Parallel C/Python package for numerical analysis of PAW DFT wavefunctions
WARNING: PAWpySeed is still in early development. Documentation is incomplete, and some features are not yet thoroughly tested. High-priority issues for the next couple months include: 1) documentation page containing the mathematical formalism, 2) examples and tutorials, 3) standardized unit tests. The evaluation of overlap operators is tested, but a standard test suite is not yet published, and some features still require more thorough testing.
PAWpySeed is a parallelized Python and C tool for reading and analyzing the optimized band structure and wave functions of VASP DFT calculations. The code is written for the PAW formalism developed by P.E. Blochl and implemented in VASP.
Note: Before installing with pip or the setup script, please read about the dependencies and set up your environment correctly!
You can install PAWpySeed with
pip install pawpyseed
This has been tested on Scientific Linux 7 and Linux Mint 18,
but should work for systems that have the appropriate
packages and environment variables defined as described below.
Note that the setup script compiles and installs some C code
as a shared object to be used by
ctypes and places it
in the package directory under
Installation can also be performed
by cloning this repository and running the
in the root directory of the repository.
python setup.py build python setup.py install
build command, in addition to the standard distutils setup,
compiles the C code in the
pawpyseed.core module into a shared
object in the core module,
pawpy.so. See below for
All dependencies indicate the minimum version tested. PAWpySeed might work fine with earlier versions, but use of older versions will not be officially supported.
python>=3.5 numpy>=1.14 scipy>=1.0 pymatgen>=2018.2.13
icc >= 16.0.4 OR gcc >= 4.8.5 Intel Math Kernel Library >= 11.3.4
Intel MKL is available for free installation on a variety of platforms. Most computing clusters will have Intel MKL, and you can install it on your desktop (or any system to which you have root access) by following the relevant instructions at the following URL: https://software.intel.com/en-us/articles/free-ipsxe-tools-and-libraries. After Intel MKL is installed, add the following line to your .bashrc to link MKL (NOTE: this might not be the exact directory that MKL is in, you need to check that first):
export MKLROOT=/opt/intel/compilers_and_libraries_2018/linux/mkl export LD_LIBRARY_PATH=$MKLROOT/lib/intel64_lin:$LD_LIBRARY_PATH export C_INCLUDE_PATH=$MKLROOT/include:$C_INCLUDE_PATH
The last line is optional but might be useful for future PAWpySeed builds and other programs which make use of MKL. The setup.py file will now take care of C compilation.
Optional Python dependencies (not used now but might be in the future):
Theory and Input
The projector augmented wave (PAW) method is a technique used in plane wave density functional theory to simplify the description of the wavefunctions near the nuclei of a system. The strong Coulombic forces near an atomic nucleus creates quickly oscillating wavefunctions that are not well described by plane waves without prohibitively large basis sets, so a "pseudopotential" is introduced near the atomic nuclei which results in smooth "pseudowavefunctions" well described by plane waves. The full wavefunctions can be recovered by a linear transform of the pseudowavefunctions. The PAW method requires three sets of functions: projector functions, onto which pseudowavefunctions are projected to probe their character; full partial waves, which describe atomic valence states derived from the true potential; and pseudo partial waves, which are derived from the full partial waves and pseudopotential.
The projector functions and partial waves are unique to each element and stored in the POTCAR file used in a VASP calculation. The pseudowavefunction is the part of the wavefunction optimized during a DFT calculation and is stored in the WAVECAR output file in VASP. PAWpySeed parses both files to retrieve all parts of the full Kohn Sham wavefunctions.
The main purpose of PAWpySeed is to evaluate overlap operators between Kohn-Sham wavefunctions from different structures, which is not done by standard plane-wave DFT codes. Such functionality can be useful for analyzing the composition of defect levels in solids, which is main application for which the code is currently focused.
- Python Interface
- Computationally intensive tasks in C
- Parallelized with openmp
- Read pseudowavefunctions
- Read projectors and partial waves from VASP POTCAR
- Evaluate overlap operators between bands, including when bands belong to different structures with the same lattice
- Project point defect levels onto bulk valence and conduction bands
- Convenient pycdt interface
- Localize orbitals with SCDM-k
- Atomic Hartree Fock and GGA DFT database for use in charge corrections and other applications
- Read noncollinear pseudowavefunctions
- Convert PAW wavefunctions to NC wavefunctions (for use in GW calculations)
- Perturbative charge corrections
- Read pseudopotential, atomic charge density, and other POTCAR data
- Perform general operator expectation values on full wavefunctions
The code in PAWpySeed is based on a several algorithms and codes, which are enumerated here.
The PAW method was developed by P. E. Blochl in 1994. His paper deriving the method
was helpful to me in deriving the extensions to the formalism needed to develop
- P. E. Blochl. Projector augmented-wave method. Phys. Rev. B, 50:17953, 1994.
PAWpySeed is primarily built to read and process the output of VASP calculations.
PAWpySeed reads PAW wavefunctions and calculate overlap operators using algorithms
derived from VASP and other plane-wave codes, so the following citations are necessary.
The last citation is specifically for the PAW method and potentials. See the VASP website
at http://community.hartree.stfc.ac.uk/wiki/site/admin/vasp.html for information
on citing specific functionals.
- G. Kresse and J. Hafner. Ab initio molecular dynamics for liquid metals. Phys. Rev. B, 47:558, 1993.
- G. Kresse and J. Hafner. Ab initio molecular-dynamics simulation of the liquid-metal-amorphous-semiconductor transition in germanium. Phys. Rev. B, 49:14251, 1994.
- G. Kresse and J. Furthmüller. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mat. Sci., 6:15, 1996.
- G. Kresse and J. Furthmüller. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B, 54:11169, 1996.
- G. Kresse and D. Joubert. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B, 59:1758, 1999.
NUMSBT is a code written by J. D. Talman, which implements an algorithm that
calculates the spherical Bessel transform (SBT) in O(NlogN) time.
employs the high-k transform algorithm implemented in NUMSBT
to calculate the overlap operators between
overlapping augmentation spheres that have different positions or elements.
It is also used to filter out high-frequency components from AE partial
waves, which allows projections from pseudowavefunctions to AE partial
waves to be performed in real space, which is a vital component of the
NUMSBT is distributed under the Standard CPC License, and the algorithm is
developed in the following paper:
- Talman, J. Computer Physics Communications 2009, 180, 332 –338.
- Doxygen: Doxygen is a documentation generator from which I built the docs for PAWpySeed. It is an excellent tool that allows for clean, up-to-date documentaton that is easy to make and navigate. Check it out at http://www.stack.nl/~dimitri/doxygen/
Questions and Comments
Find a bug? Areas of code unclearly documented? Other questions? Feel free to contact Kyle Bystrom at firstname.lastname@example.org with the subject "pawpyseed: <Topic>".