In order to use c++2py tools the C-code must be rewritten to C++.
In particular, instead of direct creation of Numpy arrays STL
containers must be used.
The local Hamiltonian is now output after the density matrix.
This is mainly needed for debug purposes. At a later stage the
output should be better formatted and controlled.
At the main SC script 'sc_dmft.py' requires importing a user DMFT
script as a module. Ideally, this should be implemented in a different
way so that the user script imports a function from the self-consistent
script.
Noramlly, the Fermi energy is read from DOSCAR. However, this does
not work in case of a self-consistent calculation in which DOSCAR
is not written between iterations. One of the options is
to modify slightly the output to LOCPROJ and add EFERMI to the
first line.
Since 'n_orbitals' can be a 2D array in case of spin-polarized
calculations, one should use 'numpy.max' instead of 'max' to
extract the maximum number of bands.
In the new version of VASP LOCPROJ contains the eigenvalues and
Fermi weights. Also, during a charge self-consistency calculation
the file EIGENVAL is not written at intermediate iterations. It is,
thus, preferential to use LOCPROJ to get the named data.
At the moment, EIGENVAL will still be used if it is complete but
in the future this dependence should be removed completely.
The band indices should be converted to Fortran convention,
i.e. starting from 1, in the output files because the are
used in the density matrix file which is read by a Fortran code.
The format of LOCPROJ has been modified again (in VASP 5.4.2
build from Dec 02, 2015).
Now, there is an additional line before each projector block
providing the spin, k-, and band indices, as well as
eigenvalues and Fermi weights.
Scripts 'run_plovasp.sh' have been replaced by a template in which
the path must be set by the user.
Also, .gitignore has been added to example 'lunio3'.
At one step of the orthogonaliztion procedure two matrix multiplications
have been replaced with one matrix multiplication and a element-wise
multiplication of a vector and a matrix.
