def test_lasso_selection_sweep():
"""Tests uoi_selection_sweep for UoI_Lasso."""
# toy data
X = np.array([[-1, 2, 3], [4, 1, -7], [1, 3, 1], [4, 3, 12], [8, 11, 2]])
beta = np.array([1, 4, 2])
y = np.dot(X, beta)
# toy regularization
reg_param_values = [{'alpha': 1.0}, {'alpha': 2.0}]
lasso1 = Lasso(alpha=1.0, fit_intercept=True, normalize=True)
lasso2 = Lasso(alpha=2.0, fit_intercept=True, normalize=True)
lasso = UoI_Lasso(fit_intercept=True, normalize=True)
coefs = lasso.uoi_selection_sweep(X, y, reg_param_values)
lasso1.fit(X, y)
lasso2.fit(X, y)
assert np.allclose(coefs[0], lasso1.coef_)
assert np.allclose(coefs[1], lasso2.coef_)
def test_lasso_selection_sweep():
"""Tests uoi_selection_sweep for UoI_Lasso."""
# toy data
X = np.array([[-1, 2, 3], [4, 1, -7], [1, 3, 1], [4, 3, 12], [8, 11, 2]],
dtype=float)
beta = np.array([1, 4, 2], dtype=float)
y = np.dot(X, beta)
# toy regularization
reg_param_values = [{'alpha': 1.0}, {'alpha': 2.0}]
lasso = UoI_Lasso(fit_intercept=True, warm_start=False)
lasso1 = Lasso(alpha=1.0, fit_intercept=True, max_iter=lasso.max_iter)
lasso2 = Lasso(alpha=2.0, fit_intercept=True, max_iter=lasso.max_iter)
lasso.output_dim = 1
coefs = lasso.uoi_selection_sweep(X, y, reg_param_values)
lasso1.fit(X, y)
lasso2.fit(X, y)
assert np.allclose(coefs[0], lasso1.coef_)
assert np.allclose(coefs[1], lasso2.coef_)