def test_krandinit(self):
data = TESTDATA_2D
datas = [data.reshape((200, 2)), data.reshape((20, 20))[:10]]
k = int(1e6)
for data in datas:
np.random.seed(1234)
init = _krandinit(data, k)
orig_cov = np.cov(data, rowvar=0)
init_cov = np.cov(init, rowvar=0)
assert_allclose(orig_cov, init_cov, atol=1e-2)
def test_krandinit(self):
data = TESTDATA_2D
datas = [data.reshape((200, 2)), data.reshape((20, 20))[:10]]
k = int(1e6)
for data in datas:
np.random.seed(1234)
init = _krandinit(data, k)
orig_cov = np.cov(data, rowvar=0)
init_cov = np.cov(init, rowvar=0)
assert_allclose(orig_cov, init_cov, atol=1e-2)
def test_krandinit(self):
data = TESTDATA_2D
datas = [data.reshape((200, 2)), data.reshape((20, 20))[:10]]
k = int(1e6)
for data in datas:
# check that np.random.Generator can be used (numpy >= 1.17)
if hasattr(np.random, 'default_rng'):
rng = np.random.default_rng(1234)
else:
rng = np.random.RandomState(1234)
init = _krandinit(data, k, rng)
orig_cov = np.cov(data, rowvar=0)
init_cov = np.cov(init, rowvar=0)
assert_allclose(orig_cov, init_cov, atol=1e-2)