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![Oleg E. Peil](/assets/img/avatar_default.png)
In the new version of VASP LOCPROJ contains the eigenvalues and Fermi weights. Also, during a charge self-consistency calculation the file EIGENVAL is not written at intermediate iterations. It is, thus, preferential to use LOCPROJ to get the named data. At the moment, EIGENVAL will still be used if it is complete but in the future this dependence should be removed completely.
138 lines
5.6 KiB
Python
138 lines
5.6 KiB
Python
r"""
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vasp.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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self.efermi = vasp_data.doscar.efermi
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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.doscar.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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if not vasp_data.eigenval.eigs is None:
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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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# 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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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 = 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=np.float64)
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overlap = np.zeros((ns, nproj, nproj), dtype=np.float64)
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# ov_min = np.ones((ns, nproj, nproj), dtype=np.float64) * 100.0
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# ov_max = np.zeros((ns, nproj, nproj), dtype=np.float64)
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for ispin in xrange(ns):
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for ik in xrange(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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for ispin in xrange(ns):
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print
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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)*" " + "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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