diff --git a/src/io_tsp.py b/src/io_tsp.py
index c1256cc..51b24e0 100644
--- a/src/io_tsp.py
+++ b/src/io_tsp.py
@@ -50,12 +50,13 @@ class ProblemInstance:
         print('best_sol: ' + str(self.best_sol))
         print('exist optimal: ' + str(self.exist_opt))
 
-    def plot_data(self):
+    def plot_data(self,show_numbers=False):
         plt.figure(figsize=(8, 8))
         plt.title(self.name)
         plt.scatter(self.points[:, 1], self.points[:, 2])
-        for i, txt in enumerate(np.arange(self.nPoints)):  # tour_found[:-1]
-            plt.annotate(txt, (self.points[i, 1], self.points[i, 2]))
+        if show_numbers:
+            for i, txt in enumerate(np.arange(self.nPoints)):  # tour_found[:-1]
+                plt.annotate(txt, (self.points[i, 1], self.points[i, 2]))
         plt.show()
 
     def create_dist_matrix(self):
diff --git a/src/utils.py b/src/utils.py
index e09ab5b..e6b90f8 100644
--- a/src/utils.py
+++ b/src/utils.py
@@ -11,7 +11,9 @@ def compute_length(solution, dist_matrix):
     return total_length
 
 
-def distance_euc(zi, zj):
-    xi, xj = zi[0], zj[0]
-    yi, yj = zi[1], zj[1]
-    return round(np.sqrt((xi - xj) ** 2 + (yi - yj) ** 2), 0)
+def distance_euc(point_i, point_j):
+    rounding=0
+    x_i, y_i = point_i[0], point_i[1]
+    x_j, y_j = point_j[0], point_j[1]
+    distance = np.sqrt((x_i - x_j) ** 2 + (y_i - y_j) ** 2)
+    return round(distance, rounding)