diff --git a/src/visuals/results.py b/src/visuals/results.py
index a647063..d21c2c7 100644
--- a/src/visuals/results.py
+++ b/src/visuals/results.py
@@ -1,5 +1,6 @@
 
 import os
+import time
 import numpy as np
 import matplotlib.pyplot as plt
 from matplotlib.patches import Ellipse
@@ -13,19 +14,20 @@ def print_results(dic_stats, show=False, save=False):
     Position error in meters due to a height variation of 7 cm (Standard deviation already knowing the sex)
     Position error not knowing the gender (13cm as average difference --> 7.5cm of error to add)
     """
+
+    # ALE figure
     dir_out = 'docs'
     phase = 'test'
     x_min = 0
     x_max = 38
     xx = np.linspace(0, 60, 100)
-    mm_std = 0.04
     mm_gender = 0.0556
     excl_clusters = ['all', '50', '>50', 'easy', 'moderate', 'hard']
     clusters = tuple([clst for clst in dic_stats[phase]['our'] if clst not in excl_clusters])
     yy_gender = target_error(xx, mm_gender)
     yy_gps = np.linspace(5., 5., xx.shape[0])
 
-    # Precision on same instances
+    plt.figure(0)
     fig_name = 'results.png'
     plt.xlabel("Distance [meters]")
     plt.ylabel("Average localization error [m]")
@@ -39,8 +41,7 @@ def print_results(dic_stats, show=False, save=False):
 
     plt.plot(xx, yy_gps, '-', label="GPS Error", color='y')
     for idx, method in enumerate(['m3d_merged', 'geom_merged', 'md_merged', 'our_merged', '3dop_merged']):
-        dic_errs = dic_stats[phase][method]['mean']
-        errs = get_values(dic_errs, clusters)
+        errs = [dic_stats[phase][method][clst]['mean'] for clst in clusters]
         xxs = get_distances(clusters)
 
         plt.plot(xxs, errs, marker=mks[idx], markersize=mksizes[idx], linewidth=lws[idx], label=labels[idx],
@@ -53,29 +54,19 @@ def print_results(dic_stats, show=False, save=False):
         plt.savefig(os.path.join(dir_out, fig_name))
     plt.close()
 
-    # FIGURE SPREAD
-    fig_name = 'spread.png'
-    # fig = plt.figure(3)
-    # ax = fig.add_subplot(1, 1, 1)
+    # SPREAD b Figure
+    plt.figure(1)
     fig, ax = plt.subplots(2, sharex=True)
     plt.xlabel("Distance [m]")
     plt.ylabel("Aleatoric uncertainty [m]")
     ar = 0.5  # Change aspect ratio of ellipses
     scale = 1.5  # Factor to scale ellipses
     rec_c = 0  # Center of the rectangle
-    # rec_h = 2.8  # Height of the rectangle
     plots_line = True
-    # ax[0].set_ylim([-3, 3])
-    # ax[1].set_ylim([0, 3])
-    # ax[1].set_ylabel("Aleatoric uncertainty [m]")
-    # ax[0].set_ylabel("Confidence intervals")
 
-    dic_ale = dic_stats[phase]['our']['std_ale']
-    bbs = np.array(get_values(dic_ale, clusters))
+    bbs = np.array([dic_stats[phase]['our'][key]['std_ale'] for key in clusters])
     xxs = get_distances(clusters)
     yys = target_error(np.array(xxs), mm_gender)
-    # ale_het = tuple(bbs - yys)
-    # plt.plot(xxs, ale_het, marker='s', label=method)
     ax[1].plot(xxs, bbs, marker='s', color='b', label="Spread b")
     ax[1].plot(xxs, yys,  '--', color='lightgreen', label="Task error", linewidth=2.5)
     yys_up = [rec_c + ar/2 * scale * yy for yy in yys]
@@ -94,7 +85,6 @@ def print_results(dic_stats, show=False, save=False):
         bi = Ellipse((xx, rec_c), width=bbs[idx]*ar*scale, height=scale, angle=90, color='b',linewidth=1.8,
                      fill=False)
 
-        # ax[0].add_patch(rectangle)
         ax[0].add_patch(te)
         ax[0].add_patch(bi)
 
@@ -107,10 +97,12 @@ def print_results(dic_stats, show=False, save=False):
 
 
 def target_error(xx, mm):
+    """Multiplication"""
     return mm * xx
 
 
 def get_distances(clusters):
+    """Extract distances as intermediate values between 2 clusters"""
 
     clusters_ext = list(clusters)
     clusters_ext.insert(0, str(0))
@@ -122,14 +114,6 @@ def get_distances(clusters):
     return tuple(distances)
 
 
-def get_values(dic_err, clusters):
-
-    errs = []
-    for key in clusters:
-        errs.append(dic_err[key])
-    return errs
-
-
 def get_confidence_points(confidences, distances, errors):
 
     confidence_points = []
@@ -142,4 +126,4 @@ def get_confidence_points(confidences, distances, errors):
         distance_points.append(dd)
         distance_points.append(dd)
 
-    return distance_points, confidence_points
\ No newline at end of file
+    return distance_points, confidence_points