Elk Transport code and subsequent updates (#229)

* elk-transport
* minor updates
* specify explicitly fortran compiler and python exe in CMAKE

Co-authored-by: Alexander Hampel <ahampel@flatironinstitute.org>
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@ -145,6 +145,8 @@ endif()
# Python
if(PythonSupport)
add_subdirectory(python/${PROJECT_NAME})
# elk binary i/o code for wrappers
add_subdirectory(python/${PROJECT_NAME}/converters/elktools/elkwrappers)
endif()
# Docs

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@ -45,13 +45,17 @@ First perform a standard :ref:`DFT+DMFT calculation <full_charge_selfcons>` for
real-frequency self energy.
.. note::
If you use a CT-QMC impurity solver you need to perform an **analytic continuation** of
self energies and Green functions from Matsubara frequencies to the real-frequency axis!
This packages does NOT provide methods to do this, but a list of options available within the TRIQS framework
is given :ref:`here <ac>`. Keep in mind that all these methods have to be used very carefully. Especially for optics calculations
it is crucial to perform the analytic continuation in such a way that the real-frequency self energy
is accurate around the Fermi energy as low-energy features strongly influence the final results.
If you use a CT-QMC impurity solver you need to perform an **analytic continuation** of
self energies and Green functions from Matsubara frequencies to the real-frequency axis!
This packages does NOT provide methods to do this, but a list of options available within the TRIQS framework
is given :ref:`here <ac>`. Keep in mind that all these methods have to be used very carefully. Especially for optics calculations
it is crucial to perform the analytic continuation in such a way that the real-frequency self energy
is accurate around the Fermi energy as low-energy features strongly influence the final results.
Below will describe the prerequisites from the different DFT codes.
Prequisites from Wien2k
^^^^^^^^^^^^^^^^^^^^^^^
Besides the self energy the Wien2k files read by the transport converter (:meth:`convert_transport_input <dft.converters.wien2k.Wien2kConverter.convert_transport_input>`) are:
* :file:`.struct`: The lattice constants specified in the struct file are used to calculate the unit cell volume.
* :file:`.outputs`: In this file the k-point symmetries are given.
@ -61,8 +65,22 @@ Besides the self energy the Wien2k files read by the transport converter (:meth:
* :file:`.h5`: The hdf5 archive has to be present and should contain the dft_input subgroup. Otherwise :meth:`convert_dft_input <dft.converters.wien2k.Wien2kConverter.convert_dft_input>` needs to be called before :meth:`convert_transport_input <dft.converters.wien2k.Wien2kConverter.convert_transport_input>`.
These Wien2k files are read and the relevant information is stored in the hdf5 archive by using the following::
from triqs_dft_tools.converters.wien2k import *
from triqs_dft_tools.sumk_dft_tools import *
Converter = Wien2kConverter(filename='case', repacking=True)
Converter.convert_transport_input()
SK = SumkDFTTools(hdf_file='case.h5', use_dft_blocks=True)
The converter :meth:`convert_transport_input <dft.converters.wien2k.Wien2kConverter.convert_transport_input>`
reads the required data of the Wien2k output and stores it in the `dft_transp_input` subgroup of your hdf file.
Wien2k optics package
---------------------
^^^^^^^^^^^^^^^^^^^^^
The basics steps to calculate the matrix elements of the momentum operator with the Wien2k optics package are:
1) Perform a standard Wien2k calculation for your material.
@ -79,22 +97,39 @@ You can read off the Fermi energy from the :file:`case.scf2` file. Please do not
Furthermore it is necessary to set line 6 to "ON" and put a "1" in the following line to enable the printing of the matrix elements to :file:`case.pmat`.
Using the transport code
------------------------
First we have to read the Wien2k files and store the relevant information in the hdf5 archive::
from triqs_dft_tools.converters.wien2k import *
Prequisites from Elk
^^^^^^^^^^^^^^^^^^^^
The Elk transport converter (:meth:`convert_transport_input <dft.converters.elk.ElkConverter.convert_transport_input>`) reads in the following files:
* `LATTICE.OUT`: Real and reciprocal lattice structure and cell volumes.
* `SYMCRYS.OUT`: Crystal symmetries.
* `PMAT.OUT`: Fortran binary containing the velocity matrix elements.
* :file:`.h5`: The hdf5 archive has to be present and should contain the dft_input subgroup. Otherwise :meth:`convert_dft_input <dft.converters.elk.ElkConverter.convert_dft_input>` needs to be called before :meth:`convert_transport_input <dft.converters.elk.ElkConverter.convert_transport_input>`. It is recommended to call :meth:`convert_dft_input <dft.converters.elk.ElkConverter.convert_dft_input>` before :meth:`convert_transport_input <dft.converters.elk.ElkConverter.convert_transport_input>`.
Except for `PMAT.OUT`, the other files are standard outputs from Elk's groundstate calculation and are used in :meth:`convert_dft_input <dft.converters.elk.ElkConverter.convert_dft_input>`. The `PMAT.OUT` file on the otherhand is generated by Elk by running **task 120**, see [#userguide2]_. Note that unlike in the Wien2k transport converter, the Elk transport converter uses the correlated band window stored in the `dft_misc_input` (which originates from running :meth:`convert_dft_input <dft.converters.elk.ElkConverter.convert_dft_input>`).
These Elk files are then read and the relevant information is stored in the hdf5 archive by using the following::
from triqs_dft_tools.converters.elk import *
from triqs_dft_tools.sumk_dft_tools import *
Converter = Wien2kConverter(filename='case', repacking=True)
Converter = ElkConverter(filename='case', repacking=True)
Converter.convert_transport_input()
SK = SumkDFTTools(hdf_file='case.h5', use_dft_blocks=True)
The converter :meth:`convert_transport_input <dft.converters.wien2k.Wien2kConverter.convert_transport_input>`
reads the required data of the Wien2k output and stores it in the `dft_transp_input` subgroup of your hdf file.
Additionally we need to read and set the self energy, the chemical potential and the double counting::
reads the required data of the Elk output and stores it in the `dft_transp_input` subgroup of your hdf file.
Using the transport code
------------------------
Once we have converted the transport data from the DFT codes (see above), we also need to read and set the self energy, the chemical potential and the double counting::
with HDFArchive('case.h5', 'r') as ar:
SK.set_Sigma([ar['dmft_output']['Sigma_w']])
@ -108,18 +143,18 @@ As next step we can calculate the transport distribution :math:`\Gamma_{\alpha\b
with_Sigma=True, broadening=0.0, beta=40)
Here the transport distribution is calculated in :math:`xx` direction for the frequencies :math:`\Omega=0.0` and :math:`0.1`.
To use the previously obtained self energy we set with_Sigma to True and the broadening to :math:`0.0`.
To use the previously obtained self energy we set `with_Sigma` to **True** and the broadening to :math:`0.0`.
As we also want to calculate the Seebeck coefficient and the thermal conductivity we have to include :math:`\Omega=0.0` in the mesh.
Note that the current version of the code repines the :math:`\Omega` values to the closest values on the self energy mesh.
For complete description of the input parameters see the :meth:`transport_distribution reference <dft.sumk_dft_tools.SumkDFTTools.transport_distribution>`.
The resulting transport distribution is not automatically saved, but this can be easily achieved with::
SK.save(['Gamma_w','Om_meshr','omega','directions'])
SK.save(['Gamma_w','Om_mesh','omega','directions'])
You can retrieve it from the archive by::
SK.Gamma_w, SK.Om_meshr, SK.omega, SK.directions = SK.load(['Gamma_w','Om_meshr','omega','directions'])
SK.Gamma_w, SK.Om_mesh, SK.omega, SK.directions = SK.load(['Gamma_w','Om_mesh','omega','directions'])
Finally the optical conductivity :math:`\sigma(\Omega)`, the Seebeck coefficient :math:`S` and the thermal conductivity :math:`\kappa^{\text{el}}` can be obtained with::
@ -129,9 +164,44 @@ Finally the optical conductivity :math:`\sigma(\Omega)`, the Seebeck coefficient
It is strongly advised to check convergence in the number of k-points!
Example
-------
Here we present an example calculation of the DFT optical conductivity of SrVO3 comparing the results from the Elk and Wien2k inputs. The DFT codes used 4495 k-points in the
irreducible Brillouin zone with Wanner projectors generated within a correlated energy window of [-8, 7.5] eV. We assume that the required DFT files have been read and saved by the TRIQS
interface routines as discussed previously. Below is an example script to generate the conductivities::
from sumk_dft_tools import *
import numpy
SK = SumkDFTTools(hdf_file=filename+'.h5', use_dft_blocks=True)
#Generate numpy mesh for omega values
om_mesh = list(numpy.linspace(0.0,5.0,51))
#Generate and save the transport distribution
SK.transport_distribution(directions=['xx'], Om_mesh=om_mesh, energy_window=[-8.0, 7.5], with_Sigma=False, broadening=-0.05, beta=40, n_om=1000)
SK.save(['Gamma_w','Om_mesh','omega','directions'])
#Generate and save conductivities
SK.conductivity_and_seebeck(beta=40)
SK.save(['seebeck','optic_cond','kappa'])
The optic_cond variable can be loaded by using :meth:`SK.load` and then plotted to generate the following figure.
.. image:: transport_plots/opt_comp.png
:width: 700
:align: center
Note that the differences between the conductivities arise from the differences in the velocities generated in the DFT codes. The DMFT optical conductivity can easily be calculated by adjusting
the above example script by setting `with_Sigma` to **True**. In this case however, the SK object will need the DMFT self-energy on the real frequency axis.
References
----------
.. [#transp1] `V. S. Oudovenko, G. Palsson, K. Haule, G. Kotliar, S. Y. Savrasov, Phys. Rev. B 73, 035120 (2006) <http://link.aps.org/doi/10.1103/PhysRevB.73.0351>`_
.. [#transp2] `J. M. Tomczak, K. Haule, T. Miyake, A. Georges, G. Kotliar, Phys. Rev. B 82, 085104 (2010) <https://link.aps.org/doi/10.1103/PhysRevB.82.085104>`_
.. [#userguide] `P. Blaha, K. Schwarz, G. K. H. Madsen, D. Kvasnicka, J. Luitz, ISBN 3-9501031-1-2 <http://www.wien2k.at/reg_user/textbooks/usersguide.pdf>`_
.. [#userguide2] `J. K. Dewhurst, S. Sharma, L. Nordstrom, F. Cricchio, O. Granas, and E. K. U. Gross, The Elk Code Manual <https://elk.sourceforge.io/elk.pdf>`_

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@ -310,7 +310,7 @@ class ElkConverter(ConverterTools,Elk_tools,read_Elk):
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)
[amat,amatinv,bmat,bmatinv,cell_vol] = 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
@ -388,9 +388,12 @@ class ElkConverter(ConverterTools,Elk_tools,read_Elk):
#remove "spatom"
del shells[ish]['spatom']
n_orbits=len(orbits)
#Note that the T numpy array is defined for all shells.
#new variable: dft_code - this determines which DFT code the inputs come from.
#used for certain routines within dft_tools if treating the inputs differently is required.
dft_code = 'elk'
# Save it to the HDF:
ar = HDFArchive(self.hdf_file, 'a')
if not (self.dft_subgrp in ar):
@ -400,7 +403,7 @@ class ElkConverter(ConverterTools,Elk_tools,read_Elk):
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']
'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr', 'dft_code']
for it in things_to_save:
ar[self.dft_subgrp][it] = locals()[it]
del ar
@ -647,3 +650,110 @@ class ElkConverter(ConverterTools,Elk_tools,read_Elk):
del ar
mpi.report('Converted the band character data')
def convert_transport_input(self):
"""
Reads the necessary information for transport calculations on:
- the optical band window and the velocity matrix elements from :file:`case.pmat`
and stores the data in the hdf5 archive.
"""
if not (mpi.is_master_node()):
return
# get needed data from hdf file
with HDFArchive(self.hdf_file, 'r') as ar:
if not (self.dft_subgrp in ar):
raise IOError("convert_transport_input: No %s subgroup in hdf file found! Call convert_dft_input first." % self.dft_subgrp)
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 = ['band_window','vkl','nstsv']
for it in things_to_read:
if not hasattr(self, it):
setattr(self, it, ar[self.misc_subgrp][it])
#unlike in WIEN2k, Elk writes the velocities (momentum) matrix elements for all bands.
#Therefore, we can use the indices in the n_orbitals array to extract the desired elements.
#However, the PMAT.OUT file is in Fortran-binary, so the file is read in by python wrappers
#around the reading fortran code.
# Read relevant data from PMAT.OUT binary file
###########################################
# band_window_optics: same as Elk converter's band_window, but rearranged to be compatible
# for the transport calculations.
# velocities_k: velocity (momentum) matrix elements between all bands in band_window_optics
# and each k-point.
#load fortran wrapper module
import triqs_dft_tools.converters.elktools.elkwrappers.getpmatelk as et
#elk velocities for all bands
pmat=numpy.zeros([self.nstsv,self.nstsv,3],dtype=complex)
n_spin_blocks = self.SP + 1 - self.SO
#TRIQS' velocities array used in its transport routines
velocities_k = [[] for isp in range(n_spin_blocks)]
#TRIQS' band_window array used in its transport routines
band_window_optics = []
mpi.report("Reading PMAT.OUT")
#read velocities for each k-point
for ik in range(self.n_k):
#need to use a fortran array for wrapper
f_vkl = numpy.asfortranarray(self.vkl[ik,:])
#read the ik velocity using the wrapper
pmat[:,:,:]=et.getpmatelk(ik+1,self.nstsv,f_vkl)
#loop over spin
for isp in range(n_spin_blocks):
#no. correlated bands at ik
nu1=self.band_window[isp][ik,0]-1
nu2=self.band_window[isp][ik,1]-1
n_bands=nu2-nu1+1
#put into velocity array (code similar to that in wien.py.
if n_bands <= 0:
velocity_xyz = numpy.zeros((1, 1, 3), dtype=complex)
else:
velocity_xyz = numpy.zeros(
(n_bands, n_bands, 3), dtype=complex)
#CHECK these lines
velocity_xyz[:,:,:]=pmat[nu1:nu2+1,nu1:nu2+1,:]
velocities_k[isp].append(velocity_xyz)
#rearrange Elk's band_window array into band_window_optics array format
for isp in range(n_spin_blocks):
band_window_optics_isp = []
for ik in range(self.n_k):
nu1=self.band_window[isp][ik,0]
nu2=self.band_window[isp][ik,1]
band_window_optics_isp.append((nu1, nu2))
n_bands=nu2-nu1+1
band_window_optics.append(numpy.array(band_window_optics_isp))
#read in the cell volume from LATTICE.OUT
mpi.report("Reading LATTICE.OUT")
[amat,amatinv,bmat,bmatinv,cell_vol] = read_Elk.readlat(self)
#read in the crystal symmetries
mpi.report("Reading SYMCRYS.OUT")
[n_symmetries,spinmat,rot_symmetries,tr] = read_Elk.readsym(self)
# Put data to HDF5 file
with HDFArchive(self.hdf_file, 'a') as ar:
if not (self.transp_subgrp in ar):
ar.create_group(self.transp_subgrp)
# The subgroup containing the data. If it does not exist, it is
# created. If it exists, the data is overwritten!!!
things_to_save = ['band_window_optics', 'velocities_k']
for it in things_to_save:
ar[self.transp_subgrp][it] = locals()[it]
things_to_save_misc = ['n_symmetries', 'rot_symmetries','cell_vol']
for it in things_to_save_misc:
ar[self.misc_subgrp][it] = locals()[it]
mpi.report("Reading complete!")

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@ -0,0 +1,34 @@
# List the sources
set(module_name "getpmatelk")
set(fortran_src_file "${CMAKE_CURRENT_SOURCE_DIR}/getpmatelk.f90")
set(generated_module_file ${module_name}${TRIQS_PYTHON_MODULE_EXT})
add_custom_target(${module_name} ALL
DEPENDS ${generated_module_file}
)
##generate the fortran python wrapper shared library
add_custom_command(
OUTPUT ${generated_module_file}
COMMAND ${TRIQS_PYTHON_EXECUTABLE} -m numpy.f2py --f90exec=${CMAKE_Fortran_COMPILER} -c ${fortran_src_file} -m ${module_name} > elk_f2py.log
WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}
)
# where to install
install(DIRECTORY ${CMAKE_CURRENT_BINARY_DIR} DESTINATION
${TRIQS_PYTHON_LIB_DEST_ROOT}/${PROJECT_NAME}/converters/elktools FILES_MATCHING PATTERN "*.so"
PERMISSIONS OWNER_READ OWNER_WRITE OWNER_EXECUTE GROUP_READ GROUP_EXECUTE
WORLD_READ WORLD_EXECUTE PATTERN "CMakeFiles" EXCLUDE)
message(STATUS "foo include dir: ${CMAKE_CURRENT_BINARY_DIR}")
message(STATUS "foo include dir: ${CMAKE_BINARY_DIR}")
message(STATUS "foo include dir: ${TRIQS_PYTHON_LIB_DEST_ROOT}/${PROJECT_NAME}")
# user warning
message(STATUS "-----------------------------------------------------------------------------")
message(STATUS " ******** USER NOTE ******** ")
message(STATUS " This version of DFTTools contains interface routines to read Elk's binary ")
message(STATUS " files. ")
message(STATUS "-----------------------------------------------------------------------------")

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@ -0,0 +1,65 @@
! Copyright (C) 2010 S. Sharma, J. K. Dewhurst and E. K. U. Gross.
! This file is distributed under the terms of the GNU General Public License.
! version 6.2.8 file modified by A. D. N. James for interface with TRIQS
subroutine getpmatelk(ik,nstsv,vkl,pmat)
!use modmain
implicit none
! arguments
integer, intent(in) :: ik !Need to read this in for the interface
integer, intent(in) :: nstsv !Need to read this in for the interface
real(8), intent(in) :: vkl(3) !TRIQS uses reduced kpts set
complex(8), intent(out) :: pmat(nstsv,nstsv,3)
! local variables
integer recl,nstsv_,i
real(8) vkl_(3),t1
!adnj - set up tolerance for lattice vectors, although this is an input in Elk,
! it is not advised to change this in Elk. Therefore, it should be fine to set
!it as a constant here.
real(8) epslat
epslat=1.d-6
! find the record length
inquire(iolength=recl) vkl_,nstsv_,pmat
!$OMP CRITICAL(u150)
do i=1,2
open(150,file='PMAT.OUT',form='UNFORMATTED',access='DIRECT',recl=recl,err=10)
read(150,rec=ik,err=10) vkl_,nstsv_,pmat
exit
10 continue
if (i.eq.2) then
write(*,*)
write(*,'("Error(getpmat): unable to read from PMAT.OUT")')
write(*,*)
stop
end if
close(150)
end do
!$OMP END CRITICAL(u150)
!adnj edit - updated for vkl array from TRIQS
t1=abs(vkl(1)-vkl_(1))+abs(vkl(2)-vkl_(2))+abs(vkl(3)-vkl_(3))
if (t1.gt.epslat) then
write(*,*)
write(*,'("Error(getpmat): differing vectors for k-point ",I8)') ik
!write(*,'(" current : ",3G18.10)') vkl(:,ik)
write(*,'(" current : ",3G18.10)') vkl(:)
write(*,'(" PMAT.OUT : ",3G18.10)') vkl_
write(*,*)
stop
end if
if (nstsv.ne.nstsv_) then
write(*,*)
write(*,'("Error(getpmat): differing nstsv for k-point ",I8)') ik
write(*,'(" current : ",I8)') nstsv
write(*,'(" PMAT.OUT : ",I8)') nstsv_
write(*,*)
stop
end if
return
end subroutine

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@ -527,7 +527,7 @@ class readElkfiles:
def readlat(self):
"""
Read in the symmetries in lattice coordinates
Read in information about the lattice.
"""
dft_file='LATTICE.OUT'
R = self.read_elk_file2( dft_file, self.fortran_to_replace)
@ -552,9 +552,11 @@ class readElkfiles:
x = next(R)
for j in range(3):
amatinv[i,j] = atof(x[j])
#reciprocal lattice matrices
#read in cell volume (for transport)
x = next(R)
cell_vol = atof(x[-1])
#cycling through information which is not needed
for i in range(5):
for i in range(4):
x = next(R)
#reading in the reciprocal lattice vectors as matrix
for i in range(3):
@ -572,7 +574,7 @@ class readElkfiles:
except StopIteration: # a more explicit error if the file is corrupted.
raise IOError("Elk_converter : reading PROJ.OUT file failed!")
R.close()
return amat,amatinv,bmat,bmatinv
return amat,amatinv,bmat,bmatinv,cell_vol
def read_geometry(self):
"""

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@ -261,6 +261,10 @@ class HkConverter(ConverterTools):
R.close()
#new variable: dft_code - this determines which DFT code the inputs come from.
#used for certain routines within dft_tools if treating the inputs differently is required.
dft_code = 'hk'
# Save to the HDF5:
with HDFArchive(self.hdf_file, 'a') as ar:
if not (self.dft_subgrp in ar):
@ -268,6 +272,6 @@ class HkConverter(ConverterTools):
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']
'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr', 'dft_code']
for it in things_to_save:
ar[self.dft_subgrp][it] = locals()[it]

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@ -386,6 +386,10 @@ class VaspConverter(ConverterTools):
proj_or_hk = self.proj_or_hk
#new variable: dft_code - this determines which DFT code the inputs come from.
#used for certain routines within dft_tools if treating the inputs differently is required.
dft_code = 'vasp'
# Save it to the HDF:
with HDFArchive(self.hdf_file,'a') as ar:
if not (self.dft_subgrp in ar): ar.create_group(self.dft_subgrp)
@ -394,7 +398,7 @@ class VaspConverter(ConverterTools):
'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','proj_or_hk',
'kpts','kpt_weights', 'kpt_basis']
'kpts','kpt_weights', 'kpt_basis', 'dft_code']
if self.proj_or_hk == 'hk' or self.proj_or_hk == True:
things_to_save.append('proj_mat_csc')
for it in things_to_save: ar[self.dft_subgrp][it] = locals()[it]

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@ -300,6 +300,10 @@ class Wannier90Converter(ConverterTools):
# n_orbitals required by triqs h5 standard, which actually contains the number of bands
n_orbitals = np.full((n_k, n_spin_blocks), n_bands)
#new variable: dft_code - this determines which DFT code the inputs come from.
#used for certain routines within dft_tools if treating the inputs differently is required.
dft_code = 'w90'
# Finally, save all required data into the HDF archive:
if mpi.is_master_node():
with HDFArchive(self.hdf_file, 'a') as archive:
@ -310,7 +314,7 @@ class Wannier90Converter(ConverterTools):
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', 'kpt_weights', 'kpts']
'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr', 'kpt_weights', 'kpts', 'dft_code']
if self.bloch_basis:
np.append(things_to_save, 'kpt_basis')
for it in things_to_save:

View File

@ -259,6 +259,10 @@ class Wien2kConverter(ConverterTools):
R.close()
# Reading done!
#new variable: dft_code - this determines which DFT code the inputs come from.
#used for certain routines within dft_tools if treating the inputs differently is required.
dft_code = 'wien2k'
# Save it to the HDF:
with HDFArchive(self.hdf_file, 'a') as ar:
if not (self.dft_subgrp in ar):
@ -268,7 +272,7 @@ class Wien2kConverter(ConverterTools):
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']
'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr', 'dft_code']
for it in things_to_save:
ar[self.dft_subgrp][it] = locals()[it]

View File

@ -126,7 +126,7 @@ class SumkDFT(object):
req_things_to_read = ['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']
'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr', 'dft_code']
self.subgroup_present, self.values_not_read = self.read_input_from_hdf(
subgrp=self.dft_data, things_to_read=req_things_to_read)
# test if all required properties have been found
@ -1986,7 +1986,7 @@ class SumkDFT(object):
return self.chemical_potential
def calc_density_correction(self, filename=None, dm_type='wien2k', spinave=False, kpts_to_write=None):
def calc_density_correction(self, filename=None, dm_type=None, spinave=False, kpts_to_write=None):
r"""
Calculates the charge density correction and stores it into a file.
@ -2004,7 +2004,10 @@ class SumkDFT(object):
Name of the file to store the charge density correction.
dm_type : string
DFT code to write the density correction for. Options:
'vasp', 'wien2k', 'elk'
'vasp', 'wien2k', 'elk' or 'qe'. Needs to be set for 'qe'
spinave : logical
Elk specific and for magnetic calculations in DMFT only.
It averages the spin to keep the DFT part non-magnetic.
kpts_to_write : iterable of int
Indices of k points that are written to file. If None (default),
all k points are written. Only implemented for dm_type 'vasp'
@ -2016,6 +2019,10 @@ class SumkDFT(object):
the corresponing total charge `dens`.
"""
#automatically set dm_type if required
if dm_type==None:
dm_type = self.dft_code
assert dm_type in ('vasp', 'wien2k','elk', 'qe'), "'dm_type' must be either 'vasp', 'wienk', 'elk' or 'qe'"
#default file names
if filename is None:

View File

@ -962,6 +962,7 @@ class SumkDFTTools(SumkDFT):
dens_mat : list of numpy array
A list of density matrices projected to all shells provided in the input.
"""
assert self.dft_code in ('wien2k'), "This routine has only been implemented for wien2k inputs"
things_to_read = ['dens_mat_below', 'n_parproj',
'proj_mat_all', 'rot_mat_all', 'rot_mat_all_time_inv']
@ -1063,13 +1064,20 @@ class SumkDFTTools(SumkDFT):
r"""
Reads the data for transport calculations from the hdf5 archive.
"""
assert self.dft_code in ('wien2k','elk'), "Transport has only been implemented for wien2k and elk inputs"
thingstoread = ['band_window_optics', 'velocities_k']
self.read_input_from_hdf(
subgrp=self.transp_data, things_to_read=thingstoread)
thingstoread = ['band_window', 'lattice_angles', 'lattice_constants',
'lattice_type', 'n_symmetries', 'rot_symmetries']
if(self.dft_code=="wien2k"):
thingstoread = ['band_window', 'lattice_angles', 'lattice_constants',
'lattice_type', 'n_symmetries', 'rot_symmetries']
elif(self.dft_code=="elk"):
thingstoread = ['band_window', 'n_symmetries',
'rot_symmetries','cell_vol']
self.read_input_from_hdf(
subgrp=self.misc_data, things_to_read=thingstoread)
if(self.dft_code=="wien2k"):
self.cell_vol = self.cellvolume(self.lattice_type, self.lattice_constants, self.lattice_angles)[1]
def cellvolume(self, lattice_type, lattice_constants, latticeangle):
r"""
@ -1222,8 +1230,8 @@ class SumkDFTTools(SumkDFT):
assert broadening != 0.0 and broadening is not None, "transport_distribution: Broadening necessary to calculate transport distribution!"
self.omega = numpy.linspace(
energy_window[0] - max(Om_mesh), energy_window[1] + max(Om_mesh), n_om)
mesh = [energy_window[0] -
max(Om_mesh), energy_window[1] + max(Om_mesh), n_om]
mesh = MeshReFreq(energy_window[0] -
max(Om_mesh), energy_window[1] + max(Om_mesh), n_om)
mu = 0.0
# Define mesh for optic conductivity
@ -1291,8 +1299,8 @@ class SumkDFTTools(SumkDFT):
A_kw[isp][A_i, A_i, iw]).trace().real * self.bz_weights[ik])
for direction in self.directions:
self.Gamma_w[direction] = (mpi.all_reduce(mpi.world, self.Gamma_w[direction], lambda x, y: x + y)
/ self.cellvolume(self.lattice_type, self.lattice_constants, self.lattice_angles)[1] / self.n_symmetries)
self.Gamma_w[direction] = (mpi.all_reduce(mpi.world, self.Gamma_w[direction], lambda x, y: x + y) / self.cell_vol / self.n_symmetries)
def transport_coefficient(self, direction, iq, n, beta, method=None):
r"""

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View File

@ -4,6 +4,7 @@ set(all_tests
elk_equiv_convert
elk_bands_convert
elk_bandcharacter_convert
elk_transport_convert
)
file(GLOB all_test_files RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} *.py)

View File

@ -0,0 +1,24 @@
import os
from h5 import *
from triqs.utility.comparison_tests import *
from triqs.utility.h5diff import h5diff
import triqs.utility.mpi as mpi
from triqs_dft_tools.converters import ElkConverter
#get current working directory path
cwd = format(os.getcwd())
#location of test directory
testdir = cwd+'/elk_transport_convert'
#change to test directory
os.chdir(testdir)
Converter = ElkConverter(filename='SrVO3', repacking=True)
Converter.hdf_file = 'elk_transport_convert.out.h5'
Converter.convert_dft_input()
Converter.convert_transport_input()
if mpi.is_master_node():
h5diff('elk_transport_convert.out.h5','elk_transport_convert.ref.h5')
#return to cwd
os.chdir(cwd)

View File

@ -0,0 +1 @@
0.3195858311

View File

@ -0,0 +1,452 @@
10 : nkpt
41 : nstsv
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(state, eigenvalue and occupancy below)
1 -2.080512267 2.000000000
2 -1.131321703 2.000000000
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17 0.1963657132 2.000000000
18 0.2274578760 1.999999992
19 0.2274578760 1.999999992
20 0.2274578760 1.999999992
21 0.2789989931 1.999610736
22 0.2789989931 1.999610736
23 0.2789989931 1.999610736
24 0.3630465670 0.2125849074E-03
25 0.3630465670 0.2125849074E-03
26 0.4679515512 0.5451436638E-13
27 0.4679515512 0.5451436638E-13
28 0.4816851639 0.3026205990E-14
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2 0.2500000000 0.000000000 0.000000000 : k-point, vkl
(state, eigenvalue and occupancy below)
1 -2.080514726 2.000000000
2 -1.131961789 2.000000000
3 -1.131259898 2.000000000
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19 0.2167716847 1.999999999
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21 0.2813385282 1.999363080
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24 0.3633365372 0.1999973668E-03
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28 0.5351273961 0.3934381465E-19
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40 1.073147780 0.000000000
41 1.117669614 0.000000000
3 0.5000000000 0.000000000 0.000000000 : k-point, vkl
(state, eigenvalue and occupancy below)
1 -2.080513814 2.000000000
2 -1.132561075 2.000000000
3 -1.131197618 2.000000000
4 -1.131197618 2.000000000
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21 0.2837216985 1.998948331
22 0.3521551601 0.2103206695E-02
23 0.3521551601 0.2103206695E-02
24 0.3636863396 0.1858002276E-03
25 0.4484244397 0.3325073415E-11
26 0.5555227437 0.5372873872E-21
27 0.5580564637 0.000000000
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4 0.2500000000 0.2500000000 0.000000000 : k-point, vkl
(state, eigenvalue and occupancy below)
1 -2.080511824 2.000000000
2 -1.131887251 2.000000000
3 -1.131837766 2.000000000
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25 0.4476081414 0.3948501584E-11
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(state, eigenvalue and occupancy below)
1 -2.080516644 2.000000000
2 -1.132505567 2.000000000
3 -1.131831469 2.000000000
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21 0.3223628472 0.7157458658
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23 0.3543219376 0.1333364737E-02
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(state, eigenvalue and occupancy below)
1 -2.080520955 2.000000000
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3 -1.132455893 2.000000000
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20 0.2182249352 1.999999999
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8 0.5000000000 0.2500000000 0.2500000000 : k-point, vkl
(state, eigenvalue and occupancy below)
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9 0.5000000000 0.5000000000 0.2500000000 : k-point, vkl
(state, eigenvalue and occupancy below)
1 -2.080522680 2.000000000
2 -1.132393654 2.000000000
3 -1.132393654 2.000000000
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18 0.2164950169 1.999999999
19 0.2164950169 1.999999999
20 0.2410648719 1.999999868
21 0.3604113155 0.3701939464E-03
22 0.3604113155 0.3701939464E-03
23 0.3684696462 0.6788161140E-04
24 0.4636321561 0.1353371421E-12
25 0.5182938651 0.1361140024E-17
26 0.5766230558 0.000000000
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35 0.8661545522 0.000000000
36 0.8942150917 0.000000000
37 0.8942150917 0.000000000
38 0.9782302280 0.000000000
39 1.024092075 0.000000000
40 1.057377171 0.000000000
41 1.057377171 0.000000000
10 0.5000000000 0.5000000000 0.5000000000 : k-point, vkl
(state, eigenvalue and occupancy below)
1 -2.080527855 2.000000000
2 -1.132357683 2.000000000
3 -1.132357683 2.000000000
4 -1.132357683 2.000000000
5 -0.9410634384 2.000000000
6 -0.3473114993 2.000000000
7 -0.3473114993 2.000000000
8 -0.3473114993 2.000000000
9 -0.2965931205 2.000000000
10 -0.2965931205 2.000000000
11 -0.2965931205 2.000000000
12 0.4838027108E-01 2.000000000
13 0.7515130093E-01 2.000000000
14 0.7515130093E-01 2.000000000
15 0.9826324489E-01 2.000000000
16 0.9826324489E-01 2.000000000
17 0.9826324489E-01 2.000000000
18 0.2427459837 1.999999811
19 0.2427459837 1.999999811
20 0.2427459837 1.999999811
21 0.3727487023 0.2757673925E-04
22 0.3727487023 0.2757673925E-04
23 0.3727487023 0.2757673925E-04
24 0.5184055902 0.1329499565E-17
25 0.5184055902 0.1329499565E-17
26 0.5489625930 0.2137846515E-20
27 0.5489625930 0.2137846515E-20
28 0.5489625930 0.2137846515E-20
29 0.6285993875 0.000000000
30 0.7678355226 0.000000000
31 0.7678355226 0.000000000
32 0.7814941986 0.000000000
33 0.7814941986 0.000000000
34 0.7814941986 0.000000000
35 0.8648326754 0.000000000
36 0.9932575682 0.000000000
37 0.9932575682 0.000000000
38 0.9932575682 0.000000000
39 1.011442529 0.000000000
40 1.011442529 0.000000000
41 1.011442529 0.000000000

View File

@ -0,0 +1,31 @@
scale
1.0
scale1
1.0
scale2
1.0
scale3
1.0
avec
7.260500000 0.000000000 0.000000000
0.000000000 7.260500000 0.000000000
0.000000000 0.000000000 7.260500000
atoms
3 : nspecies
'Sr.in' : spfname
1 : natoms; atpos, bfcmt below
0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
'V.in' : spfname
1 : natoms; atpos, bfcmt below
0.50000000 0.50000000 0.50000000 0.00000000 0.00000000 0.00000000
'O.in' : spfname
3 : natoms; atpos, bfcmt below
0.00000000 0.50000000 0.50000000 0.00000000 0.00000000 0.00000000
0.50000000 0.00000000 0.50000000 0.00000000 0.00000000 0.00000000
0.50000000 0.50000000 0.00000000 0.00000000 0.00000000 0.00000000

View File

@ -0,0 +1,11 @@
10 : nkpt; k-point, vkl, wkpt, nmat below
1 0.000000000 0.000000000 0.000000000 0.1562500000E-01 401
2 0.2500000000 0.000000000 0.000000000 0.9375000000E-01 397
3 0.5000000000 0.000000000 0.000000000 0.4687500000E-01 372
4 0.2500000000 0.2500000000 0.000000000 0.1875000000 374
5 0.5000000000 0.2500000000 0.000000000 0.1875000000 386
6 0.5000000000 0.5000000000 0.000000000 0.4687500000E-01 392
7 0.2500000000 0.2500000000 0.2500000000 0.1250000000 386
8 0.5000000000 0.2500000000 0.2500000000 0.1875000000 386
9 0.5000000000 0.5000000000 0.2500000000 0.9375000000E-01 388
10 0.5000000000 0.5000000000 0.5000000000 0.1562500000E-01 396

View File

@ -0,0 +1,41 @@
+----------------------------+
| Real-space lattice vectors |
+----------------------------+
vector a1 : 7.260500000 0.000000000 0.000000000
vector a2 : 0.000000000 7.260500000 0.000000000
vector a3 : 0.000000000 0.000000000 7.260500000
Stored column-wise as a matrix :
7.260500000 0.000000000 0.000000000
0.000000000 7.260500000 0.000000000
0.000000000 0.000000000 7.260500000
Inverse of matrix :
0.1377315612 0.000000000 0.000000000
0.000000000 0.1377315612 0.000000000
0.000000000 0.000000000 0.1377315612
Unit cell volume : 382.7362428
+----------------------------------+
| Reciprocal-space lattice vectors |
+----------------------------------+
vector b1 : 0.8653929216 0.000000000 0.000000000
vector b2 : 0.000000000 0.8653929216 0.000000000
vector b3 : 0.000000000 0.000000000 0.8653929216
Stored column-wise as a matrix :
0.8653929216 0.000000000 0.000000000
0.000000000 0.8653929216 0.000000000
0.000000000 0.000000000 0.8653929216
Inverse of matrix :
1.155544464 0.000000000 0.000000000
0.000000000 1.155544464 0.000000000
0.000000000 0.000000000 1.155544464
Brillouin zone volume : 0.6480970070

Binary file not shown.

View File

@ -0,0 +1,8 @@
1 10 1 0 5 : nproj, nkpt, nspinor, spinorb, natmtot
1 : Proj index
2 1 2 3 : Species index, natoms, l, lm submatrix size
1 : Subset no. of equivalent atoms
1 2 : atom, spatom
3 4 5 : lm indices
1 : Cubic Harmonics

View File

@ -0,0 +1,580 @@
(translation vectors and rotation matrices are in lattice coordinates)
48 : nsymcrys
Crystal symmetry : 1
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
1 0 0
0 1 0
0 0 1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 2
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
-1 0 0
0 -1 0
0 0 -1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 3
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
-1 0 0
0 0 -1
0 -1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 4
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
-1 0 0
0 0 -1
0 1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 5
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
-1 0 0
0 0 1
0 -1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 6
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
-1 0 0
0 0 1
0 1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 7
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
-1 0 0
0 1 0
0 0 -1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 8
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
-1 0 0
0 1 0
0 0 1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 9
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 -1 0
-1 0 0
0 0 -1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 10
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 -1 0
-1 0 0
0 0 1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 11
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 -1 0
0 0 -1
-1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 12
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 -1 0
0 0 -1
1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 13
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 -1 0
0 0 1
-1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 14
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 -1 0
0 0 1
1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 15
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 -1 0
1 0 0
0 0 -1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 16
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 -1 0
1 0 0
0 0 1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 17
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 -1
-1 0 0
0 -1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 18
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 -1
-1 0 0
0 1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 19
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 -1
0 -1 0
-1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 20
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 -1
0 -1 0
1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 21
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 -1
0 1 0
-1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 22
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 -1
0 1 0
1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 23
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 -1
1 0 0
0 -1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 24
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 -1
1 0 0
0 1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 25
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 1
-1 0 0
0 -1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 26
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 1
-1 0 0
0 1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 27
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 1
0 -1 0
-1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 28
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 1
0 -1 0
1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 29
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 1
0 1 0
-1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 30
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 1
0 1 0
1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 31
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 1
1 0 0
0 -1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 32
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 0 1
1 0 0
0 1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 33
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 1 0
-1 0 0
0 0 -1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 34
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 1 0
-1 0 0
0 0 1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 35
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 1 0
0 0 -1
-1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 36
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 1 0
0 0 -1
1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 37
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 1 0
0 0 1
-1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 38
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 1 0
0 0 1
1 0 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 39
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 1 0
1 0 0
0 0 -1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 40
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
0 1 0
1 0 0
0 0 1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 41
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
1 0 0
0 -1 0
0 0 -1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 42
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
1 0 0
0 -1 0
0 0 1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 43
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
1 0 0
0 0 -1
0 -1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 44
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
1 0 0
0 0 -1
0 1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 45
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
1 0 0
0 0 1
0 -1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 46
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
1 0 0
0 0 1
0 1 0
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 47
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
1 0 0
0 1 0
0 0 -1
global spin rotation :
1 0 0
0 1 0
0 0 1
Crystal symmetry : 48
spatial translation :
0.000000000 0.000000000 0.000000000
spatial rotation :
-1 0 0
0 -1 0
0 0 1
global spin rotation :
1 0 0
0 1 0
0 0 1

View File

@ -0,0 +1,141 @@
10 5 3 : number of k-points, lmmax, reduced lmmax
1 0.000000000 0.000000000 0.000000000 : k-point index, k-point (lattice coordinates)
1 12 28 : spinor index, minimum and maximum band indices
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2 0.2500000000 0.000000000 0.000000000 : k-point index, k-point (lattice coordinates)
1 12 28 : spinor index, minimum and maximum band indices
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View File

@ -0,0 +1,42 @@
tasks
0
120
805
ngridk
4 4 4
! Path for species files
sppath
'/home/elk-6.2.8/species/'
! Maximum length for G+k vectors
rgkmax
7.0
avec
7.260500000 0.000000000 0.000000000
0.000000000 7.260500000 0.000000000
0.000000000 0.000000000 7.260500000
atoms
3 : nspecies
'Sr.in' : spfname
1 : natoms; atposl, bfcmt below
0.50000000 0.50000000 0.50000000 0.00000000 0.00000000 0.00000000
'V.in' : spfname
1 : natoms; atposl, bfcmt below
0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
'O.in' : spfname
3 : natoms; atposl, bfcmt below
0.50000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
0.00000000 0.50000000 0.00000000 0.00000000 0.00000000 0.00000000
0.00000000 0.00000000 0.50000000 0.00000000 0.00000000 0.00000000
!Wannier projectors
wanproj !projector flag
1 !number of projectors - next 3 lines are repeated for each projector
2 2 3 !species, l, reduced max lm (rlmmax) value
7 8 9 !the lm quanties which will be projected (vector length eq. rlmmax)
-0.294 0.27562 ![-8.0, 7.5] eV energy window

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