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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 describe_features(self, traj):
 """Return a list of dictionaries describing the SASA features. Parameters traj : mdtraj.Trajectory The trajectory to describe Returns ------- feature_descs : list of dict Dictionary describing each feature with the following information about the atoms participating in each SASA feature - resnames: names of residues - atominds: atom index or atom indices in mode="residue" - resseqs: residue ids (not necessarily 0-indexed) - resids: unique residue ids (0-indexed) - featurizer: SASA - featuregroup: atom or residue """


        feature_descs = []
        _, mapping = md.geometry.sasa.shrake_rupley(traj, mode=self.mode, get_mapping=True)
        top = traj.topology

        if self.mode == "residue":
            resids = np.unique(mapping)
            resseqs = [top.residue(ri).resSeq for ri in resids]
            resnames = [top.residue(ri).name for ri in resids]
            atoms_in_res = [res.atoms for res in top.residues]
            aind_tuples = []
            # For each resdiue...
            for i,x in enumerate(atoms_in_res):
                # For each atom in the residues, append it's index
                aind_tuples.append([atom.index for atom in x])
            zippy = itertools.product(['SASA'],['N/A'],[self.mode], zip(aind_tuples, resseqs, resids, resnames))
        else:
            resids = [top.atom(ai).residue.index for ai in mapping]
            resseqs = [top.atom(ai).residue.resSeq for ai in mapping]
            resnames = [top.atom(ai).residue.name for ai in mapping]
            zippy = itertools.product(['SASA'],['N/A'],[self.mode], zip(mapping, resseqs, resids, resnames))

        feature_descs.extend(dict_maker(zippy))

        return feature_descs