How to use the fitlins.interfaces.afni.Pval function in fitlins

remlfit = afni.Remlfit()
        remlfit.inputs.in_files = img_path
        remlfit.inputs.matrix = design_fname
        remlfit.inputs.out_file = "glt_results.nii.gz"
        remlfit.inputs.var_file = "glt_extra_variables.nii.gz"
        remlfit.inputs.tout = True
        remlfit.inputs.rout = True
        remlfit.inputs.fout = True
        remlfit.inputs.verb = True
        remlfit.inputs.usetemp = True
        remlfit.inputs.goforit = True
        remlfit.inputs.mask = self.inputs.mask_file
        reml_res = remlfit.run()

        # get pvals and zscore buckets (niftis with heterogenous intent codes)
        pval = Pval()
        pval.inputs.in_file = reml_res.outputs.out_file
        pval.inputs.out_file = "pval_maps.nii.gz"
        pvals = pval.run()

        zscore = Pval()
        zscore.inputs.in_file = reml_res.outputs.out_file
        zscore.inputs.out_file = "zscore_maps.nii.gz"
        zscore.inputs.zscore = True
        zscores = zscore.run()

        # create maps object
        maps = {
            "stat": nb.load(reml_res.outputs.out_file),
            "effect_variance": nb.load(reml_res.outputs.var_file),
            "z_score": nb.load(zscores.outputs.out_file),
            "p_value": nb.load(pvals.outputs.out_file),

remlfit.inputs.tout = True
        remlfit.inputs.rout = True
        remlfit.inputs.fout = True
        remlfit.inputs.verb = True
        remlfit.inputs.usetemp = True
        remlfit.inputs.goforit = True
        remlfit.inputs.mask = self.inputs.mask_file
        reml_res = remlfit.run()

        # get pvals and zscore buckets (niftis with heterogenous intent codes)
        pval = Pval()
        pval.inputs.in_file = reml_res.outputs.out_file
        pval.inputs.out_file = "pval_maps.nii.gz"
        pvals = pval.run()

        zscore = Pval()
        zscore.inputs.in_file = reml_res.outputs.out_file
        zscore.inputs.out_file = "zscore_maps.nii.gz"
        zscore.inputs.zscore = True
        zscores = zscore.run()

        # create maps object
        maps = {
            "stat": nb.load(reml_res.outputs.out_file),
            "effect_variance": nb.load(reml_res.outputs.var_file),
            "z_score": nb.load(zscores.outputs.out_file),
            "p_value": nb.load(pvals.outputs.out_file),
        }
        maps["effect_size"] = maps["stat"]
        self.save_remlfit_results(maps, contrasts, runtime)
        #########################
        # Results are saved to self in save_remlfit_results, if the

def _parse_inputs(self, skip=None):
        if skip is None:
            skip = []
        return super(Pval, self)._parse_inputs(skip)