Added ANTS functions antsIntroduction.sh, WarpImageMultiTransform, build...

nipype/interfaces/ants/__init__.py

@@ -0,0 +1,7 @@
+# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
+# vi: set ft=python sts=4 ts=4 sw=4 et:
+"""Top-level namespace for ants."""
+from nipype.interfaces.ants.base import ANTSCommand
+from nipype.interfaces.ants.normalize import (BuildTemplate, 
+                                         WarpImageMultiTransform, GenWarpFields)
+

nipype/interfaces/ants/base.py

@@ -0,0 +1,25 @@
+# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
+# vi: set ft=python sts=4 ts=4 sw=4 et:
+"""The ants module provides basic functions for interfacing with ANTS tools."""
+
+__docformat__ = 'restructuredtext'
+
+# Standard library imports
+import os
+from copy import deepcopy
+
+# Third-party imports
+import numpy as np
+
+# Local imports
+from nipype.interfaces.base import (TraitedSpec, File, traits,
+                                    Directory, InputMultiPath,
+                                    OutputMultiPath, CommandLine,
+                                    CommandLineInputSpec, isdefined)
+import logging
+logger = logging.getLogger('iflogger')
+
+class ANTSCommand(CommandLine):
+    def __init__(self, **inputs):
+        self.inputs.environ['ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS']='1'
+        return super(ANTSCommand, self).__init__(**inputs)

nipype/interfaces/ants/normalize.py

@@ -0,0 +1,299 @@
+# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
+# vi: set ft=python sts=4 ts=4 sw=4 et:
+"""The ants module provides basic functions for interfacing with ants functions.
+
+   Change directory to provide relative paths for doctests
+   >>> import os
+   >>> filepath = os.path.dirname( os.path.realpath( __file__ ) )
+   >>> datadir = os.path.realpath(os.path.join(filepath, '../../testing/data'))
+   >>> os.chdir(datadir)
+
+"""
+
+__docformat__ = 'restructuredtext'
+
+# Standard library imports
+import logging
+import os
+from glob import glob
+
+# Third-party imports
+import numpy as np
+import scipy.io as sio
+
+# Local imports
+from nipype.interfaces.base import (TraitedSpec, File, traits,
+                                    Directory, InputMultiPath,
+                                    OutputMultiPath, CommandLine,
+                                    CommandLineInputSpec, isdefined)
+from nipype.utils.filemanip import (filename_to_list,copyfiles, list_to_filename,
+                                    split_filename, fname_presuffix)
+from nipype.interfaces.ants.base import ANTSCommand
+
+class BuildTemplateInputSpec(CommandLineInputSpec):
+    dimension = traits.Enum(3, 2, argstr='-d %d',usedefault=True,
+                             desc='image dimension (2 or 3)', position=1)
+    out_prefix = traits.Str('antsTMPL_',argstr='-o %s',usedefault=True,
+                             desc='Prefix that is prepended to all output files '
+                             '(default = antsTMPL_)')
+    in_files = traits.List(File(exists=True), mandatory=True,
+                             desc='list of images to generate template from',argstr='%s',position=-1)
+    parallelization = traits.Enum(0,1,2,argstr='-c %d',usedefault=True,
+                             desc='control for parallel processing (0 = serial, '
+                             '1 = use PBS, 2 = use PEXEC, 3 = use Apple XGrid')
+    gradient_step_size = traits.Float(argstr='-g %f',desc='smaller magnitude '
+                             'results in more cautious steps (default = .25)')
+    iteration_limit = traits.Int(argstr='-i %d',desc='iterations of template '
+                             'construction (default 4)')
+    num_cores = traits.Int(argstr='-j %d',requires=['parallelization'],desc='Requires parallelization = 2 (PEXEC). '
+                             'Sets number of cpu cores to use (default 2)')
+    max_iterations = traits.List(traits.Int,argstr='-m %s',sep='x',
+                             desc='maximum number of iterations (must be list of integers '
+                             'in the form [J,K,L...]: J = coarsest resolution iterations, '
+                             'K = middle resolution interations, L = fine resolution '
+                             'iterations')
+    bias_field_correction = traits.Bool(argstr = '-n 1',
+                             desc='Applies bias field correction to moving image')
+    rigid_body_registration = traits.Bool(argstr='-r 1',
+                             desc='registers inputs before creating template (useful'
+                             'if no initial template available)')
+    similarity_metric = traits.Enum('PR','CC','MI','MSQ',argstr='-s %s',
+                             desc='Type of similartiy metric used for registration '
+                             '(CC = cross correlation, MI = mutual information, '
+                             'PR = probability mapping, MSQ = mean square difference)')
+    transformation_model = traits.Enum('GR','EL','SY','S2','EX','DD',argstr='-t %s',usedefault=True,
+                             desc='Type of transofmration model used for registration '
+                             '(EL = elastic transformation model, SY = SyN with time, '
+                             'arbitrary number of time points, S2 =  SyN with time '
+                             'optimized for 2 time points, GR = greedy SyN, EX = '
+                             'exponential, DD = diffeomorphic demons style exponential '
+                             'mapping')
+    use_first_as_target = traits.Bool(desc='uses first volume as target of all inputs. '
+                             'When not used, an unbiased average image is used to start.')
+
+class BuildTemplateOutputSpec(TraitedSpec):
+    final_template_file = File(exists=True, desc='final ANTS template')
+    template_files = traits.Either(traits.List(File(exists=True)),
+                             File(exists=True), desc='Templates from different stages of iteration')
+    subject_outfiles = output_images = traits.Either(traits.List(File(exists=True)),
+                             File(exists=True), desc='Outputs for each input image. '
+                             'Includes warp field, inverse warp, Affine, original image (repaired) '
+                             'and warped image (deformed)')
+
+
+class BuildTemplate(ANTSCommand):
+    """Uses the ANTS command buildtemplateparallel.sh to generate a template from the files listed in in_files.
+
+    .. note::
+      This can take a VERY long time to complete
+
+    Examples
+    --------
+
+    >>> from nipype.interfaces.ants import BuildTemplate
+    >>> tmpl = BuildTemplate()
+    >>> tmpl.inputs.in_files = ['foo.nii','bar.nii']
+    >>> tmpl.inputs.max_iterations = [30,90,20]
+    >>> tpml.cmdline
+    'buildtemplateparallel.sh -d 3 -m 30x90x20 -o antsTMPL_ -c 0 -t GR foo.nii bar.nii'
+
+    """
+
+    _cmd = 'buildtemplateparallel.sh'
+    input_spec = BuildTemplateInputSpec
+    output_spec = BuildTemplateOutputSpec
+
+
+
+    def _format_arg(self, opt, spec, val):
+        if opt == 'num_cores':
+            if self.inputs.parallelization == 2:
+                return '-j '+val
+            else: 
+                return ''
+        if opt == 'in_files':
+            if self.inputs.use_first_as_target:
+                start='-z '
+            else:
+                start=''
+            return start+' '.join([os.path.split(name)[1] for name in val])
+        return super(BuildTemplate,self)._format_arg(opt,spec,val)
+
+    def _list_outputs(self):
+        outputs = self._outputs().get()
+        outputs['template_files'] = []
+        for i in range(len(glob(os.path.realpath('*iteration*')))):
+            temp = os.path.realpath('%s_iteration_%d/%stemplate.nii.gz'%(self.inputs.transformation_model,i,self.inputs.out_prefix))
+            os.rename(temp,os.path.realpath('%s_iteration_%d/%stemplate_i%d.nii.gz'%(self.inputs.transformation_model,i,self.inputs.out_prefix,i)))
+            outputs['template_files'].append(os.path.realpath('%s_iteration_%d/%stemplate_i%d.nii.gz'%(self.inputs.transformation_model,i,self.inputs.out_prefix,i)))
+        outputs['final_template_file'] = os.path.realpath('%stemplate.nii.gz'%self.inputs.out_prefix)
+        outputs['subject_outfiles'] = []
+        for filename in self.inputs.in_files:
+            pth, base, ext = split_filename(filename)
+            temp = glob(os.path.realpath('%s%s*'%(self.inputs.out_prefix,base)))
+            for file_ in temp:
+                outputs['subject_outfiles'].append(file_)
+        return outputs
+
+
+
+
+class WarpImageMultiTransformInputSpec(CommandLineInputSpec):
+    dimension = traits.Enum(3, 2, argstr='%d',usedefault=True,
+                             desc='image dimension (2 or 3)',position=1)
+    moving_image = File(argstr='%s',desc='image to apply transformation '
+                             'to (generally a coregistered functional)',
+                              mandatory=True, copyfile=True)
+    out_postfix = traits.Str('_wimt',argstr='%s',
+                             desc='Postfix that is prepended to all output files '
+                             '(default = _wimt)',usedefault=True)
+    reference_image = File(argstr='-R %s',desc='reference image space that you '
+                             'wish to warp INTO',xor=['tightest_box'])
+    tightest_box = traits.Bool(argstr='--tightest-bounding-box',
+                             desc='computes tightest bounding box (overrided by '
+                             'reference_image if given)',xor=['reference_image'])
+    reslice_by_header = traits.Bool(argstr='--reslice-by-header',
+                             desc='Uses orientation matrix and origin encoded in '
+                             'reference image file header. Not typically used with '
+                             'additional transforms')
+    use_nearest = traits.Bool(argstr='--use-NN',desc='Use nearest neighbor interpolation')
+    use_bspline = traits.Bool(argstr='--use-Bspline',desc='Use 3rd order'
+                             'B-Spline interpolation')
+    transformation_series = InputMultiPath(File(exists=True),argstr='%s',
+                             desc='transformation file(s) to be applied',
+                             mandatory=True, copyfile=False)
+    invert_affine = traits.List(traits.Int, desc='List of Affine transformations to invert. '
+                             'E.g.: [1,4,5] inverts the 1st, 4th, and 5th Affines '
+                             'found in transformation_series')
+
+
+
+
+
+class WarpImageMultiTransformOutputSpec(TraitedSpec):
+    output_images = traits.Either(traits.List(File(exists=True)),
+                             File(exists=True))
+
+class WarpImageMultiTransform(ANTSCommand):
+    """Uses the ANTS command WarpImageMultiTransform to warp an image (moving image) from one space to another (fixed/template space)
+
+    Examples
+    --------
+
+    >>> from nipype.interfaces.ants import WarpImageMultiTransform
+    >>> wimt = WarpImageMultiTransform()
+    >>> wimt.inputs.moving_image = 'foo.nii'
+    >>> wimt.inputs.reference_image = 'ants_deformed.nii.gz'
+    >>> wimt.inputs.transformation_series = ['ants_Warp.nii.gz','ants_Affine.txt']
+    >>> wimt.cmdline
+    'WarpImageMultiTransform 3 foo.nii foo_wimt.nii -R ants_deformed.nii.gz ants_Warp.nii.gz ants_Affine.txt'
+
+    """
+
+    _cmd = 'WarpImageMultiTransform'
+    input_spec = WarpImageMultiTransformInputSpec
+    output_spec = WarpImageMultiTransformOutputSpec
+
+    def _format_arg(self, opt, spec, val):
+        if opt == 'out_postfix':
+            return os.path.split(self.inputs.moving_image)[-1].partition('.')[0]+val+'.'+os.path.split(self.inputs.moving_image)[-1].partition('.')[2]
+        if opt == 'transformation_series':
+            series = ''
+            affine_counter = 0
+            for transformation in val:
+                if transformation.find('Affine')!=-1 and isdefined(self.inputs.invert_affine):
+                     affine_counter = affine_counter + 1
+                     if self.inputs.invert_affine.__contains__(affine_counter):
+                         series=series+'-i '+transformation+' '
+                     else:
+                         series=series+transformation+' '
+                else:
+                     series=series+transformation+' '
+
+            return series
+        return super(WarpImageMultiTransform,self)._format_arg(opt,spec,val)
+
+    def _list_outputs(self):
+        outputs = self._outputs().get()
+        outputs['output_images'] = glob(os.path.join(os.getcwd(),os.path.split(self.inputs.moving_image)[-1].partition('.')[0]+self.inputs.out_postfix+'*'))[0]
+        print outputs['output_images']
+        return outputs    
+
+
+class AntsIntroductionInputSpec(CommandLineInputSpec):
+    dimension = traits.Enum(3, 2, argstr='-d %d',usedefault=True,
+                             desc='image dimension (2 or 3)', position=1)
+    reference_image = File(argstr='-r %s',desc='template file to warp to',
+                             mandatory=True, copyfile=True)
+    input_image = File(argstr='-i %s',desc='input image to warp to template',
+                             mandatory=True, copyfile=False)
+    force_proceed = traits.Bool(argstr='-f 1',
+                             desc='force script to proceed even if headers may '
+                             'be incompatible')
+    inverse_warp_template_labels = traits.Bool(argstr='-l', 
+                             desc='Applies inverse warp to the template labels '
+                             'to estimate label positions in target space (use '
+                             'for template-based segmentation)')
+    max_iterations = traits.List(traits.Int,argstr='-m %s',sep='x',
+                             desc='maximum number of iterations (must be list of integers '
+                             'in the form [J,K,L...]: J = coarsest resolution iterations, '
+                             'K = middle resolution interations, L = fine resolution '
+                             'iterations')
+    bias_field_correction = traits.Bool(argstr='-n 1', 
+                             desc='Applies bias field correction to moving image')
+    out_prefix = traits.Str('ants_',argstr='-o %s', usedefault=True,
+                             desc='Prefix that is prepended to all output files '
+                             '(default = ants_)')
+    quality_check = traits.Bool(argstr='-q 1', 
+                             desc='Perform a quality check of the result')
+    similarity_metric = traits.Enum('PR','CC','MI','MSQ',argstr='-s %s',
+                             desc='Type of similartiy metric used for registration '
+                             '(CC = cross correlation, MI = mutual information, '
+                             'PR = probability mapping, MSQ = mean square difference)')
+    transformation_model = traits.Enum('GR','EL','SY','S2','EX','DD','RI','RA',argstr='-t %s',
+                             desc='Type of transofmration model used for registration '
+                             '(EL = elastic transformation model, SY = SyN with time, '
+                             'arbitrary number of time points, S2 =  SyN with time '
+                             'optimized for 2 time points, GR = greedy SyN, EX = '
+                             'exponential, DD = diffeomorphic demons style exponential '
+                             'mapping, RI = purely rigid, RA = affine rigid')
+
+class AntsIntroductionOutputSpec(TraitedSpec):
+    affine_transformation = File(exists=True, desc='affine (prefix_Affine.txt)')
+    warp_field = File(exists=True, desc='warp field (prefix_Warp.nii)')
+    inverse_warp_field = File(exists=True, desc='inverse warp field (prefix_InverseWarp.nii)')
+    input_file = File(exists=True, desc='input image (prefix_repaired.nii)')
+    output_file = File(exists=True, desc='output image (prefix_deformed.nii)')
+
+class GenWarpFields(ANTSCommand):
+    """Uses ANTS to generate matrices to warp data from one space to another.
+
+    Examples
+    --------
+
+    >>> from nipype.interfaces.ants import GenWarpFields
+    >>> warp = GenWarpFields()
+    >>> warp.inputs.reference_image = 'template.nii'
+    >>> warp.inputs.input_image = 'brain.nii'
+    >>> warp.inputs.max_iterations = [30,90,20]
+    >>> warp.cmdline
+    'antsIntroduction -d 3 -i brain.nii -m 30x90x20 -o ants_ -r template.nii'
+
+    """
+
+    _cmd = 'antsIntroduction.sh'
+    input_spec = AntsIntroductionInputSpec
+    output_spec = AntsIntroductionOutputSpec
+
+    def _list_outputs(self):
+        outputs = self._outputs().get()
+
+        outputs['affine_transformation'] = os.path.join(os.getcwd(),self.inputs.out_prefix+'Affine.txt')
+        outputs['warp_field'] = os.path.join(os.getcwd(),self.inputs.out_prefix+'Warp.nii.gz')
+        outputs['inverse_warp_field'] = os.path.join(os.getcwd(),self.inputs.out_prefix+'InverseWarp.nii.gz')
+        outputs['input_file'] = os.path.join(os.getcwd(),self.inputs.out_prefix+'repaired.nii.gz')
+        outputs['output_file'] = os.path.join(os.getcwd(),self.inputs.out_prefix+'deformed.nii.gz')
+
+        return outputs    
+
+

nipype/interfaces/ants/setup.py

@@ -0,0 +1,14 @@
+# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
+# vi: set ft=python sts=4 ts=4 sw=4 et:
+def configuration(parent_package='',top_path=None):
+    from numpy.distutils.misc_util import Configuration
+
+    config = Configuration('ants', parent_package, top_path)
+
+    config.add_data_dir('tests')
+
+    return config
+
+if __name__ == '__main__':
+    from numpy.distutils.core import setup
+    setup(**configuration(top_path='').todict())