[new] Different test time for different problems

template/utils/tsp.py

@@ -1,147 +0,0 @@
-import os
-import signal
-import json
-import math
-import timeit
-
-from utils.load_data import load_data
-from utils.load_data import log
-
-def timeout_handler(signum, frame):
-    raise Exception("Timeout")
-
-def dist(node_0, node_1, coords):
-        """
-        Euclidean distance between two nodes.
-        """
-        coord_0, coord_1 = coords[node_0], coords[node_1]
-        return math.sqrt((coord_0[0] - coord_1[0]) ** 2 + (coord_0[1] - coord_1[1]) ** 2)
-
-def fitness(solution, coords):
-    N = len(coords)
-    if(len(solution) != N):
-        return math.inf
-    cur_fit = 0
-    for i in range(len(solution)):
-        cur_fit += dist(solution[i % N], solution[(i + 1) % N], coords)
-    return cur_fit
-
-def TSP_Bench(tsp_file, model, *args, max_it=1000, timeout=60):
-
-    start = timeit.default_timer()
-
-    # Model Running
-    best_solution, fitness_list = TSP(tsp_file, model, *args, max_it=max_it,timeout=timeout)
-    # Model End
-
-    stop = timeit.default_timer()
-    print('[*] Running for: {time:.2f} seconds'.format(time=(stop - start)))
-
-    print()
-    return best_solution, fitness_list, (stop - start)
-
-def TSP_Bench_ALL(tsp_file_path, model, *args, max_it=1000, timeout=60):
-    best_solutions = []
-    fitness_lists = []
-    times = []
-    for root, _, files in os.walk(tsp_file_path):
-        if(files):
-            for f in files:
-                # Get input file name
-                tsp_file = str(root) + '/' + str(f)
-                log(tsp_file)
-
-                # Run TSP
-                best_solution, fitness_list, time = TSP_Bench(tsp_file, model, *args, max_it=max_it,timeout=timeout)
-                best_solutions.append(best_solution)
-                fitness_lists.append(fitness_lists)
-                times.append(time)
-
-    return best_solutions, fitness_lists, times
-
-def TSP(tsp_file, model, *args, max_it=1000, timeout=60):
-
-    best_solution = []
-    fitness_list = []
-
-    nodes = load_data(tsp_file)
-
-    model = model()
-    # Set timeout
-    signal.signal(signal.SIGALRM, timeout_handler)
-    signal.alarm(timeout)
-
-    if not os.path.exists('output'):
-        os.makedirs('output')
-
-    # Try your algorithm
-    try:
-        model.init(nodes, *args)
-        best_solution, fitness_list = model.fit(max_it)
-    except Exception as exc: 
-        if(str(exc) == "Timeout"):
-            log("Timeout -3")
-            with open('output/' + os.path.splitext(os.path.basename(tsp_file))[0] + '.txt', "w") as outfile:
-                outfile.write("-3")
-        elif (len(best_solution) == 0):
-            print(exec)
-            log("No Answer -1")
-            with open('output/' + os.path.splitext(os.path.basename(tsp_file))[0] + '.txt', "w") as outfile:
-                outfile.write("-1")
-        else:
-            print(exc)
-            log("Unkown -4")
-            with open('output/' + os.path.splitext(os.path.basename(tsp_file))[0] + '.txt', "w") as outfile:
-                outfile.write("-4")
-
-        best_solution = [-1] * len(nodes)
-        return best_solution, fitness_list
-    
-    signal.alarm(0)
-
-    # Collect results
-    if(len(fitness_list) > 0):
-        log("[Node] " + str(len(best_solution)) + ", [Best] " + str(fitness_list[fitness_list.index(min(fitness_list))]))
-
-    if (len(best_solution) != len(nodes)):
-        print(len(best_solution))
-        log("Invalid -2")
-        with open('output/' + os.path.splitext(os.path.basename(tsp_file))[0] + '.txt', "w") as outfile:
-            outfile.write("-2")
-        best_solution = [-1] * len(nodes)
-    else:
-        # log("Writing the best solution to file" )
-        with open('output/' + os.path.splitext(os.path.basename(tsp_file))[0] + '.txt', "w") as outfile:
-            outfile.write(str(model.fitness(best_solution)))
-            outfile.write("\n")
-            outfile.write(", ".join(str(item) for item in best_solution))
-
-        # Write to JSON
-        data = {}
-
-        data['nodes'] = []
-        for i in range(len(nodes)):
-            data['nodes'].append({
-                'title': str(i),
-                'id': i,
-                'x': int(nodes[i][0]),
-                'y': int(nodes[i][1])
-            })
-
-        data['edges'] = []
-        for i in range(len(best_solution)):
-            if i == len(best_solution)-1:
-                data['edges'].append({
-                    'source': best_solution[i],
-                    'target': best_solution[0]
-                })
-            else:
-                data['edges'].append({
-                    'source': best_solution[i],
-                    'target': best_solution[i+1]
-                })
-
-        with open('output/' + os.path.splitext(os.path.basename(tsp_file))[0] + '.json', 'w') as outfile:
-            json.dump(data, outfile)
-
-    return best_solution, fitness_list