custodian.vasp.jobs module

This module implements basic kinds of jobs for VASP runs.

class custodian.vasp.jobs.GenerateVaspInputJob(input_set, contcar_only=True, **kwargs)

Bases: Job

Generates a VASP input based on an existing directory. This is typically used to modify the VASP input files before the next VaspJob.

  • Parameters
    • input_set (str) – Full path to the input set. E.g., “pymatgen.io.vasp.sets.MPNonSCFSet”.
    • contcar_only (bool) – If True (default), only CONTCAR structures are used as input to the input set.

postprocess()

Dummy postprocess.

run()

Run the calculation.

setup()

Dummy setup

class custodian.vasp.jobs.VaspJob(vasp_cmd, output_file=’vasp.out’, stderr_file=’std_err.txt’, suffix=’’, final=True, backup=True, auto_npar=False, auto_gamma=True, settings_override=None, gamma_vasp_cmd=None, copy_magmom=False, auto_continue=False)

Bases: Job

A basic vasp job. Just runs whatever is in the directory. But conceivably can be a complex processing of inputs etc. with initialization.

This constructor is necessarily complex due to the need for flexibility. For standard kinds of runs, it’s often better to use one of the static constructors. The defaults are usually fine too.

  • Parameters
    • vasp_cmd (str) – Command to run vasp as a list of args. For example, if you are using mpirun, it can be something like [“mpirun”, “pvasp.5.2.11”]
    • output_file (str) – Name of file to direct standard out to. Defaults to “vasp.out”.
    • stderr_file (str) – Name of file to direct standard error to. Defaults to “std_err.txt”.
    • suffix (str) – A suffix to be appended to the final output. E.g., to rename all VASP output from say vasp.out to vasp.out.relax1, provide “.relax1” as the suffix.
    • final (bool) – Indicating whether this is the final vasp job in a series. Defaults to True.
    • backup (bool) – Whether to backup the initial input files. If True, the INCAR, KPOINTS, POSCAR and POTCAR will be copied with a “.orig” appended. Defaults to True.
    • auto_npar (bool) – Whether to automatically tune NPAR to be sqrt( number of cores) as recommended by VASP for DFT calculations. Generally, this results in significant speedups. Defaults to False. Set to False for HF, GW and RPA calculations.
    • auto_gamma (bool) – Whether to automatically check if run is a Gamma 1x1x1 run, and whether a Gamma optimized version of VASP exists with “.gamma” appended to the name of the VASP executable (typical setup in many systems). If so, run the gamma optimized version of VASP instead of regular VASP. You can also specify the gamma vasp command using the gamma_vasp_cmd argument if the command is named differently.
    • settings_override ([dict]) – An ansible style list of dict to override changes. For example, to set ISTART=1 for subsequent runs and to copy the CONTCAR to the POSCAR, you will provide:
    [{"dict": "INCAR", "action": {"_set": {"ISTART": 1}}},
 {"file": "CONTCAR",
  "action": {"_file_copy": {"dest": "POSCAR"}}}]
    • gamma_vasp_cmd (str) – Command for gamma vasp version when auto_gamma is True. Should follow the list style of subprocess. Defaults to None, which means “.gamma” is added to the last argument of the standard vasp_cmd.
    • copy_magmom (bool) – Whether to copy the final magmom from the OUTCAR to the next INCAR. Useful for multi-relaxation runs where the CHGCAR and WAVECAR are sometimes deleted (due to changes in fft grid, etc.). Only applies to non-final runs.
    • auto_continue (bool) – Whether to automatically continue a run if a STOPCAR is present. This is very useful if using the wall-time handler which will write a read-only STOPCAR to prevent VASP from deleting it once it finishes

classmethod constrained_opt_run(vasp_cmd, lattice_direction, initial_strain, atom_relax=True, max_steps=20, algo=’bfgs’, **vasp_job_kwargs)

Returns a generator of jobs for a constrained optimization run. Typical use case is when you want to approximate a biaxial strain situation, e.g., you apply a defined strain to a and b directions of the lattice, but allows the c-direction to relax.

Some guidelines on the use of this method: i. It is recommended you do not use the Auto kpoint generation. The

grid generated via Auto may fluctuate with changes in lattice param, resulting in numerical noise.

  1. Make sure your EDIFF/EDIFFG is properly set in your INCAR. The optimization relies on these values to determine convergence.
  • Parameters
    • vasp_cmd (str) – Command to run vasp as a list of args. For example, if you are using mpirun, it can be something like [“mpirun”, “pvasp.5.2.11”]
    • lattice_direction (str) – Which direction to relax. Valid values are “a”, “b” or “c”.
    • initial_strain (float) – An initial strain to be applied to the lattice_direction. This can usually be estimated as the negative of the strain applied in the other two directions. E.g., if you apply a tensile strain of 0.05 to the a and b directions, you can use -0.05 as a reasonable first guess for initial strain.
    • atom_relax (bool) – Whether to relax atomic positions.
    • max_steps (int) – The maximum number of runs. Defaults to 20 ( highly unlikely that this limit is ever reached).
    • algo (str) – Algorithm to use to find minimum. Default is “bfgs”, which is fast, but can be sensitive to numerical noise in energy calculations. The alternative is “bisection”, which is more robust but can be a bit slow. The code does fall back on the bisection when bfgs gives a nonsensical result, e.g., negative lattice params.
    • **vasp_job_kwargs – Passthrough kwargs to VaspJob. See custodian.vasp.jobs.VaspJob.

  • Returns

    Generator of jobs. At the end of the run, an “EOS.txt” is written which provides a quick look at the E vs lattice parameter.

classmethod double_relaxation_run(vasp_cmd, auto_npar=True, ediffg=-0.05, half_kpts_first_relax=False, auto_continue=False)

Returns a list of two jobs corresponding to an AFLOW style double relaxation run.

  • Parameters
    • vasp_cmd (str) – Command to run vasp as a list of args. For example, if you are using mpirun, it can be something like [“mpirun”, “pvasp.5.2.11”]
    • auto_npar (bool) – Whether to automatically tune NPAR to be sqrt( number of cores) as recommended by VASP for DFT calculations. Generally, this results in significant speedups. Defaults to True. Set to False for HF, GW and RPA calculations.
    • ediffg (float) – Force convergence criteria for subsequent runs ( ignored for the initial run.)
    • half_kpts_first_relax (bool) – Whether to halve the kpoint grid for the first relaxation. Speeds up difficult convergence considerably. Defaults to False.
    • auto_continue (bool) – Whether to automatically continue a run if a STOPCAR is present. This is very useful if using the wall-time handler which will write a read-only STOPCAR to prevent VASP from deleting it once it finishes. Defaults to False.

  • Returns

    List of two jobs corresponding to an AFLOW style run.

classmethod full_opt_run(vasp_cmd, vol_change_tol=0.02, max_steps=10, ediffg=-0.05, half_kpts_first_relax=False, **vasp_job_kwargs)

Returns a generator of jobs for a full optimization run. Basically, this runs an infinite series of geometry optimization jobs until the

  • Parameters
    • vasp_cmd (str) – Command to run vasp as a list of args. For example, if you are using mpirun, it can be something like [“mpirun”, “pvasp.5.2.11”]
    • vol_change_tol (float) – The tolerance at which to stop a run. Defaults to 0.05, i.e., 5%.
    • max_steps (int) – The maximum number of runs. Defaults to 10 ( highly unlikely that this limit is ever reached).
    • ediffg (float) – Force convergence criteria for subsequent runs ( ignored for the initial run.)
    • half_kpts_first_relax (bool) – Whether to halve the kpoint grid for the first relaxation. Speeds up difficult convergence considerably. Defaults to False.
    • **vasp_job_kwargs – Passthrough kwargs to VaspJob. See custodian.vasp.jobs.VaspJob.

  • Returns

    Generator of jobs.

classmethod metagga_opt_run(vasp_cmd, auto_npar=True, ediffg=-0.05, half_kpts_first_relax=False, auto_continue=False)

Returns a list of thres jobs to perform an optimization for any metaGGA functional. There is an initial calculation of the GGA wavefunction which is fed into the initial metaGGA optimization to precondition the electronic structure optimizer. The metaGGA optimization is performed using the double relaxation scheme

postprocess()

Postprocessing includes renaming and gzipping where necessary. Also copies the magmom to the incar if necessary

run()

Perform the actual VASP run.

  • Returns

    (subprocess.Popen) Used for monitoring.

setup()

Performs initial setup for VaspJob, including overriding any settings and backing up.

terminate()

Ensure all vasp jobs are killed.

class custodian.vasp.jobs.VaspNEBJob(vasp_cmd, output_file=’neb_vasp.out’, stderr_file=’neb_std_err.txt’, suffix=’’, final=True, backup=True, auto_npar=True, half_kpts=False, auto_gamma=True, auto_continue=False, gamma_vasp_cmd=None, settings_override=None)

Bases: VaspJob

A NEB vasp job, especially for CI-NEB running at PBS clusters. The class is added for the purpose of handling a different folder arrangement in NEB calculation.

This constructor is a simplified version of VaspJob, which satisfies the need for flexibility. For standard kinds of runs, it’s often better to use one of the static constructors. The defaults are usually fine too.

  • Parameters
    • vasp_cmd (str) – Command to run vasp as a list of args. For example, if you are using mpirun, it can be something like [“mpirun”, “pvasp.5.2.11”]
    • output_file (str) – Name of file to direct standard out to. Defaults to “vasp.out”.
    • stderr_file (str) – Name of file to direct standard error to. Defaults to “std_err.txt”.
    • suffix (str) – A suffix to be appended to the final output. E.g., to rename all VASP output from say vasp.out to vasp.out.relax1, provide “.relax1” as the suffix.
    • final (bool) – Indicating whether this is the final vasp job in a series. Defaults to True.
    • backup (bool) – Whether to backup the initial input files. If True, the INCAR, KPOINTS, POSCAR and POTCAR will be copied with a “.orig” appended. Defaults to True.
    • auto_npar (bool) – Whether to automatically tune NPAR to be sqrt( number of cores) as recommended by VASP for DFT calculations. Generally, this results in significant speedups. Defaults to True. Set to False for HF, GW and RPA calculations.
    • half_kpts (bool) – Whether to halve the kpoint grid for NEB. Speeds up convergence considerably. Defaults to False.
    • auto_gamma (bool) – Whether to automatically check if run is a Gamma 1x1x1 run, and whether a Gamma optimized version of VASP exists with “.gamma” appended to the name of the VASP executable (typical setup in many systems). If so, run the gamma optimized version of VASP instead of regular VASP. You can also specify the gamma vasp command using the gamma_vasp_cmd argument if the command is named differently.
    • auto_continue (bool) – Whether to automatically continue a run if a STOPCAR is present. This is very useful if using the wall-time handler which will write a read-only STOPCAR to prevent VASP from deleting it once it finishes.
    • gamma_vasp_cmd (str) – Command for gamma vasp version when auto_gamma is True. Should follow the list style of subprocess. Defaults to None, which means “.gamma” is added to the last argument of the standard vasp_cmd.
    • settings_override ([dict]) – An ansible style list of dict to override changes. For example, to set ISTART=1 for subsequent runs and to copy the CONTCAR to the POSCAR, you will provide:
    [{"dict": "INCAR", "action": {"_set": {"ISTART": 1}}},
 {"file": "CONTCAR",
  "action": {"_file_copy": {"dest": "POSCAR"}}}]

postprocess()

Postprocessing includes renaming and gzipping where necessary.

run()

Perform the actual VASP run.

  • Returns

    (subprocess.Popen) Used for monitoring.

setup()

Performs initial setup for VaspNEBJob, including overriding any settings and backing up.

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