How to use the gseapy.gsea function in gseapy

def run(data, gmt, cls, permutation_type='phenotype', method='signal_to_noise', permution_num=1000):
        prefix = gp.__name__ + "."
        for importer, modname, ispkg in pkgutil.iter_modules(gp.__path__, prefix):
            if modname == "gseapy.gsea":
                module = __import__(modname, fromlist="dummy")
        vs = gp.__version__.split(".")
        if int(vs[0]) == 0 and int(vs[1]) < 9:
            module.ranking_metric = GSEA._ranking_metric
        else:
            module.ranking_metric = GSEA._ranking_metric2
        gp.algorithm.ranking_metric = GSEA._ranking_metric
        res = gp.gsea(data, gmt, cls, permutation_type=permutation_type, permutation_num=permution_num,
                      outdir=os.path.join(os.path.dirname(os.path.realpath(__file__)), 'images'), method=method)
        return GSEA(res.res2d, data, gmt, cls)

def run_gsea(gene_exp: str, gene_set: str, phenotype_class: str, permutations: int = 500, output_dir: str = GSEA):
    """Run GSEA on a given dataset with a given gene set.

    :param gene_exp: file with gene expression data
    :param gene_set: gmt files containing pathway gene sets
    :param phenotype_class: cls file containing information on class labels
    :param permutations: number of permutations
    :param output_dir: output directory
    :return:
    """
    return gseapy.gsea(
        data=gene_exp,
        gene_sets=gene_set,
        cls=phenotype_class,  # cls=class_vector
        max_size=3000,
        # set permutation_type to phenotype if samples >=15
        permutation_type='phenotype',
        permutation_num=permutations,  # reduce number to speed up test
        outdir=output_dir,  # do not write output to disk
        no_plot=True,  # Skip plotting
        processes=4,
        format='png',
    )