parameters: (meta_game, per_player_repeats, ignore_repeats=False,
                    epsilon=0.01)
return_statement: return dist, dict()
docstring: Maximum Gini CCE.
docstring_summary: Maximum Gini CCE.
docstring_tokens: Maximum Gini CCE .
function: def _approx_mgcce(meta_game, per_player_repeats, ignore_repeats=False,
                    epsilon=0.01):
    """Maximum Gini CCE."""
    a_mat, meta = _cce_constraints(
        meta_game, [0.0] * len(per_player_repeats), remove_null=True,
        zero_tolerance=1e-8)
    max_ab = 0.0
    if a_mat.size:
      max_ab = np.max(a_mat.mean(axis=1))
    a_mat, meta = _cce_constraints(
        meta_game, [epsilon * max_ab] * len(per_player_repeats), remove_null=True,
        zero_tolerance=1e-8)
    a_mats = _partition_by_player(
        a_mat, meta["p_vec"], len(per_player_repeats))
    dist, _ = _try_two_solvers(
        _qp_cce,
        meta_game, a_mats, [0.0] * len(per_player_repeats),
        action_repeats=(None if ignore_repeats else per_player_repeats))
    return dist, dict()
function_tokens: def _approx_mgcce ( meta_game , per_player_repeats , ignore_repeats = False , epsilon = 0.01 ) : a_mat , meta = _cce_constraints ( meta_game , [ 0.0 ] * len ( per_player_repeats ) , remove_null = True , zero_tolerance = 1e-8 ) max_ab = 0.0 if a_mat . size : max_ab = np . max ( a_mat . mean ( axis = 1 ) ) a_mat , meta = _cce_constraints ( meta_game , [ epsilon * max_ab ] * len ( per_player_repeats ) , remove_null = True , zero_tolerance = 1e-8 ) a_mats = _partition_by_player ( a_mat , meta [ "p_vec" ] , len ( per_player_repeats ) ) dist , _ = _try_two_solvers ( _qp_cce , meta_game , a_mats , [ 0.0 ] * len ( per_player_repeats ) , action_repeats = ( None if ignore_repeats else per_player_repeats ) ) return dist , dict ( )