mirror of
https://github.com/triqs/dft_tools
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535 lines
24 KiB
Python
535 lines
24 KiB
Python
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################################################################################
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#
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# TRIQS: a Toolbox for Research in Interacting Quantum Systems
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#
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# Copyright (C) 2011 by M. Aichhorn, L. Pourovskii, V. Vildosola
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#
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# TRIQS is free software: you can redistribute it and/or modify it under the
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# terms of the GNU General Public License as published by the Free Software
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# Foundation, either version 3 of the License, or (at your option) any later
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# version.
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#
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# TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY
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# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
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# details.
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#
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# You should have received a copy of the GNU General Public License along with
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# TRIQS. If not, see <http://www.gnu.org/licenses/>.
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#
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################################################################################
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from types import *
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import numpy
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from pytriqs.archive import *
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import pytriqs.utility.mpi as mpi
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import string
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def read_fortran_file (filename):
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""" Returns a generator that yields all numbers in the Fortran file as float, one by one"""
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import os.path
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if not(os.path.exists(filename)) : raise IOError, "File %s does not exist."%filename
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for line in open(filename,'r') :
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for x in line.replace('D','E').split() :
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yield string.atof(x)
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class Wien2kConverter:
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"""
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Conversion from Wien2k output to an hdf5 file that can be used as input for the SumkLDA class.
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"""
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def __init__(self, filename, lda_subgrp = 'SumK_LDA', symm_subgrp = 'SymmCorr', repacking = False):
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"""
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Init of the class. Variable filename gives the root of all filenames, e.g. case.ctqmcout, case.h5, and so on.
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"""
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assert type(filename)==StringType,"LDA_file must be a filename"
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self.hdf_file = filename+'.h5'
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self.lda_file = filename+'.ctqmcout'
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self.symm_file = filename+'.symqmc'
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self.parproj_file = filename+'.parproj'
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self.symmpar_file = filename+'.sympar'
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self.band_file = filename+'.outband'
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self.lda_subgrp = lda_subgrp
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self.symm_subgrp = symm_subgrp
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# Checks if h5 file is there and repacks it if wanted:
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import os.path
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if (os.path.exists(self.hdf_file) and repacking):
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self.__repack()
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def convert_dmft_input(self):
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"""
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Reads the input files, and stores the data in the HDFfile
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"""
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# Read and write only on the master node
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if not (mpi.is_master_node()): return
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mpi.report("Reading input from %s..."%self.lda_file)
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# R is a generator : each R.Next() will return the next number in the file
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R = read_fortran_file(self.lda_file)
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try:
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energy_unit = R.next() # read the energy convertion factor
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n_k = int(R.next()) # read the number of k points
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k_dep_projection = 1
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SP = int(R.next()) # flag for spin-polarised calculation
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SO = int(R.next()) # flag for spin-orbit calculation
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charge_below = R.next() # total charge below energy window
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density_required = R.next() # total density required, for setting the chemical potential
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symm_op = 1 # Use symmetry groups for the k-sum
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# the information on the non-correlated shells is not important here, maybe skip:
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n_shells = int(R.next()) # number of shells (e.g. Fe d, As p, O p) in the unit cell,
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# corresponds to index R in formulas
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shells = [ [ int(R.next()) for i in range(4) ] for icrsh in range(n_shells) ] # reads iatom, sort, l, dim
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n_corr_shells = int(R.next()) # number of corr. shells (e.g. Fe d, Ce f) in the unit cell,
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# corresponds to index R in formulas
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# now read the information about the shells:
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corr_shells = [ [ int(R.next()) for i in range(6) ] for icrsh in range(n_corr_shells) ] # reads iatom, sort, l, dim, SO flag, irep
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self.inequiv_shells(corr_shells) # determine the number of inequivalent correlated shells, has to be known for further reading...
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use_rotations = 1
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rot_mat = [numpy.identity(corr_shells[icrsh][3],numpy.complex_) for icrsh in xrange(n_corr_shells)]
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# read the matrices
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rot_mat_time_inv = [0 for i in range(n_corr_shells)]
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for icrsh in xrange(n_corr_shells):
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for i in xrange(corr_shells[icrsh][3]): # read real part:
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for j in xrange(corr_shells[icrsh][3]):
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rot_mat[icrsh][i,j] = R.next()
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for i in xrange(corr_shells[icrsh][3]): # read imaginary part:
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for j in xrange(corr_shells[icrsh][3]):
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rot_mat[icrsh][i,j] += 1j * R.next()
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if (SP==1): # read time inversion flag:
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rot_mat_time_inv[icrsh] = int(R.next())
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# Read here the info for the transformation of the basis:
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n_reps = [1 for i in range(self.n_inequiv_corr_shells)]
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dim_reps = [0 for i in range(self.n_inequiv_corr_shells)]
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T = []
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for icrsh in range(self.n_inequiv_corr_shells):
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n_reps[icrsh] = int(R.next()) # number of representatives ("subsets"), e.g. t2g and eg
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dim_reps[icrsh] = [int(R.next()) for i in range(n_reps[icrsh])] # dimensions of the subsets
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# The transformation matrix:
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# is of dimension 2l+1 without SO, and 2*(2l+1) with SO!
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ll = 2*corr_shells[self.invshellmap[icrsh]][2]+1
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lmax = ll * (corr_shells[self.invshellmap[icrsh]][4] + 1)
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T.append(numpy.zeros([lmax,lmax],numpy.complex_))
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# now read it from file:
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for i in xrange(lmax):
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for j in xrange(lmax):
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T[icrsh][i,j] = R.next()
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for i in xrange(lmax):
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for j in xrange(lmax):
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T[icrsh][i,j] += 1j * R.next()
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# Spin blocks to be read:
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n_spin_blocs = SP + 1 - SO
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# read the list of n_orbitals for all k points
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n_orbitals = numpy.zeros([n_k,n_spin_blocs],numpy.int)
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for isp in range(n_spin_blocs):
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for ik in xrange(n_k):
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n_orbitals[ik,isp] = int(R.next())
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# Initialise the projectors:
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proj_mat = numpy.zeros([n_k,n_spin_blocs,n_corr_shells,max(numpy.array(corr_shells)[:,3]),max(n_orbitals)],numpy.complex_)
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# Read the projectors from the file:
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for ik in xrange(n_k):
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for icrsh in range(n_corr_shells):
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no = corr_shells[icrsh][3]
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# first Real part for BOTH spins, due to conventions in dmftproj:
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for isp in range(n_spin_blocs):
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for i in xrange(no):
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for j in xrange(n_orbitals[ik][isp]):
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proj_mat[ik,isp,icrsh,i,j] = R.next()
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# now Imag part:
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for isp in range(n_spin_blocs):
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for i in xrange(no):
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for j in xrange(n_orbitals[ik][isp]):
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proj_mat[ik,isp,icrsh,i,j] += 1j * R.next()
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# now define the arrays for weights and hopping ...
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bz_weights = numpy.ones([n_k],numpy.float_)/ float(n_k) # w(k_index), default normalisation
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hopping = numpy.zeros([n_k,n_spin_blocs,max(n_orbitals),max(n_orbitals)],numpy.complex_)
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# weights in the file
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for ik in xrange(n_k) : bz_weights[ik] = R.next()
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# if the sum over spins is in the weights, take it out again!!
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sm = sum(bz_weights)
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bz_weights[:] /= sm
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# Grab the H
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# we use now the convention of a DIAGONAL Hamiltonian!!!!
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for isp in range(n_spin_blocs):
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for ik in xrange(n_k) :
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no = n_orbitals[ik,isp]
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for i in xrange(no):
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hopping[ik,isp,i,i] = R.next() * energy_unit
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# keep some things that we need for reading parproj:
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self.n_shells = n_shells
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self.shells = shells
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self.n_corr_shells = n_corr_shells
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self.corr_shells = corr_shells
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self.n_spin_blocs = n_spin_blocs
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self.n_orbitals = n_orbitals
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self.n_k = n_k
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self.SO = SO
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self.SP = SP
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self.energy_unit = energy_unit
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except StopIteration : # a more explicit error if the file is corrupted.
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raise "Wien2k_converter : reading file lda_file failed!"
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R.close()
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#-----------------------------------------
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# Store the input into HDF5:
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ar = HDFArchive(self.hdf_file,'a')
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if not (self.lda_subgrp in ar): ar.create_group(self.lda_subgrp)
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# The subgroup containing the data. If it does not exist, it is created.
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# If it exists, the data is overwritten!!!
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ar[self.lda_subgrp]['energy_unit'] = energy_unit
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ar[self.lda_subgrp]['n_k'] = n_k
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ar[self.lda_subgrp]['k_dep_projection'] = k_dep_projection
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ar[self.lda_subgrp]['SP'] = SP
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ar[self.lda_subgrp]['SO'] = SO
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ar[self.lda_subgrp]['charge_below'] = charge_below
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ar[self.lda_subgrp]['density_required'] = density_required
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ar[self.lda_subgrp]['symm_op'] = symm_op
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ar[self.lda_subgrp]['n_shells'] = n_shells
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ar[self.lda_subgrp]['shells'] = shells
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ar[self.lda_subgrp]['n_corr_shells'] = n_corr_shells
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ar[self.lda_subgrp]['corr_shells'] = corr_shells
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ar[self.lda_subgrp]['use_rotations'] = use_rotations
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ar[self.lda_subgrp]['rot_mat'] = rot_mat
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ar[self.lda_subgrp]['rot_mat_time_inv'] = rot_mat_time_inv
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ar[self.lda_subgrp]['n_reps'] = n_reps
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ar[self.lda_subgrp]['dim_reps'] = dim_reps
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ar[self.lda_subgrp]['T'] = T
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ar[self.lda_subgrp]['n_orbitals'] = n_orbitals
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ar[self.lda_subgrp]['proj_mat'] = proj_mat
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ar[self.lda_subgrp]['bz_weights'] = bz_weights
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ar[self.lda_subgrp]['hopping'] = hopping
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del ar
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# Symmetries are used,
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# Now do the symmetries for correlated orbitals:
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self.read_symmetry_input(orbits=corr_shells,symm_file=self.symm_file,symm_subgrp=self.symm_subgrp,SO=SO,SP=SP)
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def convert_parproj_input(self, par_proj_subgrp='SumK_LDA_ParProj', symm_par_subgrp='SymmPar'):
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"""
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Reads the input for the partial charges projectors from case.parproj, and stores it in the symm_par_subgrp
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group in the HDF5.
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"""
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if not (mpi.is_master_node()): return
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self.par_proj_subgrp = par_proj_subgrp
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self.symm_par_subgrp = symm_par_subgrp
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mpi.report("Reading parproj input from %s..."%self.parproj_file)
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dens_mat_below = [ [numpy.zeros([self.shells[ish][3],self.shells[ish][3]],numpy.complex_) for ish in range(self.n_shells)]
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for isp in range(self.n_spin_blocs) ]
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R = read_fortran_file(self.parproj_file)
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n_parproj = [int(R.next()) for i in range(self.n_shells)]
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n_parproj = numpy.array(n_parproj)
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# Initialise P, here a double list of matrices:
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proj_mat_pc = numpy.zeros([self.n_k,self.n_spin_blocs,self.n_shells,max(n_parproj),max(numpy.array(self.shells)[:,3]),max(self.n_orbitals)],numpy.complex_)
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rot_mat_all = [numpy.identity(self.shells[ish][3],numpy.complex_) for ish in xrange(self.n_shells)]
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rot_mat_all_time_inv = [0 for i in range(self.n_shells)]
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for ish in range(self.n_shells):
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# read first the projectors for this orbital:
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for ik in xrange(self.n_k):
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for ir in range(n_parproj[ish]):
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for isp in range(self.n_spin_blocs):
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for i in xrange(self.shells[ish][3]): # read real part:
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for j in xrange(self.n_orbitals[ik][isp]):
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proj_mat_pc[ik,isp,ish,ir,i,j] = R.next()
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for isp in range(self.n_spin_blocs):
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for i in xrange(self.shells[ish][3]): # read imaginary part:
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for j in xrange(self.n_orbitals[ik][isp]):
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proj_mat_pc[ik,isp,ish,ir,i,j] += 1j * R.next()
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# now read the Density Matrix for this orbital below the energy window:
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for isp in range(self.n_spin_blocs):
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for i in xrange(self.shells[ish][3]): # read real part:
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for j in xrange(self.shells[ish][3]):
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dens_mat_below[isp][ish][i,j] = R.next()
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for isp in range(self.n_spin_blocs):
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for i in xrange(self.shells[ish][3]): # read imaginary part:
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for j in xrange(self.shells[ish][3]):
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dens_mat_below[isp][ish][i,j] += 1j * R.next()
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if (self.SP==0): dens_mat_below[isp][ish] /= 2.0
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# Global -> local rotation matrix for this shell:
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for i in xrange(self.shells[ish][3]): # read real part:
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for j in xrange(self.shells[ish][3]):
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rot_mat_all[ish][i,j] = R.next()
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for i in xrange(self.shells[ish][3]): # read imaginary part:
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for j in xrange(self.shells[ish][3]):
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rot_mat_all[ish][i,j] += 1j * R.next()
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#print Dens_Mat_below[0][ish],Dens_Mat_below[1][ish]
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if (self.SP):
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rot_mat_all_time_inv[ish] = int(R.next())
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R.close()
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#-----------------------------------------
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# Store the input into HDF5:
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ar = HDFArchive(self.hdf_file,'a')
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if not (self.par_proj_subgrp in ar): ar.create_group(self.par_proj_subgrp)
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# The subgroup containing the data. If it does not exist, it is created.
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# If it exists, the data is overwritten!!!
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thingstowrite = ['dens_mat_below','n_parproj','proj_mat_pc','rot_mat_all','rot_mat_all_time_inv']
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for it in thingstowrite: exec "ar['%s']['%s'] = %s"%(self.par_proj_subgrp,it,it)
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del ar
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# Symmetries are used,
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# Now do the symmetries for all orbitals:
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self.read_symmetry_input(orbits=self.shells,symm_file=self.symmpar_file,symm_subgrp=self.symm_par_subgrp,SO=self.SO,SP=self.SP)
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def convert_bands_input(self, bands_subgrp = 'SumK_LDA_Bands'):
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"""
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Converts the input for momentum resolved spectral functions, and stores it in bands_subgrp in the
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HDF5.
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"""
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if not (mpi.is_master_node()): return
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self.bands_subgrp = bands_subgrp
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mpi.report("Reading bands input from %s..."%self.band_file)
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R = read_fortran_file(self.band_file)
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try:
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n_k = int(R.next())
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# read the list of n_orbitals for all k points
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n_orbitals = numpy.zeros([n_k,self.n_spin_blocs],numpy.int)
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for isp in range(self.n_spin_blocs):
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for ik in xrange(n_k):
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n_orbitals[ik,isp] = int(R.next())
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# Initialise the projectors:
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proj_mat = numpy.zeros([n_k,self.n_spin_blocs,self.n_corr_shells,max(numpy.array(self.corr_shells)[:,3]),max(n_orbitals)],numpy.complex_)
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# Read the projectors from the file:
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for ik in xrange(n_k):
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for icrsh in range(self.n_corr_shells):
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no = self.corr_shells[icrsh][3]
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# first Real part for BOTH spins, due to conventions in dmftproj:
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for isp in range(self.n_spin_blocs):
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for i in xrange(no):
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for j in xrange(n_orbitals[ik,isp]):
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proj_mat[ik,isp,icrsh,i,j] = R.next()
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# now Imag part:
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for isp in range(self.n_spin_blocs):
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for i in xrange(no):
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for j in xrange(n_orbitals[ik,isp]):
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proj_mat[ik,isp,icrsh,i,j] += 1j * R.next()
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hopping = numpy.zeros([n_k,self.n_spin_blocs,max(n_orbitals),max(n_orbitals)],numpy.complex_)
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# Grab the H
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# we use now the convention of a DIAGONAL Hamiltonian!!!!
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for isp in range(self.n_spin_blocs):
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for ik in xrange(n_k) :
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no = n_orbitals[ik,isp]
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for i in xrange(no):
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hopping[ik,isp,i,i] = R.next() * self.energy_unit
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# now read the partial projectors:
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n_parproj = [int(R.next()) for i in range(self.n_shells)]
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n_parproj = numpy.array(n_parproj)
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# Initialise P, here a double list of matrices:
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proj_mat_pc = numpy.zeros([n_k,self.n_spin_blocs,self.n_shells,max(n_parproj),max(numpy.array(self.shells)[:,3]),max(n_orbitals)],numpy.complex_)
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for ish in range(self.n_shells):
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for ik in xrange(n_k):
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for ir in range(n_parproj[ish]):
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for isp in range(self.n_spin_blocs):
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for i in xrange(self.shells[ish][3]): # read real part:
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for j in xrange(n_orbitals[ik,isp]):
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proj_mat_pc[ik,isp,ish,ir,i,j] = R.next()
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for i in xrange(self.shells[ish][3]): # read imaginary part:
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for j in xrange(n_orbitals[ik,isp]):
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proj_mat_pc[ik,isp,ish,ir,i,j] += 1j * R.next()
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except StopIteration : # a more explicit error if the file is corrupted.
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raise "Wien2k_converter : reading file band_file failed!"
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R.close()
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# reading done!
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#-----------------------------------------
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# Store the input into HDF5:
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ar = HDFArchive(self.hdf_file,'a')
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if not (self.bands_subgrp in ar): ar.create_group(self.bands_subgrp)
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# The subgroup containing the data. If it does not exist, it is created.
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# If it exists, the data is overwritten!!!
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thingstowrite = ['n_k','n_orbitals','proj_mat','hopping','n_parproj','proj_mat_pc']
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for it in thingstowrite: exec "ar['%s']['%s'] = %s"%(self.bands_subgrp,it,it)
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del ar
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def read_symmetry_input(self, orbits, symm_file, symm_subgrp, SO, SP):
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"""
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Reads input for the symmetrisations from symm_file, which is case.sympar or case.symqmc.
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"""
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if not (mpi.is_master_node()): return
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mpi.report("Reading symmetry input from %s..."%symm_file)
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n_orbits = len(orbits)
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R=read_fortran_file(symm_file)
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try:
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n_s = int(R.next()) # Number of symmetry operations
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n_atoms = int(R.next()) # number of atoms involved
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perm = [ [int(R.next()) for i in xrange(n_atoms)] for j in xrange(n_s) ] # list of permutations of the atoms
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if SP:
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time_inv = [ int(R.next()) for j in xrange(n_s) ] # timeinversion for SO xoupling
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else:
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time_inv = [ 0 for j in xrange(n_s) ]
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# Now read matrices:
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mat = []
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for in_s in xrange(n_s):
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mat.append( [ numpy.zeros([orbits[orb][3], orbits[orb][3]],numpy.complex_) for orb in xrange(n_orbits) ] )
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for orb in range(n_orbits):
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for i in xrange(orbits[orb][3]):
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for j in xrange(orbits[orb][3]):
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mat[in_s][orb][i,j] = R.next() # real part
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for i in xrange(orbits[orb][3]):
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for j in xrange(orbits[orb][3]):
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mat[in_s][orb][i,j] += 1j * R.next() # imaginary part
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# determine the inequivalent shells:
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#SHOULD BE FINALLY REMOVED, PUT IT FOR ALL ORBITALS!!!!! (PS: FIXME?)
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#self.inequiv_shells(orbits)
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mat_tinv = [numpy.identity(orbits[orb][3],numpy.complex_)
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for orb in range(n_orbits)]
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if ((SO==0) and (SP==0)):
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# here we need an additional time inversion operation, so read it:
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for orb in range(n_orbits):
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for i in xrange(orbits[orb][3]):
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for j in xrange(orbits[orb][3]):
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mat_tinv[orb][i,j] = R.next() # real part
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for i in xrange(orbits[orb][3]):
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for j in xrange(orbits[orb][3]):
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mat_tinv[orb][i,j] += 1j * R.next() # imaginary part
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except StopIteration : # a more explicit error if the file is corrupted.
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raise "Wien2k_converter : reading file symm_file failed!"
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R.close()
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# Save it to the HDF:
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ar=HDFArchive(self.hdf_file,'a')
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if not (symm_subgrp in ar): ar.create_group(symm_subgrp)
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thingstowrite = ['n_s','n_atoms','perm','orbits','SO','SP','time_inv','mat','mat_tinv']
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for it in thingstowrite: exec "ar['%s']['%s'] = %s"%(symm_subgrp,it,it)
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del ar
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def __repack(self):
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"""Calls the h5repack routine, in order to reduce the file size of the hdf5 archive.
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Should only be used BEFORE the first invokation of HDFArchive in the program, otherwise
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the hdf5 linking is broken!!!"""
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import subprocess
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if not (mpi.is_master_node()): return
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mpi.report("Repacking the file %s"%self.hdf_file)
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retcode = subprocess.call(["h5repack","-i%s"%self.hdf_file, "-otemphgfrt.h5"])
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if (retcode!=0):
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mpi.report("h5repack failed!")
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else:
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subprocess.call(["mv","-f","temphgfrt.h5","%s"%self.hdf_file])
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def inequiv_shells(self,lst):
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"""
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|
The number of inequivalent shells is calculated from lst, and a mapping is given as
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map(i_corr_shells) = i_inequiv_corr_shells
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invmap(i_inequiv_corr_shells) = i_corr_shells
|
|
in order to put the Self energies to all equivalent shells, and for extracting Gloc
|
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"""
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|
|
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tmp = []
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self.shellmap = [0 for i in range(len(lst))]
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self.invshellmap = [0]
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self.n_inequiv_corr_shells = 1
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tmp.append( lst[0][1:3] )
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|
|
if (len(lst)>1):
|
|
for i in range(len(lst)-1):
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|
|
fnd = False
|
|
for j in range(self.n_inequiv_corr_shells):
|
|
if (tmp[j]==lst[i+1][1:3]):
|
|
fnd = True
|
|
self.shellmap[i+1] = j
|
|
if (fnd==False):
|
|
self.shellmap[i+1] = self.n_inequiv_corr_shells
|
|
self.n_inequiv_corr_shells += 1
|
|
tmp.append( lst[i+1][1:3] )
|
|
self.invshellmap.append(i+1)
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