mirror of https://github.com/triqs/dft_tools
192 lines
6.1 KiB
ReStructuredText
192 lines
6.1 KiB
ReStructuredText
.. highlight:: python
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#########
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PLO tools
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#########
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Introduction
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************
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This set of tools is intended for processing of raw projectors read
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from VASP. One of the main tasks is to generate an orthonormalized subset
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of PLOs constructed according to the :doc:`config-file </config>`.
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To produce the final output the following steps are undertaken:
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* Parse input config-file
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* Input raw VASP data
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* Convert the raw VASP data into an internal representaion and check it for consistency.
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* Generate a set of projector shells according to the parameters of the config-file
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* Create a set of projector groups
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* Perform necessary group operations (such as :ref:`orthogonalization<ortho>`) on the constituing shells
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* Calculate and output some useful quantities (bare density matrix, DOS, etc.)
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Initial Processing
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******************
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The raw data from VASP files is initially read in simple objects (containers).
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Then these objects are combined in an another object containing all necessary
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electronic structure data. At this stage simple consistency checks are performed:
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* the basic dimensions, such as the number of bands, number of `k`-points, etc.,
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are consistent for all data
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* the `k`-point mesh are read both the IBZKPT and EIGENVAL and it is worth checking
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that both sets are coinciding
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* in case tetrahedron data is read from IBZKPT, the tetrahedron volume must be related
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to the total volume of the unit cell as derived from POSCAR
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All electronic structure from VASP is stored in a class ElectronicStructure:
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.. autoclass:: triqs_dft_tools.converters.plovasp.elstruct.ElectronicStructure
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:members:
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Consistency with parameters
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* parameters in the config-file should pass trivial checks such as that the ion
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list does not contain non-existing ions (boundary check for ion indices)
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.. function:: check_vasp_data_consistency(conf_pars, vasp_data)
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**Parameters**:
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- *conf_pars* (dict) : dictionary of input parameters from conf-file
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- *vasp_data* (dict) : dictionary containing all VASP data
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**Returns**:
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*None*
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**Raises**:
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A meaningful exception indicating an inconsistency in the input data
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Selecting projector subsets
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===========================
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The first step of PLO processing is to select subsets of projectors
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corresponding to PLO groups. Each group contains a set of shells.
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Each projector shell is represented by an object 'ProjectorShell'
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that contains an array of projectors and information on the shell itself
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(orbital number, ions, etc.). 'ProjectorShell's are contained in
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both a list of shells (according to the original list as read
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from config-file) and in a 'ProjectorGroup' object, the latter
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also providing information about the energy window.
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`[In fact, shell container can be a simple dictionary.]`
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Order of operations:
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- transform projectors (all bands) in each shell
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- select transformed shell projectors for a given group within the window
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- orthogonalize if necessary projectors within a group by performing
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the following operations for each k-point:
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* combine all projector shells into a single array
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* orthogonalize the array
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* distribute back the arrays assuming that the order is preserved
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.. autoclass:: triqs_dft_tools.converters.plovasp.proj_shell.ProjectorShell
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:members:
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The class is using a helper function `select_bands()` for selecting a subset of bands.
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.. function:: select_bands(eigvals, emin, emax)
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**Parameters**:
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- *eigvals* (numpy.array) : array of eigenvalues
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- *emin*, *emax* (float) : energy window
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**Returns**:
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*ib_win*, *nb_min*, *nb_max* (numpy.array[int], int, int) :
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lowest and highest indices of the selected bands
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.. _ortho:
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Orthogonalization
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-----------------
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At the second stage the selected projectors are orthogonalized (orthonormalized).
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Orthogonalization can be performed in different ways if projection is made
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on several ions or if several correlated shells per ion are considered.
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In the case of several correlated ions per unit cell (and one correlated shell per ion)
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at least two options can be considered:
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#. Projectors are normalized for each ion separetely. In this case, corresponding
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Wannier functions for different ions are generally not orthogonal.
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#. Projectors are normalized for all ions in the unit cell simultaneously. This
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ensures that the Wannier functions for different ions are mutually orthogonal.
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The way the normalization of a PLO group is done is controlled by two group parameters:
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- *NORMALIZE* (True/False) : indicates whether the PLO group is normalized (True by default)
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- *NORMION* (True/False) : indicates whether the PLO group is normalized on a per-ion basis
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(False by default)
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Storing generated projectors
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****************************
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After the PLOs are generated they are stored to text files which can be subsequently
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converted to TRIQS h5-files (using the converter). The general format of the file
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is a JSON-header containing all necessary parameters followed by a set of arrays.
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There is always one (control) file containing general information (`k`-kpoints, lattice vectors etc.)
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and `at least` one file containing correlated groups (one file for each group).
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Control file format
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===================
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Filename '<namebase>.ctrl'. Contains the data shared between all shells.
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The JSON-header consists of the following elements:
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* *nk*: number of `k`-points
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* *ns*: number of spin channels
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* *nc_flag*: collinear/noncollinear case (False/True)
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* *ng*: number of projector groups
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* Symmetry information (list of symmetry operations)
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* *efermi*: Fermi level (optional)
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* Lattice information
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Projector-group file format
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===========================
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Projector-group files have names '<namebase>.plog<Ng>'.
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They essentially contain serialized objects of class 'ProjectorGroup'.
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The JSON-header has, thus, the following elements:
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* *shells*: list of shells
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* each shell is a dictionary:
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- *lshell*: orbital number `l`
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- *nion*: number of ions
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- *ndim*: number of orbitals/ion
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- *nbmax*: maxmimum number of bands (needed for array allocations)
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* *emin*, *emax*: energy window
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