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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 filter_against_normal(self, normal_mutations, maf_min=0.2, maf_count_threshold=20, count_min=1):
 """Filters mutations that are in the given normal"""

        assert(normal_mutations.chrom == self.chrom)
        assert(normal_mutations.pos == self.pos)
        assert(normal_mutations.ref == self.ref)

        def passes_normal_criteria(mut):
            return (mut.count >= maf_count_threshold and mut.maf > maf_min) or \
                (mut.count < maf_count_threshold and mut.count > count_min)

        nms = normal_mutations
        muts = MutationsAtSinglePosition(self.chrom, self.pos, self.cov, self.ref)

        for snv in self.snvs:
            if not (snv in nms.snvs and passes_normal_criteria(nms.snvs[snv])):
                muts.add_snv(self.snvs[snv])

        for dlt in self.deletions:
            if not (dlt in nms.deletions and passes_normal_criteria(nms.deletions[dlt])):
                muts.add_deletion(self.deletions[dlt])

        for ins in self.insertions:
            if not (ins in nms.insertions and passes_normal_criteria(nms.insertions[ins])):
                muts.add_insertion(self.insertions[ins])

        return muts