[fix] test your model

template/main.py

@@ -2,120 +2,10 @@ import os
 import signal
 import json
 
-from model.anneal_model import SimAnneal
+from utils.tsp import TSP
+from utils.tsp import TSP_Bench_ALL
 from model.my_model import MyModel
 
-def log(msg):
-    print('[*] {msg}'.format(msg=msg))
-
-def load_data(file):
-    coords = []
-    with open(file, "r") as infile:
-        line = infile.readline()
-        # Skip instance header
-        while "NODE_COORD_SECTION" not in line:
-            line = infile.readline()
-
-        for line in infile.readlines():
-            line = line.replace("\n", "")
-            if line and 'EOF' not in line:
-                line = [float(x) for x in line.lstrip().split(" ", 1)[1].split(" ") if x]
-                coords.append(line)
-    return coords
-
-def timeout_handler(signum, frame):
-    print("Timeout")
-    raise Exception("Timeout")
- 
-def TSP(tsp_file, model):
-
-    best_solution = []
-    fitness_list = []
-
-    coords = load_data(tsp_file)
-
-    # Set timeout
-    # signal.signal(signal.SIGALRM, timeout_handler)
-    # signal.alarm(60)
-
-    # Try your algorithm
-    try:
-        model.init(coords)
-        best_solution, fitness_list = model.fit(max_it=10000)
-    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")
-        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")
-
-    # Collect results
-    if(len(fitness_list) > 0):
-        log("Best: " + str(fitness_list[-1]))
-
-    if (len(best_solution) == 0):
-        log("No Answer -1")
-        with open('output/' + os.path.splitext(os.path.basename(tsp_file))[0] + '.txt', "w") as outfile:
-            outfile.write("-1")
-    elif (len(best_solution) != len(coords)):
-        log("Invalid -2")
-        with open('output/' + os.path.splitext(os.path.basename(tsp_file))[0] + '.txt', "w") as outfile:
-            outfile.write("-2")
-    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(coords)):
-            data['nodes'].append({
-                'title': str(i),
-                'id': i,
-                'x': int(coords[i][0]),
-                'y': int(coords[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)
-
-
 if __name__ == "__main__":
-
+    model = MyModel()
-    for root, _, files in os.walk('./data'):
+    TSP_Bench_ALL("./data", model)
-        if(files):
-            for f in files:
-                # Get input file name
-                tsp_file = str(root) + '/' + str(f)
-                log(tsp_file)
-
-                # Your Model
-                # model = MyModel()
-
-                # Simulated Annealing
-                model = SimAnneal()
-
-                TSP(tsp_file, model)
-
-                print()