added ModifyAffine

nipype/algorithms/misc.py

@@ -116,3 +116,39 @@ def _list_outputs(self):
  outputs["thresholded_volumes"].append(base + '_thresholded.nii')
  return outputs
 
+class ModifyAffineInputSpec(TraitedSpec):
+ volumes = InputMultiPath(File(exists=True), desc='volumes which affine matrices will be modified', mandatory=True)
+ transformation_matrix = traits.Array(value=np.eye(4), shape=(4,4), desc="transformation matrix that will be left multiplied by the affine matrix", usedefault=True)
+
+class ModifyAffineOutputSpec(TraitedSpec):
+ transformed_volumes = OutputMultiPath(File(exist=True))
+
+class ModifyAffine(BaseInterface):
+ '''
+ LEft multiplies the affine matrix with a specified values. Saves the volume as a nifti file.
+ '''
+ input_spec = ModifyAffineInputSpec
+ output_spec = ModifyAffineOutputSpec
+
+ def _gen_output_filename(self, name):
+ _, base, _ = split_filename(name)
+ return os.path.abspath(base + "_transformed.nii")
+
+ def _run_interface(self, runtime):
+ for fname in self.inputs.volumes:
+ img = nifti.load(fname)
+
+ affine = img.get_affine()
+ affine = np.dot(self.inputs.transformation_matrix,affine)
+
+ nifti.save(nifti.Nifti1Image(img.get_data(), affine, img.get_header()), self._gen_output_filename(fname))
+
+ runtime.returncode=0
+ return runtime
+
+ def _list_outputs(self):
+ outputs = self._outputs().get()
+ outputs['transformed_volumes'] = []
+ for fname in self.inputs.volumes:
+ outputs['transformed_volumes'].append(self._gen_output_filename(fname))
+ return outputs