Source code for triqs_dft_tools.converters.plovasp.elstruct


################################################################################
#
# 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
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# details.
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# 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

[docs] 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. """
[docs] 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))
[docs] 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)