[doc] Corrected errors in the Ce example scripts

doc/guide/dftdmft_singleshot.rst

@@ -145,7 +145,7 @@ Most of these parameters are self-explanatory. The first,
 details on the solver parameters, we refer the user to
 the :ref:`CTHYB solver <triqscthyb:welcome>` documentation.
 
-We assume that the conversion to the hdf5 archive is alreadz done. We
+We assume that the conversion to the hdf5 archive is already done. We
 can check now in this archive, if previous runs are present, or if we have to start
 from scratch::
 

doc/guide/images_scripts/Ce-gamma.py

@@ -2,7 +2,6 @@ from pytriqs.applications.dft.sumk_dft import *
 from pytriqs.applications.dft.converters.wien2k_converter import *
 from pytriqs.applications.impurity_solvers.hubbard_I.hubbard_solver import Solver
 
-
 import os
 dft_filename = os.getcwd().rpartition('/')[2]
 
@@ -10,14 +9,12 @@ beta = 40
 U_int = 6.00
 J_hund = 0.70
 Loops =  5                       # Number of DMFT sc-loops
-Mix = 0.7                        # Mixing factor in QMC
+mixing = 0.7                     # Mixing factor
 DC_type = 0                      # 0...FLL, 1...Held, 2... AMF, 3...Lichtenstein
 chemical_potential_init=0.0      # initial chemical potential
 
-HDFfilename = dft_filename+'.h5'
-
 # Convert DMFT input:
-Converter = Wien2kConverter(filename=filename)
+Converter = Wien2kConverter(filename=dft_filename)
 Converter.convert_dft_input()
 mpi.barrier()
 
@@ -25,7 +22,7 @@ mpi.barrier()
 previous_runs = 0
 previous_present = False
 if mpi.is_master_node():
-    f = HDFArchive(filename+'.h5','a')
+    f = HDFArchive(dft_filename+'.h5','a')
     if 'dmft_output' in f:
         ar = f['dmft_output']
         if 'iterations' in ar:
@@ -53,11 +50,11 @@ if previous_present:
         ar = HDFArchive(dft_filename+'.h5','a')
         S.Sigma << ar['dmft_output']['Sigma']
         del ar
-        chemical_potential,dc_imp,dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
+        SK.chemical_potential,SK.dc_imp,SK.dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
     S.Sigma << mpi.bcast(S.Sigma)
-    SK.set_mu(chemical_potential)
+    SK.chemical_potential = mpi.bcast(SK.chemical_potential)
-    SK.set_dc(dc_imp,dc_energ)
+    SK.dc_imp = mpi.bcast(SK.dc_imp)
-    
+    SK.dc_energ = mpi.bcast(SK.dc_energ)
 
 # DMFT loop:
 for iteration_number in range(1,Loops+1):
@@ -78,7 +75,7 @@ for iteration_number in range(1,Loops+1):
         if ((iteration_number==1)and(previous_present==False)):
             dc_value_init=U_int/2.0
             dm=S.G.density()
-	        SK.calc_dc( dm, U_interact = U_int, J_hund = J_hund, orb = 0, use_dc_formula = DC_type, use_dc_value=dc_value_init)
+	    SK.calc_dc( dm, U_interact = U_int, J_hund = J_hund, orb = 0, use_dc_formula = DC_type, use_dc_value=dc_value_init)
 
         # calculate non-interacting atomic level positions:
         eal = SK.eff_atomic_levels()[0]
@@ -89,11 +86,11 @@ for iteration_number in range(1,Loops+1):
 
         # Now mix Sigma and G with factor Mix, if wanted:
         if (iteration_number>1 or previous_present):
-            if (mpi.is_master_node() and (sigma_mix<1.0)):
+            if (mpi.is_master_node() and (mixing<1.0)):
                 ar = HDFArchive(dft_filename+'.h5','a')
-                mpi.report("Mixing Sigma and G with factor %s"%sigma_mix)
+                mpi.report("Mixing Sigma and G with factor %s"%mixing)
-                S.Sigma << sigma_mix * S.Sigma + (1.0-sigma_mix) * ar['dmft_output']['Sigma']
+                S.Sigma << mixing * S.Sigma + (1.0-mixing) * ar['dmft_output']['Sigma']
-                S.G << sigma_mix * S.G + (1.0-sigma_mix) * ar['dmft_output']['G']
+                S.G << mixing * S.G + (1.0-mixing) * ar['dmft_output']['G']
                 del ar
             S.G << mpi.bcast(S.G)
             S.Sigma << mpi.bcast(S.Sigma)
@@ -104,8 +101,8 @@ for iteration_number in range(1,Loops+1):
         SK.calc_dc( dm, U_interact = U_int, J_hund = J_hund, orb = 0, use_dc_formula = DC_type )
 
         # correlation energy calculations:
-        correnerg = 0.5 * (S.G * S.Sigma).total_density()
+        SK.correnerg = 0.5 * (S.G * S.Sigma).total_density()
-        mpi.report("Corr. energy = %s"%correnerg)
+        mpi.report("Corr. energy = %s"%SK.correnerg)
 
         # store the impurity self-energy, GF as well as correlation energy in h5
         if mpi.is_master_node():
@@ -145,7 +142,7 @@ mpi.report("Trace of Density Matrix: %s"%d)
 
 # store correlation energy contribution to be read by Wien2ki and then included to DFT+DMFT total energy
 if (mpi.is_master_node()):
-    correnerg -= DCenerg[0]
+    SK.correnerg -= SK.dc_energ[0]
     f=open(dft_filename+'.qdmft','a')
-    f.write("%.16f\n"%correnerg)
+    f.write("%.16f\n"%SK.correnerg)
     f.close()

doc/guide/images_scripts/Ce-gamma_DOS.py

@@ -14,24 +14,22 @@ ommax=6.0
 N_om=2001
 broadening = 0.02
 
-HDFfilename = dft_filename+'.h5'
-
 # Convert DMFT input:
 Converter = Wien2kConverter(filename=dft_filename,repacking=True)
 Converter.convert_dft_input()
 Converter.convert_parproj_input()
 
-
-
 # Init the SumK class
 SK = SumkDFTTools(hdf_file=dft_filename+'.h5',use_dft_blocks=False)
 
 # load old chemical potential and DC
 if mpi.is_master_node():
-    chemical_potential,dc_imp,dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
+    SK.chemical_potential,SK.dc_imp,SK.dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
-SK.set_mu(chemical_potential)
+
-SK.set_dc(dc_imp,dc_energ)
+SK.chemical_potential = mpi.bcast(SK.chemical_potential)
-    
+SK.dc_imp = mpi.bcast(SK.dc_imp)
+SK.dc_energ = mpi.bcast(SK.dc_energ)
+
 if (mpi.is_master_node()):
     print 'DC after reading SK: ',SK.dc_imp[0]