def max_average_ball2():
sample_number, k, r = 2 ** 10, 2, 4
data_2d = np.random.randint(0, 500, (sample_number, 2))
artificial_cluster_size = 2 ** 6
artificial_cluster = np.random.randint(100, 130, (artificial_cluster_size, 2))
data_2d = np.vstack((data_2d, artificial_cluster))
sample_number += artificial_cluster_size
mat = __distances__(data_2d)
t = 50
# closest = np.sum(mat, axis=1).argsort()[t:]
return __max_average_ball__(r, mat, t)
def max_average_ball2():
sample_number, k, r = 2**10, 2, 4
data_2d = np.random.randint(0, 500, (sample_number, 2))
artificial_cluster_size = 2**6
artificial_cluster = np.random.randint(100, 130,
(artificial_cluster_size, 2))
data_2d = np.vstack((data_2d, artificial_cluster))
sample_number += artificial_cluster_size
mat = __distances__(data_2d)
t = 50
# closest = np.sum(mat, axis=1).argsort()[t:]
return __max_average_ball__(r, mat, t)
def distances():
data = np.random.normal(0, 5, (10, 2))
mat = __distances__(data)
plt.scatter(*zip(*data))
return mat
def distances():
data = np.random.normal(0, 5, (10, 2))
mat = __distances__(data)
plt.scatter(*zip(*data))
return mat
