@verbose
def _mixed_norm_solver_cd(M, G, alpha, lipschitz_constant, maxit=10000,
                          tol=1e-8, verbose=None, init=None, n_orient=1):
    """Solves L21 inverse problem with coordinate descent"""
    from sklearn.linear_model.coordinate_descent import MultiTaskLasso

    n_sensors, n_times = M.shape
    n_sensors, n_sources = G.shape

    if init is not None:
        init = init.T

    clf = MultiTaskLasso(alpha=alpha / len(M), tol=tol, normalize=False,
                         fit_intercept=False, max_iter=maxit,
                         warm_start=True)
    clf.coef_ = init
    clf.fit(G, M)

    X = clf.coef_.T
    active_set = np.any(X, axis=1)
    X = X[active_set]
    gap, pobj, dobj, _ = dgap_l21(M, G, X, active_set, alpha, n_orient)
    return X, active_set, pobj
dataset/ETHPy150Open mne-tools/mne-python/mne/inverse_sparse/mxne_optim.py/_mixed_norm_solver_cd/original