def analyze_internal_angles(self, return_plot=False):
        """Analyze the internal angles of the grid. Angles shouldn't be too
        small because this can cause problems/uncertainties in the
        Finite-Element solution of the forward problem. This function prints
        the min/max values, as well as quantiles, to the command line, and can
        also produce a histogram plot of the angles.

        Parameters
        ----------
        return_plot: bool
            if true, return (fig, ax) objects of the histogram plot

        Returns
        -------
        fig: matplotlib.figure
            figure object
        ax: matplotlib.axes
            axes object

        Examples
        --------

            >>> import crtomo.grid as CRGrid
                grid = CRGrid.crt_grid()
                grid.load_elem_file('elem.dat')
                fig, ax = grid.analyze_internal_angles(Angles)
            This grid was sorted using CutMcK. The nodes were resorted!
            Triangular grid found
            Minimal angle: 22.156368696965796 degrees
            Maximal angle: 134.99337326279496 degrees
            Angle percentile 10%: 51.22 degrees
            Angle percentile 20%: 55.59 degrees
            Angle percentile 30%: 58.26 degrees
            Angle percentile 40%: 59.49 degrees
            Angle percentile 50%: 59.95 degrees
            Angle percentile 60%: 60.25 degrees
            Angle percentile 70%: 61.16 degrees
            Angle percentile 80%: 63.44 degrees
            Angle percentile 90%: 68.72 degrees
            generating plot...
            >>> # save to file with
                fig.savefig('element_angles.png', dpi=300)

        """
        angles = self.get_internal_angles().flatten()

        print('Minimal angle: {0} degrees'.format(np.min(angles)))
        print('Maximal angle: {0} degrees'.format(np.max(angles)))
        # print out quantiles
        for i in range(10, 100, 10):
            print('Angle percentile {0}%: {1:0.2f} degrees'.format(
                i,
                np.percentile(angles, i),
            ))

        if return_plot:
            print('generating plot...')
            fig, ax = plt.subplots(1, 1, figsize=(12 / 2.54, 8 / 2.54))
            ax.hist(angles, int(angles.size / 10))
            ax.set_xlabel('angle [deg]')
            ax.set_ylabel('count')
            fig.tight_layout()
            # fig.savefig('plot_element_angles.jpg', dpi=300)
            return fig, ax
Analyze the internal angles of the grid. Angles shouldn't be too
        small because this can cause problems/uncertainties in the
        Finite-Element solution of the forward problem. This function prints
        the min/max values, as well as quantiles, to the command line, and can
        also produce a histogram plot of the angles.

        Parameters
        ----------
        return_plot: bool
            if true, return (fig, ax) objects of the histogram plot

        Returns
        -------
        fig: matplotlib.figure
            figure object
        ax: matplotlib.axes
            axes object

        Examples
        --------

            >>> import crtomo.grid as CRGrid
                grid = CRGrid.crt_grid()
                grid.load_elem_file('elem.dat')
                fig, ax = grid.analyze_internal_angles(Angles)
            This grid was sorted using CutMcK. The nodes were resorted!
            Triangular grid found
            Minimal angle: 22.156368696965796 degrees
            Maximal angle: 134.99337326279496 degrees
            Angle percentile 10%: 51.22 degrees
            Angle percentile 20%: 55.59 degrees
            Angle percentile 30%: 58.26 degrees
            Angle percentile 40%: 59.49 degrees
            Angle percentile 50%: 59.95 degrees
            Angle percentile 60%: 60.25 degrees
            Angle percentile 70%: 61.16 degrees
            Angle percentile 80%: 63.44 degrees
            Angle percentile 90%: 68.72 degrees
            generating plot...
            >>> # save to file with
                fig.savefig('element_angles.png', dpi=300)