Eigenvals Calculation

This example runs the tbmodels eigenvals command, which calculated the eigenvalues of a tight-binding model for a given set of k-points.

#!/usr/bin/env runaiida
# -*- coding: utf-8 -*-

# © 2017-2019, ETH Zurich, Institut für Theoretische Physik
# Author: Dominik Gresch <greschd@gmx.ch>
Runs a 'tbmodels eigenvals' calculation.

from __future__ import division, print_function, unicode_literals

import os

from aiida.orm import Code
from aiida.orm import SinglefileData
from aiida.orm.querybuilder import QueryBuilder
from aiida.engine import run_get_pk
from aiida.plugins import DataFactory

from aiida_tbmodels.calculations.eigenvals import EigenvalsCalculation

def get_singlefile_instance(description, path):
    Retrieve an instance of SinglefileData with the given description, loading it from ``path`` if it does not exist.
    query_builder = QueryBuilder()
        SinglefileData, filters={'description': {
            '==': description
    res = query_builder.all()
    if len(res) == 0:
        # create archive
        res = SinglefileData(file=os.path.abspath(path))
        res.description = description
    elif len(res) > 1:
        raise ValueError(
            'Query returned more than one matching SinglefileData instance.'
        res = res[0][0]
    return res

def run_eigenvals():
    Creates and runs the eigenvals calculation.
    builder = EigenvalsCalculation.get_builder()
    builder.code = Code.get_from_string('tbmodels')

    builder.tb_model = get_singlefile_instance(
        description=u'InSb TB model', path='./reference_input/model.hdf5'

    # single-core on local machine
    builder.metadata.options = dict(
        resources=dict(num_machines=1, tot_num_mpiprocs=1), withmpi=False

    builder.kpoints = DataFactory('array.kpoints')()
    builder.kpoints.set_kpoints_mesh([4, 4, 4], offset=[0, 0, 0])

    result, pid = run_get_pk(builder)
    print('\nRan calculation with PID', pid)
    print('Result:', result)

if __name__ == '__main__':