Merge pull request #435 from chrisfilo/fix/spm_bool

Fix/spm bool

Author: chrisgorgo

nipype/interfaces/spm/base.py

@@ -253,8 +253,10 @@ def _list_outputs(self):
 
     def _format_arg(self, opt, spec, val):
         """Convert input to appropriate format for SPM."""
-
-        return val
+        if spec.is_trait_type(traits.Bool):
+            return int(val)
+        else:
+            return val
 
     def _parse_inputs(self, skip=()):
         spmdict = {}

nipype/interfaces/spm/model.py

@@ -117,7 +117,7 @@ def _format_arg(self, opt, spec, val):
                 return [val]
             else:
                 return val
-        return val
+        return super(Level1Design, self)._format_arg(opt, spec, val)
 
     def _parse_inputs(self):
         """validate spm realign options if set to None ignore
@@ -200,7 +200,7 @@ def _format_arg(self, opt, spec, val):
                 return {'%s' % val: 1}
             else:
                 return val
-        return val
+        return super(EstimateModel, self)._format_arg(opt, spec, val)
 
     def _parse_inputs(self):
         """validate spm realign options if set to None ignore
@@ -747,7 +747,7 @@ def _format_arg(self, opt, spec, val):
                     outdict[mapping[key]] = keyval
                 outlist.append(outdict)
             return outlist
-        return val
+        return super(FactorialDesign, self)._format_arg(opt, spec, val)
 
     def _parse_inputs(self):
         """validate spm realign options if set to None ignore
@@ -893,8 +893,6 @@ def _format_arg(self, opt, spec, val):
         """
         if opt in ['in_files']:
             return np.array(val, dtype=object)
-        if opt in ['include_intercept']:
-            return int(val)
         if opt in ['user_covariates']:
             outlist = []
             mapping = {'name': 'cname', 'vector': 'c',

nipype/interfaces/spm/preprocess.py

@@ -87,7 +87,7 @@ def _format_arg(self, opt, spec, val):
             return scans_for_fnames(filename_to_list(val),
                                     keep4d=False,
                                     separate_sessions=True)
-        return val
+        return super(SliceTiming, self)._format_arg(opt, spec, val)
 
     def _list_outputs(self):
         outputs = self._outputs().get()
@@ -177,9 +177,7 @@ def _format_arg(self, opt, spec, val):
             return scans_for_fnames(val,
                                     keep4d=True,
                                     separate_sessions=True)
-        if opt == 'register_to_mean': # XX check if this is necessary
-            return int(val)
-        return val
+        return super(Realign, self)._format_arg(opt, spec, val)
 
     def _parse_inputs(self):
         """validate spm realign options if set to None ignore
@@ -296,7 +294,7 @@ def _format_arg(self, opt, spec, val):
                 return scans_for_fnames(val+self.inputs.apply_to_files)
             else:
                 return scans_for_fnames(val)
-        return val
+        return super(Coregister, self)._format_arg(opt, spec, val)
 
     def _parse_inputs(self):
         """validate spm coregister options if set to None ignore
@@ -411,7 +409,7 @@ def _format_arg(self, opt, spec, val):
         if opt in ['write_wrap']:
             if len(val) != 3:
                 raise ValueError('%s must have 3 elements' % opt)
-        return val
+        return super(Normalize, self)._format_arg(opt, spec, val)
 
     def _parse_inputs(self):
         """validate spm realign options if set to None ignore
@@ -560,13 +558,11 @@ def _format_arg(self, opt, spec, val):
                 return scans_for_fname(val)
         if 'output_type' in opt:
             return [int(v) for v in val]
-        if opt == 'save_bias_corrected':
-            return int(val)
         if opt == 'mask_image':
             return scans_for_fname(val)
         if opt == 'clean_masks':
             return clean_masks_dict[val]
-        return val
+        return super(Segment, self)._format_arg(opt, spec, val)
 
     def _list_outputs(self):
         outputs = self._outputs().get()
@@ -785,10 +781,8 @@ def _format_arg(self, opt, spec, val):
                     return [val[0], val[0], val[0]]
                 else:
                     return val
-        if opt == 'implicit_masking':
-            return int(val)
 
-        return val
+        return super(Smooth, self)._format_arg(opt, spec, val)
 
     def _list_outputs(self):
         outputs = self._outputs().get()
@@ -879,7 +873,7 @@ def _format_arg(self, opt, spec, val):
             new_param['its'] = val[2]
             return [new_param]
         else:
-            return val
+            return super(DARTEL, self)._format_arg(opt, spec, val)
 
     def _list_outputs(self):
         outputs = self._outputs().get()
@@ -965,10 +959,8 @@ def _format_arg(self, opt, spec, val):
                 return val
             else:
                 return [val, val, val]
-        elif opt == 'modulate':
-            return int(val)
         else:
-            return val
+            return super(DARTELNorm2MNI, self)._format_arg(opt, spec, val)
 
     def _list_outputs(self):
         outputs = self._outputs().get()
@@ -1040,7 +1032,7 @@ def _format_arg(self, opt, spec, val):
         if opt in ['flowfield_files']:
             return scans_for_fnames(val, keep4d=True)
         else:
-            return val
+            return super(CreateWarped, self)._format_arg(opt, spec, val)
 
     def _list_outputs(self):
         outputs = self._outputs().get()

nipype/interfaces/spm/tests/test_base.py

@@ -11,6 +11,8 @@
 import nipype.interfaces.spm.base as spm
 from nipype.interfaces.spm import no_spm
 import nipype.interfaces.matlab as mlab
+from nipype.interfaces.spm.base import SPMCommandInputSpec
+from nipype.interfaces.base import traits
 
 try:
     matlab_cmd = os.environ['MATLABCMD']
@@ -121,7 +123,19 @@ class TestClass(spm.SPMCommand):
     out = dc._generate_job(prefix='test', contents=contents)
     yield assert_equal, out, 'test.onsets = {...\n[1, 2, 3, 4];...\n};\n'
 
-
+def test_bool():
+    class TestClassInputSpec(SPMCommandInputSpec):
+        test_in = include_intercept = traits.Bool(field='testfield')
+        
+    class TestClass(spm.SPMCommand):
+        input_spec = TestClassInputSpec
+        _jobtype = 'jobtype'
+        _jobname = 'jobname'
+    dc = TestClass()  # dc = derived_class
+    dc.inputs.test_in = True
+    out = dc._make_matlab_command(dc._parse_inputs())
+    yield assert_equal, out.find('jobs{1}.jobtype{1}.jobname{1}.testfield = 1;') > 0, 1
+    
 def test_make_matlab_command():
     class TestClass(spm.SPMCommand):
         _jobtype = 'jobtype'