k_means.py 文件源码

def find_nearest_point(points, p):
    # initialize
    minimal_distance = euclidean(p, points[0])
    minimal_distance_point_index = 0

    for i in range(1, len(points)):
        distance = euclidean(p, points[i])
        if distance < minimal_distance:
            minimal_distance = distance
            minimal_distance_point_index = i

    return minimal_distance_point_index, minimal_distance


# compute k-means cost function