dft_tools/python/converters/vasp_converter.py

################################################################################
#
# 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/>.
#
################################################################################

from types import *
import numpy
from pytriqs.archive import *
from pytriqs.applications.dft.converters.converter_tools import *
import os.path
try:
    import simplejson as json
except ImportError:
    import json
#from plotools import ProjectorGroup, ProjectorShell

class VaspConverter(ConverterTools):
    """
    Conversion from VASP output 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',
                       parproj_subgrp='dft_parproj_input', symmpar_subgrp='dft_symmpar_input',
                       bands_subgrp = 'dft_bands_input', misc_subgrp = 'dft_misc_input',
                       transp_subgrp = 'dft_transp_input', repacking = False):
        """
        Init of the class. Variable filename gives the root of all filenames, e.g. case.ctqmcout, case.h5, and so on. 
        """

        assert type(filename)==StringType, "Please provide the DFT files' base name as a string."
        if hdf_filename is None: hdf_filename = filename+'.h5'
        self.hdf_file = hdf_filename
        self.basename = filename
        self.ctrl_file = filename+'.ctrl'
#        self.pmat_file = filename+'.pmat'
        self.dft_subgrp = dft_subgrp
        self.symmcorr_subgrp = symmcorr_subgrp
        self.parproj_subgrp = parproj_subgrp
        self.symmpar_subgrp = symmpar_subgrp
        self.bands_subgrp = bands_subgrp
        self.misc_subgrp = misc_subgrp
        self.transp_subgrp = transp_subgrp

        # Checks if h5 file is there and repacks it if wanted:
        if (os.path.exists(self.hdf_file) and repacking):
            ConverterTools.repack(self)


    def read_data(self, fh):
        """
        Generator for reading plain data.
        """
        for line in fh:
            line_ = line.strip()
            if not line or (line_ == '' or line_[0] == '#'):
                continue

            for val in map(float, line.split()):
                yield val

    def read_header_and_data(self, filename):
        """
        Opens a file and returns a JSON-header and the generator for the plain data.
        """
        fh = open(filename, 'rt')
        header = ""
        for line in fh:
            if not "#END" in line:
                header += line
            else:
                break

        f_gen = self.read_data(fh)

        return header, f_gen

    def convert_dft_input(self):
        """
        Reads the input files, and stores the data in the HDFfile
        """
        energy_unit = 1.0 # VASP interface always uses eV
        k_dep_projection = 1
# Symmetries are switched off for the moment
# TODO: implement symmetries
        symm_op = 0                                   # Use symmetry groups for the k-sum

        # Read and write only on the master node
        if not (mpi.is_master_node()): return
        mpi.report("Reading input from %s..."%self.ctrl_file)

        # R is a generator : each R.Next() will return the next number in the file
        jheader, rf = self.read_header_and_data(self.ctrl_file)
        print jheader
        ctrl_head = json.loads(jheader)

        ng = ctrl_head['ngroups']
        n_k = ctrl_head['nk']
# Note the difference in name conventions!
        SP = ctrl_head['ns'] - 1
        SO = ctrl_head['nc_flag']

        kpts = numpy.zeros((n_k, 3))
        bz_weights = numpy.zeros(n_k)
        try:
            for ik in xrange(n_k):
                kx, ky, kz = rf.next(), rf.next(), rf.next()
                kpts[ik, :] = kx, ky, kz
                bz_weights[ik] = rf.next()
        except StopIteration:
            raise "VaspConverter: error reading %s"%self.ctrl_file

#        if nc_flag:
## TODO: check this
#            n_spin_blocs = 1
#        else:
#            n_spin_blocs = ns
        n_spin_blocs = SP + 1 - SO

# Read PLO groups
# First, we read everything into a temporary data structure
# TODO: think about multiple shell groups and how to map them on h5 structures
        assert ng == 1, "Only one group is allowed at the moment"

        try:
            for ig in xrange(ng):
                gr_file = self.basename + '.pg%i'%(ig + 1)
                jheader, rf = self.read_header_and_data(gr_file)
                gr_head = json.loads(jheader)

                e_win = gr_head['ewindow']
                nb_max = gr_head['nb_max']
                p_shells = gr_head['shells']
                density_required = gr_head['nelect']
                charge_below = 0.0 # This is not defined in VASP interface

# Note that in the DftTools convention each site gives a separate correlated shell!
                n_corr_shells = sum([len(sh['ion_list']) for sh in p_shells])

                corr_shells = []
                shion_to_corr_shell = [[] for ish in xrange(len(p_shells))]
                icsh = 0
                for ish, sh in enumerate(p_shells):
                    ion_list = sh['ion_list']
                    for i, ion in enumerate(ion_list):
                        pars = {}
                        pars['atom'] = ion
                        pars['sort'] = sh['ion_sort']
                        pars['l'] = sh['lorb']
                        pars['dim'] = sh['ndim']
                        pars['SO'] = SO
# TODO: check what 'irep' entry does (it seems to be very specific to dmftproj)
                        pars['irep'] = 0
                        corr_shells.append(pars)
                        shion_to_corr_shell[ish].append(i)

# TODO: generalize this to the case of multiple shell groups
                n_shells = n_corr_shells # No non-correlated shells at the moment
                shells = corr_shells

# FIXME: atomic sorts in Wien2K are not the same as in VASP.
#        A symmetry analysis from OUTCAR or symmetry file should be used
#        to define equivalence classes of sites.
            n_inequiv_shells, corr_to_inequiv, inequiv_to_corr = ConverterTools.det_shell_equivalence(self, corr_shells)

# NB!: these rotation matrices are specific to Wien2K! Set to identity in VASP
            use_rotations = 1
            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)]

# TODO: implement transformation matrices
            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):
                n_reps[ish] = 1   # Always 1 in VASP
                ineq_first = inequiv_to_corr[ish]
                dim_reps[ish] = [corr_shells[ineq_first]['dim']]   # Just the dimension of the shell
            
                # The transformation matrix:
                # is of dimension 2l+1 without SO, and 2*(2l+1) with SO!
                ll = 2 * corr_shells[inequiv_to_corr[ish]]['l']+1
                lmax = ll * (corr_shells[inequiv_to_corr[ish]]['SO'] + 1)
# TODO: at the moment put T-matrices to identities
                T.append(numpy.identity(lmax, numpy.complex_))
                
#            if nc_flag:
## TODO: implement the noncollinear part
#                raise NotImplementedError("Noncollinear calculations are not implemented")
#            else:
            hopping = numpy.zeros([n_k, n_spin_blocs, nb_max, nb_max], numpy.complex_)
            band_window = [numpy.zeros((n_k, 2), dtype=int) for isp in xrange(n_spin_blocs)]
            n_orbitals = numpy.zeros([n_k, n_spin_blocs], numpy.int)

            for isp in xrange(n_spin_blocs):
                for ik in xrange(n_k):
                    ib1, ib2 = int(rf.next()), int(rf.next())
                    band_window[isp][ik, :2] = ib1, ib2
                    nb = ib2 - ib1 + 1
                    n_orbitals[ik, isp] = nb
                    for ib in xrange(nb):
                        hopping[ik, isp, ib, ib] = rf.next()

# Projectors
            print n_orbitals
            print [crsh['dim'] for crsh in corr_shells]
            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_)

# TODO: implement reading from more than one projector group
# In 'dmftproj' each ion represents a separate correlated shell.
# In my interface a 'projected shell' includes sets of ions.
# How to reconcile this? Two options:
#
# 1. Redefine 'projected shell' in my interface to make it correspond to one site only.
#    In this case the list of ions must be defined at the level of the projector group.
#
# 2. Split my 'projected shell' to several 'correlated shells' here in the converter.
#
# At the moment I choose i.2 for its simplicity. But one should consider possible
# use cases and decide which solution is to be made permanent.
#
            for ish, sh in enumerate(p_shells):
                for isp in xrange(n_spin_blocs):
                    for ik in xrange(n_k):
                        for ion in xrange(len(sh['ion_list'])):
                            icsh = shion_to_corr_shell[ish][ion]
                            for ilm in xrange(sh['ndim']):
                                for ib in xrange(n_orbitals[ik, isp]):
                                    # This is to avoid confusion with the order of arguments
                                    pr = rf.next()
                                    pi = rf.next()
                                    proj_mat[ik, isp, icsh, ilm, ib] = complex(pr, pi)

            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:
                print "%s:"%(it), locals()[it]
                setattr(self,it,locals()[it])

        except StopIteration:
           raise "VaspConverter: error reading %s"%self.gr_file

        rf.close()

#
#        try:
#            energy_unit = R.next()                        # read the energy convertion factor
#            n_k = int(R.next())                           # read the number of k points
#            k_dep_projection = 1                          
#            SP = int(R.next())                            # flag for spin-polarised calculation
#            SO = int(R.next())                            # flag for spin-orbit calculation
#            charge_below = R.next()                       # total charge below energy window
#            density_required = R.next()                   # total density required, for setting the chemical potential
#            symm_op = 1                                   # Use symmetry groups for the k-sum
#
#            # the information on the non-correlated shells is not important here, maybe skip:
#            n_shells = int(R.next())                      # number of shells (e.g. Fe d, As p, O p) in the unit cell, 
#                                                          # 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) ]
#
#            n_corr_shells = int(R.next())                 # number of corr. shells (e.g. Fe d, Ce f) in the unit cell, 
#                                                          # 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 = 1
#            rot_mat = [numpy.identity(corr_shells[icrsh]['dim'],numpy.complex_) for icrsh in range(n_corr_shells)]
#           
#            # read the matrices
#            rot_mat_time_inv = [0 for i in range(n_corr_shells)]
#
#            for icrsh in range(n_corr_shells):
#                for i in range(corr_shells[icrsh]['dim']):    # read real part:
#                    for j in range(corr_shells[icrsh]['dim']):
#                        rot_mat[icrsh][i,j] = R.next()
#                for i in range(corr_shells[icrsh]['dim']):    # read imaginary part:
#                    for j in range(corr_shells[icrsh]['dim']):
#                        rot_mat[icrsh][i,j] += 1j * R.next()
#
#                if (SP==1):             # read time inversion flag:
#                    rot_mat_time_inv[icrsh] = int(R.next())
#                    
#            # Read here the info for the transformation of the basis:
#            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):
#                n_reps[ish] = int(R.next())   # number of representatives ("subsets"), e.g. t2g and eg
#                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 without SO, and 2*(2l+1) with SO!
#                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_))
#                
#                # now read it from file:
#                for i in range(lmax):
#                    for j in range(lmax):
#                        T[ish][i,j] = R.next()
#                for i in range(lmax):
#                    for j in range(lmax):
#                        T[ish][i,j] += 1j * R.next()
#    
#            # Spin blocks to be read:
#            n_spin_blocs = SP + 1 - SO   
#                 
#            # read the list of n_orbitals for all k points
#            n_orbitals = numpy.zeros([n_k,n_spin_blocs],numpy.int)
#            for isp in range(n_spin_blocs):
#                for ik in range(n_k):
#                    n_orbitals[ik,isp] = int(R.next())
#            
#            # Initialise the projectors:
#            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_)
#
#            # Read the projectors from the file:
#            for ik in range(n_k):
#                for icrsh in range(n_corr_shells):
#                    n_orb = corr_shells[icrsh]['dim']
#                    # first Real part for BOTH spins, due to conventions in dmftproj:
#                    for isp in range(n_spin_blocs):
#                        for i in range(n_orb):
#                            for j in range(n_orbitals[ik][isp]):
#                                proj_mat[ik,isp,icrsh,i,j] = R.next()
#                    # now Imag part:
#                    for isp in range(n_spin_blocs):
#                        for i in range(n_orb):
#                            for j in range(n_orbitals[ik][isp]):
#                                proj_mat[ik,isp,icrsh,i,j] += 1j * R.next()
#          
#            # now define the arrays for weights and hopping ...
#            bz_weights = numpy.ones([n_k],numpy.float_)/ float(n_k)  # w(k_index),  default normalisation 
#            hopping = numpy.zeros([n_k,n_spin_blocs,max(n_orbitals),max(n_orbitals)],numpy.complex_)
#
#            # 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
#            # we use now the convention of a DIAGONAL Hamiltonian -- convention for Wien2K.
#            for isp in range(n_spin_blocs):
#                for ik in range(n_k) :
#                    n_orb = n_orbitals[ik,isp]
#                    for i in range(n_orb):
#                        hopping[ik,isp,i,i] = R.next() * energy_unit
#            
#            # 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 "Wien2k_converter : reading file %s failed!"%filename
#
#        R.close()
#        # Reading done!
        
        # Save it to the HDF:
        ar = HDFArchive(self.hdf_file,'a')
        if not (self.dft_subgrp in ar): ar.create_group(self.dft_subgrp) 
        # The subgroup containing the data. If it does not exist, it is created. If it exists, the data is overwritten!
        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

        # Symmetries are used, so now convert symmetry information for *correlated* orbitals:
        self.convert_symmetry_input(ctrl_head, orbits=self.corr_shells, symm_subgrp=self.symmcorr_subgrp)
# TODO: Implement misc_input
#        self.convert_misc_input(bandwin_file=self.bandwin_file,struct_file=self.struct_file,outputs_file=self.outputs_file,
#                                misc_subgrp=self.misc_subgrp,SO=self.SO,SP=self.SP,n_k=self.n_k)


    def convert_parproj_input(self):
        """
        Reads the input for the partial charges projectors from case.parproj, and stores it in the symmpar_subgrp
        group in the HDF5.
        """

        if not (mpi.is_master_node()): return
        mpi.report("Reading input from %s..."%self.parproj_file)

        dens_mat_below = [ [numpy.zeros([self.shells[ish]['dim'],self.shells[ish]['dim']],numpy.complex_) for ish in range(self.n_shells)] 
                           for isp in range(self.n_spin_blocs) ]

        R = ConverterTools.read_fortran_file(self,self.parproj_file,self.fortran_to_replace)

        n_parproj = [int(R.next()) for i in range(self.n_shells)]
        n_parproj = numpy.array(n_parproj)
                
        # Initialise P, here a double list of matrices:
        proj_mat_all = 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_)
        
        rot_mat_all = [numpy.identity(self.shells[ish]['dim'],numpy.complex_) for ish in range(self.n_shells)]
        rot_mat_all_time_inv = [0 for i in range(self.n_shells)]

        for ish in range(self.n_shells):
            # read first the projectors for this orbital:
            for ik in range(self.n_k):
                for ir in range(n_parproj[ish]):

                    for isp in range(self.n_spin_blocs):
                        for i in range(self.shells[ish]['dim']):    # read real part:
                            for j in range(self.n_orbitals[ik][isp]):
                                proj_mat_all[ik,isp,ish,ir,i,j] = R.next()
                            
                    for isp in range(self.n_spin_blocs):
                        for i in range(self.shells[ish]['dim']):    # read imaginary part:
                            for j in range(self.n_orbitals[ik][isp]):
                                proj_mat_all[ik,isp,ish,ir,i,j] += 1j * R.next()
                                        
                    
            # now read the Density Matrix for this orbital below the energy window:
            for isp in range(self.n_spin_blocs):
                for i in range(self.shells[ish]['dim']):    # read real part:
                    for j in range(self.shells[ish]['dim']):
                        dens_mat_below[isp][ish][i,j] = R.next()
            for isp in range(self.n_spin_blocs):
                for i in range(self.shells[ish]['dim']):    # read imaginary part:
                    for j in range(self.shells[ish]['dim']):
                        dens_mat_below[isp][ish][i,j] += 1j * R.next()
                if (self.SP==0): dens_mat_below[isp][ish] /= 2.0

            # Global -> local rotation matrix for this shell:
            for i in range(self.shells[ish]['dim']):    # read real part:
                for j in range(self.shells[ish]['dim']):
                    rot_mat_all[ish][i,j] = R.next()
            for i in range(self.shells[ish]['dim']):    # read imaginary part:
                for j in range(self.shells[ish]['dim']):
                    rot_mat_all[ish][i,j] += 1j * R.next()
                    
            if (self.SP):
                rot_mat_all_time_inv[ish] = int(R.next())

        R.close()
        # Reading done!

        # Save it to the HDF:
        ar = HDFArchive(self.hdf_file,'a')
        if not (self.parproj_subgrp in ar): ar.create_group(self.parproj_subgrp) 
        # The subgroup containing the data. If it does not exist, it is created. If it exists, the data is overwritten!
        things_to_save = ['dens_mat_below','n_parproj','proj_mat_all','rot_mat_all','rot_mat_all_time_inv']
        for it in things_to_save: ar[self.parproj_subgrp][it] = locals()[it]
        del ar

        # Symmetries are used, so now convert symmetry information for *all* orbitals:
        self.convert_symmetry_input(orbits=self.shells,symm_file=self.symmpar_file,symm_subgrp=self.symmpar_subgrp,SO=self.SO,SP=self.SP)


    def convert_bands_input(self):
        """
        Converts the input for momentum resolved spectral functions, and stores it in bands_subgrp in the
        HDF5.
        """

        if not (mpi.is_master_node()): return
        mpi.report("Reading bands input from %s..."%self.band_file)

        R = ConverterTools.read_fortran_file(self,self.band_file,self.fortran_to_replace)
        try:
            n_k = int(R.next())

            # read the list of n_orbitals for all k points
            n_orbitals = numpy.zeros([n_k,self.n_spin_blocs],numpy.int)
            for isp in range(self.n_spin_blocs):
                for ik in range(n_k):
                    n_orbitals[ik,isp] = int(R.next())

            # Initialise the projectors:
            proj_mat = numpy.zeros([n_k,self.n_spin_blocs,self.n_corr_shells,max([crsh['dim'] for crsh in self.corr_shells]),max(n_orbitals)],numpy.complex_)

            # Read the projectors from the file:
            for ik in range(n_k):
                for icrsh in range(self.n_corr_shells):
                    n_orb = self.corr_shells[icrsh]['dim']
                    # first Real part for BOTH spins, due to conventions in dmftproj:
                    for isp in range(self.n_spin_blocs):
                        for i in range(n_orb):
                            for j in range(n_orbitals[ik,isp]):
                                proj_mat[ik,isp,icrsh,i,j] = R.next()
                    # now Imag part:
                    for isp in range(self.n_spin_blocs):
                        for i in range(n_orb):
                            for j in range(n_orbitals[ik,isp]):
                                proj_mat[ik,isp,icrsh,i,j] += 1j * R.next()

            hopping = numpy.zeros([n_k,self.n_spin_blocs,max(n_orbitals),max(n_orbitals)],numpy.complex_)

            # Grab the H
            # we use now the convention of a DIAGONAL Hamiltonian!!!!
            for isp in range(self.n_spin_blocs):
                for ik in range(n_k) :
                    n_orb = n_orbitals[ik,isp]
                    for i in range(n_orb):
                        hopping[ik,isp,i,i] = R.next() * self.energy_unit

            # now read the partial projectors:
            n_parproj = [int(R.next()) for i in range(self.n_shells)]
            n_parproj = numpy.array(n_parproj)
            
            # Initialise P, here a double list of matrices:
            proj_mat_all = numpy.zeros([n_k,self.n_spin_blocs,self.n_shells,max(n_parproj),max([sh['dim'] for sh in self.shells]),max(n_orbitals)],numpy.complex_)

            for ish in range(self.n_shells):
                for ik in range(n_k):
                    for ir in range(n_parproj[ish]):
                        for isp in range(self.n_spin_blocs):
                                    
                            for i in range(self.shells[ish]['dim']):    # read real part:
                                for j in range(n_orbitals[ik,isp]):
                                    proj_mat_all[ik,isp,ish,ir,i,j] = R.next()
                            
                            for i in range(self.shells[ish]['dim']):    # read imaginary part:
                                for j in range(n_orbitals[ik,isp]):
                                    proj_mat_all[ik,isp,ish,ir,i,j] += 1j * R.next()

        except StopIteration : # a more explicit error if the file is corrupted.
            raise "Wien2k_converter : reading file band_file failed!"

        R.close()
        # Reading done!

        # Save it to the HDF:
        ar = HDFArchive(self.hdf_file,'a')
        if not (self.bands_subgrp in ar): ar.create_group(self.bands_subgrp)
        # The subgroup containing the data. If it does not exist, it is created. If it exists, the data is overwritten!
        things_to_save = ['n_k','n_orbitals','proj_mat','hopping','n_parproj','proj_mat_all']
        for it in things_to_save: ar[self.bands_subgrp][it] = locals()[it]
        del ar


    def convert_misc_input(self, bandwin_file, struct_file, outputs_file, misc_subgrp, SO, SP, n_k):
        """
        Reads input for the band window from bandwin_file, which is case.oubwin,
                            structure from struct_file, which is case.struct,
                            symmetries from outputs_file, which is case.outputs.
        """

        if not (mpi.is_master_node()): return
        things_to_save = []

        # Read relevant data from .oubwin/up/dn files
        #############################################
        # band_window: Contains the index of the lowest and highest band within the
        #              projected subspace (used by dmftproj) for each k-point.

        if (SP == 0 or SO == 1):
            files = [self.bandwin_file]
        elif SP == 1:
            files = [self.bandwin_file+'up', self.bandwin_file+'dn']
        else: # SO and SP can't both be 1
            assert 0, "convert_transport_input: Reding oubwin error! Check SP and SO!"
        
        band_window = [numpy.zeros((n_k, 2), dtype=int) for isp in range(SP + 1 - SO)]
        for isp, f in enumerate(files):
            if os.path.exists(f):
                mpi.report("Reading input from %s..."%f)
                R = ConverterTools.read_fortran_file(self, f, self.fortran_to_replace)
                assert int(R.next()) == n_k, "convert_misc_input: Number of k-points is inconsistent in oubwin file!"
                assert int(R.next()) == SO, "convert_misc_input: SO is inconsistent in oubwin file!"
                for ik in xrange(n_k):
                    R.next()
                    band_window[isp][ik,0] = R.next() # lowest band
                    band_window[isp][ik,1] = R.next() # highest band
                    R.next()
                things_to_save.append('band_window')

        R.close() # Reading done!

        # Read relevant data from .struct file
        ######################################
        # lattice_type: bravais lattice type as defined by Wien2k
        # lattice_constants: unit cell parameters in a. u.
        # lattice_angles: unit cell angles in rad

        if (os.path.exists(self.struct_file)):
            mpi.report("Reading input from %s..."%self.struct_file)
        
            with open(self.struct_file) as R:
                try:
                    R.readline()
                    lattice_type = R.readline().split()[0]
                    R.readline()
                    temp = R.readline()
                    print temp
                    lattice_constants = numpy.array([float(temp[0+10*i:10+10*i].strip()) for i in range(3)])
                    lattice_angles = numpy.array([float(temp[30+10*i:40+10*i].strip()) for i in range(3)]) * numpy.pi / 180.0
                    things_to_save.extend(['lattice_type', 'lattice_constants', 'lattice_angles'])
                except IOError:
                    raise "convert_misc_input: reading file %s failed" %self.struct_file

        # Read relevant data from .outputs file
        #######################################
        # rot_symmetries: matrix representation of all (space group) symmetry operations
        
        if (os.path.exists(self.outputs_file)):
            mpi.report("Reading input from %s..."%self.outputs_file)
        
            rot_symmetries = []
            with open(self.outputs_file) as R:
                try:
                    while 1:
                        temp = R.readline().strip(' ').split()
                        if (temp[0] =='PGBSYM:'):
                            n_symmetries = int(temp[-1])
                            break
                    for i in range(n_symmetries):
                        while 1:
                            if (R.readline().strip().split()[0] == 'Symmetry'): break
                        sym_i = numpy.zeros((3, 3), dtype = float)
                        for ir in range(3):
                            temp = R.readline().strip().split()
                            for ic in range(3):
                                sym_i[ir, ic] = float(temp[ic])
                        R.readline()
                        rot_symmetries.append(sym_i)
                    things_to_save.extend(['n_symmetries', 'rot_symmetries'])
                    things_to_save.append('rot_symmetries')
                except IOError:
                    raise "convert_misc_input: reading file %s failed" %self.outputs_file

        # Save it to the HDF:
        ar=HDFArchive(self.hdf_file,'a')
        if not (misc_subgrp in ar): ar.create_group(misc_subgrp)
        for it in things_to_save: ar[misc_subgrp][it] = locals()[it]
        del ar


    def convert_transport_input(self):
        """ 
        Reads the input files necessary for transport calculations
        and stores the data in the HDFfile
        """
        if not (mpi.is_master_node()): return
        
        # Check if SP, SO and n_k are already in h5
        ar = HDFArchive(self.hdf_file, 'a')
        if not (self.dft_subgrp in ar): raise IOError, "convert_transport_input: No %s subgroup in hdf file found! Call convert_dmft_input first." %self.dft_subgrp
        SP = ar[self.dft_subgrp]['SP']
        SO = ar[self.dft_subgrp]['SO']
        n_k = ar[self.dft_subgrp]['n_k']
        del ar

        # Read relevant data from .pmat/up/dn files
        ###########################################
        # band_window_optics: Contains the index of the lowest and highest band within the
        #                     band window (used by optics) for each k-point.
        # velocities_k: velocity (momentum) matrix elements between all bands in band_window_optics
        #               and each k-point.

        if (SP == 0 or SO == 1):
            files = [self.pmat_file]
        elif SP == 1:
            files = [self.pmat_file+'up', self.pmat_file+'dn']
        else: # SO and SP can't both be 1
            assert 0, "convert_transport_input: Reading velocity file error! Check SP and SO!"

        velocities_k = [[] for f in files]
        band_window_optics = []
        for isp, f in enumerate(files):
            if not os.path.exists(f) : raise IOError, "convert_transport_input: File %s does not exist" %f
            mpi.report("Reading input from %s..."%f)

            R = ConverterTools.read_fortran_file(self, f, {'D':'E','(':'',')':'',',':' '})
            band_window_optics_isp = []
            for ik in xrange(n_k):
                R.next()
                nu1 = int(R.next())
                nu2 = int(R.next())
                band_window_optics_isp.append((nu1, nu2))
                n_bands = nu2 - nu1 + 1
                for _ in range(4): R.next()
                if n_bands <= 0:
                    velocity_xyz = numpy.zeros((1, 1, 3), dtype = complex)
                else:
                    velocity_xyz = numpy.zeros((n_bands, n_bands, 3), dtype = complex)
                    for nu_i in range(n_bands):
                        for nu_j in range(nu_i, n_bands):
                            for i in range(3):
                                velocity_xyz[nu_i][nu_j][i] = R.next() + R.next()*1j
                                if (nu_i != nu_j): velocity_xyz[nu_j][nu_i][i] = velocity_xyz[nu_i][nu_j][i].conjugate()
                velocities_k[isp].append(velocity_xyz)
            band_window_optics.append(numpy.array(band_window_optics_isp))
            R.close() # Reading done!

        # Put data to HDF5 file
        ar = HDFArchive(self.hdf_file, 'a')
        if not (self.transp_subgrp in ar): ar.create_group(self.transp_subgrp)
        # The subgroup containing the data. If it does not exist, it is created. If it exists, the data is overwritten!!!
        things_to_save = ['band_window_optics', 'velocities_k']
        for it in things_to_save: ar[self.transp_subgrp][it] = locals()[it]
        del ar

    def convert_symmetry_input(self, ctrl_head, orbits, symm_subgrp):
        """
        Reads input for the symmetrisations from symm_file, which is case.sympar or case.symqmc.
        """

# In VASP interface the symmetries are read directly from *.ctrl file
# For the moment the symmetry parameters are just stubs
        n_symm = 0
        n_atoms = 1
        perm = [0]
        n_orbits = len(orbits)
        SP = ctrl_head['ns']
        SO = ctrl_head['nc_flag']
        time_inv = [0]
        mat = [numpy.identity(1)]
        mat_tinv = [numpy.identity(1)]
#        if not (mpi.is_master_node()): return
#        mpi.report("Reading input from %s..."%symm_file)
#
#        n_orbits = len(orbits)
#
#        R = ConverterTools.read_fortran_file(self,symm_file,self.fortran_to_replace)
#
#        try:
#            n_symm = int(R.next())           # Number of symmetry operations
#            n_atoms = int(R.next())       # number of atoms involved
#            perm = [ [int(R.next()) for i in range(n_atoms)] for j in range(n_symm) ]    # list of permutations of the atoms
#            if SP: 
#                time_inv = [ int(R.next()) for j in range(n_symm) ]           # time inversion for SO coupling
#            else:
#                time_inv = [ 0 for j in range(n_symm) ]
#
#            # Now read matrices:
#            mat = []  
#            for i_symm in range(n_symm):
#                
#                mat.append( [ numpy.zeros([orbits[orb]['dim'], orbits[orb]['dim']],numpy.complex_) for orb in range(n_orbits) ] )
#                for orb in range(n_orbits):
#                    for i in range(orbits[orb]['dim']):
#                        for j in range(orbits[orb]['dim']):
#                            mat[i_symm][orb][i,j] = R.next()            # real part
#                    for i in range(orbits[orb]['dim']):
#                        for j in range(orbits[orb]['dim']):
#                            mat[i_symm][orb][i,j] += 1j * R.next()      # imaginary part
#
#            mat_tinv = [numpy.identity(orbits[orb]['dim'],numpy.complex_)
#                        for orb in range(n_orbits)]
#
#            if ((SO==0) and (SP==0)):
#                # here we need an additional time inversion operation, so read it:
#                for orb in range(n_orbits):
#                    for i in range(orbits[orb]['dim']):
#                        for j in range(orbits[orb]['dim']):
#                            mat_tinv[orb][i,j] = R.next()            # real part
#                    for i in range(orbits[orb]['dim']):
#                        for j in range(orbits[orb]['dim']):
#                            mat_tinv[orb][i,j] += 1j * R.next()      # imaginary part


        # Save it to the HDF:
        ar=HDFArchive(self.hdf_file,'a')
        if not (symm_subgrp in ar): ar.create_group(symm_subgrp)
        things_to_save = ['n_symm','n_atoms','perm','orbits','SO','SP','time_inv','mat','mat_tinv']
        for it in things_to_save:
            print "%s:"%(it), locals()[it]
            ar[symm_subgrp][it] = locals()[it]
        del ar