How to use the refinem.plots.gc_plots.GcPlots function in refinem

axes_pc1_cov = self.fig.add_subplot(247)
            axes_tetra_pc1_pc3 = self.fig.add_subplot(248)  
            axes_gc_coverage = self.fig.add_subplot(245)
            axes_tetra_pc1_pc2 = self.fig.add_subplot(244)            
        else:
            # note: the ordering here is specific and ensures
            # proper linked brushing
            axes_gc_dist = self.fig.add_subplot(231)
            axes_tetra_dist = self.fig.add_subplot(234)
            axes_deltaGC_td = self.fig.add_subplot(232)
            axes_pc1_td = self.fig.add_subplot(235)
            axes_tetra_pc1_pc2 = self.fig.add_subplot(233)
            axes_tetra_pc1_pc3 = self.fig.add_subplot(236)

        # create plots
        gc_plots = GcPlots(self.options)
        scatter, delta_gc, seq_len, label_plot_order = gc_plots.plot_on_axes(self.fig,
                                                                    genome_scaffold_stats,
                                                                    highlight_scaffold_ids,
                                                                    link_scaffold_ids,
                                                                    genome_stats.mean_gc,
                                                                    gc_dist,
                                                                    [gc_perc],
                                                                    None,
                                                                    axes_gc_dist,
                                                                    True)
                                                                                                     
        td_plots = TdPlots(self.options)
        _scatter, td, _, _ = td_plots.plot_on_axes(self.fig,
                                                    genome_scaffold_stats,
                                                    highlight_scaffold_ids,
                                                    link_scaffold_ids,

# create subplots depending on availability of coverage information
        if len(genome_stats.mean_coverage) >= 1:
            axes_hist_GC = self.fig.add_subplot(321)
            axes_scatter_GC = self.fig.add_subplot(322)
            axes_hist_TD = self.fig.add_subplot(323)
            axes_scatter_TD = self.fig.add_subplot(324)
            axes_hist_cov_perc = self.fig.add_subplot(325)
            axes_scatter_cov_perc = self.fig.add_subplot(326)
        else:
            axes_hist_GC = self.fig.add_subplot(221)
            axes_scatter_GC = self.fig.add_subplot(222)
            axes_hist_TD = self.fig.add_subplot(223)
            axes_scatter_TD = self.fig.add_subplot(224)

        gc_plots = GcPlots(self.options)
        scatter, _, _, _ = gc_plots.plot_on_axes(self.fig,
                                                    genome_scaffold_stats,
                                                    highlight_scaffold_ids,
                                                    link_scaffold_ids,
                                                    genome_stats.mean_gc,
                                                    gc_dist,
                                                    [gc_perc],
                                                    axes_hist_GC,
                                                    axes_scatter_GC,
                                                    True)

        td_plots = TdPlots(self.options)
        td_plots.plot_on_axes(self.fig,
                                genome_scaffold_stats,
                                highlight_scaffold_ids,
                                link_scaffold_ids,

genomes_processed,
                                        len(genome_stats),
                                        genomes_processed * 100.0 / len(genome_stats)))
                sys.stdout.flush()

            genome_scaffold_stats = {}
            for scaffold_id in scaffold_stats.scaffolds_in_genome[genome_id]:
                genome_scaffold_stats[scaffold_id] = scaffold_stats.stats[scaffold_id]
                
            if len(genome_scaffold_stats) <= 1:
                self.logger.info('Skipping plots for {} as it contains only {:,} contigs.'.format(genome_id, len(genome_scaffold_stats)))
                continue
                
            if individual_plots:
                # GC plot
                gc_plots = GcPlots(plot_options)
                gc_plots.plot(genome_scaffold_stats, 
                                highlight_scaffolds_ids, 
                                link_scaffold_ids, 
                                gs.mean_gc, 
                                gc_dist, 
                                [plot_options.gc_perc])

                output_plot = os.path.join(output_dir, genome_id + '.gc_plots.' + plot_options.image_type)
                gc_plots.save_plot(output_plot, dpi=plot_options.dpi)
                gc_plots.save_html(os.path.join(output_dir, genome_id + '.gc_plots.html'))

                # TD plot
                td_plots = TdPlots(plot_options)
                td_plots.plot(genome_scaffold_stats, 
                                highlight_scaffolds_ids, 
                                link_scaffold_ids,