def _plot_confidence(self, canvas, helper_data, helper_prediction, label, **kwargs):
    _, free_dims, Xgrid, _, _, _, _, _ = helper_data
    update_not_existing_kwargs(kwargs, pl().defaults.confidence_interval)  # @UndefinedVariable
    if 1 <= len(free_dims):
        if len(free_dims)==1:
            percs = helper_prediction[1]
            fills = []
            for d in range(helper_prediction[0].shape[1]):
                fills.append(pl().fill_between(canvas, Xgrid[:,free_dims[0]], percs[0][:,d], percs[1][:,d], label=label, **kwargs))
            return dict(gpconfidence=fills)
        else:
            pass #Nothing to plot!
    else:
        raise RuntimeError('Can only plot confidence interval in one input dimension')
dataset/ETHPy150Open SheffieldML/GPy/GPy/plotting/gpy_plot/gp_plots.py/_plot_confidence/swapped operands of `<=`