Fixed normalized coverage

EIVPackage/EIVGeneral/coverage_metrices.py

@@ -64,8 +64,11 @@ def epistemic_coverage(prediction_triple,  y, q=0.95, normalize_errors=False):
         y = y.view((-1,1))
     assert y.shape == mean.shape
     # fix interval based on epis_unc
-    interval_length = multivariate_interval_length(dim=y.shape[1], q=q) \
-            * epis_unc
+    if not normalize_errors:
+        interval_length = multivariate_interval_length(dim=y.shape[1], q=q) \
+                * epis_unc
+    else:
+        interval_length = multivariate_interval_length(dim=y.shape[1], q=q) 
     total_unc = torch.sqrt(epis_unc**2 + aleat_unc **2)
     # numerical computation
     errors = mean - y