mirror of https://github.com/triqs/dft_tools
191 lines
7.9 KiB
Python
191 lines
7.9 KiB
Python
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################################################################################
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#
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# TRIQS: a Toolbox for Research in Interacting Quantum Systems
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#
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# Copyright (C) 2011 by M. Ferrero, O. Parcollet
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#
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# DFT tools: Copyright (C) 2011 by M. Aichhorn, L. Pourovskii, V. Vildosola
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#
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# PLOVasp: Copyright (C) 2015 by O. E. Peil
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#
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# TRIQS is free software: you can redistribute it and/or modify it under the
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# terms of the GNU General Public License as published by the Free Software
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# Foundation, either version 3 of the License, or (at your option) any later
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# version.
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#
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# TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY
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# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
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# details.
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#
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# You should have received a copy of the GNU General Public License along with
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# TRIQS. If not, see <http://www.gnu.org/licenses/>.
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#
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################################################################################
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r"""
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plovasp.elstruct
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================
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Internal representation of VASP electronic structure data.
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"""
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import numpy as np
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class ElectronicStructure:
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"""
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Class containing electronic structure data.
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**Parameters:**
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- *natom* (int) : total number of atoms
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- *nktot* (int) : total number of `k`-points
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- *nband* (int) : total number of bands
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- *nspin* (int) : spin-polarization
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- *nc_flag* (True/False) : non-collinearity flag
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- *efermi* (float) : Fermi level read from DOSCAR
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- *proj_raw* (array[complex]) : raw projectors from PLOCAR
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- *eigvals* (array[float]) : KS eigenvalues
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- *ferw* (array[float]) : Fermi weights from VASP
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- *kmesh* (dict) : parameters of the `k`-mesh
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- *structure* (dict) : parameters of the crystal structure
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- *symmetry* (dict) : paramters of symmetry
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When the object is created a simple consistency check
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of the data coming from different VASP files is performed.
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"""
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def __init__(self, vasp_data):
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self.natom = vasp_data.poscar.nq
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self.type_of_ion = vasp_data.poscar.type_of_ion
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self.nktot = vasp_data.kpoints.nktot
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self.kmesh = {'nktot': self.nktot}
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self.kmesh['kpoints'] = vasp_data.kpoints.kpts
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self.kmesh['kweights'] = vasp_data.kpoints.kwghts
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try:
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self.kmesh['ntet'] = vasp_data.kpoints.ntet
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self.kmesh['itet'] = vasp_data.kpoints.itet
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self.kmesh['volt'] = vasp_data.kpoints.volt
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except AttributeError:
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pass
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# Note that one should not subtract this Fermi level from eigenvalues
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# here because the true Fermi level might be provided by conf-file
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# (for instance, for spaghetti calculations)
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try:
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self.efermi = vasp_data.doscar.efermi
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except AttributeError:
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pass
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# Note that the number of spin-components of projectors might be different from those
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# of bands in case of non-collinear calculations
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self.nspin = vasp_data.plocar.nspin
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self.nc_flag = vasp_data.plocar.ncdij == 4
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self.nband = vasp_data.plocar.nband
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# Check that the number of k-points is the same in all files
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_, ns_plo, nk_plo, nb_plo = vasp_data.plocar.plo.shape
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assert nk_plo == self.nktot, "PLOCAR is inconsistent with IBZKPT (number of k-points)"
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# FIXME: Reading from EIGENVAL is obsolete and should be
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# removed completely.
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# if not vasp_data.eigenval.eigs is None:
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if False:
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print("eigvals from EIGENVAL")
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self.eigvals = vasp_data.eigenval.eigs
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self.ferw = vasp_data.eigenval.ferw.transpose((2, 0, 1))
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nk_eig = vasp_data.eigenval.nktot
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assert nk_eig == self.nktot, "PLOCAR is inconsistent with EIGENVAL (number of k-points)"
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# Check that the number of band is the same in PROJCAR and EIGENVAL
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assert nb_plo == self.nband, "PLOCAR is inconsistent with EIGENVAL (number of bands)"
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else:
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print("eigvals from LOCPROJ")
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self.eigvals = vasp_data.plocar.eigs
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self.ferw = vasp_data.plocar.ferw.transpose((2, 0, 1))
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self.efermi = vasp_data.doscar.efermi
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# For later use it is more convenient to use a different order of indices
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# [see ProjectorGroup.orthogonalization()]
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self.proj_raw = vasp_data.plocar.plo
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self.proj_params = vasp_data.plocar.proj_params
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# Not needed any more since PROJCAR contains projectors only for a subset of sites
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# Check that the number of atoms is the same in PLOCAR and POSCAR
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# natom_plo = vasp_data.plocar.params['nion']
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# assert natom_plo == self.natom, "PLOCAR is inconsistent with POSCAR (number of atoms)"
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self.structure = {'a_brav': vasp_data.poscar.a_brav}
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self.structure['nqtot'] = vasp_data.poscar.nq
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self.structure['kpt_basis'] = vasp_data.poscar.kpt_basis
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self.structure['ntypes'] = vasp_data.poscar.ntypes
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self.structure['nq_types'] = vasp_data.poscar.nions
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# Concatenate coordinates grouped by type into one array
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self.structure['qcoords'] = np.vstack(vasp_data.poscar.q_types)
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self.structure['type_of_ion'] = vasp_data.poscar.type_of_ion
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self.kmesh['kpoints_cart'] = 0.0 * self.kmesh['kpoints']
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for ik in range(self.nktot):
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for ii in range(3):
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self.kmesh['kpoints_cart'][ik] += self.kmesh['kpoints'][ik,ii]*self.structure['kpt_basis'][:,ii]
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# FIXME: This can be removed if ion coordinates are stored in a continuous array
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## Construct a map to access coordinates by index
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# self.structure['ion_index'] = []
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# for isort, nq in enumerate(self.structure['nq_types']):
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# for iq in range(nq):
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# self.structure['ion_index'].append((isort, iq))
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def debug_density_matrix(self):
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"""
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Calculate and output the density and overlap matrix out of projectors defined in el_struct.
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"""
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plo = self.proj_raw
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nproj, ns, nk, nb = plo.shape
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ions = sorted(list(set([param['isite'] for param in self.proj_params])))
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nions = len(ions)
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norb = nproj // nions
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# Spin factor
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sp_fac = 2.0 if ns == 1 and not self.nc_flag else 1.0
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den_mat = np.zeros((ns, nproj, nproj), dtype=float)
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overlap = np.zeros((ns, nproj, nproj), dtype=float)
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# ov_min = np.ones((ns, nproj, nproj), dtype=float) * 100.0
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# ov_max = np.zeros((ns, nproj, nproj), dtype=float)
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for ispin in range(ns):
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for ik in range(nk):
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kweight = self.kmesh['kweights'][ik]
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occ = self.ferw[ispin, ik, :]
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den_mat[ispin, :, :] += np.dot(plo[:, ispin, ik, :] * occ, plo[:, ispin, ik, :].T.conj()).real * kweight * sp_fac
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ov = np.dot(plo[:, ispin, ik, :], plo[:, ispin, ik, :].T.conj()).real
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overlap[ispin, :, :] += ov * kweight
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# ov_max = np.maximum(ov, ov_max)
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# ov_min = np.minimum(ov, ov_min)
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# Output only the site-diagonal parts of the matrices
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print()
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print(" Unorthonormalized density matrices and overlaps:")
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for ispin in range(ns):
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print(" Spin:", ispin + 1)
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for io, ion in enumerate(ions):
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print(" Site:", ion)
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iorb_inds = [(ip, param['m']) for ip, param in enumerate(self.proj_params) if param['isite'] == ion]
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norb = len(iorb_inds)
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dm = np.zeros((norb, norb))
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ov = np.zeros((norb, norb))
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for ind, iorb in iorb_inds:
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for ind2, iorb2 in iorb_inds:
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dm[iorb, iorb2] = den_mat[ispin, ind, ind2]
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ov[iorb, iorb2] = overlap[ispin, ind, ind2]
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print(" Density matrix" + (12*norb - 12 + 2)*" " + "Overlap")
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for drow, dov in zip(dm, ov):
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out = ''.join(map("{0:12.7f}".format, drow))
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out += " "
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out += ''.join(map("{0:12.7f}".format, dov))
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print(out)
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