add results for extraction of paths at last iteration

results/result_exploitation.py

@@ -61,26 +61,3 @@ plt.ylabel("Temps d'exécution (s)")
 plt.title("Temps d'exécution de la routine d'optimisation\npour un problème 256*256*256 avec 10 générations de 64 fourmis.")
 plt.legend()
 plt.show()
-
-
-###########################################################################
-## Test stability of the code
-###########################################################################
-
-for i in range(1, 7):
-    throughputs = []
-    iter_list = []
-    iter = 1
-    with open(f"16np_32ants_400iter/cost_opti_16np_32ants_400iter_{i}.txt", 'r') as file:
-        for line in file:
-            cost = float(line.strip("\n"))
-            throughputs.append(cost)
-            iter_list.append(iter)
-            iter +=1
-        plt.plot(iter_list, throughputs, '*-', label=f"Batch {i}")
-
-plt.title("Résulats de plusiseurs batchs pour 400 générations de 32 fourmis sur 16 process.")
-plt.xlabel("Iteration")
-plt.ylabel("Throughput optimal (MPoint/s)")
-plt.legend()
-plt.show()

results/stability_test.py

+import matplotlib.pyplot as plt
+import math
+
+###########################################################################
+## Test stability of the code
+###########################################################################
+
+for i in range(1, 7):
+    throughputs = []
+    iter_list = []
+    iter = 1
+    with open(f"16np_32ants_400iter/cost_opti_16np_32ants_400iter_{i}.txt", 'r') as file:
+        for line in file:
+            cost = float(line.strip("\n"))
+            throughputs.append(cost)
+            iter_list.append(iter)
+            iter +=1
+        plt.plot(iter_list, throughputs, '*-', label=f"Batch {i}")
+
+plt.title("Résulats de plusiseurs batchs pour 400 générations de 32 fourmis sur 16 process.")
+plt.xlabel("Iteration")
+plt.ylabel("Throughput optimal (MPoint/s)")
+plt.legend()
+plt.show()
+
+###########################################################################
+## Test stability of path at last iteration
+###########################################################################
+
+batches = [1, 2, 3, 4, 5, 6]
+fig, axs = plt.subplots(2, 3)
+max_nb_paths = 0
+width = 0.5
+
+for batch in batches:
+    paths = []
+    count = []
+    costs= []
+    with open(f"16np_32ants_400iter/result_16np_32ants_400iter_{batch}.out", "r") as file:
+        for line in file:
+            if line[0:4] == "Path":
+                iteration = int(line.split(" ")[4])
+                if iteration == 399:
+                    path = (line.split("[")[1]).split("]")[0]
+                    cost = -1*float((line.split(" ")[-1]).strip(".\n"))
+                    if path in paths:
+                        i = paths.index(path)
+                        count[i] +=1
+                        costs[i] += cost
+                    else:
+                        paths.append(path)
+                        count.append(1)
+                        costs.append(cost)
+    for i in range(len(paths)):
+        costs[i] = costs[i]/count[i]
+    costs, paths, count = map(list, zip(*sorted(zip(costs, paths, count), reverse=True)))
+    if len(paths) > max_nb_paths:
+        max_nb_paths = len(paths)
+    axs[(batch-1)%2, math.floor((batch-1)/2)].bar(range(len(paths)), count, width=width)
+    axs[(batch-1)%2, math.floor((batch-1)/2)].set_title(f"Batch {batch}")
+
+for batch in batches:
+    axs[(batch-1)%2, math.floor((batch-1)/2)].set_xlim(-2*width, max_nb_paths + 2*width)
+axs[0, 0].set_ylabel("Nombre de fourmis par chemin")
+axs[0, 0].set_xlabel("Chemins triés par throughput décroissant")
+fig.suptitle("Chemins suivis à la dernière itération pour différents batchs.")
+fig.tight_layout(pad=0.5)
+plt.show()
+plt.close(10)
\ No newline at end of file