diff --git a/AUTHORS.txt b/AUTHORS.txt index 820b55e1..91fed75e 100644 --- a/AUTHORS.txt +++ b/AUTHORS.txt @@ -1,6 +1,7 @@ Markus Aichhorn Michel Ferrero Alexander Hampel +Alyn James Gernot Kraberger Olivier Parcollet Oleg Peil diff --git a/doc/about.rst b/doc/about.rst index 79519de8..f221f1e9 100644 --- a/doc/about.rst +++ b/doc/about.rst @@ -17,7 +17,7 @@ of full charge self-consistency [#dft_tools2]_, necessary for total energy calculations. The package at hand is fully implemented as an application based on the TRIQS library [#dft_tools3]_. -**Developers**: M. Aichhorn, L. Pourovskii, P.Seth, V. Vildosola, M. Zingl, O. E. Peil, X. Deng, J. Mravlje, G. Kraberger, C. Martins, M. Ferrero, O. Parcollet +**Developers**: M. Aichhorn, L. Pourovskii, A. Hampel, P.Seth, V. Vildosola, M. Zingl, O. E. Peil, X. Deng, J. Mravlje, G. Kraberger, A. James, C. Martins, M. Ferrero, O. Parcollet **Related papers**: diff --git a/doc/guide/conv_elk.rst b/doc/guide/conv_elk.rst new file mode 100644 index 00000000..f7e93346 --- /dev/null +++ b/doc/guide/conv_elk.rst @@ -0,0 +1,189 @@ +.. _convElk: + +Interface with Elk +===================== + +This is the first iteration of the Elk-TRIQS interface, so certain inputs may change in later updates. The Elk part of the interface is not currently in the main distribution, but it can be found :ref:`here `. + +We assume that the user has obtained a self-consistent solution of the +Kohn-Sham equations with Elk (a full tutorial can be found here :ref:`Elk SVO tutorial `). Also, the user needs to be familiar with the main in/output files of Elk, and how to run +the DFT code. Further information about Elk can be found on the :ref:`official Elk website `. + +Conversion for the DMFT self-consistency cycle +---------------------------------------------- + +Once the user has obtained the groundstate calculation, they will have to rerun Elk but with some small changes to the inputs in the elk.in file which will be explained below. The Elk part of the interface calculates and outputs the Wannier projectors. All downfolding related flags are set in the elk input file, and Elk determines automatically by symmetry equivalent sites. The TRIQS Elk converter then reads in these projectors along with the other Elk ascii files which would have been generated in the Elk ground state calculation. This information is then packed into the HDF5 file. + +In the following, we use SrVO3 as an example to explain the flags required in the elk.in input file. An example elk.in of SrVO3 is available in the :ref:`SrVO3 tutorial `. + +.. literalinclude:: ../tutorials/images_scripts/elk.in_SVO + + +The projectors are generated in Elk using these alterations in the elk.in file:: + + task + 805 + + wanproj + 1 !1) number of projector species + 2 2 3 !2) species number, l value and lm submatrix size + 7 8 9 !3) cubic harmonic lm indices + -0.055 0.07 !4) Correlated energy window in Hartrees (this is [-1.5, 1.9] in eV) + +The first flag "task" specifies Elk to do the Wannier projector calculation in the Elk input convention. The "wanproj" flag specifies the information needed to generate the desired projectors (the exclamation marks are comment flags in Fortran). Below gives the meaning of each line: + +#. The number of different species to generate the projectors for. If the material has multiple atoms of the same species, then the projectors will be generated for all of these atoms. Information about whether these atoms are symmetrically equivalent is written to the PROJ.OUT file. Generating projectors for multiple species requires lines 2) and 3) to be repeated for each projector species. +#. The desired species index (relative to the order of the "atoms" input in elk.in), the l value and the number of wanted lm orbitals for the projectors. +#. The lm indices (in the cubic harmonics by default) where lm = 1 refers to the s orbital, lm = 2,3,4 refers to the p orbitals, lm = 5,6,7,8,9 refers to the d orbitals and finally lm = 10,11,12,13,14,15,16 refers to the f orbitals. In the example above, this specifies that we want the t2g orbitals which has size 3 [last number in line 2)] and the lm indices are 7, 8 and 9 as specified in line 3). If, on the other hand, the user wishes to use all of the d-orbitals then all 5 orbital indices need to be included along with specifying that all 5 orbitals will be used [at the end of line 2)]. +#. The correlated energy window (in Hartree) to generate the projectors within. + +It should be noted that the indices in line 3) will change if another lm basis is used. +The default is the cubic harmonic basis. The flags in elk.in required to change the spherical harmonic basis are:: + + cubic + .true. + + lmirep + .true. + +Above are the default inputs. If both of these flags are set to .false., the projectors will be generated in the complex spherical harmonic basis. It is possible to generate the projectors in Elk's irreducible basis by setting cubic to .false., but this is experimental and the TRIQS side of the interface is +currently unable to convert the projectors in that basis. Finally, these projectors are written to file in the complex spherical harmonic basis. + +.. _Elk_files: + +The rest of the elk.in file can remain unchanged. This 805 task calculates the projectors which are written into the WANPROJ_L**_S**_A****.OUT file(s). Along with this, the other written file (PROJ.OUT) specficies some information about the projectors (like atom equivalency, lm indices and so on) needed for reading the files into the TRIQS library. The PROJ.OUT file contains comments about its outputs. Here's a list of all of the input files needed for this part of the TRIQS converter: + +#. WANPROJ_L**_S**_A****.OUT - file containing the projectors and band window indices. +#. PROJ.OUT - specficies some information about the projectors. + (like atom equivalency, lm indices and so on) needed for reading into the TRIQS library. +#. EIGVAL.OUT - contains the energies and latice vector coordinates for each k-point. +#. EFERMI.OUT - contains the Fermi energy. +#. KPOINTS.OUT - contains the k-point weights and lattice vectors. +#. SYMCRYS.OUT - has the crystal symmetries used for symmetries observables. +#. LATTICE.OUT - has lattice-Cartesian basis transformation matrices. +#. GEOMETRY.OUT - file with the lattice positions of every atom of each species. + +Moreover, the Wannier charge density matrix (in WANCHARGE.OUT) and the Wannier spectral function (in WANSF_L**_S**_A****_0*.OUT) are calculated. These files are not used in the interface. + +As a side note, there are two other tasks which also generate the Wannier projectors. Task 804 generates the same outputs as 805 except it doesn't calculate the Wannier charge and spectral function. Task 806 outputs the same information as 805, but it generates the projectors (and other k-dependent variables) on a different user defined ngridk mesh. These tasks are parallelized with both OpenMP and MPI. + +The Elk outputs are read into the TRIQS library using the following lines:: + + from triqs_dft_tools.converters.elk import * + Converter = ElkConverter(filename=filename, repacking=True) + Converter.convert_dft_input() + +The first two lines import and load the Elk converter module and the last line executes the conversion into the filename.h5 HDF5 file. + + +Data for post-processing - Correlated Spectral functions +-------------------------------------------------------- + +In case you want to do post-processing of your data using the module :class:`SumkDFTTools `, some more files have to be converted to the HDF5 archive. Some of this has been laid out in :ref:`analysis`, but the Elk specific functions are described in the following sections. Below, we will discuss how to input the information for correlated spectral functions (band structures) and which is then calculated using "spaghettis" in :ref:`analysis`. However, band character band structure plots have not yet been implemented. + +In Elk, the elk.in requires the altered flag:: + + task + 820 + +As well as the wanproj flag (which has be discussed previously) and the plot1d flag (refer to the Elk manual). The new output files of this task required for the interface are: + +#. BAND.OUT - the energy eigenvalues along the user specified path. +#. PROJ_WANBAND.OUT - same as PROJ.OUT but for band structure projectors +#. WANPROJ_L**_S**_A****_WANBAND.OUT - same as WANPROJ_L**_S**_A****.OUT + but for band structure projectors. + +(The ascii output files which have the new extension of _WANBAND.OUT are specific for this post processing calculation.) + +The band structure information is converted into TRIQS by using:: + + Converter.convert_bands_input() + +Spectral function from Elk inputs +--------------------------------- + +Elk does not calculate the theta projectors for partial DOS calculations. Instead, Elk outputs the band characters into the file BC.OUT when using the elk.in task:: + + task + 803 + +The contents of BC.OUT need to be converted into the HDF5 file by using the Elk Converter module:: + + from triqs_dft_tools.converters.elk import * + Converter = ElkConverter(filename=filename, repacking=True) + Converter.dft_band_characters() + +Once these have been saved to the HDF5 file (called "filename" here), the spectral function can be calculated with:: + + SK.elk_dos(broadening=0.0, with_Sigma=True, with_dc=True, pdos=False, nk=None) + +This outputs the total spectral function and the partial spectral function if enabled. Most of the user inputs are similar to the "SK.dos_parproj_basis()" module in :ref:`analysis`. The "pdos" flag when "True" enables the partial dos of each lm value to be calculated. It should be noted that these band characters are in Elk's irreducible lm basis and as such, the user has to check the irreducible representation used in Elk. This information can be found in the file ELMIREP.OUT after running task 10 (the DOS calculating task). The "nk" flag enables the calculation of the occupied spectral funciton. Here, nk needs to be the occupation density matrix (calculated from integrating the Green's function on the Matsubara axis) in the Bloch basis. This input needs to be in the same format as the occupation density matrix "deltaN" calculated in the sumk_DFT.calc_density_correction(dm_type='elk') module. + + +Spectral function Contour Plots (Fermi Surfaces) from Elk inputs +--------------------------------------------------------------- + +Here, we will discuss how to plot the Fermi surface contour or any other non-zero omega spectral function contour plot. This is currently tailored for the Elk inputs. From this point, we will refer to these contours as Fermi surfaces. The energy eigenvalues, projectors and so on required for the Fermi surface plot needs to be outputed from Elk. This is done by using:: + + task + 807 + +in Elk, but unlike the previous Elk interface tasks, the k-mesh grid needs to be specified. This is done like using the same inputs as the Fermi surface calculations in Elk. In Elk, The user needs to specify the "plot3d" input flag used to generate the k-mesh which the interface variables are evaluated on. A simple example is for SrVO3 where plot3d would look something like:: + + plot3d + 0.0 0.0 0.0 !1) origin + 1.0 0.0 0.0 !2) vertex 1 + 0.0 1.0 0.0 !3) vertex 2 + 0.0 0.0 1.0 !4) vertex 3 + 32 32 32 !5) k-mesh grid size + +Lines 1) to 4) specifies the corners (in lattice coordinates) of the k-grid box and line 5) is the grid size in each direction (see the Elk manual). If the user desires to plot a 2D plane, then the user should define the plane using lines 2) and 3) [relative to line 1)] and define line 4) to be the cross-product of lines 2) and 3) [i.e. the vector in line 4) is normal to the 2D plane]. The outputs will be in terms of the k-dependent quantities in the irreducible Brillouin zone (IBZ). The files needed for the interface are: + +#. EIGVAL_FS.OUT - same as EIGVAL.OUT but the output is of the Fermi surface calculation. +#. KPOINT_FS.OUT - same as KPOINT.OUT but the output is of the Fermi surface calculation. +#. PROJ_FS.OUT - same as PROJ.OUT but the output is of the Fermi surface calculation. +#. WANPROJ_L**_S**_A****_FS.OUT - same as WANPROJ_L**_S**_A****.OUT but the output is of the Fermi surface calculation. +#. EFERMI.OUT - contains the Fermi energy. +#. SYMCRYS.OUT - has the crystal symmetries used for symmetries observables. +#. LATTICE.OUT - has lattice-Cartesian basis transformation matrices. + +(The ascii output files which have the extension of _FS.OUT are specific for this post processing calculation.) + +These outputs are converted to the HDF5 file by:: + + from triqs_dft_tools.converters.elk import * + Converter = ElkConverter(filename=filename, repacking=True) + Converter.convert_fs_input() + +The spectral function for the Fermi surface plots are calculated with:: + + SK.fs_plot(broadening=0.0, mesh=None, FS=True, plane=True, sym=True, orthvec=None, with_Sigma=True, with_dc=True) + +The new flags specify the following: + +#. "FS" - determines whether the output will be the Fermi surface and uses the closest omega value to 0.0 in the mesh. +#. "plane" - required to specify whether the Elk input parameters were generated on a k-mesh plane. +#. "sym" - needed if the IBZ will be folded out by using symmetry operations. +#. "orthvec" - (numpy array of length 3) needs to be specified if using "plane" as this input is the orthonormal vector to the 2D plane required for the folding out process. + +To give the user a range of output capabilities, This routine can be used in the following ways: + +#. If using "with_Sigma", the mesh will be the same as the self-energy. However, by setting FS=False, the user can input a mesh option if they desire the "Fermi surface" plots for each omega value (commensurate with the self-energy mesh) within the input range. + +#. If the user is generating the DFT Spectral function plot (i.e. with_Sigma and with_dc both set to False), a mesh needs to be specified if FS=False. This function will output the spectral functions for the input mesh. Otherwise if FS is True, this would return the spectral function at omega=0.0. + +The output files will have the form of "Akw_FS_X.dat" (X being either up, down or ud) if FS=True or "Akw_X_omega_Y.dat" (Y being the omega mesh index) otherwise. The latter file will have the omega values within the file (the fourth column). The first three columns of both output file types specifies the cartesian lattice vector (kx, ky, kz) and the last column is the spectral function values. + + +DFT+DMFT wavefunction dependent quantities +------------------------------------------ + +The DFT+DMFT wavefunctions and occupations are generated in Elk by diagonalizing the full DFT+DMFT density matrix at each k-point during task 808. These are used to update the electron density which is then used to solve the Kohn-Sham equations once to complete a FCSC DFT+DMFT cycle. It is possible to calculate quantities which are solely dependent on the wavefunctions and occupations by using the aforementioned diagonalized set. After generating the DMATDMFT.OUT file, these diagonalized wavefunctions and occupations are calculated by amending elk.in with the new task:: + + task + 809 + +This will write the new second variational eigenvectors and occupations in the EVECSV.OUT and OCCSV.OUT binary files respectively. Then the wavefunction dependent quantities implemented within Elk can be calculated using these DFT+DMFT wavefunctions and occupations. Note that this only works for energy independent quantities. Also, the user has to ensure that the second variational eigenvectors will be used in determining the wavefunction dependent quantities. This is done by looking for the variable "tevecsv" in init0.f90 of Elk's source code and making sure that this is set to .true. for the task number the user wishes to use. + + + diff --git a/doc/guide/conversion.rst b/doc/guide/conversion.rst index 7e5065d6..68478843 100644 --- a/doc/guide/conversion.rst +++ b/doc/guide/conversion.rst @@ -7,8 +7,8 @@ The first step for a DMFT calculation is to provide the necessary input based on a DFT calculation. We will not review how to do the DFT calculation here in this documentation, but refer the user to the documentation and tutorials that come with the actual DFT -package. At the moment, there are two full charge self consistent interfaces, for the -Wien2k and the VASP DFT packages, resp. In addition, there is an interface to Wannier90, as well +package. At the moment, there are three full charge self consistent interfaces, for the +Wien2k, VASP and Elk DFT packages, resp. In addition, there is an interface to Wannier90, as well as a light-weight general-purpose interface. In the following, we will describe the usage of these conversion tools. @@ -17,6 +17,7 @@ conversion tools. conv_wien2k conv_vasp + conv_elk conv_W90 conv_generalhk diff --git a/doc/guide/dftdmft_selfcons.rst b/doc/guide/dftdmft_selfcons.rst index 6e4db995..906372ee 100644 --- a/doc/guide/dftdmft_selfcons.rst +++ b/doc/guide/dftdmft_selfcons.rst @@ -180,6 +180,36 @@ To understand the difference please make sure to read `ISTART flag VASP wiki `NELMIN` ensure that VASP does not terminate after the default number of iterations of 60. + +Elk +--------- + +The Elk CSC implementation is fairly similar to the Wien2k implementation. At the end of the :ref:`DMFT python script `, the density matrix in Bloch space needs to be calculated along with the correlation energy. This is written to DMATDMFT.OUT. An example of this (using the Migdal correlation energy formula) is given below:: + + #output the density matrix for Elk interface + dN, d = SK.calc_density_correction(dm_type='elk') + #correlation energy via the Migdal formula + correnerg = 0.5 * (S.G_iw * S.Sigma_iw).total_density() + #subtract the double counting energy + correnerg -= SK.dc_energ[0] + #convert to Hartree + correnerg = correnerg/SK.energy_unit + #save the correction to energy + if (mpi.is_master_node()): + f=open('DMATDMFT.OUT','a') + f.write("%.16f\n"%correnerg) + f.close() + +To read this into Elk and update the electron density, run task 808. So elk.in is amended with the following:: + + task + 808 + +This solves the Kohn-Sham equations once with the updated electron density and outputs the new set of energy eigenvalues and wavefunctions. To start the next fully charge self-consistent DFT+DMFT cycle (FCSC), a new set of projectors need to be generated (using task 805) and the whole procedure continues until convergence. The Elk potential rms value for each FCSC DFT+DMFT cycle is given in DMFT_INFO.OUT. An extensive example for SrVO:math:`_3` can be found here: :ref:`Elk SVO tutorial `. + +This FCSC method should be universal irrespective to what type of ground state calculation performed. However, not all types of ground state calculations have been tested. + + Other DFT codes --------------- diff --git a/doc/guide/soc.rst b/doc/guide/soc.rst index 47356af6..56a43f22 100644 --- a/doc/guide/soc.rst +++ b/doc/guide/soc.rst @@ -14,15 +14,18 @@ The second variant is a bit more involved and needs quite some expertise, so thi Treatment of SOC in DFT ----------------------- -For now, TRIQS/DFTTools does only work with Wien2k when performing calculations with SO. +For now, TRIQS/DFTTools does only work with Wien2k and Elk when performing calculations with SO. The treatment of SOC in the VASP package is fundamentally different to the way Wien2k treats it, and the interface does not handle that at the moment. -Therefore, this guide describes how to do an SOC calculation using the Wien2k DFT package. +Therefore, this guide describes how to do an SOC calculation using the Wien2k and Elk DFT packages. + +Treatment of SOC in Wien2k +-------------------------- First, a Wien2k calculation including SOC has to be performed. For details, we refer the reader to the `documentation of Wien2k `_ . As a matter of fact, we need the output for the DFT band structure for both spin directions explicitly. That means that one needs to do a spin-polarised DFT calculation with SOC, but, however, with magnetic moment set to zero. In the Wien2k initialisation procedure, one can choose for the option -nom when ``lstart`` is called. This means that the charge densities are initialised without magnetic splitting. The SOC calculation is then performed in a standard way as described in the Wien2k manual. -Performing the projection -~~~~~~~~~~~~~~~~~~~~~~~~~ +Performing the projection in Wien2k +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Note that the final ``x lapw2 -almd -so -up`` and ``x lapw2 -almd -so -dn`` have to be run *on a single core*, which implies that, before, ``x lapw2 -up``, ``x lapw2 -dn``, and ``x lapwso -up`` have to be run in single-core mode (at least once). @@ -33,6 +36,13 @@ As usual, it is important to check for warnings (e.g., about eigenvalues of the Note that in presence of SOC, it is not possible to project only onto the :math:`t_{2g}` subshell because it is not an irreducible representation. +Treatment of SOC in Elk +------------------------- + +First, a Elk calculation including SOC has to be performed. For details, we refer the reader to the SOC Elk examples in Elk's example directory and `Elk manual `_ for further information about the input flags. Then the projectors can be generated using the ``wanproj`` input flag in the same format as in :ref:`conv_elk`. Like in Wien2k, you cannot project only onto the :math:`t_{2g}` subshell because it is not an irreducible representation in SOC calculations. + +After generating the projectors +------------------------------- We strongly suggest using the :py:meth:`.dos_wannier_basis` functionality of the :py:class:`.SumkDFTTools` class (see :download:`calculate_dos_wannier_basis.py `) and compare the Wannier-projected orbitals to the original DFT DOS (they should be more or less equal). Note that, with SOC, there are usually off-diagonal elements of the spectral function, which can also be imaginary. @@ -40,4 +50,4 @@ The imaginary part can be found in the third column of the files ``DOS_wann_...` After the projection, one can proceed with the DMFT calculation. However, two things need to be noted here. First, since the spin is not a good quantum number any more, there are off-diagonal elements in the hybridisation function and the local Hamiltonian coupling the two spin directions. This will eventually lead to a fermonic sign problem when QMC is used as a impurity solver. Second, although the :math:`e_{g}` subshell needs to be included in the projection, it can in many cases be neglected in the solution of the Anderson impurity model, after a transformation to a rotated local basis is done. This basis, diagonalising the local Hamiltonian in the presence of SOC, is often called the numerical j-basis. How rotations are performed is described in :ref:`basisrotation`, and the cutting of the orbitals in :ref:`blockstructure`. -A DMFT calculation including SOC for Sr2MgOsO6 is included in the :ref:`tutorials`. +A DMFT calculation including SOC for Sr2MgOsO6 using Wien2k is included in the :ref:`tutorials`. diff --git a/doc/reference/converters.rst b/doc/reference/converters.rst index ba448810..3dd80215 100644 --- a/doc/reference/converters.rst +++ b/doc/reference/converters.rst @@ -58,6 +58,24 @@ VASP Converter :special-members: +Elk Converter +------------------- +.. _refElkconverter: +.. autoclass:: triqs_dft_tools.converters.elk.ElkConverter + :members: + :special-members: + +Elk Tools +------------------- +.. _refElkTools: +.. autoclass:: triqs_dft_tools.converters.elktools.ElkConverterTools + :members: + :special-members: + +.. autoclass:: triqs_dft_tools.converters.elktools.readElkfiles + :members: + :special-members: + Converter Tools --------------- .. autoclass:: triqs_dft_tools.converters.converter_tools.ConverterTools diff --git a/doc/tutorials.rst b/doc/tutorials.rst index 8342013c..bf1d4dd0 100644 --- a/doc/tutorials.rst +++ b/doc/tutorials.rst @@ -60,3 +60,16 @@ Complex example: NiO tutorials/nio_csc + + +Elk interface examples +----------------------- + +Converter example: SrVO3 +"""""""""""""""""""""""" + +.. toctree:: + :maxdepth: 2 + + tutorials/svo_elk/srvo3 + diff --git a/doc/tutorials/svo_elk/dft_dmft_cthyb_elk.py b/doc/tutorials/svo_elk/dft_dmft_cthyb_elk.py new file mode 100644 index 00000000..adc04ac6 --- /dev/null +++ b/doc/tutorials/svo_elk/dft_dmft_cthyb_elk.py @@ -0,0 +1,165 @@ +import triqs.utility.mpi as mpi +from triqs.operators.util import * +from h5 import HDFArchive +from triqs_cthyb import * +from triqs.gf import * +from triqs_dft_tools.sumk_dft import * +from triqs_dft_tools.converters.elk import * + +dft_filename='SrVO3' +beta = 40 +loops = 2 # Number of DMFT sc-loops +sigma_mix = 1.0 # Mixing factor of Sigma after solution of the AIM +use_blocks = True # use bloc structure from DFT input +prec_mu = 0.0001 +h_field = 0.0 + + +# Solver parameters +p = {} +p["max_time"] = -1 +p["length_cycle"] = 200 +p["n_warmup_cycles"] = 10000 +p["n_cycles"] = 1000000 +p["perform_tail_fit"] = True +p["fit_max_moment"] = 4 +p["fit_min_n"] = 30 +p["fit_max_n"] = 60 + +# If conversion step was not done, we could do it here. Uncomment the lines it you want to do this. +Converter = ElkConverter(filename=dft_filename, repacking=True) +Converter.convert_dft_input() +mpi.barrier() + +previous_runs = 0 +previous_present = False +if mpi.is_master_node(): + with HDFArchive(dft_filename+'.h5','a') as f: + if 'dmft_output' in f: + ar = f['dmft_output'] + if 'iterations' in ar: + previous_present = True + previous_runs = ar['iterations'] + else: + f.create_group('dmft_output') +previous_runs = mpi.bcast(previous_runs) +previous_present = mpi.bcast(previous_present) + +SK=SumkDFT(hdf_file=dft_filename+'.h5',use_dft_blocks=use_blocks,h_field=h_field) + +n_orb = SK.corr_shells[0]['dim'] +l = SK.corr_shells[0]['l'] +spin_names = ["up","down"] +orb_names = [i for i in range(n_orb)] + +## KANAMORI DENSITY-DENSITY (for full Kanamori use h_int_kanamori) +# Define interaction paramters, DC and Hamiltonian +U = 4.0 +J = 0.65 +dc_type = 1 # DC type: 0 FLL, 1 Held, 2 AMF +# Construct U matrix for density-density calculations +Umat, Upmat = U_matrix_kanamori(n_orb=n_orb, U_int=U, J_hund=J) +# Construct density-density Hamiltonian +h_int = h_int_density(spin_names, orb_names, map_operator_structure=SK.sumk_to_solver[0], U=Umat, Uprime=Upmat) + +## SLATER HAMILTONIAN +## Define interaction paramters, DC and Hamiltonian +#U = 9.6 +#J = 0.8 +#dc_type = 0 # DC type: 0 FLL, 1 Held, 2 AMF +## Construct Slater U matrix +#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='wien2k')) +#Umat = t2g_submatrix(U_cubic, convention='wien2k') +## Construct Slater Hamiltonian +#h_int = h_int_slater(spin_names, orb_names, map_operator_structure=SK.sumk_to_solver[0], U_matrix=Umat) + +# Use GF structure determined by DFT blocks +gf_struct = [(block, indices) for block, indices in SK.gf_struct_solver[0].items()] + +# Construct Solver +S = Solver(beta=beta, gf_struct=gf_struct) + +if previous_present: + chemical_potential = 0 + dc_imp = 0 + dc_energ = 0 + if mpi.is_master_node(): + with HDFArchive(dft_filename+'.h5','r') as ar: + S.Sigma_iw << ar['dmft_output']['Sigma_iw'] + chemical_potential,dc_imp,dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ']) + S.Sigma_iw << mpi.bcast(S.Sigma_iw) + chemical_potential = mpi.bcast(chemical_potential) + dc_imp = mpi.bcast(dc_imp) + dc_energ = mpi.bcast(dc_energ) + SK.set_mu(chemical_potential) + SK.set_dc(dc_imp,dc_energ) + +for iteration_number in range(1,loops+1): + if mpi.is_master_node(): print("Iteration = ", iteration_number) + + SK.symm_deg_gf(S.Sigma_iw,ish=0) # symmetrise Sigma + 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()) + + # Init the DC term and the real part of Sigma, if no previous runs found: + if (iteration_number==1 and previous_present==False): + 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] + + # Calculate new G0_iw to input into the solver: + S.G0_iw << inverse(S.Sigma_iw + inverse(S.G_iw)) + + # Solve the impurity problem: + S.solve(h_int=h_int, **p) + + # Solved. Now do post-processing: + mpi.report("Total charge of impurity problem : %.6f"%S.G_iw.total_density()) + + # Now mix Sigma and G with factor sigma_mix, if wanted: + if (iteration_number>1 or previous_present): + if mpi.is_master_node(): + with HDFArchive(dft_filename+'.h5','r') as ar: + mpi.report("Mixing Sigma and G with factor %s"%sigma_mix) + S.Sigma_iw << sigma_mix * S.Sigma_iw + (1.0-sigma_mix) * ar['dmft_output']['Sigma_iw'] + S.G_iw << sigma_mix * S.G_iw + (1.0-sigma_mix) * ar['dmft_output']['G_iw'] + + S.G_iw << mpi.bcast(S.G_iw) + S.Sigma_iw << mpi.bcast(S.Sigma_iw) + + # Write the final Sigma and G to the hdf5 archive: + if mpi.is_master_node(): + with HDFArchive(dft_filename+'.h5','a') as ar: + ar['dmft_output']['iterations'] = iteration_number + previous_runs + ar['dmft_output']['G_tau'] = S.G_tau + ar['dmft_output']['G_iw'] = S.G_iw + ar['dmft_output']['Sigma_iw'] = S.Sigma_iw + ar['dmft_output']['G0-%s'%(iteration_number)] = S.G0_iw + ar['dmft_output']['G-%s'%(iteration_number)] = S.G_iw + ar['dmft_output']['Sigma-%s'%(iteration_number)] = S.Sigma_iw + + # Set the new double counting: + dm = S.G_iw.density() # compute the density matrix of the impurity problem + SK.calc_dc(dm, U_interact = U, J_hund = J, orb = 0, use_dc_formula = dc_type) + + # Save stuff into the user_data group of hdf5 archive in case of rerun: + SK.save(['chemical_potential','dc_imp','dc_energ']) + +#For FCSC calculations +#output the density matrix for Elk interface +dN, d = SK.calc_density_correction(dm_type='elk') +#correlation energy via the Migdal formula +correnerg = 0.5 * (S.G_iw * S.Sigma_iw).total_density() +#subtract the double counting energy +correnerg -= SK.dc_energ[0] +#convert to Hartree +correnerg = correnerg/SK.energy_unit +#save the correction to energy +if (mpi.is_master_node()): + f=open('DMATDMFT.OUT','a') + f.write("%.16f\n"%correnerg) + f.close() + diff --git a/doc/tutorials/svo_elk/elk.in b/doc/tutorials/svo_elk/elk.in new file mode 100644 index 00000000..d960f566 --- /dev/null +++ b/doc/tutorials/svo_elk/elk.in @@ -0,0 +1,41 @@ +!Calculates the V t2g Wannier projectors, Wannier charge and Wannier DOS of SrVO3 + +!Example by Alyn D. N. James + +tasks + 0 + 805 + +ngridk + 12 12 12 + +sppath + '../../../species/' + +rgkmax + 7.0 + +avec + 7.260500000 0.000000000 0.000000000 + 0.000000000 7.260500000 0.000000000 + 0.000000000 0.000000000 7.260500000 + +atoms + 3 : nspecies +'Sr.in' : spfname + 1 : natoms; atposl, bfcmt below + 0.50000000 0.50000000 0.50000000 0.00000000 0.00000000 0.00000000 +'V.in' : spfname + 1 : natoms; atposl, bfcmt below + 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 +'O.in' : spfname + 3 : natoms; atposl, bfcmt below + 0.50000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 + 0.00000000 0.50000000 0.00000000 0.00000000 0.00000000 0.00000000 + 0.00000000 0.00000000 0.50000000 0.00000000 0.00000000 0.00000000 + +wanproj !projector flag + 1 !number of projectors - next 3 lines are repeated for each projector + 2 2 3 !species, l, reduced max lm (rlmmax) value + 7 8 9 !the lm quanties which will be projected (vector length eq. rlmmax) +-0.055 0.07 ![-1.5, 1.9] eV t2g correlated energy window diff --git a/doc/tutorials/svo_elk/elk_fcsc.sh b/doc/tutorials/svo_elk/elk_fcsc.sh new file mode 100644 index 00000000..9bad628c --- /dev/null +++ b/doc/tutorials/svo_elk/elk_fcsc.sh @@ -0,0 +1,81 @@ +#!/bin/bash + +#(Crude) shell script for FCSC calculations using the Elk-TRIQS setup. + +#You may put job scheduler (PBS, Slurm or other) information here +#Note mpirun command lines may have to be altered for the +#scheduler used + + +# +#the Elk executable (may have to update path and version used) +export elk_ex="${HOME}/elk-6.2.8/src/elk" +#this variable is already linked in the $PATH in .bashrc +export triqs_ex="python" + +#initial variables which can be tweeked +#max loop index - Input variable +export imax=20 +#python file prefix - user's script +export triqs_name="dft_dmft_cthyb_elk" + + +#DFT+DMFT self-consistent cycle shell output file +export out_file="FCSC.OUT" +#elk interface tasks +export e2t_task=805 +export t2e_task=808 +#Master input file for the dft interface calculation. +export elk_master_file="elk_master.in" +#input elk file +export elk_infile="elk.in" +#output elk file +export elk_outfile="elk.out" +#output triqs file +export triqs_outfile="SC_DMFT.OUT" +#this variable will be used to replace the string TASK in elk_master.in +export task="TASK" +#check if master file exists +if [ ! -e "$elk_master_file" ]; then + echo "No master input file" > $out_file + exit +fi + +echo " "> $elk_outfile +echo " "> $triqs_outfile + +echo "Maximum number of iterations = "$imax > $out_file +echo "Number of processors used = "$NUMPROC >> $out_file +for (( i=1; i<=$imax; i++)); do + echo "SC loop "$i" of "$imax >> $out_file + echo " ">> $out_file + + #copy master input to elk.in + cp $elk_master_file $elk_infile + #replace TASK string to interface task + sed -i "s/$task*/$e2t_task/" $elk_infile + #executes elk (generate projectors) + echo "SC loop "$i" of "$imax >> $elk_outfile + mpirun $elk_ex >> $elk_outfile + echo " ">> $elk_outfile + echo "Interfaced Elk to TRIQS via task "$e2t_task >> $out_file + + #executes triqs + echo "SC loop "$i" of "$imax >> $triqs_outfile + mpirun $triqs_ex $triqs_name".py" >> $triqs_outfile + echo " " >> $triqs_outfile + echo "TRIQS DMFT loop(s) done " >> $out_file + + #copy master input to elk.in + cp $elk_master_file $elk_infile + #replace TASK string to interface task + sed -i "s/$task*/$t2e_task/" $elk_infile + #executes elk (density update) + mpirun $elk_ex >> $elk_outfile + echo " ">> $elk_outfile + echo "Interfaced TRIQS dmft outputs into elk via task "$t2e_task >> $out_file + echo " ">> $out_file +done +#end + + diff --git a/doc/tutorials/svo_elk/elk_master.in b/doc/tutorials/svo_elk/elk_master.in new file mode 100644 index 00000000..b1cac3ee --- /dev/null +++ b/doc/tutorials/svo_elk/elk_master.in @@ -0,0 +1,40 @@ +!Calculates the V t2g Wannier projectors, Wannier charge and Wannier DOS of SrVO3 + +!Example by Alyn D. N. James + +tasks + TASK + +ngridk + 12 12 12 + +sppath + '../../../species/' + +rgkmax + 7.0 + +avec + 7.260500000 0.000000000 0.000000000 + 0.000000000 7.260500000 0.000000000 + 0.000000000 0.000000000 7.260500000 + +atoms + 3 : nspecies +'Sr.in' : spfname + 1 : natoms; atposl, bfcmt below + 0.50000000 0.50000000 0.50000000 0.00000000 0.00000000 0.00000000 +'V.in' : spfname + 1 : natoms; atposl, bfcmt below + 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 +'O.in' : spfname + 3 : natoms; atposl, bfcmt below + 0.50000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 + 0.00000000 0.50000000 0.00000000 0.00000000 0.00000000 0.00000000 + 0.00000000 0.00000000 0.50000000 0.00000000 0.00000000 0.00000000 + +wanproj !projector flag + 1 !number of projectors - next 3 lines are repeated for each projector + 2 2 3 !species, l, reduced max lm (rlmmax) value + 7 8 9 !the lm quanties which will be projected (vector length eq. rlmmax) +-0.055 0.07 ![-1.5, 1.9] eV t2g correlated energy window diff --git a/doc/tutorials/svo_elk/srvo3.rst b/doc/tutorials/svo_elk/srvo3.rst new file mode 100644 index 00000000..f20e4de2 --- /dev/null +++ b/doc/tutorials/svo_elk/srvo3.rst @@ -0,0 +1,239 @@ +.. _SrVO3_elk: + +This example is almost identical to the :ref:`Wien2k-TRIQS SrVO3 example `. On the example of SrVO3 we will discuss now how to set up a full working calculation using Elk, including the initialization of the :ref:`CTHYB solver `. Some additional parameter are introduced to make the calculation more efficient. This is a more advanced example, which is also suited for parallel execution. + +For the convenience of the user, we provide also a full python script (:download:`dft_dmft_cthyb_elk.py `). The user has to adapt it to their own needs. How to execute your script is described :ref:`here`. + +For more details we refer to the :ref:`documentation `, now we will discuss the conversion for Elk. + +A brief note before discussing the example. This interface works for any type of ground state Elk calculation using the interface calls described in this example (i.e. the interface is universal). If the user wishes to perform a spin-polarized calculation in DMFT alone (non magnetic DFT inputs), they have to lift the up / down spin symmetry manually (not shown here). + + +Elk to TRIQS +============ + +First, we perform a DFT calculation, using the Elk package. As main input file we have to provide the so-called elk.in :file:`elk.in`. We use the following: + +.. literalinclude:: elk.in + +This :download:`elk.in` will generate the ground state (task 0) and the Wannier projectors (task 805) in a small energy window for the :math:`V` :math:`t_{2g}` orbitals. The elk executable is run in the directory including the elk.in file. + +A simple python script that initializes the converter is:: + + from triqs_dft_tools.converters.elk import * + Converter = elkConverter(filename = "SrVO3") + +After initializing the converter, we can now convert the input text files into an hdf5 archive by:: + + Converter.convert_dft_input() + +This reads all necessary data from the :ref:`Elk output `, and stores the converted input for the DMFT calculation in the file :file:`SrVO3.h5`. + + +The DMFT calculation +==================== + +The DMFT script itself is, except very few details, independent of the DFT package that was used to calculate the local orbitals. As soon as one has converted everything to the hdf5 format, the following procedure is practically the same. + +Loading modules +--------------- + +First, we load the necessary modules:: + + from triqs_dft_tools.sumk_dft import * + from triqs.gf import * + from h5 import HDFArchive + from triqs.operators.util import * + from triqs_cthyb import * + import triqs.utility.mpi as mpi + +The last two lines load the modules for the construction of the +:ref:`CTHYB solver `. + +Initializing SumkDFT +-------------------- + +We define some parameters, which should be self-explanatory:: + + dft_filename = 'SrVO3' # filename + U = 4.0 # interaction parameters + J = 0.65 + beta = 40 # inverse temperature + loops = 15 # number of DMFT loops + mix = 0.8 # mixing factor of Sigma after solution of the AIM + dc_type = 1 # DC type: 0 FLL, 1 Held, 2 AMF + use_blocks = True # use bloc structure from DFT input + prec_mu = 0.0001 # precision of chemical potential + + +And next, we can initialize the :class:`SumkDFT ` class:: + + SK = SumkDFT(hdf_file=dft_filename+'.h5',use_dft_blocks=use_blocks) + +Initializing the solver +----------------------- + +We also have to specify the :ref:`CTHYB solver ` related settings. We assume that the DMFT script for SrVO3 is executed on 16 cores. A sufficient set of parameters for a first guess is:: + + p = {} + # solver + p["length_cycle"] = 200 + p["n_warmup_cycles"] = 100000 + p["n_cycles"] = 1000000 + # tail fit + p["perform_tail_fit"] = True + p["fit_max_moment"] = 4 + p["fit_min_n"] = 30 + p["fit_max_n"] = 60 + +Here we use a tail fit to deal with numerical noise of higher Matsubara frequencies. For other options and more details on the solver parameters, we refer to :ref:`CTHYB solver ` documentation. It is important to note that the solver parameters have to be adjusted for each material individually. A guide on how to set the tail fit parameters is given :ref:`below `. + +The next step is to initialize the :class:`solver class `. It consist of two parts: + +#. Calculating the multi-band interaction matrix, and constructing the + interaction Hamiltonian. +#. Initializing the solver class itself. + +The first step is done using methods of the :ref:`TRIQS ` library:: + + n_orb = SK.corr_shells[0]['dim'] + l = SK.corr_shells[0]['l'] + spin_names = ["up","down"] + orb_names = [i for i in range(n_orb)] + # Use GF structure determined by DFT blocks: + gf_struct = [(block, indices) for block, indices in SK.gf_struct_solver[0].iteritems()] + # Construct U matrix for density-density calculations: + Umat, Upmat = U_matrix_kanamori(n_orb=n_orb, U_int=U, J_hund=J) + +We assumed here that we want to use an interaction matrix with Kanamori definitions of :math:`U` and :math:`J`. + +Next, we construct the Hamiltonian and the solver:: + + h_int = h_int_density(spin_names, orb_names, map_operator_structure=SK.sumk_to_solver[0], U=Umat, Uprime=Upmat) + S = Solver(beta=beta, gf_struct=gf_struct) + +For simplicity, we take only density-density interactions into account here. Other Hamiltonians with, e.g. with full rotational invariant interactions are: + +* h_int_kanamori +* h_int_slater + +For other choices of the interaction matrices (e.g Slater representation) or Hamiltonians, we refer to the reference manual of the :ref:`TRIQS ` library. + +As a last step, we initialize the subgroup in the hdf5 archive to store the results:: + + if mpi.is_master_node(): + with HDFArchive(dft_filename+'.h5') as ar: + if (not ar.is_group('dmft_output')): + ar.create_group('dmft_output') + +DMFT cycle +---------- + +Now we can go to the definition of the self-consistency step. It consists again of the basic steps with some additional refinements:: + + for iteration_number in range(1,loops+1): + if mpi.is_master_node(): print "Iteration = ", iteration_number + + SK.symm_deg_gf(S.Sigma_iw,ish=0) # symmetrizing Sigma + 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()) + + # In the first loop, init the DC term and the real part of Sigma: + if (iteration_number==1): + 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] + + # Calculate new G0_iw to input into the solver: + S.G0_iw << S.Sigma_iw + inverse(S.G_iw) + S.G0_iw << inverse(S.G0_iw) + + # Solve the impurity problem: + S.solve(h_int=h_int, **p) + + # Solved. Now do post-solution stuff: + mpi.report("Total charge of impurity problem : %.6f"%S.G_iw.total_density()) + + # Now mix Sigma and G with factor mix, if wanted: + if (iteration_number>1): + if mpi.is_master_node(): + with HDFArchive(dft_filename+'.h5','r') as ar: + mpi.report("Mixing Sigma and G with factor %s"%mix) + S.Sigma_iw << mix * S.Sigma_iw + (1.0-mix) * ar['dmft_output']['Sigma_iw'] + S.G_iw << mix * S.G_iw + (1.0-mix) * ar['dmft_output']['G_iw'] + S.G_iw << mpi.bcast(S.G_iw) + S.Sigma_iw << mpi.bcast(S.Sigma_iw) + + # Write the final Sigma and G to the hdf5 archive: + if mpi.is_master_node(): + with HDFArchive(dft_filename+'.h5') as ar: + ar['dmft_output']['iterations'] = iteration_number + ar['dmft_output']['G_0'] = S.G0_iw + ar['dmft_output']['G_tau'] = S.G_tau + ar['dmft_output']['G_iw'] = S.G_iw + ar['dmft_output']['Sigma_iw'] = S.Sigma_iw + + # Set the new double counting: + dm = S.G_iw.density() # compute the density matrix of the impurity problem + SK.calc_dc(dm, U_interact = U, J_hund = J, orb = 0, use_dc_formula = dc_type) + + # Save stuff into the user_data group of hdf5 archive in case of rerun: + SK.save(['chemical_potential','dc_imp','dc_energ']) + + +TRIQS to Elk (Fully Charge Self-Consistent DFT+DMFT) +==================================================== + +To output the DMATDMFT.OUT file for a fully charge self-consistent calculation, add the following lines to the end of the DMFT python script:: + + #output the density matrix for Elk interface + dN, d = SK.calc_density_correction() + #correlation energy via the Migdal formula + correnerg = 0.5 * (S.G_iw * S.Sigma_iw).total_density() + #subtract the double counting energy + correnerg -= SK.dc_energ[0] + #convert to Hartree + correnerg = correnerg/SK.energy_unit + #save the correction to energy + if (mpi.is_master_node()): + f=open('DMATDMFT.OUT','a') + f.write("%.16f\n"%correnerg) + f.close() + +To update the electron density and solve the Kohn-Sham equations once, run task 808 in elk.in. Automating this cycle can be done by running the shell script (:download:`elk_fcsc.sh `) and having an :download:`elk_master.in` file which replaces the tasks in elk.in for each new task in the FCSC DFT+DMFT cycle (see :download:`elk_master.in `. Assuming that the ground state has been calculated, this shell script executes the following: + +#. generate the projectors (task 805) +#. execute the DMFT cycle(s) +#. update the electron density +#. -> (1) ... + +The user just needs to specify the maximum number of FCSC cycles, as well as the number of OpenMP threads for Elk (`OMP_NUM_THREADS`) and the number of MPI ranks in the bash script. + +This is all we need for the one-shot or FCSC DFT+DMFT calculation. All results of this calculation will be stored in a separate subgroup in the hdf5 file, called `dmft_output`. Note that the script performs 15 DMFT cycles, but does not check for convergence. It would be possible to build in convergence criteria. A simple check for convergence can be also done if you store multiple quantities of each iteration and analyse the convergence manually. In general, it is advisable to start with less good statistics (fewer measurements), and increase the number of measurements close to convergence (e.g. after a few initial iterations). This helps to keep computational costs low during the first iterations. + +Using the Kanamori Hamiltonian and the parameters above (but on 16 cores), your self energy after the **first iteration** should look something like: + +.. image:: SrVO3_Sigma_iw_it1.png + :width: 700 + :align: center + +.. _tailfit: + + +Tail fit parameters +------------------- + +A good way to identify suitable tail fit parameters is by "human inspection". Therefore disabled the tail fitting first:: + + p["perform_tail_fit"] = False + +and perform only one DMFT iteration. The resulting self energy can be tail fitted by hand:: + + Sigma_iw_fit = S.Sigma_iw.copy() + Sigma_iw_fit << tail_fit(S.Sigma_iw, fit_max_moment = 4, fit_min_n = 40, fit_max_n = 160)[0] + +Plot the self energy and adjust the tail fit parameters such that you obtain a proper fit. The :meth:`fit_tail function ` is part of the :ref:`TRIQS ` library. + +For a self energy which is going to zero for :math:`i\omega \rightarrow 0` our suggestion is to start the tail fit (:emphasis:`fit_min_n`) at a Matsubara frequency considerable above the minimum of the self energy and to stop (:emphasis:`fit_max_n`) before the noise fully takes over. If it is difficult to find a reasonable fit in this region you should increase your statistics (number of measurements). Keep in mind that :emphasis:`fit_min_n` and :emphasis:`fit_max_n` also depend on :math:`\beta`. diff --git a/python/triqs_dft_tools/converters/__init__.py b/python/triqs_dft_tools/converters/__init__.py index 8900eeec..32131913 100644 --- a/python/triqs_dft_tools/converters/__init__.py +++ b/python/triqs_dft_tools/converters/__init__.py @@ -24,6 +24,7 @@ from .wien2k import Wien2kConverter from .hk import HkConverter from .vasp import VaspConverter from .wannier90 import Wannier90Converter +from .elk import ElkConverter -__all__ =['Wien2kConverter','HkConverter','Wannier90Converter','VaspConverter'] +__all__ =['Wien2kConverter','HkConverter','Wannier90Converter','VaspConverter','ElkConverter'] diff --git a/python/triqs_dft_tools/converters/elk.py b/python/triqs_dft_tools/converters/elk.py new file mode 100644 index 00000000..50e6ce82 --- /dev/null +++ b/python/triqs_dft_tools/converters/elk.py @@ -0,0 +1,640 @@ + +########################################################################## +# +# TRIQS: a Toolbox for Research in Interacting Quantum Systems +# +# Copyright (C) 2019 by A. D. N. James, A. Hampel and M. Aichhorn +# +# TRIQS is free software: you can redistribute it and/or modify it under the +# terms of the GNU General Public License as published by the Free Software +# Foundation, either version 3 of the License, or (at your option) any later +# version. +# +# TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY +# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more +# details. +# +# You should have received a copy of the GNU General Public License along with +# TRIQS. If not, see . +# +########################################################################## + +from types import * +import numpy +from .converter_tools import * +import os.path +from h5 import * +from locale import atof +from triqs_dft_tools.converters.elktools import readElkfiles as read_Elk +from triqs_dft_tools.converters.elktools import ElkConverterTools as Elk_tools + +class ElkConverter(ConverterTools,Elk_tools,read_Elk): + """ + Conversion from Elk output to an hdf5 file that can be used as input for the SumkDFT class. + """ + + def __init__(self, filename, hdf_filename=None, + dft_subgrp='dft_input', symmcorr_subgrp='dft_symmcorr_input', + bc_subgrp='dft_bandchar_input', symmpar_subgrp='dft_symmpar_input', + bands_subgrp='dft_bands_input', misc_subgrp='dft_misc_input', + transp_subgrp='dft_transp_input',fs_subgrp='dft_fs_input', + repacking=False): + """ + Initialise the class. + + Parameters + ---------- + filename : string + Base name of DFT files. + hdf_filename : string, optional + Name of hdf5 archive to be created. + dft_subgrp : string, optional + Name of subgroup storing necessary DFT data. + symmcorr_subgrp : string, optional + Name of subgroup storing correlated-shell symmetry data. + parproj_subgrp : string, optional + Name of subgroup storing partial projector data. + symmpar_subgrp : string, optional + Name of subgroup storing partial-projector symmetry data. + bands_subgrp : string, optional + Name of subgroup storing band data. + misc_subgrp : string, optional + Name of subgroup storing miscellaneous DFT data. + transp_subgrp : string, optional + Name of subgroup storing transport data. + repacking : boolean, optional + Does the hdf5 archive need to be repacked to save space? + + """ + + assert isinstance(filename, str), "ElkConverter: Please provide the DFT files' base name as a string." + if hdf_filename is None: + hdf_filename = filename + '.h5' + self.hdf_file = hdf_filename + self.dft_file = 'PROJ.OUT' + self.band_file = 'BAND.OUT' + self.eval_file = 'EIGVAL.OUT' + self.efermi_file = 'EFERMI.OUT' + self.kp_file = 'KPOINTS.OUT' + self.geom_file='GEOMETRY.OUT' + self.dft_subgrp = dft_subgrp + self.symmcorr_subgrp = symmcorr_subgrp + self.bc_subgrp = bc_subgrp + self.symmpar_subgrp = symmpar_subgrp + self.bands_subgrp = bands_subgrp + self.misc_subgrp = misc_subgrp + self.transp_subgrp = transp_subgrp + self.fs_subgrp = fs_subgrp + self.fortran_to_replace = {'D': 'E'} + + # Checks if h5 file is there and repacks it if wanted: + if (os.path.exists(self.hdf_file) and repacking): + ConverterTools.repack(self) + + def check_dens(self,n_k,nstsv,occ,bz_weights,n_spin_blocs,band_window,SO): + """ + Check the charge density below the correlated energy window and up to the Fermi level + """ + + density_required=0.0E-7 + charge_below=0.0E-7 + #calculate the valence charge and charge below lower energy window bound + #Elk does not use the tetrahedron method when calculating these charges + for ik in range(n_k): + for ist in range(nstsv): + #calculate the charge over all the bands + density_required+=occ[ik][ist]*bz_weights[ik] + for isp in range(n_spin_blocs): + #Convert occ list from elk to two index format for spins + jst=int((isp)*nstsv*0.5) + #Take lowest index in band_window for SO system + if(SO==0): + nst=band_window[isp][ik, 0]-1 + else: + band=[band_window[0][ik, 0],band_window[1][ik, 0]] + nst=min(band)-1 + #calculate the charge below energy window + for ist in range(jst,nst): + charge_below+=occ[ik][ist]*bz_weights[ik] + #return charges + return(density_required,charge_below) + + def rotsym(self,n_shells,shells,n_symm,ind,basis,T,mat): + """ + Rotates the symmetry matrices into basis defined by the T unitary matrix + the outputted projectors are rotated to the irreducible representation + and then reduced in size to the orbitals used to construct the projectors. + """ + + for ish in range(n_shells): + #check that the T matrix is not the Identity (i.e. not using spherical + #harmonics). + if(basis[ish]!=0): + #put mat into temporary matrix + temp=mat + #index range of lm values used to create the Wannier projectors + min_ind=numpy.min(ind[ish][:]) + max_ind=numpy.max(ind[ish][:])+1 + #dimension of lm values used to construct the projectors + dim=shells[ish]['dim'] + #loop over all symmetries + for isym in range(n_symm): + #rotate symmetry matrix into basis defined by T + mat[isym][ish]=numpy.matmul(T[ish],mat[isym][ish]) + mat[isym][ish]=numpy.matmul(mat[isym][ish],T[ish].transpose()) + #put desired subset of transformed symmetry matrix into temp matrix for symmetry isym + for id in range(len(ind[ish])): + i=ind[ish][id] + for jd in range(len(ind[ish][:])): + j=ind[ish][jd] + temp[isym][ish][id,jd]=mat[isym][ish][i,j] + #put temp matrix into mat + mat=temp + #reduce size of lm arrays in mat lm dim + for isym in range(n_symm): + dim=shells[ish]['dim'] + mat[isym][ish]=mat[isym][ish][:dim,:dim] + return mat + + def update_so_quatities(self,n_shells,shells,n_corr_shells,corr_shells,n_inequiv_shells,dim_reps,n_k,n_symm,n_orbitals,proj_mat,T,su2,mat,sym=True): + """ + Changes the array sizes and elements for arrays used in spin-orbit coupled calculations. + """ + + #change dim for each shell + for ish in range(n_shells): + shells[ish]['dim'] = 2*shells[ish]['dim'] + for ish in range(n_corr_shells): + corr_shells[ish]['dim'] = 2*corr_shells[ish]['dim'] + for ish in range(n_inequiv_shells): + dim_reps[ish]=[2*dim_reps[ish][i] for i in range(len(dim_reps[ish]))] + #Make temporary array of original n_orbitals + n_orbitals_orig=n_orbitals + #Make SO n_orbitals array + #loop over k-points + for ik in range(n_k): + #new orbital array + n_orbitals[ik,0]=max(n_orbitals[ik,:]) + #reduce array size + n_orbitals=n_orbitals[:,:1] + #Resize proj_mat, mat, T + #make temporary projector array + proj_mat_tmp = numpy.zeros([n_k, 1, n_corr_shells, max([crsh['dim'] for crsh in corr_shells]), numpy.max(n_orbitals)], numpy.complex_) + for ish in range(n_corr_shells): + #update proj_mat + for ik in range(n_k): + #extra array elements in "dim" dimension + size=int(0.5*corr_shells[ish]['dim']) + #put each spinor into tmp array and ensure elements are assigned correctly in case of change of max(n_orbitals) + proj_mat_tmp[ik][0][ish][0:size][0:n_orbitals_orig[ik,0]]=proj_mat[ik][0][ish][0:size][0:n_orbitals_orig[ik,0]] + #put other spinor projectors into extra "dim" elements + proj_mat_tmp[ik][0][ish][size:2*size][0:n_orbitals_orig[ik,1]]=proj_mat[ik][1][ish][0:size][0:n_orbitals_orig[ik,1]] + #update T + #extra array elements in each dimension + size=2*corr_shells[ish]['l']+1 + #extend the arrays + T[ish]=numpy.lib.pad(T[ish],((0,size),(0,size)),'constant',constant_values=(0.0)) + #make block diagonal + T[ish][size:2*size,size:2*size]=T[ish][0:size,0:size] + #update the symmetries arrays if needed + if(sym): + #update mat - This includes the spin SU(2) matrix for spin-coupled calculations + #size of each quadrant in the lm symmetry array. + size=int(0.5*corr_shells[ish]['dim']) + #temporary spin block array for SU(2) spin operations on mat + spinmat = numpy.zeros([size,2,size,2],numpy.complex_) + for isym in range(n_symm): + #expand size of array + mat[isym][ish]=numpy.lib.pad(mat[isym][ish],((0,size),(0,size)),'constant',constant_values=(0.0)) + #make arraye block diagonal + mat[isym][ish][size:2*size,size:2*size]=mat[isym][ish][0:size,0:size] + #apply SU(2) spin matrices to lm symmetries + #put mat into array of spin blocks + for i1,i2 in numpy.ndindex(2,2): + spinmat[0:size,i1,0:size,i2] = mat[isym][ish][i1*size:(i1+1)*size,i2*size:(i2+1)*size] + #apply the SU(2) spin matrices + for ilm,jlm in numpy.ndindex(size,size): + spinmat[ilm,:,jlm,:] = numpy.dot(su2[isym][:,:],spinmat[ilm,:,jlm,:]) + #put spinmat into back in mat format + for i1,i2 in numpy.ndindex(2,2): + mat[isym][ish][i1*size:(i1+1)*size,i2*size:(i2+1)*size] = spinmat[0:size,i1,0:size,i2] + #assign arrays and delete temporary arrays + del proj_mat + proj_mat = proj_mat_tmp + del proj_mat_tmp, n_orbitals_orig + return shells,corr_shells,dim_reps,n_orbitals,proj_mat,T,mat + + def sort_dft_eigvalues(self,n_spin_blocs,SO,n_k,n_orbitals,band_window,en,energy_unit): + """ + Rearranges the energy eigenvalue arrays into TRIQS format + """ + + hopping = numpy.zeros([n_k, n_spin_blocs, numpy.max(n_orbitals), numpy.max(n_orbitals)], numpy.complex_) + #loop over spin + for isp in range(n_spin_blocs): + #loop over k-points + for ik in range(n_k): + #loop over bands + for ist in range(0,n_orbitals[ik, isp]): + #converter index for spin polarised Elk indices and take SO into consideration + if(SO==0): + jst=int(band_window[isp][ik, 0]-1+ist) + else: + band=[band_window[0][ik, 0],band_window[1][ik, 0]] + jst=int(min(band)-1+ist) + #correlated window energies + hopping[ik,isp,ist,ist]=en[ik][jst]*energy_unit + return hopping + + def convert_dft_input(self): + """ + Reads the appropriate files and stores the data for the + + - dft_subgrp + - symmcorr_subgrp + - misc_subgrp + + in the hdf5 archive. + + """ + # Read and write only on the master node + if not (mpi.is_master_node()): + return + filext='.OUT' + dft_file='PROJ'+filext + mpi.report("Reading %s" % dft_file) + #Energy conversion - Elk uses Hartrees + energy_unit = 27.2113850560 # Elk uses hartrees + #The projectors change size per k-point + k_dep_projection = 1 + #Symmetries are used + symm_op = 1 # Use symmetry groups for the k-sum + shells=[] + #read information about projectors calculated in the Elk calculation + [gen_info,n_corr_shells,n_inequiv_shells,corr_to_inequiv,inequiv_to_corr,corr_shells,n_reps,dim_reps,ind,basis,T] = read_Elk.read_proj(self,dft_file) + #get info for HDF5 file from gen_info + n_k=gen_info['n_k'] + SP=gen_info['spinpol']-1 + #Elk uses spinor wavefunctions. Therefore these two spinor wavefunctions have spin-orbit coupling incorporated in them. Here we read in the spinors + n_spin_blocs = SP + 1 + SO=gen_info['SO'] + n_atoms=gen_info['natm'] + #Elk only calculates Wannier projectors (no theta projectors generated): + n_shells=n_corr_shells + for ish in range(n_shells): + shells.append(corr_shells[ish].copy()) + #remove last 2 entries from corr_shlls + del shells[ish]['SO'] + del shells[ish]['irep'] + shells[ish]['dim'] = 2*shells[ish]['l']+1 + #read eigenvalues calculated in the Elk calculation + mpi.report("Reading %s and EFERMI.OUT" % self.eval_file) + [en,occ,nstsv]=read_Elk.read_eig(self) + #read projectors calculated in the Elk calculation + proj_mat = numpy.zeros([n_k, n_spin_blocs, n_corr_shells, max([crsh['dim'] for crsh in corr_shells]), nstsv], numpy.complex_) + mpi.report("Reading projector(s)") + for ish in range(n_corr_shells): + [n_orbitals,band_window,rep,proj_mat]=read_Elk.read_projector(self,corr_shells,n_spin_blocs,ish,proj_mat,ind,T,basis,filext) + #read kpoints calculated in the Elk calculation + mpi.report("Reading %s" % self.kp_file) + [bz_weights,vkl]=read_Elk.read_kpoints(self) + #symmetry matrix + mpi.report("Reading GEOMETRY.OUT") + #read in atom posistions, the symmetry operators (in lattice coordinates) and lattice vectors + [ns, na, atpos]=read_Elk.read_geometry(self) + #Read symmetry files + mpi.report("Reading SYMCRYS.OUT") + [n_symm,spinmat,symmat,tr] = read_Elk.readsym(self) + mpi.report("Reading LATTICE.OUT") + [amat,amatinv,bmat,bmatinv] = read_Elk.readlat(self) + #calculating atom permutations + perm = Elk_tools.gen_perm(self,n_symm,ns,na,n_atoms,symmat,tr,atpos) + #determine the cartesian lattice symmetries and the spin axis rotations + #required for the spinors (for SO for now) + su2 = [] + symmatc=[] + for isym in range(n_symm): + #convert the lattice symmetry matrices into cartesian coordinates + tmp = numpy.matmul(amat,symmat[isym]) + symmatc.append(numpy.matmul(tmp,amatinv)) + #convert the spin symmetry matrices into cartesian coordinates + spinmatc = numpy.matmul(amat,spinmat[isym]) + spinmatc = numpy.matmul(spinmatc,amatinv) + #calculate the rotation angle and spin axis vector in cartesian coordinates + [v,th] = self.rotaxang(spinmatc[:,:]) + #calculate the SU(2) matrix from the angle and spin axis vector + su2.append(self.axangsu2(v,th)) + del tmp + + #calculating the symmetries in complex harmonics + mat = Elk_tools.symlat_to_complex_harmonics(self,n_symm,n_corr_shells,symmatc,corr_shells) + mat = self.rotsym(n_corr_shells,corr_shells,n_symm,ind,basis,T,mat) + + #The reading is done. Some variables may need to change for TRIQS compatibility. + #Alter size of some of the arrays if spin orbit coupling is enabled. + #For SO in Elk, the eigenvalues and eigenvector band indices are in asscending order w.r.t energy + if(SO==1): + [shells,corr_shells,dim_reps,n_orbitals,proj_mat,T,mat]=self.update_so_quatities(n_shells,shells,n_corr_shells,corr_shells,n_inequiv_shells,dim_reps,n_k,n_symm,n_orbitals,proj_mat,T,su2,mat) + #reduce n_spin_blocs + n_spin_blocs = SP + 1 - SO + + #put the energy eigenvalues arrays in TRIQS format + hopping = self.sort_dft_eigvalues(n_spin_blocs,SO,n_k,n_orbitals,band_window,en,energy_unit) + + #Elk does not use global to local matrix rotation (Rotloc) as is done in Wien2k. However, the projectors + #require a symmetry matrix to rotate from jatom to iatom. Below finds the non inversion + #symmetric matrices which were used in calculating the projectors + use_rotations = 1 + rot_mat = [numpy.identity(corr_shells[icrsh]['dim'], numpy.complex_) for icrsh in range(n_corr_shells)] + for icrsh in range(n_corr_shells): + incrsh = corr_to_inequiv[icrsh] + iatom = corr_shells[incrsh]['atom'] + for isym in range(n_symm): + jatom=perm[isym][corr_shells[icrsh]['atom']-1] + #determinant determines if crystal symmetry matrix has inversion symmetry (=-1) + det = numpy.linalg.det(symmat[isym][:,:]) + if((jatom==iatom)&(det>0.0)): + rot_mat[icrsh][:,:]=mat[isym][icrsh][:,:] + #used first desired symmetry in crystal symmetry list + break + # Elk does not currently use time inversion symmetry + rot_mat_time_inv = [0 for i in range(n_corr_shells)] + + #Check that the charge of all the bands and below the correlated window have been calculated correctly + [density_required, charge_below] = self.check_dens(n_k,nstsv,occ,bz_weights,n_spin_blocs,band_window,SO) + #calculate the required charge (density_required) to remain charge neutral + mpi.report("The total charge of the system = %f" %density_required) + mpi.report("The charge below the correlated window = %f" %charge_below) + mpi.report("The charge within the correlated window = %f" %(density_required - charge_below)) + + #Elk interface does not calculate theta projectors, hence orbits are the same as Wannier projectors + orbits=[] + #remove the spatom index to avoid errors in the symmetry routines + for ish in range(n_corr_shells): + #remove "spatom" + del corr_shells[ish]['spatom'] + orbits.append(corr_shells[ish].copy()) + for ish in range(n_shells): + #remove "spatom" + del shells[ish]['spatom'] + n_orbits=len(orbits) + + #Note that the T numpy array is defined for all shells. + + # Save it to the HDF: + ar = HDFArchive(self.hdf_file, 'a') + if not (self.dft_subgrp in ar): + ar.create_group(self.dft_subgrp) + # The subgroup containing the data. If it does not exist, it is + # created. If it exists, the data is overwritten! + things_to_save = ['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', + 'n_inequiv_shells', 'corr_to_inequiv', 'inequiv_to_corr'] + for it in things_to_save: + ar[self.dft_subgrp][it] = locals()[it] + del ar + # Save it to the HDF: + ar = HDFArchive(self.hdf_file, 'a') + symm_subgrp=self.symmcorr_subgrp + #Elk does not use time inversion symmetry + time_inv = [0 for j in range(n_symm)] + mat_tinv = [numpy.identity(orbits[orb]['dim'], numpy.complex_) + for orb in range(n_orbits)] + #Save all the symmetry data + if not (symm_subgrp in ar): + ar.create_group(symm_subgrp) + things_to_save_sym = ['n_symm', 'n_atoms', 'perm', + 'orbits', 'SO', 'SP', 'time_inv', 'mat', 'mat_tinv'] + for it in things_to_save_sym: + ar[symm_subgrp][it] = locals()[it] + del ar + #Save misc info + things_to_save_misc = ['band_window','vkl','nstsv'] + # Save it to the HDF: + ar = HDFArchive(self.hdf_file, 'a') + if not (self.misc_subgrp in ar): + ar.create_group(self.misc_subgrp) + for it in things_to_save_misc: + ar[self.misc_subgrp][it] = locals()[it] + del ar + mpi.report('Converted the Elk ground state data') + + + def convert_bands_input(self): + """ + Reads the appropriate files and stores the data for the bands_subgrp in the hdf5 archive. + + """ + # Read and write only on the master node + if not (mpi.is_master_node()): + return + filext='_WANBAND.OUT' + dft_file='PROJ'+filext + mpi.report("Reading %s" % dft_file) + #Energy conversion - Elk uses Hartrees + energy_unit = 27.2113850560 # Elk uses hartrees + shells=[] + #read information about projectors calculated in the Elk calculation + [gen_info,n_corr_shells,n_inequiv_shells,corr_to_inequiv,inequiv_to_corr,corr_shells,n_reps,dim_reps,ind,basis,T] = read_Elk.read_proj(self,dft_file) + #get info for HDF5 file from gen_info + n_k=gen_info['n_k'] + SP=gen_info['spinpol']-1 + #Elk uses spinor wavefunctions. Therefore these two spinor wavefunctions have spin-orbit coupling incorporated in them. Here we read in the spinors + n_spin_blocs = SP + 1 + SO=gen_info['SO'] + #Elk only calculates Wannier projectors (no theta projectors generated): + n_shells=n_corr_shells + for ish in range(n_shells): + shells.append(corr_shells[ish].copy()) + #remove last 2 entries from corr_shlls + del shells[ish]['SO'] + del shells[ish]['irep'] + shells[ish]['dim'] = 2*shells[ish]['l']+1 + + #read in the band eigenvalues + mpi.report("Reading BAND.OUT") + en=numpy.loadtxt('BAND.OUT') + nstsv=int(len(en[:,1])/n_k) + #convert the en array into a workable format + entmp = numpy.zeros([n_k,nstsv], numpy.complex_) + enj=0 + for ist in range(nstsv): + for ik in range(n_k): + entmp[ik,ist]=en[enj,1] + enj+=1 + del en + #read projectors + proj_mat = numpy.zeros([n_k, n_spin_blocs, n_corr_shells, max([crsh['dim'] for crsh in corr_shells]), nstsv], numpy.complex_) + mpi.report("Reading projector(s)") + for ish in range(n_corr_shells): + [n_orbitals,band_window,rep,proj_mat]=read_Elk.read_projector(self,corr_shells,n_spin_blocs,ish,proj_mat,ind,T,basis,filext) + + #alter arrays for spin-orbit coupling + if(SO==1): + mat=[] + su2=[] + n_symm=1 + [shells,corr_shells,dim_reps,n_orbitals,proj_mat,T,mat]=self.update_so_quatities(n_shells,shells,n_corr_shells,corr_shells,n_inequiv_shells,dim_reps,n_k,n_symm,n_orbitals,proj_mat,T,su2,mat,sym=False) + #reduce n_spin_blocs + n_spin_blocs = SP + 1 - SO + + #put the energy eigenvalues arrays in TRIQS format + hopping = self.sort_dft_eigvalues(n_spin_blocs,SO,n_k,n_orbitals,band_window,entmp,energy_unit) + + # No partial projectors generate, set to 0: + n_parproj = numpy.array([0]) + proj_mat_all = numpy.array([0]) + + # Save it to the HDF: + ar = HDFArchive(self.hdf_file, 'a') + if not (self.bands_subgrp in ar): + ar.create_group(self.bands_subgrp) + # The subgroup containing the data. If it does not exist, it is + # created. If it exists, the data is overwritten! + things_to_save = ['n_k', 'n_orbitals', 'proj_mat', + 'hopping', 'n_parproj', 'proj_mat_all'] + for it in things_to_save: + ar[self.bands_subgrp][it] = locals()[it] + del ar + mpi.report('Converted the band data') + + def convert_fs_input(self): + """ + Reads the appropriate files and stores the data for the FS_subgrp in the hdf5 archive. + + """ + # Read and write only on the master node + if not (mpi.is_master_node()): + return + filext='_FS.OUT' + dft_file='PROJ'+filext + mpi.report("Reading %s" % dft_file) + #Energy conversion - Elk uses Hartrees + energy_unit = 27.2113850560 # Elk uses hartrees + shells=[] + #read information about projectors calculated in the Elk calculation + [gen_info,n_corr_shells,n_inequiv_shells,corr_to_inequiv,inequiv_to_corr,corr_shells,n_reps,dim_reps,ind,basis,T] = read_Elk.read_proj(self,dft_file) + #get info for HDF5 file from gen_info + n_k=gen_info['n_k'] + SP=gen_info['spinpol']-1 + #Elk uses spinor wavefunctions. Therefore these two spinor wavefunctions have spin-orbit coupling incorporated in them. Here we read in the spinors + n_spin_blocs = SP + 1 + SO=gen_info['SO'] + #Elk only calculates Wannier projectors (no theta projectors generated): + n_shells=n_corr_shells + for ish in range(n_shells): + shells.append(corr_shells[ish].copy()) + #remove last 2 entries from corr_shlls + del shells[ish]['SO'] + del shells[ish]['irep'] + shells[ish]['dim'] = 2*shells[ish]['l']+1 + + #read in the eigenvalues used for the FS calculation + mpi.report("Reading EIGVAL_FS.OUT and EFERMI.OUT") + [en,occ,nstsv]=read_Elk.read_eig(self,filext=filext) + #read kpoints calculated in the Elk FS calculation + mpi.report("Reading KPOINT_FS.OUT") + [bz_weights,vkl]=read_Elk.read_kpoints(self,filext=filext) + + #read projectors + proj_mat = numpy.zeros([n_k, n_spin_blocs, n_corr_shells, max([crsh['dim'] for crsh in corr_shells]), nstsv], numpy.complex_) + mpi.report("Reading projector(s)") + for ish in range(n_corr_shells): + [n_orbitals,band_window,rep,proj_mat]=read_Elk.read_projector(self,corr_shells,n_spin_blocs,ish,proj_mat,ind,T,basis,filext) + + #Need lattice symmetries to unfold the irreducible BZ + #Read symmetry files + mpi.report("Reading SYMCRYS.OUT") + [n_symm,spinmat,symlat,tr] = read_Elk.readsym(self) + mpi.report("Reading LATTICE.OUT") + [amat,amatinv,bmat,bmatinv] = read_Elk.readlat(self) + #Put eigenvalues into array of eigenvalues for the correlated window + #alter arrays for spin-orbit coupling + if(SO==1): + mat=[] + su2=[] + [shells,corr_shells,dim_reps,n_orbitals,proj_mat,T,mat]=self.update_so_quatities(n_shells,shells,n_corr_shells,corr_shells,n_inequiv_shells,dim_reps,n_k,n_symm,n_orbitals,proj_mat,T,su2,mat,sym=False) + #reduce n_spin_blocs + n_spin_blocs = SP + 1 - SO + + #put the energy eigenvalues arrays in TRIQS format + hopping = self.sort_dft_eigvalues(n_spin_blocs,SO,n_k,n_orbitals,band_window,en,energy_unit) + + # Save it to the HDF: + ar = HDFArchive(self.hdf_file, 'a') + if not (self.fs_subgrp in ar): + ar.create_group(self.fs_subgrp) + # The subgroup containing the data. If it does not exist, it is + # created. If it exists, the data is overwritten! + things_to_save = ['n_k', 'n_orbitals', 'proj_mat','bmat', + 'hopping', 'vkl','symlat', 'n_symm'] + for it in things_to_save: + ar[self.fs_subgrp][it] = locals()[it] + del ar + mpi.report('Converted the FS data') + + def dft_band_characters(self): + """ + Reads in the band characters generated in Elk to be used for + PDOS and band character band structure plots. + """ + + if not (mpi.is_master_node()): + return + mpi.report("Reading BC.OUT") + + # get needed data from hdf file + # from general info + ar = HDFArchive(self.hdf_file, 'a') + things_to_read = ['SP', 'SO','n_k','n_orbitals'] + for it in things_to_read: + if not hasattr(self, it): + setattr(self, it, ar[self.dft_subgrp][it]) + #from misc info + things_to_read = ['nstsv','band_window'] + for it in things_to_read: + if not hasattr(self, it): + setattr(self, it, ar[self.misc_subgrp][it]) + #from sym info + things_to_read = ['n_atoms'] + symm_subgrp=self.symmcorr_subgrp + for it in things_to_read: + if not hasattr(self, it): + setattr(self, it, ar[symm_subgrp][it]) + + #read in band characters + [bc,maxlm] = read_Elk.read_bc(self) + #set up SO bc array + if (self.SO): + tmp = numpy.zeros([2*maxlm,1,self.n_atoms,self.nstsv,self.n_k], numpy.float_) + #put both spinors into the lm array indices. + tmp[0:maxlm,0,:,:,:]=bc[0:maxlm,0,:,:,:] + tmp[maxlm:2*maxlm,0,:,:,:]=bc[0:maxlm,1,:,:,:] + maxlm=2*maxlm + del bc + bc = tmp + del tmp + + #reduce bc matrix to band states stored in hdf file + n_spin_blocs=self.SP+1-self.SO + tmp = numpy.zeros([maxlm,n_spin_blocs,self.n_atoms,numpy.max(self.n_orbitals),self.n_k], numpy.float_) + for ik in range(self.n_k): + for isp in range(n_spin_blocs): + nst=self.n_orbitals[ik,isp] + ibot=self.band_window[isp][ik, 0]-1 + itop=ibot+nst + tmp[:,isp,:,0:nst,ik]=bc[:,isp,:,ibot:itop,ik] + del bc + bc = tmp + del tmp + + things_to_save = ['maxlm', 'bc'] + if not (self.bc_subgrp in ar): + ar.create_group(self.bc_subgrp) + for it in things_to_save: + ar[self.bc_subgrp][it] = locals()[it] + del ar + mpi.report('Converted the band character data') + diff --git a/python/triqs_dft_tools/converters/elktools/__init__.py b/python/triqs_dft_tools/converters/elktools/__init__.py new file mode 100644 index 00000000..28231317 --- /dev/null +++ b/python/triqs_dft_tools/converters/elktools/__init__.py @@ -0,0 +1,27 @@ + +########################################################################## +# +# TRIQS: a Toolbox for Research in Interacting Quantum Systems +# +# Copyright (C) 2019 by A. D. N. James, A. Hampel and M. Aichhorn +# +# TRIQS is free software: you can redistribute it and/or modify it under the +# terms of the GNU General Public License as published by the Free Software +# Foundation, either version 3 of the License, or (at your option) any later +# version. +# +# TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY +# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more +# details. +# +# You should have received a copy of the GNU General Public License along with +# TRIQS. If not, see . +# +########################################################################## + +from .readElkfiles import readElkfiles +from .elk_converter_tools import ElkConverterTools + +__all__ =['readElkfiles','ElkConverterTools'] + diff --git a/python/triqs_dft_tools/converters/elktools/elk_converter_tools.py b/python/triqs_dft_tools/converters/elktools/elk_converter_tools.py new file mode 100644 index 00000000..c7686e3d --- /dev/null +++ b/python/triqs_dft_tools/converters/elktools/elk_converter_tools.py @@ -0,0 +1,296 @@ + +########################################################################## +# +# TRIQS: a Toolbox for Research in Interacting Quantum Systems +# +# Copyright (C) 2019 by A. D. N. James, M. Zingl and M. Aichhorn +# +# TRIQS is free software: you can redistribute it and/or modify it under the +# terms of the GNU General Public License as published by the Free Software +# Foundation, either version 3 of the License, or (at your option) any later +# version. +# +# TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY +# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more +# details. +# +# You should have received a copy of the GNU General Public License along with +# TRIQS. If not, see . +# +########################################################################## + +from types import * +import numpy +import os.path +from locale import atof + + +class ElkConverterTools: + """ + Conversion Tools required to help covert Elk outputs into the TRIQS format. + """ + + def __init__(self): + pass + + def rotaxang(self,rot): + """ + This routine determines the axis of rotation vector (v) and the angle of rotation (th). + If R corresponds to an improper rotation then only the proper part is used and the determinant + is set to -1. The rotation convention follows the "right-hand rule". See Elk's rotaxang + routine. + """ + eps=1E-8 + v=numpy.zeros([3], numpy.float_) + # find the determinant + det=numpy.linalg.det(rot) + if (abs(det-1.0)eps): + # theta not equal to 0 or pi + th=-numpy.arctan2(t1,t2) + v[:]=v[:]/t1 + else: + # special case of sin(th)=0 + if(t2>eps): + # zero angle: axis arbitrary + th=0.0 + v[:]=1.0/numpy.sqrt(3.0) + else: + # rotation by pi + th=numpy.pi + if((rotp[0,0]>=rotp[1,1])&(rotp[0,0]>=rotp[2,2])): + if(rotp[0,0]<(-1.0+eps)): + mpi.report(rotp[0,0],-1.0+eps) + raise "sym_converter : Invalid rotation matrix!" + v[0]=numpy.sqrt(abs(rotp[0,0]+1.0)/2.0) + v[1]=(rotp[1,0]+rotp[0,1])/(4.0*v[0]) + v[2]=(rotp[2,0]+rotp[0,2])/(4.0*v[0]) + elif((rotp[1,1]>=rotp[0,0])&(rotp[1,1]>=rotp[2,2])): + if(rotp[1,1]<(-1.0+eps)): + mpi.report(rotp[1,1],-1.0+eps) + raise "sym_converter : Invalid rotation matrix!" + v[1]=numpy.sqrt(abs(rotp[1,1]+1.0)/2.0) + v[2]=(rotp[2,1]+rotp[1,2])/(4.0*v[1]) + v[0]=(rotp[0,1]+rotp[1,0])/(4.0*v[1]) + else: + if(rotp[2,2]<(-1.0+eps)): + mpi.report(rotp[2,2],-1.0+eps) + raise "sym_converter : Invalid rotation matrix!" + v[2]=numpy.sqrt(abs(rotp[2,2]+1.0)/2.0) + v[0]=(rotp[0,2]+rotp[2,0])/(4.0*v[2]) + v[1]=(rotp[1,2]+rotp[2,1])/(4.0*v[2]) + # return theta and v + return v,th + + def axangsu2(self,v,th): + """ + Calculate the rotation SU(2) matrix - see Elk's axangsu2 routine. + """ + su2=numpy.zeros([2,2], numpy.complex_) + t1=numpy.sqrt(numpy.dot(v,v)) + if(t1<1E-8): + raise "sym_converter : zero length axis vector!" + # normalise the vector + t1=1.0/t1 + x=v[0]*t1; y=v[1]*t1; z=v[2]*t1 + #calculate the SU(2) matrix + cs=numpy.cos(0.5*th) + sn=numpy.sin(0.5*th) + su2[0,0]=cs-z*sn*1j + su2[0,1]=-y*sn-x*sn*1j + su2[1,0]=y*sn-x*sn*1j + su2[1,1]=cs+z*sn*1j + #return the SU(2) matrix + return su2 + + def v3frac(self,v,eps): + """ + This finds the fractional part of 3-vector v components. This uses the + same method as in Elk (version 6.2.8) r3fac subroutine. + """ + v[0]=v[0]-numpy.floor(v[0]) + if(v[0] < 0): v[0]+=1 + if((1-v[0]) < eps): v[0]=0 + if(v[0] < eps): v[0]=0 + v[1]=v[1]-numpy.floor(v[1]) + if(v[1] < 0): v[1]+=1 + if((1-v[1]) < eps): v[1]=0 + if(v[1] < eps): v[1]=0 + v[2]=v[2]-numpy.floor(v[2]) + if(v[2] < 0): v[2]+=1 + if((1-v[2]) < eps): v[2]=0 + if(v[2] < eps): v[2]=0 + return v + + def gen_perm(self,nsym,ns,na,natmtot,symmat,tr,atpos,epslat=1E-6): + """ + Generate the atom permutations per symmetry. + """ + perm=[] + iea=[] + for isym in range(nsym): + iea.append(numpy.zeros([natmtot,ns], numpy.int_)) + #loop over species + for js in range(ns): + #loop over species atoms + v=numpy.zeros([3,na[js]], numpy.float_) + v2=numpy.zeros(3, numpy.float_) + for ia in range(na[js]): + v[:,ia]=self.v3frac(atpos[js][ia][0:3],epslat) + for ia in range(na[js]): + v2[:]=numpy.matmul(symmat[isym][:,:],(atpos[js][ia][0:3]+tr[isym])) + v2[:]=self.v3frac(v2,epslat) + for ja in range(na[js]): + t1=sum(abs(v[:,ja]-v2[:])) #check + if(t1 < epslat): + iea[isym][ja,js]=ia + break + #put iea into perm format + for isym in range(nsym): + perm.append([]) + ja=0 + prv_atms=0 + for js in range(ns): + for ia in range(na[js]): + perm[isym].append(iea[isym][ia,js]+prv_atms+1) + ja+=1 + prv_atms+=na[js] + #output perm + return perm + + def symlat_to_complex_harmonics(self,nsym,n_shells,symlat,shells): + """ + This calculates the Elk (crystal) symmetries in complex spherical harmonics + This follows the methodology used in Elk's rotzflm, ylmrot and ylmroty routines. + """ + #need SciPy routines to get Euler angles - need version 1.4+ + #from scipy.spatial.transform import Rotation as R + symmat=[] + rot=numpy.identity(3, numpy.float_) + angi=numpy.zeros(3, numpy.float_) + #loop over symmetries + for isym in range(nsym): + symmat.append([]) + for ish in range(n_shells): + l=shells[ish]['l'] + symmat[isym].append(numpy.zeros([2*l+1, 2*l+1], numpy.complex_)) + #get determinant + det=numpy.linalg.det(symlat[isym]) + p=1 + #p is -1 for improper symmetries + if(det<0.0): p=-1 + rot[:,:]=p*symlat[isym][:,:] + #r=R.from_matrix(rot) + #get the y-convention Euler angles as used by Elk. + #ang=r.as_euler('zyz') + ang=self.zyz_euler(rot) + #Elk uses inverse rotations, i.e. the function is being rotated, not the spherical harmonics + angi[0]=-ang[2] + angi[1]=-ang[1] + angi[2]=-ang[0] + #calculate the symmetry in the complex spherical harmonic basis. + d = self.ylmrot(p,angi,l) + symmat[isym][ish][:,:] = d[:,:] + #return the complex spherical harmonic + return symmat + + def zyz_euler(self,rot): + """ + This calculates the Euler angles of matrix rot in the y-convention. + See Elk's roteuler routine. + This will be made redundent when TRIQS uses scipy version 1.4+ + """ + eps=1E-8 + pi=numpy.pi + ang=numpy.zeros(3, numpy.float_) + #get the Euler angles + if((abs(rot[2,0])>eps) or (abs(rot[2,1])>eps)): + ang[0]=numpy.arctan2(rot[2,1],rot[2,0]) + if(abs(rot[2,0])>abs(rot[2,1])): + ang[1]=numpy.arctan2(rot[2,0]/numpy.cos(ang[0]),rot[2,2]) + else: + ang[1]=numpy.arctan2(rot[2,1]/numpy.sin(ang[0]),rot[2,2]) + ang[2]=numpy.arctan2(rot[1,2],-rot[0,2]) + else: + ang[0]=numpy.arctan2(rot[0,1],rot[0,0]) + if(rot[2,2]>0.0): + ang[1]=0.0 + ang[2]=0.0 + else: + ang[1]=pi + ang[2]=pi + #return Euler angles + return ang + + + def ylmrot(self,p,angi,l): + """ + calculates the rotation matrix in complex spherical harmonics for l. + THIS HAS ONLY BEEN TESTED FOR l=2. + """ + d=numpy.identity(2*l+1, numpy.complex_) + # generate the rotation matrix about the y-axis + dy=self.ylmroty(angi[1],l) + # apply inversion to odd l values if required + if(p==-1): + if(l % 2.0 != 0): + dy*=-1 + # rotation by alpha and gamma + for m1 in range(-l,l+1,1): + lm1=l+m1 + for m2 in range(-l,l+1,1): + lm2=l+m2 + t1=-m1*angi[0]-m2*angi[2] + d[lm1,lm2]=dy[lm1,lm2]*(numpy.cos(t1)+1j*numpy.sin(t1)) + #return the rotation matrix + return d + + def ylmroty(self,beta,l): + """ + returns the rotation matrix around the y-axis with angle beta. + This uses the same real matrix formual as in Elk - see Elk's manual for ylmroty description + """ + #import the factorial function - needed for later versions of scipy (needs testing) + from scipy import special as spec + #calculates the rotation matrix in complex spherical harmonics for l + dy=numpy.identity(2*l+1, numpy.float_) + #sine and cosine of beta + cb=numpy.cos(beta/2.0) + sb=numpy.sin(beta/2.0) + # generate the rotaion operator for m-components of input l + for m1 in range(-l,l+1,1): + for m2 in range(-l,l+1,1): + sm=0.0 + minlm=numpy.amin([l+m1, l-m2]) + 1 + for k in range(minlm): + if(((l+m1-k)>=0) and ((l-m2-k)>=0) and ((m2-m1+k)>=0)): + j=2*(l-k)+m1-m2 + if(j==0): + t1=1.0 + else: + t1=cb**j + j=2*k+m2-m1 + if(j!=0): + t1=t1*sb**j + t2=t1/(spec.factorial(k)*spec.factorial(l+m1-k)*spec.factorial(l-m2-k)*spec.factorial(m2-m1+k)) + if(k % 2.0 != 0): + t2=-t2 + sm+=t2 + t1=numpy.sqrt(spec.factorial(l+m1)*spec.factorial(l-m1)*spec.factorial(l+m2)*spec.factorial(l-m2)) + dy[m1+l,m2+l]=t1*sm + #return y-rotation matrix + return dy + diff --git a/python/triqs_dft_tools/converters/elktools/readElkfiles.py b/python/triqs_dft_tools/converters/elktools/readElkfiles.py new file mode 100644 index 00000000..c3bbdea6 --- /dev/null +++ b/python/triqs_dft_tools/converters/elktools/readElkfiles.py @@ -0,0 +1,687 @@ + +########################################################################## +# +# TRIQS: a Toolbox for Research in Interacting Quantum Systems +# +# Copyright (C) 2019 by A. D. N. James, M. Zingl and M. Aichhorn +# +# TRIQS is free software: you can redistribute it and/or modify it under the +# terms of the GNU General Public License as published by the Free Software +# Foundation, either version 3 of the License, or (at your option) any later +# version. +# +# TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY +# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more +# details. +# +# You should have received a copy of the GNU General Public License along with +# TRIQS. If not, see . +# +########################################################################## + +from types import * +import numpy +from triqs_dft_tools.converters.converter_tools import * +import os.path +from locale import atof + + +class readElkfiles: + """ + Read in the Elk output files for the elk_converter.py routines. + """ + + def __init__(self): + self.dft_file = 'PROJ.OUT' + self.band_file = 'BAND.OUT' + self.eval_file = 'EIGVAL.OUT' + self.efermi_file = 'EFERMI.OUT' + self.kp_file = 'KPOINTS.OUT' + self.geom_file='GEOMETRY.OUT' + + def read_elk_file(self, filename, to_replace): + #this function is almost identical to read_fortran_file, but it removes words after ':' + """ + Returns a generator that yields all numbers in the Fortran file as float, with possible replacements. + + Parameters + ---------- + filename : string + Name of Fortran-produced file. + to_replace : dict of str:str + Dictionary defining old_char:new_char. + + Yields + ------ + string + The next number in file. + + """ + #import os.path + #import string + import locale + from locale import atof + if not(os.path.exists(filename)): + raise IOError("File %s does not exist." % filename) + for line in open(filename, 'r'): + for old, new in to_replace.items(): + line = line.replace(old, new) + # removes the substring after ':' character - if it exists + if ":" in line: + line = self.split_string(line) + if "(" in line: + line = self.split_string3(line) + for x in line.split(): + yield atof(x) + + def read_elk_file2(self, filename, to_replace): + #this function is almost identical to read_fortran_file, but it removes words after '(' + """ + Returns a generator that yields all numbers in the Fortran file as float, with possible replacements. + + Parameters + ---------- + filename : string + Name of Fortran-produced file. + to_replace : dict of str:str + Dictionary defining old_char:new_char. + + Yields + ------ + string + The next number in file. + + """ + import os.path + import string + if not(os.path.exists(filename)): + raise IOError("File %s does not exist." % filename) + for line in open(filename, 'r'): + for old, new in to_replace.items(): + line = line.replace(old, new) + # removes the substring after '(' character - if it exists + if "(" in line: + line = self.split_string2(line,'(') + # removes the substring after '+' character - if it exists + if "+" in line: + line = self.split_string2(line,'+') + # removes the substring after '|' character - if it exists + if "|" in line: + line = self.split_string2(line,'|') + #only include lines which have multiple characters + if(len(line)>1): + yield line.split() + + def split_string(self,line): + """ + This removes the excess information after ':' of the string read in from the file + """ + temp = line.split(':') + line = temp[0] + return line + + def split_string2(self,line,str): + """ + This removes the excess information after 'str' of the string read in from the file + """ + temp = line.split(str) + line = temp[0] + return line + + def split_string3(self,line): + """ + This removes the excess information after '(' of the string read in from the file + """ + temp = line.split('(') + line = temp[0] + return line + + + def read_proj(self,dft_file):#,things_to_set): + """ + This function reads the contents of PROJ.OUT and returns them for general use. + """ + #read in PROJ.OUT file + R = self.read_elk_file( dft_file, self.fortran_to_replace) + try: + #arrays of entry names + gen_info_entries = ['nproj', 'n_k', 'spinpol', 'SO','natm'] + proj_entries = ['sort', 'natom', 'l', 'dim'] + at_entries = ['spatom','atom'] + #Read in the No. of projectors, no. of k-points, spin and spinorb info + gen_info = {name: int(val) for name, val in zip(gen_info_entries, R)} + #mpi.report(gen_info) + #read in the information of all the projectors + #initialized variables + icorr=0 + lmax=3 #maximum l value that will be used + n_shells=0 + n_inequiv_shells=0 + #local arrays + neqatom=[]#numpy.zeros([n_shells], numpy.int) + proj=[] + shells=[]#numpy.zeros([n_shells], numpy.int) + corr_shells=[]#numpy.zeros([n_shells], numpy.int) + prjtype=[] + wan=[] + proj_info=[]#numpy.zeros([n_shells], numpy.int) + T=[] + basis=[] + inequiv_to_corr=[] + corr_to_inequiv=[] + ind=[] + proj_idx=[] + at=[] + idxlm=[] + #assign global variables + n_k=gen_info['n_k'] + SO=gen_info['SO'] + #loop over projector flags + for ip in range(gen_info['nproj']): + #projector index + proj_idx.append(int(next(R))) + proj.append({name: int(val) for name, val in zip(proj_entries, R)}) + na=proj[ip]['natom'] # integer which reduces when reading in atom info + while(na>0): + neqatom.append(int(next(R))) + na-=neqatom[ip] + #appends the mapping array to index of inequivalent atom in shells + inequiv_to_corr.append(icorr) + for ia in range(neqatom[ip]): + corr_to_inequiv.append(n_inequiv_shells) + at.append({name: int(val) for name, val in zip(at_entries, R)}) + shells.append(proj[ip].copy()) + shells[n_shells].update({'atom':at[n_shells]['atom'], 'spatom':at[n_shells]['spatom']}) + corr_shells.append(shells[n_shells].copy()) + n_orb=2*shells[n_shells]['l']+1 + #lm submatrix indices + idxlm.append(numpy.zeros(2*lmax+1, dtype=numpy.int_)) + nrep=proj[ip]['dim'] + for i in range(nrep): + idxlm[n_shells][i]=next(R)-1 + ind.append(idxlm[n_shells][0:nrep]) + #determine basis type and transformation matrix + basis.append(int(next(R))) + #determine whether which basis the projectors where generated in + #spherical harmonics + T.append(numpy.zeros([n_orb, n_orb], dtype=numpy.complex_)) + #Elk generated unitary basis + if (basis[n_shells]==2): + #reads the transformation matrix + for i in range(n_orb): + for j in range(n_orb): + T[n_shells][i, j] = next(R) + for i in range(n_orb): + for j in range(n_orb): + T[n_shells][i, j] += 1j * next(R) + #transformation matrix from spherical harmonics to cubic basis + elif (basis[n_shells]==1): + T[n_shells]=self.determine_T(shells[n_shells]['l']) + else: + for i in range(n_orb): + T[n_shells][i,i] = 1.0 + #index for the next inequivalent atom (+1 to index is not needed as this is incorporated in + #neqatom[ish] + n_shells+=1 + #increase the numer of inequivalent atoms + n_inequiv_shells+=1 + #increase the inequiv_to_corr value + icorr+=neqatom[ip] + #end reading the file if read the last projector + if (ip+1==gen_info['nproj']): + break + #determine the irreducible representation + dim_reps=[] + n_reps=[] + irep=[] + for ish in range(n_inequiv_shells): + isheq=inequiv_to_corr[ish] + [n_reps,dim_reps,irep] = self.determine_rep(isheq,ish,corr_shells,basis,ind,n_reps,dim_reps,irep) + for ish in range(n_shells): + ishin=corr_to_inequiv[ish] + corr_shells[ish].update({'SO':SO, 'irep':irep[ishin]}) + + except StopIteration: # a more explicit error if the file is corrupted. + #raise "Elk_converter : reading PROJ.OUT file failed!" + raise IOError("Elk_converter : reading PROJ.OUT file failed!") + + R.close() + #output desired information + return (gen_info,n_shells,n_inequiv_shells,corr_to_inequiv,inequiv_to_corr,corr_shells,n_reps,dim_reps,ind,basis,T) + + def determine_T(self,l): + """ + Current version calculates the transformation matrix T to convert the inputs from spherical + harmonics to the cubic basis (as used in TRIQS and Wien2k). + This routine is currently very similar to spherical_to_cubic in the TRIQS library. + This routine can be extended to include other unitary rotation matrices + """ + from math import sqrt + size=2*l+1 + T = numpy.zeros((size,size),dtype=complex) + if(l == 0): + T[0,0]= 1.0 + elif(l == 1): + T[0,0] = 1.0/sqrt(2); T[0,2] = -1.0/sqrt(2) + T[1,0] = 1j/sqrt(2); T[1,2] = 1j/sqrt(2) + T[2,1] = 1.0 + elif l == 2: + T[0,2] = 1.0 + T[1,0] = 1.0/sqrt(2); T[1,4] = 1.0/sqrt(2) + T[2,0] =-1.0/sqrt(2); T[2,4] = 1.0/sqrt(2) + T[3,1] = 1.0/sqrt(2); T[3,3] =-1.0/sqrt(2) + T[4,1] = 1.0/sqrt(2); T[4,3] = 1.0/sqrt(2) + elif l == 3: + #This needs to be checked + T[0,0] = 1.0/sqrt(2); T[0,6] = -1.0/sqrt(2) + T[1,1] = 1.0/sqrt(2); T[1,5] = 1.0/sqrt(2) + T[2,2] = 1.0/sqrt(2); T[2,4] = -1.0/sqrt(2) + T[3,3] = 1.0 + T[4,2] = 1j/sqrt(2); T[4,4] = 1j/sqrt(2) + T[5,1] = 1j/sqrt(2); T[5,5] = -1j/sqrt(2) + T[6,0] = 1j/sqrt(2); T[6,6] = 1j/sqrt(2) + else: raise ValueError("determine: implemented only for l=0,1,2,3") + return numpy.matrix(T) + + + def determine_rep(self,ish,ishin,corr_shells,basis,ind,n_reps,dim_reps,irep): + """ + Determines the irreducible representation used for projection calculation. + Only for Cubic harmonics at the moment + """ + #if all of the orbitals were used to construct the projectors + rep=corr_shells[ish]['dim'] + if(rep==2*corr_shells[ish]['l']+1): + n_reps.append(1) + dim_reps.append([corr_shells[ish]['dim']]) + irep.append(1) + #if a subset of obitals were used for generating the projectors (l>1) + #if Elk generated T matrix is used + elif((basis[ish]==2)&(corr_shells[ish]['l']>1)): + if (corr_shells[ish]['l']==2): + n_reps.append(2) + dim_reps.append([3, 2]) + irep.append(dim_reps[ishin].index(rep)+1) + elif (corr_shells[ish]['l']==3): + n_reps.append(3) + dim_reps.append([1, 3, 3]) + #cubic T matrix + elif((basis[ish]==1)&(corr_shells[ish]['l']>1)): + if (corr_shells[ish]['l']==2): + n_reps.append(2) + dim_reps.append([2, 3]) + irep.append(dim_reps[ishin].index(rep)+1) + elif (corr_shells[ish]['l']==3): + n_reps.append(3) + dim_reps.append([2, 2, 3]) + #determine the dim_reps from the lm indices in ind + if(rep==3): + irep.append(3) + else: + for i in range(2): + #look for ind[i]==0 + if(ind[i]==0): + irep.append(1) + break + #default to irep=2 + elif(i==1): + irep.append(2) + + else: + raise ValueError("Elk_converter (determine_rep) : irreducible representations were not found!") + + return (n_reps,dim_reps,irep) + + def read_projector(self,shell,n_spin_blocks,ish,proj_mat,ind,T,basis,filext): + """ + This function reads the contents of WANPROJ_L**_S**_A****.OUT + """ + import string + l = str(shell[ish]['l']).zfill(2) + s = str(shell[ish]['sort']).zfill(2) + a = str(shell[ish]['spatom']).zfill(4) + #construct file name from atoms info + wan_shells_file = 'WANPROJ_L'+l+'_S'+s+'_A'+a+filext + R = self.read_elk_file(wan_shells_file, self.fortran_to_replace) + try: + #no. of kpts and number of orbital + gen_entries = ['n_k', 'lmmax','dim_rep'] + gen = {name: int(val) for name, val in zip(gen_entries, R)} + #projector lm size + dim=gen['lmmax'] + #no. of lm used to construct projector + dim_rep=gen['dim_rep'] + lat=[] + n_k=gen['n_k'] + n_orbitals = numpy.zeros([n_k, n_spin_blocks], numpy.int) + band_window = [None for isp in range(n_spin_blocks)] + for isp in range(n_spin_blocks): + band_window[isp] = numpy.zeros([n_k, 2], dtype=int) + for ik in range(0,n_k): + #k-point index and correlated band window indices + lat_entries = ['ik','vklx','vkly','vklz'] + lat.append({name: int(val) for name, val in zip(lat_entries, R)}) + #loop over each spin + for isp in range(0,n_spin_blocks): + #band window indices + proj_entries = ['isp', 'ist_min','ist_max'] + proj_dim={name: int(val) for name, val in zip(proj_entries, R)} + if(isp+1!=proj_dim['isp']): + raise IOError("Elk_converter (",wan_shells_file,") : reading spin projecotrs failed!") + return + #setting band window arrays + n_orbitals[ik,isp]=proj_dim['ist_max']-proj_dim['ist_min']+1 + band_window[isp][ik, 0] = proj_dim['ist_min'] + band_window[isp][ik, 1] = proj_dim['ist_max'] + #define temporary matrix for reading in the projectors + mat = numpy.zeros([dim, n_orbitals[ik,isp]], numpy.complex_) + # Real part + for j in range(dim): + for i in range(n_orbitals[ik,isp]): + mat[j, i] = next(R) + # Imag part: + for j in range(dim): + for i in range(n_orbitals[ik,isp]): + mat[j, i] += 1j * next(R) + #rotate projectors into basis T + if(basis[ish]!=0): + mat[:,:]=numpy.matmul(T[ish],mat[:,:]) + + #put desired projector subset into master array + proj_mat[ik,isp,ish,0:dim_rep,0:n_orbitals[ik,isp]]=mat[ind[ish],0:n_orbitals[ik,isp]] + #delete temporary index + del mat + #resize array length of band indices to maximum number used + proj_mat=proj_mat[:,:,:,:,:numpy.max(n_orbitals)] + + except StopIteration: # a more explicit error if the file is corrupted. + raise IOError("Elk_converter (read projectors): reading file failed!") + R.close() + return(n_orbitals,band_window,dim_rep,proj_mat) + + def read_eig(self,filext=".OUT"): + """ + This function reads the contents of EIGVAL.OUT and EFERMI.OUT + """ + import string + #construct file name from atoms info + R = self.read_elk_file( self.efermi_file, self.fortran_to_replace) + try: + efermi=next(R) + except StopIteration: # a more explicit error if the file is corrupted. + raise IOError("Elk_converter (EFERMI.OUT): reading file failed!") + eval_file = 'EIGVAL'+filext + R = self.read_elk_file( eval_file, self.fortran_to_replace) + try: + #no. of kpts + n_k=int(next(R)) + #no. second variation states (no. bands) + nstsv=int(next(R)) + en=[] + occ=[] + kp2=[] + for ik in range(0,n_k): + #k index and corresponing lattice coordinates + k_entries = ['ik', 'vklx','vkly','vklz'] + kp2.append([{name: val for name, val in zip(k_entries, R)}]) + en.append([]) + occ.append([]) + for ist in range(0,nstsv): + #stores the band index, energy eigenvalues and occupancies + en_entries = ['ist', 'hopping','occ'] + read_en={name: val for name, val in zip(en_entries, R)} + #Energy eigenvalues and occupations + en[ik].append(read_en['hopping']-efermi) + occ[ik].append(read_en['occ']) + + except StopIteration: # a more explicit error if the file is corrupted. + raise IOError("Elk_converter (EIGVAL.OUT): reading file failed!") + R.close() + return(en,occ,nstsv) + + def read_kpoints(self,filext=".OUT"): + """ + This function reads the contents of KPOINTS.OUT + """ + import string + kp_file = 'KPOINTS'+filext + R = self.read_elk_file( kp_file, self.fortran_to_replace) + try: + #no. of kpts + n_k=int(next(R)) + kp=[] + #reads in the k index, lattice vectors, weights and nmat for each kpt + #array for bz weights + bz_weights = numpy.ones([n_k], numpy.float_) / float(n_k) + #array for lattice vectors + vkl = numpy.ones([n_k,3], numpy.float_) + for ik in range(n_k): + #k-grid info + k_entries = ['ik', 'vklx','vkly','vklz', 'bz_weights', 'nmat'] + kp.append({name: val for name, val in zip(k_entries, R)}) + #convert to integers + kp[ik]['ik']=int(kp[ik]['ik']) + #read in BZ weights + bz_weights[ik]=kp[ik]['bz_weights'] + j=0 + for i in range(1,4): + vkl[ik,j]=kp[ik][k_entries[i]] + j=j+1 + except StopIteration: # a more explicit error if the file is corrupted. + raise IOError("Elk_converter (KPOINTS.OUT): reading file failed!") + R.close() + return(bz_weights,vkl) + + def readsym(self): + """ + Read in the (crystal) symmetries in lattice coordinates + """ + dft_file='SYMCRYS.OUT' + R = self.read_elk_file2( dft_file, self.fortran_to_replace) + try: + symmat=[] + spinmat=[] + tr=[] + #maximum symmetries + nsym = 48 + #set up symmetry matrices + for isym in range(nsym): + symmat.append(numpy.zeros([3, 3], numpy.float_)) + spinmat.append(numpy.zeros([3, 3], numpy.float_)) + tr.append(numpy.zeros([3], numpy.float_)) + #read the number of crystal symmetries + x = next(R) + nsym = int(atof(x[0])) + #read each symmetry + for isym in range(nsym): + #read the symmetry index and check it + x = next(R) + isymm = int(x[3]) + if(isym+1!=isymm): + raise IOError("Elk_converter : reading symmetries failed!") + #next read has no useful infomation + x = next(R) + #read in the translation vector used for symmetries + x = next(R) + for i in range(3): + tr[isym][i]=atof(x[i]) + #read in the spatial symmetries + #string with no useful information + x = next(R) + #read in the spatial symmetry + for i in range(3): + x = next(R) + for j in range(3): + symmat[isym][i,j]=int(atof(x[j])) + #string with no useful information + x = next(R) + #read in the spin symmetries + for i in range(3): + x = next(R) + for j in range(3): + spinmat[isym][i,j]=int(atof(x[j])) + + except StopIteration: # a more explicit error if the file is corrupted. + raise IOError("Elk_converter : reading SYMCRYS.OUT file failed!") + R.close() + return nsym,spinmat,symmat,tr + + def readlat(self): + """ + Read in the symmetries in lattice coordinates + """ + dft_file='LATTICE.OUT' + R = self.read_elk_file2( dft_file, self.fortran_to_replace) + try: + amat = numpy.zeros([3, 3], numpy.float_) + amatinv = numpy.zeros([3, 3], numpy.float_) + bmat = numpy.zeros([3, 3], numpy.float_) + bmatinv = numpy.zeros([3, 3], numpy.float_) + #real space lattice matrices + #cycling through information which is not needed + for i in range(4): + x = next(R) + #reading in the lattice vectors as matrix + for i in range(3): + x = next(R) + for j in range(3): + amat[i,j] = atof(x[j]) + #cycling through information which is not needed + x = next(R) + #reading in the inverse lattice matrix + for i in range(3): + x = next(R) + for j in range(3): + amatinv[i,j] = atof(x[j]) + #reciprocal lattice matrices + #cycling through information which is not needed + for i in range(5): + x = next(R) + #reading in the reciprocal lattice vectors as matrix + for i in range(3): + x = next(R) + for j in range(3): + bmat[i,j] = atof(x[j]) + #cycling through information which is not needed + x = next(R) + #reading in the inverse reciprocal lattice matrix + for i in range(3): + x = next(R) + for j in range(3): + bmatinv[i,j] = atof(x[j]) + + except StopIteration: # a more explicit error if the file is corrupted. + raise IOError("Elk_converter : reading PROJ.OUT file failed!") + R.close() + return amat,amatinv,bmat,bmatinv + + def read_geometry(self): + """ + This function reads the contents of GEOMETRY.OUT + """ + import string + #read in the Geometery file + dft_file='GEOMETRY.OUT' + #atom positions in lattice coordinates + R = self.read_elk_file2( dft_file, self.fortran_to_replace) + nspecies=0 + na=[] + atpos_entries = ['kx', 'ky','kz','Bkx', 'Bky', 'Bkz'] + atpos=[] + try: + i=0 + #cycle through file until "atoms" is found + while(i<1000): + x = next(R) + if "atoms" in x: + break + elif(i==1000): + raise IOError("Elk_converter : Could not find 'atoms' in GEOMETRY.OUT!") + i+=1 + #read in the number of species + x = next(R) + ns = int(atof(x[0])) + #loop over species + for js in range(ns): + #Skip species name + x = next(R) + #read in the number of atoms per species + x = next(R) + na.append(int(atof(x[0]))) + #loop over atomss pre species + atpos.append([]) + for ia in range(na[js]): + atpos[js].append(numpy.zeros(6, numpy.float_)) + x = next(R) + for j in range(6): + atpos[js][ia][j]=atof(x[j]) + except StopIteration: # a more explicit error if the file is corrupted. + raise IOError("Elk_converter : Could not open GEOMETRY.OUT!") + R.close() + return ns, na, atpos + +#band character dependent calculations + def read_bc(self): + """ + Read in the ELK generated band characters from BC.OUT + """ + + #import string + file = 'BC.OUT' + R = self.read_elk_file(file, self.fortran_to_replace) + try: + #no. of kpts and number of orbital + gen_entries = ['maxlm', 'nspinor','natmtot','nstsv','nkpt','irep'] + gen = {name: int(val) for name, val in zip(gen_entries, R)} + #projector lm size + #check the read in information complies with previous read in data + nspinor=self.SP+1 + if(gen['nspinor'] != nspinor): + mpi.report('HDF file nspinor = %s'%nspinor) + mpi.report('BC.OUT nspinor = %s'%gen['nspinor']) + raise IOError("Elk_converter (",file,") : reading nspinor failed!") + return + if(gen['natmtot'] != self.n_atoms): + raise IOError("Elk_converter (",file,") : reading no. of atoms failed!") + return + if(gen['nstsv'] != self.nstsv): + raise IOError("Elk_converter (",file,") : reading all states failed!") + return + if(gen['nkpt'] != self.n_k): + raise IOError("Elk_converter (",file,") : reading kpoints failed failed!") + return + if(gen['irep'] == 0): + raise IOError("Elk_converter (",file,") : Band characters are in spherical hamonics, may have issues with the PDOS!") + return + + dim=gen['maxlm'] + lmax=numpy.sqrt(dim)-1 + bc = numpy.zeros([dim,nspinor,self.n_atoms,self.nstsv,self.n_k], numpy.float_) + + for ik in range(0,self.n_k): + for iatom in range(0,self.n_atoms): + for ispn in range(0,nspinor): + entry = ['ispn','ias','is','ia','ik'] + ent = {name: int(val) for name, val in zip(entry, R)} + #k-point index and correlated band window indices + #check read in values + if(ent['ispn'] != ispn+1): + raise IOError("Elk_converter (",file,") : reading ispn failed!") + return + if(ent['ias'] != iatom+1): + raise IOError("Elk_converter (",file,") : reading iatom failed!") + return + if(ent['ik'] != ik+1): + raise IOError("Elk_converter (",file,") : reading ik failed!") + return + + for ist in range(self.nstsv): + for lm in range(dim): + bc[lm,ispn,iatom,ist,ik] = next(R) + + except StopIteration: # a more explicit error if the file is corrupted. + raise IOError("Elk_converter (read BC.OUT): reading file failed!") + R.close() + return(bc,dim) + diff --git a/python/triqs_dft_tools/sumk_dft.py b/python/triqs_dft_tools/sumk_dft.py index 1b103263..5e427528 100644 --- a/python/triqs_dft_tools/sumk_dft.py +++ b/python/triqs_dft_tools/sumk_dft.py @@ -42,7 +42,7 @@ class SumkDFT(object): def __init__(self, hdf_file, h_field=0.0, use_dft_blocks=False, dft_data='dft_input', symmcorr_data='dft_symmcorr_input', parproj_data='dft_parproj_input', symmpar_data='dft_symmpar_input', bands_data='dft_bands_input', transp_data='dft_transp_input', - misc_data='dft_misc_input'): + misc_data='dft_misc_input',bc_data='dft_bandchar_input',fs_data='dft_fs_input'): r""" Initialises the class from data previously stored into an hdf5 archive. @@ -92,6 +92,8 @@ class SumkDFT(object): self.bands_data = bands_data self.transp_data = transp_data self.misc_data = misc_data + self.bc_data = bc_data + self.fs_data = fs_data self.h_field = h_field self.block_structure = BlockStructure() @@ -1973,7 +1975,7 @@ class SumkDFT(object): return self.chemical_potential - def calc_density_correction(self, filename=None, dm_type='wien2k'): + def calc_density_correction(self, filename=None, dm_type='wien2k',spinave=False): r""" Calculates the charge density correction and stores it into a file. @@ -1997,13 +1999,16 @@ class SumkDFT(object): the corresponing total charge `dens`. """ - assert dm_type in ('vasp', 'wien2k'), "'dm_type' must be either 'vasp' or 'wienk'" - + assert dm_type in ('vasp', 'wien2k','elk'), "'dm_type' must be either 'vasp', 'wienk' or 'elk'" + #default file names if filename is None: if dm_type == 'wien2k': filename = 'dens_mat.dat' elif dm_type == 'vasp': filename = 'GAMMA' + elif dm_type == 'elk': + filename = 'DMATDMFT.OUT' + assert isinstance(filename, str), ("calc_density_correction: " "filename has to be a string!") @@ -2152,6 +2157,50 @@ class SumkDFT(object): valim = (deltaN['up'][ik][inu, imu].imag + deltaN['down'][ik][inu, imu].imag) / 2.0 f.write(" %.14f %.14f"%(valre, valim)) f.write("\n") + + elif dm_type == 'elk': + # output each k-point density matrix for Elk + if mpi.is_master_node(): + # read in misc data from .h5 file + things_to_read = ['band_window','vkl','nstsv'] + self.subgroup_present, self.value_read = self.read_input_from_hdf( + subgrp=self.misc_data, things_to_read=things_to_read) + # open file + with open(filename, 'w') as f: + # determine the number of spin blocks + n_spin_blocks = self.SP + 1 - self.SO + nbmax = numpy.max(self.n_orbitals) + # output beta and mu in Hartrees + beta = G_latt_iw.mesh.beta * self.energy_unit + mu = self.chemical_potential/self.energy_unit + # ouput n_k, nspin and max orbitals - a check + f.write(" %d %d %d %.14f %.14f ! nkpt, nspin, nstmax, beta, mu\n"%(self.n_k, n_spin_blocks, nbmax, beta, mu)) + for ik in range(self.n_k): + for ispn in range(n_spin_blocks): + #Determine the SO density matrix band indices from the spinor band indices + if(self.SO==1): + band0=[self.band_window[0][ik, 0],self.band_window[1][ik, 0]] + band1=[self.band_window[0][ik, 1],self.band_window[1][ik, 1]] + ib1=int(min(band0)) + ib2=int(max(band1)) + else: + #Determine the density matrix band indices from the spinor band indices + ib1 = self.band_window[ispn][ik, 0] + ib2 = self.band_window[ispn][ik, 1] + f.write(" %d %d %d %d ! ik, ispn, minist, maxist\n"%(ik + 1, ispn + 1, ib1, ib2)) + for inu in range(self.n_orbitals[ik, ispn]): + for imu in range(self.n_orbitals[ik, ispn]): + #output non-magnetic or spin-averaged density matrix + if((self.SP==0) or (spinave)): + valre = (deltaN['up'][ik][inu, imu].real + deltaN['down'][ik][inu, imu].real) / 2.0 + valim = (deltaN['up'][ik][inu, imu].imag + deltaN['down'][ik][inu, imu].imag) / 2.0 + else: + valre = deltaN[spn[ispn]][ik][inu, imu].real + valim = deltaN[spn[ispn]][ik][inu, imu].imag + f.write(" %.14f %.14f"%(valre, valim)) + f.write("\n") + + else: raise NotImplementedError("Unknown density matrix type: '%s'"%(dm_type)) diff --git a/python/triqs_dft_tools/sumk_dft_tools.py b/python/triqs_dft_tools/sumk_dft_tools.py index e11f42d7..e3af641c 100644 --- a/python/triqs_dft_tools/sumk_dft_tools.py +++ b/python/triqs_dft_tools/sumk_dft_tools.py @@ -186,8 +186,8 @@ class SumkDFTTools(SumkDFT): f.close() return DOS, DOSproj, DOSproj_orb - - + + def dos_wannier_basis_all(self, mu=None, broadening=None, mesh=None, with_Sigma=True, with_dc=True, save_to_file=True): """ Calculates the density of states in the basis of the Wannier functions. @@ -235,7 +235,7 @@ class SumkDFTTools(SumkDFT): #print(spn) n_local_orbs = self.proj_mat_csc.shape[2] gf_struct_parproj_all = [[(sp, list(range(n_local_orbs))) for sp in spn]] - + glist_all = [GfReFreq(indices=inner, window=(om_min, om_max), n_points=n_om) for block, inner in gf_struct_parproj_all[0]] G_loc_all = BlockGf(name_list=spn, block_list=glist_all, make_copies=False) @@ -463,6 +463,361 @@ class SumkDFTTools(SumkDFT): return DOS, DOSproj, DOSproj_orb + # Elk total and partial dos calculations + # Uses .data of only GfReFreq objects. + def elk_dos(self, mu=None, broadening=None, mesh=None, with_Sigma=True, with_dc=True, save_to_file=True,pdos=False,nk=None): + """ + This calculates the total DOS and the partial DOS (orbital-DOS) from the band characters calculated in Elk. + + Parameters + ---------- + mu : double, optional + Chemical potential, overrides the one stored in the hdf5 archive. + broadening : double, optional + Lorentzian broadening of the spectra. If not given, standard value of lattice_gf is used. + mesh : real frequency MeshType, optional + Omega mesh for the real-frequency Green's function. Given as parameter to lattice_gf. + with_Sigma : boolean, optional + If True, the self energy is used for the calculation. If false, the DOS is calculated without self energy. + with_dc : boolean, optional + If True the double counting correction is used. + save_to_file : boolean, optional + If True, text files with the calculated data will be created. + pdos : allows the partial density of states to be calculated + nk : diagonal of the occupation function (from the Matsubara Green's function) + in the band basis (has form nk[spn][n_k][n_orbital]) + + Returns + ------- + DOS : Dict of numpy arrays + Contains the full density of states. + pDOS : Dict of numpy arrays + partial (orbital resolved) DOS for each atom. + """ + + if (pdos): + things_to_read = ['maxlm', 'bc'] + value_read = self.read_input_from_hdf( + subgrp=self.bc_data, things_to_read=things_to_read) + if not value_read: + return value_read + things_to_read = ['n_atoms'] + value_read = self.read_input_from_hdf( + subgrp=self.symmcorr_data, things_to_read=things_to_read) + if not value_read: + return value_read + + if (mesh is None) and (not with_Sigma): + raise ValueError("lattice_gf: Give the mesh=(om_min,om_max,n_points) for the lattice GfReFreq.") + if mesh is None: + om_mesh = [x.real for x in self.Sigma_imp_w[0].mesh] + om_min = om_mesh[0] + om_max = om_mesh[-1] + n_om = len(om_mesh) + mesh = (om_min, om_max, n_om) + else: + om_min, om_max, n_om = mesh + om_mesh = numpy.linspace(om_min, om_max, n_om) + if mu is None: + mu = self.chemical_potential + + spn = self.spin_block_names[self.SO] + + DOS = {sp: numpy.zeros([n_om], numpy.float_) + for sp in self.spin_block_names[self.SO]} + #set up temporary arrays for pdos calculations + if (pdos): + pDOS = {sp: numpy.zeros([self.n_atoms,self.maxlm,n_om], numpy.float_) + for sp in self.spin_block_names[self.SO]} + ntoi = self.spin_names_to_ind[self.SO] + else: + pDOS = [] + + ikarray = numpy.array(range(self.n_k)) + for ik in mpi.slice_array(ikarray): + + G_latt_w = self.lattice_gf( + ik=ik, mu=mu, iw_or_w="w", broadening=broadening, mesh=mesh, with_Sigma=with_Sigma, with_dc=with_dc) + G_latt_w *= self.bz_weights[ik] + if(nk!=None): + for iom in range(n_om): + for bname, gf in G_latt_w: + numpy.fill_diagonal(G_latt_w[bname].data[iom,:,:].imag, nk[bname][ik][:]*G_latt_w[bname].data[iom,:,:].imag.diagonal()) + + # Non-projected DOS + for iom in range(n_om): + for bname, gf in G_latt_w: + DOS[bname][iom] -= gf.data[iom, :, :].imag.trace() / \ + numpy.pi + + + # Partial DOS + if (pdos): + for bname, gf in G_latt_w: + isp=ntoi[bname] + nst=self.n_orbitals[ik,isp] + tmp = numpy.zeros([nst]) + for iom in range(n_om): + #get diagonal spectral function + tmp[:] = -gf.data[iom, :, :].imag.diagonal() / numpy.pi + #calculate the pDOS of all atoms + for iatom in range(self.n_atoms): + bcar=self.bc[:,isp,iatom,0:nst,ik] + pDOS[bname][iatom,:,iom] += numpy.matmul(bcar,tmp) + del tmp + mpi.barrier() + # Collect data from mpi: + for bname in DOS: + DOS[bname] = mpi.all_reduce( + mpi.world, DOS[bname], lambda x, y: x + y) + if (pdos): + for bname in pDOS: + for iatom in range(self.n_atoms): + for lm in range(self.maxlm): + pDOS[bname][iatom,lm,:] = mpi.all_reduce( + mpi.world, pDOS[bname][iatom,lm,:], lambda x, y: x + y) + + + # Write to files + if save_to_file and mpi.is_master_node(): + for sp in self.spin_block_names[self.SO]: + f = open('TDOS_%s.dat' % sp, 'w') + for iom in range(n_om): + f.write("%s %s\n" % (om_mesh[iom], DOS[sp][iom])) + f.close() + + # Partial + if (pdos): + for iatom in range(self.n_atoms): + f = open('pDOS_%s_atom_%s.dat' % (sp, iatom), 'w') + for lm in range(self.maxlm): + for iom in range(n_om): + f.write("%s %s\n" % + (om_mesh[iom], pDOS[sp][iatom,lm,iom])) + f.write("\n") + f.close() + + return DOS, pDOS + + # vector manipulation used in Elk for symmetry operations - This is already in elktools, this should + # put somewhere for general use by the converter and this script. + def v3frac(self,v,eps): + #This finds the fractional part of 3-vector v components. This uses the + #same method as in Elk (version 6.2.8) r3fac subroutine. + v[0]=v[0]-numpy.floor(v[0]) + if(v[0] < 0): v[0]+=1 + if((1-v[0]) < eps): v[0]=0 + if(v[0] < eps): v[0]=0 + v[1]=v[1]-numpy.floor(v[1]) + if(v[1] < 0): v[1]+=1 + if((1-v[1]) < eps): v[1]=0 + if(v[1] < eps): v[1]=0 + v[2]=v[2]-numpy.floor(v[2]) + if(v[2] < 0): v[2]+=1 + if((1-v[2]) < eps): v[2]=0 + if(v[2] < eps): v[2]=0 + return v + + # Calculate the spectral function at an energy contour omega - i.e. Fermi surface plots + # Uses .data of only GfReFreq objects. + def fs_plot(self, mu=None, broadening=None, mesh=None, FS=True, plane=True, sym=True, orthvec=None, with_Sigma=True, with_dc=True, save_to_file=True): + """ + Calculates the correlated spectral function at specific frequencies. The default output is the + correlated spectral function at zero frequency - this relates the the Fermi surface. + + Parameters + ---------- + mu : double, optional + Chemical potential, overrides the one stored in the hdf5 archive. + broadening : double, optional + Lorentzian broadening of the spectra. If not given, standard value of lattice_gf is used. + mesh : real frequency MeshType, optional + Omega mesh for the real-frequency Green's function. Given as parameter to lattice_gf. + plane : boolean, optional + True assumes that the k-mesh of eigenvalues calculated was a plane. + sym: boolean, optional + Uses the symmetry operations to fold out the correlated spectral function in the BZ + FS: boolean + Flag for calculating the spectral function at the Fermi level (omega->0) + orthvec: double (3) element numpy array, optional + This is used to determine the vectors used in the plane calculations after folding out the IBZ. + This needs to correspond to the same orthonormal LATTICE inputs vectors used in the DFT code + which generated the plane of energy eigenvalues. + The default is orthvec=[0,0,1]. + with_Sigma : boolean, optional + If True, the self energy is used for the calculation. If false, the DOS is calculated without self energy. + with_dc : boolean, optional + If True the double counting correction is used. + save_to_file : boolean, optional + If True, text files with the calculated data will be created. + + Returns + ------- + nk : int + The number of k-points in the plane. + vkc : Dict of numpy arrays [shape - (nk, 3)] + Contains the cartesian vectors which the spectral function has been evaluated on. + Akw : Dict of numpy arrays [shape - (spn)(self.n_k, n_om)] + Correlated spectral function - the data as it is written to the files. + iknr : int array + An array of k-point indices which mape the Akw over the unfolded BZ. + """ + #default vector tolerance used in Elk. This should not be alter. + epslat=1E-6 + #read in the energy contour energies and projectors + things_to_read = ['n_k','bmat','symlat','n_symm','vkl', + 'n_orbitals', 'proj_mat', 'hopping'] + value_read = self.read_input_from_hdf( + subgrp=self.fs_data, things_to_read=things_to_read) + if not value_read: + return value_read + + if with_Sigma is True: + om_mesh = [x.real for x in self.Sigma_imp_w[0].mesh] + #for Fermi Surface calculations + if FS: + jw=[i for i in range(len(om_mesh)) if om_mesh[i] == 0.0] + if len(jw)==0: + mpi.report('Sigma_imp_w mesh does not include zero frequency value') + mpi.report('Using the next absolute lowest frequency value.') + abs_om_mesh = [abs(i) for i in om_mesh] + jw=[i for i in range(len(abs_om_mesh)) if abs_om_mesh[i] == numpy.min(abs_om_mesh[:])] + mpi.report(jw) + #for many energy contour calculations + else: + if mesh: + om_mn=mesh[0] + om_mx=mesh[1] + jw=[i for i in range(len(om_mesh)) if((om_mesh[i]<=om_mx)and(om_mesh[i]>=om_mn))] + om_min = om_mesh[0] + om_max = om_mesh[-1] + n_om = len(om_mesh) + mesh = (om_min, om_max, n_om) + print(mesh) + if broadening is None: + broadening=0.0 + print(broadening) + elif mesh is None: + #default is to set "mesh" to be just for the Fermi surface - omega=0.0 + om_min = 0.000 + om_max = 0.001 + n_om = 3 + mesh = (om_min, om_max, n_om) + om_mesh = numpy.linspace(om_min, om_max, n_om) + if broadening is None: + broadening=0.01 + FS=True + print(with_Sigma,with_dc) + jw=[i for i in range(len(om_mesh)) if((om_mesh[i]<=om_max)and(om_mesh[i]>=om_min))] + else: + #a range of frequencies can be used if desired + om_min, om_max, n_om = mesh + om_mesh = numpy.linspace(om_min, om_max, n_om) + FS=False + jw=[i for i in range(len(om_mesh)) if((om_mesh[i]<=om_max)and(om_mesh[i]>=om_min))] + if mu is None: + mu = self.chemical_potential + + #orthogonal vector used for plane calculations + if orthvec is None: + #set to [0,0,1] by default + orthvec = numpy.zeros(3,dtype=numpy.float_) + orthvec[2] = 1.0 + elif orthvec.size != 3: + assert 0, "The input numpy orthvec is not the required size of 3!" + + spn = self.spin_block_names[self.SO] + + Akw = {sp: numpy.zeros([self.n_k, n_om], numpy.float_) + for sp in spn} + + #Cartesian lattice coordinates array + vkc = numpy.zeros([self.n_k,3], numpy.float_) + + ikarray = numpy.array(range(self.n_k)) + for ik in mpi.slice_array(ikarray): + #calculate the catesian coordinates of IBZ + vkc[ik,:] = numpy.matmul(self.bmat,self.vkl[ik,:]) + + G_latt_w = self.lattice_gf( + ik=ik, mu=mu, iw_or_w="w", broadening=broadening, mesh=mesh, with_Sigma=with_Sigma, with_dc=with_dc) + + for iom in range(n_om): + for bname, gf in G_latt_w: + Akw[bname][ik, iom] += gf.data[iom,:,:].imag.trace() / (-1.0 * numpy.pi) + mpi.barrier() + + # Collect data from mpi: + for sp in spn: + Akw[sp] = mpi.all_reduce(mpi.world, Akw[sp], lambda x, y: x + y) + mpi.barrier() + + #fold out the IBZ k-points using the lattice vectors and symmetries + #reducible number of k-points (which will alter after out folding) + nk = self.n_k + iknr = numpy.arange(self.n_k) + if sym: + vkltmp = self.vkl + v = numpy.zeros(3, numpy.float_) + v_orth = numpy.zeros(3, numpy.float_) + for isym in range(self.n_symm): + #calculate the orthonormal vector after symmetry operation. This is used to + #check if the orthonormal vector after the symmetry operation is parallel + #or anit-parallel to the original vector. + if plane: + vo = numpy.matmul(self.symlat[isym][:,:],orthvec[:].transpose()) + #check if the vectors are parallel or anti-parallel respectively + t1 = numpy.array_equal(vo, orthvec) + if(not t1): + #exit this symmetry operation + continue + + for ik in range(self.n_k): + #find point in BZ by symmetry operation + v[:]=numpy.matmul(self.symlat[isym][:,:],self.vkl[ik,:]) + #shift back in to range [0,1) - Elk specific + v[:]=self.v3frac(v,epslat) + #add vector to list if not present and add the equivalent Akw value + #convert to cartesian + v[:] = numpy.matmul(self.bmat,v[:]) + #alter temporary arrays + nk += 1 + vkc = numpy.vstack((vkc,v)) + iknr = numpy.append(iknr,ik) + vkltmp = numpy.vstack((vkltmp,v)) + #remove duplicates + [vkc,ind]=numpy.unique(vkc,return_index=True,axis=0) + iknr=iknr[ind] + nk=vkc.shape[0] + #sort the indices for output in decending order + iksrt=numpy.lexsort(([vkc[:,i] for i in range(0,vkc.shape[1], 1)])) + #rearrange the vkc and iknr arrays + vkc=vkc[iksrt] + iknr=iknr[iksrt] + + # Write to files + if save_to_file and mpi.is_master_node(): + for sp in self.spin_block_names[self.SO]: + if FS: + #Output default FS spectral function + f = open('Akw_FS_%s.dat' % sp, 'w') + for ik in range(nk): + jk=iknr[ik] + f.write("%s %s %s %s\n" % (vkc[ik,0], vkc[ik,1], vkc[ik,2], Akw[bname][jk, jw[0]])) + f.close() + else: + #Output spectral function from multiple frequencies + for iom in jw: + #output the energy contours in multiple files with mesh index. + f = open('Akw_%s_omega_%s.dat' % (sp, iom), 'w') + for ik in range(nk): + jk=iknr[ik] + f.write("%s %s %s %s %s\n" % (vkc[ik,0], vkc[ik,1], vkc[ik,2], om_mesh[iom], Akw[bname][jk, iom])) + f.close() + return nk, vkc, Akw, iknr + + + # Uses .data of only GfReFreq objects. def spaghettis(self, broadening=None, plot_shift=0.0, plot_range=None, ishell=None, mu=None, save_to_file='Akw_'): """ @@ -497,7 +852,7 @@ class SumkDFTTools(SumkDFT): subgrp=self.bands_data, things_to_read=things_to_read) if not value_read: return value_read - if ishell is not None: + if ishell: things_to_read = ['rot_mat_all', 'rot_mat_all_time_inv'] value_read = self.read_input_from_hdf( subgrp=self.parproj_data, things_to_read=things_to_read) @@ -792,12 +1147,12 @@ class SumkDFTTools(SumkDFT): # Uses .data of only GfReFreq objects. def transport_distribution(self, beta, directions=['xx'], energy_window=None, Om_mesh=[0.0], with_Sigma=False, n_om=None, broadening=0.0): r""" - Calculates the transport distribution + Calculates the transport distribution .. math:: \Gamma_{\alpha\beta}\left(\omega+\Omega/2, \omega-\Omega/2\right) = \frac{1}{V} \sum_k Tr\left(v_{k,\alpha}A_{k}(\omega+\Omega/2)v_{k,\beta}A_{k}\left(\omega-\Omega/2\right)\right) - in the direction :math:`\alpha\beta`. The velocities :math:`v_{k}` are read from the transport subgroup of the hdf5 archive. + in the direction :math:`\alpha\beta`. The velocities :math:`v_{k}` are read from the transport subgroup of the hdf5 archive. Parameters ---------- @@ -807,14 +1162,14 @@ class SumkDFTTools(SumkDFT): directions : list of double, optional :math:`\alpha\beta` e.g.: ['xx','yy','zz','xy','xz','yz']. energy_window : list of double, optional - Specifies the upper and lower limit of the frequency integration for :math:`\Omega=0.0`. The window is automatically enlarged by the largest :math:`\Omega` value, + Specifies the upper and lower limit of the frequency integration for :math:`\Omega=0.0`. The window is automatically enlarged by the largest :math:`\Omega` value, hence the integration is performed in the interval [energy_window[0]-max(Om_mesh), energy_window[1]+max(Om_mesh)]. Om_mesh : list of double, optional :math:`\Omega` frequency mesh of the optical conductivity. For the conductivity and the Seebeck coefficient :math:`\Omega=0.0` has to be part of the mesh. In the current version Om_mesh is repined to the mesh provided by the self-energy! The actual mesh is printed on the screen and stored as member Om_mesh. with_Sigma : boolean, optional - Determines whether the calculation is performed with or without self energy. If this parameter is set to False the self energy is set to zero (i.e. the DFT band + Determines whether the calculation is performed with or without self energy. If this parameter is set to False the self energy is set to zero (i.e. the DFT band structure :math:`A(k,\omega)` is used). Note: For with_Sigma=False it is necessary to specify the parameters energy_window, n_om and broadening. n_om : integer, optional Number of equidistant frequency points in the interval [energy_window[0]-max(Om_mesh), energy_window[1]+max(Om_mesh)]. This parameters is only used if @@ -873,7 +1228,7 @@ class SumkDFTTools(SumkDFT): n_om = len(self.omega) mpi.report("Using omega mesh provided by Sigma!") - if energy_window is not None: + if energy_window: # Find according window in Sigma mesh ioffset = numpy.sum( self.omega < energy_window[0] - max(Om_mesh)) @@ -979,7 +1334,7 @@ class SumkDFTTools(SumkDFT): def transport_coefficient(self, direction, iq, n, beta, method=None): r""" Calculates the transport coefficient A_n in a given direction for a given :math:`\Omega`. The required members (Gamma_w, directions, Om_mesh) have to be obtained first - by calling the function :meth:`transport_distribution `. For n>0 A is set to NaN if :math:`\Omega` is not 0.0. + by calling the function :meth:`transport_distribution `. For n>0 A is set to NaN if :math:`\Omega` is not 0.0. Parameters ---------- @@ -1042,10 +1397,10 @@ class SumkDFTTools(SumkDFT): def conductivity_and_seebeck(self, beta, method=None): r""" - Calculates the Seebeck coefficient and the optical conductivity by calling - :meth:`transport_coefficient `. - The required members (Gamma_w, directions, Om_mesh) have to be obtained first by calling the function - :meth:`transport_distribution `. + Calculates the Seebeck coefficient and the optical conductivity by calling + :meth:`transport_coefficient `. + The required members (Gamma_w, directions, Om_mesh) have to be obtained first by calling the function + :meth:`transport_distribution `. Parameters ---------- @@ -1060,7 +1415,7 @@ class SumkDFTTools(SumkDFT): seebeck : dictionary of double Seebeck coefficient in each direction. If zero is not present in Om_mesh the Seebeck coefficient is set to NaN. - kappa : dictionary of double. + kappa : dictionary of double. thermal conductivity in each direction. If zero is not present in Om_mesh the thermal conductivity is set to NaN """ diff --git a/test/python/CMakeLists.txt b/test/python/CMakeLists.txt index 369c2846..3c71ddee 100644 --- a/test/python/CMakeLists.txt +++ b/test/python/CMakeLists.txt @@ -5,7 +5,7 @@ foreach(file ${all_h5_ref_files}) endforeach() # Copy other files -FILE(COPY SrVO3.pmat SrVO3.struct SrVO3.outputs SrVO3.oubwin SrVO3.ctqmcout SrVO3.symqmc SrVO3.sympar SrVO3.parproj hk_convert_hamiltonian.hk LaVO3-Pnma_hr.dat LaVO3-Pnma.inp LaVO3-Pnma_ef_hr.dat LaVO3-Pnma_ef.inp LaVO3-Pbnm.inp LaVO3-Pbnm_hr.dat DESTINATION ${CMAKE_CURRENT_BINARY_DIR}) +FILE(COPY SrVO3.pmat SrVO3.struct SrVO3.outputs SrVO3.oubwin SrVO3.ctqmcout SrVO3.symqmc SrVO3.sympar SrVO3.parproj hk_convert_hamiltonian.hk LaVO3-Pnma_hr.dat LaVO3-Pnma.inp LaVO3-Pnma_ef_hr.dat LaVO3-Pnma_ef.inp LaVO3-Pbnm.inp LaVO3-Pbnm_hr.dat EFERMI.OUT EIGVAL.OUT GEOMETRY.OUT KPOINTS.OUT LATTICE.OUT PROJ.OUT SYMCRYS.OUT WANPROJ_L02_S03_A0001.OUT DESTINATION ${CMAKE_CURRENT_BINARY_DIR}) # List of all tests diff --git a/test/python/EFERMI.OUT b/test/python/EFERMI.OUT new file mode 100644 index 00000000..c6f3bb6e --- /dev/null +++ b/test/python/EFERMI.OUT @@ -0,0 +1 @@ + 0.2995688599 diff --git a/test/python/EIGVAL.OUT b/test/python/EIGVAL.OUT new file mode 100644 index 00000000..a23d79a2 --- /dev/null +++ b/test/python/EIGVAL.OUT @@ -0,0 +1,5860 @@ + 29 : nkpt + 198 : nstsv + + 1 0.000000000 0.000000000 0.000000000 : k-point, vkl + (state, eigenvalue and occupancy below) + 1 -2.763355033 1.000000000 + 2 -2.763355032 1.000000000 + 3 -2.763355028 1.000000000 + 4 -2.763355026 1.000000000 + 5 -2.763330853 1.000000000 + 6 -2.763330852 1.000000000 + 7 -2.763330849 1.000000000 + 8 -2.763330846 1.000000000 + 9 -2.669478312 1.000000000 + 10 -2.669478309 1.000000000 + 11 -2.669478307 1.000000000 + 12 -2.669478301 1.000000000 + 13 -2.669465091 1.000000000 + 14 -2.669465088 1.000000000 + 15 -2.669465087 1.000000000 + 16 -2.669465080 1.000000000 + 17 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l, lm submatrix size + 1 : Subset no. of equivalent atoms + 1 9 : atom, spatom + 1 2 3 4 5 : lm indices + 1 : Cubic Harmonics + diff --git a/test/python/SYMCRYS.OUT b/test/python/SYMCRYS.OUT new file mode 100644 index 00000000..3874790c --- /dev/null +++ b/test/python/SYMCRYS.OUT @@ -0,0 +1,580 @@ + +(translation vectors and rotation matrices are in lattice coordinates) + + 48 : nsymcrys + +Crystal symmetry : 1 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 1 0 0 + 0 1 0 + 0 0 1 + global spin rotation : + 1 0 0 + 0 1 0 + 0 0 1 + +Crystal symmetry : 2 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + -1 0 0 + 0 -1 0 + 0 0 -1 + global spin rotation : + -1 0 0 + 0 -1 0 + 0 0 -1 + +Crystal symmetry : 3 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + -1 0 -1 + 0 -1 -1 + 0 0 1 + global spin rotation : + -1 0 -1 + 0 -1 -1 + 0 0 1 + +Crystal symmetry : 4 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + -1 0 -1 + 0 -1 -1 + 1 1 1 + global spin rotation : + -1 0 -1 + 0 -1 -1 + 1 1 1 + +Crystal symmetry : 5 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + -1 0 -1 + 0 1 0 + 0 0 1 + global spin rotation : + -1 0 -1 + 0 1 0 + 0 0 1 + +Crystal symmetry : 6 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + -1 0 -1 + 0 1 0 + 1 -1 0 + global spin rotation : + -1 0 -1 + 0 1 0 + 1 -1 0 + +Crystal symmetry : 7 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + -1 0 0 + -1 0 -1 + 1 -1 0 + global spin rotation : + -1 0 0 + -1 0 -1 + 1 -1 0 + +Crystal symmetry : 8 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + -1 0 0 + -1 0 -1 + 1 1 1 + global spin rotation : + -1 0 0 + -1 0 -1 + 1 1 1 + +Crystal symmetry : 9 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + -1 0 -1 + -1 0 0 + 1 1 1 + global spin rotation : + -1 0 -1 + -1 0 0 + 1 1 1 + +Crystal symmetry : 10 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + -1 0 0 + 0 -1 0 + 1 1 1 + global spin rotation : + -1 0 0 + 0 -1 0 + 1 1 1 + +Crystal symmetry : 11 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + -1 0 0 + 0 1 1 + 0 0 -1 + global spin rotation : + -1 0 0 + 0 1 1 + 0 0 -1 + +Crystal symmetry : 12 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + -1 0 0 + 0 1 1 + 1 -1 0 + global spin rotation : + -1 0 0 + 0 1 1 + 1 -1 0 + +Crystal symmetry : 13 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 -1 -1 + -1 0 -1 + 0 0 1 + global spin rotation : + 0 -1 -1 + -1 0 -1 + 0 0 1 + +Crystal symmetry : 14 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 -1 -1 + -1 0 -1 + 1 1 1 + global spin rotation : + 0 -1 -1 + -1 0 -1 + 1 1 1 + +Crystal symmetry : 15 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 -1 -1 + 0 -1 0 + -1 1 0 + global spin rotation : + 0 -1 -1 + 0 -1 0 + -1 1 0 + +Crystal symmetry : 16 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 -1 -1 + 0 -1 0 + 1 1 1 + global spin rotation : + 0 -1 -1 + 0 -1 0 + 1 1 1 + +Crystal symmetry : 17 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 -1 -1 + 1 0 0 + -1 1 0 + global spin rotation : + 0 -1 -1 + 1 0 0 + -1 1 0 + +Crystal symmetry : 18 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 -1 -1 + 1 0 0 + 0 0 1 + global spin rotation : + 0 -1 -1 + 1 0 0 + 0 0 1 + +Crystal symmetry : 19 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 -1 0 + -1 0 0 + 0 0 -1 + global spin rotation : + 0 -1 0 + -1 0 0 + 0 0 -1 + +Crystal symmetry : 20 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 -1 0 + -1 0 0 + 1 1 1 + global spin rotation : + 0 -1 0 + -1 0 0 + 1 1 1 + +Crystal symmetry : 21 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 -1 0 + 0 -1 -1 + -1 1 0 + global spin rotation : + 0 -1 0 + 0 -1 -1 + -1 1 0 + +Crystal symmetry : 22 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 -1 0 + 0 -1 -1 + 1 1 1 + global spin rotation : + 0 -1 0 + 0 -1 -1 + 1 1 1 + +Crystal symmetry : 23 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 -1 0 + 1 0 1 + -1 1 0 + global spin rotation : + 0 -1 0 + 1 0 1 + -1 1 0 + +Crystal symmetry : 24 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 -1 0 + 1 0 1 + 0 0 -1 + global spin rotation : + 0 -1 0 + 1 0 1 + 0 0 -1 + +Crystal symmetry : 25 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 1 0 + -1 0 -1 + 0 0 1 + global spin rotation : + 0 1 0 + -1 0 -1 + 0 0 1 + +Crystal symmetry : 26 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 1 0 + -1 0 -1 + 1 -1 0 + global spin rotation : + 0 1 0 + -1 0 -1 + 1 -1 0 + +Crystal symmetry : 27 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 1 0 + 0 1 1 + -1 -1 -1 + global spin rotation : + 0 1 0 + 0 1 1 + -1 -1 -1 + +Crystal symmetry : 28 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 1 0 + 0 1 1 + 1 -1 0 + global spin rotation : + 0 1 0 + 0 1 1 + 1 -1 0 + +Crystal symmetry : 29 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 1 0 + 1 0 0 + -1 -1 -1 + global spin rotation : + 0 1 0 + 1 0 0 + -1 -1 -1 + +Crystal symmetry : 30 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 0 1 0 + 1 0 0 + 0 0 1 + global spin rotation : + 0 1 0 + 1 0 0 + 0 0 1 + +Crystal symmetry : 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spatial rotation : + 0 1 1 + 1 0 1 + 0 0 -1 + global spin rotation : + 0 1 1 + 1 0 1 + 0 0 -1 + +Crystal symmetry : 37 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 1 0 0 + 0 -1 -1 + -1 1 0 + global spin rotation : + 1 0 0 + 0 -1 -1 + -1 1 0 + +Crystal symmetry : 38 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 1 0 0 + 0 -1 -1 + 0 0 1 + global spin rotation : + 1 0 0 + 0 -1 -1 + 0 0 1 + +Crystal symmetry : 39 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 1 0 0 + 0 1 0 + -1 -1 -1 + global spin rotation : + 1 0 0 + 0 1 0 + -1 -1 -1 + +Crystal symmetry : 40 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + -1 0 -1 + -1 0 0 + 1 -1 0 + global spin rotation : + -1 0 -1 + -1 0 0 + 1 -1 0 + +Crystal symmetry : 41 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 1 0 0 + 1 0 1 + -1 -1 -1 + global spin rotation : + 1 0 0 + 1 0 1 + -1 -1 -1 + +Crystal symmetry : 42 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 1 0 0 + 1 0 1 + -1 1 0 + global spin rotation : + 1 0 0 + 1 0 1 + -1 1 0 + +Crystal symmetry : 43 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 1 0 1 + 0 -1 0 + -1 1 0 + global spin rotation : + 1 0 1 + 0 -1 0 + -1 1 0 + +Crystal symmetry : 44 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 1 0 1 + 0 -1 0 + 0 0 -1 + global spin rotation : + 1 0 1 + 0 -1 0 + 0 0 -1 + +Crystal symmetry : 45 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 1 0 1 + 0 1 1 + -1 -1 -1 + global spin rotation : + 1 0 1 + 0 1 1 + -1 -1 -1 + +Crystal symmetry : 46 + spatial translation : + 0.000000000 0.000000000 0.000000000 + spatial rotation : + 1 0 1 + 0 1 1 + 0 0 -1 + global spin rotation : + 1 0 1 + 0 1 1 + 0 0 -1 + +Crystal symmetry : 47 + spatial translation : 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1.5821110666053109E-003 -1.9305843239022815E-002 7.3948291649094874E-003 2.5688598808826721E-003 + -1.9767026871361268E-002 8.4426494513562697E-002 -2.6094952282863501E-002 2.4923907921858054E-002 -1.1177681357214296E-003 -3.6005327747597925E-004 -7.0240465340215663E-002 7.0067441465269817E-002 4.6047114315541258E-003 1.0799486561424800E-002 -2.0487605704491808E-002 3.4839956073978738E-002 7.0142582582294897E-003 7.9975662292034750E-003 + + -0.60015773798531369 -5.0225238992998238E-002 0.13063212040555733 9.9799692804757076E-002 0.14917781334256933 -0.37993231353675305 -0.29689379032611091 -0.46702805110246015 0.15913249010285188 5.3779164048848270E-002 -0.27667727536871395 -6.2534079394356151E-002 -7.1940661470902362E-002 3.5728857045359483E-002 + 0.12513852393147354 7.9746348301775238E-002 0.28704964953365653 -0.23164717062473977 -6.7587487154241455E-005 -1.6859114705447542E-005 -1.7104135401375415E-002 7.5672602065902286E-003 -2.0136396425954241E-002 3.6421478846619837E-002 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5.6409533612357590E-003 -7.0477909475885336E-003 -1.0277870876457942E-007 -4.3011662977353827E-007 -1.0640171628618248E-006 -1.5286082450541400E-006 7.1860420168931794E-007 2.6466629684853761E-006 0.66184234685942644 -0.44377404257980341 + 0.68031660721465670 -0.60161052802426451 2.7070370424292500E-005 1.3354910134519976E-005 1.2741033758256748E-005 1.0848415333525319E-005 -2.3261354329708051E-007 -1.4072033348751234E-006 -3.3014824616144793E-002 -5.8852923173934292E-002 + 8.6364269664945832E-006 -6.5616494681544313E-006 -4.0913092091266991E-006 8.6724760294995755E-006 2.2195363311994289E-005 4.0226256061987531E-006 -1.8246459653525218E-005 2.9571228869928674E-005 1.4273821865600726E-005 -6.1757545031093207E-006 + diff --git a/test/python/elk.in b/test/python/elk.in new file mode 100644 index 00000000..4b9a3491 --- /dev/null +++ b/test/python/elk.in @@ -0,0 +1,53 @@ +! This example generates the spin-polarised Wannier projector outputs for Ba2YIrO6 +! Wannier Ir-d states + +! Example by Alyn D. N. James + +tasks + 0 + 805 + +spinorb + .true. + +ngridk + 8 8 8 + +rgkmax + 7.0 + +!Path to Elk's species directory +sppath + '../../../../../species/' + +avec + 7.888832000 7.888832000 0.000000000 + 7.888832000 -7.888832000 0.000000000 + 7.888832000 0.000000000 7.888832000 + +atoms + 4 : nspecies +'O.in' : spfname + 6 : natoms; atposl, bfcmt below + 0.26449000 0.26449000 0.47102000 0.00000000 0.00000000 0.00000000 + 0.73551000 0.73551000 0.52898000 0.00000000 0.00000000 0.00000000 + 0.73551000 0.73551000 0.00000000 0.00000000 0.00000000 0.00000000 + 0.26449000 0.26449000 0.00000000 0.00000000 0.00000000 0.00000000 + 0.73551000 0.26449000 0.00000000 0.00000000 0.00000000 0.00000000 + 0.26449000 0.73551000 0.00000000 0.00000000 0.00000000 0.00000000 +'Ba.in' : spfname + 2 : natoms; atposl, bfcmt below + 0.75000000 0.25000000 0.50000000 0.00000000 0.00000000 0.00000000 + 0.25000000 0.75000000 0.50000000 0.00000000 0.00000000 0.00000000 +'Ir.in' : spfname + 1 : natoms; atposl, bfcmt below + 0.50000000 0.50000000 0.00000000 0.00000000 0.00000000 0.00000000 +'Y.in' : spfname + 1 : natoms; atposl, bfcmt below + 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 + +wanproj !projector flag + 1 !number of projectors + 3 2 5 !species, l, lm submatrix size + 5 6 7 8 9 !the lm quanties which will be projected (vector length eq. rlmmax) +-0.045 0.1617 ![-1.22, 4] eV correlated energy window including the t2g+eg+Op. diff --git a/test/python/elk_convert.py b/test/python/elk_convert.py new file mode 100644 index 00000000..9fe8c900 --- /dev/null +++ b/test/python/elk_convert.py @@ -0,0 +1,34 @@ +################################################################################ +# +# TRIQS: a Toolbox for Research in Interacting Quantum Systems +# +# Copyright (C) 2011 by M. Aichhorn, L. Pourovskii, V. Vildosola +# +# TRIQS is free software: you can redistribute it and/or modify it under the +# terms of the GNU General Public License as published by the Free Software +# Foundation, either version 3 of the License, or (at your option) any later +# version. +# +# TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY +# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more +# details. +# +# You should have received a copy of the GNU General Public License along with +# TRIQS. If not, see . +# +################################################################################ + +from h5 import * +from triqs.utility.comparison_tests import * +from triqs.utility.h5diff import h5diff +import triqs.utility.mpi as mpi + +from triqs_dft_tools.converters import ElkConverter + +Converter = ElkConverter(filename='Ba2YIrO6') +Converter.hdf_file = 'elk_convert.out.h5' +Converter.convert_dft_input() + +if mpi.is_master_node(): + h5diff('elk_convert.out.h5','elk_convert.ref.h5') diff --git a/test/python/elk_convert.ref.h5 b/test/python/elk_convert.ref.h5 new file mode 100644 index 00000000..2ffe186b Binary files /dev/null and b/test/python/elk_convert.ref.h5 differ