Merge pull request #426 from chrisfilo/fix/abspaths

Fixed output files hashing and returned paths.

Author: chrisgorgo

doc/devel/interface_specs.rst

@@ -194,6 +194,9 @@ Common
 	    TraitError: The 'infile' trait of a BetInputSpec instance must be a file 
 	    name, but a value of 'does_not_exist.nii' <type 'str'> was specified.
 	    
+``hash_files``
+	To be used with inputs that are defining output filenames. When this flag is set to false any Nipype will not try to hash any files described by this input. This is useful to avoid rerunning when the specified output file already exists and has changed.
+	    
 ``desc``
 	All trait objects have a set of default metadata attributes.  ``desc``
 	is one of those and is used as a simple, one-line docstring.  The

nipype/interfaces/fsl/dti.py

@@ -102,7 +102,7 @@ def _list_outputs(self):
 
 class EddyCorrectInputSpec(FSLCommandInputSpec):
     in_file = File(exists=True, desc='4D input file', argstr='%s', position=0, mandatory=True)
-    out_file = File(desc='4D output file', argstr='%s', position=1, genfile=True)
+    out_file = File(desc='4D output file', argstr='%s', position=1, genfile=True, hash_files=False)
     ref_num = traits.Int(argstr='%d', position=2, desc='reference number', mandatory=True)
 
 
@@ -143,6 +143,7 @@ def _list_outputs(self):
         outputs['eddy_corrected'] = self.inputs.out_file
         if not isdefined(outputs['eddy_corrected']):
             outputs['eddy_corrected'] = self._gen_fname(self.inputs.in_file, suffix='_edc')
+        outputs['eddy_corrected'] = os.path.abspath(outputs['eddy_corrected'])
         return outputs
 
     def _gen_filename(self, name):
@@ -492,7 +493,7 @@ class VecRegInputSpec(FSLCommandInputSpec):
     in_file = File(exists=True, argstr='-i %s', desc='filename for input vector or tensor field',
                   mandatory=True)
     out_file = File(argstr='-o %s', desc='filename for output registered vector or tensor field',
-                   genfile=True)
+                   genfile=True, hash_files=False)
     ref_vol = File(exists=True, argstr='-r %s', desc='filename for reference (target) volume',
                   mandatory=True)
     affine_mat = File(exists=True, argstr='-t %s',
@@ -554,6 +555,7 @@ def _list_outputs(self):
             pth, base_name = os.path.split(self.inputs.in_file)
             outputs['out_file'] = self._gen_fname(base_name, cwd=os.path.abspath(pth),
                                                  suffix='_vreg')
+        outputs['out_file'] = os.path.abspath(outputs['out_file'])
         return outputs
 
     def _gen_filename(self, name):
@@ -610,7 +612,7 @@ def _list_outputs(self):
 class FindTheBiggestInputSpec(FSLCommandInputSpec):
     in_files = traits.List(File, exists=True, argstr='%s', desc='a list of input volumes or a singleMatrixFile',
                           position=0, mandatory=True)
-    out_file = File(argstr='%s', desc='file with the resulting segmentation', position=2, genfile=True)
+    out_file = File(argstr='%s', desc='file with the resulting segmentation', position=2, genfile=True, hash_files=False)
 
 
 class FindTheBiggestOutputSpec(TraitedSpec):
@@ -648,6 +650,7 @@ def _list_outputs(self):
         outputs['out_file'] = self.inputs.out_file
         if not isdefined(outputs['out_file']):
             outputs['out_file'] = self._gen_fname('biggestSegmentation', suffix='')
+        outputs['out_file'] = os.path.abspath(outputs['out_file'])
         return outputs
 
     def _gen_filename(self, name):
@@ -762,8 +765,8 @@ class DistanceMapInputSpec(FSLCommandInputSpec):
                      desc="binary mask to contrain calculations")
     invert_input = traits.Bool(argstr="--invert", desc="invert input image")
     local_max_file = traits.Either(traits.Bool, File, argstr="--localmax=%s",
-                                   desc="write an image of the local maxima")
-    distance_map = File(genfile=True, argstr="--out=%s", desc="distance map to write")
+                                   desc="write an image of the local maxima", hash_files=False)
+    distance_map = File(genfile=True, argstr="--out=%s", desc="distance map to write", hash_files=False)
 
 
 class DistanceMapOutputSpec(TraitedSpec):
@@ -804,13 +807,15 @@ def _list_outputs(self):
                                                       suffix="_dstmap",
                                                       use_ext=True,
                                                       newpath=os.getcwd())
+        outputs["distance_map"] = os.path.abspath(outputs["distance_map"])
         if isdefined(_si.local_max_file):
             outputs["local_max_file"] = _si.local_max_file
             if isinstance(_si.local_max_file, bool):
                 outputs["local_max_file"] = fname_presuffix(_si.in_file,
                                                            suffix="_lclmax",
                                                            use_ext=True,
                                                            newpath=os.getcwd())
+            outputs["local_max_file"] = os.path.abspath(outputs["local_max_file"]))
         return outputs
 
     def _gen_filename(self, name):
@@ -905,7 +910,7 @@ class MakeDyadicVectorsInputSpec(FSLCommandInputSpec):
     theta_vol = File(exists=True, mandatory=True, position=0, argstr="%s")
     phi_vol = File(exists=True, mandatory=True, position=1, argstr="%s")
     mask = File(exists=True, position=2, argstr="%s")
-    output = File("dyads", position=3, usedefault=True, argstr="%s")
+    output = File("dyads", position=3, usedefault=True, argstr="%s", hash_files=False)
     perc = traits.Float(desc="the {perc}% angle of the output cone of \
 uncertainty (output will be in degrees)",
                         position=4,

nipype/interfaces/fsl/maths.py

@@ -16,7 +16,7 @@ class MathsInput(FSLCommandInputSpec):
 
     in_file = File(position=2, argstr="%s", exists=True, mandatory=True,
                 desc="image to operate on")
-    out_file = File(genfile=True, position=-2, argstr="%s", desc="image to write")
+    out_file = File(genfile=True, position=-2, argstr="%s", desc="image to write", hash_files=False)
     _dtypes = ["float", "char", "int", "short", "double", "input"]
     internal_datatype = traits.Enum(*_dtypes, position=1, argstr="-dt %s",
                                     desc="datatype to use for calculations (default is float)")
@@ -39,9 +39,10 @@ class MathsCommand(FSLCommand):
 
     def _list_outputs(self):
         outputs = self.output_spec().get()
-        outputs["out_file"] = os.path.abspath(self.inputs.out_file)
+        outputs["out_file"] = self.inputs.out_file
         if not isdefined(self.inputs.out_file):
             outputs["out_file"] = self._gen_fname(self.inputs.in_file, suffix=self._suffix)
+        outputs["out_file"] = os.path.abspath(self.inputs.out_file)
         return outputs
 
     def _gen_filename(self, name):

nipype/interfaces/fsl/model.py

@@ -1285,28 +1285,28 @@ class ClusterInputSpec(FSLCommandInputSpec):
                              desc='threshold for input volume')
     out_index_file = traits.Either(traits.Bool, File,
                                    argstr='--oindex=%s',
-                                   desc='output of cluster index (in size order)')
+                                   desc='output of cluster index (in size order)', hash_files=False)
     out_threshold_file = traits.Either(traits.Bool, File,
                                        argstr='--othresh=%s',
-                                       desc='thresholded image')
+                                       desc='thresholded image', hash_files=False)
     out_localmax_txt_file = traits.Either(traits.Bool, File,
                                           argstr='--olmax=%s',
-                                          desc='local maxima text file')
+                                          desc='local maxima text file', hash_files=False)
     out_localmax_vol_file = traits.Either(traits.Bool, File,
                                           argstr='--olmaxim=%s',
-                                          desc='output of local maxima volume')
+                                          desc='output of local maxima volume', hash_files=False)
     out_size_file = traits.Either(traits.Bool, File,
                                   argstr='--osize=%s',
-                                  desc='filename for output of size image')
+                                  desc='filename for output of size image', hash_files=False)
     out_max_file = traits.Either(traits.Bool, File,
                                  argstr='--omax=%s',
-                                 desc='filename for output of max image')
+                                 desc='filename for output of max image', hash_files=False)
     out_mean_file = traits.Either(traits.Bool, File,
                                   argstr='--omean=%s',
-                                  desc='filename for output of mean image')
+                                  desc='filename for output of mean image', hash_files=False)
     out_pval_file = traits.Either(traits.Bool, File,
                                   argstr='--opvals=%s',
-                                  desc='filename for image output of log pvals')
+                                  desc='filename for image output of log pvals', hash_files=False)
     pthreshold = traits.Float(argstr='--pthresh=%.10f',
                               requires=['dlh', 'volume'],
                               desc='p-threshold for clusters')
@@ -1387,7 +1387,7 @@ def _list_outputs(self):
                                                           suffix='_' + suffix,
                                                           change_ext=change_ext)
                 else:
-                    outputs[outkey] = inval
+                    outputs[outkey] = os.pardir.abspath(inval)
         return outputs
 
     def _format_arg(self, name, spec, value):