linter happy

Author: Badr-MOUFAD

skglm/solvers/group_prox_newton.py

@@ -68,7 +68,7 @@ def _solve(self, X, y, datafit, penalty, w_init=None, Xw_init=None):
         all_groups = np.arange(n_groups)
         stop_crit = 0.
         p_objs_out = []
-        
+
         # TODO: to be isolated in a seperated method
         is_sparse = issparse(X)
         if is_sparse:

skglm/solvers/prox_newton.py

@@ -84,7 +84,7 @@ def _solve(self, X, y, datafit, penalty, w_init=None, Xw_init=None):
         is_sparse = issparse(X)
         if is_sparse:
             X_bundles = (X.data, X.indptr, X.indices)
-            
+
         # TODO: to be isolated in a seperated method
         if is_sparse:
             datafit.initialize_sparse(X.data, X.indptr, X.indices, y)