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dft_tools/python/triqs_dft_tools/sumk_dft_tools.py
2023-04-14 23:43:23 +01:00

989 lines
48 KiB
Python

##########################################################################
#
# TRIQS: a Toolbox for Research in Interacting Quantum Systems
#
# Copyright (C) 2011 by M. Aichhorn, L. Pourovskii, V. Vildosola
#
# 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/>.
#
##########################################################################
"""
Extension to the SumkDFT class with some analyiss tools
"""
import sys
from types import *
import numpy
from triqs.gf import *
import triqs.utility.mpi as mpi
from .symmetry import *
from .sumk_dft import SumkDFT
from scipy.integrate import *
from scipy.interpolate import *
if not hasattr(numpy, 'full'):
# polyfill full for older numpy:
numpy.full = lambda a, f: numpy.zeros(a) + f
class SumkDFTTools(SumkDFT):
"""
Extends the SumkDFT class with some tools for analysing the data.
"""
def __init__(self, hdf_file, h_field=0.0, mesh=None, beta=40, n_iw=1025, use_dft_blocks=False, dft_data='dft_input', symmcorr_data='dft_symmcorr_input',
parproj_data='dft_parproj_input', symmpar_data='dft_symmpar_input', bands_data='dft_bands_input',
transp_data='dft_transp_input', misc_data='dft_misc_input', cont_data='dft_contours_input'):
"""
Initialisation of the class. Parameters are exactly as for SumKDFT.
"""
SumkDFT.__init__(self, hdf_file=hdf_file, h_field=h_field, mesh=mesh, beta=beta, n_iw=n_iw,
use_dft_blocks=use_dft_blocks, dft_data=dft_data, symmcorr_data=symmcorr_data,
parproj_data=parproj_data, symmpar_data=symmpar_data, bands_data=bands_data,
transp_data=transp_data, misc_data=misc_data, cont_data=cont_data)
# Uses .data of only GfReFreq objects.
# Uses .data of only GfReFreq objects.
def density_of_states(self, mu=None, broadening=None, mesh=None, with_Sigma=True, with_dc=True, proj_type=None, dosocc=False, save_to_file=True):
"""
Calculates the density of states. The basis of the projected density of states is
specified by proj_type.
Parameters
----------
mu : double, optional
Chemical potential, overrides the one stored in the hdf5 archive.
broadening : double, optional
Lorentzian broadening of the spectra.
If not given, standard value of lattice_gf is used.
mesh : real frequency MeshType, optional
Omega mesh for the real-frequency Green's function.
Given as parameter to lattice_gf.
with_Sigma : boolean, optional
If True, the self energy is used for the calculation.
If false, the DOS is calculated without self energy.
with_dc : boolean, optional
If True the double counting correction is used.
proj_type : string, optional
Output the orbital-projected DOS type from the following options:
'wann' - Wannier DOS calculated from the Wannier projectors
'vasp' - Vasp orbital-projected DOS only from Vasp inputs
'wien2k' - Wien2k orbital-projected DOS from the wien2k theta projectors
'elk' - Elk orbital-projected DOS only from Elk inputs
dosocc : boolean, optional
If True, the occupied DOS, DOSproj and DOSproj_orb will be returned.
The prerequisite of this option is to have calculated the band-resolved
density matrices generated by occupations().
save_to_file : boolean, optional
If True, text files with the calculated data will be created.
Returns
-------
DOS : Dict of numpy arrays
Contains the full density of states.
DOSproj : Dict of numpy arrays
DOS projected to atoms. Empty if proj_type = None
DOSproj_orb : Dict of numpy arrays
DOS projected to atoms and resolved into orbital contributions.
Empty if proj_type = None
"""
if(proj_type!=None):
#assert proj_type in ('wann', 'vasp','wien2k','elk'), "'proj_type' must be either 'wann', 'vasp', 'wien2k', or 'elk'"
assert proj_type in ('wann', 'vasp','wien2k',), "'proj_type' must be either 'wann', 'vasp', 'wien2k'"
if(proj_type!='wann'):
assert proj_type==self.dft_code, "proj_type must be from the corresponding dft inputs."
if (with_Sigma):
assert isinstance(self.Sigma_imp[0].mesh, MeshReFreq), "SumkDFT.mesh must be real if with_Sigma is True"
mesh=self.Sigma_imp[0].mesh
elif mesh is not None:
assert isinstance(mesh, MeshReFreq), "mesh must be of form MeshReFreq"
if broadening is None:
broadening=0.001
elif self.mesh is not None:
assert isinstance(self.mesh, MeshReFreq), "self.mesh must be of form MeshReFreq"
mesh=self.mesh
if broadening is None:
broadening=0.001
else:
assert 0, "ReFreqMesh input required for calculations without real frequency self-energy"
mesh_val = numpy.linspace(mesh.omega_min,mesh.omega_max,len(mesh))
n_om = len(mesh)
om_minplot = mesh_val[0] - 0.001
om_maxplot = mesh_val[-1] + 0.001
#Read in occupations from HDF5 file if required
if(dosocc):
mpi.report('Reading occupations generated by self.occupations().')
thingstoread = ['occik']
subgroup_present, values_not_read = self.read_input_from_hdf(
subgrp=self.misc_data, things_to_read=thingstoread)
if len(values_not_read) > 0 and mpi.is_master_node:
raise ValueError(
'ERROR: One or more necessary SumK input properties have not been found in the given h5 archive:', self.values_not_read)
#initialise projected DOS type if required
spn = self.spin_block_names[self.SO]
n_shells=1
if (proj_type == 'wann'):
n_shells = self.n_corr_shells
gf_struct = self.gf_struct_sumk.copy()
dims = [self.corr_shells[ish]['dim'] for ish in range(n_shells)]
shells_type = 'corr'
elif (proj_type == 'vasp'):
n_shells=1
gf_struct = [[(sp, list(range(self.proj_mat_csc.shape[2]))) for sp in spn]]
dims = [self.proj_mat_csc.shape[2]]
shells_type = 'csc'
elif (proj_type == 'wien2k'):
self.load_parproj()
n_shells = self.n_shells
gf_struct = [[(sp, self.shells[ish]['dim']) for sp in spn]
for ish in range(n_shells)]
dims = [self.shells[ish]['dim'] for ish in range(n_shells)]
shells_type = 'all'
# #commented out for now - unsure this produces DFT+DMFT PDOS
# elif (proj_type == 'elk'):
# n_shells = self.n_shells
# dims = [self.shells[ish]['dim'] for ish in range(n_shells)]
# gf_struct = [[(sp, self.shells[ish]['dim']) for sp in spn]
# for ish in range(n_shells)]
# things_to_read = ['band_dens_muffin']
# subgroup_present, values_not_read = self.read_input_from_hdf(
# subgrp=self.bc_data, things_to_read=things_to_read)
# if len(values_not_read) > 0 and mpi.is_master_node:
# raise ValueError(
# 'ERROR: One or more necessary SumK input properties have not been found in the given h5 archive:', self.values_not_read)
#set-up output arrays
DOS = {sp: numpy.zeros([n_om],float) for sp in spn}
DOSproj = [{} for ish in range(n_shells)]
DOSproj_orb = [{} for ish in range(n_shells)]
#set-up Green's function object
if (proj_type != None):
G_loc = []
for ish in range(n_shells):
glist = [GfReFreq(target_shape=(block_dim, block_dim), mesh=mesh)
for block, block_dim in gf_struct[ish]]
G_loc.append(
BlockGf(name_list=spn, block_list=glist, make_copies=False))
G_loc[ish].zero()
dim = dims[ish]
for sp in spn:
DOSproj[ish][sp] = numpy.zeros([n_om], float)
DOSproj_orb[ish][sp] = numpy.zeros(
[n_om, dim, dim], complex)
#calculate the DOS
ikarray = numpy.array(list(range(self.n_k)))
for ik in mpi.slice_array(ikarray):
G_latt_w = self.lattice_gf(
ik=ik, mu=mu, broadening=broadening, mesh=mesh, with_Sigma=with_Sigma, with_dc=with_dc)
G_latt_w *= self.bz_weights[ik]
#output occupied DOS if nk inputted
if(dosocc):
for bname, gf in G_latt_w:
G_latt_w[bname].data[:,:,:] *= self.occik[bname][ik]
# DOS
for bname, gf in G_latt_w:
DOS[bname] -= gf.data.imag.trace(axis1=1, axis2=2)/numpy.pi
# Projected DOS:
if (proj_type != None):
for ish in range(n_shells):
tmp = G_loc[ish].copy()
tmp.zero()
tmp << self.proj_type_G_loc(G_latt_w, tmp, ik, ish, proj_type)
G_loc[ish] += tmp
mpi.barrier()
# Collect data from mpi:
for bname in DOS:
DOS[bname] = mpi.all_reduce(
mpi.world, DOS[bname], lambda x, y: x + y)
# Collect data from mpi and put in projected arrays
if(proj_type != None):
for ish in range(n_shells):
G_loc[ish] << mpi.all_reduce(
mpi.world, G_loc[ish], lambda x, y: x + y)
# Symmetrize and rotate to local coord. system if needed:
if((proj_type!='vasp') and (proj_type!='elk')):
if self.symm_op != 0:
if proj_type=='wann':
G_loc = self.symmcorr.symmetrize(G_loc)
else:
G_loc = self.symmpar.symmetrize(G_loc)
if self.use_rotations:
for ish in range(n_shells):
for bname, gf in G_loc[ish]:
G_loc[ish][bname] << self.rotloc(
ish, gf, direction='toLocal',shells=shells_type)
# G_loc can now also be used to look at orbitally-resolved quantities
for ish in range(n_shells):
for bname, gf in G_loc[ish]: # loop over spins
DOSproj[ish][bname] = -gf.data.imag.trace(axis1=1, axis2=2) / numpy.pi
DOSproj_orb[ish][bname][
:, :, :] += (1.0j*(gf-gf.conjugate().transpose())/2.0/numpy.pi).data[:,:,:]
# Write to files
if save_to_file and mpi.is_master_node():
for sp in spn:
f = open('DOS_%s.dat' % sp, 'w')
for iom in range(n_om):
f.write("%s %s\n" % (mesh_val[iom], DOS[sp][iom]))
f.close()
# Partial
if(proj_type!=None):
for ish in range(n_shells):
f = open('DOS_' + proj_type + '_%s_proj%s.dat' % (sp, ish), 'w')
for iom in range(n_om):
f.write("%s %s\n" %
(mesh_val[iom], DOSproj[ish][sp][iom]))
f.close()
# Orbitally-resolved
for i in range(dims[ish]):
for j in range(dims[ish]):
#For Elk with parproj - skip off-diagonal elements
#if(proj_type=='elk') and (i!=j): continue
f = open('DOS_' + proj_type + '_' + sp + '_proj' + str(ish) +
'_' + str(i) + '_' + str(j) + '.dat', 'w')
for iom in range(n_om):
f.write("%s %s %s\n" % (
mesh_val[iom], DOSproj_orb[ish][sp][iom, i, j].real,DOSproj_orb[ish][sp][iom, i, j].imag))
f.close()
return DOS, DOSproj, DOSproj_orb
def proj_type_G_loc(self, G_latt, G_inp, ik, ish, proj_type=None):
"""
Internal routine which calculates the project Green's function subject to the
proj_type input.
Parameters
----------
G_latt : Gf
block of lattice Green's functions to be projected/downfolded
G_inp : Gf
block of local Green's functions used as a template for G_proj
ik : integer
integer specifing k-point index.
ish : integer
integer specifing shell index.
proj_type : string, optional
Output the orbital-projected DOS type from the following options:
'wann' - Wannier DOS calculated from the Wannier projectors
'vasp' - Vasp orbital-projected DOS only from Vasp inputs
'wien2k' - Wien2k orbital-projected DOS from the wien2k theta projectors
'elk' - Elk orbital-projected DOS only from Elk inputs
Returns
-------
G_proj : Gf
projected/downfolded lattice Green's function
Contains the band-resolved density matrices per k-point.
"""
G_proj = G_inp.copy()
if (proj_type == 'wann'):
for bname, gf in G_proj:
G_proj[bname] << self.downfold(ik, ish, bname,
G_latt[bname], gf) # downfolding G
elif (proj_type == 'vasp'):
for bname, gf in G_latt:
G_proj[bname] << self.downfold(ik, ish, bname, gf, G_proj[bname], shells='csc')
elif (proj_type == 'wien2k'):
tmp = G_proj.copy()
for ir in range(self.n_parproj[ish]):
tmp.zero()
for bname, gf in tmp:
tmp[bname] << self.downfold(ik, ish, bname,
G_latt[bname], gf, shells='all', ir=ir)
G_proj += tmp
# elif (proj_type == 'elk'):
# dim = self.shells[ish]['dim']
# ntoi = self.spin_names_to_ind[self.SO]
# for bname, gf in G_latt:
# n_om = len(gf.data[:,0,0])
# isp=ntoi[bname]
# nst=self.n_orbitals[ik,isp]
# #matrix multiply band resolved muffin density with
# #diagonal of band resolved spectral function and fill diagonal of
# #DOSproj_orb orbital dimensions with the result for each frequency
# bdm=self.band_dens_muffin[ik,isp,ish,0:dim,0:nst]
# tmp=[numpy.matmul(bdm, gf.data[iom,:,:].diagonal())
# for iom in range(n_om)]
# tmp=numpy.asarray(tmp)
# tmp2 = numpy.zeros([n_om,dim,dim], dtype=complex)
# if(dim==1):
# tmp2[:,0,0]=tmp[:,0]
# else:
# [numpy.fill_diagonal(tmp2[iom,:,:],tmp[iom,:])
# for iom in range(n_om)]
# G_proj[bname].data[:,:,:] = tmp2[:,:,:]
return G_proj
def load_parproj(self,data_type=None):
"""
Internal routine which loads the n_parproj, proj_mat_all, rot_mat_all and
rot_mat_all_time_inv from parproj data from .h5 file.
Parameters
----------
data_type : string, optional
which data type desired to be read in.
'band' - reads data converted by bands_convert()
None - reads data converted by parproj_convert()
"""
#read in the projectors
things_to_read = ['n_parproj', 'proj_mat_all']
if data_type == 'band':
subgroup_present, values_not_read = self.read_input_from_hdf(
subgrp=self.bands_data, things_to_read=things_to_read)
else:
subgroup_present, values_not_read = self.read_input_from_hdf(
subgrp=self.parproj_data, things_to_read=things_to_read)
if self.symm_op:
self.symmpar = Symmetry(self.hdf_file, subgroup=self.symmpar_data)
if len(values_not_read) > 0 and mpi.is_master_node:
raise ValueError(
'ERROR: One or more necessary SumK input properties have not been found in the given h5 archive:', self.values_not_read)
#read general data
things_to_read = ['rot_mat_all', 'rot_mat_all_time_inv']
subgroup_present, values_not_read = self.read_input_from_hdf(
subgrp=self.parproj_data, things_to_read=things_to_read)
if len(values_not_read) > 0 and mpi.is_master_node:
raise ValueError(
'ERROR: One or more necessary SumK input properties have not been found in the given h5 archive:', self.values_not_read)
def occupations(self, mu=None, with_Sigma=True, with_dc=True, save_occ=True):
"""
Calculates the band resolved density matrices (occupations) from the Matsubara
frequency self-energy.
Parameters
----------
mu : double, optional
Chemical potential, overrides the one stored in the hdf5 archive.
with_Sigma : boolean, optional
If True, the self energy is used for the calculation.
If false, the DOS is calculated without self energy.
with_dc : boolean, optional
If True the double counting correction is used.
save_occ : boolean, optional
If True, saves the band resolved density matrix in misc_data.
save_to_file : boolean, optional
If True, text files with the calculated data will be created.
Returns
-------
occik : Dict of numpy arrays
Contains the band-resolved density matrices per k-point.
"""
if with_Sigma:
mesh = self.Sigma_imp[0].mesh
else:
mesh = self.mesh
assert isinstance(mesh, MeshImFreq), "SumkDFT.mesh must be real if with_Sigma is True or mesh is not given"
if mu is None:
mu = self.chemical_potential
ntoi = self.spin_names_to_ind[self.SO]
spn = self.spin_block_names[self.SO]
occik = {}
for sp in spn:
#same format as gf.data ndarray
occik[sp] = [numpy.zeros([1, self.n_orbitals[ik, ntoi[sp]], self.n_orbitals[ik, ntoi[sp]]], numpy.double) for ik in range(self.n_k)]
#calculate the occupations
ikarray = numpy.array(range(self.n_k))
for ik in range(self.n_k):
G_latt = self.lattice_gf(
ik=ik, mu=mu, with_Sigma=with_Sigma, with_dc=with_dc)
for bname, gf in G_latt:
occik[bname][ik][0,:,:] = gf.density().real
# Collect data from mpi:
for sp in spn:
occik[sp] = mpi.all_reduce(mpi.world, occik[sp], lambda x, y: x + y)
mpi.barrier()
#save to HDF5 file (if specified)
if save_occ and mpi.is_master_node():
things_to_save_misc = ['occik']
# Save it to the HDF:
ar = HDFArchive(self.hdf_file, 'a')
if not (self.misc_data in ar):
ar.create_group(self.misc_data)
for it in things_to_save_misc:
ar[self.misc_data][it] = locals()[it]
del ar
return occik
# Uses .data of only GfReFreq objects.
def spectral_contours(self, mu=None, broadening=None, mesh=None, plot_range=None, FS=True, with_Sigma=True, with_dc=True, proj_type=None, save_to_file=True):
"""
Calculates the correlated spectral function at the Fermi level (relating to the Fermi
surface) or at specific frequencies.
Parameters
----------
mu : double, optional
Chemical potential, overrides the one stored in the hdf5 archive.
broadening : double, optional
Lorentzian broadening of the spectra.
If not given, standard value of lattice_gf is used.
mesh : real frequency MeshType, optional
Omega mesh for the real-frequency Green's function.
Given as parameter to lattice_gf.
plot_range : list of double, optional
Sets the energy window for plotting to (plot_range[0],plot_range[1]).
If not provided, the min and max values of the energy mesh is used.
FS : boolean
Flag for calculating the spectral function at the Fermi level (omega ~ 0)
If False, the spectral function will be generated for each frequency within
plot_range.
with_Sigma : boolean, optional
If True, the self energy is used for the calculation.
If false, the DOS is calculated without self energy.
with_dc : boolean, optional
If True the double counting correction is used.
proj_type : string, optional
Output the orbital-projected A(k,w) type from the following:
'wann' - Wannier A(k,w) calculated from the Wannier projectors
save_to_file : boolean, optional
If True, text files with the calculated data will be created.
Returns
-------
Akw : Dict of numpy arrays
(Correlated) k-resolved spectral function
pAkw : Dict of numpy arrays
(Correlated) k-resolved spectral function projected to atoms.
Empty if proj_type = None
pAkw_orb : Dict of numpy arrays
(Correlated) k-resolved spectral function projected to atoms and
resolved into orbital contributions. Empty if proj_type = None
"""
if(proj_type!=None):
assert proj_type in ('wann'), "'proj_type' must be 'wann' if not None"
#read in the energy contour energies and projectors
things_to_read = ['n_k','bmat','BZ_n_k','BZ_iknr','BZ_vkl',
'n_orbitals', 'proj_mat', 'hopping']
subgroup_present, values_not_read = self.read_input_from_hdf(
subgrp=self.cont_data, things_to_read=things_to_read)
if len(values_not_read) > 0 and mpi.is_master_node:
raise ValueError(
'ERROR: One or more necessary SumK input properties have not been found in the given h5 archive:', self.values_not_read)
if mu is None:
mu = self.chemical_potential
if (with_Sigma):
assert isinstance(self.Sigma_imp[0].mesh, MeshReFreq), "SumkDFT.mesh must be real if with_Sigma is True"
mesh=self.Sigma_imp[0].mesh
elif mesh is not None:
assert isinstance(mesh, MeshReFreq), "mesh must be of form MeshReFreq"
if broadening is None:
broadening=0.001
elif self.mesh is not None:
assert isinstance(self.mesh, MeshReFreq), "self.mesh must be of form MeshReFreq"
mesh=self.mesh
if broadening is None:
broadening=0.001
else:
assert 0, "ReFreqMesh input required for calculations without real frequency self-energy"
mesh_val = numpy.linspace(mesh.omega_min,mesh.omega_max,len(mesh))
n_om = len(mesh)
om_minplot = mesh_val[0] - 0.001
om_maxplot = mesh_val[-1] + 0.001
#for Fermi Surface calculations
if FS:
dw = abs(mesh_val[1]-mesh_val[0])
#ensure that a few frequencies around the Fermi level are included
plot_range = [-2*dw, 2*dw]
mpi.report('Generated A(k,w) will be evaluted at closest frequency to 0.0 in given mesh ')
if plot_range is None:
n_om = len(mesh_val[(mesh_val > om_minplot)&(mesh_val < om_maxplot)])
mesh_val2 = mesh_val[(mesh_val > om_minplot)&(mesh_val < om_maxplot)]
else:
om_minplot = plot_range[0]
om_maxplot = plot_range[1]
n_om = len(mesh_val[(mesh_val > om_minplot)&(mesh_val < om_maxplot)])
mesh_val2 = mesh_val[(mesh_val > om_minplot)&(mesh_val < om_maxplot)]
#\omega ~= 0.0 index for FS file
abs_mesh_val = [abs(i) for i in mesh_val2]
jw=[i for i in range(len(abs_mesh_val)) if abs_mesh_val[i] == numpy.min(abs_mesh_val[:])]
#calculate the spectral functions for the irreducible set of k-points
[Akw, pAkw, pAkw_orb] = self.gen_Akw(mu=mu, broadening=broadening, mesh=mesh, \
plot_shift=0.0, plot_range=plot_range, \
shell_list=None, with_Sigma=with_Sigma, with_dc=with_dc, \
proj_type=proj_type)
if save_to_file and mpi.is_master_node():
spn = self.spin_block_names[self.SO]
vkc = numpy.zeros(3, float)
mesh_val2 = mesh_val[(mesh_val > om_minplot)&(mesh_val < om_maxplot)]
if FS:
n_om = 1
else:
n_om = len(mesh_val2)
for sp in spn:
# Open file for storage:
for iom in range(n_om):
if FS:
f = open('Akw_FS_' + sp + '.dat', 'w')
jom=jw[0]
else:
f = open('Akw_omega_%s_%s.dat' % (iom, sp), 'w')
jom=iom
f.write("#Spectral function evaluated at frequency = %s\n" %mesh_val2[jom])
for ik in range(self.BZ_n_k):
jk=self.BZ_iknr[ik]
vkc[:] = numpy.matmul(self.bmat,self.BZ_vkl[ik,:])
f.write("%s %s %s %s\n" % (vkc[0], vkc[1], vkc[2], Akw[sp][jk, jom]))
f.close()
if (proj_type!=None):
n_shells = len(pAkw[:])
for iom in range(n_om):
for sp in spn:
for ish in range(n_shells):
if FS:
strng = 'Akw_FS' + '_' + proj_type + '_' + sp + '_proj' + str(ish)
jom=jw[0]
else:
strng = 'Akw_omega_' + str(iom) + '_' + proj_type + '_' + sp + '_proj' + str(ish)
jom=iom
f = open(strng + '.dat', 'w')
f.write("#Spectral function evaluated at frequency = %s\n" %mesh_val2[jom])
for ik in range(self.BZ_n_k):
jk=self.BZ_iknr[ik]
vkc[:] = numpy.matmul(self.bmat,self.BZ_vkl[ik,:])
f.write("%s %s %s %s\n" % (vkc[0], vkc[1], vkc[2],
pAkw[ish][sp][jk, jom]))
f.close()
dim=len(pAkw_orb[ish][sp][0, 0, 0, :])
for i in range(dim):
for j in range(dim):
#For Elk with parproj - skip off-diagonal elements
if(proj_type=='elk') and (i!=j): continue
strng2 = strng + '_' + str(i) + '_' + str(j)
# Open file for storage:
f = open(strng2 + '.dat', 'w')
for ik in range(self.BZ_n_k):
jk=self.BZ_iknr[ik]
vkc[:] = numpy.matmul(self.bmat,self.BZ_vkl[ik,:])
f.write("%s %s %s %s\n" % (vkc[0], vkc[1], vkc[2],
pAkw_orb[ish][sp][jk, jom, i, j]))
f.close()
return Akw, pAkw, pAkw_orb
# Uses .data of only GfReFreq objects.
def spaghettis(self, mu=None, broadening=None, mesh=None, plot_shift=0.0, plot_range=None, shell_list=None, with_Sigma=True, with_dc=True, proj_type=None, save_to_file=True):
"""
Calculates the k-resolved spectral function A(k,w) (band structure)
Parameters
----------
mu : double, optional
Chemical potential, overrides the one stored in the hdf5 archive.
broadening : double, optional
Lorentzian broadening of the spectra.
If not given, standard value of lattice_gf is used.
mesh : real frequency MeshType, optional
Omega mesh for the real-frequency Green's function.
Given as parameter to lattice_gf.
plot_shift : double, optional
Offset for each A(k,w) for stacked plotting of spectra.
plot_range : list of double, optional
Sets the energy window for plotting to (plot_range[0],plot_range[1]).
If not provided, the min and max values of the energy mesh is used.
shell_list : list of integers, optional
Contains the indices of the shells of which the projected spectral function
is calculated for.
If shell_list = None and proj_type is not None, then the projected spectral
function is calculated for all shells.
with_Sigma : boolean, optional
If True, the self energy is used for the calculation.
If false, the DOS is calculated without self energy.
with_dc : boolean, optional
If True the double counting correction is used.
proj_type : string, optional
Output the orbital-projected A(k,w) type from the following:
'wann' - Wannier A(k,w) calculated from the Wannier projectors
'wien2k' - Wien2k orbital-projected A(k,w) from the wien2k theta projectors
save_to_file : boolean, optional
If True, text files with the calculated data will be created.
Returns
-------
Akw : Dict of numpy arrays
(Correlated) k-resolved spectral function
pAkw : Dict of numpy arrays
(Correlated) k-resolved spectral function projected to atoms.
Empty if proj_type = None
pAkw_orb : Dict of numpy arrays
(Correlated) k-resolved spectral function projected to atoms and
resolved into orbital contributions. Empty if proj_type = None
"""
#initialisation
if(proj_type!=None):
assert proj_type in ('wann', 'wien2k'), "'proj_type' must be either 'wann', 'wien2k'"
if(proj_type!='wann'):
assert proj_type==self.dft_code, "proj_type must be from the corresponding dft inputs."
things_to_read = ['n_k', 'n_orbitals', 'proj_mat', 'hopping']
subgroup_present, values_not_read = self.read_input_from_hdf(
subgrp=self.bands_data, things_to_read=things_to_read)
if len(values_not_read) > 0 and mpi.is_master_node:
raise ValueError(
'ERROR: One or more necessary SumK input properties have not been found in the given h5 archive:', self.values_not_read)
if(proj_type=='wien2k'):
self.load_parproj(data_type='band')
if mu is None:
mu = self.chemical_potential
if (with_Sigma):
assert isinstance(self.Sigma_imp[0].mesh, MeshReFreq), "SumkDFT.mesh must be real if with_Sigma is True"
mesh=self.Sigma_imp[0].mesh
elif mesh is not None:
assert isinstance(mesh, MeshReFreq), "mesh must be of form MeshReFreq"
if broadening is None:
broadening=0.001
elif self.mesh is not None:
assert isinstance(self.mesh, MeshReFreq), "self.mesh must be of form MeshReFreq"
mesh=self.mesh
if broadening is None:
broadening=0.001
else:
assert 0, "ReFreqMesh input required for calculations without real frequency self-energy"
mesh_val = numpy.linspace(mesh.omega_min,mesh.omega_max,len(mesh))
n_om = len(mesh)
om_minplot = mesh_val[0] - 0.001
om_maxplot = mesh_val[-1] + 0.001
if plot_range is None:
om_minplot = mesh_val[0] - 0.001
om_maxplot = mesh_val[-1] + 0.001
else:
om_minplot = plot_range[0]
om_maxplot = plot_range[1]
n_om = len(mesh_val[(mesh_val > om_minplot)&(mesh_val < om_maxplot)])
[Akw, pAkw, pAkw_orb] = self.gen_Akw(mu=mu, broadening=broadening, mesh=mesh, \
plot_shift=plot_shift, plot_range=plot_range, \
shell_list=shell_list, with_Sigma=with_Sigma, with_dc=with_dc, \
proj_type=proj_type)
if save_to_file and mpi.is_master_node():
mesh_val2 = mesh_val[(mesh_val > om_minplot)&(mesh_val < om_maxplot)]
spn = self.spin_block_names[self.SO]
for sp in spn:
# Open file for storage:
f = open('Akw_' + sp + '.dat', 'w')
for ik in range(self.n_k):
for iom in range(n_om):
f.write('%s %s %s\n' %(ik, mesh_val2[iom], Akw[sp][ik, iom]))
f.write('\n')
f.close()
if (proj_type!=None):
n_shells = len(pAkw[:])
if shell_list==None:
shell_list=[ish for ish in range(n_shells)]
for sp in spn:
for ish in range(n_shells):
jsh=shell_list[ish]
f = open('Akw_' + proj_type + '_' +
sp + '_proj' + str(jsh) + '.dat', 'w')
for ik in range(self.n_k):
for iom in range(n_om):
f.write('%s %s %s\n' % (
ik, mesh_val2[iom], pAkw[ish][sp][ik, iom]))
f.write('\n')
f.close()
#get orbital dimension from the length of dimension of the array
dim=len(pAkw_orb[ish][sp][0, 0, 0, :])
for i in range(dim):
for j in range(dim):
#For Elk with parproj - skip off-diagonal elements
if(proj_type=='elk') and (i!=j): continue
# Open file for storage:
f = open('Akw_' + proj_type + '_' + sp + '_proj' + str(jsh)
+ '_' + str(i) + '_' + str(j) + '.dat', 'w')
for ik in range(self.n_k):
for iom in range(n_om):
f.write('%s %s %s\n' % (
ik, mesh_val2[iom], pAkw_orb[ish][sp][ik, iom, i, j]))
f.write('\n')
f.close()
return Akw, pAkw, pAkw_orb
def gen_Akw(self, mu, broadening, mesh, plot_shift, plot_range, shell_list, with_Sigma, with_dc, proj_type):
"""
Internal routine used by spaghettis and spectral_contours to Calculate the k-resolved spectral
function A(k,w). For advanced users only.
Parameters
----------
mu : double
Chemical potential, overrides the one stored in the hdf5 archive.
broadening : double
Lorentzian broadening of the spectra.
mesh : real frequency MeshType, optional
Omega mesh for the real-frequency Green's function.
Given as parameter to lattice_gf.
plot_shift : double
Offset for each A(k,w) for stacked plotting of spectra.
plot_range : list of double
Sets the energy window for plotting to (plot_range[0],plot_range[1]).
shell_list : list of integers, optional
Contains the indices of the shells of which the projected spectral function
is calculated for.
If shell_list = None and proj_type is not None, then the projected spectral
function is calculated for all shells.
with_Sigma : boolean
If True, the self energy is used for the calculation.
If false, the DOS is calculated without self energy.
with_dc : boolean
If True the double counting correction is used.
proj_type : string
Output the orbital-projected A(k,w) type from the following:
'wann' - Wannier A(k,w) calculated from the Wannier projectors
'wien2k' - Wien2k orbital-projected A(k,w) from the wien2k theta projectors
Returns
-------
Akw : Dict of numpy arrays
(Correlated) k-resolved spectral function
pAkw : Dict of numpy arrays
(Correlated) k-resolved spectral function projected to atoms.
Empty if proj_type = None
pAkw_orb : Dict of numpy arrays
(Correlated) k-resolved spectral function projected to atoms and
resolved into orbital contributions. Empty if proj_type = None
"""
mesh_val = numpy.linspace(mesh.omega_min,mesh.omega_max,len(mesh))
n_om = len(mesh)
om_minplot = mesh_val[0] - 0.001
om_maxplot = mesh_val[-1] + 0.001
if plot_range is None:
om_minplot = mesh_val[0] - 0.001
om_maxplot = mesh_val[-1] + 0.001
else:
om_minplot = plot_range[0]
om_maxplot = plot_range[1]
n_om = len(mesh_val[(mesh_val > om_minplot)&(mesh_val < om_maxplot)])
#set-up spectral functions
spn = self.spin_block_names[self.SO]
Akw = {sp: numpy.zeros([self.n_k, n_om], float) for sp in spn}
pAkw = []
pAkw_orb = []
#set-up projected A(k,w) and parameters if required
if (proj_type):
if (proj_type == 'wann'):
n_shells = self.n_corr_shells
gf_struct = self.gf_struct_sumk.copy()
dims = [self.corr_shells[ish]['dim'] for ish in range(n_shells)]
shells_type = 'corr'
elif (proj_type == 'wien2k'):
n_shells = self.n_shells
gf_struct = [[(sp, self.shells[ish]['dim']) for sp in spn]
for ish in range(n_shells)]
dims = [self.shells[ish]['dim'] for ish in range(n_shells)]
shells_type = 'all'
#only outputting user specified parproj shells
if shell_list!=None:
for ish in shell_list:
if(ish > n_shells) or (ish < 0):
raise IOError("indices in shell_list input do not correspond \
to existing self.shells indices")
n_shells = len(shell_list)
mpi.report("calculating spectral functions for following user specified shell_list:")
[mpi.report('%s : %s '%(ish, self.shells[ish])) for ish in shell_list]
else:
shell_list=[ish for ish in range(n_shells)]
#projected Akw via projectors
pAkw = [{} for ish in range(n_shells)]
pAkw_orb = [{} for ish in range(n_shells)]
#set-up Green's function object
G_loc = []
for ish in range(n_shells):
jsh=shell_list[ish]
dim = dims[ish]
for sp in spn:
pAkw[ish][sp] = numpy.zeros([self.n_k, n_om], float)
pAkw_orb[ish][sp] = numpy.zeros([self.n_k, n_om, dim, dim], float)
glist = [GfReFreq(target_shape=(block_dim, block_dim), mesh=mesh)
for block, block_dim in gf_struct[ish]]
G_loc.append(
BlockGf(name_list=spn, block_list=glist, make_copies=False))
G_loc[ish].zero()
#calculate the spectral function
ikarray = numpy.array(list(range(self.n_k)))
for ik in mpi.slice_array(ikarray):
G_latt_w = self.lattice_gf(ik=ik, mu=mu, broadening=broadening, mesh=mesh, with_Sigma=with_Sigma, with_dc=with_dc)
# Non-projected A(k,w)
for bname, gf in G_latt_w:
Akw[bname][ik] = -gf.data[numpy.where((mesh_val > om_minplot) &
(mesh_val < om_maxplot))].imag.trace(axis1=1, axis2=2)/numpy.pi
# shift Akw for plotting stacked k-resolved eps(k) curves
Akw[bname][ik] += ik * plot_shift
#project spectral functions
if (proj_type!=None):
# Projected A(k,w):
for ish in range(n_shells):
G_loc[ish].zero()
tmp = G_loc[ish].copy()
tmp.zero()
tmp << self.proj_type_G_loc(G_latt_w, tmp, ik, ish, proj_type)
G_loc[ish] += tmp
# Rotate to local frame
if (self.use_rotations):
for ish in range(n_shells):
jsh=shell_list[ish]
for bname, gf in G_loc[ish]:
G_loc[ish][bname] << self.rotloc(
jsh, gf, direction='toLocal', shells=shells_type)
for ish in range(n_shells):
for bname, gf in G_loc[ish]: # loop over spins
pAkw_orb[ish][bname][ik,:,:,:] = -gf.data[numpy.where((mesh_val > om_minplot) &
(mesh_val < om_maxplot)),:,:].imag/numpy.pi
# shift pAkw_orb for plotting stacked k-resolved eps(k) curves
pAkw_orb[ish][sp][ik] += ik * plot_shift
# Collect data from mpi
mpi.barrier()
for sp in spn:
Akw[sp] = mpi.all_reduce(mpi.world, Akw[sp], lambda x, y: x + y)
if (proj_type):
for ish in range(n_shells):
pAkw_orb[ish][sp] = mpi.all_reduce(mpi.world, pAkw_orb[ish][sp], lambda x, y: x + y)
pAkw[ish][sp] = pAkw_orb[ish][sp].trace(axis1=2, axis2=3)
mpi.barrier()
return Akw, pAkw, pAkw_orb
def partial_charges(self, mu=None, with_Sigma=True, with_dc=True):
"""
Calculates the orbitally-resolved density matrix for all the orbitals considered in the input, consistent with
the definition of Wien2k. Hence, (possibly non-orthonormal) projectors have to be provided in the partial projectors subgroup of
the hdf5 archive.
Parameters
----------
with_Sigma : boolean, optional
If True, the self energy is used for the calculation. If false, partial charges are calculated without self-energy correction.
mu : double, optional
Chemical potential, overrides the one stored in the hdf5 archive.
with_dc : boolean, optional
If True the double counting correction is used.
Returns
-------
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']
subgroup_present, values_not_read = self.read_input_from_hdf(
subgrp=self.parproj_data, things_to_read=things_to_read)
if len(values_not_read) > 0 and mpi.is_master_node:
raise ValueError(
'ERROR: One or more necessary SumK input properties have not been found in the given h5 archive:', self.values_not_read)
if self.symm_op:
self.symmpar = Symmetry(self.hdf_file, subgroup=self.symmpar_data)
spn = self.spin_block_names[self.SO]
ntoi = self.spin_names_to_ind[self.SO]
# Density matrix in the window
self.dens_mat_window = [[numpy.zeros([self.shells[ish]['dim'], self.shells[ish]['dim']], complex)
for ish in range(self.n_shells)]
for isp in range(len(spn))]
# Set up G_loc
gf_struct_parproj = [[(sp, self.shells[ish]['dim']) for sp in spn]
for ish in range(self.n_shells)]
G_loc = [BlockGf(name_block_generator=[(block, GfImFreq(target_shape=(block_dim, block_dim), mesh=self.mesh))
for block, block_dim in gf_struct_parproj[ish]], make_copies=False)
for ish in range(self.n_shells)]
for ish in range(self.n_shells):
G_loc[ish].zero()
ikarray = numpy.array(list(range(self.n_k)))
for ik in mpi.slice_array(ikarray):
G_latt_iw = self.lattice_gf(ik=ik, mu=mu, with_Sigma=with_Sigma, with_dc=with_dc)
G_latt_iw *= self.bz_weights[ik]
for ish in range(self.n_shells):
tmp = G_loc[ish].copy()
for ir in range(self.n_parproj[ish]):
for bname, gf in tmp:
tmp[bname] << self.downfold(ik, ish, bname, G_latt_iw[
bname], gf, shells='all', ir=ir)
G_loc[ish] += tmp
# Collect data from mpi:
for ish in range(self.n_shells):
G_loc[ish] << mpi.all_reduce(
mpi.world, G_loc[ish], lambda x, y: x + y)
mpi.barrier()
# Symmetrize and rotate to local coord. system if needed:
if self.symm_op != 0:
G_loc = self.symmpar.symmetrize(G_loc)
if self.use_rotations:
for ish in range(self.n_shells):
for bname, gf in G_loc[ish]:
G_loc[ish][bname] << self.rotloc(
ish, gf, direction='toLocal', shells='all')
for ish in range(self.n_shells):
isp = 0
for bname, gf in G_loc[ish]:
self.dens_mat_window[isp][ish] = G_loc[ish].density()[bname]
isp += 1
# Add density matrices to get the total:
dens_mat = [[self.dens_mat_below[ntoi[spn[isp]]][ish] + self.dens_mat_window[isp][ish]
for ish in range(self.n_shells)]
for isp in range(len(spn))]
return dens_mat
def print_hamiltonian(self):
"""
Prints the Kohn-Sham Hamiltonian to the text files hamup.dat and hamdn.dat (no spin orbit-coupling), or to ham.dat (with spin-orbit coupling).
"""
if self.SP == 1 and self.SO == 0:
f1 = open('hamup.dat', 'w')
f2 = open('hamdn.dat', 'w')
for ik in range(self.n_k):
for i in range(self.n_orbitals[ik, 0]):
f1.write('%s %s\n' %
(ik, self.hopping[ik, 0, i, i].real))
for i in range(self.n_orbitals[ik, 1]):
f2.write('%s %s\n' %
(ik, self.hopping[ik, 1, i, i].real))
f1.write('\n')
f2.write('\n')
f1.close()
f2.close()
else:
f = open('ham.dat', 'w')
for ik in range(self.n_k):
for i in range(self.n_orbitals[ik, 0]):
f.write('%s %s\n' %
(ik, self.hopping[ik, 0, i, i].real))
f.write('\n')
f.close()