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Added a wrapper function set_Sigma for more standard API

This commit is contained in:
Priyanka Seth 2015-11-02 11:42:47 +01:00
parent 0a07681455
commit f93fd828c0
13 changed files with 18 additions and 17 deletions
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2
dft_dmft_cthyb.py
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@ -77,7 +77,7 @@ for iteration_number in range(1,loops+1):
if mpi.is_master_node(): print "Iteration = ", iteration_number
SK.symm_deg_gf(S.Sigma_iw,orb=0) # symmetrise Sigma
SK.put_Sigma(Sigma_imp = [ S.Sigma_iw ]) # put Sigma into the SumK class
SK.set_Sigma([ S.Sigma_iw ]) # set Sigma into the SumK class
chemical_potential = SK.calc_mu( precision = prec_mu ) # find the chemical potential for given density
S.G_iw << SK.extract_G_loc()[0] # calc the local Green function
mpi.report("Total charge of Gloc : %.6f"%S.G_iw.total_density())

8
doc/guide/analysis.rst
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@ -64,9 +64,9 @@ where:
It is important that each data file has to contain three columns: the real frequency mesh, the real part and the imaginary part
of the self energy - exactly in this order! The mesh should be the same for all files read in and non-uniform meshes are not supported.
Finally, we put the self energy into the `SK` object::
Finally, we set the self energy into the `SK` object::
SK.put_Sigma(Sigma_imp = [SigmaReFreq])
SK.set_Sigma([SigmaReFreq])
and additionally set the chemical potential and the double counting correction from the DMFT calculation::
@ -96,7 +96,7 @@ the output is printed into the files
* `DOS_wannier_(sp)_proj(i)_(m)_(n).dat`: As above, but printed as orbitally-resolved matrix in indices
`(m)` and `(n)`. For `d` orbitals, it gives the DOS separately for, e.g., :math:`d_{xy}`, :math:`d_{x^2-y^2}`, and so on,
otherwise, the ouptput is returned by the function for a further usage in :program:`python`.
otherwise, the output is returned by the function for a further usage in :program:`python`.
Partial charges
---------------
@ -104,7 +104,7 @@ Partial charges
Since we can calculate the partial charges directly from the Matsubara Green's functions, we also do not need a
real frequency self energy for this purpose. The calculation is done by::
SK.put_Sigma(Sigma_imp = SigmaImFreq)
SK.set_Sigma(SigmaImFreq)
dm = SK.partial_charges(beta=40.0, with_Sigma=True, with_dc=True)
which calculates the partial charges using the self energy, double counting, and chemical potential as set in the

2
doc/guide/dftdmft_selfcons.rst
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@ -41,7 +41,7 @@ These steps are not necessary, but can help to reduce fluctuations in the total
Now we calculate the modified charge density::
# find exact chemical potential
SK.put_Sigma(Sigma_imp = [ S.Sigma_iw ])
SK.set_Sigma([ S.Sigma_iw ])
chemical_potential = SK.calc_mu( precision = 0.000001 )
dN, d = SK.calc_density_correction(filename = dft_filename+'.qdmft')
SK.save(['chemical_potential','dc_imp','dc_energ'])

4
doc/guide/dftdmft_singleshot.rst
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@ -50,7 +50,7 @@ iterations and the self-consistency condition::
n_loops = 5
for iteration_number in range(n_loops) : # start the DMFT loop
SK.put_Sigma(Sigma_imp = [ S.Sigma ]) # Put self energy to the SumK class
SK.set_Sigma([ S.Sigma ]) # Put self energy to the SumK class
chemical_potential = SK.calc_mu() # calculate the chemical potential for the given density
S.G_iw << SK.extract_G_loc()[0] # extract the local Green function
S.G0_iw << inverse(S.Sigma_iw + inverse(S.G_iw)) # finally get G0, the input for the Solver
@ -239,7 +239,7 @@ refinements::
if mpi.is_master_node(): print "Iteration = ", iteration_number
SK.symm_deg_gf(S.Sigma_iw,orb=0) # symmetrise Sigma
SK.put_Sigma(Sigma_imp = [ S.Sigma_iw ]) # put Sigma into the SumK class
SK.set_Sigma([ S.Sigma_iw ]) # put Sigma into the SumK class
chemical_potential = SK.calc_mu( precision = prec_mu ) # find the chemical potential for given density
S.G_iw << SK.extract_G_loc()[0] # calc the local Green function
mpi.report("Total charge of Gloc : %.6f"%S.G_iw.total_density())

2
doc/guide/images_scripts/Ce-gamma.py
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@ -65,7 +65,7 @@ for iteration_number in range(1,Loops+1):
itn = iteration_number + previous_runs
# put Sigma into the SumK class:
SK.put_Sigma(Sigma_imp = [ S.Sigma ])
SK.set_Sigma([ S.Sigma ])
# Compute the SumK, possibly fixing mu by dichotomy
chemical_potential = SK.calc_mu( precision = 0.000001 )

2
doc/guide/images_scripts/Ce-gamma_DOS.py
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@ -47,7 +47,7 @@ S.set_atomic_levels( eal = eal )
# Run the solver to get GF and self-energy on the real axis
S.GF_realomega(ommin=ommin, ommax = ommax, N_om=N_om,U_int=U_int,J_hund=J_hund)
SK.put_Sigma(Sigma_imp = [S.Sigma])
SK.set_Sigma([S.Sigma])
# compute DOS
SK.dos_parproj_basis(broadening=broadening)

2
doc/guide/images_scripts/dft_dmft_cthyb.py
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@ -82,7 +82,7 @@ for iteration_number in range(1,loops+1):
if mpi.is_master_node(): print "Iteration = ", iteration_number
SK.symm_deg_gf(S.Sigma_iw,orb=0) # symmetrise Sigma
SK.put_Sigma(Sigma_imp = [ S.Sigma_iw ]) # put Sigma into the SumK class
SK.set_Sigma([ S.Sigma_iw ]) # set Sigma into the SumK class
chemical_potential = SK.calc_mu( precision = prec_mu ) # find the chemical potential for given density
S.G_iw << SK.extract_G_loc()[0] # calc the local Green function
mpi.report("Total charge of Gloc : %.6f"%S.G_iw.total_density())

2
doc/guide/images_scripts/dft_dmft_cthyb_slater.py
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@ -83,7 +83,7 @@ for iteration_number in range(1,loops+1):
if mpi.is_master_node(): print "Iteration = ", iteration_number
SK.symm_deg_gf(S.Sigma_iw,orb=0) # symmetrise Sigma
SK.put_Sigma(Sigma_imp = [ S.Sigma_iw ]) # put Sigma into the SumK class
SK.set_Sigma([ S.Sigma_iw ]) # set Sigma into the SumK class
chemical_potential = SK.calc_mu( precision = prec_mu ) # find the chemical potential for given density
S.G_iw << SK.extract_G_loc()[0] # calc the local Green function
mpi.report("Total charge of Gloc : %.6f"%S.G_iw.total_density())

2
doc/guide/transport.rst
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@ -86,7 +86,7 @@ reads the required data of the Wien2k output and stores it in the `dft_transp_in
Additionally we need to read and set the self energy, the chemical potential and the double counting::
ar = HDFArchive('case.h5', 'a')
SK.put_Sigma(Sigma_imp = [ar['dmft_output']['Sigma_w']])
SK.set_Sigma([ar['dmft_output']['Sigma_w']])
chemical_potential,dc_imp,dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
SK.set_mu(chemical_potential)
SK.set_dc(dc_imp,dc_energ)

3
python/sumk_dft.py
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@ -510,6 +510,8 @@ class SumkDFT:
return G_latt
def set_Sigma(self,Sigma_imp):
self.put_Sigma(Sigma_imp)
def put_Sigma(self, Sigma_imp):
r"""
@ -557,7 +559,6 @@ class SumkDFT:
for icrsh in range(self.n_corr_shells):
for bname,gf in SK_Sigma_imp[icrsh]: gf << self.rotloc(icrsh,gf,direction='toGlobal')
def extract_G_loc(self, mu=None, with_Sigma=True, with_dc=True):
r"""
Extracts the local downfolded Green function by the Brillouin-zone integration of the lattice Green's function.

2
test/sigma_from_file.py
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@ -24,7 +24,7 @@ a_list = [a for a,al in SK.gf_struct_solver[0].iteritems()]
g_list = [read_gf_from_txt([['Sigma_' + a + '.dat']], a) for a in a_list]
Sigma_txt = BlockGf(name_list = a_list, block_list = g_list, make_copies=False)
SK.put_Sigma(Sigma_imp = [Sigma_txt])
SK.set_Sigma([Sigma_txt])
SK.hdf_file = 'sigma_from_file.output.h5'
SK.save(['Sigma_imp_w'])

2
test/srvo3_Gloc.py
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@ -41,7 +41,7 @@ gf_struct = set_operator_structure(spin_names,orb_names,orb_hybridized)
glist = [ GfImFreq(indices=inner,beta=beta) for block,inner in gf_struct.iteritems()]
Sigma_iw = BlockGf(name_list = gf_struct.keys(), block_list = glist, make_copies = False)
SK.put_Sigma([Sigma_iw])
SK.set_Sigma([Sigma_iw])
Gloc=SK.extract_G_loc()
ar = HDFArchive('srvo3_Gloc.output.h5','w')

2
test/srvo3_transp.py
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@ -34,7 +34,7 @@ SK = SumkDFTTools(hdf_file='SrVO3.h5', use_dft_blocks=True)
ar = HDFArchive('SrVO3_Sigma.h5', 'a')
Sigma = ar['dmft_transp_input']['Sigma_w']
SK.put_Sigma(Sigma_imp = [Sigma])
SK.set_Sigma([Sigma])
SK.chemical_potential = ar['dmft_transp_input']['chemical_potential']
SK.dc_imp = ar['dmft_transp_input']['dc_imp']
del ar