Plot a scatter plot of the inducing inputs.

    :param [int] which_indices: which input dimensions to plot against each other
    :param bool legend: whether to plot the legend on the figure
    :param plot_limits: the plot limits for the plot
    :type plot_limits: (xmin, xmax, ymin, ymax) or ((xmin, xmax), (ymin, ymax))
    :param str marker: marker to use [default is custom arrow like]
    :param kwargs: the kwargs for the scatter plots
    :param str projection: for now 2d or 3d projection (other projections can be implemented, see developer documentation)

def plot_latent_inducing(self,
                        which_indices=None,
                        legend=False,
                        plot_limits=None,
                        marker=None,
                        projection='2d',
                        **kwargs):
    """
    Plot a scatter plot of the inducing inputs.

    :param [int] which_indices: which input dimensions to plot against each other
    :param bool legend: whether to plot the legend on the figure
    :param plot_limits: the plot limits for the plot
    :type plot_limits: (xmin, xmax, ymin, ymax) or ((xmin, xmax), (ymin, ymax))
    :param str marker: marker to use [default is custom arrow like]
    :param kwargs: the kwargs for the scatter plots
    :param str projection: for now 2d or 3d projection (other projections can be implemented, see developer documentation)
    """
    canvas, projection, kwargs, sig_dims = _new_canvas(self, projection, kwargs, which_indices)

    if legend: label = 'inducing'
    else: label = None
    if marker is not None:
        kwargs['marker'] = marker
    update_not_existing_kwargs(kwargs, pl().defaults.inducing_2d)  # @UndefinedVariable
    from .data_plots import _plot_inducing
    scatters = _plot_inducing(self, canvas, sig_dims[:2], projection, label, **kwargs)
    return pl().add_to_canvas(canvas, dict(scatter=scatters), legend=legend)