G0W0 convergence studyΒΆ

G0W0 convergence study wrt ecuteps and the number of bands in W.

../_images/sphx_glr_run_gwconv_ecuteps_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()

import sys
import os
import numpy as np

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


def make_inputs(paral_kgb=1):
    """
    Returns a tuple of 4 input files for SCF, NSCF, SCR, SIGMA calculations.
    These files are then used as templates for the convergence study
    wrt ecuteps and the number of bands in W.
    """
    multi = abilab.MultiDataset(abidata.structure_from_ucell("SiC"),
                                pseudos=abidata.pseudos("14si.pspnc", "6c.pspnc"), ndtset=4)

    ecut = 12
    global_vars = dict(
        ecut=ecut,
        istwfk="*1",
        paral_kgb=paral_kgb,
        gwpara=2,
        iomode=1,
    )

    ecuteps = 4
    ngkpt = [4, 4, 4]
    shiftk = [0, 0, 0]

    multi.set_vars(global_vars)
    multi.set_kmesh(ngkpt=ngkpt, shiftk=shiftk)

    # SCF
    multi[0].set_vars(
        nband=10,
        tolvrs=1.e-8,
    )

    # NSCF
    multi[1].set_vars(
        nband=25,
        tolwfr=1.e-8,
        iscf=-2
    )

    # SCR
    multi[2].set_vars(
        optdriver=3,
        ecutwfn=ecut,
        nband=20,
        symchi=1,
        inclvkb=0,
        ecuteps=ecuteps,
    )

    # SIGMA
    multi[3].set_vars(
        optdriver=4,
        nband=20,
        ecutwfn=ecut,
        ecutsigx=ecut,
        #ecutsigx=(4*ecut), ! This is problematic
        symsigma=1,
        ecuteps=ecuteps,
        )

    multi[3].set_kptgw(kptgw=[[0,0,0], [0.5, 0, 0]], bdgw=[1, 8])

    return multi.split_datasets()


def build_flow(options):
    # 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 our templates
    scf_inp, nscf_inp, scr_inp, sig_inp = make_inputs()

    ecuteps_list = np.arange(2, 8, 2)
    max_ecuteps = max(ecuteps_list)

    flow = flowtk.Flow(workdir=options.workdir, manager=options.manager)

    # Band structure work to produce the WFK file
    bands = flowtk.BandStructureWork(scf_inp, nscf_inp)
    flow.register_work(bands)

    # Build a work made of two SCR runs with different value of nband
    # Use max_ecuteps for the dielectric matrix (sigma tasks will
    # read a submatrix when we test the convergence wrt to ecuteps.
    scr_work = flowtk.Work()

    for inp in scr_inp.generate(nband=[10, 15]):
        inp.set_vars(ecuteps=max_ecuteps)
        scr_work.register_scr_task(inp, deps={bands.nscf_task: "WFK"})

    flow.register_work(scr_work)

    # Do a convergence study wrt ecuteps, each work is connected to a
    # different SCR file computed with a different value of nband.

    # Build a list of sigma inputs with different ecuteps
    sigma_inputs = list(sig_inp.generate(ecuteps=ecuteps_list))

    for scr_task in scr_work:
        sigma_conv = flowtk.SigmaConvWork(wfk_node=bands.nscf_task, scr_node=scr_task, sigma_inputs=sigma_inputs)
        flow.register_work(sigma_conv)

    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())

Total running time of the script: ( 0 minutes 1.427 seconds)

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