def generate_mayavi_line_plot(self, srcid_sciclasses_list,
                                  use_linfit_segments=False,
                                  enable_mayavi2_interactive_gui=False):
        """ Generate a Mayavi mlab 3D plot which summarizes iterative
        classification of a TUTOR source over the number of epochs
        used/added.
        """
        # TODO: I would like to plot each sci class a different color
        #    - I should have each science class re-use a single number/color
        #    - I should label which science class by color, as Y axis labels
        # TODO: I will need to insert a 0 point onto arrays (for s[0]?)

        if enable_mayavi2_interactive_gui:
            from enthought.mayavi.scripts import mayavi2
            mayavi2.standalone(globals())
        from enthought.mayavi import mlab

        # scalar cut plane plotting module stuff:
        import enthought.mayavi
        from enthought.mayavi.modules.scalar_cut_plane import ScalarCutPlane
        
        epoch_ids = [0] # x
        class_groups = [0] # y
        probs = [0] # z
        styles = [0] # numbers used for coloring & glyph sizes

        used_final_classes = []
        i_srcid = 0
        for final_class in self.pars['interested_sci_classes']:
            if not finalclass_ordered_dict.has_key(final_class):
                continue # skip this science class since nothing to plot
            else:
                used_final_classes.append(final_class)
            srcid_sciclasses_list = finalclass_ordered_dict[final_class]
            for src_id,sci_classes in srcid_sciclasses_list:
                print 'src_id:', src_id, '\t', final_class
                sci_classes.generate_linearfit_endpoints_segments()
                i = 0
                for class_name,class_dict in sci_classes.class_dict.iteritems():
                    class_style = self.sciclass_style_dict[class_name]

                    if use_linfit_segments:
                        for segment_dict in class_dict['linfit_segments']:

                            epoch_ids.extend([segment_dict['epoch_ids'][0]])
                            class_groups.extend([i_srcid])
                            probs.extend([0])
                            styles.extend([0])

                            epoch_ids.extend(segment_dict['epoch_ids'])
                            class_groups.extend([i_srcid]*len(segment_dict['epoch_ids']))
                            probs.extend(segment_dict['probs'])
                            styles.extend([class_style]*len(segment_dict['epoch_ids']))
                            epoch_ids.extend([segment_dict['epoch_ids'][-1]])
                            class_groups.extend([i_srcid])
                            probs.extend([0])
                            styles.extend([0])
                    else:
                        epoch_ids.extend([class_dict['epoch_ids'][0]])
                        class_groups.extend([i_srcid])
                        probs.extend([0])
                        styles.extend([0])

                        epoch_ids.extend(class_dict['epoch_ids'])
                        class_groups.extend([i_srcid]*len(class_dict['epoch_ids']))
                        probs.extend(class_dict['probs'])
                        styles.extend([class_style]*len(class_dict['epoch_ids']))

                        epoch_ids.extend([class_dict['epoch_ids'][-1]])
                        class_groups.extend([i_srcid])
                        probs.extend([0])
                        styles.extend([0])
                    i += 1
                i_srcid += 3 # Y spacing between srcids within a science-class
            i_srcid += 20 # Y spacing between science-class groups
        mlab.plot3d(numpy.array(epoch_ids),
                    numpy.array(class_groups),
                    numpy.array(probs)*100.0,
                    numpy.array(styles),
                    colormap="Paired",
                    tube_radius=1)
        #            extent=[0,600,
        #                    0,i_srcid,
        #                    15, 110])

                    
        mlab.axes(xlabel='N of epochs',
                  ylabel='science class',
                  zlabel='% Prob.')#,
        # DEBUG/UPGRADE: These seem to trigger some bug about Actor methods:
        #          extent=[0,600,
        #                  0,i_srcid,
        #                  -10, 110])

        title_str = "num_srcids=%d   probability_cut=%0.2lf   factor_threshold=%0.2lf   bin_size=%d   poly_order=%d" % (\
                           self.pars['num_srcids_to_retrieve_plot'],
                           self.pars['sciclass_probability_cut'],
                           self.pars['polyfit_factor_threshold'],
                           self.pars['polyfit_bin_size'],
                           self.pars['polyfit_poly_order'])

        ##### TITLE:
        # The 'z' is a flag in Mayavi2 v3.1.0 documentation:
        #mlab.text(0.01, 0.97, title_str, width=1.0, name='title', z=0.0)
        mlab.text(0.01, 0.97, title_str, width=1.0, name='title')

        ##### SCIENCE CLASS LABELS:
        # TODO: Eventually I would like the class labels to be colored and
        #    placed on the y axis, but this requires:
        #     1) later mayavi version to allow 3D text positioning
        #     2) ability to match text color to the line color-map.
        if 1:
            used_final_classes.reverse()
            y = 0.95
            for class_name in used_final_classes:
                class_str = "%2d   %s" %(len(finalclass_ordered_dict[class_name]),
                                           class_name)
                mlab.text(0.85, y, class_str, width=0.095*(len(class_str)/20.0))
                y -= 0.018

        ##### Add a x-axis plane (I can't figure out code to make it opaque)
        if 0:
            cp = ScalarCutPlane()
            mayavi.add_module(cp)
            cp.implicit_plane._hideshow() # this un-displays the plane
            cp.implicit_plane.normal = 0,0,1
            cp.implicit_plane.origin = 150,168,15
            #cp.implicit_plane.position= 0.15 # feature not available yet
            print '##### cp:'
            cp.print_traits()
            print '##### cp.implicit_plane:'
            cp.implicit_plane.print_traits()
            print '##### cp.implicit_plane._HideShowAction:'
            cp.implicit_plane._HideShowAction.print_traits()

        ##### Camera position:
        if enable_mayavi2_interactive_gui:
            camera_distance = 600
        else:
            camera_distance = 1200
        enthought.mayavi.tools.camera.view(azimuth=50,
                                           elevation=70, # 0:looking down to -z
                                           distance=camera_distance,
                                           focalpoint=(100,(i_srcid*0.4),50))

        #enthought.mayavi.mlab.show_pipeline() # this introspecive feature is not available in current mayavi version.

        #####If no Mayavi2 GUI, we allow user to resize image before saving file
        if not enable_mayavi2_interactive_gui:
            print 'Please resize window & Press a Key.'
            import curses
            stdscr = curses.initscr()
            while 1:
                c = stdscr.getch()
                break
            curses.endwin()
        
        ##### Save figure:
        img_fpath ="/tmp/%s%s.png" %(title_str.replace('=','').replace(' ','_'),
                                     self.pars['save_plot_image_suffix'])
        if os.path.exists(img_fpath):
            os.system('rm ' + img_fpath)
        mlab.savefig(img_fpath)#, size=(500,500))#, dpi=200) #size flag doesn't do anything
        print "Saved:", img_fpath