How to use the gseapy.plot.gseaplot function in gseapy

length = len(database.findAll('DTG'))
        fig_num = self.fignum if self.fignum <= length else length
        for idx in range(fig_num):
            # extract statistical resutls from results.edb file
            enrich_term, hit_ind, nes, pval, fdr= gsea_edb_parser(results_path, index=idx)
            gene_set = gene_set_dict.get(enrich_term)
            # calculate enrichment score
            RES = enrichment_score(gene_list=gene_list, 
                                   correl_vector=correl_vector,
                                   gene_set=gene_set, 
                                   weighted_score_type=self.weighted_score_type,
                                   nperm=0)[-1]
            # plotting
            term = enrich_term.replace('/','_').replace(":","_")
            outfile = '{0}/{1}.{2}.{3}'.format(self.outdir, term, self.module, self.format)
            gseaplot(rank_metric=rank_metric, term=enrich_term, 
                         hit_indices=hit_ind, nes=nes, pval=pval, fdr=fdr, 
                         RES=RES, pheno_pos=pos, pheno_neg=neg, 
                         figsize=self.figsize, ofname=outfile)

        self._logger.info("Congratulations! Your plots have been reproduced successfully!\n")

for i, temp in enumerate(tempes):
            name, rnk = names[i], rankings[i]
            self._logger.info("Calculate Enrichment Score for Sample: %s "%name)
            es, esnull, hit_ind, RES = temp.get()
            # create results subdir
            self.outdir= os.path.join(outdir, str(name))
            mkdirs(self.outdir)
            # save results
            self.resultsOnSamples[name] = pd.Series(data=es, index=subsets, name=name)
            # plotting
            if self._noplot: continue
            self._logger.info("Plotting Sample: %s \n" % name)
            for i, term in enumerate(subsets):
                term = term.replace('/','_').replace(":","_")
                outfile = '{0}/{1}.{2}.{3}'.format(self.outdir, term, self.module, self.format)
                gseaplot(rank_metric=rnk, term=term, 
                         hit_indices=hit_ind[i], nes=es[i], pval=1, fdr=1, 
                         RES=RES[i], pheno_pos='', pheno_neg='', 
                         figsize=self.figsize, ofname=outfile)
        # save es, nes to file
        self._save(outdir)

        return

if self._outdir is None: return
        #Plotting
        top_term = self.res2d.index[:graph_num]
        # multi-threading
        pool = Pool(self._processes)
        for gs in top_term:
            hit = results.get(gs)['hit_indices']
            NES = 'nes' if self.module != 'ssgsea' else 'es'
            term = gs.replace('/','_').replace(":","_")
            outfile = '{0}/{1}.{2}.{3}'.format(self.outdir, term, self.module, self.format)
            # gseaplot(rank_metric=rank_metric, term=term, hit_indices=hit,
            #           nes=results.get(gs)[NES], pval=results.get(gs)['pval'], 
            #           fdr=results.get(gs)['fdr'], RES=results.get(gs)['RES'],
            #           pheno_pos=pheno_pos, pheno_neg=pheno_neg, figsize=figsize,
            #           ofname=outfile)
            pool.apply_async(gseaplot, args=(rank_metric, term, hit, results.get(gs)[NES],
                                              results.get(gs)['pval'],results.get(gs)['fdr'],
                                              results.get(gs)['RES'],
                                              pheno_pos, pheno_neg, 
                                              figsize, 'seismic', outfile))
            if self.module == 'gsea':
                outfile2 = "{0}/{1}.heatmap.{2}".format(self.outdir, term, self.format)
                # heatmap(df=self.heatmat.iloc[hit, :], title=term, ofname=outfile2, 
                #         z_score=0, figsize=(self._width, len(hit)/2))
                pool.apply_async(heatmap, args=(self.heatmat.iloc[hit, :], 0, term, 
                                               (self._width, len(hit)/2+2), 'RdBu_r',
                                                True, True, outfile2))
        pool.close()
        pool.join()