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dftio is to assist machine learning communities to transcript DFT output into a format that is easy to read or used by machine learning models.

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dftio

dftio is to assist machine learning communities in transcribing and manipulating DFT output into a format that is easy to read or used by machine learning models.

dftio uses multiprocessing to paralleling the processing, and provide a standard dataset class that reads the processed dataset directly.

Installation

The user can install dftio once located in the root directory, and run:

pip install .

The dependent packages will be installed accordingly. However, the user can always manage the dependency themselves, here are the packages that dftio requires:

Supports

Current:

Package Structure Eigenvalues Hamiltonian Density matrix Overlap matrix
ABACUS
RESCU
SIESTA
Gaussian

Ongoing:

  • Charge density
  • Atomic Orbitals
  • Wave Function
  • Wave Function Coefficients

How to use

To parse the DFT output files into readable data format, user can follows:

dftio parse [-h] [-ll {DEBUG,3,INFO,2,WARNING,1,ERROR,0}] [-lp LOG_PATH] [-m MODE] [-r ROOT] [-p PREFIX] [-o OUTROOT] [-f FORMAT] [-ham] [-ovp] [-dm] [-eig]

optional arguments:
  -h, --help            show this help message and exit
  -ll {DEBUG,3,INFO,2,WARNING,1,ERROR,0}, --log-level {DEBUG,3,INFO,2,WARNING,1,ERROR,0}
                        set verbosity level by string or number, 0=ERROR, 1=WARNING, 2=INFO and 3=DEBUG (default: INFO)
  -lp LOG_PATH, --log-path LOG_PATH
                        set log file to log messages to disk, if not specified, the logs will only be output to console (default: None)
  -m MODE, --mode MODE  The name of the DFT software. (default: abacus)
  -r ROOT, --root ROOT  The root directory of the DFT files. (default: ./)
  -p PREFIX, --prefix PREFIX
                        The prefix of the DFT files under root. (default: frame)
  -o OUTROOT, --outroot OUTROOT
                        The output root directory. (default: ./)
  -f FORMAT, --format FORMAT
                        The output root directory. (default: dat)
  -ham, --hamiltonian   Whether to parse the Hamiltonian matrix. (default: False)
  -ovp, --overlap       Whether to parse the Overlap matrix (default: False)
  -dm, --density_matrix
                        Whether to parse the Density matrix (default: False)
  -eig, --eigenvalue    Whether to parse the kpoints and eigenvalues (default: False)

Call for Contributors

dftio is an open-source tool that calls for enthusiastic developers to contribute their talent. One can contribute through raising function requirement issues, or contact the current developer directly.

Current Contributors (in alphabetical order)

Qiangqiang Gu, Jijie Zou, Mingkang Liu, Zixi Gan, Zhanghao Zhouyin

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dftio is to assist machine learning communities to transcript DFT output into a format that is easy to read or used by machine learning models.

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