Inconsistency in primitive_lattice results between get_magnetic_symmetry_dataset & get_magnetic_symmetry in the Python interface #370
Description
I've discovered an inconsistency in Spglib: the primitive_lattice results from get_magnetic_symmetry_dataset and get_magnetic_symmetry do not match. Specifically, the latter's output seems to be the transpose of the former's. This issue is consistent across multiple tests, not just a single instance.
Here's a brief code example demonstrating the problem:
>>> import numpy as np
>>> from spglib import get_magnetic_symmetry_dataset, get_magnetic_symmetry
>>> lattice = np.array(
[
[1.06949000e01, 0.00000000e00, 0.00000000e00],
[3.84998337e-16, 6.28750000e00, 0.00000000e00],
[3.09590711e-16, 3.09590711e-16, 5.05600000e00],
]
)
>>> positions = np.array(
[
[0.0, 0.0, 0.0],
[0.5, 0.0, 0.5],
[0.5, 0.5, 0.5],
[0.0, 0.5, 0.0],
[0.2794, 0.25, 0.9906],
[0.2206, 0.75, 0.4906],
[0.7206, 0.75, 0.0094],
[0.7794, 0.25, 0.5094],
]
)
>>> numbers = [0, 0, 0, 0, 0, 0, 0, 0]
>>> magmoms = np.array(
[
[3.0, 0.4, 0.0],
[-3.0, -0.4, 0.0],
[-3.0, 0.4, 0.0],
[3.0, -0.4, 0.0],
[4.5, 0.0, 0.0],
[-4.5, 0.0, 0.0],
[4.5, 0.0, 0.0],
[-4.5, 0.0, 0.0],
]
)
>>> dataset = get_magnetic_symmetry_dataset((lattice, positions, numbers, magmoms))
>>> symdict = get_magnetic_symmetry((lattice, positions, numbers, magmoms))
>>> dataset
{'uni_number': 544, 'msg_type': 3, 'hall_number': 292, 'tensor_rank': 1, 'n_operations': 8, 'rotations': array([[[ 1, 0, 0],
[ 0, 1, 0],
[ 0, 0, 1]],
[[-1, 0, 0],
[ 0, -1, 0],
[ 0, 0, -1]],
[[-1, 0, 0],
[ 0, -1, 0],
[ 0, 0, 1]],
[[ 1, 0, 0],
[ 0, 1, 0],
[ 0, 0, -1]],
[[ 1, 0, 0],
[ 0, -1, 0],
[ 0, 0, -1]],
[[-1, 0, 0],
[ 0, 1, 0],
[ 0, 0, 1]],
[[-1, 0, 0],
[ 0, 1, 0],
[ 0, 0, -1]],
[[ 1, 0, 0],
[ 0, -1, 0],
[ 0, 0, 1]]], dtype=int32), 'translations': array([[-0.00000000e+00, -0.00000000e+00, -0.00000000e+00],
[-0.00000000e+00, -0.00000000e+00, -0.00000000e+00],
[ 5.00000000e-01, 0.00000000e+00, 5.00000000e-01],
[ 5.00000000e-01, 0.00000000e+00, 5.00000000e-01],
[ 5.00000000e-01, 5.00000000e-01, 5.00000000e-01],
[ 5.00000000e-01, 5.00000000e-01, 5.00000000e-01],
[ 6.16297582e-33, 5.00000000e-01, 0.00000000e+00],
[ 6.16297582e-33, 5.00000000e-01, 0.00000000e+00]]), 'time_reversals': array([False, False, False, False, True, True, True, True]), 'n_atoms': 8, 'equivalent_atoms': array([0, 0, 0, 0, 4, 4, 4, 4], dtype=int32), 'transformation_matrix': array([[1., 0., 0.],
[0., 1., 0.],
[0., 0., 1.]]), 'origin_shift': array([0., 0., 0.]), 'n_std_atoms': 8, 'std_lattice': array([[1.06949000e+01, 0.00000000e+00, 0.00000000e+00],
[3.84998337e-16, 6.28750000e+00, 0.00000000e+00],
[3.09590711e-16, 3.09590711e-16, 5.05600000e+00]]), 'std_types': array([0, 0, 0, 0, 0, 0, 0, 0], dtype=int32), 'std_positions': array([[ 1.54074396e-33, 0.00000000e+00, 0.00000000e+00],
[ 5.00000000e-01, 0.00000000e+00, 5.00000000e-01],
[ 5.00000000e-01, 5.00000000e-01, 5.00000000e-01],
[-4.62223187e-33, 5.00000000e-01, 0.00000000e+00],
[ 2.79400000e-01, 2.50000000e-01, 9.90600000e-01],
[ 2.20600000e-01, 7.50000000e-01, 4.90600000e-01],
[ 7.20600000e-01, 7.50000000e-01, 9.40000000e-03],
[ 7.79400000e-01, 2.50000000e-01, 5.09400000e-01]]), 'std_tensors': array([[ 3. , 0.4, 0. ],
[-3. , -0.4, 0. ],
[-3. , 0.4, 0. ],
[ 3. , -0.4, 0. ],
[ 4.5, 0. , 0. ],
[-4.5, 0. , 0. ],
[ 4.5, 0. , 0. ],
[-4.5, 0. , 0. ]]), 'std_rotation_matrix': array([[1.00000000e+00, 1.23259516e-32, 0.00000000e+00],
[0.00000000e+00, 1.00000000e+00, 0.00000000e+00],
[0.00000000e+00, 0.00000000e+00, 1.00000000e+00]]), 'primitive_lattice': array([[-3.09590711e-16, -3.09590711e-16, -5.05600000e+00],
[-3.84998337e-16, -6.28750000e+00, -0.00000000e+00],
[-1.06949000e+01, -0.00000000e+00, -0.00000000e+00]])}
>>> symdict
{'rotations': array([[[ 1, 0, 0],
[ 0, 1, 0],
[ 0, 0, 1]],
[[-1, 0, 0],
[ 0, -1, 0],
[ 0, 0, -1]],
[[-1, 0, 0],
[ 0, -1, 0],
[ 0, 0, 1]],
[[ 1, 0, 0],
[ 0, 1, 0],
[ 0, 0, -1]],
[[ 1, 0, 0],
[ 0, -1, 0],
[ 0, 0, -1]],
[[-1, 0, 0],
[ 0, 1, 0],
[ 0, 0, 1]],
[[-1, 0, 0],
[ 0, 1, 0],
[ 0, 0, -1]],
[[ 1, 0, 0],
[ 0, -1, 0],
[ 0, 0, 1]]], dtype=int32), 'translations': array([[-0.00000000e+00, -0.00000000e+00, -0.00000000e+00],
[-0.00000000e+00, -0.00000000e+00, -0.00000000e+00],
[ 5.00000000e-01, 0.00000000e+00, 5.00000000e-01],
[ 5.00000000e-01, 0.00000000e+00, 5.00000000e-01],
[ 5.00000000e-01, 5.00000000e-01, 5.00000000e-01],
[ 5.00000000e-01, 5.00000000e-01, 5.00000000e-01],
[ 6.16297582e-33, 5.00000000e-01, 0.00000000e+00],
[ 6.16297582e-33, 5.00000000e-01, 0.00000000e+00]]), 'time_reversals': array([False, False, False, False, True, True, True, True]), 'equivalent_atoms': array([0, 0, 0, 0, 4, 4, 4, 4], dtype=int32), 'primitive_lattice': array([[-3.09590711e-16, -3.84998337e-16, -1.06949000e+01],
[-3.09590711e-16, -6.28750000e+00, -0.00000000e+00],
[-5.05600000e+00, -0.00000000e+00, -0.00000000e+00]])}
>>> symdict['primitive_lattice'] == dataset['primitive_lattice']
array([[ True, False, False],
[False, True, True],
[False, True, True]])
>>> symdict['primitive_lattice'] == dataset['primitive_lattice'].T
array([[ True, True, True],
[ True, True, True],
[ True, True, True]])
>>> import spglib
>>> spglib.get_version()
(2, 1, 0)The comparison shows that symdict['primitive_lattice'] is indeed the transpose of dataset['primitive_lattice']. This inconsistency might affect users needing accurate lattice information. I hope this information helps in resolving the issue.