How to use the tigramite.data_processing._get_lag_connect_matrix function in tigramite

stab_params = dict()
    # Define the unstable parameter set
    unst_params = dict()
    # Get the dimensionality and coefficient
    max_delay, unst_coef, message = request.param
    # Loop over all possible delays from this max delay
    for delay in range(max_delay):
        for a_params, a_coef in zip([stab_params, unst_params],
                                    [stab_coef, unst_coef]):
            node_id = delay
            # Correlate each node with the 0th node, using a stable coefficient
            a_params[node_id] = [((0, -delay), stab_coef)]
            # Autocorrelate each node N with delay N and the given coefficient
            a_params[node_id] = [((node_id, -delay), a_coef)]
    # Return the stable and unstable coefficients
    return pp._get_lag_connect_matrix(stab_params),\
           pp._get_lag_connect_matrix(unst_params),\
           message

# Define the unstable parameter set
    unst_params = dict()
    # Get the dimensionality and coefficient
    max_delay, unst_coef, message = request.param
    # Loop over all possible delays from this max delay
    for delay in range(max_delay):
        for a_params, a_coef in zip([stab_params, unst_params],
                                    [stab_coef, unst_coef]):
            node_id = delay
            # Correlate each node with the 0th node, using a stable coefficient
            a_params[node_id] = [((0, -delay), stab_coef)]
            # Autocorrelate each node N with delay N and the given coefficient
            a_params[node_id] = [((node_id, -delay), a_coef)]
    # Return the stable and unstable coefficients
    return pp._get_lag_connect_matrix(stab_params),\
           pp._get_lag_connect_matrix(unst_params),\
           message