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diff --git a/.coverage.DESKTOP-ATMEKSV.10052.XHqUUOFx b/.coverage.DESKTOP-ATMEKSV.10052.XHqUUOFx
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diff --git a/src/bayesvalidrox/post_processing/post_processing.py b/src/bayesvalidrox/post_processing/post_processing.py
index 6520a40f9f2393798f6b8abac026b9ed38fe33ca..50b32dbea7effb358a5e47835a9002efa97587c8 100644
--- a/src/bayesvalidrox/post_processing/post_processing.py
+++ b/src/bayesvalidrox/post_processing/post_processing.py
@@ -244,14 +244,14 @@ class PostProcessing:
                             " of samples!")
 
         # Generate random samples if necessary
-        Samples = self._get_sample() if samples is None else samples
+        samples = self._get_sample() if samples is None else samples
 
         # Run the original model with the generated samples
         if outputs is None:
-            outputs = self._eval_model(Samples, key_str='validSet')
+            outputs = self._eval_model(samples, key_str='validSet')
 
         # Run the PCE model with the generated samples
-        pce_outputs, _ = MetaModel.eval_metamodel(samples=Samples)
+        pce_outputs, _ = MetaModel.eval_metamodel(samples=samples)
 
         self.rmse = {}
         self.valid_error = {}
@@ -321,6 +321,7 @@ class PostProcessing:
 
             if len(name_util) == 0:
                 continue
+            print(seq_dict)
 
             # Box plot when Replications have been detected.
             if any(int(name.split("rep_", 1)[1]) > 1 for name in name_util):
@@ -493,6 +494,8 @@ class PostProcessing:
                         seq_values = np.nan_to_num(seq_values)
 
                         # Plot the error evolution for each output
+                        print(x_idx.shape)
+                        print(seq_values.mean(axis=1).shape)
                         plt.semilogy(x_idx, seq_values.mean(axis=1),
                                      marker=markers[idx], ls='--', lw=2,
                                      color=colors[idx],