LCPQ/dft_tools
3
0
Fork 0
mirror of https://github.com/triqs/dft_tools synced 2024-08-29 07:22:01 +02:00
Code Issues Releases Wiki Activity

Fix save function and call in init

Browse Source
This commit is contained in:
Priyanka Seth 2014-11-19 16:54:13 +01:00
parent 84bd1ed655
commit be69c7345b
6 changed files with 8 additions and 13 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
doc/Ce-gamma.py
View File

@ -130,7 +130,7 @@ for Iteration_Number in range(1,Loops+1):
#Save stuff:
SK.save()
SK.save(['chemical_potential','dc_imp','dc_energ'])
if (mpi.is_master_node()):
print 'DC after solver: ',SK.dc_imp[SK.invshellmap[0]]

4
doc/DFTDMFTmain.rst
View File

@ -100,9 +100,9 @@ set up the loop over DMFT iterations and the self-consistency condition::
l=2,T=None, dim_reps=None, irep=None, n_cycles =10000,
length_cycle=200,n_warmup_cycles=1000)
dm = S.G.density() # density matrix of the impurity problem
dm = S.G.density() # Density matrix of the impurity problem
SK.set_dc( dm, U_interact = U, J_hund = J, use_dc_formula = 0) # Set the double counting term
SK.save() # save everything to the hdf5 arxive
SK.save(['chemical_potential','dc_imp','dc_energ']) # Save data in the hdf5 archive
These basic steps are enough to set up the basic DMFT Loop. For a detailed description of the :class:`SumkDFT` routines,
see the reference manual. After the self-consistency steps, the solution of the Anderson impurity problem is calculation by CTQMC.

2
doc/advanced.rst
View File

@ -144,7 +144,7 @@ previous section, with some additional refinement::
SK.set_dc( dm, U_interact = U, J_hund = J, orb = 0, use_dc_formula = dc_type)
#Save stuff:
SK.save()
SK.save(['chemical_potential','dc_imp','dc_energ'])
This is all we need for the DFT+DMFT calculation. At the end, all results are stored in the hdf5 output file.

2
doc/selfcons.rst
View File

@ -36,7 +36,7 @@ Now we calculate the modified charge density::
SK.put_Sigma(Sigma_imp = [ S.Sigma ])
chemical_potential = SK.find_mu( precision = 0.000001 )
dN, d = SK.calc_density_correction(filename = dft_filename+'.qdmft')
SK.save()
SK.save(['chemical_potential','dc_imp','dc_energ'])
First we find the chemical potential with high precision, and after that the routine
``SK.calc_density_correction(filename)`` calculates the density matrix including correlation effects. The result

4
lda_dmft_cthyb.py
View File

@ -131,8 +131,8 @@ for iteration_number in range(1,loops+1):
# Set the double counting
SK.set_dc( dm, U_interact = U, J_hund = J, orb = 0, use_dc_formula = dc_type)
# Save stuff into the hdf5 archive:
SK.save()
# Save stuff into the dft_output group of hdf5 archive in case of rerun:
SK.save(['chemical_potential','dc_imp','dc_energ'])
if mpi.is_master_node():
ar = HDFArchive("dftdmft.h5",'w')

7
python/sumk_dft.py
View File

@ -114,11 +114,6 @@ class SumkDFT:
# Analyse the block structure and determine the smallest blocks, if desired
if use_dft_blocks: dm = self.analyse_block_structure()
# Now save new things to HDF5:
# FIXME WHAT HAPPENS TO h_field? INPUT TO __INIT__? ADD TO OPTIONAL_THINGS?
things_to_save = ['chemical_potential','dc_imp','dc_energ','h_field']
self.save(things_to_save)
################
# HDF5 FUNCTIONS
################
@ -171,7 +166,7 @@ class SumkDFT:
def save(self,things_to_save):
"""Saves some quantities into an HDF5 archive"""
"""Saves given quantities into the 'dft_output' subgroup of the HDF5 archive"""
if not (mpi.is_master_node()): return # do nothing on nodes
ar = HDFArchive(self.hdf_file,'a')