def phonon_unfold():
atoms = FaceCenteredCubic(size=(1, 1, 1), symbol="Cu", pbc=True)
symbols = atoms.get_chemical_symbols()
#symbols[-1] = 'Ag'
atoms.set_chemical_symbols(symbols)
calc = EMT()
atoms.set_calculator(calc)
phonon = calculate_phonon(atoms,
calc,
ndim=np.eye(3) * 2,
primitive_matrix=np.eye(3) / 1.0)
kpts, x, X, names = kpath()
kpts = [
np.dot(
k,
np.linalg.inv((np.array([[0, 1, 1], [1, 0, 1], [1, 1, 0]]) / 2.0)))
for k in kpts
]
phonon.set_qpoints_phonon(kpts, is_eigenvectors=True)
freqs, eigvecs = phonon.get_qpoints_phonon()
sc = atoms
sc_mat = np.linalg.inv((np.array([[0, 1, 1], [1, 0, 1], [1, 1, 0]]) / 2.0))
spos = sc.get_scaled_positions()
uf = phonon_unfolder(atoms, sc_mat, eigvecs, kpts)
weights = uf.get_weights()
ax = None
ax = plot_band_weight([list(x)] * freqs.shape[1],
freqs.T * 33.356,
weights[:, :].T * 0.98 + 0.01,
xticks=[names, X],
axis=ax)
# print freqs
# for i in range(freqs.shape[1]):
# plt.plot(x, freqs[:, i], color='blue', alpha=0.2, linewidth=2.5)
plt.xticks(X, names)
plt.ylabel('Frequency (cm$^{-1}$)')
plt.ylim([0, 350])
plt.title('with defect (1/4) (method: reciprocal)')
get_phonon_prim(ax)
plt.savefig('defrec4.png')
plt.show()
def get_structure():
DDB = abilab.abiopen('out_DDB')
struct = DDB.structure
atoms = DDB.structure.to_ase_atoms()
scaled_positions = struct.frac_coords
cell = struct.lattice_vectors()
numbers = struct.atomic_numbers
masses = [atomic_masses[i] for i in numbers]
print numbers
print cell
print scaled_positions
points = kpath()[-1]
sc_mat = np.linalg.inv((np.array([[0, 1, 1], [1, 0, 1], [1, 1, 0]]) / 2.0))
kpath_bounds = [np.dot(k, sc_mat) for k in points]
print kpath_bounds
phbst, phdos = DDB.anaget_phbst_and_phdos_files(
nqsmall=5,
asr=1,
chneut=1,
dipdip=0,
verbose=1,
lo_to_splitting=False,
qptbounds=kpath_bounds,
)
#phbst.plot_phbands()
qpoints = phbst.qpoints.frac_coords
print qpoints
nqpts = len(qpoints)
nbranch = 3 * len(numbers)
evals = np.zeros([nqpts, nbranch])
evecs = np.zeros([nqpts, nbranch, nbranch], dtype='complex128')
m = np.sqrt(np.kron(masses, [1, 1, 1]))
#positions=np.kron(scaled_positions,[1,1,1])
for iqpt, qpt in enumerate(qpoints):
for ibranch in range(nbranch):
phmode = phbst.get_phmode(qpt, ibranch)
evals[iqpt, ibranch] = phmode.freq
evec = phmode.displ_cart * m
phase = [
np.exp(-2j * np.pi * np.dot(pos, qpt))
for pos in scaled_positions
]
phase = np.kron(phase, [1, 1, 1])
evec *= phase
evec /= np.linalg.norm(evec)
evecs[iqpt, :, ibranch] = evec
uf = phonon_unfolder(atoms, sc_mat, evecs, qpoints, phase=False)
weights = uf.get_weights()
print weights.min(), weights.max()
x = np.arange(nqpts)
freqs = evals
names = ['$\Gamma$', 'X', 'W', '$\Gamma$', 'L']
#ax=plot_band_weight([list(x)]*freqs.shape[1],freqs.T*33.356,weights[:,:].T*0.98+0.01,xticks=[names,X],axis=ax)
ax = plot_band_weight([list(x)] * freqs.shape[1],
freqs.T * 27 * 33.356,
weights[:, :].T * 0.98 + 0.01,
xticks=[names, [1, 2, 3, 4, 5]],
style='alpha')
plt.show()
def nc_unfolder(fname, sc_mat, kx=None, knames=None, ghost_atoms=None):
ncfile = abilab.abiopen(fname)
struct = ncfile.structure
atoms = ncfile.structure.to_ase_atoms()
scaled_positions = struct.frac_coords
cell = struct.lattice_vectors()
numbers = struct.atomic_numbers
masses = [atomic_masses[i] for i in numbers]
#print numbers
#print cell
#print scaled_positions
#print kpath_bounds
phbst = ncfile.phbands
#phbst.plot_phbands()
qpoints = phbst.qpoints.frac_coords
nqpts = len(qpoints)
nbranch = 3 * len(numbers)
evals = np.zeros([nqpts, nbranch])
evecs = np.zeros([nqpts, nbranch, nbranch], dtype='complex128')
m = np.sqrt(np.kron(masses, [1, 1, 1]))
#positions=np.kron(scaled_positions,[1,1,1])
freqs = phbst.phfreqs
displ_carts = phbst.phdispl_cart
for iqpt, qpt in enumerate(qpoints):
print(iqpt, qpt)
for ibranch in range(nbranch):
#phmode = ncfile.get_phmode(qpt, ibranch)
#print(2)
evals[iqpt, ibranch] = freqs[iqpt, ibranch]
#evec=phmode.displ_cart *m
#phase = [np.exp(-2j*np.pi*np.dot(pos,qpt)) for pos in scaled_positions]
#phase = np.kron(phase,[1,1,1])
#evec*=phase
#evec /= np.linalg.norm(evec)
evec = displacement_cart_to_evec(displ_carts[iqpt, ibranch, :],
masses,
scaled_positions,
qpoint=qpt,
add_phase=True)
evecs[iqpt, :, ibranch] = evec
uf = phonon_unfolder(atoms,
sc_mat,
evecs,
qpoints,
phase=False,
ghost_atoms=ghost_atoms)
weights = uf.get_weights()
x = np.arange(nqpts)
freqs = evals
#names = ['$\Gamma$', 'X', 'W', '$\Gamma$', 'L']
#ax=plot_band_weight([list(x)]*freqs.shape[1],freqs.T*33.356,weights[:,:].T*0.98+0.01,xticks=[names,X],axis=ax)
ax = plot_band_weight([list(x)] * freqs.shape[1],
freqs.T * 8065.6,
weights[:, :].T * 0.98 + 0.01,
xticks=[knames, kx],
style='alpha')
#plt.show()
return ax
def DDB_unfolder(DDB_fname,
kpath_bounds,
sc_mat,
knames=None,
kx=None,
dipdip=1):
DDB = abilab.abiopen(DDB_fname)
struct = DDB.structure
atoms = DDB.structure.to_ase_atoms()
scaled_positions = struct.frac_coords
cell = struct.lattice_vectors()
numbers = struct.atomic_numbers
masses = [atomic_masses[i] for i in numbers]
#print numbers
#print cell
#print scaled_positions
#print kpath_bounds
phbst, phdos = DDB.anaget_phbst_and_phdos_files(
nqsmall=2,
asr=1,
chneut=1,
dipdip=dipdip,
verbose=1,
ndivsm=40,
lo_to_splitting=True,
qptbounds=kpath_bounds,
)
#phbst.plot_phbands()
qpoints = phbst.qpoints.frac_coords
nqpts = len(qpoints)
nbranch = 3 * len(numbers)
evals = np.zeros([nqpts, nbranch])
evecs = np.zeros([nqpts, nbranch, nbranch], dtype='complex128')
m = np.sqrt(np.kron(masses, [1, 1, 1]))
#positions=np.kron(scaled_positions,[1,1,1])
for iqpt, qpt in enumerate(qpoints):
for ibranch in range(nbranch):
phmode = phbst.get_phmode(qpt, ibranch)
evals[iqpt, ibranch] = phmode.freq
#evec=phmode.displ_cart *m
#phase = [np.exp(-2j*np.pi*np.dot(pos,qpt)) for pos in scaled_positions]
#phase = np.kron(phase,[1,1,1])
#evec*=phase
#evec /= np.linalg.norm(evec)
evec = displacement_cart_to_evec(phmode.displ_cart,
masses,
scaled_positions,
qpoint=qpt,
add_phase=True)
evecs[iqpt, :, ibranch] = evec
uf = phonon_unfolder(atoms, sc_mat, evecs, qpoints, phase=False)
weights = uf.get_weights()
x = np.arange(nqpts)
freqs = evals
xpts = []
for ix, xx in enumerate(x):
for q in kpath_bounds:
if np.sum((np.array(qpoints[ix]) - np.array(q))**
2) < 0.00001 and ix not in xpts:
xpts.append(ix)
if knames is None:
knames = [str(k) for k in kpath_bounds]
#names = ['$\Gamma$', 'X', 'W', '$\Gamma$', 'L']
#ax=plot_band_weight([list(x)]*freqs.shape[1],freqs.T*33.356,weights[:,:].T*0.98+0.01,xticks=[names,X],axis=ax)
ax = plot_band_weight([list(x)] * freqs.shape[1],
freqs.T * 8065.6,
weights[:, :].T * 0.98 + 0.01,
xticks=[knames, xpts],
style='alpha')
#ax=plot_band_weight([list(x)]*freqs.shape[1],freqs.T*8065.6,weights[:,:].T*0.98+0.000001,xticks=[knames, kx],style='alpha' )
#plt.show()
return ax