mirror of
https://github.com/triqs/dft_tools
synced 2024-12-21 20:03:41 +01:00
[wannier] few minor tidying changes while reading through
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@ -1,5 +1,5 @@
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################################################################################
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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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@ -18,7 +18,7 @@
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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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##########################################################################
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###
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# Wannier90 to HDF5 converter for the SumkDFT class of dfttools/TRIQS;
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@ -49,8 +49,10 @@ import numpy
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import math
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from pytriqs.archive import *
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from converter_tools import *
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from itertools import product
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import os.path
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class Wannier90Converter(ConverterTools):
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"""
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Conversion from Wannier90 output to an hdf5 file that can be used as input for the SumkDFT class.
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@ -77,10 +79,13 @@ class Wannier90Converter(ConverterTools):
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"""
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self._name = "Wannier90Converter"
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assert type(seedname)==StringType, self._name + ": Please provide the DFT files' base name as a string."
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if hdf_filename is None: hdf_filename = seedname+'.h5'
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assert type(seedname) == StringType, self._name + \
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": Please provide the DFT files' base name as a string."
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if hdf_filename is None:
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hdf_filename = seedname + '.h5'
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self.hdf_file = hdf_filename
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# if the w90 output is seedname_hr.dat, the input file for the converter must be called seedname.inp
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# if the w90 output is seedname_hr.dat, the input file for the
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# converter must be called seedname.inp
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self.inp_file = seedname + '.inp'
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self.w90_seed = seedname
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self.dft_subgrp = dft_subgrp
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@ -93,7 +98,6 @@ class Wannier90Converter(ConverterTools):
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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 appropriate files and stores the data for the
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@ -106,41 +110,50 @@ class Wannier90Converter(ConverterTools):
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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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if not (mpi.is_master_node()):
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return
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mpi.report("Reading input from %s..." % self.inp_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.inp_file,self.fortran_to_replace)
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R = ConverterTools.read_fortran_file(
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self, self.inp_file, self.fortran_to_replace)
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shell_entries = ['atom', 'sort', 'l', 'dim']
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corr_shell_entries = ['atom', 'sort', 'l', 'dim', 'SO', 'irep']
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# First, let's read the input file with the parameters needed for the conversion
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try:
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kmesh_mode = int(R.next()) # read k-point mesh generation option
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# read k - point mesh generation option
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kmesh_mode = int(R.next())
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if kmesh_mode >= 0:
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# read k-point mesh size from input
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nki = [int(R.next()) for idir in range(3)]
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else:
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# some default grid, if everything else fails...
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nki = [8, 8, 8]
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density_required = float(R.next()) # read the total number of electrons per cell
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# read the total number of electrons per cell
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density_required = float(R.next())
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# we do not read shells, because we have no additional shells beyond correlated ones,
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# and the data will be copied from corr_shells into shells (see below)
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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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# number of corr. shells (e.g. Fe d, Ce f) in the unit cell,
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n_corr_shells = int(R.next())
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# now read the information about the correlated shells (atom, sort, l, dim, SO flag, 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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corr_shells = [{name: int(val) for name, val in zip(
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corr_shell_entries, R)} for icrsh in range(n_corr_shells)]
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except StopIteration: # a more explicit error if the file is corrupted.
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mpi.report(self._name + ": reading input file %s failed!"%self.inp_file)
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mpi.report(self._name + ": reading input file %s failed!" %
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self.inp_file)
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# close the input file
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R.close()
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# Set or derive some quantities
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symm_op = 0 # Wannier90 does not use symmetries to reduce the k-points
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# Wannier90 does not use symmetries to reduce the k-points
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# the following might change in future versions
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### copy corr_shells into shells (see above)
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symm_op = 0
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# copy corr_shells into shells (see above)
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n_shells = n_corr_shells
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shells = []
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for ish in range(n_shells):
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shells.append({key: corr_shells[ish].get(key,None) for key in shell_entries})
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shells.append({key: corr_shells[ish].get(
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key, None) for key in shell_entries})
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###
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SP = 0 # NO spin-polarised calculations for now
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SO = 0 # NO spin-orbit calculation for now
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@ -150,13 +163,16 @@ class Wannier90Converter(ConverterTools):
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# this is more general
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n_spin = SP + 1 - SO
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dim_corr_shells = sum([sh['dim'] for sh in corr_shells])
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mpi.report("Total number of WFs expected in the correlated shells: %d"%dim_corr_shells)
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mpi.report(
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"Total number of WFs expected in the correlated shells: %d" % dim_corr_shells)
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# determine the number of inequivalent correlated shells and maps, needed for further processing
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n_inequiv_shells, corr_to_inequiv, inequiv_to_corr = ConverterTools.det_shell_equivalence(self,corr_shells)
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n_inequiv_shells, corr_to_inequiv, inequiv_to_corr = ConverterTools.det_shell_equivalence(
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self, corr_shells)
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mpi.report("Number of inequivalent shells: %d" % n_inequiv_shells)
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mpi.report("Shell representatives: " + format(inequiv_to_corr))
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shells_map = [inequiv_to_corr[corr_to_inequiv[ish]] for ish in range(n_corr_shells)]
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shells_map = [inequiv_to_corr[corr_to_inequiv[ish]]
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for ish in range(n_corr_shells)]
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mpi.report("Mapping: " + format(shells_map))
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# build the k-point mesh, if its size was given on input (kmesh_mode >= 0),
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@ -175,26 +191,26 @@ class Wannier90Converter(ConverterTools):
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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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spin_w90name = ['_up', '_down']
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hamr_full = []
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# TODO: generalise to SP=1 (only partially done)
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rot_mat_time_inv = [0 for i in range(n_corr_shells)]
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# Second, let's read the file containing the Hamiltonian in WF basis produced by Wannier90
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for isp in range(n_spin):
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### begin loop on isp
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# begin loop on isp
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# build filename according to wannier90 conventions
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if SP == 1:
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mpi.report("Reading information for spin component n. %d"%isp)
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mpi.report(
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"Reading information for spin component n. %d" % isp)
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hr_file = self.w90_seed + spin_w90name[isp] + '_hr.dat'
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else:
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hr_file = self.w90_seed + '_hr.dat'
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# now grab the data from the H(R) file
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mpi.report("The Hamiltonian in MLWF basis is extracted from %s ..."%hr_file)
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mpi.report(
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"The Hamiltonian in MLWF basis is extracted from %s ..." % hr_file)
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nr, rvec, rdeg, nw, hamr = self.read_wannier90hr(hr_file)
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# number of R vectors, their indices, their degeneracy, number of WFs, H(R)
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mpi.report("... done: %d R vectors, %d WFs found" % (nr, nw))
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@ -230,15 +246,18 @@ class Wannier90Converter(ConverterTools):
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mpi.report("Number of WFs equal to number of correlated orbitals")
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# we assume spin up and spin down always have same total number of WFs
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n_orbitals = numpy.ones([self.n_k,n_spin],numpy.int)*self.nwfs
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n_orbitals = numpy.ones(
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[self.n_k, n_spin], numpy.int) * self.nwfs
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else:
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# consistency check between the _up and _down file contents
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if nr != self.nrpt: mpi.report("Different number of R vectors for spin-up/spin-down!")
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if nw != self.nwfs: mpi.report("Different number of WFs for spin-up/spin-down!")
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if nr != self.nrpt:
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mpi.report("Different number of R vectors for spin-up/spin-down!")
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if nw != self.nwfs:
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mpi.report("Different number of WFs for spin-up/spin-down!")
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hamr_full.append(hamr)
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##FIXME: when do we actually need deepcopy()?
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# FIXME: when do we actually need deepcopy()?
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# hamr_full.append(deepcopy(hamr))
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for ir in range(nr):
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@ -265,18 +284,18 @@ class Wannier90Converter(ConverterTools):
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for icrsh in range(n_corr_shells):
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if not numpy.allclose(rot_mat_[icrsh], rot_mat[icrsh], atol=self._w90zero, rtol=1.e-15):
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mpi.report("Rotations for spin component n. %d do not match!" % isp)
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### end loop on isp
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# end loop on isp
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mpi.report("The k-point grid has dimensions: %d, %d, %d" % tuple(nki))
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# if calculations are spin-polarized, then renormalize k-point weights
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if SP == 1: bz_weights = 0.5 * bz_weights
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if SP == 1:
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bz_weights = 0.5 * bz_weights
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# Third, compute the hoppings in reciprocal space
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hopping = numpy.zeros([self.n_k, n_spin, numpy.max(n_orbitals), numpy.max(n_orbitals)], numpy.complex_)
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for isp in range(n_spin):
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# make Fourier transform H(R) -> H(k) : it can be done one spin at a time
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hamk = self.fourierham(self.nwfs, hamr_full[isp])
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hamk = self.fourier_ham(self.nwfs, hamr_full[isp])
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# copy the H(k) in the right place of hoppings... is there a better way to do this??
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for ik in range(self.n_k):
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#hopping[ik,isp,:,:] = deepcopy(hamk[ik][:,:])*energy_unit
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@ -284,7 +303,8 @@ class Wannier90Converter(ConverterTools):
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# Then, initialise the projectors
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k_dep_projection = 0 # we always have the same number of WFs at each k-point
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proj_mat = numpy.zeros([self.n_k,n_spin,n_corr_shells,max([crsh['dim'] for crsh in corr_shells]),numpy.max(n_orbitals)],numpy.complex_)
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proj_mat = numpy.zeros([self.n_k, n_spin, n_corr_shells, max(
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[crsh['dim'] for crsh in corr_shells]), numpy.max(n_orbitals)], numpy.complex_)
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iorb = 0
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# Projectors simply consist in identity matrix blocks selecting those MLWFs that
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# correspond to the specific correlated shell indexed by icrsh.
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@ -292,22 +312,23 @@ class Wannier90Converter(ConverterTools):
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# file and that the ordering of MLWFs matches the corr_shell info from the input.
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for icrsh in range(n_corr_shells):
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norb = corr_shells[icrsh]['dim']
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proj_mat[:,:,icrsh,0:norb,iorb:iorb+norb] = numpy.identity(norb,numpy.complex_)
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proj_mat[:, :, icrsh, 0:norb, iorb:iorb +
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norb] = numpy.identity(norb, numpy.complex_)
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iorb += norb
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# Finally, save all required data into the HDF archive:
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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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if not (self.dft_subgrp in ar):
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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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for it in things_to_save:
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ar[self.dft_subgrp][it] = locals()[it]
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del ar
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def read_wannier90hr(self, hr_filename="wannier_hr.dat"):
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"""
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Method for reading the seedname_hr.dat file produced by Wannier90 (http://wannier.org)
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@ -333,7 +354,8 @@ class Wannier90Converter(ConverterTools):
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"""
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# Read only from the master node
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if not (mpi.is_master_node()): return
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if not (mpi.is_master_node()):
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return
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try:
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with open(hr_filename, "r") as hr_filedesc:
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@ -345,7 +367,8 @@ class Wannier90Converter(ConverterTools):
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mpi.report("Reading %s..." % hr_filename + hr_data[0])
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try:
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num_wf = int(hr_data[1]) # reads number of Wannier functions per spin
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# reads number of Wannier functions per spin
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num_wf = int(hr_data[1])
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nrpt = int(hr_data[2])
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except ValueError:
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mpi.report("Could not read number of WFs or R vectors")
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@ -353,7 +376,8 @@ class Wannier90Converter(ConverterTools):
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# allocate arrays to save the R vector indexes and degeneracies and the Hamiltonian
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rvec_idx = numpy.zeros((nrpt, 3), dtype=int)
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rvec_deg = numpy.zeros(nrpt, dtype=int)
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h_of_r = [numpy.zeros((num_wf, num_wf), dtype=numpy.complex_) for n in range(nrpt)]
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h_of_r = [numpy.zeros((num_wf, num_wf), dtype=numpy.complex_)
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for n in range(nrpt)]
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# variable currpos points to the current line in the file
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currpos = 2
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@ -367,25 +391,26 @@ class Wannier90Converter(ConverterTools):
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raise IndexError("wrong number of R vectors??")
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rvec_deg[ir] = int(x)
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ir += 1
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# for each direct lattice vector R
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for ir in range(nrpt):
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# read the block of the Hamiltonian H(R)
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for jj in range(num_wf):
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for ii in range(num_wf):
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# for each direct lattice vector R read the block of the
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# Hamiltonian H(R)
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for ir, jj, ii in product(range(nrpt), range(num_wf), range(num_wf)):
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# advance one line, split the line into tokens
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currpos += 1
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cline = hr_data[currpos].split()
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# check if the orbital indexes in the file make sense
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if int(cline[3]) != ii + 1 or int(cline[4]) != jj + 1:
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mpi.report("Inconsistent indices at %s%s of R n. %s"%(ii,jj,ir))
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rcurr = numpy.array([int(cline[0]), int(cline[1]), int(cline[2])])
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mpi.report(
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"Inconsistent indices at %s%s of R n. %s" % (ii, jj, ir))
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rcurr = numpy.array(
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[int(cline[0]), int(cline[1]), int(cline[2])])
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if ii == 0 and jj == 0:
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rvec_idx[ir] = rcurr
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rprec = rcurr
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else:
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# check if the vector indices are consistent
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if not numpy.array_equal(rcurr, rprec):
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mpi.report("Inconsistent indices for R vector n. %s"%ir)
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mpi.report(
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"Inconsistent indices for R vector n. %s" % ir)
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# fill h_of_r with the matrix elements of the Hamiltonian
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h_of_r[ir][ii, jj] = complex(float(cline[5]), float(cline[6]))
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@ -396,8 +421,6 @@ class Wannier90Converter(ConverterTools):
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# return the data into variables
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return nrpt, rvec_idx, rvec_deg, num_wf, h_of_r
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def find_rot_mat(self, n_sh, sh_lst, sh_map, ham0):
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"""
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Method for finding the matrices that bring from local to global coordinate systems
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@ -424,12 +447,14 @@ class Wannier90Converter(ConverterTools):
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"""
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# initialize the rotation matrices to identities
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rot_mat = [numpy.identity(sh_lst[ish]['dim'], dtype=complex) for ish in range(n_sh)]
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rot_mat = [numpy.identity(sh_lst[ish]['dim'], dtype=complex)
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for ish in range(n_sh)]
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istatus = 0
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hs = ham0.shape
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if hs[0] != hs[1] or hs[0] != sum([sh['dim'] for sh in sh_lst]):
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mpi.report("find_rot_mat: wrong block structure of input Hamiltonian!")
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mpi.report(
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"find_rot_mat: wrong block structure of input Hamiltonian!")
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istatus = 0
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# this error will lead into troubles later... early return
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return istatus, rot_mat
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@ -443,7 +468,8 @@ class Wannier90Converter(ConverterTools):
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# nw = number of orbitals in this shell
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nw = sh_lst[ish]["dim"]
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# diagonalize the sub-block of H(0) corresponding to this shell
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eigval, eigvec = numpy.linalg.eigh(ham0[iwf:iwf+nw, iwf:iwf+nw])
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eigval, eigvec = numpy.linalg.eigh(
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ham0[iwf:iwf + nw, iwf:iwf + nw])
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# find the indices sorting the eigenvalues in ascending order
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eigsrt = eigval[0:nw].argsort()
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# order eigenvalues and eigenvectors and save in a list
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@ -460,15 +486,20 @@ class Wannier90Converter(ConverterTools):
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for ish in range(n_sh):
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try:
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# build rotation matrices by combining the unitary transformations that diagonalize H(0)
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rot_mat[ish] = numpy.dot(eigvec_lst[ish],eigvec_lst[sh_map[ish]].conjugate().transpose())
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# build rotation matrices by combining the unitary
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# transformations that diagonalize H(0)
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rot_mat[ish] = numpy.dot(eigvec_lst[ish], eigvec_lst[
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sh_map[ish]].conjugate().transpose())
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except ValueError:
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mpi.report("Global-to-local rotation matrices cannot be constructed!")
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mpi.report(
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"Global-to-local rotation matrices cannot be constructed!")
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istatus = 1
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# check that eigenvalues are the same (within accuracy) for equivalent shells
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||||
# check that eigenvalues are the same (within accuracy) for
|
||||
# equivalent shells
|
||||
if not numpy.allclose(eigval_lst[ish], eigval_lst[sh_map[ish]], atol=self._w90zero, rtol=1.e-15):
|
||||
mpi.report("ERROR: eigenvalue mismatch between equivalent shells! %d"%ish)
|
||||
mpi.report(
|
||||
"ERROR: eigenvalue mismatch between equivalent shells! %d" % ish)
|
||||
eigval_diff = eigval_lst[ish] - eigval_lst[sh_map[ish]]
|
||||
mpi.report("Eigenvalue difference: " + format(eigval_diff))
|
||||
istatus = 0
|
||||
@ -477,8 +508,6 @@ class Wannier90Converter(ConverterTools):
|
||||
|
||||
return istatus, rot_mat
|
||||
|
||||
|
||||
|
||||
def kmesh_build(self, msize=None, mmode=0):
|
||||
"""
|
||||
Method for the generation of the k-point mesh.
|
||||
@ -502,27 +531,24 @@ class Wannier90Converter(ConverterTools):
|
||||
|
||||
"""
|
||||
|
||||
if mmode == 0:
|
||||
if mmode != 0:
|
||||
raise ValueError("Mesh generation mode not supported: %s" % mmode)
|
||||
|
||||
# a regular mesh including Gamma point
|
||||
nkpt = msize[0] * msize[1] * msize[2] # total number of k-points
|
||||
# total number of k-points
|
||||
nkpt = msize[0] * msize[1] * msize[2]
|
||||
kmesh = numpy.zeros((nkpt, 3), dtype=float)
|
||||
ii = 0
|
||||
for ix in range(msize[0]):
|
||||
for iy in range(msize[1]):
|
||||
for iz in range(msize[2]):
|
||||
for ix, iy, iz in product(range(msize[0]), range(msize[1]), range(msize[2])):
|
||||
kmesh[ii, :] = [float(ix) / msize[0], float(iy) / msize[1], float(iz) / msize[2]]
|
||||
ii += 1
|
||||
# weight is equal for all k-points because wannier90 uses uniform grid on whole BZ
|
||||
# (normalization is always 1 and takes into account spin degeneracy)
|
||||
wk = numpy.ones([nkpt], dtype=float) / float(nkpt)
|
||||
else:
|
||||
raise ValueError("Mesh generation mode not supported: %s"%mmode)
|
||||
|
||||
return nkpt, kmesh, wk
|
||||
|
||||
|
||||
|
||||
def fourierham(self, norb, h_of_r):
|
||||
def fourier_ham(self, norb, h_of_r):
|
||||
"""
|
||||
Method for obtaining H(k) from H(R) via Fourier transform
|
||||
The R vectors and k-point mesh are read from global module variables
|
||||
@ -541,16 +567,12 @@ class Wannier90Converter(ConverterTools):
|
||||
|
||||
"""
|
||||
|
||||
imag = 1j
|
||||
twopi = 2 * numpy.pi
|
||||
|
||||
h_of_k = [numpy.zeros((norb, norb), dtype=numpy.complex_) for ik in range(self.n_k)]
|
||||
for ik in range(self.n_k):
|
||||
ridx = numpy.array(range(self.nrpt))
|
||||
for ir in ridx:
|
||||
for ik, ir in product(range(self.n_k), ridx):
|
||||
rdotk = twopi * numpy.dot(self.k_mesh[ik], self.rvec[ir])
|
||||
factor = (math.cos(rdotk) + imag * math.sin(rdotk)) / float(self.rdeg[ir])
|
||||
factor = (math.cos(rdotk) + 1j * math.sin(rdotk)) / float(self.rdeg[ir])
|
||||
h_of_k[ik][:, :] += factor * h_of_r[ir][:, :]
|
||||
|
||||
return h_of_k
|
||||
|
||||
|
Loading…
Reference in New Issue
Block a user