diff --git a/src/suite.py b/src/suite.py
index f892703..3725deb 100644
--- a/src/suite.py
+++ b/src/suite.py
@@ -360,9 +360,7 @@ class CVSuite:
         # Normalise data using loaded scalers
         for idx, value in enumerate(data):
             d = np.array(value)
-            data[idx] = self.scaler[idx].transform(d.astype(np.float32).reshape(1, -1))[
-                0
-            ][0]
+            data[idx] = self.scaler[idx].transform(d.astype(np.float32).reshape(1, -1))[0][0]
 
         data = np.array([data], dtype=np.float32)
 
@@ -397,13 +395,19 @@ class CVSuite:
                 modelnr = (idx * 2) + idy
                 guesses = self.models[modelnr][2]
                 
+                for guess in guesses:
+                    print(guess)
+                
                 # Convert guess array
                 tag_true = [guess[0] for guess in guesses ]
                 tag_predict = [guess[1] for guess in guesses ]
                 
                 labels = [Tree(tag).name for tag in range(0, 8)]
                 
-                sns.heatmap(confusion_matrix(tag_true, tag_predict), xticklabels=labels, yticklabels=labels, ax=graph, annot=True, cbar=False, fmt='g')
+                cm = confusion_matrix(tag_true, tag_predict)
+                cmn = cmn = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]
+                sns.heatmap(cmn, xticklabels=labels, yticklabels=labels, ax=graph, annot=True, cbar=False, fmt='.2f')
+                
                 graph.set_title(self.models[modelnr][0])
                 graph.set_xlabel("Predicted")
                 graph.set_ylabel("Actual")
@@ -508,7 +512,7 @@ class CVSuite:
                 img_sobel = img_gray
 
             self.canvas.add(img_sobel, "Sobel_edge")
-            self.log.add("Sobel nonzero", cv2.countNonZero(img_sobel))
+            # self.log.add("Sobel nonzero", cv2.countNonZero(img_sobel))
 
             # Canny edge
             img_canny = cv2.Canny(image=img_blur, threshold1=ct1, threshold2=ct2)
@@ -551,8 +555,9 @@ class CVSuite:
 
             # Write results to CSV file
             if not part_update:
-                self.runTest(self.log.data)
-                self.drawConfusionMatrix()
+                if self.models != []:
+                    self.runTest(self.log.data)
+                    self.drawConfusionMatrix()
                 
                 self.log.update()
             else: