def test_merge():
t = TDigest()
t2 = TDigest()
t3 = TDigest()
a = np.random.uniform(0, 1, N)
b = np.random.uniform(2, 3, N)
data = np.concatenate([a, b])
t2.update(a)
t3.update(b)
t2_centroids = t2.centroids()
t.merge(t2, t3)
assert t.min() == min(t2.min(), t3.min())
assert t.max() == max(t2.max(), t3.max())
assert t.size() == t2.size() + t3.size()
# Check no mutation of args
assert (t2.centroids() == t2_centroids).all()
# *Quantile
q = np.array([0.001, 0.01, 0.1, 0.3, 0.5, 0.7, 0.9, 0.99, 0.999])
est = t.quantile(q)
q_est = quantiles_to_q(data, est)
np.testing.assert_allclose(q, q_est, atol=0.012, rtol=0)
# *CDF
x = q_to_x(data, q)
q_est = t.cdf(x)
np.testing.assert_allclose(q, q_est, atol=0.005)
with pytest.raises(TypeError):
t.merge(t2, 'not a tdigest')
def percentiles_from_tdigest(self, q, *digests):
# pylint: disable = import-outside-toplevel
from crick import TDigest
t = TDigest()
t.merge(*digests)
return np.array(t.quantile(q))
def _percentiles_from_tdigest(qs, digests):
from crick import TDigest
t = TDigest()
t.merge(*digests)
return np.array(t.quantile(qs / 100.0))
def _percentiles_from_tdigest(qs, digests):
from crick import TDigest
t = TDigest()
t.merge(*digests)
return np.array(t.quantile(qs / 100.0))