work in NiO tutorial

doc/CMakeLists.txt

@@ -18,6 +18,6 @@ add_custom_target(doc_sphinx ALL DEPENDS ${sphinx_top} ${CMAKE_CURRENT_BINARY_DI
 # ---------------------------------
 install(DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/html/ COMPONENT documentation DESTINATION share/doc/triqs_dft_tools
  FILES_MATCHING
- REGEX "\\.(html|pdf|png|gif|jpg|js|xsl|css|py|txt|inv|bib)$"
+ REGEX "\\.(html|pdf|png|gif|jpg|js|xsl|css|py|txt|inv|bib|cfg)$"
  PATTERN "_*"
  )

doc/guide/conv_vasp.rst

@@ -5,9 +5,7 @@ Interface with VASP
 ===================
 
 .. warning::
-  The VASP interface is in the alpha-version and the VASP part of it is not
-  yet publicly released. The documentation may, thus, be subject to changes
-  before the final release.
+  The VASP interface is in the alpha-version. The documentation may, thus, be subject to changes before the final release.
 
 *Limitations of the alpha-version:*
 
@@ -26,7 +24,8 @@ in the :ref:`PLOVasp User's Guide <plovasp>`. Here, a quick-start guide is prese
 
 The VASP interface relies on new options introduced since version
 5.4.x. In particular, a new INCAR-option `LOCPROJ`
-and new `LORBIT` modes 13 and 14 have been added.
+and new `LORBIT` modes 13 and 14 have been added as well as the new ICHARG
+mode 5 for charge self-consistent calculations
 
 Option `LOCPROJ` selects a set of localized projectors that will
 be written to file `LOCPROJ` after a successful VASP run.
@@ -41,7 +40,7 @@ with the indices corresponding to the site position in the POSCAR file;
 `<projector type>` chooses a particular type of the local basis function.
 The recommended projector type is `Pr 2`. The formalism for this type
 of projectors is presented in
-`M. Schüler et al. 2018 J. Phys.: Condens. Matter 30 475901 <https://doi.org/10.1088/1361-648X/aae80a>`_.
+`M. Schüler et al. 2018 J. Phys.: Condens. Matter 30 475901 <https://doi.org/10.1088/1361-648X/aae80a>`_. For details on `LOCPROJ` also have a look in the `VASP wiki <https://cms.mpi.univie.ac.at/wiki/index.php/LOCPROJ>`_
 
 The allowed labels of the local states defined in terms of cubic
 harmonics are:

doc/guide/plovasp.rst

@@ -55,21 +55,25 @@ A PLOVasp input file can contain three types of sections:
 Section [General]
 """""""""""""""""
 
-The entire section is optional and it contains three parameters:
+The entire section is optional and it contains four parameters:
 
 *  **BASENAME** (string): provides a base name for output files.
    Default filenames are :file:`vasp.*`.
 *  **DOSMESH** ([float float] integer): if this parameter is given,
    the projected density of states for each projected orbital will be
-   evaluated and stored to files :file:`pdos_<n>.dat`, where `n` is the
-   orbital index. The energy
-   mesh is defined by three numbers: `EMIN`  `EMAX`  `NPOINTS`. The first two
+   evaluated and stored to files :file:`pdos_<s>_<n>.dat`, where `s` is the
+   shell index and `n` the ion index. The energy mesh is defined by three 
+   numbers: `EMIN`  `EMAX`  `NPOINTS`. The first two
    can be omitted in which case they are taken to be equal to the projector
    energy window. **Important note**: at the moment this option works
    only if the tetrahedron integration method (`ISMEAR = -4` or `-5`)
    is used in VASP to produce `LOCPROJ`.
 *  **EFERMI** (float): provides the Fermi level. This value overrides
    the one extracted from VASP output files.
+*  **HK** (True/False): If True, the projectors are applied the the Kohn-Sham
+   eigenvalues which results in a Hamitlonian H(k) in orbital basis. The H(k)
+   is written for each group to a file :file:`Basename.hk<Ng>`. It is recommended
+   to also set `COMPLEMENT = True` (see below). Default is False.
 
 There are no required parameters in this section.
 
@@ -94,6 +98,8 @@ given by `LSHELL` must be present in the LOCPROJ file.
 There are additional optional parameters that allow one to transform
 the local states:
 
+*  **CORR** (True/False): Determines if shell is correlated or not. At least one
+   shell has to be correlated. Default is True.
 *  **TRANSFORM** (matrix): local transformation matrix applied to all states
    in the projector shell. The matrix is defined by a (multiline) block
    of floats, with each line corresponding to a row. The number of columns
@@ -131,6 +137,13 @@ Optional group parameters:
    condition will be enforced on each site separately but the Wannier functions
    on different sites will not be orthogonal. If `NORMION = False`, the Wannier functions
    on different sites included in the group will be orthogonal to each other.
+*  **BANDS** (int int): the energy window specified by two ints: band index of 
+   lowest band and band index of highest band. Using this overrides the selection
+   in `EWINDOW`. 
+*  **COMPLEMENT** (True/False). If True, the orthogonal complement is calculated 
+   resulting in unitary (quadratic) projectors, i.e., the same number of orbitals
+   as bands. It is required to have an equal number of bands in the energy window
+   at each k-point. Default is False.
 
 
 .. _transformation_file:

doc/tutorials.rst

@@ -23,3 +23,12 @@ Full charge self consistency with Wien2k: :math:`\gamma`-Ce
 
    tutorials/ce-gamma-fscs_wien2k
 
+A full example with VASP: NiO
+-----------------------------------------------------------
+
+.. toctree::
+   :maxdepth: 2
+
+
+   tutorials/nio_csc
+

doc/tutorials/images_scripts/INCAR

@@ -0,0 +1,18 @@
+System  = NiO
+
+ISMEAR = -5
+
+# the energy window to optimize projector channels
+EMIN = -3
+EMAX = 7
+
+NBANDS = 16
+LMAXMIX = 6
+
+# switch off all symmetries
+ISYM = -1
+
+# project to Ni d and O p states
+LORBIT = 14
+LOCPROJ = 1 : d : Pr 1
+LOCPROJ = 2 : p : Pr 1

doc/tutorials/images_scripts/INCAR.rst

@@ -0,0 +1,7 @@
+.. _INCAR:
+
+INCAR
+-----------
+
+.. literalinclude:: INCAR
+   :language: bash

doc/tutorials/images_scripts/KPOINTS

@@ -0,0 +1,4 @@
+Automatically generated mesh
+       0
+Gamma
+ 6 6 6

doc/tutorials/images_scripts/KPOINTS.rst

@@ -0,0 +1,7 @@
+.. _KPOINTS:
+
+KPOINTS
+-----------
+
+.. literalinclude:: KPOINTS
+   :language: bash

doc/tutorials/images_scripts/NiO_local_lattice_GF.py

@@ -0,0 +1,90 @@
+from itertools import *
+import numpy as np
+import pytriqs.utility.mpi as mpi
+from pytriqs.archive import *
+from pytriqs.gf import *
+from triqs_dft_tools.sumk_dft import *
+from triqs_dft_tools.sumk_dft_tools import *
+from pytriqs.operators.util.hamiltonians import *
+from pytriqs.operators.util.U_matrix import *
+from triqs_cthyb import *
+import warnings
+warnings.filterwarnings("ignore", category=FutureWarning)
+
+filename = 'vasp'
+SK = SumkDFT(hdf_file = filename+'.h5', use_dft_blocks = False)
+
+beta = 5.0
+
+# We analyze the block structure of the Hamiltonian
+Sigma = SK.block_structure.create_gf(beta=beta)
+
+SK.put_Sigma([Sigma])
+G = SK.extract_G_loc()
+SK.analyse_block_structure_from_gf(G, threshold = 1e-3)
+
+
+# Setup CTQMC Solver
+n_orb = SK.corr_shells[0]['dim']
+spin_names = ['up','down']
+orb_names = [i for i in range(0,n_orb)]
+
+
+# Print some information on the master node
+iteration_offset = 0
+Sigma_iw = 0
+if mpi.is_master_node():
+    ar = HDFArchive(filename+'.h5','a')
+    if not 'DMFT_results' in ar: ar.create_group('DMFT_results')
+    if not 'Iterations' in ar['DMFT_results']: ar['DMFT_results'].create_group('Iterations')
+    if 'iteration_count' in ar['DMFT_results']: 
+        iteration_offset = ar['DMFT_results']['iteration_count']+1
+        print('offset',iteration_offset)
+        Sigma_iw = ar['DMFT_results']['Iterations']['Sigma_it'+str(iteration_offset-1)]
+        SK.dc_imp = ar['DMFT_results']['Iterations']['dc_imp'+str(iteration_offset-1)]
+        SK.dc_energ = ar['DMFT_results']['Iterations']['dc_energ'+str(iteration_offset-1)]
+        SK.chemical_potential = ar['DMFT_results']['Iterations']['chemical_potential'+str(iteration_offset-1)].real
+
+iteration_offset = mpi.bcast(iteration_offset)
+Sigma_iw = mpi.bcast(Sigma_iw)
+SK.dc_imp = mpi.bcast(SK.dc_imp)
+SK.dc_energ = mpi.bcast(SK.dc_energ)
+SK.chemical_potential = mpi.bcast(SK.chemical_potential)
+
+
+SK.put_Sigma(Sigma_imp = [Sigma_iw])
+
+ikarray = numpy.array(range(SK.n_k))
+
+# set up the orbitally resolved local lattice greens function:
+n_orbs = SK.proj_mat_csc.shape[2]
+spn = SK.spin_block_names[SK.SO]
+mesh = Sigma_iw.mesh
+block_structure = [range(n_orbs) for sp in spn]
+gf_struct = [(spn[isp], block_structure[isp])
+         for isp in range(SK.n_spin_blocks[SK.SO])]
+block_ind_list = [block for block, inner in gf_struct]
+glist = lambda: [GfImFreq(indices=inner, mesh=mesh)
+    for block, inner in gf_struct]
+
+G_latt_orb = BlockGf(name_list=block_ind_list,
+             block_list=glist(), make_copies=False)
+G_latt_orb.zero()
+
+for ik in mpi.slice_array(ikarray):
+    G_latt_KS = SK.lattice_gf(ik=ik, beta=beta)
+    G_latt_KS *= SK.bz_weights[ik]
+    for bname, gf in G_latt_orb:
+        add_g_ik = gf.copy()
+        add_g_ik.zero()
+        add_g_ik << SK.downfold(ik, 0, bname, G_latt_KS[bname], gf, shells='csc', ir=None)
+        gf << gf + add_g_ik
+        
+G_latt_orb << mpi.all_reduce(
+                mpi.world, G_latt_orb, lambda x, y: x + y)
+
+mpi.barrier()
+
+if mpi.is_master_node(): 
+    ar['DMFT_results']['Iterations']['G_latt_orb_it'+str(iteration_offset-1)] = G_latt_orb
+if mpi.is_master_node(): del ar

doc/tutorials/images_scripts/POSCAR

@@ -0,0 +1,10 @@
+NiO
+4.17  #taken from 9x9x9 with sigma=0.2 ismear=2
+ +0.0000000000  +0.5000000000  +0.5000000000 
+ +0.5000000000  +0.0000000000  +0.5000000000 
+ +0.5000000000  +0.5000000000  +0.0000000000 
+Ni O
+ 1 1
+Direct
+ +0.0000000000  +0.0000000000  +0.0000000000 
+ +0.5000000000  +0.5000000000  +0.5000000000 

doc/tutorials/images_scripts/POSCAR.rst

@@ -0,0 +1,7 @@
+.. _POSCAR:
+
+POSCAR
+-----------
+
+.. literalinclude:: POSCAR
+   :language: bash

doc/tutorials/images_scripts/converter.py

@@ -0,0 +1,3 @@
+from triqs_dft_tools.converters.vasp_converter import *
+Converter = VaspConverter(filename = 'nio')
+Converter.convert_dft_input()

doc/tutorials/images_scripts/converter.py.rst

@@ -0,0 +1,10 @@
+.. _converter.py:
+
+converter.py
+-------------------
+
+Download :download:`converter.py <./converter.py>`.
+
+
+.. literalinclude:: converter.py
+   :language: python

doc/tutorials/images_scripts/nio.py

@@ -0,0 +1,149 @@
+from itertools import *
+import numpy as np
+import pytriqs.utility.mpi as mpi
+from pytriqs.archive import *
+from pytriqs.gf import *
+from triqs_dft_tools.sumk_dft import *
+from triqs_dft_tools.sumk_dft_tools import *
+from pytriqs.operators.util.hamiltonians import *
+from pytriqs.operators.util.U_matrix import *
+from triqs_cthyb import *
+
+filename = 'vasp'
+
+SK = SumkDFT(hdf_file = filename+'.h5', use_dft_blocks = False)
+
+beta = 5.0 
+ 
+Sigma = SK.block_structure.create_gf(beta=beta)
+SK.put_Sigma([Sigma])
+G = SK.extract_G_loc()
+SK.analyse_block_structure_from_gf(G, threshold = 1e-3)
+for i_sh in range(len(SK.deg_shells)):
+    num_block_deg_orbs = len(SK.deg_shells[i_sh])
+    mpi.report('found {0:d} blocks of degenerate orbitals in shell {1:d}'.format(num_block_deg_orbs, i_sh))
+    for iblock in range(num_block_deg_orbs):
+        mpi.report('block {0:d} consists of orbitals:'.format(iblock))
+        for keys in SK.deg_shells[i_sh][iblock].keys():
+            mpi.report('  '+keys)
+
+# Setup CTQMC Solver
+
+n_orb = SK.corr_shells[0]['dim']
+spin_names = ['up','down']
+orb_names = [i for i in range(0,n_orb)]
+orb_hyb = False
+
+#gf_struct = set_operator_structure(spin_names, orb_names, orb_hyb)
+gf_struct = SK.gf_struct_solver[0]
+mpi.report('Sumk to Solver: %s'%SK.sumk_to_solver)
+mpi.report('GF struct sumk: %s'%SK.gf_struct_sumk)
+mpi.report('GF struct solver: %s'%SK.gf_struct_solver)
+
+S = Solver(beta=beta, gf_struct=gf_struct)
+
+# Construct the Hamiltonian and save it in Hamiltonian_store.txt
+H = Operator() 
+U = 8.0
+J = 1.0
+
+
+U_sph = U_matrix(l=2, U_int=U, J_hund=J)
+U_cubic = transform_U_matrix(U_sph, spherical_to_cubic(l=2, convention=''))
+Umat, Upmat = reduce_4index_to_2index(U_cubic)
+
+H = h_int_density(spin_names, orb_names, map_operator_structure=SK.sumk_to_solver[0], U=Umat, Uprime=Upmat)
+
+# Print some information on the master node
+mpi.report('Greens function structure is: %s '%gf_struct)
+mpi.report('U Matrix set to:\n%s'%Umat)
+mpi.report('Up Matrix set to:\n%s'%Upmat)
+
+# Parameters for the CTQMC Solver
+p = {}
+p["max_time"] = -1
+p["random_name"] = ""
+p["random_seed"] = 123 * mpi.rank + 567
+p["length_cycle"] = 100
+p["n_warmup_cycles"] = 20000
+p["n_cycles"] = 200000
+p["fit_max_moment"] = 4
+p["fit_min_n"] = 30
+p["fit_max_n"] = 50
+p["perform_tail_fit"] = True
+
+# Double Counting: 0 FLL, 1 Held, 2 AMF
+DC_type = 0
+
+# Prepare hdf file and and check for previous iterations
+n_iterations = 10
+
+iteration_offset = 0
+if mpi.is_master_node():
+    ar = HDFArchive(filename+'.h5','a')
+    if not 'DMFT_results' in ar: ar.create_group('DMFT_results')
+    if not 'Iterations' in ar['DMFT_results']: ar['DMFT_results'].create_group('Iterations')
+    if 'iteration_count' in ar['DMFT_results']: 
+        iteration_offset = ar['DMFT_results']['iteration_count']+1
+        S.Sigma_iw = ar['DMFT_results']['Iterations']['Sigma_it'+str(iteration_offset-1)]
+        SK.dc_imp = ar['DMFT_results']['Iterations']['dc_imp'+str(iteration_offset-1)]
+        SK.dc_energ = ar['DMFT_results']['Iterations']['dc_energ'+str(iteration_offset-1)]
+        SK.chemical_potential = ar['DMFT_results']['Iterations']['chemical_potential'+str(iteration_offset-1)].real
+
+iteration_offset = mpi.bcast(iteration_offset)
+S.Sigma_iw = mpi.bcast(S.Sigma_iw)
+SK.dc_imp = mpi.bcast(SK.dc_imp)
+SK.dc_energ = mpi.bcast(SK.dc_energ)
+SK.chemical_potential = mpi.bcast(SK.chemical_potential)
+
+# Calc the first G0
+SK.put_Sigma(Sigma_imp = [S.Sigma_iw])
+SK.calc_mu(precision=0.01)
+S.G_iw << SK.extract_G_loc()[0]
+SK.symm_deg_gf(S.G_iw, orb=0)
+
+#Init the DC term and the self-energy if no previous iteration was found
+if iteration_offset == 0:
+    dm = S.G_iw.density()
+    SK.calc_dc(dm, U_interact=U, J_hund=J, orb=0, use_dc_formula=DC_type)
+    S.Sigma_iw << SK.dc_imp[0]['up'][0,0]
+
+mpi.report('%s DMFT cycles requested. Starting with iteration %s.'%(n_iterations,iteration_offset))
+
+# The infamous DMFT self consistency cycle
+for it in range(iteration_offset, iteration_offset + n_iterations):
+    
+    mpi.report('Doing iteration: %s'%it)
+    
+    # Get G0
+    S.G0_iw << inverse(S.Sigma_iw + inverse(S.G_iw))
+    # Solve the impurity problem
+    S.solve(h_int = H, **p)
+    if mpi.is_master_node(): 
+        ar['DMFT_results']['Iterations']['Gimp_it'+str(it)] = S.G_iw
+        ar['DMFT_results']['Iterations']['Gtau_it'+str(it)] = S.G_tau
+        ar['DMFT_results']['Iterations']['Sigma_uns_it'+str(it)] = S.Sigma_iw
+    # Calculate double counting
+    dm = S.G_iw.density()
+    SK.calc_dc(dm, U_interact=U, J_hund=J, orb=0, use_dc_formula=DC_type)
+    # Get new G
+    SK.symm_deg_gf(S.Sigma_iw,orb=0)
+    SK.put_Sigma(Sigma_imp=[S.Sigma_iw])
+    SK.calc_mu(precision=0.01)
+    S.G_iw << SK.extract_G_loc()[0]
+    
+    # print densities
+    for sig,gf in S.G_iw:
+        mpi.report("Orbital %s density: %.6f"%(sig,dm[sig][0,0]))
+    mpi.report('Total charge of Gloc : %.6f'%S.G_iw.total_density())
+
+    if mpi.is_master_node(): 
+        ar['DMFT_results']['iteration_count'] = it
+        ar['DMFT_results']['Iterations']['Sigma_it'+str(it)] = S.Sigma_iw
+        ar['DMFT_results']['Iterations']['Gloc_it'+str(it)] = S.G_iw
+        ar['DMFT_results']['Iterations']['G0loc_it'+str(it)] = S.G0_iw
+        ar['DMFT_results']['Iterations']['dc_imp'+str(it)] = SK.dc_imp
+        ar['DMFT_results']['Iterations']['dc_energ'+str(it)] = SK.dc_energ
+        ar['DMFT_results']['Iterations']['chemical_potential'+str(it)] = SK.chemical_potential
+
+if mpi.is_master_node(): del ar

doc/tutorials/images_scripts/nio.py.rst

@@ -0,0 +1,9 @@
+.. _nio.py:
+
+nio.py
+-----------
+
+Download :download:`nio.py <./nio.py>`.
+
+.. literalinclude:: nio.py
+   :language: python

doc/tutorials/images_scripts/plo.cfg

@@ -0,0 +1,27 @@
+[General]
+BASENAME = nio
+DOSMESH = -21 55 400
+
+[Group 1]
+SHELLS = 1 2
+EWINDOW = -9 2
+NORMION = False
+NORMALIZE = True
+
+[Shell 1] # Ni d shell
+LSHELL = 2
+IONS = 1
+CORR = True
+TRANSFORM = 1.0  0.0  0.0  0.0  0.0
+            0.0  1.0  0.0  0.0  0.0
+            0.0  0.0  1.0  0.0  0.0
+            0.0  0.0  0.0  1.0  0.0
+            0.0  0.0  0.0  0.0  1.0
+
+[Shell 2] # O p shell
+LSHELL = 1
+IONS = 2
+CORR = False
+TRANSFORM = 1.0  0.0  0.0
+            0.0  1.0  0.0
+            0.0  0.0  1.0

doc/tutorials/images_scripts/plo.cfg.rst

@@ -0,0 +1,9 @@
+.. _plo.cfg:
+
+plo.cfg
+-----------
+
+Download :download:`plo.cfg<./plo.cfg>`.
+
+.. literalinclude:: plo.cfg
+   :language: bash

doc/tutorials/nio_csc.rst

@@ -0,0 +1,59 @@
+.. _nio_csc:
+
+DFT and projections
+==================================================
+
+We will perform charge self-consitent DFT+DMFT calcluations for the charge-transfer insulator NiO. We still start from scratch and provide all necessary input files to do the calculations.
+
+VASP setup
+-------------------------------
+We start by running a simple VASP calculation to converge the charge density initially.
+Use the :ref:`INCAR`, :ref:`POSCAR`, and :ref:`KPOINTS` provided and use your 
+own :file:`POTCAR` file.
+
+Let us take a look in the :file:`INCAR`, where we have to specify local orbitals as basis 
+for our many-body calculation.
+
+.. literalinclude:: images_scripts/INCAR
+
+`LORBIT = 14` takes care of optimizing the projectors in the energy window defined
+by `EMIN` and `EMAX`. We switch off all symmetries with `ISYM=-1` since symmetries
+are not implemented in the later DMFT scripts. Finally, we select the relevant orbitals
+for atom 1 (Ni, d-orbitals) and 2 (O, p-orbitals) by the two `LOCPROJ` lines.
+For details refer to the VASP wiki on the `LOCPROJ <https://cms.mpi.univi
+e.ac.at/wiki/index.php/LOCPROJ>`_ flag. The projectors are stored in the file `LOCPROJ`.
+
+
+plovasp
+------------------------------
+Next, we postprocess the projectors, which VASP stored in the file `LOCPROJ`.
+We do this by invoking :program:`plovasp plo.cfg` which is configured by an input file, e.g., named :ref:`plo.cfg`.
+
+.. literalinclude:: images_scripts/plo.cfg
+
+Here, in `[General]' we set the basename and the grid for calculating the density of
+states. In `[Group 1]` we define a group of two shells which are orthonormalized with
+respect to states in an energy window from `-9` to `2` for all ions simultanously
+(`NORMION = False`). We define the two shells, which correspond to the Ni d states
+and the O p states. Only the Ni shell is treated as correlated (`CORR = True`), i.e.,
+is supplemented with a Coulomb interaction later in the DMFT calculation.
+
+Converting to hdf5 file
+-------------------------------
+We gather the output generated by :program:`plovasp` into a hdf5 archive which :program:`dft_tools` is able to read. We do this by running :program:`python converter.py` on the script :ref:`converter.py`:
+
+.. literalinclude:: images_scripts/converter.py
+
+Now we are all set to perform a dmft calculation.
+
+DMFT
+==================================================
+
+dmft script
+------------------------------
+
+Since the python script for performing the dmft loop pretty much resembles that presented in the tutorial on :ref:`srvo3`, we will not go into detail here but simply provide the script :ref:`nio.py`. Following Kunes et al. in `PRB 75 165115 (2007) <https://journals.aps.org/prb/abstract/10.1103/PhysRevB.75.165115>`_ we use :math:`U=8` and :math:`J=1`. Here, we use :math:`\beta=5` instead of :math:`\beta=10` to speed up the calculations.
+
+Local lattice Green's function for all projected orbitals
+----------------------
+We calculate the local lattice Green's function - now also for the uncorrelated orbitals, i.e., the O p states. Therefor we use :download:`NiO_local_lattice_GF.py <images_scripts/NiO_local_lattice_GF.py`

python/converters/vasp_converter.py

@@ -381,7 +381,7 @@ class VaspConverter(ConverterTools):
                           'symm_op','n_shells','shells','n_corr_shells','corr_shells','use_rotations','rot_mat',
                           'rot_mat_time_inv','n_reps','dim_reps','T','n_orbitals','proj_mat','bz_weights','hopping',
                           'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr','proj_or_hk']
-            if self.proj_or_hk == 'hk':
+            if self.proj_or_hk == 'hk' or True:
                 things_to_save.append('proj_mat_csc')
             for it in things_to_save: ar[self.dft_subgrp][it] = locals()[it]
 

python/sumk_dft.py

@@ -97,13 +97,13 @@ class SumkDFT(object):
             # Read input from HDF:
             things_to_read = ['energy_unit', 'n_k', 'k_dep_projection', 'SP', 'SO', 'charge_below', 'density_required',
                               'symm_op', 'n_shells', 'shells', 'n_corr_shells', 'corr_shells', 'use_rotations', 'rot_mat',
-                              'rot_mat_time_inv', 'n_reps', 'dim_reps', 'T', 'n_orbitals', 'proj_mat', 'bz_weights', 'hopping',
+                              'rot_mat_time_inv', 'n_reps', 'dim_reps', 'T', 'n_orbitals', 'proj_mat', 'proj_mat_csc', 'bz_weights', 'hopping',
                               'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr','proj_or_hk']
             self.subgroup_present, self.value_read = self.read_input_from_hdf(
                 subgrp=self.dft_data, things_to_read=things_to_read)
-            if self.proj_or_hk == 'hk':
-                self.subgroup_present, self.value_read = self.read_input_from_hdf(
-                subgrp=self.dft_data, things_to_read=['proj_mat_csc'])
+           # if self.proj_or_hk == 'hk':
+           #     self.subgroup_present, self.value_read = self.read_input_from_hdf(
+           #     subgrp=self.dft_data, things_to_read=['proj_mat_csc'])
             if self.symm_op:
                 self.symmcorr = Symmetry(hdf_file, subgroup=self.symmcorr_data)