Added a wrapper function set_Sigma for more standard API

dft_dmft_cthyb.py

@@ -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())

doc/guide/analysis.rst

@@ -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 

doc/guide/dftdmft_selfcons.rst

@@ -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'])

doc/guide/dftdmft_singleshot.rst

@@ -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())

doc/guide/images_scripts/Ce-gamma.py

@@ -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 )

doc/guide/images_scripts/Ce-gamma_DOS.py

@@ -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)

doc/guide/images_scripts/dft_dmft_cthyb.py

@@ -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())

doc/guide/images_scripts/dft_dmft_cthyb_slater.py

@@ -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())

doc/guide/transport.rst

@@ -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)

python/sumk_dft.py

@@ -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.

test/sigma_from_file.py

@@ -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'])

test/srvo3_Gloc.py

@@ -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')

test/srvo3_transp.py

@@ -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