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dft_tools/python/triqs_dft_tools/converters/plovasp/elstruct.py

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################################################################################
#
# TRIQS: a Toolbox for Research in Interacting Quantum Systems
#
# Copyright (C) 2011 by M. Ferrero, O. Parcollet
#
# DFT tools: Copyright (C) 2011 by M. Aichhorn, L. Pourovskii, V. Vildosola
#
# PLOVasp: Copyright (C) 2015 by O. E. Peil
#
# TRIQS 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.
#
# TRIQS 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
# TRIQS. If not, see <http://www.gnu.org/licenses/>.
#
################################################################################
r"""
plovasp.elstruct
================
Internal representation of VASP electronic structure data.
"""
import numpy as np
class ElectronicStructure:
"""
Class containing electronic structure data.
**Parameters:**
- *natom* (int) : total number of atoms
- *nktot* (int) : total number of `k`-points
- *nband* (int) : total number of bands
- *nspin* (int) : spin-polarization
- *nc_flag* (True/False) : non-collinearity flag
- *efermi* (float) : Fermi level read from DOSCAR
- *proj_raw* (array[complex]) : raw projectors from PLOCAR
- *eigvals* (array[float]) : KS eigenvalues
- *ferw* (array[float]) : Fermi weights from VASP
- *kmesh* (dict) : parameters of the `k`-mesh
- *structure* (dict) : parameters of the crystal structure
- *symmetry* (dict) : paramters of symmetry
When the object is created a simple consistency check
of the data coming from different VASP files is performed.
"""
def __init__(self, vasp_data):
self.natom = vasp_data.poscar.nq
self.type_of_ion = vasp_data.poscar.type_of_ion
self.nktot = vasp_data.kpoints.nktot
self.kmesh = {'nktot': self.nktot}
self.kmesh['kpoints'] = vasp_data.kpoints.kpts
# VASP.6.
self.nc_flag = vasp_data.plocar.nc_flag
self.kmesh['kweights'] = vasp_data.kpoints.kwghts
try:
self.kmesh['ntet'] = vasp_data.kpoints.ntet
self.kmesh['itet'] = vasp_data.kpoints.itet
self.kmesh['volt'] = vasp_data.kpoints.volt
except AttributeError:
pass
# Note that one should not subtract this Fermi level from eigenvalues
# here because the true Fermi level might be provided by conf-file
# (for instance, for spaghetti calculations)
try:
self.efermi = vasp_data.doscar.efermi
except AttributeError:
pass
# Note that the number of spin-components of projectors might be different from those
# of bands in case of non-collinear calculations
self.nspin = vasp_data.plocar.nspin
self.nband = vasp_data.plocar.nband
# Check that the number of k-points is the same in all files
_, ns_plo, nk_plo, nb_plo = vasp_data.plocar.plo.shape
assert nk_plo == self.nktot, "PLOCAR is inconsistent with IBZKPT (number of k-points)"
# FIXME: Reading from EIGENVAL is obsolete and should be
# removed completely.
# if not vasp_data.eigenval.eigs is None:
if False:
print("eigvals from EIGENVAL")
self.eigvals = vasp_data.eigenval.eigs
self.ferw = vasp_data.eigenval.ferw.transpose((2, 0, 1))
nk_eig = vasp_data.eigenval.nktot
assert nk_eig == self.nktot, "PLOCAR is inconsistent with EIGENVAL (number of k-points)"
# Check that the number of band is the same in PROJCAR and EIGENVAL
assert nb_plo == self.nband, "PLOCAR is inconsistent with EIGENVAL (number of bands)"
else:
print("eigvals from LOCPROJ")
self.eigvals = vasp_data.plocar.eigs
self.ferw = vasp_data.plocar.ferw.transpose((2, 0, 1))
self.efermi = vasp_data.doscar.efermi
# For later use it is more convenient to use a different order of indices
# [see ProjectorGroup.orthogonalization()]
self.proj_raw = vasp_data.plocar.plo
self.proj_params = vasp_data.plocar.proj_params
# Not needed any more since PROJCAR contains projectors only for a subset of sites
# Check that the number of atoms is the same in PLOCAR and POSCAR
# natom_plo = vasp_data.plocar.params['nion']
# assert natom_plo == self.natom, "PLOCAR is inconsistent with POSCAR (number of atoms)"
self.structure = {'a_brav': vasp_data.poscar.a_brav}
self.structure['nqtot'] = vasp_data.poscar.nq
self.structure['kpt_basis'] = vasp_data.poscar.kpt_basis
self.structure['ntypes'] = vasp_data.poscar.ntypes
self.structure['nq_types'] = vasp_data.poscar.nions
# Concatenate coordinates grouped by type into one array
self.structure['qcoords'] = np.vstack(vasp_data.poscar.q_types)
self.structure['type_of_ion'] = vasp_data.poscar.type_of_ion
self.kmesh['kpoints_cart'] = 0.0 * self.kmesh['kpoints']
for ik in range(self.nktot):
for ii in range(3):
self.kmesh['kpoints_cart'][ik] += self.kmesh['kpoints'][ik,ii]*self.structure['kpt_basis'][:,ii]
# FIXME: This can be removed if ion coordinates are stored in a continuous array
## Construct a map to access coordinates by index
# self.structure['ion_index'] = []
# for isort, nq in enumerate(self.structure['nq_types']):
# for iq in range(nq):
# self.structure['ion_index'].append((isort, iq))
def debug_density_matrix(self):
"""
Calculate and output the density and overlap matrix out of projectors defined in el_struct.
"""
plo = self.proj_raw
nproj, ns, nk, nb = plo.shape
ions = sorted(list(set([param['isite'] for param in self.proj_params])))
nions = len(ions)
norb = nproj // nions
# Spin factor
sp_fac = 2.0 if ns == 1 and self.nc_flag == False else 1.0
if self.nc_flag == False:
den_mat = np.zeros((ns, nproj, nproj), dtype=float)
overlap = np.zeros((ns, nproj, nproj), dtype=float)
for ispin in range(ns):
for ik in range(nk):
kweight = self.kmesh['kweights'][ik]
occ = self.ferw[ispin, ik, :]
den_mat[ispin, :, :] += np.dot(plo[:, ispin, ik, :] * occ, plo[:, ispin, ik, :].T.conj()).real * kweight * sp_fac
ov = np.dot(plo[:, ispin, ik, :], plo[:, ispin, ik, :].T.conj()).real
overlap[ispin, :, :] += ov * kweight
# Output only the site-diagonal parts of the matrices
print()
print(" Unorthonormalized density matrices and overlaps:")
for ispin in range(ns):
print(" Spin:", ispin + 1)
for io, ion in enumerate(ions):
print(" Site:", ion)
iorb_inds = [(ip, param['m']) for ip, param in enumerate(self.proj_params) if param['isite'] == ion]
norb = len(iorb_inds)
dm = np.zeros((norb, norb))
ov = np.zeros((norb, norb))
for ind, iorb in iorb_inds:
for ind2, iorb2 in iorb_inds:
dm[iorb, iorb2] = den_mat[ispin, ind, ind2]
ov[iorb, iorb2] = overlap[ispin, ind, ind2]
print(" Density matrix" + (12*norb - 12 + 2)*" " + "Overlap")
for drow, dov in zip(dm, ov):
out = ''.join(map("{0:12.7f}".format, drow))
out += " "
out += ''.join(map("{0:12.7f}".format, dov))
print(out)
else:
print("!! WARNING !! Non Collinear Routine")
den_mat = np.zeros((ns, nproj, nproj), dtype=float)
overlap = np.zeros((ns, nproj, nproj), dtype=float)
for ispin in range(ns):
for ik in range(nk):
kweight = self.kmesh['kweights'][ik]
occ = self.ferw[ispin, ik, :]
den_mat[ispin, :, :] += np.dot(plo[:, ispin, ik, :] * occ, plo[:, ispin, ik, :].T.conj()).real * kweight * sp_fac
ov = np.dot(plo[:, ispin, ik, :], plo[:, ispin, ik, :].T.conj()).real
overlap[ispin, :, :] += ov * kweight
# Output only the site-diagonal parts of the matrices
print()
print(" Unorthonormalized density matrices and overlaps:")
for ispin in range(ns):
print(" Spin:", ispin + 1)
for io, ion in enumerate(ions):
print(" Site:", ion)
iorb_inds = [(ip, param['m']) for ip, param in enumerate(self.proj_params) if param['isite'] == ion]
norb = len(iorb_inds)
dm = np.zeros((norb, norb))
ov = np.zeros((norb, norb))
for ind, iorb in iorb_inds:
for ind2, iorb2 in iorb_inds:
dm[iorb, iorb2] = den_mat[ispin, ind, ind2]
ov[iorb, iorb2] = overlap[ispin, ind, ind2]
print(" Density matrix" + (12*norb - 12 + 2)*" " + "Overlap")
for drow, dov in zip(dm, ov):
out = ''.join(map("{0:12.7f}".format, drow))
out += " "
out += ''.join(map("{0:12.7f}".format, dov))
print(out)
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