Check that the correct number of weights is passed (#206)

Author: mathurinm

celer/group_fast.pyx

@@ -151,7 +151,8 @@ cpdef celer_grp(
         int[::1] X_indptr, floating[::1] X_mean, floating[:] y, floating alpha,
         floating[:] w, floating[:] R, floating[::1] theta,
         floating[::1] norms_X_grp, floating tol, int max_iter, int max_epochs,
-        int gap_freq=10, floating tol_ratio_inner=0.3, int p0=100, bint prune=1, bint use_accel=1,
+        int gap_freq=10, floating tol_ratio_inner=0.3, int p0=100,
+        bint prune=1, bint use_accel=1,
         bint verbose=0):
 
     pb = LASSO

celer/homotopy.py

@@ -183,10 +183,14 @@ def celer_path(X, y, pb, eps=1e-3, n_alphas=100, alphas=None,
     X_dense, X_data, X_indices, X_indptr = _sparse_and_dense(X)
 
     if weights is None:
-        weights = np.ones(n_groups) if pb == GRPLASSO else np.ones(n_features)
-        weights = weights.astype(X.dtype)
+        weights = np.ones(n_features).astype(X.dtype)
     elif (weights <= 0).any():
         raise ValueError("0 or negative weights are not supported.")
+    elif weights.shape[0] != X.shape[1]:
+        raise ValueError(
+            "As many weights as features must be passed. "
+            f"Expected {X.shape[1]}, got {weights.shape[0]}."
+        )
 
     if alphas is None:
         if pb == LASSO:

celer/lasso_fast.pyx

@@ -217,8 +217,6 @@ def celer(
                 scal = dnorm_l1(
                     is_sparse, theta_in, X, X_data, X_indices, X_indptr,
                     notin_WS, X_mean, weights, center, positive)
-                # print(scal)
-                # print(np.linalg.norm(np.asarray(X)[:, np.asarray(C)].T @ np.asarray(theta_in), ord=np.inf))
 
                 if scal > 1. :
                     tmp = 1. / scal