def colormapped_bedfile(self, genome, cmap=None):
        """
        Create a BED file with padj encoded as color

        Features will be colored according to adjusted pval (phred
        transformed).  Downregulated features have the sign flipped.

        Parameters
        ----------
        cmap : matplotlib colormap
            Default is matplotlib.cm.RdBu_r

        Notes
        -----
        Requires a FeatureDB to be attached.
        """
        if self.db is None:
            raise ValueError("FeatureDB required")
        db = gffutils.FeatureDB(self.db)

        def scored_feature_generator(d):
            for i in range(len(d)):
                try:
                    feature = db[d.ix[i]]
                except gffutils.FeatureNotFoundError:
                    raise gffutils.FeatureNotFoundError(d.ix[i])
                score = -10 * np.log10(d.padj[i])
                lfc = d.log2FoldChange[i]
                if np.isnan(lfc):
                    score = 0
                if lfc < 0:
                    score *= -1
                feature.score = str(score)
                feature = extend_fields(
                    gff2bed(gffutils.helpers.asinterval(feature)), 9)
                fields = feature.fields[:]
                fields[6] = fields[1]
                fields[7] = fields[2]
                fields.append(str(d.padj[i]))
                fields.append(str(d.pval[i]))
                fields.append('%.3f' % d.log2FoldChange[i])
                fields.append(d.baseMeanB[i] % '%.3f')
                fields.append('%.3f' % d.baseMeanB[i])
                yield pybedtools.create_interval_from_list(fields)

        x = pybedtools.BedTool(scored_feature_generator(self)).saveas()
        norm = x.colormap_normalize()
        if cmap is None:
            cmap = cm.RdBu_r
        cmap = colormap_adjust.cmap_center_point_adjust(
            cmap, [norm.vmin, norm.vmax], 0)

        def score_zeroer(f):
            f.score = '0'
            return f
        return x.each(add_color, cmap=cmap, norm=norm)\
                .sort()\
                .each(score_zeroer)\
                .truncate_to_chrom(genome)\
                .saveas()
dataset/ETHPy150Open daler/metaseq/metaseq/results_table.py/DESeqResults.colormapped_bedfile/swapped operands of `%`