diff --git a/src/bayesvalidrox/post_processing/post_processing.py b/src/bayesvalidrox/post_processing/post_processing.py
index 6e2ee60a26dcb0a2866a45e3b1cfa7bbac6178c3..7c8a3706ed49dba863030994b9d4f01ab003a75b 100644
--- a/src/bayesvalidrox/post_processing/post_processing.py
+++ b/src/bayesvalidrox/post_processing/post_processing.py
@@ -215,7 +215,9 @@ class PostProcessing:
 
         """
         if samples is None:
-            samples = self._get_sample(n_samples)
+            samples = self.engine.ExpDesign.generate_samples(
+            n_samples, sampling_method="random"
+        )
         else:
             n_samples = samples.shape[0]
 
@@ -272,7 +274,10 @@ class PostProcessing:
         n_samples = samples.shape[0] if samples is not None else n_samples
 
         # Generate random samples if necessary
-        samples = self._get_sample(n_samples) if samples is None else samples
+        if samples is None:
+            samples = self.engine.ExpDesign.generate_samples(
+            n_samples, sampling_method="random"
+        )
 
         # Run the original model with the generated samples
         if outputs is None:
@@ -814,13 +819,15 @@ class PostProcessing:
             Output dictionary with model outputs for all given output types in
             `engine.out_names`. The default is None.
 
-        Return
-        ------
-        None
+        Returns
+        -------
+        None.
 
         """
         if samples is None:
-            samples = self._get_sample(n_samples)
+            samples = self.engine.ExpDesign.generate_samples(
+            n_samples, sampling_method="random"
+        )
         else:
             n_samples = samples.shape[0]
 
@@ -973,28 +980,6 @@ class PostProcessing:
                 )
                 plt.close(fig)
 
-    # -------------------------------------------------------------------------
-
-    def _get_sample(self, n_samples):
-        """
-        Generates random samples taken from the input parameter space.
-
-        Parameters
-        ----------
-        n_samples : int
-            Number of samples to generate.
-
-        Returns
-        -------
-        samples : array of shape (n_samples, n_params)
-            Generated samples.
-
-        """
-        samples = self.engine.ExpDesign.generate_samples(
-            n_samples, sampling_method="random"
-        )
-        return samples
-
     # -------------------------------------------------------------------------
     def _plot_validation(self):
         """