def test_inverse_transform():
"""tests inverse_transform"""
def norm(x):
return (x - np.min(x)) / (np.max(x) - np.min(x))
X, y = make_moons(100)
X = norm(X)
embedder = ParametricUMAP(parametric_reconstruction=True)
embedding = embedder.fit_transform(X)
Z = embedder.transform(X)
X_r = embedder.inverse_transform(Z)
def test_inverse_transform(moon_dataset):
"""tests inverse_transform"""
def norm(x):
return (x - np.min(x)) / (np.max(x) - np.min(x))
X = norm(moon_dataset)
embedder = ParametricUMAP(parametric_reconstruction=True)
Z = embedder.fit_transform(X)
X_r = embedder.inverse_transform(Z)
# completes successfully
assert X_r is not None
assert X_r.shape == X.shape
