Merge pull request #1234 from oesteban/enh/DivisionWarningsTSNR

[ENH] Remove warnings in tSNR calculation

Author: satra

nipype/algorithms/misc.py

@@ -263,6 +263,14 @@ class TSNRInputSpec(BaseInterfaceInputSpec):
     in_file = InputMultiPath(File(exists=True), mandatory=True,
                              desc='realigned 4D file or a list of 3D files')
     regress_poly = traits.Range(low=1, desc='Remove polynomials')
+    tsnr_file = File('tsnr.nii.gz', usedefault=True, hash_files=False,
+                     desc='output tSNR file')
+    mean_file = File('mean.nii.gz', usedefault=True, hash_files=False,
+                     desc='output mean file')
+    stddev_file = File('stdev.nii.gz', usedefault=True, hash_files=False,
+                       desc='output tSNR file')
+    detrended_file = File('detrend.nii.gz', usedefault=True, hash_files=False,
+                          desc='input file after detrending')
 
 
 class TSNROutputSpec(TraitedSpec):
@@ -288,24 +296,18 @@ class TSNR(BaseInterface):
     input_spec = TSNRInputSpec
     output_spec = TSNROutputSpec
 
-    def _gen_output_file_name(self, suffix=None):
-        _, base, ext = split_filename(self.inputs.in_file[0])
-        if suffix in ['mean', 'stddev']:
-            return os.path.abspath(base + "_tsnr_" + suffix + ext)
-        elif suffix in ['detrended']:
-            return os.path.abspath(base + "_" + suffix + ext)
-        else:
-            return os.path.abspath(base + "_tsnr" + ext)
-
     def _run_interface(self, runtime):
         img = nb.load(self.inputs.in_file[0])
         header = img.header.copy()
         vollist = [nb.load(filename) for filename in self.inputs.in_file]
         data = np.concatenate([vol.get_data().reshape(
-            vol.shape[:3] + (-1,)) for vol in vollist], axis=3)
+            vol.get_shape()[:3] + (-1,)) for vol in vollist], axis=3)
+        data = data.nan_to_num()
+
         if data.dtype.kind == 'i':
             header.set_data_dtype(np.float32)
             data = data.astype(np.float32)
+
         if isdefined(self.inputs.regress_poly):
             timepoints = img.shape[-1]
             X = np.ones((timepoints, 1))
@@ -318,26 +320,28 @@ def _run_interface(self, runtime):
                                              betas[1:, :, :, :], 0, 3)),
                                   0, 4)
             data = data - datahat
-            img = nb.Nifti1Image(data, img.affine, header)
-            nb.save(img, self._gen_output_file_name('detrended'))
+            img = nb.Nifti1Image(data, img.get_affine(), header)
+            nb.save(img, op.abspath(self.inputs.detrended_file))
+
         meanimg = np.mean(data, axis=3)
         stddevimg = np.std(data, axis=3)
-        tsnr = meanimg / stddevimg
-        img = nb.Nifti1Image(tsnr, img.affine, header)
-        nb.save(img, self._gen_output_file_name())
-        img = nb.Nifti1Image(meanimg, img.affine, header)
-        nb.save(img, self._gen_output_file_name('mean'))
-        img = nb.Nifti1Image(stddevimg, img.affine, header)
-        nb.save(img, self._gen_output_file_name('stddev'))
+        tsnr = np.zeros_like(meanimg)
+        tsnr[stddevimg > 1.e-3] = meanimg[stddevimg > 1.e-3] / stddevimg[stddevimg > 1.e-3]
+        img = nb.Nifti1Image(tsnr, img.get_affine(), header)
+        nb.save(img, op.abspath(self.inputs.tsnr_file))
+        img = nb.Nifti1Image(meanimg, img.get_affine(), header)
+        nb.save(img, op.abspath(self.inputs.mean_file))
+        img = nb.Nifti1Image(stddevimg, img.get_affine(), header)
+        nb.save(img, op.abspath(self.inputs.stddev_file))
         return runtime
 
     def _list_outputs(self):
         outputs = self._outputs().get()
-        outputs['tsnr_file'] = self._gen_output_file_name()
-        outputs['mean_file'] = self._gen_output_file_name('mean')
-        outputs['stddev_file'] = self._gen_output_file_name('stddev')
+        for k in ['tsnr_file', 'mean_file', 'stddev_file']:
+            outputs[k] = op.abspath(getattr(self.inputs, k))
+
         if isdefined(self.inputs.regress_poly):
-            outputs['detrended_file'] = self._gen_output_file_name('detrended')
+            outputs['detrended_file'] = op.abspath(self.inputs.detrended_file) 
         return outputs