def __init__(self,
path,
atoms=None,
min_hopping_norm=1e-4,
max_distance=None,
nelect=0,
efermi=0):
self.path = path
self.tb_up = pythtb.w90(path, 'wannier90.up')
self.tb_dn = pythtb.w90(path, 'wannier90.dn')
self.tbmodel_up = self.tb_up.model(
min_hopping_norm=min_hopping_norm, max_distance=max_distance)
self.tbmodel_dn = self.tb_dn.model(
min_hopping_norm=min_hopping_norm, max_distance=max_distance)
self.efermi = efermi
self.nelect = nelect
self.atoms = atoms
self.basis = None
self.kpts = None
self.kweights = None
basis_fname = os.path.join(self.path, 'basis.txt')
if os.path.exists(basis_fname):
self.basis = read_basis(basis_fname)
self.nwann = len(self.basis.keys())
self.block_dict = basis_to_block(self.basis)
def test_consistency_pythtb(prefix, sample):
"""
Check that a model from Wannier90 output is consistent with a
PythTB reference from the same files.
"""
pt_model = pt.w90(sample(""), prefix).model()
tb_model = tb.Model.from_wannier_files(
hr_file=sample(prefix + "_hr.dat"),
win_file=sample(prefix + ".win"),
# This might be needed if pythtb supports wsvec.dat
# wsvec_file=sample('silicon_wsvec.dat'),
xyz_file=sample(prefix + "_centres.xyz"),
)
# pylint: disable=protected-access
assert np.allclose(pt_model._gen_ham([0, 0, 0]),
tb_model.hamilton([0, 0, 0]))
assert np.allclose(pt_model._gen_ham([0, 0, 0]),
tb_model.hamilton([0, 0, 0], convention=1))
k = (0.123412512, 0.6234615, 0.72435235)
assert np.allclose(pt_model._gen_ham(k), tb_model.hamilton(k,
convention=1))
assert np.allclose(pt_model.get_lat(), tb_model.uc)
assert np.allclose(pt_model.get_orb() % 1, tb_model.pos)
def run(path,
prefix,
labels,
scmat,
output_figure,
kvectors,
knames,
npoints=200,
min_hopping_norm=0.0001):
w90reader = w90(path=path, prefix=prefix)
tb = w90reader.model(min_hopping_norm=min_hopping_norm)
#labels = ['pz', 'px', 'py'] * 12 + ['dz2', 'dxy', 'dyz', 'dx2', 'dxz'] * 4
#scmat=[[1,-1,0],[1,1,0],[0,0,2]]
u = wannier_unfolder(tb, labels, sc_matrix=scmat)
u.plot_unfolded_band(
#kvectors=np.array([[0, 0, 0], [0.5, 0, 0], [0.5, 0.5, 0],
# [0, 0, 0], [.5, .5, .5]]),
kvectors=kvectors,
#knames=['$\Gamma$', 'X', 'M', '$\Gamma$', 'R'],
knames=knames,
npoints=npoints,
ax=None,
)
plt.savefig(output_figure)
plt.show()
def test_nodefect():
w90reader = w90(path='data_nodefect', prefix='wannier90')
#w90reader = w90(path='data', prefix='wannier90')
tb = w90reader.model(min_hopping_norm=0.05)
labels = ['pz', 'px', 'py'] * 12 + ['dz2', 'dxy', 'dyz', 'dx2', 'dxz'] * 4
scmat=[[1,-1,0],[1,1,0],[0,0,2]]
u = wannier_unfolder(tb, labels, sc_matrix=scmat)
u.plot_unfolded_band()
plt.savefig('STO_nodefect.pdf')
plt.savefig('STO_nodefect.png')
plt.show()
def __init__(self, path, prefix, zero_level=0):
self.path = path
self.prefix = prefix
self.wannier = tb.w90(path, prefix)
self.zero_level = zero_level
self._orbital_positons = []
for orbital_position in self.wannier.red_cen:
self._orbital_positons.append(list(orbital_position))
TightBinding.__init__(self, self.create_crystal())
self.set_model(zero_level=self.zero_level)
def get_pythtb(wan_calculation, xyz_workaround=False):
tmpdir = tempfile.mkdtemp()
seedname = os.path.splitext(wan_calculation._INPUT_FILE)[0]
out_dir = os.path.join(wan_calculation.out.retrieved.folder.abspath,
"path")
for filepath in [
os.path.join(wan_calculation.folder.abspath, "raw_input",
"{}.win".format(seedname)),
os.path.join(out_dir, "{}.wout".format(seedname)),
os.path.join(out_dir, "{}_hr.dat".format(seedname)),
os.path.join(out_dir, "{}_wsvec.dat".format(seedname)),
os.path.join(out_dir, "{}_centres.xyz".format(seedname)),
os.path.join(out_dir, "{}_band.kpt".format(seedname)),
os.path.join(out_dir, "{}_band.dat".format(seedname)),
]:
if os.path.exists(filepath):
shutil.copy(filepath,
os.path.join(tmpdir, os.path.basename(filepath)))
else:
print("Skipping {}".format(os.path.basename(filepath)))
if xyz_workaround:
parsed = raw_wout_parser(
open(os.path.join(out_dir,
"{}.wout".format(seedname))).readlines())
num_atoms = len(wan_calculation.inp.structure.sites)
num_wf = len(parsed['wannier_functions_output'])
xyz = []
xyz.append(str(num_atoms + num_wf))
xyz.append(str(num_atoms + num_wf))
for wf in parsed['wannier_functions_output']:
xyz.append("X {} {} {}".format(wf['coordinates'][0],
wf['coordinates'][1],
wf['coordinates'][2]))
for site in wan_calculation.inp.structure.sites:
xyz.append("{} {} {} {}".format(site.kind_name, site.position[0],
site.position[1],
site.position[2]))
with open(os.path.join(tmpdir, "{}_centres.xyz".format(seedname)),
'w') as f:
f.write("\n".join(xyz))
tb_w90 = pythtb.w90(tmpdir, seedname)
# Remove the folder
shutil.rmtree(tmpdir)
return tb_w90
def test_defect():
w90reader = w90(path='data', prefix='wannier90')
tb = w90reader.model(min_hopping_norm=0.05)
labels = ['pz', 'px', 'py'] * 12 + ['dz2', 'dxy', 'dyz', 'dx2', 'dxz'] * 4
scmat=[[1,-1,0],[1,1,0],[0,0,2]]
u = wannier_unfolder(tb, labels, sc_matrix=scmat)
u.plot_unfolded_band(
kvectors=np.array([[0, 0, 0], [0.5, 0, 0], [0.5, 0.5, 0],
[0, 0, 0], [.5, .5, .5]]),
knames=['$\Gamma$', 'X', 'M', '$\Gamma$', 'R'],
npoints=200,
ax=None,
)
plt.savefig('STO_defect.pdf')
plt.savefig('STO_defect.png')
plt.show()
def test_si_pythtb():
pt_model = pt.w90(SAMPLES_DIR, 'silicon').model()
tb_model = tb.Model.from_wannier_files(
hr_file=os.path.join(SAMPLES_DIR, 'silicon_hr.dat'),
win_file=os.path.join(SAMPLES_DIR, 'silicon.win'),
# This might be needed if pythtb supports wsvec.dat
# wsvec_file=os.path.join(SAMPLES_DIR, 'silicon_wsvec.dat'),
xyz_file=os.path.join(SAMPLES_DIR, 'silicon_centres.xyz')
)
assert np.allclose(pt_model._gen_ham([0, 0, 0]), tb_model.hamilton([0, 0, 0]))
assert np.allclose(pt_model._gen_ham([0, 0, 0]), tb_model.hamilton([0, 0, 0], convention=1))
k = (0.123412512, 0.6234615, 0.72435235)
assert np.allclose(pt_model._gen_ham(k), tb_model.hamilton(k, convention=1))
assert np.allclose(pt_model.get_lat(), tb_model.uc)
assert np.allclose(pt_model.get_orb() % 1, tb_model.pos)
def test_1d(dt=0.0, t=1):
mymodel = pythtb.w90(path='../test',
prefix='wannier90.up').model(min_hopping_norm=0.001)
kpath = np.array([[0.0, 0, 0], [0, 1, 0], [1, 1, 0], [0, 0, 0], [1, 1, 1],
[0, 1, 0]]) / 2.0
kpath = np.dot(kpath, np.array([[1, -1, 0], [1, 1, 0], [0, 0, 2]]))
kpoints, zs, special_zs = ase.dft.kpoints.bandpath(kpath,
cell=np.eye(3),
npoints=210)
xticks = (['GM', 'X', 'M', 'GM', 'R', 'X'], special_zs)
evals = mymodel.solve_all(kpoints)
myanatb = anatb(mymodel, kpts=kpoints)
myanatb.plot_COHP_fatband(k_x=zs,
xticks=xticks,
iblock=range(0, 36),
jblock=range(36, 56))
return
def test_consistency_pythtb(prefix, sample):
pt_model = pt.w90(sample(''), prefix).model()
tb_model = tb.Model.from_wannier_files(
hr_file=sample(prefix + '_hr.dat'),
win_file=sample(prefix + '.win'),
# This might be needed if pythtb supports wsvec.dat
# wsvec_file=sample('silicon_wsvec.dat'),
xyz_file=sample(prefix + '_centres.xyz'))
assert np.allclose(pt_model._gen_ham([0, 0, 0]),
tb_model.hamilton([0, 0, 0]))
assert np.allclose(pt_model._gen_ham([0, 0, 0]),
tb_model.hamilton([0, 0, 0], convention=1))
k = (0.123412512, 0.6234615, 0.72435235)
assert np.allclose(pt_model._gen_ham(k), tb_model.hamilton(k,
convention=1))
assert np.allclose(pt_model.get_lat(), tb_model.uc)
assert np.allclose(pt_model.get_orb() % 1, tb_model.pos)