mirror of https://github.com/triqs/dft_tools
271 lines
14 KiB
Python
271 lines
14 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) 2014 by M. Betzinger, P. Seth
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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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from converter_tools import *
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class FleurConverter(ConverterTools):
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"""
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Conversion from Fleur output to an hdf5 file that can be used as input for the SumkDFT class.
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"""
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def __init__(self, filename, hdf_filename = None,
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dft_subgrp = 'dft_input', parproj_subgrp='dft_parproj_input',
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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, "Please provide the DFT files' base name as a string."
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if hdf_filename is None: hdf_filename = filename
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self.hdf_file = hdf_filename+'.h5'
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#self.dft_file = filename+'.ctqmcout'
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#self.parproj_file = filename+'.parproj'
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self.dft_file = 'ctqmcout'
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self.parproj_file = 'parproj'
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self.dft_subgrp = dft_subgrp
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self.parproj_subgrp = parproj_subgrp
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self.fortran_to_replace = {'D':'E'}
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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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ConverterTools.repack(self)
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def convert_dft_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.dft_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 = ConverterTools.read_fortran_file(self,self.dft_file,self.fortran_to_replace)
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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 = 0 # 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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# now read the information about the shells (atom, sort, l, dim):
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shell_entries = ['atom', 'sort', 'l', 'dim']
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shells = [ {name: int(val) for name, val in zip(shell_entries, R)} for ish in range(n_shells) ]
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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 (atom, sort, l, dim, SO flag, irep):
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corr_shell_entries = ['atom', 'sort', 'l', 'dim', 'SO', 'irep']
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corr_shells = [ {name: int(val) for name, val in zip(corr_shell_entries, R)} for icrsh in range(n_corr_shells) ]
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# determine the number of inequivalent correlated shells and maps, needed for further reading
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n_inequiv_shells, corr_to_inequiv, inequiv_to_corr = ConverterTools.det_shell_equivalence(self,corr_shells)
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use_rotations = 1
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rot_mat = [numpy.identity(corr_shells[icrsh]['dim'],numpy.complex_) for icrsh in range(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 range(n_corr_shells):
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for i in range(corr_shells[icrsh]['dim']): # read real part:
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for j in range(corr_shells[icrsh]['dim']):
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rot_mat[icrsh][i,j] = R.next()
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for i in range(corr_shells[icrsh]['dim']): # read imaginary part:
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for j in range(corr_shells[icrsh]['dim']):
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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(n_inequiv_shells)]
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dim_reps = [0 for i in range(n_inequiv_shells)]
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T = []
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for ish in range(n_inequiv_shells):
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n_reps[ish] = int(R.next()) # number of representatives ("subsets"), e.g. t2g and eg
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dim_reps[ish] = [int(R.next()) for i in range(n_reps[ish])] # 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[inequiv_to_corr[ish]]['l']+1
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lmax = ll * (corr_shells[inequiv_to_corr[ish]]['SO'] + 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 range(lmax):
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for j in range(lmax):
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T[ish][i,j] = R.next()
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for i in range(lmax):
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for j in range(lmax):
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T[ish][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 range(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([crsh['dim'] for crsh in corr_shells]),max(n_orbitals)],numpy.complex_)
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# Read the projectors from the file:
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for ik in range(n_k):
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for icrsh in range(n_corr_shells):
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n_orb = corr_shells[icrsh]['dim']
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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 range(n_orb):
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for j in range(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 range(n_orb):
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for j in range(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 range(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 -- convention for Fleur
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for isp in range(n_spin_blocs):
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for ik in range(n_k) :
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n_orb = n_orbitals[ik,isp]
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for i in range(n_orb):
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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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things_to_set = ['n_shells','shells','n_corr_shells','corr_shells','n_spin_blocs','n_orbitals','n_k','SO','SP','energy_unit']
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for it in things_to_set: setattr(self,it,locals()[it])
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except StopIteration : # a more explicit error if the file is corrupted.
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raise "Fleur_converter : reading file %s failed!"%filename
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R.close()
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# Reading done!
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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 (self.dft_subgrp in ar): ar.create_group(self.dft_subgrp)
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# The subgroup containing the data. If it does not exist, it is created. If it exists, the data is overwritten!
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things_to_save = ['energy_unit','n_k','k_dep_projection','SP','SO','charge_below','density_required',
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'symm_op','n_shells','shells','n_corr_shells','corr_shells','use_rotations','rot_mat',
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'rot_mat_time_inv','n_reps','dim_reps','T','n_orbitals','proj_mat','bz_weights','hopping',
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'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr']
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for it in things_to_save: ar[self.dft_subgrp][it] = locals()[it]
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del ar
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def convert_parproj_input(self):
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"""
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Reads the input for the partial charges projectors from case.parproj, and stores it in the symmpar_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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mpi.report("Reading parproj input from %s..."%self.parproj_file)
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dens_mat_below = [ [numpy.zeros([self.shells[ish]['dim'],self.shells[ish]['dim']],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 = ConverterTools.read_fortran_file(self,self.parproj_file,self.fortran_to_replace)
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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([sh['dim'] for sh in self.shells]),max(self.n_orbitals)],numpy.complex_)
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rot_mat_all = [numpy.identity(self.shells[ish]['dim'],numpy.complex_) for ish in range(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 range(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 range(self.shells[ish]['dim']): # read real part:
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for j in range(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 range(self.shells[ish]['dim']): # read imaginary part:
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for j in range(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 range(self.shells[ish]['dim']): # read real part:
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for j in range(self.shells[ish]['dim']):
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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 range(self.shells[ish]['dim']): # read imaginary part:
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for j in range(self.shells[ish]['dim']):
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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 range(self.shells[ish]['dim']): # read real part:
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for j in range(self.shells[ish]['dim']):
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rot_mat_all[ish][i,j] = R.next()
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for i in range(self.shells[ish]['dim']): # read imaginary part:
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for j in range(self.shells[ish]['dim']):
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rot_mat_all[ish][i,j] += 1j * R.next()
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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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# Reading done!
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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 (self.parproj_subgrp in ar): ar.create_group(self.parproj_subgrp)
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# The subgroup containing the data. If it does not exist, it is created. If it exists, the data is overwritten!
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things_to_save = ['dens_mat_below','n_parproj','proj_mat_pc','rot_mat_all','rot_mat_all_time_inv']
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for it in things_to_save: ar[self.parproj_subgrp][it] = locals()[it]
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del ar
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