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# interfaces.freesurfer.model

## Binarize

Link to code

Wraps command mri_binarize

Use FreeSurfer mri_binarize to threshold an input volume

### Examples

    >>> binvol = Binarize(in_file='structural.nii', min=10, binary_file='foo_out.nii')
    >>> binvol.cmdline
    'mri_binarize --o foo_out.nii --i structural.nii --min 10.000000'

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input volume
            flag: --i %s

    [Optional]
    abs: (a boolean)
            take abs of invol first (ie, make unsigned)
            flag: --abs
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    bin_col_num: (a boolean)
            set binarized voxel value to its column number
            flag: --bincol
    bin_val: (an integer (int or long))
            set vox within thresh to val (default is 1)
            flag: --binval %d
    bin_val_not: (an integer (int or long))
            set vox outside range to val (default is 0)
            flag: --binvalnot %d
    binary_file: (a file name)
            binary output volume
            flag: --o %s
    count_file: (a boolean or a file name)
            save number of hits in ascii file (hits, ntotvox, pct)
            flag: --count %s
    dilate: (an integer (int or long))
            niters: dilate binarization in 3D
            flag: --dilate %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
    erode: (an integer (int or long))
            nerode: erode binarization in 3D (after any dilation)
            flag: --erode  %d
    erode2d: (an integer (int or long))
            nerode2d: erode binarization in 2D (after any 3D erosion)
            flag: --erode2d %d
    frame_no: (an integer (int or long))
            use 0-based frame of input (default is 0)
            flag: --frame %s
    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: (a boolean)
            set binval=0, binvalnot=1
            flag: --inv
    mask_file: (an existing file name)
            must be within mask
            flag: --mask maskvol
    mask_thresh: (a float)
            set thresh for mask
            flag: --mask-thresh %f
    match: (a list of items which are an integer (int or long))
            match instead of threshold
            flag: --match %d...
    max: (a float)
            max thresh
            flag: --max %f
            mutually_exclusive: wm_ven_csf
    merge_file: (an existing file name)
            merge with mergevol
            flag: --merge %s
    min: (a float)
            min thresh
            flag: --min %f
            mutually_exclusive: wm_ven_csf
    out_type: (u'nii' or u'nii.gz' or u'mgz')
            output file type
    rmax: (a float)
            compute max based on rmax*globalmean
            flag: --rmax %f
    rmin: (a float)
            compute min based on rmin*globalmean
            flag: --rmin %f
    subjects_dir: (an existing directory name)
            subjects directory
    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
    ventricles: (a boolean)
            set match vals those for aseg ventricles+choroid (not 4th)
            flag: --ventricles
    wm: (a boolean)
            set match vals to 2 and 41 (aseg for cerebral WM)
            flag: --wm
    wm_ven_csf: (a boolean)
            WM and ventricular CSF, including choroid (not 4th)
            flag: --wm+vcsf
            mutually_exclusive: min, max
    zero_edges: (a boolean)
            zero the edge voxels
            flag: --zero-edges
    zero_slice_edge: (a boolean)
            zero the edge slice voxels
            flag: --zero-slice-edges

Outputs:

    binary_file: (an existing file name)
            binarized output volume
    count_file: (a file name)
            ascii file containing number of hits

## Concatenate

Link to code

Wraps command mri_concat

Use Freesurfer mri_concat to combine several input volumes into one output volume. Can concatenate by frames, or compute a variety of statistics on the input volumes.

### Examples

Combine two input volumes into one volume with two frames

    >>> concat = Concatenate()
    >>> concat.inputs.in_files = ['cont1.nii', 'cont2.nii']
    >>> concat.inputs.concatenated_file = 'bar.nii'
    >>> concat.cmdline
    'mri_concat --o bar.nii --i cont1.nii --i cont2.nii'

Inputs:

    [Mandatory]
    in_files: (a list of items which are an existing file name)
            Individual volumes to be concatenated
            flag: --i %s...

    [Optional]
    add_val: (a float)
            Add some amount to the input volume
            flag: --add %f
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    combine: (a boolean)
            Combine non-zero values into single frame volume
            flag: --combine
    concatenated_file: (a file name)
            Output volume
            flag: --o %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
    gmean: (an integer (int or long))
            create matrix to average Ng groups, Nper=Ntot/Ng
            flag: --gmean %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
    keep_dtype: (a boolean)
            Keep voxelwise precision type (default is float
            flag: --keep-datatype
    mask_file: (an existing file name)
            Mask input with a volume
            flag: --mask %s
    max_bonfcor: (a boolean)
            Compute max and bonferroni correct (assumes -log10(ps))
            flag: --max-bonfcor
    max_index: (a boolean)
            Compute the index of max voxel in concatenated volumes
            flag: --max-index
    mean_div_n: (a boolean)
            compute mean/nframes (good for var)
            flag: --mean-div-n
    multiply_by: (a float)
            Multiply input volume by some amount
            flag: --mul %f
    multiply_matrix_file: (an existing file name)
            Multiply input by an ascii matrix in file
            flag: --mtx %s
    paired_stats: (u'sum' or u'avg' or u'diff' or u'diff-norm' or u'diff-
             norm1' or u'diff-norm2')
            Compute paired sum, avg, or diff
            flag: --paired-%s
    sign: (u'abs' or u'pos' or u'neg')
            Take only pos or neg voxles from input, or take abs
            flag: --%s
    sort: (a boolean)
            Sort each voxel by ascending frame value
            flag: --sort
    stats: (u'sum' or u'var' or u'std' or u'max' or u'min' or u'mean')
            Compute the sum, var, std, max, min or mean of the input volumes
            flag: --%s
    subjects_dir: (an existing directory name)
            subjects directory
    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
    vote: (a boolean)
            Most frequent value at each voxel and fraction of occurances
            flag: --vote

Outputs:

    concatenated_file: (an existing file name)
            Path/name of the output volume

## GLMFit

Link to code

Wraps command mri_glmfit

Use FreeSurfer’s mri_glmfit to specify and estimate a general linear model.

### Examples

    >>> glmfit = GLMFit()
    >>> glmfit.inputs.in_file = 'functional.nii'
    >>> glmfit.inputs.one_sample = True
    >>> glmfit.cmdline == 'mri_glmfit --glmdir %s --y functional.nii --osgm'%os.getcwd()
    True

Inputs:

    [Mandatory]
    in_file: (a file name)
            input 4D file
            flag: --y %s

    [Optional]
    allow_ill_cond: (a boolean)
            allow ill-conditioned design matrices
            flag: --illcond
    allow_repeated_subjects: (a boolean)
            allow subject names to repeat in the fsgd file (must appear before
            --fsgd
            flag: --allowsubjrep
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    calc_AR1: (a boolean)
            compute and save temporal AR1 of residual
            flag: --tar1
    check_opts: (a boolean)
            don't run anything, just check options and exit
            flag: --checkopts
    compute_log_y: (a boolean)
            compute natural log of y prior to analysis
            flag: --logy
    contrast: (a list of items which are an existing file name)
            contrast file
            flag: --C %s...
    cortex: (a boolean)
            use subjects ?h.cortex.label as label
            flag: --cortex
            mutually_exclusive: label_file
    debug: (a boolean)
            turn on debugging
            flag: --debug
    design: (an existing file name)
            design matrix file
            flag: --X %s
            mutually_exclusive: fsgd, design, one_sample
    diag: (an integer (int or long))
            Gdiag_no : set diagnositc level
    diag_cluster: (a boolean)
            save sig volume and exit from first sim loop
            flag: --diag-cluster
    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
    fixed_fx_dof: (an integer (int or long))
            dof for fixed effects analysis
            flag: --ffxdof %d
            mutually_exclusive: fixed_fx_dof_file
    fixed_fx_dof_file: (a file name)
            text file with dof for fixed effects analysis
            flag: --ffxdofdat %d
            mutually_exclusive: fixed_fx_dof
    fixed_fx_var: (an existing file name)
            for fixed effects analysis
            flag: --yffxvar %s
    force_perm: (a boolean)
            force perumtation test, even when design matrix is not orthog
            flag: --perm-force
    fsgd: (a tuple of the form: (an existing file name, u'doss' or
             u'dods'))
            freesurfer descriptor file
            flag: --fsgd %s %s
            mutually_exclusive: fsgd, design, one_sample
    fwhm: (a floating point number >= 0.0)
            smooth input by fwhm
            flag: --fwhm %f
    glm_dir: (a unicode string)
            save outputs to dir
            flag: --glmdir %s
    hemi: (u'lh' or u'rh')
            surface hemisphere
    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_mask: (a boolean)
            invert mask
            flag: --mask-inv
    label_file: (an existing file name)
            use label as mask, surfaces only
            flag: --label %s
            mutually_exclusive: cortex
    mask_file: (an existing file name)
            binary mask
            flag: --mask %s
    no_contrast_ok: (a boolean)
            do not fail if no contrasts specified
            flag: --no-contrasts-ok
    no_est_fwhm: (a boolean)
            turn off FWHM output estimation
            flag: --no-est-fwhm
    no_mask_smooth: (a boolean)
            do not mask when smoothing
            flag: --no-mask-smooth
    no_prune: (a boolean)
            do not prune
            flag: --no-prune
            mutually_exclusive: prunethresh
    one_sample: (a boolean)
            construct X and C as a one-sample group mean
            flag: --osgm
            mutually_exclusive: one_sample, fsgd, design, contrast
    pca: (a boolean)
            perform pca/svd analysis on residual
            flag: --pca
    per_voxel_reg: (a list of items which are an existing file name)
            per-voxel regressors
            flag: --pvr %s...
    profile: (an integer (int or long))
            niters : test speed
            flag: --profile %d
    prune: (a boolean)
            remove voxels that do not have a non-zero value at each frame (def)
            flag: --prune
    prune_thresh: (a float)
            prune threshold. Default is FLT_MIN
            flag: --prune_thr %f
            mutually_exclusive: noprune
    resynth_test: (an integer (int or long))
            test GLM by resynthsis
            flag: --resynthtest %d
    save_cond: (a boolean)
            flag to save design matrix condition at each voxel
            flag: --save-cond
    save_estimate: (a boolean)
            save signal estimate (yhat)
            flag: --yhat-save
    save_res_corr_mtx: (a boolean)
            save residual error spatial correlation matrix (eres.scm). Big!
            flag: --eres-scm
    save_residual: (a boolean)
            save residual error (eres)
            flag: --eres-save
    seed: (an integer (int or long))
            used for synthesizing noise
            flag: --seed %d
    self_reg: (a tuple of the form: (an integer (int or long), an integer
             (int or long), an integer (int or long)))
            self-regressor from index col row slice
            flag: --selfreg %d %d %d
    sim_done_file: (a file name)
            create file when simulation finished
            flag: --sim-done %s
    sim_sign: (u'abs' or u'pos' or u'neg')
            abs, pos, or neg
            flag: --sim-sign %s
    simulation: (a tuple of the form: (u'perm' or u'mc-full' or u'mc-z',
             an integer (int or long), a float, a unicode string))
            nulltype nsim thresh csdbasename
            flag: --sim %s %d %f %s
    subject_id: (a unicode string)
            subject id for surface geometry
    subjects_dir: (an existing directory name)
            subjects directory
    surf: (a boolean)
            analysis is on a surface mesh
            flag: --surf %s %s %s
            requires: subject_id, hemi
    surf_geo: (a unicode string, nipype default value: white)
            surface geometry name (e.g. white, pial)
    synth: (a boolean)
            replace input with gaussian
            flag: --synth
    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
    uniform: (a tuple of the form: (a float, a float))
            use uniform distribution instead of gaussian
            flag: --uniform %f %f
    var_fwhm: (a floating point number >= 0.0)
            smooth variance by fwhm
            flag: --var-fwhm %f
    vox_dump: (a tuple of the form: (an integer (int or long), an integer
             (int or long), an integer (int or long)))
            dump voxel GLM and exit
            flag: --voxdump %d %d %d
    weight_file: (an existing file name)
            weight for each input at each voxel
            mutually_exclusive: weighted_ls
    weight_inv: (a boolean)
            invert weights
            flag: --w-inv
            mutually_exclusive: weighted_ls
    weight_sqrt: (a boolean)
            sqrt of weights
            flag: --w-sqrt
            mutually_exclusive: weighted_ls
    weighted_ls: (an existing file name)
            weighted least squares
            flag: --wls %s
            mutually_exclusive: weight_file, weight_inv, weight_sqrt

Outputs:

    beta_file: (an existing file name)
            map of regression coefficients
    dof_file: (a file name)
            text file with effective degrees-of-freedom for the analysis
    error_file: (a file name)
            map of residual error
    error_stddev_file: (a file name)
            map of residual error standard deviation
    error_var_file: (a file name)
            map of residual error variance
    estimate_file: (a file name)
            map of the estimated Y values
    frame_eigenvectors: (a file name)
            matrix of frame eigenvectors from residual PCA
    ftest_file: (a list of items which are any value)
            map of test statistic values
    fwhm_file: (a file name)
            text file with estimated smoothness
    gamma_file: (a list of items which are any value)
            map of contrast of regression coefficients
    gamma_var_file: (a list of items which are any value)
            map of regression contrast variance
    glm_dir: (an existing directory name)
            output directory
    mask_file: (a file name)
            map of the mask used in the analysis
    sig_file: (a list of items which are any value)
            map of F-test significance (in -log10p)
    singular_values: (a file name)
            matrix singular values from residual PCA
    spatial_eigenvectors: (a file name)
            map of spatial eigenvectors from residual PCA
    svd_stats_file: (a file name)
            text file summarizing the residual PCA

## Label2Annot

Link to code

Wraps command mris_label2annot

Converts a set of surface labels to an annotation file

### Examples

    >>> from nipype.interfaces.freesurfer import Label2Annot
    >>> l2a = Label2Annot()
    >>> l2a.inputs.hemisphere = 'lh'
    >>> l2a.inputs.subject_id = '10335'
    >>> l2a.inputs.in_labels = ['lh.aparc.label']
    >>> l2a.inputs.orig = 'lh.pial'
    >>> l2a.inputs.out_annot = 'test'
    >>> l2a.cmdline
    'mris_label2annot --hemi lh --l lh.aparc.label --a test --s 10335'

Inputs:

    [Mandatory]
    hemisphere: (u'lh' or u'rh')
            Input hemisphere
            flag: --hemi %s
    in_labels: (a list of items which are any value)
            List of input label files
            flag: --l %s...
    orig: (an existing file name)
            implicit {hemisphere}.orig
    out_annot: (a string)
            Name of the annotation to create
            flag: --a %s
    subject_id: (a string, nipype default value: subject_id)
            Subject name/ID
            flag: --s %s

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    color_table: (an existing file name)
            File that defines the structure names, their indices, and their
            color
            flag: --ctab %s
    copy_inputs: (a boolean)
            copy implicit inputs and create a temp subjects_dir
    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
    keep_max: (a boolean)
            Keep label with highest 'stat' value
            flag: --maxstatwinner
    subjects_dir: (an existing directory name)
            subjects directory
    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
    verbose_off: (a boolean)
            Turn off overlap and stat override messages
            flag: --noverbose

Outputs:

    out_file: (an existing file name)
            Output annotation file

## Label2Label

Link to code

Wraps command mri_label2label

Converts a label in one subject’s space to a label in another subject’s space using either talairach or spherical as an intermediate registration space.

If a source mask is used, then the input label must have been created from a surface (ie, the vertex numbers are valid). The format can be anything supported by mri_convert or curv or paint. Vertices in the source label that do not meet threshold in the mask will be removed from the label.

### Examples

    >>> from nipype.interfaces.freesurfer import Label2Label
    >>> l2l = Label2Label()
    >>> l2l.inputs.hemisphere = 'lh'
    >>> l2l.inputs.subject_id = '10335'
    >>> l2l.inputs.sphere_reg = 'lh.pial'
    >>> l2l.inputs.white = 'lh.pial'
    >>> l2l.inputs.source_subject = 'fsaverage'
    >>> l2l.inputs.source_label = 'lh-pial.stl'
    >>> l2l.inputs.source_white = 'lh.pial'
    >>> l2l.inputs.source_sphere_reg = 'lh.pial'
    >>> l2l.cmdline
    'mri_label2label --hemi lh --trglabel lh-pial_converted.stl --regmethod surface --srclabel lh-pial.stl --srcsubject fsaverage --trgsubject 10335'

Inputs:

    [Mandatory]
    hemisphere: (u'lh' or u'rh')
            Input hemisphere
            flag: --hemi %s
    source_label: (an existing file name)
            Source label
            flag: --srclabel %s
    source_sphere_reg: (an existing file name)
            Implicit input <hemisphere>.sphere.reg
    source_subject: (a string)
            Source subject name
            flag: --srcsubject %s
    source_white: (an existing file name)
            Implicit input <hemisphere>.white
    sphere_reg: (an existing file name)
            Implicit input <hemisphere>.sphere.reg
    subject_id: (a string, nipype default value: subject_id)
            Target subject
            flag: --trgsubject %s
    white: (an existing file name)
            Implicit input <hemisphere>.white

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    copy_inputs: (a boolean)
            If running as a node, set this to True.This will copy the input
            files to the node directory.
    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
    out_file: (a file name)
            Target label
            flag: --trglabel %s
    registration_method: (u'surface' or u'volume', nipype default value:
             surface)
            Registration method
            flag: --regmethod %s
    subjects_dir: (an existing directory name)
            subjects directory
    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:

    out_file: (an existing file name)
            Output label

## Label2Vol

Link to code

Wraps command mri_label2vol

Make a binary volume from a Freesurfer label

### Examples

    >>> binvol = Label2Vol(label_file='cortex.label', template_file='structural.nii', reg_file='register.dat', fill_thresh=0.5, vol_label_file='foo_out.nii')
    >>> binvol.cmdline
    'mri_label2vol --fillthresh 0 --label cortex.label --reg register.dat --temp structural.nii --o foo_out.nii'

Inputs:

    [Mandatory]
    annot_file: (an existing file name)
            surface annotation file
            flag: --annot %s
            mutually_exclusive: label_file, annot_file, seg_file, aparc_aseg
            requires: subject_id, hemi
    aparc_aseg: (a boolean)
            use aparc+aseg.mgz in subjectdir as seg
            flag: --aparc+aseg
            mutually_exclusive: label_file, annot_file, seg_file, aparc_aseg
    label_file: (a list of items which are an existing file name)
            list of label files
            flag: --label %s...
            mutually_exclusive: label_file, annot_file, seg_file, aparc_aseg
    seg_file: (an existing file name)
            segmentation file
            flag: --seg %s
            mutually_exclusive: label_file, annot_file, seg_file, aparc_aseg
    template_file: (an existing file name)
            output template volume
            flag: --temp %s

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %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
    fill_thresh: (0.0 <= a floating point number <= 1.0)
            thresh : between 0 and 1
            flag: --fillthresh %.f
    hemi: (u'lh' or u'rh')
            hemisphere to use lh or rh
            flag: --hemi %s
    identity: (a boolean)
            set R=I
            flag: --identity
            mutually_exclusive: reg_file, reg_header, identity
    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_mtx: (a boolean)
            Invert the registration matrix
            flag: --invertmtx
    label_hit_file: (a file name)
            file with each frame is nhits for a label
            flag: --hits %s
    label_voxel_volume: (a float)
            volume of each label point (def 1mm3)
            flag: --labvoxvol %f
    map_label_stat: (a file name)
            map the label stats field into the vol
            flag: --label-stat %s
    native_vox2ras: (a boolean)
            use native vox2ras xform instead of tkregister-style
            flag: --native-vox2ras
    proj: (a tuple of the form: (u'abs' or u'frac', a float, a float, a
             float))
            project along surface normal
            flag: --proj %s %f %f %f
            requires: subject_id, hemi
    reg_file: (an existing file name)
            tkregister style matrix VolXYZ = R*LabelXYZ
            flag: --reg %s
            mutually_exclusive: reg_file, reg_header, identity
    reg_header: (an existing file name)
            label template volume
            flag: --regheader %s
            mutually_exclusive: reg_file, reg_header, identity
    subject_id: (a unicode string)
            subject id
            flag: --subject %s
    subjects_dir: (an existing directory name)
            subjects directory
    surface: (a unicode string)
            use surface instead of white
            flag: --surf %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
    vol_label_file: (a file name)
            output volume
            flag: --o %s

Outputs:

    vol_label_file: (an existing file name)
            output volume

## MRISPreproc

Link to code

Wraps command mris_preproc

Use FreeSurfer mris_preproc to prepare a group of contrasts for a second level analysis

### Examples

    >>> preproc = MRISPreproc()
    >>> preproc.inputs.target = 'fsaverage'
    >>> preproc.inputs.hemi = 'lh'
    >>> preproc.inputs.vol_measure_file = [('cont1.nii', 'register.dat'),                                            ('cont1a.nii', 'register.dat')]
    >>> preproc.inputs.out_file = 'concatenated_file.mgz'
    >>> preproc.cmdline
    'mris_preproc --hemi lh --out concatenated_file.mgz --target fsaverage --iv cont1.nii register.dat --iv cont1a.nii register.dat'

Inputs:

    [Mandatory]
    hemi: (u'lh' or u'rh')
            hemisphere for source and target
            flag: --hemi %s
    target: (a unicode string)
            target subject name
            flag: --target %s

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %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
    fsgd_file: (an existing file name)
            specify subjects using fsgd file
            flag: --fsgd %s
            mutually_exclusive: subjects, fsgd_file, subject_file
    fwhm: (a float)
            smooth by fwhm mm on the target surface
            flag: --fwhm %f
            mutually_exclusive: num_iters
    fwhm_source: (a float)
            smooth by fwhm mm on the source surface
            flag: --fwhm-src %f
            mutually_exclusive: num_iters_source
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    num_iters: (an integer (int or long))
            niters : smooth by niters on the target surface
            flag: --niters %d
            mutually_exclusive: fwhm
    num_iters_source: (an integer (int or long))
            niters : smooth by niters on the source surface
            flag: --niterssrc %d
            mutually_exclusive: fwhm_source
    out_file: (a file name)
            output filename
            flag: --out %s
    proj_frac: (a float)
            projection fraction for vol2surf
            flag: --projfrac %s
    smooth_cortex_only: (a boolean)
            only smooth cortex (ie, exclude medial wall)
            flag: --smooth-cortex-only
    source_format: (a unicode string)
            source format
            flag: --srcfmt %s
    subject_file: (an existing file name)
            file specifying subjects separated by white space
            flag: --f %s
            mutually_exclusive: subjects, fsgd_file, subject_file
    subjects: (a list of items which are any value)
            subjects from who measures are calculated
            flag: --s %s...
            mutually_exclusive: subjects, fsgd_file, subject_file
    subjects_dir: (an existing directory name)
            subjects directory
    surf_area: (a unicode string)
            Extract vertex area from subject/surf/hemi.surfname to use as input.
            flag: --area %s
            mutually_exclusive: surf_measure, surf_measure_file, surf_area
    surf_dir: (a unicode string)
            alternative directory (instead of surf)
            flag: --surfdir %s
    surf_measure: (a unicode string)
            Use subject/surf/hemi.surf_measure as input
            flag: --meas %s
            mutually_exclusive: surf_measure, surf_measure_file, surf_area
    surf_measure_file: (a list of items which are an existing file name)
            file alternative to surfmeas, still requires list of subjects
            flag: --is %s...
            mutually_exclusive: surf_measure, surf_measure_file, surf_area
    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
    vol_measure_file: (a list of items which are a tuple of the form: (an
             existing file name, an existing file name))
            list of volume measure and reg file tuples
            flag: --iv %s %s...

Outputs:

    out_file: (a file name)
            preprocessed output file

## MRISPreprocReconAll

Link to code

Wraps command mris_preproc

Extends MRISPreproc to allow it to be used in a recon-all workflow

### Examples

    >>> preproc = MRISPreprocReconAll()
    >>> preproc.inputs.target = 'fsaverage'
    >>> preproc.inputs.hemi = 'lh'
    >>> preproc.inputs.vol_measure_file = [('cont1.nii', 'register.dat'),                                            ('cont1a.nii', 'register.dat')]
    >>> preproc.inputs.out_file = 'concatenated_file.mgz'
    >>> preproc.cmdline
    'mris_preproc --hemi lh --out concatenated_file.mgz --s subject_id --target fsaverage --iv cont1.nii register.dat --iv cont1a.nii register.dat'

Inputs:

    [Mandatory]
    hemi: (u'lh' or u'rh')
            hemisphere for source and target
            flag: --hemi %s
    target: (a unicode string)
            target subject name
            flag: --target %s

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    copy_inputs: (a boolean)
            If running as a node, set this to True this will copy some implicit
            inputs to the node directory.
    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
    fsgd_file: (an existing file name)
            specify subjects using fsgd file
            flag: --fsgd %s
            mutually_exclusive: subjects, fsgd_file, subject_file
    fwhm: (a float)
            smooth by fwhm mm on the target surface
            flag: --fwhm %f
            mutually_exclusive: num_iters
    fwhm_source: (a float)
            smooth by fwhm mm on the source surface
            flag: --fwhm-src %f
            mutually_exclusive: num_iters_source
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    lh_surfreg_target: (a file name)
            Implicit target surface registration file
            requires: surfreg_files
    num_iters: (an integer (int or long))
            niters : smooth by niters on the target surface
            flag: --niters %d
            mutually_exclusive: fwhm
    num_iters_source: (an integer (int or long))
            niters : smooth by niters on the source surface
            flag: --niterssrc %d
            mutually_exclusive: fwhm_source
    out_file: (a file name)
            output filename
            flag: --out %s
    proj_frac: (a float)
            projection fraction for vol2surf
            flag: --projfrac %s
    rh_surfreg_target: (a file name)
            Implicit target surface registration file
            requires: surfreg_files
    smooth_cortex_only: (a boolean)
            only smooth cortex (ie, exclude medial wall)
            flag: --smooth-cortex-only
    source_format: (a unicode string)
            source format
            flag: --srcfmt %s
    subject_file: (an existing file name)
            file specifying subjects separated by white space
            flag: --f %s
            mutually_exclusive: subjects, fsgd_file, subject_file
    subject_id: (a string, nipype default value: subject_id)
            subject from whom measures are calculated
            flag: --s %s
            mutually_exclusive: subjects, fsgd_file, subject_file, subject_id
    subjects: (a list of items which are any value)
            subjects from who measures are calculated
            flag: --s %s...
            mutually_exclusive: subjects, fsgd_file, subject_file
    subjects_dir: (an existing directory name)
            subjects directory
    surf_area: (a unicode string)
            Extract vertex area from subject/surf/hemi.surfname to use as input.
            flag: --area %s
            mutually_exclusive: surf_measure, surf_measure_file, surf_area
    surf_dir: (a unicode string)
            alternative directory (instead of surf)
            flag: --surfdir %s
    surf_measure: (a unicode string)
            Use subject/surf/hemi.surf_measure as input
            flag: --meas %s
            mutually_exclusive: surf_measure, surf_measure_file, surf_area
    surf_measure_file: (an existing file name)
            file necessary for surfmeas
            flag: --meas %s
            mutually_exclusive: surf_measure, surf_measure_file, surf_area
    surfreg_files: (a list of items which are an existing file name)
            lh and rh input surface registration files
            flag: --surfreg %s
            requires: lh_surfreg_target, rh_surfreg_target
    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
    vol_measure_file: (a list of items which are a tuple of the form: (an
             existing file name, an existing file name))
            list of volume measure and reg file tuples
            flag: --iv %s %s...

Outputs:

    out_file: (a file name)
            preprocessed output file

## MS_LDA

Link to code

Wraps command mri_ms_LDA

Perform LDA reduction on the intensity space of an arbitrary # of FLASH images

### Examples

    >>> grey_label = 2
    >>> white_label = 3
    >>> zero_value = 1
    >>> optimalWeights = MS_LDA(lda_labels=[grey_label, white_label],                                 label_file='label.mgz', weight_file='weights.txt',                                 shift=zero_value, vol_synth_file='synth_out.mgz',                                 conform=True, use_weights=True,                                 images=['FLASH1.mgz', 'FLASH2.mgz', 'FLASH3.mgz'])
    >>> optimalWeights.cmdline
    'mri_ms_LDA -conform -label label.mgz -lda 2 3 -shift 1 -W -synth synth_out.mgz -weight weights.txt FLASH1.mgz FLASH2.mgz FLASH3.mgz'

Inputs:

    [Mandatory]
    images: (a list of items which are an existing file name)
            list of input FLASH images
            flag: %s, position: -1
    lda_labels: (a list of from 2 to 2 items which are an integer (int or
             long))
            pair of class labels to optimize
            flag: -lda %s
    vol_synth_file: (a file name)
            filename for the synthesized output volume
            flag: -synth %s
    weight_file: (a file name)
            filename for the LDA weights (input or output)
            flag: -weight %s

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    conform: (a boolean)
            Conform the input volumes (brain mask typically already conformed)
            flag: -conform
    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
    label_file: (a file name)
            filename of the label volume
            flag: -label %s
    mask_file: (a file name)
            filename of the brain mask volume
            flag: -mask %s
    shift: (an integer (int or long))
            shift all values equal to the given value to zero
            flag: -shift %d
    subjects_dir: (an existing directory name)
            subjects directory
    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
    use_weights: (a boolean)
            Use the weights from a previously generated weight file
            flag: -W

Outputs:

    vol_synth_file: (an existing file name)
    weight_file: (an existing file name)

## OneSampleTTest

Link to code

Wraps command mri_glmfit

Inputs:

    [Mandatory]
    in_file: (a file name)
            input 4D file
            flag: --y %s

    [Optional]
    allow_ill_cond: (a boolean)
            allow ill-conditioned design matrices
            flag: --illcond
    allow_repeated_subjects: (a boolean)
            allow subject names to repeat in the fsgd file (must appear before
            --fsgd
            flag: --allowsubjrep
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    calc_AR1: (a boolean)
            compute and save temporal AR1 of residual
            flag: --tar1
    check_opts: (a boolean)
            don't run anything, just check options and exit
            flag: --checkopts
    compute_log_y: (a boolean)
            compute natural log of y prior to analysis
            flag: --logy
    contrast: (a list of items which are an existing file name)
            contrast file
            flag: --C %s...
    cortex: (a boolean)
            use subjects ?h.cortex.label as label
            flag: --cortex
            mutually_exclusive: label_file
    debug: (a boolean)
            turn on debugging
            flag: --debug
    design: (an existing file name)
            design matrix file
            flag: --X %s
            mutually_exclusive: fsgd, design, one_sample
    diag: (an integer (int or long))
            Gdiag_no : set diagnositc level
    diag_cluster: (a boolean)
            save sig volume and exit from first sim loop
            flag: --diag-cluster
    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
    fixed_fx_dof: (an integer (int or long))
            dof for fixed effects analysis
            flag: --ffxdof %d
            mutually_exclusive: fixed_fx_dof_file
    fixed_fx_dof_file: (a file name)
            text file with dof for fixed effects analysis
            flag: --ffxdofdat %d
            mutually_exclusive: fixed_fx_dof
    fixed_fx_var: (an existing file name)
            for fixed effects analysis
            flag: --yffxvar %s
    force_perm: (a boolean)
            force perumtation test, even when design matrix is not orthog
            flag: --perm-force
    fsgd: (a tuple of the form: (an existing file name, u'doss' or
             u'dods'))
            freesurfer descriptor file
            flag: --fsgd %s %s
            mutually_exclusive: fsgd, design, one_sample
    fwhm: (a floating point number >= 0.0)
            smooth input by fwhm
            flag: --fwhm %f
    glm_dir: (a unicode string)
            save outputs to dir
            flag: --glmdir %s
    hemi: (u'lh' or u'rh')
            surface hemisphere
    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_mask: (a boolean)
            invert mask
            flag: --mask-inv
    label_file: (an existing file name)
            use label as mask, surfaces only
            flag: --label %s
            mutually_exclusive: cortex
    mask_file: (an existing file name)
            binary mask
            flag: --mask %s
    no_contrast_ok: (a boolean)
            do not fail if no contrasts specified
            flag: --no-contrasts-ok
    no_est_fwhm: (a boolean)
            turn off FWHM output estimation
            flag: --no-est-fwhm
    no_mask_smooth: (a boolean)
            do not mask when smoothing
            flag: --no-mask-smooth
    no_prune: (a boolean)
            do not prune
            flag: --no-prune
            mutually_exclusive: prunethresh
    one_sample: (a boolean)
            construct X and C as a one-sample group mean
            flag: --osgm
            mutually_exclusive: one_sample, fsgd, design, contrast
    pca: (a boolean)
            perform pca/svd analysis on residual
            flag: --pca
    per_voxel_reg: (a list of items which are an existing file name)
            per-voxel regressors
            flag: --pvr %s...
    profile: (an integer (int or long))
            niters : test speed
            flag: --profile %d
    prune: (a boolean)
            remove voxels that do not have a non-zero value at each frame (def)
            flag: --prune
    prune_thresh: (a float)
            prune threshold. Default is FLT_MIN
            flag: --prune_thr %f
            mutually_exclusive: noprune
    resynth_test: (an integer (int or long))
            test GLM by resynthsis
            flag: --resynthtest %d
    save_cond: (a boolean)
            flag to save design matrix condition at each voxel
            flag: --save-cond
    save_estimate: (a boolean)
            save signal estimate (yhat)
            flag: --yhat-save
    save_res_corr_mtx: (a boolean)
            save residual error spatial correlation matrix (eres.scm). Big!
            flag: --eres-scm
    save_residual: (a boolean)
            save residual error (eres)
            flag: --eres-save
    seed: (an integer (int or long))
            used for synthesizing noise
            flag: --seed %d
    self_reg: (a tuple of the form: (an integer (int or long), an integer
             (int or long), an integer (int or long)))
            self-regressor from index col row slice
            flag: --selfreg %d %d %d
    sim_done_file: (a file name)
            create file when simulation finished
            flag: --sim-done %s
    sim_sign: (u'abs' or u'pos' or u'neg')
            abs, pos, or neg
            flag: --sim-sign %s
    simulation: (a tuple of the form: (u'perm' or u'mc-full' or u'mc-z',
             an integer (int or long), a float, a unicode string))
            nulltype nsim thresh csdbasename
            flag: --sim %s %d %f %s
    subject_id: (a unicode string)
            subject id for surface geometry
    subjects_dir: (an existing directory name)
            subjects directory
    surf: (a boolean)
            analysis is on a surface mesh
            flag: --surf %s %s %s
            requires: subject_id, hemi
    surf_geo: (a unicode string, nipype default value: white)
            surface geometry name (e.g. white, pial)
    synth: (a boolean)
            replace input with gaussian
            flag: --synth
    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
    uniform: (a tuple of the form: (a float, a float))
            use uniform distribution instead of gaussian
            flag: --uniform %f %f
    var_fwhm: (a floating point number >= 0.0)
            smooth variance by fwhm
            flag: --var-fwhm %f
    vox_dump: (a tuple of the form: (an integer (int or long), an integer
             (int or long), an integer (int or long)))
            dump voxel GLM and exit
            flag: --voxdump %d %d %d
    weight_file: (an existing file name)
            weight for each input at each voxel
            mutually_exclusive: weighted_ls
    weight_inv: (a boolean)
            invert weights
            flag: --w-inv
            mutually_exclusive: weighted_ls
    weight_sqrt: (a boolean)
            sqrt of weights
            flag: --w-sqrt
            mutually_exclusive: weighted_ls
    weighted_ls: (an existing file name)
            weighted least squares
            flag: --wls %s
            mutually_exclusive: weight_file, weight_inv, weight_sqrt

Outputs:

    beta_file: (an existing file name)
            map of regression coefficients
    dof_file: (a file name)
            text file with effective degrees-of-freedom for the analysis
    error_file: (a file name)
            map of residual error
    error_stddev_file: (a file name)
            map of residual error standard deviation
    error_var_file: (a file name)
            map of residual error variance
    estimate_file: (a file name)
            map of the estimated Y values
    frame_eigenvectors: (a file name)
            matrix of frame eigenvectors from residual PCA
    ftest_file: (a list of items which are any value)
            map of test statistic values
    fwhm_file: (a file name)
            text file with estimated smoothness
    gamma_file: (a list of items which are any value)
            map of contrast of regression coefficients
    gamma_var_file: (a list of items which are any value)
            map of regression contrast variance
    glm_dir: (an existing directory name)
            output directory
    mask_file: (a file name)
            map of the mask used in the analysis
    sig_file: (a list of items which are any value)
            map of F-test significance (in -log10p)
    singular_values: (a file name)
            matrix singular values from residual PCA
    spatial_eigenvectors: (a file name)
            map of spatial eigenvectors from residual PCA
    svd_stats_file: (a file name)
            text file summarizing the residual PCA

## SegStats

Link to code

Wraps command mri_segstats

Use FreeSurfer mri_segstats for ROI analysis

### Examples

    >>> import nipype.interfaces.freesurfer as fs
    >>> ss = fs.SegStats()
    >>> ss.inputs.annot = ('PWS04', 'lh', 'aparc')
    >>> ss.inputs.in_file = 'functional.nii'
    >>> ss.inputs.subjects_dir = '.'
    >>> ss.inputs.avgwf_txt_file = 'avgwf.txt'
    >>> ss.inputs.summary_file = 'summary.stats'
    >>> ss.cmdline
    'mri_segstats --annot PWS04 lh aparc --avgwf ./avgwf.txt --i functional.nii --sum ./summary.stats'

Inputs:

    [Mandatory]
    annot: (a tuple of the form: (a unicode string, u'lh' or u'rh', a
             unicode string))
            subject hemi parc : use surface parcellation
            flag: --annot %s %s %s
            mutually_exclusive: segmentation_file, annot, surf_label
    segmentation_file: (an existing file name)
            segmentation volume path
            flag: --seg %s
            mutually_exclusive: segmentation_file, annot, surf_label
    surf_label: (a tuple of the form: (a unicode string, u'lh' or u'rh',
             a unicode string))
            subject hemi label : use surface label
            flag: --slabel %s %s %s
            mutually_exclusive: segmentation_file, annot, surf_label

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    avgwf_file: (a boolean or a file name)
            Save as binary volume (bool or filename)
            flag: --avgwfvol %s
    avgwf_txt_file: (a boolean or a file name)
            Save average waveform into file (bool or filename)
            flag: --avgwf %s
    brain_vol: (u'brain-vol-from-seg' or u'brainmask')
            Compute brain volume either with ``brainmask`` or ``brain-vol-from-
            seg``
            flag: --%s
    brainmask_file: (an existing file name)
            Load brain mask and compute the volume of the brain as the non-zero
            voxels in this volume
            flag: --brainmask %s
    calc_power: (u'sqr' or u'sqrt')
            Compute either the sqr or the sqrt of the input
            flag: --%s
    calc_snr: (a boolean)
            save mean/std as extra column in output table
            flag: --snr
    color_table_file: (an existing file name)
            color table file with seg id names
            flag: --ctab %s
            mutually_exclusive: color_table_file, default_color_table,
             gca_color_table
    cortex_vol_from_surf: (a boolean)
            Compute cortex volume from surf
            flag: --surf-ctx-vol
    default_color_table: (a boolean)
            use $FREESURFER_HOME/FreeSurferColorLUT.txt
            flag: --ctab-default
            mutually_exclusive: color_table_file, default_color_table,
             gca_color_table
    empty: (a boolean)
            Report on segmentations listed in the color table
            flag: --empty
    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
    etiv: (a boolean)
            Compute ICV from talairach transform
            flag: --etiv
    etiv_only: (u'etiv' or u'old-etiv' or u'--%s-only')
            Compute etiv and exit. Use ``etiv`` or ``old-etiv``
    euler: (a boolean)
            Write out number of defect holes in orig.nofix based on the euler
            number
            flag: --euler
    exclude_ctx_gm_wm: (a boolean)
            exclude cortical gray and white matter
            flag: --excl-ctxgmwm
    exclude_id: (an integer (int or long))
            Exclude seg id from report
            flag: --excludeid %d
    frame: (an integer (int or long))
            Report stats on nth frame of input volume
            flag: --frame %d
    gca_color_table: (an existing file name)
            get color table from GCA (CMA)
            flag: --ctab-gca %s
            mutually_exclusive: color_table_file, default_color_table,
             gca_color_table
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    in_file: (an existing file name)
            Use the segmentation to report stats on this volume
            flag: --i %s
    in_intensity: (a file name)
            Undocumented input norm.mgz file
            flag: --in %s --in-intensity-name %s
    intensity_units: (u'MR')
            Intensity units
            flag: --in-intensity-units %s
            requires: in_intensity
    mask_erode: (an integer (int or long))
            Erode mask by some amount
            flag: --maskerode %d
    mask_file: (an existing file name)
            Mask volume (same size as seg
            flag: --mask %s
    mask_frame: (an integer (int or long))
            Mask with this (0 based) frame of the mask volume
            requires: mask_file
    mask_invert: (a boolean)
            Invert binarized mask volume
            flag: --maskinvert
    mask_sign: (u'abs' or u'pos' or u'neg' or u'--masksign %s')
            Sign for mask threshold: pos, neg, or abs
    mask_thresh: (a float)
            binarize mask with this threshold <0.5>
            flag: --maskthresh %f
    multiply: (a float)
            multiply input by val
            flag: --mul %f
    non_empty_only: (a boolean)
            Only report nonempty segmentations
            flag: --nonempty
    partial_volume_file: (an existing file name)
            Compensate for partial voluming
            flag: --pv %s
    segment_id: (a list of items which are any value)
            Manually specify segmentation ids
            flag: --id %s...
    sf_avg_file: (a boolean or a file name)
            Save mean across space and time
            flag: --sfavg %s
    subcort_gm: (a boolean)
            Compute volume of subcortical gray matter
            flag: --subcortgray
    subjects_dir: (an existing directory name)
            subjects directory
    summary_file: (a file name)
            Segmentation stats summary table file
            flag: --sum %s, position: -1
    supratent: (a boolean)
            Undocumented input flag
            flag: --supratent
    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
    total_gray: (a boolean)
            Compute volume of total gray matter
            flag: --totalgray
    vox: (a list of items which are an integer (int or long))
            Replace seg with all 0s except at C R S (three int inputs)
            flag: --vox %s
    wm_vol_from_surf: (a boolean)
            Compute wm volume from surf
            flag: --surf-wm-vol

Outputs:

    avgwf_file: (a file name)
            Volume with functional statistics averaged over segs
    avgwf_txt_file: (a file name)
            Text file with functional statistics averaged over segs
    sf_avg_file: (a file name)
            Text file with func statistics averaged over segs and framss
    summary_file: (an existing file name)
            Segmentation summary statistics table

## SegStatsReconAll

Link to code

Wraps command mri_segstats

This class inherits SegStats and modifies it for use in a recon-all workflow. This implementation mandates implicit inputs that SegStats. To ensure backwards compatability of SegStats, this class was created.

### Examples

    >>> from nipype.interfaces.freesurfer import SegStatsReconAll
    >>> segstatsreconall = SegStatsReconAll()
    >>> segstatsreconall.inputs.annot = ('PWS04', 'lh', 'aparc')
    >>> segstatsreconall.inputs.avgwf_txt_file = 'avgwf.txt'
    >>> segstatsreconall.inputs.summary_file = 'summary.stats'
    >>> segstatsreconall.inputs.subject_id = '10335'
    >>> segstatsreconall.inputs.ribbon = 'wm.mgz'
    >>> segstatsreconall.inputs.transform = 'trans.mat'
    >>> segstatsreconall.inputs.presurf_seg = 'wm.mgz'
    >>> segstatsreconall.inputs.lh_orig_nofix = 'lh.pial'
    >>> segstatsreconall.inputs.rh_orig_nofix = 'lh.pial'
    >>> segstatsreconall.inputs.lh_pial = 'lh.pial'
    >>> segstatsreconall.inputs.rh_pial = 'lh.pial'
    >>> segstatsreconall.inputs.lh_white = 'lh.pial'
    >>> segstatsreconall.inputs.rh_white = 'lh.pial'
    >>> segstatsreconall.inputs.empty = True
    >>> segstatsreconall.inputs.brain_vol = 'brain-vol-from-seg'
    >>> segstatsreconall.inputs.exclude_ctx_gm_wm = True
    >>> segstatsreconall.inputs.supratent = True
    >>> segstatsreconall.inputs.subcort_gm = True
    >>> segstatsreconall.inputs.etiv = True
    >>> segstatsreconall.inputs.wm_vol_from_surf = True
    >>> segstatsreconall.inputs.cortex_vol_from_surf = True
    >>> segstatsreconall.inputs.total_gray = True
    >>> segstatsreconall.inputs.euler = True
    >>> segstatsreconall.inputs.exclude_id = 0
    >>> segstatsreconall.cmdline
    'mri_segstats --annot PWS04 lh aparc --avgwf ./avgwf.txt --brain-vol-from-seg --surf-ctx-vol --empty --etiv --euler --excl-ctxgmwm --excludeid 0 --subcortgray --subject 10335 --supratent --totalgray --surf-wm-vol --sum ./summary.stats'

Inputs:

    [Mandatory]
    annot: (a tuple of the form: (a unicode string, u'lh' or u'rh', a
             unicode string))
            subject hemi parc : use surface parcellation
            flag: --annot %s %s %s
            mutually_exclusive: segmentation_file, annot, surf_label
    lh_orig_nofix: (an existing file name)
            Input lh.orig.nofix
    lh_pial: (an existing file name)
            Input file must be <subject_id>/surf/lh.pial
    lh_white: (an existing file name)
            Input file must be <subject_id>/surf/lh.white
    rh_orig_nofix: (an existing file name)
            Input rh.orig.nofix
    rh_pial: (an existing file name)
            Input file must be <subject_id>/surf/rh.pial
    rh_white: (an existing file name)
            Input file must be <subject_id>/surf/rh.white
    ribbon: (a file name)
            Input file mri/ribbon.mgz
    segmentation_file: (an existing file name)
            segmentation volume path
            flag: --seg %s
            mutually_exclusive: segmentation_file, annot, surf_label
    subject_id: (a string, nipype default value: subject_id)
            Subject id being processed
            flag: --subject %s
    surf_label: (a tuple of the form: (a unicode string, u'lh' or u'rh',
             a unicode string))
            subject hemi label : use surface label
            flag: --slabel %s %s %s
            mutually_exclusive: segmentation_file, annot, surf_label
    transform: (an existing file name)
            Input transform file

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    aseg: (an existing file name)
            Mandatory implicit input in 5.3
    avgwf_file: (a boolean or a file name)
            Save as binary volume (bool or filename)
            flag: --avgwfvol %s
    avgwf_txt_file: (a boolean or a file name)
            Save average waveform into file (bool or filename)
            flag: --avgwf %s
    brain_vol: (u'brain-vol-from-seg' or u'brainmask')
            Compute brain volume either with ``brainmask`` or ``brain-vol-from-
            seg``
            flag: --%s
    brainmask_file: (an existing file name)
            Load brain mask and compute the volume of the brain as the non-zero
            voxels in this volume
            flag: --brainmask %s
    calc_power: (u'sqr' or u'sqrt')
            Compute either the sqr or the sqrt of the input
            flag: --%s
    calc_snr: (a boolean)
            save mean/std as extra column in output table
            flag: --snr
    color_table_file: (an existing file name)
            color table file with seg id names
            flag: --ctab %s
            mutually_exclusive: color_table_file, default_color_table,
             gca_color_table
    copy_inputs: (a boolean)
            If running as a node, set this to True otherwise, this will copy the
            implicit inputs to the node directory.
    cortex_vol_from_surf: (a boolean)
            Compute cortex volume from surf
            flag: --surf-ctx-vol
    default_color_table: (a boolean)
            use $FREESURFER_HOME/FreeSurferColorLUT.txt
            flag: --ctab-default
            mutually_exclusive: color_table_file, default_color_table,
             gca_color_table
    empty: (a boolean)
            Report on segmentations listed in the color table
            flag: --empty
    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
    etiv: (a boolean)
            Compute ICV from talairach transform
            flag: --etiv
    etiv_only: (u'etiv' or u'old-etiv' or u'--%s-only')
            Compute etiv and exit. Use ``etiv`` or ``old-etiv``
    euler: (a boolean)
            Write out number of defect holes in orig.nofix based on the euler
            number
            flag: --euler
    exclude_ctx_gm_wm: (a boolean)
            exclude cortical gray and white matter
            flag: --excl-ctxgmwm
    exclude_id: (an integer (int or long))
            Exclude seg id from report
            flag: --excludeid %d
    frame: (an integer (int or long))
            Report stats on nth frame of input volume
            flag: --frame %d
    gca_color_table: (an existing file name)
            get color table from GCA (CMA)
            flag: --ctab-gca %s
            mutually_exclusive: color_table_file, default_color_table,
             gca_color_table
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    in_file: (an existing file name)
            Use the segmentation to report stats on this volume
            flag: --i %s
    in_intensity: (a file name)
            Undocumented input norm.mgz file
            flag: --in %s --in-intensity-name %s
    intensity_units: (u'MR')
            Intensity units
            flag: --in-intensity-units %s
            requires: in_intensity
    mask_erode: (an integer (int or long))
            Erode mask by some amount
            flag: --maskerode %d
    mask_file: (an existing file name)
            Mask volume (same size as seg
            flag: --mask %s
    mask_frame: (an integer (int or long))
            Mask with this (0 based) frame of the mask volume
            requires: mask_file
    mask_invert: (a boolean)
            Invert binarized mask volume
            flag: --maskinvert
    mask_sign: (u'abs' or u'pos' or u'neg' or u'--masksign %s')
            Sign for mask threshold: pos, neg, or abs
    mask_thresh: (a float)
            binarize mask with this threshold <0.5>
            flag: --maskthresh %f
    multiply: (a float)
            multiply input by val
            flag: --mul %f
    non_empty_only: (a boolean)
            Only report nonempty segmentations
            flag: --nonempty
    partial_volume_file: (an existing file name)
            Compensate for partial voluming
            flag: --pv %s
    presurf_seg: (an existing file name)
            Input segmentation volume
    segment_id: (a list of items which are any value)
            Manually specify segmentation ids
            flag: --id %s...
    sf_avg_file: (a boolean or a file name)
            Save mean across space and time
            flag: --sfavg %s
    subcort_gm: (a boolean)
            Compute volume of subcortical gray matter
            flag: --subcortgray
    subjects_dir: (an existing directory name)
            subjects directory
    summary_file: (a file name)
            Segmentation stats summary table file
            flag: --sum %s, position: -1
    supratent: (a boolean)
            Undocumented input flag
            flag: --supratent
    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
    total_gray: (a boolean)
            Compute volume of total gray matter
            flag: --totalgray
    vox: (a list of items which are an integer (int or long))
            Replace seg with all 0s except at C R S (three int inputs)
            flag: --vox %s
    wm_vol_from_surf: (a boolean)
            Compute wm volume from surf
            flag: --surf-wm-vol

Outputs:

    avgwf_file: (a file name)
            Volume with functional statistics averaged over segs
    avgwf_txt_file: (a file name)
            Text file with functional statistics averaged over segs
    sf_avg_file: (a file name)
            Text file with func statistics averaged over segs and framss
    summary_file: (an existing file name)
            Segmentation summary statistics table

## SphericalAverage

Link to code

Wraps command mris_spherical_average

This program will add a template into an average surface.

### Examples

    >>> from nipype.interfaces.freesurfer import SphericalAverage
    >>> sphericalavg = SphericalAverage()
    >>> sphericalavg.inputs.out_file = 'test.out'
    >>> sphericalavg.inputs.in_average = '.'
    >>> sphericalavg.inputs.in_surf = 'lh.pial'
    >>> sphericalavg.inputs.hemisphere = 'lh'
    >>> sphericalavg.inputs.fname = 'lh.entorhinal'
    >>> sphericalavg.inputs.which = 'label'
    >>> sphericalavg.inputs.subject_id = '10335'
    >>> sphericalavg.inputs.erode = 2
    >>> sphericalavg.inputs.threshold = 5
    >>> sphericalavg.cmdline
    'mris_spherical_average -erode 2 -o 10335 -t 5.0 label lh.entorhinal lh pial . test.out'

Inputs:

    [Mandatory]
    fname: (a string)
            Filename from the average subject directory.
             Example: to use rh.entorhinal.label as the input label
             filename, set fname to 'rh.entorhinal' and which to
             'label'. The program will then search for
             '{in_average}/label/rh.entorhinal.label'
            flag: %s, position: -5
    hemisphere: (u'lh' or u'rh')
            Input hemisphere
            flag: %s, position: -4
    in_surf: (an existing file name)
            Input surface file
            flag: %s, position: -3
    subject_id: (a string)
            Output subject id
            flag: -o %s
    which: (u'coords' or u'label' or u'vals' or u'curv' or u'area')
            No documentation
            flag: %s, position: -6

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %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
    erode: (an integer (int or long))
            Undocumented
            flag: -erode %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
    in_average: (a directory name)
            Average subject
            flag: %s, position: -2
    in_orig: (an existing file name)
            Original surface filename
            flag: -orig %s
    out_file: (a file name)
            Output filename
            flag: %s, position: -1
    subjects_dir: (an existing directory name)
            subjects directory
    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
    threshold: (a float)
            Undocumented
            flag: -t %.1f

Outputs:

    out_file: (a file name)
            Output label