def run_kmeans(): # print(len(argv)) if len(argv) < 4: print( 'Not enough arguments provided. Please provide 3 arguments: K, num_iterations, path_to_input' ) exit(1) k = int(argv[1]) num_iterations = int(argv[2]) input_path = argv[3] if len(argv) == 5: random_seed = int(argv[4]) else: random_seed = 0 if k <= 1 or num_iterations <= 0: print('Please provide correct parameters') exit(1) if not os.path.exists(input_path): print('Input file does not exist') exit(1) points = load_data(input_path) if k >= len(points): print('Please set K less than size of dataset') exit(1) runner = KMeans(k, num_iterations) runner.run(points, random_seed) runner.print_results()
def run_kmeans(): list_seed = [1, 1, 1, 12, 12, 12] list_k = [3, 4, 5, 3, 4, 5] print("seed k sl1") for index, value_seed in enumerate(list_seed): k = list_k[index] num_iterations = 10 input_path = "colors_dataset_ready.txt" random_seed = value_seed if k <= 1 or num_iterations <= 0: print('Please provide correct parameters') exit(1) if not os.path.exists(input_path): print('Input file does not exist') exit(1) points = load_data(input_path) if k >= len(points): print('Please set K less than size of dataset') exit(1) runner = KMeans(k, num_iterations) runner.run(points, random_seed) print(list_seed[index], end=" ") print(list_k[index], end=" ") runner.print_results()