputMultiPath(File(exists=True),
argstr='--ixforms %s',
desc='use initial transforms (lta) on source')
in_intensity_scales = InputMultiPath(File(exists=True),
argstr='--iscalein %s',
desc='use initial intensity scales')
transform_outputs = InputMultiPath(
File(exists=False), argstr='--lta %s',
desc='output xforms to template (for each input)')
intensity_scaling = traits.Bool(
default_value=False, argstr='--iscale',
desc='allow also intensity scaling (default off)')
scaled_intensity_outputs = InputMultiPath(
File(exists=False), argstr='--iscaleout %s',
desc='final intensity scales (will activate --iscale)')
subsample_threshold = traits.Int(
argstr='--subsample %d',
desc='subsample if dim > # on all axes (default no subs.)')
average_metric = traits.Enum(
'median', 'mean', argstr='--average %d',
desc='construct template from: 0 Mean, 1 Median (default)')
initial_timepoint = traits.Int(
argstr='--inittp %d',
desc='use TP# for spacial init (default random), 0: no init')
fixed_timepoint = traits.Bool(
default_value=False, argstr='--fixtp',
desc='map everthing to init TP# (init TP is not resampled)')
no_iteration = traits.Bool(
default_value=False, argstr='--noit',
desc='do not iterate, just create first template')
initial_transforms = InputMultiPath(
File(exists=True), argstr='--ixforms %s',
desc='use initial transforms (lta) on source')
in_intensity_scales = InputMultiPath(
File(exists=True), argstr='--iscalein %s',
desc='use initial intensity scales')


class RobustTemplateOutputSpec(TraitedSpec):
out_file = File(
Expand All @@ -72,7 +83,7 @@ class RobustTemplateOutputSpec(TraitedSpec):
File(exists=True), desc="output final intensity scales")


class RobustTemplate(FSCommand):
class RobustTemplate(FSCommandOpenMP):
""" construct an unbiased robust template for longitudinal volumes

Examples
Expand All @@ -92,8 +103,10 @@ class RobustTemplate(FSCommand):
>>> template.cmdline #doctest: +NORMALIZE_WHITESPACE +ALLOW_UNICODE
'mri_robust_template --satit --average 0 --fixtp --mov structural.nii functional.nii --inittp 1 --noit --template T1.nii --subsample 200'

>>> template.inputs.transform_outputs = ['structural.lta', 'functional.lta']
>>> template.inputs.scaled_intensity_outputs = ['structural-iscale.txt', 'functional-iscale.txt']
>>> template.inputs.transform_outputs = ['structural.lta',
... 'functional.lta']
>>> template.inputs.scaled_intensity_outputs = ['structural-iscale.txt',
... 'functional-iscale.txt']
>>> template.cmdline #doctest: +NORMALIZE_WHITESPACE +ALLOW_UNICODE
'mri_robust_template --satit --average 0 --fixtp --mov structural.nii functional.nii --inittp 1 --noit --template T1.nii --iscaleout structural-iscale.txt functional-iscale.txt --subsample 200 --lta structural.lta functional.lta'

Expand Down Expand Up @@ -151,9 +164,11 @@ class FuseSegmentationsInputSpec(FSTraitedSpec):
must include the corresponding norm file for all given timepoints \
as well as for the current subject")


class FuseSegmentationsOutputSpec(TraitedSpec):
out_file = File(exists=False, desc="output fused segmentation file")


class FuseSegmentations(FSCommand):

""" fuse segmentations together from multiple timepoints
Expand Down
1 change: 1 addition & 0 deletions nipype/interfaces/freesurfer/tests/test_auto_RobustTemplate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,6 +33,7 @@ def test_RobustTemplate_inputs():
),
no_iteration=dict(argstr='--noit',
),
num_threads=dict(),
out_file=dict(argstr='--template %s',
mandatory=True,
usedefault=True,
Expand Down