Merge remote branch 'hanke/master'

* hanke/master:
  BF: Identifying all 'mode options' of BET and make them mutually exclusive
  ENH: Complete BET interface. I'm not 100% sure if there was a reason to exclude the missing options, but they seems to work fine for me.

nipype/interfaces/fsl/preprocess.py

@@ -29,7 +29,7 @@
 
 
 class BETInputSpec(FSLCommandInputSpec):
-    """Note: Currently we don't support -R, -S, -Z,-A or -A2"""
+    """"""
     # We use position args here as list indices - so a negative number
     # will put something on the end
     in_file = File(exists=True,
@@ -59,8 +59,29 @@ class BETInputSpec(FSLCommandInputSpec):
                    desc="apply thresholding to segmented brain image and mask")
     mesh = traits.Bool(argstr='-e',
                        desc="generate a vtk mesh brain surface")
-    # XXX how do we know these two are mutually exclusive?
-    _xor_inputs = ('functional', 'reduce_bias')
+    # the remaining 'options' are more like modes (mutually exclusive) that
+    # FSL actually implements in a shell script wrapper around the bet binary.
+    # for some combinations of them in specific order a call would not fail,
+    # but in general using more than one of the following is clearly not
+    # supported
+    _xor_inputs = ('functional', 'reduce_bias', 'robust', 'padding',
+                   'remove_eyes', 'surfaces', 't2_guided')
+    robust = traits.Bool(desc='robust brain centre estimation ' \
+                              '(iterates BET several times)',
+                       argstr='-R', xor=_xor_inputs)
+    padding = traits.Bool(desc='improve BET if FOV is very small in Z ' \
+                               '(by temporarily padding end slices)',
+                       argstr='-Z', xor=_xor_inputs)
+    remove_eyes = traits.Bool(desc='eye & optic nerve cleanup (can be ' \
+                                   'useful in SIENA)',
+                       argstr='-S', xor=_xor_inputs)
+    surfaces = traits.Bool(desc='run bet2 and then betsurf to get additional ' \
+                                'skull and scalp surfaces (includes ' \
+                                'registrations)',
+                           argstr='-A', xor=_xor_inputs)
+    t2_guided = File(desc='as with creating surfaces, when also feeding in ' \
+                          'non-brain-extracted T2 (includes registrations)',
+                     argstr='-A2 %s', xor=_xor_inputs)
     functional = traits.Bool(argstr='-F', xor=_xor_inputs,
                              desc="apply to 4D fMRI data")
     reduce_bias = traits.Bool(argstr='-B', xor=_xor_inputs,