# ================================== LICENSE ===================================
# Magnopy - Python package for magnons.
# Copyright (C) 2023-2026 Magnopy Team
#
# e-mail: anry@uv.es, web: magnopy.org
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
#
# ================================ END LICENSE =================================
import numpy as np
from magnopy._spinham._convention import Convention
from magnopy._spinham._hamiltonian import SpinHamiltonian
# Save local scope at this moment
old_dir = set(dir())
old_dir.add("old_dir")
[docs]
def load_grogu(filename, spin_values=None, spglib_types=None) -> SpinHamiltonian:
r"""
Reads spin Hamiltonian from the .txt file produced by |GROGU|_.
For more information on GROGU's file format see |GROGU-FF|_.
Parameters
----------
filename : str
Path to the .txt file produced by |GROGU|_.
spin_values : (M, ) iterable of floats, optional
Spin values for all magnetic atom. Order is the same as in |GROGU|_ file. Magnetic
atoms are defined as those that have at least one parameter associated with them.
If none given, magnopy uses spin values computed from DFT (as provided in the
|GROGU|_ file).
spglib_types : (M_prime, ) iterable of ints, optional
Spglib types for all atoms (not only for magnetic ones, but for all). Order is the
same as in |GROGU|_ file. If none given, then there will be no "spglib_types" key
in ``spinham.atoms``.
Returns
-------
spinham : :py:class:`.SpinHamiltonian`
Spin Hamiltonian, that is built from the |GROGU|_ file.
Raises
------
ValueError
If ``spin_values`` is provided and its length does not match the number of
magnetic atoms in the Hamiltonian.
ValueError
If ``spglib_types`` is provided and its length does not match the number of
atoms in the Hamiltonian.
"""
convention = Convention.get_predefined("grogu")
# Read the content of the file
with open(filename, "r", encoding="utf-8") as f:
lines = f.readlines()
# Read the cell
i = 0
while "cell" not in lines[i].lower() or "(ang)" not in lines[i].lower():
i += 1
i += 1
cell = [
list(map(float, lines[i].split())),
list(map(float, lines[i + 1].split())),
list(map(float, lines[i + 2].split())),
]
# Read the atoms
while "magnetic" not in lines[i].lower() or "sites" not in lines[i].lower():
i += 1
i += 1
M = int(lines[i].split()[3])
i += 1
# Check if spin_values were provided and of correct length
if spin_values is not None and len(spin_values) != M:
raise ValueError(f"Expected {M} spin values, got {len(spin_values)}")
# Check if spglib_types were provided and of correct length
if spglib_types is not None and len(spglib_types) != M:
raise ValueError(f"Expected {M} spglib types, got {len(spglib_types)}")
name_to_index = {}
atoms = dict(names=[], positions=[], spins=[], g_factors=[2 for _ in range(M)])
for atom_index in range(M):
i += 1
words = lines[i].split()
name = words[0]
name_to_index[name] = atom_index
positions = list(map(float, words[1:4]))
positions = positions @ np.linalg.inv(cell)
if spin_values is not None:
spin = spin_values[atom_index]
else:
spin = float(words[4])
atoms["names"].append(name)
atoms["positions"].append(positions)
atoms["spins"].append(spin)
# Add spglib types if provided
if spglib_types is not None:
atoms["spglib_types"] = [int(_) for _ in spglib_types]
# Construct spin Hamiltonian
spinham = SpinHamiltonian(convention=convention, cell=cell, atoms=atoms)
while (
"intra-atomic" not in lines[i].lower()
or "anisotropy" not in lines[i].lower()
or "tensor" not in lines[i].lower()
or "(mev)" not in lines[i].lower()
):
i += 1
for _ in range(M):
i += 2
name = lines[i].split()[0]
alpha = name_to_index[name]
i += 2
parameter = [
list(map(float, lines[i].split())),
list(map(float, lines[i + 1].split())),
list(map(float, lines[i + 2].split())),
]
i += 2
spinham.add_21(alpha=alpha, parameter=parameter)
while (
"exchange" not in lines[i].lower()
or "tensor" not in lines[i].lower()
or "(mev)" not in lines[i].lower()
):
i += 1
i += 1
N = int(lines[i].split()[3])
i += 2
for _ in range(N):
i += 2
words = lines[i].split()
alpha = name_to_index[words[0]]
beta = name_to_index[words[1]]
nu = tuple(list(map(int, words[2:5])))
i += 2
parameter = [
list(map(float, lines[i].split())),
list(map(float, lines[i + 1].split())),
list(map(float, lines[i + 2].split())),
]
i += 2
spinham.add_22(
alpha=alpha, beta=beta, nu=nu, parameter=parameter, when_present="replace"
)
return spinham
# Populate __all__ with objects defined in this file
__all__ = list(set(dir()) - old_dir)
# Remove all semi-private objects
__all__ = [i for i in __all__ if not i.startswith("_")]
del old_dir
