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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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('%.3f' % d.baseMeanB[i])
                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()