loo_error does not change reduction and approx attributes

ezyrb/reducedordermodel.py

@@ -3,6 +3,7 @@
 """
 import numpy as np
 import math
+import copy
 from scipy.spatial import Delaunay
 
 
@@ -74,8 +75,8 @@ def loo_error(self, norm=np.linalg.norm):
             remaining_index = db_range[:]
             remaining_index.remove(j)
             new_db = self.database[remaining_index]
-            rom = type(self)(new_db, self.reduction,
-                    self.approximation).fit()
+            rom = type(self)(new_db, copy.deepcopy(self.reduction),
+                    copy.deepcopy(self.approximation)).fit()
 
             error[j] = norm(self.database.snapshots[j] -
                             rom.predict(self.database.parameters[j]))

tests/test_reducedordermodel.py

@@ -56,6 +56,15 @@ def test_loo_error(self):
             np.array([421.299091, 344.571787,  48.711501, 300.490491]),
             rtol=1e-4)
 
+    def test_loo_error_singular_values(self):
+        pod = POD()
+        rbf = RBF()
+        db = Database(param, snapshots.T)
+        rom = ROM(db, pod, rbf).fit()
+        valid_svalues = rom.reduction.singular_values
+        rom.loo_error()
+        np.testing.assert_allclose(valid_svalues, rom.reduction.singular_values)
+
     def test_optimal_mu(self):
         pod = POD()
         rbf = RBF()