mirror of
https://github.com/triqs/dft_tools
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c4db7e6867
* remove manual module reference files * move hdf5 structure reference to guide * fix various doc strings * remove very old update_archive python script for triqs 1.2 * refine main documentation.rst file -> better overview
188 lines
8.0 KiB
Python
188 lines
8.0 KiB
Python
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##########################################################################
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#
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# TRIQS: a Toolbox for Research in Interacting Quantum Systems
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#
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# Copyright (C) 2011 by M. Aichhorn, L. Pourovskii, V. Vildosola
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#
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# TRIQS is free software: you can redistribute it and/or modify it under the
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# terms of the GNU General Public License as published by the Free Software
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# Foundation, either version 3 of the License, or (at your option) any later
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# version.
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#
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# TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY
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# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
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# details.
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#
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# You should have received a copy of the GNU General Public License along with
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# TRIQS. If not, see <http://www.gnu.org/licenses/>.
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#
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##########################################################################
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"""
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module for the symmetry operations in k sums
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"""
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import copy
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import numpy
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from types import *
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from triqs.gf import *
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from h5 import *
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import triqs.utility.mpi as mpi
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class Symmetry:
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"""
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This class provides the routines for applying symmetry operations for the k sums.
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It contains the permutations of the atoms in the unit cell, and the corresponding
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rotational matrices for each symmetry operation.
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"""
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def __init__(self, hdf_file, subgroup=None):
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"""
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Initialises the class.
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Parameters
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----------
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hdf_file : string
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Base name of the hdf5 archive with the symmetry data.
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subgroup : string, optional
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Name of subgroup storing correlated-shell symmetry data. If not given, it is assumed that
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the data is stored at the root of the hdf5 archive.
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"""
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assert isinstance(hdf_file, str), "Symmetry: hdf_file must be a filename."
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self.hdf_file = hdf_file
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things_to_read = ['n_symm', 'n_atoms', 'perm',
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'orbits', 'SO', 'SP', 'time_inv', 'mat', 'mat_tinv']
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for it in things_to_read:
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setattr(self, it, 0)
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if mpi.is_master_node():
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# Read the stuff on master:
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with HDFArchive(hdf_file, 'r') as ar:
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if subgroup is None:
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ar2 = ar
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else:
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ar2 = ar[subgroup]
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for it in things_to_read:
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setattr(self, it, ar2[it])
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del ar2
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# Broadcasting
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for it in things_to_read:
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setattr(self, it, mpi.bcast(getattr(self, it)))
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# now define the mapping of orbitals:
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# self.orb_map[iorb] = jorb gives the permutation of the orbitals as given in the list, when the
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# permutation of the atoms is done:
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self.n_orbits = len(self.orbits)
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self.orb_map = [[0 for iorb in range(
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self.n_orbits)] for i_symm in range(self.n_symm)]
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for i_symm in range(self.n_symm):
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for iorb in range(self.n_orbits):
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srch = copy.deepcopy(self.orbits[iorb])
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srch['atom'] = self.perm[i_symm][self.orbits[iorb]['atom'] - 1]
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self.orb_map[i_symm][iorb] = self.orbits.index(srch)
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def symmetrize(self, obj):
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"""
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Symmetrizes a given object.
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Parameters
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----------
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obj : list
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object to symmetrize. It has to be given as list, where its length is determined by the number
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of equivalent members of the object. Two types of objects are supported:
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- BlockGf : list of Green's functions,
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- Matrices : The format is taken from density matrices as obtained from Green's functions (DictType).
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Returns
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-------
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symm_obj : list
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Symmetrized object, of the same type as input object.
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"""
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assert isinstance(
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obj, list), "symmetrize: obj has to be a list of objects."
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assert len(
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obj) == self.n_orbits, "symmetrize: obj has to be a list of the same length as defined in the init."
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if isinstance(obj[0], BlockGf):
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# here the result is stored, it is a BlockGf!
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symm_obj = [obj[i].copy() for i in range(len(obj))]
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for iorb in range(self.n_orbits):
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symm_obj[iorb].zero() # set to zero
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else:
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# if not a BlockGf, we assume it is a matrix (density matrix), has
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# to be complex since self.mat is complex!
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symm_obj = [copy.deepcopy(obj[i]) for i in range(len(obj))]
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for iorb in range(self.n_orbits):
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if isinstance(symm_obj[iorb], dict):
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for ii in symm_obj[iorb]:
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symm_obj[iorb][ii] *= 0.0
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else:
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symm_obj[iorb] *= 0.0
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for i_symm in range(self.n_symm):
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for iorb in range(self.n_orbits):
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l = self.orbits[iorb]['l'] # s, p, d, or f
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dim = self.orbits[iorb]['dim']
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jorb = self.orb_map[i_symm][iorb]
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if isinstance(obj[0], BlockGf):
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tmp = obj[iorb].copy()
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if self.time_inv[i_symm]:
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tmp << tmp.transpose()
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for bname, gf in tmp:
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tmp[bname].from_L_G_R(self.mat[i_symm][iorb], tmp[bname], self.mat[
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i_symm][iorb].conjugate().transpose())
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tmp *= 1.0 / self.n_symm
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symm_obj[jorb] += tmp
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else:
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if isinstance(obj[iorb], dict):
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for ii in obj[iorb]:
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if self.time_inv[i_symm] == 0:
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symm_obj[jorb][ii] += numpy.dot(numpy.dot(self.mat[i_symm][iorb], obj[iorb][ii]),
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self.mat[i_symm][iorb].conjugate().transpose()) / self.n_symm
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else:
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symm_obj[jorb][ii] += numpy.dot(numpy.dot(self.mat[i_symm][iorb], obj[iorb][ii].conjugate()),
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self.mat[i_symm][iorb].conjugate().transpose()) / self.n_symm
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else:
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if self.time_inv[i_symm] == 0:
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symm_obj[jorb] += numpy.dot(numpy.dot(self.mat[i_symm][iorb], obj[iorb]),
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self.mat[i_symm][iorb].conjugate().transpose()) / self.n_symm
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else:
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symm_obj[jorb] += numpy.dot(numpy.dot(self.mat[i_symm][iorb], obj[iorb].conjugate()),
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self.mat[i_symm][iorb].conjugate().transpose()) / self.n_symm
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# Markus: This does not what it is supposed to do, check how this should work (keep for now)
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# if (self.SO == 0) and (self.SP == 0):
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# # add time inv:
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#mpi.report("Add time inversion")
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# for iorb in range(self.n_orbits):
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# if (isinstance(symm_obj[0],BlockGf)):
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# tmp = symm_obj[iorb].copy()
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# tmp << tmp.transpose()
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# for bname,gf in tmp: tmp[bname].from_L_G_R(self.mat_tinv[iorb],tmp[bname],self.mat_tinv[iorb].transpose().conjugate())
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# symm_obj[iorb] += tmp
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# symm_obj[iorb] /= 2.0
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#
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# else:
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# if isinstance(symm_obj[iorb], dict):
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# for ii in symm_obj[iorb]:
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# symm_obj[iorb][ii] += numpy.dot(numpy.dot(self.mat_tinv[iorb],symm_obj[iorb][ii].conjugate()),
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# self.mat_tinv[iorb].transpose().conjugate())
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# symm_obj[iorb][ii] /= 2.0
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# else:
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# symm_obj[iorb] += numpy.dot(numpy.dot(self.mat_tinv[iorb],symm_obj[iorb].conjugate()),
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# self.mat_tinv[iorb].transpose().conjugate())
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# symm_obj[iorb] /= 2.0
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return symm_obj
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