mirror of
https://github.com/triqs/dft_tools
synced 2024-11-03 04:33:51 +01:00
197 lines
6.6 KiB
Python
197 lines
6.6 KiB
Python
from triqs_dft_tools.sumk_dft import *
|
|
from triqs_dft_tools.converters import Wien2kConverter
|
|
from pytriqs.gf import *
|
|
from pytriqs.archive import *
|
|
import pytriqs.utility.mpi as mpi
|
|
import numpy
|
|
import copy
|
|
|
|
|
|
class TransBasis:
|
|
"""
|
|
Computates rotations into a new basis, using the condition that a given property is diagonal in the new basis.
|
|
"""
|
|
|
|
def __init__(self, SK=None, hdf_datafile=None):
|
|
"""
|
|
Initialization of the class. There are two ways to do so:
|
|
|
|
- existing SumkLDA class : when you have an existing SumkLDA instance
|
|
- from hdf5 archive : when you want to use data from hdf5 archive
|
|
|
|
Giving the class instance overrides giving the string for the hdf5 archive.
|
|
|
|
Parameters
|
|
----------
|
|
SK : class SumkLDA, optional
|
|
Existing instance of SumkLDA class.
|
|
hdf5_datafile : string, optional
|
|
Name of hdf5 archive to be used.
|
|
|
|
"""
|
|
|
|
if SK is None:
|
|
# build our own SK instance
|
|
if hdf_datafile is None:
|
|
mpi.report("trans_basis: give SK instance or HDF filename!")
|
|
return 0
|
|
|
|
Converter = Wien2kConverter(filename=hdf_datafile, repacking=False)
|
|
Converter.convert_dft_input()
|
|
del Converter
|
|
|
|
self.SK = SumkDFT(hdf_file=hdf_datafile +
|
|
'.h5', use_dft_blocks=False)
|
|
else:
|
|
self.SK = SK
|
|
|
|
self.T = copy.deepcopy(self.SK.T[0])
|
|
self.w = numpy.identity(SK.corr_shells[0]['dim'])
|
|
|
|
def calculate_diagonalisation_matrix(self, prop_to_be_diagonal='eal'):
|
|
"""
|
|
Calculates the diagonalisation matrix w, and stores it as member of the class.
|
|
|
|
Parameters
|
|
----------
|
|
prop_to_be_diagonal : string, optional
|
|
Defines the property to be diagonalized.
|
|
|
|
- 'eal' : local hamiltonian (i.e. crystal field)
|
|
- 'dm' : local density matrix
|
|
|
|
Returns
|
|
-------
|
|
wsqr : double
|
|
Measure for the degree of rotation done by the diagonalisation. wsqr=1 means no rotation.
|
|
|
|
"""
|
|
|
|
if prop_to_be_diagonal == 'eal':
|
|
prop = self.SK.eff_atomic_levels()[0]
|
|
elif prop_to_be_diagonal == 'dm':
|
|
prop = self.SK.density_matrix(method='using_point_integration')[0]
|
|
else:
|
|
mpi.report(
|
|
"trans_basis: not a valid quantitiy to be diagonal. Choices are 'eal' or 'dm'.")
|
|
return 0
|
|
|
|
if self.SK.SO == 0:
|
|
self.eig, self.w = numpy.linalg.eigh(prop['up'])
|
|
# calculate new Transformation matrix
|
|
self.T = numpy.dot(self.T.transpose().conjugate(),
|
|
self.w).conjugate().transpose()
|
|
else:
|
|
self.eig, self.w = numpy.linalg.eigh(prop['ud'])
|
|
# calculate new Transformation matrix
|
|
self.T = numpy.dot(self.T.transpose().conjugate(),
|
|
self.w).conjugate().transpose()
|
|
|
|
# measure for the 'unity' of the transformation:
|
|
wsqr = sum(abs(self.w.diagonal())**2) / self.w.diagonal().size
|
|
return wsqr
|
|
|
|
def rotate_gf(self, gf_to_rot):
|
|
"""
|
|
Uses the diagonalisation matrix w to rotate a given GF into the new basis.
|
|
|
|
Parameters
|
|
----------
|
|
gf_to_rot : BlockGf
|
|
Green's function block to rotate.
|
|
|
|
Returns
|
|
-------
|
|
gfreturn : BlockGf
|
|
Green's function rotated into the new basis.
|
|
"""
|
|
|
|
# build a full GF
|
|
gfrotated = BlockGf(name_block_generator=[(block, GfImFreq(
|
|
indices=inner, mesh=gf_to_rot.mesh)) for block, inner in self.SK.gf_struct_sumk[0]], make_copies=False)
|
|
|
|
# transform the CTQMC blocks to the full matrix:
|
|
# ish is the index of the inequivalent shell corresponding to icrsh
|
|
ish = self.SK.corr_to_inequiv[0]
|
|
for block, inner in self.gf_struct_solver[ish].iteritems():
|
|
for ind1 in inner:
|
|
for ind2 in inner:
|
|
gfrotated[self.SK.solver_to_sumk_block[ish][block]][
|
|
ind1, ind2] << gf_to_rot[block][ind1, ind2]
|
|
|
|
# Rotate using the matrix w
|
|
for bname, gf in gfrotated:
|
|
gfrotated[bname].from_L_G_R(
|
|
self.w.transpose().conjugate(), gfrotated[bname], self.w)
|
|
|
|
gfreturn = gf_to_rot.copy()
|
|
# Put back into CTQMC basis:
|
|
for block, inner in self.gf_struct_solver[ish].iteritems():
|
|
for ind1 in inner:
|
|
for ind2 in inner:
|
|
gfreturn[block][ind1, ind2] << gfrotated[
|
|
self.SK.solver_to_sumk_block[0][block]][ind1, ind2]
|
|
|
|
return gfreturn
|
|
|
|
def write_trans_file(self, filename):
|
|
"""
|
|
Writes the new transformation T into a file readable by dmftproj. By that, the requested quantity is
|
|
diagonal already at input.
|
|
|
|
Parameters
|
|
----------
|
|
filename : string
|
|
Name of the file where the transformation is stored.
|
|
"""
|
|
|
|
f = open(filename, 'w')
|
|
Tnew = self.T.conjugate()
|
|
dim = self.SK.corr_shells[0]['dim']
|
|
|
|
if self.SK.SO == 0:
|
|
|
|
for i in range(dim):
|
|
st = ''
|
|
for k in range(dim):
|
|
st += " %9.6f" % (Tnew[i, k].real)
|
|
st += " %9.6f" % (Tnew[i, k].imag)
|
|
for k in range(2 * dim):
|
|
st += " 0.0"
|
|
|
|
if i < (dim - 1):
|
|
f.write("%s\n" % (st))
|
|
else:
|
|
st1 = st.replace(' ', '*', 1)
|
|
f.write("%s\n" % (st1))
|
|
|
|
for i in range(dim):
|
|
st = ''
|
|
for k in range(2 * dim):
|
|
st += " 0.0"
|
|
for k in range(dim):
|
|
st += " %9.6f" % (Tnew[i, k].real)
|
|
st += " %9.6f" % (Tnew[i, k].imag)
|
|
|
|
if i < (dim - 1):
|
|
f.write("%s\n" % (st))
|
|
else:
|
|
st1 = st.replace(' ', '*', 1)
|
|
f.write("%s\n" % (st1))
|
|
|
|
else:
|
|
|
|
for i in range(dim):
|
|
st = ''
|
|
for k in range(dim):
|
|
st += " %9.6f" % (Tnew[i, k].real)
|
|
st += " %9.6f" % (Tnew[i, k].imag)
|
|
|
|
if i < (dim - 1):
|
|
f.write("%s\n" % (st))
|
|
else:
|
|
st1 = st.replace(' ', '*', 1)
|
|
f.write("%s\n" % (st1))
|
|
|
|
f.close()
|