Removed afni centrality interface (will do that in another branch)

Author: pintohutch

nipype/interfaces/afni/__init__.py

@@ -8,7 +8,7 @@
 
 from .base import Info
 from .preprocess import (To3D, Refit, Resample, TStat, Automask, Volreg, Merge,
-                         ZCutUp, Calc, TShift, Warp, Detrend, Despike, DegreeCentrality,
+                         ZCutUp, Calc, TShift, Warp, Detrend, Despike,
                          Copy, Fourier, Allineate, Maskave, SkullStrip, TCat, Fim,
                          BlurInMask, Autobox, TCorrMap, Bandpass, Retroicor,
                          TCorrelate, TCorr1D, BrickStat, ROIStats, AutoTcorrelate,

nipype/interfaces/afni/preprocess.py

@@ -507,131 +507,6 @@ class Despike(AFNICommand):
     output_spec = AFNICommandOutputSpec
 
 
-class CentralityInputSpec(AFNICommandInputSpec):
-    """
-    inherits the out_file parameter from AFNICommandOutputSpec base class
-    """
-
-    in_file = File(desc='input file to 3dDegreeCentrality',
-                   argstr='%s',
-                   position=-1,
-                   mandatory=True,
-                   exists=True,
-                   copyfile=False)
-
-    mask = File(desc='mask file to mask input data',
-                   argstr="-mask %s",
-                   exists=True)
-
-    thresh = traits.Float(desc='threshold to exclude connections where corr <= thresh',
-                          argstr='-thresh %f')
-
-    polort = traits.Int(desc='', argstr='-polort %d')
-
-    autoclip = traits.Bool(desc='Clip off low-intensity regions in the dataset',
-                           argstr='-autoclip')
-
-    automask = traits.Bool(desc='Mask the dataset to target brain-only voxels',
-                           argstr='-automask')
-
-
-class DegreeCentralityInputSpec(CentralityInputSpec):
-    """
-    inherits the out_file parameter from AFNICommandOutputSpec base class
-    """
-
-    in_file = File(desc='input file to 3dDegreeCentrality',
-                   argstr='%s',
-                   position=-1,
-                   mandatory=True,
-                   exists=True,
-                   copyfile=False)
-
-    mask = File(desc='mask file to mask input data',
-                   argstr="-mask %s",
-                   exists=True)
-
-    thresh = traits.Float(desc='threshold to exclude connections where corr <= thresh',
-                          argstr='-thresh %f')
-
-    sparsity = traits.Float(desc='only take the top percent of connections',
-                            argstr='-sparsity %f')
-
-    out_1d = traits.Str(desc='output filepath to text dump of correlation matrix',
-                        argstr='-out1D')
-
-    polort = traits.Int(desc='', argstr='-polort %d')
-
-    autoclip = traits.Bool(desc='Clip off low-intensity regions in the dataset',
-                           argstr='-autoclip')
-
-    automask = traits.Bool(desc='Mask the dataset to target brain-only voxels',
-                           argstr='-automask')
-
-
-class DegreeCentralityOutputSpec(AFNICommandOutputSpec):
-    """
-    inherits the out_file parameter from AFNICommandOutputSpec base class
-    """
-
-    one_d_file = File(desc='The text output of the similarity matrix computed'\
-                           'after thresholding with one-dimensional and '\
-                           'ijk voxel indices, correlations, image extents, '\
-                           'and affine matrix')
-
-
-class DegreeCentrality(AFNICommand):
-    """Performs degree centrality on a dataset using a given maskfile
-    via 3dDegreeCentrality
-
-    For complete details, see the `3dDegreeCentrality Documentation.
-    <http://afni.nimh.nih.gov/pub/dist/doc/program_help/3dDegreeCentrality.html>
-
-    Examples
-    ========
-
-    >>> from nipype.interfaces import afni as afni
-    >>> degree = afni.DegreeCentrality()
-    >>> degree.inputs.in_file = 'func_preproc.nii'
-    >>> degree.inputs.mask = 'mask.nii'
-    >>> degree.inputs.sparsity = 1 # keep the top one percent of connections
-    >>> degree.cmdline
-    '3dDegreeCentrality -sparsity 1 -mask mask.nii func_preproc.nii'
-    >>> res = degree.run() # doctest: +SKIP
-    """
-
-    _cmd = '3dDegreeCentrality'
-    input_spec = DegreeCentralityInputSpec
-    output_spec = DegreeCentralityOutputSpec
-
-
-class AutomaskInputSpec(AFNICommandInputSpec):
-    in_file = File(desc='input file to 3dAutomask',
-                   argstr='%s',
-                   position=-1,
-                   mandatory=True,
-                   exists=True,
-                   copyfile=False)
-
-    out_file = File(name_template="%s_mask", desc='output image file name',
-                    argstr='-prefix %s', name_source="in_file")
-
-    brain_file = File(name_template="%s_masked",
-                      desc="output file from 3dAutomask",
-                      argstr='-apply_prefix %s',
-                      name_source="in_file")
-
-    clfrac = traits.Float(desc='sets the clip level fraction' +
-                          ' (must be 0.1-0.9). ' +
-                          'A small value will tend to make the mask larger [default = 0.5].',
-                          argstr="-clfrac %s")
-
-    dilate = traits.Int(desc='dilate the mask outwards',
-                        argstr="-dilate %s")
-
-    erode = traits.Int(desc='erode the mask inwards',
-                       argstr="-erode %s")
-
 
 class AutomaskOutputSpec(TraitedSpec):
     out_file = File(desc='mask file',