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

nipype.interfaces.fsl.preprocess
================================


:class:`ApplyWarp`
------------------


Wraps command **applywarp**

Use FSL's applywarp to apply the results of a FNIRT registration

Examples
~~~~~~~~
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
>>> aw = fsl.ApplyWarp()
>>> aw.inputs.in_file = example_data('structural.nii')
>>> aw.inputs.ref_file = example_data('mni.nii')
>>> aw.inputs.field_file = 'my_coefficients_filed.nii' #doctest: +SKIP
>>> res = aw.run() #doctest: +SKIP

Inputs:: 

	[Mandatory]
	field_file : (an existing file name)
		file containing warp field
	in_file : (an existing file name)
		image to be warped
	ref_file : (an existing file name)
		reference image

	[Optional]
	abswarp : (a boolean)
		treat warp field as absolute: x' = w(x)
		exclusive: relwarp
	args : (a string)
		Additional parameters to the command
	datatype : ('char' or 'short' or 'int' or 'float' or 'double')
		Force output data type [char short int float double].
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	interp : ('nn' or 'trilinear' or 'sinc' or 'spline')
		interpolation method
	mask_file : (an existing file name)
		filename for mask image (in reference space)
	out_file : (a file name)
		output filename
	output_type : ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
		FSL output type
	postmat : (an existing file name)
		filename for post-transform (affine matrix)
	premat : (an existing file name)
		filename for pre-transform (affine matrix)
	relwarp : (a boolean)
		treat warp field as relative: x' = x + w(x)
		exclusive: abswarp
	superlevel : ('a' or an integer)
		level of intermediary supersampling, a for 'automatic' or integer level. Default = 2
	supersample : (a boolean)
		intermediary supersampling of output, default is off


Outputs:: 

	out_file : (an existing file name)
		Warped output file

:class:`ApplyXfm`
-----------------


Wraps command **flirt**

Currently just a light wrapper around FLIRT,
with no modifications

ApplyXfm is used to apply an existing tranform to an image


Examples
~~~~~~~~

>>> import nipype.interfaces.fsl as fsl
>>> from nipype.testing import example_data
>>> applyxfm = fsl.ApplyXfm()
>>> applyxfm.inputs.in_file = example_data('structural.nii')
>>> applyxfm.inputs.in_matrix_file = example_data('trans.mat')
>>> applyxfm.inputs.out_file = 'newfile.nii'
>>> applyxfm.inputs.reference = example_data('mni.nii')
>>> applyxfm.inputs.apply_xfm = True
>>> result = applyxfm.run() # doctest: +SKIP

Inputs:: 

	[Mandatory]
	in_file : (an existing file name)
		input file
	reference : (an existing file name)
		reference file

	[Optional]
	angle_rep : ('quaternion' or 'euler')
		representation of rotation angles
	apply_xfm : (a boolean)
		apply transformation supplied by in_matrix_file
		requires: in_matrix_file
	args : (a string)
		Additional parameters to the command
	bins : (an integer)
		number of histogram bins
	coarse_search : (an integer)
		coarse search delta angle
	cost : ('mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or 'leastsq' or 'labeldiff')
		cost function
	cost_func : ('mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or 'leastsq' or 'labeldiff')
		cost function
	datatype : ('char' or 'short' or 'int' or 'float' or 'double')
		force output data type
	display_init : (a boolean)
		display initial matrix
	dof : (an integer)
		number of transform degrees of freedom
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	fine_search : (an integer)
		fine search delta angle
	force_scaling : (a boolean)
		force rescaling even for low-res images
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	in_matrix_file : (a file name)
		input 4x4 affine matrix
	in_weight : (an existing file name)
		File for input weighting volume
	interp : ('trilinear' or 'nearestneighbour' or 'sinc')
		final interpolation method used in reslicing
	min_sampling : (a float)
		set minimum voxel dimension for sampling
	no_clamp : (a boolean)
		do not use intensity clamping
	no_resample : (a boolean)
		do not change input sampling
	no_resample_blur : (a boolean)
		do not use blurring on downsampling
	no_search : (a boolean)
		set all angular searches to ranges 0 to 0
	out_file : (a file name)
		registered output file
	out_matrix_file : (a file name)
		output affine matrix in 4x4 asciii format
	output_type : ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
		FSL output type
	padding_size : (an integer)
		for applyxfm: interpolates outside image by size
	ref_weight : (an existing file name)
		File for reference weighting volume
	rigid2D : (a boolean)
		use 2D rigid body mode - ignores dof
	schedule : (an existing file name)
		replaces default schedule
	searchr_x : (a list of from 2 to 2 items which are an integer)
		search angles along x-axis, in degrees
	searchr_y : (a list of from 2 to 2 items which are an integer)
		search angles along y-axis, in degrees
	searchr_z : (a list of from 2 to 2 items which are an integer)
		search angles along z-axis, in degrees
	sinc_width : (an integer)
		full-width in voxels
	sinc_window : ('rectangular' or 'hanning' or 'blackman')
		sinc window
	uses_qform : (a boolean)
		initialize using sform or qform
	verbose : (an integer)
		verbose mode, 0 is least


Outputs:: 

	out_file : (an existing file name)
		path/name of registered file (if generated)
	out_matrix_file : (an existing file name)
		path/name of calculated affine transform (if generated)

:class:`BET`
------------


Wraps command **bet**

Use FSL BET command for skull stripping.

For complete details, see the `BET Documentation.
<http://www.fmrib.ox.ac.uk/fsl/bet2/index.html>`_

Examples
~~~~~~~~
>>> from nipype.interfaces import fsl
>>> from nipype.testing import  example_data
>>> btr = fsl.BET()
>>> btr.inputs.in_file = example_data('structural.nii')
>>> btr.inputs.frac = 0.7
>>> res = btr.run() # doctest: +SKIP

Inputs:: 

	[Mandatory]
	in_file : (an existing file name)
		input file to skull strip

	[Optional]
	args : (a string)
		Additional parameters to the command
	center : (a list of at most 3 items which are an integer)
		center of gravity in voxels
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	frac : (a float)
		fractional intensity threshold
	functional : (a boolean)
		apply to 4D fMRI data
		exclusive: functional,reduce_bias,robust,padding,remove_eyes,surfaces,t2_guided
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	mask : (a boolean)
		create binary mask image
	mesh : (a boolean)
		generate a vtk mesh brain surface
	no_output : (a boolean)
		Don't generate segmented output
	out_file : (a file name)
		name of output skull stripped image
	outline : (a boolean)
		create surface outline image
	output_type : ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
		FSL output type
	padding : (a boolean)
		improve BET if FOV is very small in Z (by temporarily padding end slices)
		exclusive: functional,reduce_bias,robust,padding,remove_eyes,surfaces,t2_guided
	radius : (an integer)
		head radius
	reduce_bias : (a boolean)
		bias field and neck cleanup
		exclusive: functional,reduce_bias,robust,padding,remove_eyes,surfaces,t2_guided
	remove_eyes : (a boolean)
		eye & optic nerve cleanup (can be useful in SIENA)
		exclusive: functional,reduce_bias,robust,padding,remove_eyes,surfaces,t2_guided
	robust : (a boolean)
		robust brain centre estimation (iterates BET several times)
		exclusive: functional,reduce_bias,robust,padding,remove_eyes,surfaces,t2_guided
	skull : (a boolean)
		create skull image
	surfaces : (a boolean)
		run bet2 and then betsurf to get additional skull and scalp surfaces (includes registrations)
		exclusive: functional,reduce_bias,robust,padding,remove_eyes,surfaces,t2_guided
	t2_guided : (a file name)
		as with creating surfaces, when also feeding in non-brain-extracted T2 (includes registrations)
		exclusive: functional,reduce_bias,robust,padding,remove_eyes,surfaces,t2_guided
	threshold : (a boolean)
		apply thresholding to segmented brain image and mask
	vertical_gradient : (a float)
		vertical gradient in fractional intensity threshold (-1, 1)


Outputs:: 

	mask_file : (a file name)
		path/name of binary brain mask (if generated)
	meshfile : (a file name)
		path/name of vtk mesh file (if generated)
	out_file : (a file name)
		path/name of skullstripped file
	outline_file : (a file name)
		path/name of outline file (if generated)

:class:`FAST`
-------------


Wraps command **fast**

Use FSL FAST for segmenting and bias correction.

For complete details, see the `FAST Documentation.
<http://www.fmrib.ox.ac.uk/fsl/fast4/index.html>`_

Examples
~~~~~~~~
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data

Assign options through the ``inputs`` attribute:

>>> fastr = fsl.FAST()
>>> fastr.inputs.in_files = example_data('structural.nii')
>>> out = fastr.run() #doctest: +SKIP

Inputs:: 

	[Mandatory]
	in_files : (an existing file name)
		image, or multi-channel set of images, to be segmented

	[Optional]
	args : (a string)
		Additional parameters to the command
	bias_iters : (1 <= an integer <= 10)
		number of main-loop iterations during bias-field removal
	bias_lowpass : (4 <= an integer <= 40)
		bias field smoothing extent (FWHM) in mm
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	hyper : (0.0 <= a floating point number <= 1.0)
		segmentation spatial smoothness
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	img_type : (1 or 2 or 3)
		int specifying type of image: (1 = T1, 2 = T2, 3 = PD)
	init_seg_smooth : (0.0001 <= a floating point number <= 0.1)
		initial segmentation spatial smoothness (during bias field estimation)
	init_transform : (an existing file name)
		<standard2input.mat> initialise using priors
	iters_afterbias : (an integer >= 1)
		number of main-loop iterations after bias-field removal
	manual_seg : (an existing file name)
		Filename containing intensities
	mixel_smooth : (0.0 <= a floating point number <= 1.0)
		spatial smoothness for mixeltype
	no_bias : (a boolean)
		do not remove bias field
	no_pve : (a boolean)
		turn off PVE (partial volume estimation)
	number_classes : (1 <= an integer <= 10)
		number of tissue-type classes
	other_priors : (a list of from 3 to 3 items which are a file name)
		alternative prior images
	out_basename : (a file name)
		base name of output files
	output_biascorrected : (a boolean)
		output restored image (bias-corrected image)
	output_biasfield : (a boolean)
		output estimated bias field
	output_type : ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
		FSL output type
	probability_maps : (a boolean)
		outputs individual probability maps
	segment_iters : (1 <= an integer <= 50)
		number of segmentation-initialisation iterations
	segments : (a boolean)
		outputs a separate binary image for each tissue type
	use_priors : (a boolean)
		use priors throughout
	verbose : (a boolean)
		switch on diagnostic messages


Outputs:: 

	bias_field : (a file name)
		Unknown
	mixeltype : (a file name)
		path/name of mixeltype volume file _mixeltype
	partial_volume_files : (a file name)
		Unknown
	partial_volume_map : (a file name)
		path/name of partial volume file _pveseg
	probability_maps : (a file name)
		Unknown
	restored_image : (a file name)
		Unknown
	tissue_class_files : (a file name)
		Unknown
	tissue_class_map : (an existing file name)
		path/name of binary segmented volume file one val for each class  _seg

:class:`FLIRT`
--------------


Wraps command **flirt**

Use FSL FLIRT for coregistration.

For complete details, see the `FLIRT Documentation.
<http://www.fmrib.ox.ac.uk/fsl/flirt/index.html>`_

To print out the command line help, use:
    fsl.FLIRT().inputs_help()

Examples
~~~~~~~~
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
>>> flt = fsl.FLIRT(bins=640, cost_func='mutualinfo')
>>> flt.inputs.in_file = example_data('structural.nii')
>>> flt.inputs.reference = example_data('mni.nii')
>>> flt.inputs.out_file = 'moved_subject.nii'
>>> flt.inputs.out_matrix_file = 'subject_to_template.mat'
>>> res = flt.run() #doctest: +SKIP

Inputs:: 

	[Mandatory]
	in_file : (an existing file name)
		input file
	reference : (an existing file name)
		reference file

	[Optional]
	angle_rep : ('quaternion' or 'euler')
		representation of rotation angles
	apply_xfm : (a boolean)
		apply transformation supplied by in_matrix_file
		requires: in_matrix_file
	args : (a string)
		Additional parameters to the command
	bins : (an integer)
		number of histogram bins
	coarse_search : (an integer)
		coarse search delta angle
	cost : ('mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or 'leastsq' or 'labeldiff')
		cost function
	cost_func : ('mutualinfo' or 'corratio' or 'normcorr' or 'normmi' or 'leastsq' or 'labeldiff')
		cost function
	datatype : ('char' or 'short' or 'int' or 'float' or 'double')
		force output data type
	display_init : (a boolean)
		display initial matrix
	dof : (an integer)
		number of transform degrees of freedom
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	fine_search : (an integer)
		fine search delta angle
	force_scaling : (a boolean)
		force rescaling even for low-res images
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	in_matrix_file : (a file name)
		input 4x4 affine matrix
	in_weight : (an existing file name)
		File for input weighting volume
	interp : ('trilinear' or 'nearestneighbour' or 'sinc')
		final interpolation method used in reslicing
	min_sampling : (a float)
		set minimum voxel dimension for sampling
	no_clamp : (a boolean)
		do not use intensity clamping
	no_resample : (a boolean)
		do not change input sampling
	no_resample_blur : (a boolean)
		do not use blurring on downsampling
	no_search : (a boolean)
		set all angular searches to ranges 0 to 0
	out_file : (a file name)
		registered output file
	out_matrix_file : (a file name)
		output affine matrix in 4x4 asciii format
	output_type : ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
		FSL output type
	padding_size : (an integer)
		for applyxfm: interpolates outside image by size
	ref_weight : (an existing file name)
		File for reference weighting volume
	rigid2D : (a boolean)
		use 2D rigid body mode - ignores dof
	schedule : (an existing file name)
		replaces default schedule
	searchr_x : (a list of from 2 to 2 items which are an integer)
		search angles along x-axis, in degrees
	searchr_y : (a list of from 2 to 2 items which are an integer)
		search angles along y-axis, in degrees
	searchr_z : (a list of from 2 to 2 items which are an integer)
		search angles along z-axis, in degrees
	sinc_width : (an integer)
		full-width in voxels
	sinc_window : ('rectangular' or 'hanning' or 'blackman')
		sinc window
	uses_qform : (a boolean)
		initialize using sform or qform
	verbose : (an integer)
		verbose mode, 0 is least


Outputs:: 

	out_file : (an existing file name)
		path/name of registered file (if generated)
	out_matrix_file : (an existing file name)
		path/name of calculated affine transform (if generated)

:class:`FNIRT`
--------------


Wraps command **fnirt**

Use FSL FNIRT for non-linear registration.

Examples
~~~~~~~~
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
>>> fnt = fsl.FNIRT(affine_file=example_data('trans.mat'))
>>> res = fnt.run(ref_file=example_data('mni.nii', in_file=example_data('structural.nii')) #doctest: +SKIP

T1 -> Mni153

>>> from nipype.interfaces import fsl
>>> fnirt_mprage = fsl.FNIRT()
>>> fnirt_mprage.inputs.in_fwhm = [8, 4, 2, 2]
>>> fnirt_mprage.inputs.subsampling_scheme = [4, 2, 1, 1]

Specify the resolution of the warps

>>> fnirt_mprage.inputs.warp_resolution = (6, 6, 6)
>>> res = fnirt_mprage.run(in_file='structural.nii', ref_file='mni.nii', warped_file='warped.nii', fieldcoeff_file='fieldcoeff.nii')#doctest: +SKIP

We can check the command line and confirm that it's what we expect.

>>> fnirt_mprage.cmdline  #doctest: +SKIP
'fnirt --cout=fieldcoeff.nii --in=structural.nii --infwhm=8,4,2,2 --ref=mni.nii --subsamp=4,2,1,1 --warpres=6,6,6 --iout=warped.nii'

Inputs:: 

	[Mandatory]
	in_file : (an existing file name)
		name of input image
	ref_file : (an existing file name)
		name of reference image

	[Optional]
	affine_file : (an existing file name)
		name of file containing affine transform
	apply_inmask : (a list of items which are 0 or 1)
		list of iterations to use input mask on (1 to use, 0 to skip)
		exclusive: skip_inmask
	apply_intensity_mapping : (a list of items which are 0 or 1)
		List of subsampling levels to apply intensity mapping for (0 to skip, 1 to apply)
		exclusive: skip_intensity_mapping
	apply_refmask : (a list of items which are 0 or 1)
		list of iterations to use reference mask on (1 to use, 0 to skip)
		exclusive: skip_refmask
	args : (a string)
		Additional parameters to the command
	bias_regularization_lambda : (a float)
		Weight of regularisation for bias-field, default 10000
	biasfield_resolution : (a tuple of the form: (an integer, an integer, an integer))
		Resolution (in mm) of bias-field modelling local intensities, default 50,50,50
	config_file : (an existing file name)
		Name of config file specifying command line arguments
	derive_from_ref : (a boolean)
		If true, ref image is used to calculate derivatives. Default false
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	field_file : (a boolean or a file name)
		name of output file with field or true
	fieldcoeff_file : (a boolean or a file name)
		name of output file with field coefficients or true
	hessian_precision : ('double' or 'float')
		Precision for representing Hessian, double or float. Default double
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	in_fwhm : (a list of items which are an integer)
		FWHM (in mm) of gaussian smoothing kernel for input volume, default [6,4,2,2]
	in_intensitymap_file : (an existing file name)
		name of file/files containing initial intensity mapingusually generated by previos fnirt run
	inmask_file : (an existing file name)
		name of file with mask in input image space
	inmask_val : (a float)
		Value to mask out in --in image. Default =0.0
	intensity_mapping_model : ('none' or 'global_linear' or 'global_non_linearlocal_linear' or 'global_non_linear_with_bias' or 'local_non_linear')
		Model for intensity-mapping
	intensity_mapping_order : (an integer)
		Order of poynomial for mapping intensities, default 5
	inwarp_file : (an existing file name)
		name of file containing initial non-linear warps
	jacobian_file : (a boolean or a file name)
		name of file for writing out the Jacobianof the field (for diagnostic or VBM purposes)
	jacobian_range : (a tuple of the form: (a float, a float))
		Allowed range of Jacobian determinants, default 0.01,100.0
	log_file : (a file name)
		Name of log-file
	max_nonlin_iter : (a list of items which are an integer)
		Max # of non-linear iterations list, default [5,5,5,5]
	modulatedref_file : (a boolean or a file name)
		name of file for writing out intensity modulated--ref (for diagnostic purposes)
	out_intensitymap_file : (a boolean or a file name)
		name of files for writing information pertaining to intensity mapping
	output_type : ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
		FSL output type
	ref_fwhm : (a list of items which are an integer)
		FWHM (in mm) of gaussian smoothing kernel for ref volume, default [4,2,0,0]
	refmask_file : (an existing file name)
		name of file with mask in reference space
	refmask_val : (a float)
		Value to mask out in --ref image. Default =0.0
	regularization_lambda : (a list of items which are a float)
		Weight of regularisation, default depending on --ssqlambda and --regmod switches. See user documetation.
	regularization_model : ('membrane_energy' or 'bending_energy')
		Model for regularisation of warp-field [membrane_energy bending_energy], default bending_energy
	skip_implicit_in_masking : (a boolean)
		skip implicit masking  based on valuein --in image. Default = 0
	skip_implicit_ref_masking : (a boolean)
		skip implicit masking  based on valuein --ref image. Default = 0
	skip_inmask : (a boolean)
		skip specified inmask if set, default false
		exclusive: apply_inmask
	skip_intensity_mapping : (a boolean)
		Skip estimate intensity-mapping default false
		exclusive: apply_intensity_mapping
	skip_lambda_ssq : (a boolean)
		If true, lambda is not weighted by current ssq, default false
	skip_refmask : (a boolean)
		Skip specified refmask if set, default false
		exclusive: apply_refmask
	spline_order : (an integer)
		Order of spline, 2->Qadratic spline, 3->Cubic spline. Default=3
	subsampling_scheme : (a list of items which are an integer)
		sub-sampling scheme, list, default [4,2,1,1]
	warp_resolution : (a tuple of the form: (an integer, an integer, an integer))
		(approximate) resolution (in mm) of warp basis in x-, y- and z-direction, default 10,10,10
	warped_file : (a file name)
		name of output image


Outputs:: 

	field_file : (a file name)
		file with warp field
	fieldcoeff_file : (an existing file name)
		file with field coefficients
	jacobian_file : (a file name)
		file containing Jacobian of the field
	log_file : (a file name)
		Name of log-file
	modulatedref_file : (a file name)
		file containing intensity modulated --ref
	out_intensitymap_file : (a file name)
		file containing info pertaining to intensity mapping
	warped_file : (an existing file name)
		warped image

:class:`FUGUE`
--------------


Wraps command **fugue**

Use FSL FUGUE to unwarp epi's with fieldmaps

Examples
~~~~~~~~

Please insert examples for use of this command

Inputs:: 

	[Optional]
	args : (a string)
		Additional parameters to the command
	asym_se_time : (a float)
		set the fieldmap asymmetric spin echo time (sec)
	despike_2dfilter : (a boolean)
		apply a 2D de-spiking filter
	despike_theshold : (a float)
		specify the threshold for de-spiking (default=3.0)
	dwell_time : (a float)
		set the EPI dwell time per phase-encode line - same as echo spacing - (sec)
	dwell_to_asym_ratio : (a float)
		set the dwell to asym time ratio
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	fmap_in_file : (an existing file name)
		filename for loading fieldmap (rad/s)
	fmap_out_file : (a file name)
		filename for saving fieldmap (rad/s)
	fourier_order : (an integer)
		apply Fourier (sinusoidal) fitting of order N
	icorr : (a boolean)
		apply intensity correction to unwarping (pixel shift method only)
		requires: shift_in_file
	icorr_only : (a boolean)
		apply intensity correction only
		requires: unwarped_file
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	in_file : (an existing file name)
		filename of input volume
	mask_file : (an existing file name)
		filename for loading valid mask
	median_2dfilter : (a boolean)
		apply 2D median filtering
	no_extend : (a boolean)
		do not apply rigid-body extrapolation to the fieldmap
	no_gap_fill : (a boolean)
		do not apply gap-filling measure to the fieldmap
	nokspace : (a boolean)
		do not use k-space forward warping
	output_type : ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
		FSL output type
	pava : (a boolean)
		apply monotonic enforcement via PAVA
	phase_conjugate : (a boolean)
		apply phase conjugate method of unwarping
	phasemap_file : (an existing file name)
		filename for input phase image
	poly_order : (an integer)
		apply polynomial fitting of order N
	save_unmasked_fmap : (a boolean or a file name)
		saves the unmasked fieldmap when using --savefmap
		requires: fmap_out_file
	save_unmasked_shift : (a boolean or a file name)
		saves the unmasked shiftmap when using --saveshift
		requires: shift_out_file
	shift_in_file : (an existing file name)
		filename for reading pixel shift volume
	shift_out_file : (a file name)
		filename for saving pixel shift volume
	smooth2d : (a float)
		apply 2D Gaussian smoothing of sigma N (in mm)
	smooth3d : (a float)
		apply 3D Gaussian smoothing of sigma N (in mm)
	unwarp_direction : ('x' or 'y' or 'z' or 'x-' or 'y-' or 'z-')
		specifies direction of warping (default y)
	unwarped_file : (a file name)
		apply unwarping and save as filename


Outputs:: 

	unwarped_file : (an existing file name)
		unwarped file

:class:`MCFLIRT`
----------------


Wraps command **mcflirt**

Use FSL MCFLIRT to do within-modality motion correction.

For complete details, see the `MCFLIRT Documentation.
<http://www.fmrib.ox.ac.uk/fsl/mcflirt/index.html>`_

Examples
~~~~~~~~
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
>>> mcflt = fsl.MCFLIRT(in_file=example_data('functional.nii'), cost='mutualinfo')
>>> res = mcflt.run() # doctest: +SKIP

Inputs:: 

	[Mandatory]
	in_file : (an existing file name)
		timeseries to motion-correct

	[Optional]
	args : (a string)
		Additional parameters to the command
	bins : (an integer)
		number of histogram bins
	cost : ('mutualinfo' or 'woods' or 'corratio' or 'normcorr' or 'normmi' or 'leastsquares')
		cost function to optimize
	dof : (an integer)
		degrees of freedom for the transformation
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	init : (an existing file name)
		inital transformation matrix
	interpolation : ('trilinear' or 'nn' or 'sinc')
		interpolation method for transformation
	mean_vol : (a boolean)
		register to mean volume
	out_file : (a file name)
		file to write
	output_type : ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
		FSL output type
	ref_file : (an existing file name)
		target image for motion correction
	ref_vol : (an integer)
		volume to align frames to
	rotation : (an integer)
		scaling factor for rotation tolerances
	save_mats : (a boolean)
		save transformation matrices
	save_plots : (a boolean)
		save transformation parameters
	save_rms : (a boolean)
		save rms displacement parameters
	scaling : (a float)
		scaling factor to use
	smooth : (a float)
		smoothing factor for the cost function
	stages : (an integer)
		stages (if 4, perform final search with sinc interpolation
	stats_imgs : (a boolean)
		produce variance and std. dev. images
	use_contour : (a boolean)
		run search on contour images
	use_gradient : (a boolean)
		run search on gradient images


Outputs:: 

	mat_file : (an existing file name)
		transformation matrices
	mean_img : (an existing file name)
		mean timeseries image
	out_file : (an existing file name)
		motion-corrected timeseries
	par_file : (an existing file name)
		text-file with motion parameters
	rms_files : (an existing file name)
		absolute and relative displacement parameters
	std_img : (an existing file name)
		standard deviation image
	variance_img : (an existing file name)
		variance image

:class:`PRELUDE`
----------------


Wraps command **prelude**

Use FSL prelude to do phase unwrapping

Examples
~~~~~~~~

Please insert examples for use of this command

Inputs:: 

	[Mandatory]
	complex_phase_file : (an existing file name)
		complex phase input volume
		exclusive: magnitude_file,phase_file
	magnitude_file : (an existing file name)
		file containing magnitude image
		exclusive: complex_phase_file
	phase_file : (an existing file name)
		raw phase file
		exclusive: complex_phase_file

	[Optional]
	args : (a string)
		Additional parameters to the command
	end : (an integer)
		final image number to process (default Inf)
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	label_file : (a file name)
		saving the area labels output
	labelprocess2d : (a boolean)
		does label processing in 2D (slice at a time)
	mask_file : (an existing file name)
		filename of mask input volume
	num_partitions : (an integer)
		number of phase partitions to use
	output_type : ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
		FSL output type
	process2d : (a boolean)
		does all processing in 2D (slice at a time)
		exclusive: labelprocess2d
	process3d : (a boolean)
		forces all processing to be full 3D
		exclusive: labelprocess2d,process2d
	rawphase_file : (a file name)
		saving the raw phase output
	removeramps : (a boolean)
		remove phase ramps during unwrapping
	savemask_file : (a file name)
		saving the mask volume
	start : (an integer)
		first image number to process (default 0)
	threshold : (a float)
		intensity threshold for masking
	unwrapped_phase_file : (a file name)
		file containing unwrapepd phase


Outputs:: 

	unwrapped_phase_file : (a file name)
		unwrapped phase file

:class:`SUSAN`
--------------


Wraps command **susan**

use FSL SUSAN to perform smoothing

Examples
~~~~~~~~

>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
>>> print anatfile #doctest: +SKIP
anatomical.nii #doctest: +SKIP
>>> sus = fsl.SUSAN()
>>> sus.inputs.in_file = example_data('structural.nii')
>>> sus.inputs.brightness_threshold = 2000.0
>>> sus.inputs.fwhm = 8.0
>>> result = sus.run() #doctest: +SKIP

Inputs:: 

	[Mandatory]
	brightness_threshold : (a float)
		brightness threshold and should be greater than noise level and less than contrast of edges to be preserved.
	fwhm : (a float)
		fwhm of smoothing, in mm, gets converted using sqrt(8*log(2))
	in_file : (an existing file name)
		filename of input timeseries

	[Optional]
	args : (a string)
		Additional parameters to the command
	dimension : (3 or 2)
		within-plane (2) or fully 3D (3)
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	out_file : (a file name)
		output file name
	output_type : ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
		FSL output type
	usans : (a list of at most 2 items which are a tuple of the form: (an existing file name, a float))
		determines whether the smoothing area (USAN) is to be found from secondary images (0, 1 or 2). A negative value for any brightness threshold will auto-set the threshold at 10% of the robust range
	use_median : (1 or 0)
		whether to use a local median filter in the cases where single-point noise is detected


Outputs:: 

	smoothed_file : (an existing file name)
		smoothed output file

:class:`SliceTimer`
-------------------


Wraps command **slicetimer**

use FSL slicetimer to perform slice timing correction.

Examples
~~~~~~~~
>>> from nipype.interfaces import fsl
>>> from nipype.testing import example_data
>>> st = fsl.SliceTimer()
>>> st.inputs.in_file = example_data('functional.nii')
>>> st.inputs.interleaved = True
>>> result = st.run() #doctest: +SKIP

Inputs:: 

	[Mandatory]
	in_file : (an existing file name)
		filename of input timeseries

	[Optional]
	args : (a string)
		Additional parameters to the command
	custom_order : (an existing file name)
		filename of single-column custom interleave order file (first slice is referred to as 1 not 0)
	custom_timings : (an existing file name)
		slice timings, in fractions of TR, range 0:1 (default is 0.5 = no shift)
	environ : (a dictionary with keys which are a value of type 'str' and with values which are a value of type 'str')
		Environment variables
	global_shift : (a float)
		shift in fraction of TR, range 0:1 (default is 0.5 = no shift)
	ignore_exception : (a boolean)
		Print an error message instead of throwing an exception in case the interface fails to run
	index_dir : (a boolean)
		slice indexing from top to bottom
	interleaved : (a boolean)
		use interleaved acquisition
	out_file : (a file name)
		filename of output timeseries
	output_type : ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
		FSL output type
	slice_direction : (1 or 2 or 3)
		direction of slice acquisition (x=1,y=2,z=3) - default is z
	time_repetition : (a float)
		Specify TR of data - default is 3s


Outputs:: 

	slice_time_corrected_file : (an existing file name)
		slice time corrected file
