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Merge pull request #3222 from effigies/restore_ants_legacy
ENH: Restore ants.legacy interfaces
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‎nipype/interfaces/ants/legacy.py

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# -*- coding: utf-8 -*-
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"""ANTS Legacy Interfaces
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These interfaces are for programs that have been deprecated by ANTs, but
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are preserved for backwards compatibility.
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"""
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from builtins import range
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import os
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from glob import glob
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from .base import ANTSCommand, ANTSCommandInputSpec
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from ..base import TraitedSpec, File, traits, isdefined, OutputMultiPath
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from ...utils.filemanip import split_filename
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class antsIntroductionInputSpec(ANTSCommandInputSpec):
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dimension = traits.Enum(
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3,
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2,
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argstr="-d %d",
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usedefault=True,
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desc="image dimension (2 or 3)",
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position=1,
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)
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reference_image = File(
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exists=True,
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argstr="-r %s",
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desc="template file to warp to",
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mandatory=True,
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copyfile=True,
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)
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input_image = File(
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exists=True,
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argstr="-i %s",
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desc="input image to warp to template",
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mandatory=True,
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copyfile=False,
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)
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force_proceed = traits.Bool(
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argstr="-f 1",
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desc=("force script to proceed even if headers " "may be incompatible"),
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)
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inverse_warp_template_labels = traits.Bool(
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argstr="-l",
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desc=(
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"Applies inverse warp to the template labels "
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"to estimate label positions in target space (use "
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"for template-based segmentation)"
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),
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)
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max_iterations = traits.List(
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traits.Int,
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argstr="-m %s",
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sep="x",
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desc=(
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"maximum number of iterations (must be "
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"list of integers in the form [J,K,L...]: "
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"J = coarsest resolution iterations, K = "
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"middle resolution interations, L = fine "
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"resolution iterations"
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),
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)
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bias_field_correction = traits.Bool(
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argstr="-n 1", desc=("Applies bias field correction to moving " "image")
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)
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similarity_metric = traits.Enum(
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"PR",
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"CC",
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"MI",
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"MSQ",
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argstr="-s %s",
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desc=(
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"Type of similartiy metric used for registration "
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"(CC = cross correlation, MI = mutual information, "
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"PR = probability mapping, MSQ = mean square difference)"
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),
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)
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transformation_model = traits.Enum(
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"GR",
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"EL",
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"SY",
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"S2",
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"EX",
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"DD",
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"RI",
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"RA",
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argstr="-t %s",
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usedefault=True,
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desc=(
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"Type of transofmration model used for registration "
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"(EL = elastic transformation model, SY = SyN with time, "
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"arbitrary number of time points, S2 = SyN with time "
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"optimized for 2 time points, GR = greedy SyN, EX = "
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"exponential, DD = diffeomorphic demons style exponential "
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"mapping, RI = purely rigid, RA = affine rigid"
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),
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)
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out_prefix = traits.Str(
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"ants_",
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argstr="-o %s",
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usedefault=True,
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desc=("Prefix that is prepended to all output " "files (default = ants_)"),
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)
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quality_check = traits.Bool(
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argstr="-q 1", desc="Perform a quality check of the result"
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)
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class antsIntroductionOutputSpec(TraitedSpec):
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affine_transformation = File(exists=True, desc="affine (prefix_Affine.txt)")
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warp_field = File(exists=True, desc="warp field (prefix_Warp.nii)")
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inverse_warp_field = File(
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exists=True, desc="inverse warp field (prefix_InverseWarp.nii)"
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)
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input_file = File(exists=True, desc="input image (prefix_repaired.nii)")
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output_file = File(exists=True, desc="output image (prefix_deformed.nii)")
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class antsIntroduction(ANTSCommand):
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"""Uses ANTS to generate matrices to warp data from one space to another.
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Examples
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--------
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>>> from nipype.interfaces.ants.legacy import antsIntroduction
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>>> warp = antsIntroduction()
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>>> warp.inputs.reference_image = 'Template_6.nii'
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>>> warp.inputs.input_image = 'structural.nii'
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>>> warp.inputs.max_iterations = [30,90,20]
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>>> warp.cmdline
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'antsIntroduction.sh -d 3 -i structural.nii -m 30x90x20 -o ants_ -r Template_6.nii -t GR'
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"""
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_cmd = "antsIntroduction.sh"
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input_spec = antsIntroductionInputSpec
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output_spec = antsIntroductionOutputSpec
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def _list_outputs(self):
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outputs = self._outputs().get()
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transmodel = self.inputs.transformation_model
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# When transform is set as 'RI'/'RA', wrap fields should not be expected
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# The default transformation is GR, which outputs the wrap fields
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if not isdefined(transmodel) or (
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isdefined(transmodel) and transmodel not in ["RI", "RA"]
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):
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outputs["warp_field"] = os.path.join(
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os.getcwd(), self.inputs.out_prefix + "Warp.nii.gz"
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)
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outputs["inverse_warp_field"] = os.path.join(
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os.getcwd(), self.inputs.out_prefix + "InverseWarp.nii.gz"
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)
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outputs["affine_transformation"] = os.path.join(
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os.getcwd(), self.inputs.out_prefix + "Affine.txt"
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)
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outputs["input_file"] = os.path.join(
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os.getcwd(), self.inputs.out_prefix + "repaired.nii.gz"
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)
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outputs["output_file"] = os.path.join(
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os.getcwd(), self.inputs.out_prefix + "deformed.nii.gz"
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)
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return outputs
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# How do we make a pass through so that GenWarpFields is just an alias for antsIntroduction ?
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class GenWarpFields(antsIntroduction):
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pass
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class buildtemplateparallelInputSpec(ANTSCommandInputSpec):
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dimension = traits.Enum(
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3,
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2,
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4,
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argstr="-d %d",
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usedefault=True,
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desc="image dimension (2, 3 or 4)",
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position=1,
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)
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out_prefix = traits.Str(
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"antsTMPL_",
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argstr="-o %s",
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usedefault=True,
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desc=("Prefix that is prepended to all output " "files (default = antsTMPL_)"),
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)
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in_files = traits.List(
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File(exists=True),
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mandatory=True,
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desc="list of images to generate template from",
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argstr="%s",
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position=-1,
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)
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parallelization = traits.Enum(
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0,
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1,
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2,
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argstr="-c %d",
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usedefault=True,
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desc=(
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"control for parallel processing (0 = "
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"serial, 1 = use PBS, 2 = use PEXEC, 3 = "
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"use Apple XGrid"
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),
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)
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gradient_step_size = traits.Float(
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argstr="-g %f",
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desc=("smaller magnitude results in " "more cautious steps (default = " ".25)"),
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)
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iteration_limit = traits.Int(
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4, argstr="-i %d", usedefault=True, desc="iterations of template construction"
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)
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num_cores = traits.Int(
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argstr="-j %d",
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requires=["parallelization"],
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desc=(
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"Requires parallelization = 2 (PEXEC). " "Sets number of cpu cores to use"
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),
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)
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max_iterations = traits.List(
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traits.Int,
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argstr="-m %s",
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sep="x",
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desc=(
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"maximum number of iterations (must be "
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"list of integers in the form [J,K,L...]: "
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"J = coarsest resolution iterations, K = "
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"middle resolution interations, L = fine "
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"resolution iterations"
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),
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)
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bias_field_correction = traits.Bool(
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argstr="-n 1", desc=("Applies bias field correction to moving " "image")
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)
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rigid_body_registration = traits.Bool(
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argstr="-r 1",
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desc=(
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"registers inputs before creating template "
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"(useful if no initial template available)"
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),
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)
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similarity_metric = traits.Enum(
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"PR",
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"CC",
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"MI",
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"MSQ",
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argstr="-s %s",
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desc=(
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"Type of similartiy metric used for registration "
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"(CC = cross correlation, MI = mutual information, "
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"PR = probability mapping, MSQ = mean square difference)"
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),
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)
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transformation_model = traits.Enum(
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"GR",
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"EL",
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"SY",
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"S2",
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"EX",
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"DD",
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argstr="-t %s",
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usedefault=True,
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desc=(
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"Type of transofmration model used for registration "
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"(EL = elastic transformation model, SY = SyN with time, "
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"arbitrary number of time points, S2 = SyN with time "
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"optimized for 2 time points, GR = greedy SyN, EX = "
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"exponential, DD = diffeomorphic demons style exponential "
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"mapping"
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),
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)
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use_first_as_target = traits.Bool(
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desc=(
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"uses first volume as target of "
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"all inputs. When not used, an "
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"unbiased average image is used "
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"to start."
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)
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)
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class buildtemplateparallelOutputSpec(TraitedSpec):
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final_template_file = File(exists=True, desc="final ANTS template")
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template_files = OutputMultiPath(
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File(exists=True), desc="Templates from different stages of iteration"
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)
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subject_outfiles = OutputMultiPath(
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File(exists=True),
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desc=(
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"Outputs for each input image. Includes warp "
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"field, inverse warp, Affine, original image "
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"(repaired) and warped image (deformed)"
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),
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)
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class buildtemplateparallel(ANTSCommand):
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"""Generate a optimal average template
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.. warning::
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This can take a VERY long time to complete
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Examples
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--------
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>>> from nipype.interfaces.ants.legacy import buildtemplateparallel
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>>> tmpl = buildtemplateparallel()
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>>> tmpl.inputs.in_files = ['T1.nii', 'structural.nii']
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>>> tmpl.inputs.max_iterations = [30, 90, 20]
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>>> tmpl.cmdline
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'buildtemplateparallel.sh -d 3 -i 4 -m 30x90x20 -o antsTMPL_ -c 0 -t GR T1.nii structural.nii'
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"""
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_cmd = "buildtemplateparallel.sh"
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input_spec = buildtemplateparallelInputSpec
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output_spec = buildtemplateparallelOutputSpec
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def _format_arg(self, opt, spec, val):
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if opt == "num_cores":
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if self.inputs.parallelization == 2:
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return "-j " + str(val)
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else:
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return ""
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if opt == "in_files":
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if self.inputs.use_first_as_target:
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start = "-z "
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else:
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start = ""
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return start + " ".join(name for name in val)
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return super(buildtemplateparallel, self)._format_arg(opt, spec, val)
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def _list_outputs(self):
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outputs = self._outputs().get()
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outputs["template_files"] = []
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for i in range(len(glob(os.path.realpath("*iteration*")))):
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temp = os.path.realpath(
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"%s_iteration_%d/%stemplate.nii.gz"
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% (self.inputs.transformation_model, i, self.inputs.out_prefix)
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)
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os.rename(
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temp,
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os.path.realpath(
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"%s_iteration_%d/%stemplate_i%d.nii.gz"
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% (self.inputs.transformation_model, i, self.inputs.out_prefix, i)
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),
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)
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file_ = "%s_iteration_%d/%stemplate_i%d.nii.gz" % (
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self.inputs.transformation_model,
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i,
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self.inputs.out_prefix,
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i,
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)
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outputs["template_files"].append(os.path.realpath(file_))
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outputs["final_template_file"] = os.path.realpath(
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"%stemplate.nii.gz" % self.inputs.out_prefix
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)
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outputs["subject_outfiles"] = []
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for filename in self.inputs.in_files:
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_, base, _ = split_filename(filename)
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temp = glob(os.path.realpath("%s%s*" % (self.inputs.out_prefix, base)))
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for file_ in temp:
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outputs["subject_outfiles"].append(file_)
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return outputs

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