.. AUTO-GENERATED FILE -- DO NOT EDIT!

interfaces.ants.resampling
==========================


.. _nipype.interfaces.ants.resampling.ApplyTransforms:


.. index:: ApplyTransforms

ApplyTransforms
---------------

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/ants/resampling.py#L371>`__

Wraps the executable command ``antsApplyTransforms``.

ApplyTransforms, applied to an input image, transforms it according to a
reference image and a transform (or a set of transforms).

Examples
~~~~~~~~

>>> from nipype.interfaces.ants import ApplyTransforms
>>> at = ApplyTransforms()
>>> at.inputs.input_image = 'moving1.nii'
>>> at.inputs.reference_image = 'fixed1.nii'
>>> at.inputs.transforms = 'identity'
>>> at.cmdline
'antsApplyTransforms --default-value 0 --float 0 --input moving1.nii --interpolation Linear --output moving1_trans.nii --reference-image fixed1.nii -t identity'

>>> at = ApplyTransforms()
>>> at.inputs.dimension = 3
>>> at.inputs.input_image = 'moving1.nii'
>>> at.inputs.reference_image = 'fixed1.nii'
>>> at.inputs.output_image = 'deformed_moving1.nii'
>>> at.inputs.interpolation = 'Linear'
>>> at.inputs.default_value = 0
>>> at.inputs.transforms = ['ants_Warp.nii.gz', 'trans.mat']
>>> at.inputs.invert_transform_flags = [False, False]
>>> at.cmdline
'antsApplyTransforms --default-value 0 --dimensionality 3 --float 0 --input moving1.nii --interpolation Linear --output deformed_moving1.nii --reference-image fixed1.nii --transform [ ants_Warp.nii.gz, 0 ] --transform [ trans.mat, 0 ]'

>>> at1 = ApplyTransforms()
>>> at1.inputs.dimension = 3
>>> at1.inputs.input_image = 'moving1.nii'
>>> at1.inputs.reference_image = 'fixed1.nii'
>>> at1.inputs.output_image = 'deformed_moving1.nii'
>>> at1.inputs.interpolation = 'BSpline'
>>> at1.inputs.interpolation_parameters = (5,)
>>> at1.inputs.default_value = 0
>>> at1.inputs.transforms = ['ants_Warp.nii.gz', 'trans.mat']
>>> at1.inputs.invert_transform_flags = [False, False]
>>> at1.cmdline
'antsApplyTransforms --default-value 0 --dimensionality 3 --float 0 --input moving1.nii --interpolation BSpline[ 5 ] --output deformed_moving1.nii --reference-image fixed1.nii --transform [ ants_Warp.nii.gz, 0 ] --transform [ trans.mat, 0 ]'

Inputs::

        [Mandatory]
        input_image: (an existing file name)
                image to apply transformation to (generally a coregistered
                functional)
                argument: ``--input %s``
        transforms: (a list of items which are an existing file name or
                  u'identity')
                transform files: will be applied in reverse order. For example, the
                last specified transform will be applied first.
                argument: ``%s``
        reference_image: (an existing file name)
                reference image space that you wish to warp INTO
                argument: ``--reference-image %s``

        [Optional]
        default_value: (a float, nipype default value: 0.0)
                argument: ``--default-value %g``
        num_threads: (an integer (int or long), nipype default value: 1)
                Number of ITK threads to use
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        output_image: (a unicode string)
                output file name
                argument: ``--output %s``
        out_postfix: (a unicode string, nipype default value: _trans)
                Postfix that is appended to all output files (default = _trans)
        interpolation_parameters: (a tuple of the form: (an integer (int or
                  long)) or a tuple of the form: (a float, a float))
        float: (a boolean, nipype default value: False)
                Use float instead of double for computations.
                argument: ``--float %d``
        print_out_composite_warp_file: (a boolean)
                output a composite warp file instead of a transformed image
                requires: output_image
        input_image_type: (0 or 1 or 2 or 3)
                Option specifying the input image type of scalar (default), vector,
                tensor, or time series.
                argument: ``--input-image-type %d``
        environ: (a dictionary with keys which are a newbytes or None or a
                  newstr or None and with values which are a newbytes or None or a
                  newstr or None, nipype default value: {})
                Environment variables
        interpolation: (u'Linear' or u'NearestNeighbor' or
                  u'CosineWindowedSinc' or u'WelchWindowedSinc' or
                  u'HammingWindowedSinc' or u'LanczosWindowedSinc' or u'MultiLabel'
                  or u'Gaussian' or u'BSpline', nipype default value: Linear)
                argument: ``%s``
        dimension: (2 or 3 or 4)
                This option forces the image to be treated as a specified-
                dimensional image. If not specified, antsWarp tries to infer the
                dimensionality from the input image.
                argument: ``--dimensionality %d``
        invert_transform_flags: (a list of items which are a boolean)

Outputs::

        output_image: (an existing file name)
                Warped image

.. _nipype.interfaces.ants.resampling.ApplyTransformsToPoints:


.. index:: ApplyTransformsToPoints

ApplyTransformsToPoints
-----------------------

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/ants/resampling.py#L527>`__

Wraps the executable command ``antsApplyTransformsToPoints``.

ApplyTransformsToPoints, applied to an CSV file, transforms coordinates
using provided transform (or a set of transforms).

Examples
~~~~~~~~

>>> from nipype.interfaces.ants import ApplyTransforms
>>> at = ApplyTransformsToPoints()
>>> at.inputs.dimension = 3
>>> at.inputs.input_file = 'moving.csv'
>>> at.inputs.transforms = ['trans.mat', 'ants_Warp.nii.gz']
>>> at.inputs.invert_transform_flags = [False, False]
>>> at.cmdline
'antsApplyTransformsToPoints --dimensionality 3 --input moving.csv --output moving_transformed.csv --transform [ trans.mat, 0 ] --transform [ ants_Warp.nii.gz, 0 ]'

Inputs::

        [Mandatory]
        transforms: (a list of items which are an existing file name)
                transforms that will be applied to the points
                argument: ``%s``
        input_file: (an existing file name)
                Currently, the only input supported is a csv file with columns
                including x,y (2D), x,y,z (3D) or x,y,z,t,label (4D) column headers.
                The points should be defined in physical space. If in doubt how to
                convert coordinates from your files to the space required by
                antsApplyTransformsToPoints try creating/drawing a simple label
                volume with only one voxel set to 1 and all others set to 0. Write
                down the voxel coordinates. Then use ImageMaths LabelStats to find
                out what coordinates for this voxel antsApplyTransformsToPoints is
                expecting.
                argument: ``--input %s``

        [Optional]
        num_threads: (an integer (int or long), nipype default value: 1)
                Number of ITK threads to use
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        output_file: (a unicode string)
                Name of the output CSV file
                argument: ``--output %s``
        environ: (a dictionary with keys which are a newbytes or None or a
                  newstr or None and with values which are a newbytes or None or a
                  newstr or None, nipype default value: {})
                Environment variables
        dimension: (2 or 3 or 4)
                This option forces the image to be treated as a specified-
                dimensional image. If not specified, antsWarp tries to infer the
                dimensionality from the input image.
                argument: ``--dimensionality %d``
        invert_transform_flags: (a list of items which are a boolean)
                list indicating if a transform should be reversed

Outputs::

        output_file: (an existing file name)
                csv file with transformed coordinates

.. _nipype.interfaces.ants.resampling.WarpImageMultiTransform:


.. index:: WarpImageMultiTransform

WarpImageMultiTransform
-----------------------

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/ants/resampling.py#L216>`__

Wraps the executable command ``WarpImageMultiTransform``.

Warps an image from one space to another

Examples
~~~~~~~~

>>> from nipype.interfaces.ants import WarpImageMultiTransform
>>> wimt = WarpImageMultiTransform()
>>> wimt.inputs.input_image = 'structural.nii'
>>> wimt.inputs.reference_image = 'ants_deformed.nii.gz'
>>> wimt.inputs.transformation_series = ['ants_Warp.nii.gz','ants_Affine.txt']
>>> wimt.cmdline
'WarpImageMultiTransform 3 structural.nii structural_wimt.nii -R ants_deformed.nii.gz ants_Warp.nii.gz ants_Affine.txt'

>>> wimt = WarpImageMultiTransform()
>>> wimt.inputs.input_image = 'diffusion_weighted.nii'
>>> wimt.inputs.reference_image = 'functional.nii'
>>> wimt.inputs.transformation_series = ['func2anat_coreg_Affine.txt','func2anat_InverseWarp.nii.gz',     'dwi2anat_Warp.nii.gz','dwi2anat_coreg_Affine.txt']
>>> wimt.inputs.invert_affine = [1]  # this will invert the 1st Affine file: 'func2anat_coreg_Affine.txt'
>>> wimt.cmdline
'WarpImageMultiTransform 3 diffusion_weighted.nii diffusion_weighted_wimt.nii -R functional.nii -i func2anat_coreg_Affine.txt func2anat_InverseWarp.nii.gz dwi2anat_Warp.nii.gz dwi2anat_coreg_Affine.txt'

Inputs::

        [Mandatory]
        input_image: (a file name)
                image to apply transformation to (generally a coregistered
                functional)
                argument: ``%s``, position: 2
        transformation_series: (a list of items which are an existing file
                  name)
                transformation file(s) to be applied
                argument: ``%s``, position: -1

        [Optional]
        num_threads: (an integer (int or long), nipype default value: 1)
                Number of ITK threads to use
        invert_affine: (a list of items which are an integer (int or long))
                List of Affine transformations to invert.E.g.: [1,4,5] inverts the
                1st, 4th, and 5th Affines found in transformation_series. Note that
                indexing starts with 1 and does not include warp fields. Affine
                transformations are distinguished from warp fields by the word
                "affine" included in their filenames.
        output_image: (a file name)
                name of the output warped image
                argument: ``%s``, position: 3
                mutually_exclusive: out_postfix
        tightest_box: (a boolean)
                computes tightest bounding box (overrided by reference_image if
                given)
                argument: ``--tightest-bounding-box``
                mutually_exclusive: reference_image
        out_postfix: (a file name, nipype default value: _wimt)
                Postfix that is prepended to all output files (default = _wimt)
                mutually_exclusive: output_image
        use_nearest: (a boolean)
                Use nearest neighbor interpolation
                argument: ``--use-NN``
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        dimension: (3 or 2, nipype default value: 3)
                image dimension (2 or 3)
                argument: ``%d``, position: 1
        environ: (a dictionary with keys which are a newbytes or None or a
                  newstr or None and with values which are a newbytes or None or a
                  newstr or None, nipype default value: {})
                Environment variables
        reference_image: (a file name)
                reference image space that you wish to warp INTO
                argument: ``-R %s``
                mutually_exclusive: tightest_box
        use_bspline: (a boolean)
                Use 3rd order B-Spline interpolation
                argument: ``--use-BSpline``
        reslice_by_header: (a boolean)
                Uses orientation matrix and origin encoded in reference image file
                header. Not typically used with additional transforms
                argument: ``--reslice-by-header``

Outputs::

        output_image: (an existing file name)
                Warped image

.. _nipype.interfaces.ants.resampling.WarpTimeSeriesImageMultiTransform:


.. index:: WarpTimeSeriesImageMultiTransform

WarpTimeSeriesImageMultiTransform
---------------------------------

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/ants/resampling.py#L74>`__

Wraps the executable command ``WarpTimeSeriesImageMultiTransform``.

Warps a time-series from one space to another

Examples
~~~~~~~~

>>> from nipype.interfaces.ants import WarpTimeSeriesImageMultiTransform
>>> wtsimt = WarpTimeSeriesImageMultiTransform()
>>> wtsimt.inputs.input_image = 'resting.nii'
>>> wtsimt.inputs.reference_image = 'ants_deformed.nii.gz'
>>> wtsimt.inputs.transformation_series = ['ants_Warp.nii.gz','ants_Affine.txt']
>>> wtsimt.cmdline
'WarpTimeSeriesImageMultiTransform 4 resting.nii resting_wtsimt.nii -R ants_deformed.nii.gz ants_Warp.nii.gz ants_Affine.txt'

>>> wtsimt = WarpTimeSeriesImageMultiTransform()
>>> wtsimt.inputs.input_image = 'resting.nii'
>>> wtsimt.inputs.reference_image = 'ants_deformed.nii.gz'
>>> wtsimt.inputs.transformation_series = ['ants_Warp.nii.gz','ants_Affine.txt']
>>> wtsimt.inputs.invert_affine = [1] # # this will invert the 1st Affine file: ants_Affine.txt
>>> wtsimt.cmdline
'WarpTimeSeriesImageMultiTransform 4 resting.nii resting_wtsimt.nii -R ants_deformed.nii.gz ants_Warp.nii.gz -i ants_Affine.txt'

Inputs::

        [Mandatory]
        input_image: (a file name)
                image to apply transformation to (generally a coregistered
                functional)
                argument: ``%s``
        transformation_series: (a list of items which are an existing file
                  name)
                transformation file(s) to be applied
                argument: ``%s``

        [Optional]
        out_postfix: (a unicode string, nipype default value: _wtsimt)
                Postfix that is prepended to all output files (default = _wtsimt)
                argument: ``%s``
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        tightest_box: (a boolean)
                computes tightest bounding box (overrided by reference_image if
                given)
                argument: ``--tightest-bounding-box``
                mutually_exclusive: reference_image
        reslice_by_header: (a boolean)
                Uses orientation matrix and origin encoded in reference image file
                header. Not typically used with additional transforms
                argument: ``--reslice-by-header``
        num_threads: (an integer (int or long), nipype default value: 1)
                Number of ITK threads to use
        use_nearest: (a boolean)
                Use nearest neighbor interpolation
                argument: ``--use-NN``
        invert_affine: (a list of items which are an integer (int or long))
                List of Affine transformations to invert.E.g.: [1,4,5] inverts the
                1st, 4th, and 5th Affines found in transformation_series. Note that
                indexing starts with 1 and does not include warp fields. Affine
                transformations are distinguished from warp fields by the word
                "affine" included in their filenames.
        environ: (a dictionary with keys which are a newbytes or None or a
                  newstr or None and with values which are a newbytes or None or a
                  newstr or None, nipype default value: {})
                Environment variables
        reference_image: (a file name)
                reference image space that you wish to warp INTO
                argument: ``-R %s``
                mutually_exclusive: tightest_box
        use_bspline: (a boolean)
                Use 3rd order B-Spline interpolation
                argument: ``--use-Bspline``
        dimension: (4 or 3, nipype default value: 4)
                image dimension (3 or 4)
                argument: ``%d``, position: 1

Outputs::

        output_image: (an existing file name)
                Warped image
