How to use the adaptive.notebook_integration.ensure_plotly function in adaptive

This is the 3D analog of an isoline. Does *not* work with the
        `adaptive.notebook_integration.live_plot` functionality.

        Parameters
        ----------
        level : float, default: 0.0
            the function value which you are interested in.
        hull_opacity : float, default: 0.0
            the opacity of the hull of the domain.

        Returns
        -------
        plot : `plotly.offline.iplot` object
            The plot object of the isosurface.
        """
        plotly = ensure_plotly()

        vertices, faces = self._get_iso(level, which="surface")
        x, y, z = zip(*vertices)

        fig = plotly.figure_factory.create_trisurf(
            x=x, y=y, z=z, plot_edges=False, simplices=faces, title="Isosurface"
        )
        isosurface = fig.data[0]
        isosurface.update(
            lighting=dict(ambient=1, diffuse=1, roughness=1, specular=0, fresnel=0)
        )

        if hull_opacity < 1e-3:
            # Do not compute the hull_mesh.
            return plotly.offline.iplot(fig)

def _get_hull_mesh(self, opacity=0.2):
        plotly = ensure_plotly()
        hull = scipy.spatial.ConvexHull(self._bounds_points)

        # Find the colors of each plane, giving triangles which are coplanar
        # the same color, such that a square face has the same color.
        color_dict = {}

        def _get_plane_color(simplex):
            simplex = tuple(simplex)
            # If the volume of the two triangles combined is zero then they
            # belong to the same plane.
            for simplex_key, color in color_dict.items():
                points = [hull.points[i] for i in set(simplex_key + simplex)]
                points = np.array(points)
                if np.linalg.matrix_rank(points[1:] - points[0]) < 3:
                    return color
                if scipy.spatial.ConvexHull(points).volume < 1e-5:

"""Plot the learner's data in 3D using plotly.

        Does *not* work with the
        `adaptive.notebook_integration.live_plot` functionality.

        Parameters
        ----------
        with_triangulation : bool, default: False
            Add the verticices to the plot.

        Returns
        -------
        plot : `plotly.offline.iplot` object
            The 3D plot of ``learner.data``.
        """
        plotly = ensure_plotly()

        plots = []

        vertices = self.tri.vertices
        if with_triangulation:
            Xe, Ye, Ze = [], [], []
            for simplex in self.tri.simplices:
                for s in itertools.combinations(simplex, 2):
                    Xe += [vertices[i][0] for i in s] + [None]
                    Ye += [vertices[i][1] for i in s] + [None]
                    Ze += [vertices[i][2] for i in s] + [None]

            plots.append(
                plotly.graph_objs.Scatter3d(
                    x=Xe,
                    y=Ye,