mirror of
https://github.com/triqs/dft_tools
synced 2024-12-22 12:23:41 +01:00
273 lines
12 KiB
Python
273 lines
12 KiB
Python
|
|
##########################################################################
|
|
#
|
|
# TRIQS: a Toolbox for Research in Interacting Quantum Systems
|
|
#
|
|
# Copyright (C) 2011 by 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/>.
|
|
#
|
|
##########################################################################
|
|
|
|
from types import *
|
|
import numpy
|
|
from pytriqs.archive import *
|
|
import pytriqs.utility.mpi as mpi
|
|
from math import sqrt
|
|
from converter_tools import *
|
|
|
|
|
|
class HkConverter(ConverterTools):
|
|
"""
|
|
Conversion from general H(k) file 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', repacking=False):
|
|
"""
|
|
Initialise the class.
|
|
|
|
Parameters
|
|
----------
|
|
filename : string
|
|
Name of file containing the H(k) and other relevant data.
|
|
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.
|
|
The group is actually empty; it is just included for compatibility.
|
|
repacking : boolean, optional
|
|
Does the hdf5 archive need to be repacked to save space?
|
|
|
|
"""
|
|
|
|
assert type(
|
|
filename) == StringType, "HkConverter: filename must be a filename."
|
|
if hdf_filename is None:
|
|
hdf_filename = filename + '.h5'
|
|
self.hdf_file = hdf_filename
|
|
self.dft_file = filename
|
|
self.dft_subgrp = dft_subgrp
|
|
self.symmcorr_subgrp = symmcorr_subgrp
|
|
self.fortran_to_replace = {'D': 'E', '(': ' ', ')': ' ', ',': ' '}
|
|
|
|
# Checks if h5 file is there and repacks it if wanted:
|
|
import os.path
|
|
if (os.path.exists(self.hdf_file) and repacking):
|
|
ConverterTools.repack(self)
|
|
|
|
def convert_dft_input(self, first_real_part_matrix=True, only_upper_triangle=False, weights_in_file=False):
|
|
"""
|
|
Reads the appropriate files and stores the data for the dft_subgrp in the hdf5 archive.
|
|
|
|
Parameters
|
|
----------
|
|
first_real_part_matrix : boolean, optional
|
|
Should all the real components for given k be read in first, followed by the imaginary parts?
|
|
only_upper_triangle : boolean, optional
|
|
Should only the upper triangular part of H(k) be read in?
|
|
weights_in_file : boolean, optional
|
|
Are the k-point weights to be read in?
|
|
|
|
"""
|
|
|
|
# Read and write only on the master node
|
|
if not (mpi.is_master_node()):
|
|
return
|
|
mpi.report("Reading input from %s..." % self.dft_file)
|
|
|
|
# R is a generator : each R.Next() will return the next number in the
|
|
# file
|
|
R = ConverterTools.read_fortran_file(
|
|
self, self.dft_file, self.fortran_to_replace)
|
|
try:
|
|
# the energy conversion factor is 1.0, we assume eV in files
|
|
energy_unit = 1.0
|
|
# read the number of k points
|
|
n_k = int(R.next())
|
|
k_dep_projection = 0
|
|
SP = 0 # no spin-polarision
|
|
SO = 0 # no spin-orbit
|
|
# total charge below energy window is set to 0
|
|
charge_below = 0.0
|
|
# density required, for setting the chemical potential
|
|
density_required = R.next()
|
|
symm_op = 0 # No symmetry groups for the k-sum
|
|
|
|
# the information on the non-correlated shells is needed for
|
|
# defining dimension of matrices:
|
|
# number of shells considered in the Wanniers
|
|
n_shells = int(R.next())
|
|
# corresponds to index R in formulas
|
|
# now read the information about the shells (atom, sort, l, dim):
|
|
shell_entries = ['atom', 'sort', 'l', 'dim']
|
|
shells = [{name: int(val) for name, val in zip(
|
|
shell_entries, R)} for ish in range(n_shells)]
|
|
|
|
# number of corr. shells (e.g. Fe d, Ce f) in the unit cell,
|
|
n_corr_shells = int(R.next())
|
|
# corresponds to index R in formulas
|
|
# now read the information about the shells (atom, sort, l, dim, SO
|
|
# flag, irep):
|
|
corr_shell_entries = ['atom', 'sort', 'l', 'dim','SO','irep']
|
|
corr_shells = [{name: int(val) for name, val in zip(
|
|
corr_shell_entries, R)} for icrsh in range(n_corr_shells)]
|
|
|
|
# determine the number of inequivalent correlated shells and maps,
|
|
# needed for further reading
|
|
[n_inequiv_shells, corr_to_inequiv,
|
|
inequiv_to_corr] = ConverterTools.det_shell_equivalence(self, corr_shells)
|
|
|
|
use_rotations = 0
|
|
rot_mat = [numpy.identity(
|
|
corr_shells[icrsh]['dim'], numpy.complex_) for icrsh in range(n_corr_shells)]
|
|
rot_mat_time_inv = [0 for i in range(n_corr_shells)]
|
|
|
|
# Representative representations are read from file
|
|
n_reps = [1 for i in range(n_inequiv_shells)]
|
|
dim_reps = [0 for i in range(n_inequiv_shells)]
|
|
T = []
|
|
for ish in range(n_inequiv_shells):
|
|
# number of representatives ("subsets"), e.g. t2g and eg
|
|
n_reps[ish] = int(R.next())
|
|
dim_reps[ish] = [int(R.next()) for i in range(
|
|
n_reps[ish])] # dimensions of the subsets
|
|
|
|
# The transformation matrix:
|
|
# is of dimension 2l+1, it is taken to be standard d (as in
|
|
# Wien2k)
|
|
ll = 2 * corr_shells[inequiv_to_corr[ish]]['l'] + 1
|
|
lmax = ll * (corr_shells[inequiv_to_corr[ish]]['SO'] + 1)
|
|
T.append(numpy.zeros([lmax, lmax], numpy.complex_))
|
|
|
|
T[ish] = numpy.array([[0.0, 0.0, 1.0, 0.0, 0.0],
|
|
[1.0 / sqrt(2.0), 0.0, 0.0,
|
|
0.0, 1.0 / sqrt(2.0)],
|
|
[-1.0 / sqrt(2.0), 0.0, 0.0,
|
|
0.0, 1.0 / sqrt(2.0)],
|
|
[0.0, 1.0 /
|
|
sqrt(2.0), 0.0, -1.0 / sqrt(2.0), 0.0],
|
|
[0.0, 1.0 / sqrt(2.0), 0.0, 1.0 / sqrt(2.0), 0.0]])
|
|
|
|
# Spin blocks to be read:
|
|
# number of spins to read for Norbs and Ham, NOT Projectors
|
|
n_spin_blocs = SP + 1 - SO
|
|
|
|
# define the number of n_orbitals for all k points: it is the
|
|
# number of total bands and independent of k!
|
|
n_orbitals = numpy.ones(
|
|
[n_k, n_spin_blocs], numpy.int) * sum([sh['dim'] for sh in shells])
|
|
|
|
# Initialise the projectors:
|
|
proj_mat = numpy.zeros([n_k, n_spin_blocs, n_corr_shells, max(
|
|
[crsh['dim'] for crsh in corr_shells]), numpy.max(n_orbitals)], numpy.complex_)
|
|
|
|
# Read the projectors from the file:
|
|
for ik in range(n_k):
|
|
for icrsh in range(n_corr_shells):
|
|
for isp in range(n_spin_blocs):
|
|
|
|
# calculate the offset:
|
|
offset = 0
|
|
n_orb = 0
|
|
for ish in range(n_shells):
|
|
if (n_orb == 0):
|
|
if (shells[ish]['atom'] == corr_shells[icrsh]['atom']) and (shells[ish]['sort'] == corr_shells[icrsh]['sort']):
|
|
n_orb = corr_shells[icrsh]['dim']
|
|
else:
|
|
offset += shells[ish]['dim']
|
|
|
|
proj_mat[ik, isp, icrsh, 0:n_orb,
|
|
offset:offset + n_orb] = numpy.identity(n_orb)
|
|
|
|
# now define the arrays for weights and hopping ...
|
|
# w(k_index), default normalisation
|
|
bz_weights = numpy.ones([n_k], numpy.float_) / float(n_k)
|
|
hopping = numpy.zeros([n_k, n_spin_blocs, numpy.max(
|
|
n_orbitals), numpy.max(n_orbitals)], numpy.complex_)
|
|
|
|
if (weights_in_file):
|
|
# weights in the file
|
|
for ik in range(n_k):
|
|
bz_weights[ik] = R.next()
|
|
|
|
# if the sum over spins is in the weights, take it out again!!
|
|
sm = sum(bz_weights)
|
|
bz_weights[:] /= sm
|
|
|
|
# Grab the H
|
|
for isp in range(n_spin_blocs):
|
|
for ik in range(n_k):
|
|
n_orb = n_orbitals[ik, isp]
|
|
|
|
# first read all real components for given k, then read
|
|
# imaginary parts
|
|
if (first_real_part_matrix):
|
|
|
|
for i in range(n_orb):
|
|
if (only_upper_triangle):
|
|
istart = i
|
|
else:
|
|
istart = 0
|
|
for j in range(istart, n_orb):
|
|
hopping[ik, isp, i, j] = R.next()
|
|
|
|
for i in range(n_orb):
|
|
if (only_upper_triangle):
|
|
istart = i
|
|
else:
|
|
istart = 0
|
|
for j in range(istart, n_orb):
|
|
hopping[ik, isp, i, j] += R.next() * 1j
|
|
if ((only_upper_triangle)and(i != j)):
|
|
hopping[ik, isp, j, i] = hopping[
|
|
ik, isp, i, j].conjugate()
|
|
|
|
else: # read (real,im) tuple
|
|
|
|
for i in range(n_orb):
|
|
if (only_upper_triangle):
|
|
istart = i
|
|
else:
|
|
istart = 0
|
|
for j in range(istart, n_orb):
|
|
hopping[ik, isp, i, j] = R.next()
|
|
hopping[ik, isp, i, j] += R.next() * 1j
|
|
|
|
if ((only_upper_triangle)and(i != j)):
|
|
hopping[ik, isp, j, i] = hopping[
|
|
ik, isp, i, j].conjugate()
|
|
# keep some things that we need for reading parproj:
|
|
things_to_set = ['n_shells', 'shells', 'n_corr_shells', 'corr_shells',
|
|
'n_spin_blocs', 'n_orbitals', 'n_k', 'SO', 'SP', 'energy_unit']
|
|
for it in things_to_set:
|
|
setattr(self, it, locals()[it])
|
|
except StopIteration: # a more explicit error if the file is corrupted.
|
|
raise "HK Converter : reading file dft_file failed!"
|
|
|
|
R.close()
|
|
|
|
# Save to the HDF5:
|
|
ar = HDFArchive(self.hdf_file, 'a')
|
|
if not (self.dft_subgrp in ar):
|
|
ar.create_group(self.dft_subgrp)
|
|
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
|