Skip to main content

Library for generating highly-efficient generalized Monkhorst-Pack k-point grids.

Project description

kplib

pipeline status

A C++ library for finding the optimal Generalized Monkhorst-Pack k-points grid. Please send any questions about the underlying library and algorithms to kpoints@jhu.edu.

How to compile the library?

We use cmake to detect native build environment and generate native build files. For Unix-like operating systems, users can build the project by:

$ git clone https://gitlab.com/muellergroup/kplib.git
$ cd kplib
$ mkdir build
$ cd build
$ cmake ..
$ make

Then you can find a static library libkpoints.a and a dynamic library libkpoints.so in the ./build directory.

How to use the library?

There are basically two steps:

  1. copy the header file src/kPointLatticeGenerator.h to your include folder, and add the following line to your source code

     #include "kPointLatticeGenerator.h"
    
  2. link the library at the linking stage.

    For example, to link the static library and compile the object myapp.o to the final executable myapp, you can

     $ g++ myapp.o -L /path/to/lib libkpoints.a -o myapp
    

    If you want to use the dynamic library, you can

     $ export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/path/to/lib
     $ g++ myapp.o -L /path/to/lib -lkpoints -o myapp
    

    The first line tells the loader, ld, where to find the shared library at runtime, since the dynamic linkage only puts a reference of the library in the executable.

Then you are ready to go!

API

Class: kPointLatticeGenerator

template <typename T>
using Tensor = std::vector<std::vector<T>>;

/**
 * Constructor.
 *
 * To see how the variables are defined, check the "Conventions" section below)
 *
 * @param primVectorsArray            primitive lattice vectors in rows.
 * @param conventionalVectorsArray    conventional lattice vectors in rows.
 * @param latticePointOperatorsArray  point operators of the Laue Class
                                      of the input structure, expressed
                                      in the basis of primitive lattice vectors
 * @param numOperators                number of point operators in above array
 * @param isConventionalHexaognal     whether the conventional lattice is
                                      hexagonal
 */
KPointLatticeGenerator(const double primVectorsArray[3][3],
                       const double conventionalVectorsArray[3][3],
                       const int latticePointOperatorsArray[][3][3],
                       const int numOperators,
                       const bool isConventionalHexagonal);

/*
 * Specify whether to generate a gamma-centered grid or a shifted grid.
 * The available shifts are:
 *     {{0.0, 0.0, 0.5}, {0.0, 0.5, 0.0}, {0.5, 0.0, 0.0}, {0.5, 0.5, 0.0},
 *      {0.5, 0.0, 0.5}, {0.0, 0.5, 0.5}, {0.5, 0.5, 0.5}}
 * Basiclly, side centers, face centers and the body center.
 *
 * @param includeGamma   TRUE:  gamma-centered grid
 *                       FALSE: grid with one of the above shift
 *                       AUTO:  search both shifted and gamma-centered grid
 *                              and return the best one.
 */
enum INCLUDE_GAMMA { TRUE, FALSE, AUTO };
void includeGamma(INCLUDE_GAMMA includeGamma);

/*
 * @param minDistance  The returned grid should have a corresponding
 *                     real-space superlattice whose "minimum periodic distance"
 *                     is no smaller than this value.
 * @param minSize      Minimum number of total k-points of grids returned.
 */
KPointLattice getKPointLattice(const double minDistance,
                               const int minSize);

Class: KPointLattice

It's meant to hold the found k-point grid and provide query functions.

The main query routines of this type:

double getMinPeriodicDistance();

int getNumDistinctKPoints();

int numTotalKPoints();

/*
 * @return Tensor<double> 2D arrays of coordinates. It's basically a wrapper
 *                        of "double coords[][3]".
 */
Tensor<double> getKPointCoordinates();

/*
 * @return vector<int>  1D array of k-points weights.
 */
std::vector<int> getKPointWeights();

Conventions

This section specifies the conventions we use for the variables used in kPointLatticeGenerator constructor: i.e. primVectors, conventionalVectors, latticePointOperators and isConventionalHexagonal.

Lattice Vectors

Lattice vectors are expressed as row vectors of the lattice matrix:

double primtiveVectors[3][3] = {{a_x, a_y, a_z},
                                {b_x, b_y, b_z},
                                {c_a, c_z, c_y}}

Point Operators

Each operation is a 3x3 integral matrix, representing how a fractional coordinate in the primitive lattice basis is transformed under this operation.

int latticePointOperations[][3][3];

Because of the lattice vectors are expressed as rows, each symmetry operation is done through "x' = xT . R", i.e. vector times matrix.

Conventional Lattice Vectors

Becuase of the algorithm we use to efficiently iterate symmetry-preserving superlattice, the conventional lattice vectors should follow the below requirements:

  • For all lattice systems, except for triclinic, the c-vector should be along the axis of the highest order rotational operation, i.e the 4-fold, 6-fold, 3-fold, 4-fold, any 2-fold, and 2-fold rotation for cubic, hexagonal, trigonal, tetragonal, orthorhombic, and monoclinic lattices, respectively. This direction is commonly referred as the "primary symmetry direction" in crystallography textbooks.

  • For trigonal lattices, the conventional lattices should be primitive hexagonal lattices, i.e. the trigonal-centered hexagonal.

The algorithm doesn't put constraints on triclinic system, or on the centering type of lattices in the 2/m and the mmm Laue class.

(Note: User could get the primary directions from the point symmetry opeartions.)

Example of using kplib -- demo_kplib

To demonstrate the usage of the kpbib, we implement a simple C++ application to find Generalised Monkhorst-Pack k-point grids. It use spglib to determine symmetries (Togo and Tanaka, 2010) and output the k-point grid in the format of VASP KPOINTS file.

It's under the folder demo_kplib. To build this application, user should build spglib and replace the library file libsymspg.a in ./lib. Then the executable demo_kplib can be built by

$ cd demo_kplib
$ mkdir build
$ cd build
$ cmake ..
$ make

The binary is placed at ./build/demo_kplib. To call it, use:

$ demo_kplib /path/to/POSCAR /path/to/PRECALC > KPOINTS

The POSCAR is one of the standard VASP input file. The PRECALC file is the input file of demo_kplib and users can find its specifications on our website. Since it's for demonstration purposes, only the parameters MINDISTANCE, MINTOTALKPOINTS, and INCLUDEGAMMA are valid.

There are some examples of using this application in demo_kplib/examples.

For a more complete application, check our K-point Grid Generator and K-point Server.

Code snippet of demo_kpib

Below are excerpts from the application to show how to use the kplib API.

main.cpp:

#include "kPointLatticeGenerator.h"
#include "utils.h"
#include "precalc.h"
#include "poscar.h"
#include <iostream>

int main(int argc, char **argv) {
    if (argc < 3) {
        std::cerr << "Usage: ./main /path/to/POSCAR /path/to/PRECALC"
                  << std::endl;
        return 1;
    }
    // Parse POSCAR and PRECALC.
    Poscar poscar;
    poscar.readFromPoscar(std::string(argv[1]));
    Precalc precalc(argv[2]);

    // Execute the main routines.
    KPointLatticeGenerator generator = initializeKPointLatticeGeneratorObject(
        poscar.primitiveLattice, poscar.coordinates, poscar.atomTypes);

    if (precalc.getIncludeGamma() == "TRUE") {
        generator.includeGamma(TRUE);
    } else if (precalc.getIncludeGamma() == "FALSE") {
        generator.includeGamma(FALSE);
    } else if (precalc.getIncludeGamma() == "AUTO") {
        generator.includeGamma(AUTO);
    }

    KPointLattice latticeGamma = generator.getKPointLattice(
        precalc.getMinDistance(), precalc.getMinTotalKpoints());

    outputLattice(latticeGamma);
}

utils.cpp:

#include "utils.h"
#include "spglib.h"
... // other includes and functions

// Wrapper of the kPointLatticeGenerator constructor.
KPointLatticeGenerator initializeKPointLatticeGeneratorObject(
        Tensor<double> primitiveLattice,
        Tensor<double> coordinates,
        std::vector<int> atomTypes) {

    double primLatticeArray[3][3] = {0};
    double conventionalLatticeArray[3][3] = {0};
    int rotation[192][3][3] = {0};
    int size = 0;
    bool isConventionalHexagonal = false;

    // use spglib to get necessary parameters for the consturctor
    // of kPointLatticeGenerator.
    ...

    KPointLatticeGenerator generator = KPointLatticeGenerator(primLatticeArray,
            conventionalLatticeArray, rotation, size, isConventionalHexagonal);
    return generator;

}

Python interface

Installation

The source code is downloaded at https://gitlab.com/muellergroup/kplib .

$ git clone https://gitlab.com/muellergroup/kplib.git

In order to install this package use pip:

$ pip install "kplib"

Command-line interface kpgen

You can use the command line interface to generate Generalized Monkhorst-Pack k-points grid by calling kpGen in terminal.

kpGen reads the input file by using pymatgen, so it in principle support all kinds of structure format supported by pymatgen. By default, it reads POSCAR as input file. Currently, the output file which contain the k-points is writen as VASP's KPOINTS file.

Users can check and see the details of the arguments and options by kpGen --help.

python API reference and examples

For users who wants to use kplib in their python packages, the recommended method is to use the get_kpoints function. It returns a dict, the keys of which are:

  • min_periodic_distance: The minimum distance between lattice points on the real-space superlattice.
  • num_distinct_kpts: The number of distinct k-points reduced by lattice symmetry.
  • num_total_kpts: The number of total k-points.
  • coords: The coordinates of k-points, represented in refraction coordinate.
  • weights: The weights of corresponding k-points.
import numpy as np
from kplib import get_kpoints

struc = ...

kpts = get_kpoints(struc, minDistance=24.9, include_gamma=include_gamma)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

kpLib-1.0.4.tar.gz (34.4 kB view details)

Uploaded Source

File details

Details for the file kpLib-1.0.4.tar.gz.

File metadata

  • Download URL: kpLib-1.0.4.tar.gz
  • Upload date:
  • Size: 34.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.10.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.4

File hashes

Hashes for kpLib-1.0.4.tar.gz
Algorithm Hash digest
SHA256 30f9c13ca1238b192809fb86573e229ce6b5738efab8727bbf773927be9d0075
MD5 75a28abae25888589a2dcb3f6fe793f5
BLAKE2b-256 476cc27425ec0f6625e62300c4e869dcb04cd3d3f16d7ecd4ec575ddb6f8a2e7

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page