AutoVaspPy

AutoVaspPy is a high-level python module that allows for performing complex vasp calculations and analysis using python. AutoVaspPy makes extensive use of the ase and pymatgen modules to run and analyse vasp calculations.

Table of Contents

1. About The Project
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
• VaspCalculations
• Postprocessing
4. Contributing
5. License
6. Contact
7. Acknowledgements

Usage

Structures are processed using ase format and can be loaded into python using ase's read() function

from ase.io import read
structure = read("/path/to/file/")

A full list of file formats is listed in the ASE documentation.

An instance of the VaspCalculations can then be created using the loaded structure

from AutoVaspPy import VaspCalculations
vasp_calculator = VaspCalculations(structure)

The VaspCalculations class is initialised with general calculation parameters that should be adjusted to the users needs. It is recommended that all parameters are explicitly defined to ensure the user is fully aware of all the elements that may affect their results. The vasp_calculator instance has many functions that can be used for running different calculations.

The parameter_testing function allows for an automatic workflow to converge various calculation parameters of interest (k-point spacing, cut off energy etc.). Here is an example of k-point spacing convergence on a fictious magnetic system

test_values = [0.1, 0.12, 0.15, 0.2, 0.25, 0.3, 0.5]
k_spacing_convergence = vasp_calculator.parameter_testing(test="k-spacing",
                                                          values=test_values,
                                                          magnetic_moments=[5, 5, 0, 0],
                                                          hubbard_parameters=None,
                                                          plot=True)

Where plot=True the matplotlib package is used to save a figure plotting the energy of the system against the parameter tested. After the calculation is finished, a numpy array is returned which can be used for analysis and more adavanced plotting.

Pipelining Calculations

The calculation_manager function allows for the pipelining of different VASP calculations to have a fully autonomous workflow. An example is given here where the structure is relaxed, the DOS, band structure and dielectric tensor are all calculated in sequence with different settings.

calculation_settings = {

    "relax-mag":
        {"algo": "normal",
         "kspacing": 0.15,
         "write_safe_file": True},

    "scf-mag":
        {"write_safe_file": True,
         "nedos": 5000},

    "bands-mag":
        {"algo": 2,
         "read_safe_file": True,
         },

    "eps-mag":
        {"write_safe_file": True,
         "read_safe_file": True}
}

vasp_calculator.calculation_manager(calculation_sequence=calculation_settings.keys(),
                                    additional_settings=calculation_settings,
                                    magnetic_moments=[5, 5, 0, 0],
                                    hubbard_parameters=None,
                                    nkpts=300,
                                    test_run=False)
}

The calculation_sequence parameter is used to list the pipeline of calculations. The additional_settings keyword allows for different VASP parameters to be used at each stage of the calculation. The number of k-points for a band structure calculation currently has to be set with the nkpts keyword. test_run allows for testing of the pipeline with minimal VASP settings (useful for testing a pipeline locally before running a full-scale calculation with HPC resources).