Effective masses with finite differenceΒΆ

Flow to compute effective masses with finite difference method. Derivatives are computed along lines in k-space.

import sys
import os
import abipy.data as abidata
import abipy.abilab as abilab
import abipy.flowtk as flowtk


def make_scf_input(nspinor=1, usepaw=0):
    """Returns GS input file for Silicon"""
    if nspinor == 1:
        pseudos = abidata.pseudos("14si.pspnc") if usepaw == 0 else abidata.pseudos("Si.GGA_PBE-JTH-paw.xml")
    else:
        pseudos = abidata.pseudos("Si_r.psp8") if usepaw == 0 else abidata.pseudos("Si.GGA_PBE-JTH-paw.xml")

    structure = dict(
         ntypat=1,
         natom=2,
         typat=[1, 1],
         znucl=14,
         #acell=3 * [10.26310667319252], # https://docs.abinit.org/tests/v7/Input/t82.in
         acell=3 * [10.2073557], # 5.4015 Ang
         rprim=[[0.0,  0.5,  0.5],
                [0.5,  0.0,  0.5],
                [0.5,  0.5,  0.0]],
         xred=[ [0.0 , 0.0 , 0.0],
                [0.25, 0.25, 0.25]],
    )

    # Build input
    scf_input = abilab.AbinitInput(structure=structure, pseudos=pseudos)

    # Set variables
    scf_input.set_vars(
        ecut=12,
        nband=8 if nspinor == 1 else 16,
        nspinor=nspinor,
        tolvrs=1e-8,
    )

    if scf_input.ispaw:
        scf_input.set_vars(pawecutdg=2 * scf_input["ecut"])

    scf_input.set_kmesh(ngkpt=[8, 8, 8], shiftk=[0, 0, 0])

    return scf_input


def build_flow(options):
    # Set working directory (default is the name of the script with '.py' removed and "run_" replaced by "flow_")
    if not options.workdir:
        options.workdir = os.path.basename(sys.argv[0]).replace(".py", "").replace("run_", "flow_")

    # Get the SCF input (here NC with SOC)
    scf_input = make_scf_input(nspinor=2, usepaw=0)

    # Build the flow with different steps.
    from abipy.flowtk.effmass_works import EffMassLineWork
    flow = flowtk.Flow(workdir=options.workdir, manager=options.manager)

    # Multiple calculations with different step for finite difference.
    for i, step in enumerate((0.01, 0.005)):
        if i == 0: den_node = None
        work = EffMassLineWork.from_scf_input(scf_input, k0_list=(0, 0, 0),
                                              step=step, npts=10,
                                              red_dirs=[[1, 0, 0], [1, 1, 0]],
                                              cart_dirs=[[1, 0, 0], [1, 1, 1], [1, 1, 0]],
                                              den_node=den_node)
        # Will start from the DEN file produced in the first iteration.
        if i == 0: den_node = work[0]
        flow.register_work(work)

    return flow


# This block generates the thumbnails in the Abipy gallery.
# You can safely REMOVE this part if you are using this script for production runs.
if os.getenv("READTHEDOCS", False):
    __name__ = None
    import tempfile
    options = flowtk.build_flow_main_parser().parse_args(["-w", tempfile.mkdtemp()])
    build_flow(options).graphviz_imshow()


@flowtk.flow_main
def main(options):
    """
    This is our main function that will be invoked by the script.
    flow_main is a decorator implementing the command line interface.
    Command line args are stored in `options`.
    """
    return build_flow(options)


if __name__ == "__main__":
    sys.exit(main())
../_images/sphx_glr_run_effmass_finitediff_001.png

Out:

/Users/gmatteo/git_repos/pymatgen/pymatgen/util/plotting.py:550: UserWarning: Matplotlib is currently using agg, which is a non-GUI backend, so cannot show the figure.
  plt.show()

Run the script with:

run_effmass_finitediff -s

Total running time of the script: ( 0 minutes 0.514 seconds)

Gallery generated by Sphinx-Gallery