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

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


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


.. index:: ApplyTransforms

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

`Link to code <file:///build/nipype-fj7ofr/nipype-1.0.0+git69-gdb2670326/nipype/interfaces/ants/resampling.py#L376>`__

Wraps 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 --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 --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 --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)
                flag: --input %s
        reference_image: (an existing file name)
                reference image space that you wish to warp INTO
                flag: --reference-image %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.
                flag: %s

        [Optional]
        args: (a unicode string)
                Additional parameters to the command
                flag: %s
        default_value: (a float, nipype default value: 0.0)
                flag: --default-value %g
        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.
                flag: --dimensionality %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
        float: (a boolean)
                Use float instead of double for computations.
                flag: --float %d
        ignore_exception: (a boolean, nipype default value: False)
                Print an error message instead of throwing an exception in case the
                interface fails to run
        input_image_type: (0 or 1 or 2 or 3)
                Option specifying the input image type of scalar (default), vector,
                tensor, or time series.
                flag: --input-image-type %d
        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)
                flag: %s
        interpolation_parameters: (a tuple of the form: (an integer (int or
                 long)) or a tuple of the form: (a float, a float))
        invert_transform_flags: (a list of items which are a boolean)
        num_threads: (an integer (int or long), nipype default value: 1)
                Number of ITK threads to use
        out_postfix: (a unicode string, nipype default value: _trans)
                Postfix that is appended to all output files (default = _trans)
        output_image: (a unicode string)
                output file name
                flag: --output %s
        print_out_composite_warp_file: (a boolean)
                output a composite warp file instead of a transformed image
                requires: output_image
        terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
                Control terminal output: `stream` - displays to terminal immediately
                (default), `allatonce` - waits till command is finished to display
                output, `file` - writes output to file, `none` - output is ignored

Outputs::

        output_image: (an existing file name)
                Warped image

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


.. index:: ApplyTransformsToPoints

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

`Link to code <file:///build/nipype-fj7ofr/nipype-1.0.0+git69-gdb2670326/nipype/interfaces/ants/resampling.py#L532>`__

Wraps 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]
        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 spacerequired by
                antsApplyTransformsToPoints try creating/drawing a simplelabel
                volume with only one voxel set to 1 and all others set to 0.Write
                down the voxel coordinates. Then use ImageMaths LabelStats to
                findout what coordinates for this voxel antsApplyTransformsToPoints
                isexpecting.
                flag: --input %s
        transforms: (a list of items which are an existing file name)
                transforms that will be applied to the points
                flag: %s

        [Optional]
        args: (a unicode string)
                Additional parameters to the command
                flag: %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.
                flag: --dimensionality %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
        ignore_exception: (a boolean, nipype default value: False)
                Print an error message instead of throwing an exception in case the
                interface fails to run
        invert_transform_flags: (a list of items which are a boolean)
                list indicating if a transform should be reversed
        num_threads: (an integer (int or long), nipype default value: 1)
                Number of ITK threads to use
        output_file: (a unicode string)
                Name of the output CSV file
                flag: --output %s
        terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
                Control terminal output: `stream` - displays to terminal immediately
                (default), `allatonce` - waits till command is finished to display
                output, `file` - writes output to file, `none` - output is ignored

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-fj7ofr/nipype-1.0.0+git69-gdb2670326/nipype/interfaces/ants/resampling.py#L222>`__

Wraps 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)
                flag: %s, position: 2
        transformation_series: (a list of items which are an existing file
                 name)
                transformation file(s) to be applied
                flag: %s, position: -1

        [Optional]
        args: (a unicode string)
                Additional parameters to the command
                flag: %s
        dimension: (3 or 2, nipype default value: 3)
                image dimension (2 or 3)
                flag: %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
        ignore_exception: (a boolean, nipype default value: False)
                Print an error message instead of throwing an exception in case the
                interface fails to run
        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.
        num_threads: (an integer (int or long), nipype default value: 1)
                Number of ITK threads to use
        out_postfix: (a file name, nipype default value: _wimt)
                Postfix that is prepended to all output files (default = _wimt)
                mutually_exclusive: output_image
        output_image: (a file name)
                name of the output warped image
                flag: %s, position: 3
                mutually_exclusive: out_postfix
        reference_image: (a file name)
                reference image space that you wish to warp INTO
                flag: -R %s
                mutually_exclusive: tightest_box
        reslice_by_header: (a boolean)
                Uses orientation matrix and origin encoded in reference image file
                header. Not typically used with additional transforms
                flag: --reslice-by-header
        terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
                Control terminal output: `stream` - displays to terminal immediately
                (default), `allatonce` - waits till command is finished to display
                output, `file` - writes output to file, `none` - output is ignored
        tightest_box: (a boolean)
                computes tightest bounding box (overrided by reference_image if
                given)
                flag: --tightest-bounding-box
                mutually_exclusive: reference_image
        use_bspline: (a boolean)
                Use 3rd order B-Spline interpolation
                flag: --use-BSpline
        use_nearest: (a boolean)
                Use nearest neighbor interpolation
                flag: --use-NN

Outputs::

        output_image: (an existing file name)
                Warped image

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


.. index:: WarpTimeSeriesImageMultiTransform

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

`Link to code <file:///build/nipype-fj7ofr/nipype-1.0.0+git69-gdb2670326/nipype/interfaces/ants/resampling.py#L80>`__

Wraps 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)
                flag: %s
        transformation_series: (a list of items which are an existing file
                 name)
                transformation file(s) to be applied
                flag: %s

        [Optional]
        args: (a unicode string)
                Additional parameters to the command
                flag: %s
        dimension: (4 or 3, nipype default value: 4)
                image dimension (3 or 4)
                flag: %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
        ignore_exception: (a boolean, nipype default value: False)
                Print an error message instead of throwing an exception in case the
                interface fails to run
        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.
        num_threads: (an integer (int or long), nipype default value: 1)
                Number of ITK threads to use
        out_postfix: (a unicode string, nipype default value: _wtsimt)
                Postfix that is prepended to all output files (default = _wtsimt)
                flag: %s
        reference_image: (a file name)
                reference image space that you wish to warp INTO
                flag: -R %s
                mutually_exclusive: tightest_box
        reslice_by_header: (a boolean)
                Uses orientation matrix and origin encoded in reference image file
                header. Not typically used with additional transforms
                flag: --reslice-by-header
        terminal_output: (u'stream' or u'allatonce' or u'file' or u'none')
                Control terminal output: `stream` - displays to terminal immediately
                (default), `allatonce` - waits till command is finished to display
                output, `file` - writes output to file, `none` - output is ignored
        tightest_box: (a boolean)
                computes tightest bounding box (overrided by reference_image if
                given)
                flag: --tightest-bounding-box
                mutually_exclusive: reference_image
        use_bspline: (a boolean)
                Use 3rd order B-Spline interpolation
                flag: --use-Bspline
        use_nearest: (a boolean)
                Use nearest neighbor interpolation
                flag: --use-NN

Outputs::

        output_image: (an existing file name)
                Warped image
