STY: Use temporary variable to store DWI model predictions

Use temporary variable to store DWI model predictions from parallel job
in `BaseDWIModel.fit_predict` method.

Author: jhlegarreta

src/nifreeze/model/dmri.py

@@ -200,7 +200,7 @@ def fit_predict(self, index: int | None = None, **kwargs):
                 self._models[0], **(kwargs | {"gtab": gradient, "S0": self._S0})
             )
         else:
-            predicted = [None] * n_models
+            _predicted = [None] * n_models
             S0 = np.array_split(self._S0, n_models)
 
             # Parallelize process with joblib
@@ -214,9 +214,9 @@ def fit_predict(self, index: int | None = None, **kwargs):
                     for i, model in enumerate(self._models)
                 )
             for subprediction, index in results:
-                predicted[index] = subprediction
+                _predicted[index] = subprediction
 
-            predicted = np.hstack(predicted)
+            predicted = np.hstack(_predicted)
 
         retval = np.zeros_like(self._data_mask, dtype=self._dataset.dataobj.dtype)
         retval[self._data_mask, ...] = predicted