How to use the tskit.load_legacy function in tskit

def test_msprime_v_0_3_0(self):
        ts = tskit.load_legacy("tests/data/hdf5-formats/msprime-0.3.0_v2.0.hdf5")
        self.verify_tree_sequence(ts)

def test_msprime_v_0_4_0(self):
        ts = tskit.load_legacy("tests/data/hdf5-formats/msprime-0.4.0_v3.1.hdf5")
        self.verify_tree_sequence(ts)

def test_v2_no_samples(self):
        ts = multi_locus_with_mutation_example()
        tskit.dump_legacy(ts, self.temp_file, version=2)
        root = h5py.File(self.temp_file, "r+")
        del root['samples']
        root.close()
        tsp = tskit.load_legacy(self.temp_file)
        self.verify_tree_sequences_equal(ts, tsp)

def test_msprime_v_0_5_0(self):
        ts = tskit.load_legacy("tests/data/hdf5-formats/msprime-0.5.0_v10.0.hdf5")
        self.verify_tree_sequence(ts)

def verify_round_trip(self, ts, version):
        tskit.dump_legacy(ts, self.temp_file, version=version)
        tsp = tskit.load_legacy(self.temp_file)
        simplify = version < 10
        self.verify_tree_sequences_equal(ts, tsp, simplify=simplify)
        tsp.dump(self.temp_file)
        tsp = tskit.load(self.temp_file)
        self.verify_tree_sequences_equal(ts, tsp, simplify=simplify)
        for provenance in tsp.provenances():
            tskit.validate_provenance(json.loads(provenance.record))

def verify_malformed_json_v2(self, ts, group_name, attr, bad_json):
        tskit.dump_legacy(ts, self.temp_file, 2)
        # Write some bad JSON to the provenance string.
        root = h5py.File(self.temp_file, "r+")
        group = root[group_name]
        group.attrs[attr] = bad_json
        root.close()
        tsp = tskit.load_legacy(self.temp_file)
        self.verify_tree_sequences_equal(ts, tsp)

def test_duplicate_mutation_positions(self):
        ts = multi_locus_with_mutation_example()
        for version in [2, 3]:
            tskit.dump_legacy(ts, self.temp_file, version=version)
            root = h5py.File(self.temp_file, "r+")
            position = np.array(root['mutations/position'])
            position[0] = position[1]
            root['mutations/position'][:] = position
            root.close()
            self.assertRaises(
                tskit.DuplicatePositionsError, tskit.load_legacy, self.temp_file)
            tsp = tskit.load_legacy(
                self.temp_file, remove_duplicate_positions=True)
            self.assertEqual(tsp.num_sites, position.shape[0] - 1)
            position_after = list(s.position for s in tsp.sites())
            self.assertEqual(list(position[1:]), position_after)

def test_duplicate_mutation_positions_single_value(self):
        ts = multi_locus_with_mutation_example()
        for version in [2, 3]:
            tskit.dump_legacy(ts, self.temp_file, version=version)
            root = h5py.File(self.temp_file, "r+")
            root['mutations/position'][:] = 0
            root.close()
            self.assertRaises(
                tskit.DuplicatePositionsError, tskit.load_legacy, self.temp_file)
            tsp = tskit.load_legacy(
                self.temp_file, remove_duplicate_positions=True)
            self.assertEqual(tsp.num_sites, 1)
            sites = list(tsp.sites())
            self.assertEqual(sites[0].position, 0)

def run_upgrade(args):
    try:
        tree_sequence = tskit.load_legacy(args.source, args.remove_duplicate_positions)
        tree_sequence.dump(args.destination)
    except tskit.DuplicatePositionsError:
        exit(
            "Error: Duplicate mutation positions in the source file detected.\n\n"
            "This is not supported in the current file format. Running \"upgrade -d\" "

def run_upgrade(args):
    try:
        tree_sequence = tskit.load_legacy(args.source, args.remove_duplicate_positions)
    except tskit.DuplicatePositionsError:
        exit(
            "Error: Duplicate mutation positions in the source file detected.\n\n"
            "This is not supported in the current file format. Running \"upgrade -d\" "
            "will remove these duplicate positions. However, this will result in loss "
            "of data from the original file!")
    tree_sequence.dump(args.destination)