all snake_case

report.csv

@@ -1,12 +1,11 @@
 iterations,temps,distance,temperature,memory
-5000,27.38643765449524,30585.351928539098,0.6721111959865606,57221120
-10000,34.95672869682312,24959.320052117782,0.4520495689035214,78159872
-15000,42.36410355567932,22355.65496850863,0.3038679424228721,78770176
-20000,49.582820653915405,20586.442074826,0.20426018026358692,79192064
-25000,57.07359457015991,19330.841251950715,0.13730379357770844,79192064
-30000,64.29938006401062,18378.562686813006,9.23079397837336,79192064
-35000,71.69990468025208,17738.866524289828,6.204944249678936,79630336
-40000,78.93442893028259,17125.53794647948,4.170966574687698,79630336
-45000,86.24125695228577,16833.02906081847,2.8037257817525405,79630336
-50000,93.65385031700134,16518.501560679957,1.8846658486714118,79896576
-55000,101.00880336761475,16066.872733874745,1.2668733098884215,80166912
+5000,1.199178695678711,493.3990958005079,0.6721111959865606,56467456
+10000,1.9728262424468994,422.7406518985165,0.4520495689035214,70680576
+15000,2.555943727493286,422.7406518985165,0.3038679424228721,70975488
+20000,3.1493828296661377,419.07264385271634,0.20426018026358692,71512064
+25000,3.7523446083068848,419.07264385271634,0.13730379357770844,71782400
+30000,4.338656902313232,419.07264385271634,9.23079397837336,71782400
+35000,4.923287868499756,419.07264385271634,6.204944249678936,71782400
+40000,5.569959878921509,419.07264385271634,4.170966574687698,72101888
+45000,6.152648687362671,419.07264385271634,2.8037257817525405,72101888
+50000,6.784815311431885,419.07264385271634,1.8846658486714118,72368128

sa.py

@@ -125,22 +125,22 @@ def SA(cities, temperatures):
             [i,j] = sorted(random.sample(range(city_count),2))
             newTour = tour[:i] + tour[j:j+1] + tour[i+1:j] + tour[i:i+1] + tour[j+1:]
 
-            oldDistances = distance_between(tour, cities, i, j)
-            newDistances = distance_between(newTour, cities, i, j)
-            newTotalDist = distance(newTour, cities)
+            old_distances = distance_between(tour, cities, i, j)
+            new_distances = distance_between(newTour, cities, i, j)
+            new_tour_distance = distance(newTour, cities)
 
-            if math.exp( (oldDistances - newDistances) / temperature) > random.random():
+            if math.exp( (old_distances - new_distances) / temperature) > random.random():
                 tour = copy.copy(newTour)
 
-            if newTotalDist < lowest_distance:
-                lowest_distance = newTotalDist
+            if new_tour_distance < lowest_distance:
+                lowest_distance = new_tour_distance
                 lowest_tour = copy.copy(tour)
 
             if(iteration % 5000 == 0):
                 seconds_elapsed = time.time() - time_start
                 print("Iteration: " + str(iteration))
                 print("Elapsed: {:10.4f}s".format(seconds_elapsed))
-                print("New distance: {:10.4f}".format(newTotalDist))
+                print("New distance: {:10.4f}".format(new_tour_distance))
                 print("Best distance: {:10.4f}".format(lowest_distance))
                 print("Temperature: " + str(temperature))
                 print("Memory used: " + str(memory().rss))