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()
