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dft_tools/python/triqs_dft_tools/converters/elk.py
Alexander Hampel c4db7e6867 update documentation to use autosummary 
* remove manual module reference files
* move hdf5 structure reference to guide
* fix various doc strings
* remove very old update_archive python script for triqs 1.2
* refine main documentation.rst file -> better overview
2022-03-02 14:13:12 -05:00

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##########################################################################
#
# TRIQS: a Toolbox for Research in Interacting Quantum Systems
#
# Copyright (C) 2019 by A. D. N. James, A. Hampel and M. Aichhorn
#
# 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/>.
#
##########################################################################
"""
Elk converter
"""
from types import *
import numpy
from .converter_tools import *
import os.path
from h5 import *
from locale import atof
from triqs_dft_tools.converters.elktools import readElkfiles as read_Elk
from triqs_dft_tools.converters.elktools import ElkConverterTools as Elk_tools
class ElkConverter(ConverterTools,Elk_tools,read_Elk):
"""
Conversion from Elk output to an hdf5 file that can be used as input for the SumkDFT class.
"""
def __init__(self, filename, hdf_filename=None,
dft_subgrp='dft_input', symmcorr_subgrp='dft_symmcorr_input',
bc_subgrp='dft_bandchar_input', symmpar_subgrp='dft_symmpar_input',
bands_subgrp='dft_bands_input', misc_subgrp='dft_misc_input',
transp_subgrp='dft_transp_input',fs_subgrp='dft_fs_input',
repacking=False):
"""
Initialise the class.
Parameters
----------
filename : string
Base name of DFT files.
hdf_filename : string, optional
Name of hdf5 archive to be created.
dft_subgrp : string, optional
Name of subgroup storing necessary DFT data.
symmcorr_subgrp : string, optional
Name of subgroup storing correlated-shell symmetry data.
parproj_subgrp : string, optional
Name of subgroup storing partial projector data.
symmpar_subgrp : string, optional
Name of subgroup storing partial-projector symmetry data.
bands_subgrp : string, optional
Name of subgroup storing band data.
misc_subgrp : string, optional
Name of subgroup storing miscellaneous DFT data.
transp_subgrp : string, optional
Name of subgroup storing transport data.
repacking : boolean, optional
Does the hdf5 archive need to be repacked to save space?
"""
assert isinstance(filename, str), "ElkConverter: Please provide the DFT files' base name as a string."
if hdf_filename is None:
hdf_filename = filename + '.h5'
self.hdf_file = hdf_filename
self.dft_file = 'PROJ.OUT'
self.band_file = 'BAND.OUT'
self.eval_file = 'EIGVAL.OUT'
self.efermi_file = 'EFERMI.OUT'
self.kp_file = 'KPOINTS.OUT'
self.geom_file='GEOMETRY.OUT'
self.dft_subgrp = dft_subgrp
self.symmcorr_subgrp = symmcorr_subgrp
self.bc_subgrp = bc_subgrp
self.symmpar_subgrp = symmpar_subgrp
self.bands_subgrp = bands_subgrp
self.misc_subgrp = misc_subgrp
self.transp_subgrp = transp_subgrp
self.fs_subgrp = fs_subgrp
self.fortran_to_replace = {'D': 'E'}
# Checks if h5 file is there and repacks it if wanted:
if (os.path.exists(self.hdf_file) and repacking):
ConverterTools.repack(self)
def check_dens(self,n_k,nstsv,occ,bz_weights,n_spin_blocs,band_window,SO):
"""
Check the charge density below the correlated energy window and up to the Fermi level
"""
density_required=0.0E-7
charge_below=0.0E-7
#calculate the valence charge and charge below lower energy window bound
#Elk does not use the tetrahedron method when calculating these charges
for ik in range(n_k):
for ist in range(nstsv):
#calculate the charge over all the bands
density_required+=occ[ik][ist]*bz_weights[ik]
for isp in range(n_spin_blocs):
#Convert occ list from elk to two index format for spins
jst=int((isp)*nstsv*0.5)
#Take lowest index in band_window for SO system
if(SO==0):
nst=band_window[isp][ik, 0]-1
else:
band=[band_window[0][ik, 0],band_window[1][ik, 0]]
nst=min(band)-1
#calculate the charge below energy window
for ist in range(jst,nst):
charge_below+=occ[ik][ist]*bz_weights[ik]
#return charges
return(density_required,charge_below)
def rotsym(self,n_shells,shells,n_symm,ind,basis,T,mat):
"""
Rotates the symmetry matrices into basis defined by the T unitary matrix
the outputted projectors are rotated to the irreducible representation
and then reduced in size to the orbitals used to construct the projectors.
"""
for ish in range(n_shells):
#check that the T matrix is not the Identity (i.e. not using spherical
#harmonics).
if(basis[ish]!=0):
#put mat into temporary matrix
temp=mat
#index range of lm values used to create the Wannier projectors
min_ind=numpy.min(ind[ish][:])
max_ind=numpy.max(ind[ish][:])+1
#dimension of lm values used to construct the projectors
dim=shells[ish]['dim']
#loop over all symmetries
for isym in range(n_symm):
#rotate symmetry matrix into basis defined by T
mat[isym][ish]=numpy.matmul(T[ish],mat[isym][ish])
mat[isym][ish]=numpy.matmul(mat[isym][ish],T[ish].conjugate().transpose())
#put desired subset of transformed symmetry matrix into temp matrix for symmetry isym
for id in range(len(ind[ish])):
i=ind[ish][id]
for jd in range(len(ind[ish][:])):
j=ind[ish][jd]
temp[isym][ish][id,jd]=mat[isym][ish][i,j]
#put temp matrix into mat
mat=temp
#reduce size of lm arrays in mat lm dim
for isym in range(n_symm):
dim=shells[ish]['dim']
mat[isym][ish]=mat[isym][ish][:dim,:dim]
return mat
def update_so_quatities(self,n_shells,shells,n_corr_shells,corr_shells,n_inequiv_shells,dim_reps,n_k,n_symm,n_orbitals,proj_mat,T,su2,mat,sym=True):
"""
Changes the array sizes and elements for arrays used in spin-orbit coupled calculations.
"""
#change dim for each shell
for ish in range(n_shells):
shells[ish]['dim'] = 2*shells[ish]['dim']
for ish in range(n_corr_shells):
corr_shells[ish]['dim'] = 2*corr_shells[ish]['dim']
for ish in range(n_inequiv_shells):
dim_reps[ish]=[2*dim_reps[ish][i] for i in range(len(dim_reps[ish]))]
#Make temporary array of original n_orbitals
n_orbitals_orig=n_orbitals
#Make SO n_orbitals array
#loop over k-points
for ik in range(n_k):
#new orbital array
n_orbitals[ik,0]=max(n_orbitals[ik,:])
#reduce array size
n_orbitals=n_orbitals[:,:1]
#Resize proj_mat, mat, T
#make temporary projector array
proj_mat_tmp = numpy.zeros([n_k, 1, n_corr_shells, max([crsh['dim'] for crsh in corr_shells]), numpy.max(n_orbitals)], numpy.complex_)
for ish in range(n_corr_shells):
#update proj_mat
for ik in range(n_k):
#extra array elements in "dim" dimension
size=int(0.5*corr_shells[ish]['dim'])
#put each spinor into tmp array and ensure elements are assigned correctly in case of change of max(n_orbitals)
proj_mat_tmp[ik][0][ish][0:size][0:n_orbitals_orig[ik,0]]=proj_mat[ik][0][ish][0:size][0:n_orbitals_orig[ik,0]]
#put other spinor projectors into extra "dim" elements
proj_mat_tmp[ik][0][ish][size:2*size][0:n_orbitals_orig[ik,1]]=proj_mat[ik][1][ish][0:size][0:n_orbitals_orig[ik,1]]
#update T
#extra array elements in each dimension
size=2*corr_shells[ish]['l']+1
#extend the arrays
T[ish]=numpy.lib.pad(T[ish],((0,size),(0,size)),'constant',constant_values=(0.0))
#make block diagonal
T[ish][size:2*size,size:2*size]=T[ish][0:size,0:size]
#update the symmetries arrays if needed
if(sym):
#update mat - This includes the spin SU(2) matrix for spin-coupled calculations
#size of each quadrant in the lm symmetry array.
size=int(0.5*corr_shells[ish]['dim'])
#temporary spin block array for SU(2) spin operations on mat
spinmat = numpy.zeros([size,2,size,2],numpy.complex_)
for isym in range(n_symm):
#expand size of array
mat[isym][ish]=numpy.lib.pad(mat[isym][ish],((0,size),(0,size)),'constant',constant_values=(0.0))
#make arraye block diagonal
mat[isym][ish][size:2*size,size:2*size]=mat[isym][ish][0:size,0:size]
#apply SU(2) spin matrices to lm symmetries
#put mat into array of spin blocks
for i1,i2 in numpy.ndindex(2,2):
spinmat[0:size,i1,0:size,i2] = mat[isym][ish][i1*size:(i1+1)*size,i2*size:(i2+1)*size]
#apply the SU(2) spin matrices
for ilm,jlm in numpy.ndindex(size,size):
spinmat[ilm,:,jlm,:] = numpy.dot(su2[isym][:,:],spinmat[ilm,:,jlm,:])
#put spinmat into back in mat format
for i1,i2 in numpy.ndindex(2,2):
mat[isym][ish][i1*size:(i1+1)*size,i2*size:(i2+1)*size] = spinmat[0:size,i1,0:size,i2]
#assign arrays and delete temporary arrays
del proj_mat
proj_mat = proj_mat_tmp
del proj_mat_tmp, n_orbitals_orig
return shells,corr_shells,dim_reps,n_orbitals,proj_mat,T,mat
def sort_dft_eigvalues(self,n_spin_blocs,SO,n_k,n_orbitals,band_window,en,energy_unit):
"""
Rearranges the energy eigenvalue arrays into TRIQS format
"""
hopping = numpy.zeros([n_k, n_spin_blocs, numpy.max(n_orbitals), numpy.max(n_orbitals)], numpy.complex_)
#loop over spin
for isp in range(n_spin_blocs):
#loop over k-points
for ik in range(n_k):
#loop over bands
for ist in range(0,n_orbitals[ik, isp]):
#converter index for spin polarised Elk indices and take SO into consideration
if(SO==0):
jst=int(band_window[isp][ik, 0]-1+ist)
else:
band=[band_window[0][ik, 0],band_window[1][ik, 0]]
jst=int(min(band)-1+ist)
#correlated window energies
hopping[ik,isp,ist,ist]=en[ik][jst]*energy_unit
return hopping
def convert_dft_input(self):
"""
Reads the appropriate files and stores the data for the
- dft_subgrp
- symmcorr_subgrp
- misc_subgrp
in the hdf5 archive.
"""
# Read and write only on the master node
if not (mpi.is_master_node()):
return
filext='.OUT'
dft_file='PROJ'+filext
mpi.report("Reading %s" % dft_file)
#Energy conversion - Elk uses Hartrees
energy_unit = 27.2113850560 # Elk uses hartrees
#The projectors change size per k-point
k_dep_projection = 1
#Symmetries are used
symm_op = 1 # Use symmetry groups for the k-sum
shells=[]
#read information about projectors calculated in the Elk calculation
[gen_info,n_corr_shells,n_inequiv_shells,corr_to_inequiv,inequiv_to_corr,corr_shells,n_reps,dim_reps,ind,basis,T] = read_Elk.read_proj(self,dft_file)
#get info for HDF5 file from gen_info
n_k=gen_info['n_k']
SP=gen_info['spinpol']-1
#Elk uses spinor wavefunctions. Therefore these two spinor wavefunctions have spin-orbit coupling incorporated in them. Here we read in the spinors
n_spin_blocs = SP + 1
SO=gen_info['SO']
n_atoms=gen_info['natm']
#Elk only calculates Wannier projectors (no theta projectors generated):
n_shells=n_corr_shells
for ish in range(n_shells):
shells.append(corr_shells[ish].copy())
#remove last 2 entries from corr_shlls
del shells[ish]['SO']
del shells[ish]['irep']
shells[ish]['dim'] = 2*shells[ish]['l']+1
#read eigenvalues calculated in the Elk calculation
mpi.report("Reading %s and EFERMI.OUT" % self.eval_file)
[en,occ,nstsv]=read_Elk.read_eig(self)
#read projectors calculated in the Elk calculation
proj_mat = numpy.zeros([n_k, n_spin_blocs, n_corr_shells, max([crsh['dim'] for crsh in corr_shells]), nstsv], numpy.complex_)
mpi.report("Reading projector(s)")
for ish in range(n_corr_shells):
[n_orbitals,band_window,rep,proj_mat]=read_Elk.read_projector(self,corr_shells,n_spin_blocs,ish,proj_mat,ind,T,basis,filext)
#read kpoints calculated in the Elk calculation
mpi.report("Reading %s" % self.kp_file)
[bz_weights,vkl]=read_Elk.read_kpoints(self)
#symmetry matrix
mpi.report("Reading GEOMETRY.OUT")
#read in atom posistions, the symmetry operators (in lattice coordinates) and lattice vectors
[ns, na, atpos]=read_Elk.read_geometry(self)
#Read symmetry files
mpi.report("Reading SYMCRYS.OUT")
[n_symm,spinmat,symmat,tr] = read_Elk.readsym(self)
mpi.report("Reading LATTICE.OUT")
[amat,amatinv,bmat,bmatinv] = read_Elk.readlat(self)
#calculating atom permutations
perm = Elk_tools.gen_perm(self,n_symm,ns,na,n_atoms,symmat,tr,atpos)
#determine the cartesian lattice symmetries and the spin axis rotations
#required for the spinors (for SO for now)
su2 = []
symmatc=[]
for isym in range(n_symm):
#convert the lattice symmetry matrices into cartesian coordinates
tmp = numpy.matmul(amat,symmat[isym])
symmatc.append(numpy.matmul(tmp,amatinv))
#convert the spin symmetry matrices into cartesian coordinates
spinmatc = numpy.matmul(amat,spinmat[isym])
spinmatc = numpy.matmul(spinmatc,amatinv)
#calculate the rotation angle and spin axis vector in cartesian coordinates
[v,th] = self.rotaxang(spinmatc[:,:])
#calculate the SU(2) matrix from the angle and spin axis vector
su2.append(self.axangsu2(v,th))
del tmp
#calculating the symmetries in complex harmonics
mat = Elk_tools.symlat_to_complex_harmonics(self,n_symm,n_corr_shells,symmatc,corr_shells)
mat = self.rotsym(n_corr_shells,corr_shells,n_symm,ind,basis,T,mat)
#The reading is done. Some variables may need to change for TRIQS compatibility.
#Alter size of some of the arrays if spin orbit coupling is enabled.
#For SO in Elk, the eigenvalues and eigenvector band indices are in asscending order w.r.t energy
if(SO==1):
[shells,corr_shells,dim_reps,n_orbitals,proj_mat,T,mat]=self.update_so_quatities(n_shells,shells,n_corr_shells,corr_shells,n_inequiv_shells,dim_reps,n_k,n_symm,n_orbitals,proj_mat,T,su2,mat)
#reduce n_spin_blocs
n_spin_blocs = SP + 1 - SO
#put the energy eigenvalues arrays in TRIQS format
hopping = self.sort_dft_eigvalues(n_spin_blocs,SO,n_k,n_orbitals,band_window,en,energy_unit)
#Elk does not use global to local matrix rotation (Rotloc) as is done in Wien2k. However, the projectors
#require a symmetry matrix to rotate from jatom to iatom. Below finds the non inversion
#symmetric matrices which were used in calculating the projectors
use_rotations = 1
rot_mat = [numpy.identity(corr_shells[icrsh]['dim'], numpy.complex_) for icrsh in range(n_corr_shells)]
for icrsh in range(n_corr_shells):
#incrsh = corr_to_inequiv[icrsh]
#iatom = corr_shells[incrsh]['atom']
#want to rotate atom to first inequivalent atom in list
iatom = 1
for isym in range(n_symm):
jatom=perm[isym][corr_shells[icrsh]['atom']-1]
#determinant determines if crystal symmetry matrix has inversion symmetry (=-1)
det = numpy.linalg.det(symmat[isym][:,:])
if((jatom==iatom)&(det>0.0)):
#local rotation which rotates equivalent atom into its local coordinate system
#(inverse of the symmetry operator applied to the projectors in Elk)
rot_mat[icrsh][:,:]=mat[isym][icrsh][:,:].conjugate().transpose()
#used first desired symmetry in crystal symmetry list
break
# Elk does not currently use time inversion symmetry
rot_mat_time_inv = [0 for i in range(n_corr_shells)]
#Check that the charge of all the bands and below the correlated window have been calculated correctly
[density_required, charge_below] = self.check_dens(n_k,nstsv,occ,bz_weights,n_spin_blocs,band_window,SO)
#calculate the required charge (density_required) to remain charge neutral
mpi.report("The total charge of the system = %f" %density_required)
mpi.report("The charge below the correlated window = %f" %charge_below)
mpi.report("The charge within the correlated window = %f" %(density_required - charge_below))
#Elk interface does not calculate theta projectors, hence orbits are the same as Wannier projectors
orbits=[]
#remove the spatom index to avoid errors in the symmetry routines
for ish in range(n_corr_shells):
#remove "spatom"
del corr_shells[ish]['spatom']
orbits.append(corr_shells[ish].copy())
for ish in range(n_shells):
#remove "spatom"
del shells[ish]['spatom']
n_orbits=len(orbits)
#Note that the T numpy array is defined for all shells.
# Save it to the HDF:
ar = HDFArchive(self.hdf_file, 'a')
if not (self.dft_subgrp in ar):
ar.create_group(self.dft_subgrp)
# The subgroup containing the data. If it does not exist, it is
# created. If it exists, the data is overwritten!
things_to_save = ['energy_unit', 'n_k', 'k_dep_projection', 'SP', 'SO', 'charge_below', 'density_required',
'symm_op', 'n_shells', 'shells', 'n_corr_shells', 'corr_shells', 'use_rotations', 'rot_mat',
'rot_mat_time_inv', 'n_reps', 'dim_reps', 'T', 'n_orbitals', 'proj_mat', 'bz_weights', 'hopping',
'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr']
for it in things_to_save:
ar[self.dft_subgrp][it] = locals()[it]
del ar
# Save it to the HDF:
ar = HDFArchive(self.hdf_file, 'a')
symm_subgrp=self.symmcorr_subgrp
#Elk does not use time inversion symmetry
time_inv = [0 for j in range(n_symm)]
mat_tinv = [numpy.identity(orbits[orb]['dim'], numpy.complex_)
for orb in range(n_orbits)]
#Save all the symmetry data
if not (symm_subgrp in ar):
ar.create_group(symm_subgrp)
things_to_save_sym = ['n_symm', 'n_atoms', 'perm',
'orbits', 'SO', 'SP', 'time_inv', 'mat', 'mat_tinv']
for it in things_to_save_sym:
ar[symm_subgrp][it] = locals()[it]
del ar
#Save misc info
things_to_save_misc = ['band_window','vkl','nstsv']
# Save it to the HDF:
ar = HDFArchive(self.hdf_file, 'a')
if not (self.misc_subgrp in ar):
ar.create_group(self.misc_subgrp)
for it in things_to_save_misc:
ar[self.misc_subgrp][it] = locals()[it]
del ar
mpi.report('Converted the Elk ground state data')
def convert_bands_input(self):
"""
Reads the appropriate files and stores the data for the bands_subgrp in the hdf5 archive.
"""
# Read and write only on the master node
if not (mpi.is_master_node()):
return
filext='_WANBAND.OUT'
dft_file='PROJ'+filext
mpi.report("Reading %s" % dft_file)
#Energy conversion - Elk uses Hartrees
energy_unit = 27.2113850560 # Elk uses hartrees
shells=[]
#read information about projectors calculated in the Elk calculation
[gen_info,n_corr_shells,n_inequiv_shells,corr_to_inequiv,inequiv_to_corr,corr_shells,n_reps,dim_reps,ind,basis,T] = read_Elk.read_proj(self,dft_file)
#get info for HDF5 file from gen_info
n_k=gen_info['n_k']
SP=gen_info['spinpol']-1
#Elk uses spinor wavefunctions. Therefore these two spinor wavefunctions have spin-orbit coupling incorporated in them. Here we read in the spinors
n_spin_blocs = SP + 1
SO=gen_info['SO']
#Elk only calculates Wannier projectors (no theta projectors generated):
n_shells=n_corr_shells
for ish in range(n_shells):
shells.append(corr_shells[ish].copy())
#remove last 2 entries from corr_shlls
del shells[ish]['SO']
del shells[ish]['irep']
shells[ish]['dim'] = 2*shells[ish]['l']+1
#read in the band eigenvalues
mpi.report("Reading BAND.OUT")
en=numpy.loadtxt('BAND.OUT')
nstsv=int(len(en[:,1])/n_k)
#convert the en array into a workable format
entmp = numpy.zeros([n_k,nstsv], numpy.complex_)
enj=0
for ist in range(nstsv):
for ik in range(n_k):
entmp[ik,ist]=en[enj,1]
enj+=1
del en
#read projectors
proj_mat = numpy.zeros([n_k, n_spin_blocs, n_corr_shells, max([crsh['dim'] for crsh in corr_shells]), nstsv], numpy.complex_)
mpi.report("Reading projector(s)")
for ish in range(n_corr_shells):
[n_orbitals,band_window,rep,proj_mat]=read_Elk.read_projector(self,corr_shells,n_spin_blocs,ish,proj_mat,ind,T,basis,filext)
#alter arrays for spin-orbit coupling
if(SO==1):
mat=[]
su2=[]
n_symm=1
[shells,corr_shells,dim_reps,n_orbitals,proj_mat,T,mat]=self.update_so_quatities(n_shells,shells,n_corr_shells,corr_shells,n_inequiv_shells,dim_reps,n_k,n_symm,n_orbitals,proj_mat,T,su2,mat,sym=False)
#reduce n_spin_blocs
n_spin_blocs = SP + 1 - SO
#put the energy eigenvalues arrays in TRIQS format
hopping = self.sort_dft_eigvalues(n_spin_blocs,SO,n_k,n_orbitals,band_window,entmp,energy_unit)
# No partial projectors generate, set to 0:
n_parproj = numpy.array([0])
proj_mat_all = numpy.array([0])
# Save it to the HDF:
ar = HDFArchive(self.hdf_file, 'a')
if not (self.bands_subgrp in ar):
ar.create_group(self.bands_subgrp)
# The subgroup containing the data. If it does not exist, it is
# created. If it exists, the data is overwritten!
things_to_save = ['n_k', 'n_orbitals', 'proj_mat',
'hopping', 'n_parproj', 'proj_mat_all']
for it in things_to_save:
ar[self.bands_subgrp][it] = locals()[it]
del ar
mpi.report('Converted the band data')
def convert_fs_input(self):
"""
Reads the appropriate files and stores the data for the FS_subgrp in the hdf5 archive.
"""
# Read and write only on the master node
if not (mpi.is_master_node()):
return
filext='_FS.OUT'
dft_file='PROJ'+filext
mpi.report("Reading %s" % dft_file)
#Energy conversion - Elk uses Hartrees
energy_unit = 27.2113850560 # Elk uses hartrees
shells=[]
#read information about projectors calculated in the Elk calculation
[gen_info,n_corr_shells,n_inequiv_shells,corr_to_inequiv,inequiv_to_corr,corr_shells,n_reps,dim_reps,ind,basis,T] = read_Elk.read_proj(self,dft_file)
#get info for HDF5 file from gen_info
n_k=gen_info['n_k']
SP=gen_info['spinpol']-1
#Elk uses spinor wavefunctions. Therefore these two spinor wavefunctions have spin-orbit coupling incorporated in them. Here we read in the spinors
n_spin_blocs = SP + 1
SO=gen_info['SO']
#Elk only calculates Wannier projectors (no theta projectors generated):
n_shells=n_corr_shells
for ish in range(n_shells):
shells.append(corr_shells[ish].copy())
#remove last 2 entries from corr_shlls
del shells[ish]['SO']
del shells[ish]['irep']
shells[ish]['dim'] = 2*shells[ish]['l']+1
#read in the eigenvalues used for the FS calculation
mpi.report("Reading EIGVAL_FS.OUT and EFERMI.OUT")
[en,occ,nstsv]=read_Elk.read_eig(self,filext=filext)
#read kpoints calculated in the Elk FS calculation
mpi.report("Reading KPOINT_FS.OUT")
[bz_weights,vkl]=read_Elk.read_kpoints(self,filext=filext)
#read projectors
proj_mat = numpy.zeros([n_k, n_spin_blocs, n_corr_shells, max([crsh['dim'] for crsh in corr_shells]), nstsv], numpy.complex_)
mpi.report("Reading projector(s)")
for ish in range(n_corr_shells):
[n_orbitals,band_window,rep,proj_mat]=read_Elk.read_projector(self,corr_shells,n_spin_blocs,ish,proj_mat,ind,T,basis,filext)
#Need lattice symmetries to unfold the irreducible BZ
#Read symmetry files
mpi.report("Reading SYMCRYS.OUT")
[n_symm,spinmat,symlat,tr] = read_Elk.readsym(self)
mpi.report("Reading LATTICE.OUT")
[amat,amatinv,bmat,bmatinv] = read_Elk.readlat(self)
#Put eigenvalues into array of eigenvalues for the correlated window
#alter arrays for spin-orbit coupling
if(SO==1):
mat=[]
su2=[]
[shells,corr_shells,dim_reps,n_orbitals,proj_mat,T,mat]=self.update_so_quatities(n_shells,shells,n_corr_shells,corr_shells,n_inequiv_shells,dim_reps,n_k,n_symm,n_orbitals,proj_mat,T,su2,mat,sym=False)
#reduce n_spin_blocs
n_spin_blocs = SP + 1 - SO
#put the energy eigenvalues arrays in TRIQS format
hopping = self.sort_dft_eigvalues(n_spin_blocs,SO,n_k,n_orbitals,band_window,en,energy_unit)
# Save it to the HDF:
ar = HDFArchive(self.hdf_file, 'a')
if not (self.fs_subgrp in ar):
ar.create_group(self.fs_subgrp)
# The subgroup containing the data. If it does not exist, it is
# created. If it exists, the data is overwritten!
things_to_save = ['n_k', 'n_orbitals', 'proj_mat','bmat',
'hopping', 'vkl','symlat', 'n_symm']
for it in things_to_save:
ar[self.fs_subgrp][it] = locals()[it]
del ar
mpi.report('Converted the FS data')
def dft_band_characters(self):
"""
Reads in the band characters generated in Elk to be used for
PDOS and band character band structure plots.
"""
if not (mpi.is_master_node()):
return
mpi.report("Reading BC.OUT")
# get needed data from hdf file
# from general info
ar = HDFArchive(self.hdf_file, 'a')
things_to_read = ['SP', 'SO','n_k','n_orbitals']
for it in things_to_read:
if not hasattr(self, it):
setattr(self, it, ar[self.dft_subgrp][it])
#from misc info
things_to_read = ['nstsv','band_window']
for it in things_to_read:
if not hasattr(self, it):
setattr(self, it, ar[self.misc_subgrp][it])
#from sym info
things_to_read = ['n_atoms']
symm_subgrp=self.symmcorr_subgrp
for it in things_to_read:
if not hasattr(self, it):
setattr(self, it, ar[symm_subgrp][it])
#read in band characters
[bc,maxlm] = read_Elk.read_bc(self)
#set up SO bc array
if (self.SO):
tmp = numpy.zeros([2*maxlm,1,self.n_atoms,self.nstsv,self.n_k], numpy.float_)
#put both spinors into the lm array indices.
tmp[0:maxlm,0,:,:,:]=bc[0:maxlm,0,:,:,:]
tmp[maxlm:2*maxlm,0,:,:,:]=bc[0:maxlm,1,:,:,:]
maxlm=2*maxlm
del bc
bc = tmp
del tmp
#reduce bc matrix to band states stored in hdf file
n_spin_blocs=self.SP+1-self.SO
tmp = numpy.zeros([maxlm,n_spin_blocs,self.n_atoms,numpy.max(self.n_orbitals),self.n_k], numpy.float_)
for ik in range(self.n_k):
for isp in range(n_spin_blocs):
nst=self.n_orbitals[ik,isp]
ibot=self.band_window[isp][ik, 0]-1
itop=ibot+nst
tmp[:,isp,:,0:nst,ik]=bc[:,isp,:,ibot:itop,ik]
del bc
bc = tmp
del tmp
things_to_save = ['maxlm', 'bc']
if not (self.bc_subgrp in ar):
ar.create_group(self.bc_subgrp)
for it in things_to_save:
ar[self.bc_subgrp][it] = locals()[it]
del ar
mpi.report('Converted the band character data')
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