diff --git a/src/eddymotion/data/dmri.py b/src/eddymotion/data/dmri.py
index 0da7ad14..bfc4c788 100644
--- a/src/eddymotion/data/dmri.py
+++ b/src/eddymotion/data/dmri.py
@@ -83,7 +83,7 @@ def set_data(self):
         with h5py.File(self._filepath, "r") as in_file:
             self._root = in_file["/0"]
 
-    def set_transform(self, dwframe, bvec, index, affine, order=3):
+    def set_transform(self, index, affine, order=3):
         """Set an affine, and update data object and gradients."""
         reference = namedtuple("ImageGrid", ("shape", "affine"))(
             shape=self.dataobj.shape[:3], affine=self.affine
@@ -96,6 +96,9 @@ def set_transform(self, dwframe, bvec, index, affine, order=3):
         else:
             xform = Affine(matrix=affine, reference=reference)
 
+        dwframe = np.asanyarray(self.dataobj[..., index])
+        bvec = np.asanyarray(self.gradients[:3, index])
+
         dwmoving = nb.Nifti1Image(dwframe, self.affine, None)
 
         # resample and update orientation at index
diff --git a/src/eddymotion/estimator.py b/src/eddymotion/estimator.py
index b864c266..57cc4cd6 100644
--- a/src/eddymotion/estimator.py
+++ b/src/eddymotion/estimator.py
@@ -153,9 +153,6 @@ def fit(
                         )
                         data_train, data_test = logo_split(dwdata, i)
 
-                        grad_str = f"{i}, {data_test[1][:3]}, b={int(data_test[1][3])}"
-                        pbar.set_description_str(f"[{grad_str}], {n_jobs} jobs")
-
                         if not single_model:  # A true LOGO estimator
                             if hasattr(dwdata, "gradients"):
                                 kwargs["gtab"] = data_train[1]