diff --git a/app/cocal_methods.py b/app/cocal_methods.py
index 3a5e7371a0ee66d11e25de43476ae12dcb5b88c1..3c5575b9d68921cd42f568e9c53cf7c34867545b 100644
--- a/app/cocal_methods.py
+++ b/app/cocal_methods.py
@@ -444,7 +444,19 @@ class CocalMethods:
         # )
 
         # visualize result
-        fig, ax = plt.subplots(1, 1, sharex=True, squeeze=False)
+        fig, ax = plt.subplots(nrows=1, ncols=1, sharex=True, squeeze=False, figsize=(8,5))
+        fig.suptitle("Transfer behavior in frequency domain")
+
+        # empirical TF
+        ax[0, 0].scatter(
+            self.ref_frequency[mask],
+            np.abs(h_empirical[mask]),
+            label="empirical TF",
+            s=2,
+            color="black",
+        )
+
+        # fitted TF
         ax[0, 0].plot(
             f[mask],
             np.abs(h[mask]),
@@ -459,13 +471,8 @@ class CocalMethods:
             label="unc of fitted TF",
             color="blue",
         )
-        ax[0, 0].scatter(
-            self.ref_frequency[mask],
-            np.abs(h_empirical[mask]),
-            label="empirical TF",
-            s=2,
-            color="black",
-        )
+
+        # compensated TF
         ax[0, 0].scatter(
             self.ref_frequency[mask],
             np.abs(h_comp[mask]),
@@ -481,12 +488,15 @@ class CocalMethods:
             label="unc of compensated TF",
             color="red",
         )
-
+        
+        # ideal
         ax[0, 0].plot(f, np.ones_like(f), "--r", label="ideal")
+
         ax[0, 0].legend()
         ax[0, 0].set_xscale("log")
         ax[0, 0].set_yscale("log")
-        plt.savefig(self.result_image_path)
+        fig.tight_layout()
+        fig.savefig(self.result_image_path)
         # plt.show()
 
     def perform_dummy_computations(self):