Merge branch 'fix_intercept_SqrtLasso' of https://github.com/PascalCarrivain/skglm into fix_intercept_SqrtLasso

Author: PascalCarrivain

skglm/experimental/tests/test_sqrt_lasso.py

@@ -31,7 +31,7 @@ def test_vs_statsmodels():
     n_alphas = 3
     alphas = alpha_max * np.geomspace(1, 1e-2, n_alphas+1)[1:]
 
-    sqrt_lasso = SqrtLasso(tol=1e-9)
+    sqrt_lasso = SqrtLasso(tol=1e-9, fit_intercept=False)
     coefs_skglm = sqrt_lasso.path(X, y, alphas)[1]
 
     coefs_statsmodels = np.zeros((len(alphas), n_features))
@@ -54,7 +54,7 @@ def test_prox_newton_cp():
 
     alpha_max = norm(X.T @ y, ord=np.inf) / norm(y)
     alpha = alpha_max / 10
-    clf = SqrtLasso(alpha=alpha, tol=1e-12).fit(X, y)
+    clf = SqrtLasso(alpha=alpha, fit_intercept=False, tol=1e-12).fit(X, y)
     w, _, _ = _chambolle_pock_sqrt(X, y, alpha, max_iter=1000)
     np.testing.assert_allclose(clf.coef_, w)
 
@@ -70,7 +70,7 @@ def test_PDCD_WS(with_dual_init):
     dual_init = y / norm(y) if with_dual_init else None
 
     w = PDCD_WS(dual_init=dual_init).solve(X, y, SqrtQuadratic(), L1(alpha))[0]
-    clf = SqrtLasso(alpha=alpha, tol=1e-12).fit(X, y)
+    clf = SqrtLasso(alpha=alpha, fit_intercept=False, tol=1e-12).fit(X, y)
     np.testing.assert_allclose(clf.coef_, w, atol=1e-6)