def test_types(self, type_, kwargs):
X = np.random.uniform(size=(20, 3))
dX = type_(X, **kwargs)
qt = spp.QuantileTransformer()
qt.fit(X)
dqt = dpp.QuantileTransformer()
dqt.fit(dX)
def test_fit_transform_frame(self):
df = pd.DataFrame(np.random.randn(1000, 3))
ddf = dd.from_pandas(df, 2)
a = spp.QuantileTransformer()
b = dpp.QuantileTransformer()
expected = a.fit_transform(df)
result = b.fit_transform(ddf)
assert_eq_ar(result, expected, rtol=1e-3, atol=1e-3)
def test_basic(self):
rs = da.random.RandomState(0)
a = dpp.QuantileTransformer()
b = spp.QuantileTransformer()
X = rs.uniform(size=(100, 3), chunks=50)
a.fit(X)
b.fit(X)
assert_estimator_equal(a, b, atol=.02)
# set the quantiles, so that from here out, we're exact
a.quantiles_ = b.quantiles_
assert_eq_ar(a.transform(X), b.transform(X))
assert_eq_ar(X, a.inverse_transform(a.transform(X)))
