Bands Structure
For the source code, see bands.
Visualizing the WorkGraph Builder
[1]:
from workgraph_collections.ase.espresso.bands import bands_workgraph
from aiida import load_profile
load_profile()
task = bands_workgraph.task()
task.to_html()
[1]:
Visualizing the WorkGraph
[2]:
from workgraph_collections.ase.espresso.bands import bands_workgraph
wg = bands_workgraph(run_relax=True, run_scf=True)
wg.to_html()
[2]:
Example: Silicon
Prepare the inputs and submit the workflow
[3]:
from ase.build import bulk
from aiida import load_profile
from copy import deepcopy
from workgraph_collections.ase.espresso.bands import bands_workgraph
load_profile()
atoms = bulk('Si')
metadata = {
"options": {
'prepend_text' : """eval "$(conda shell.posix hook)"
conda activate aiida
export OMP_NUM_THREADS=1
""",
}
}
pseudopotentials = {"Si": "Si.pbe-nl-rrkjus_psl.1.0.0.UPF"}
# pseudo_dir = "/home/xing/data/ase/espresso_pseudo"
pseudo_dir = "/home/wang_x3/datas/pseudos/psl"
scf_input_data = {
"control": {"calculation": "scf",
},
"system": {"ecutwfc": 30, "ecutrho": 240,
"occupations": "smearing",
"degauss": 0.01,
"smearing": "cold"
},
}
bands_input_data = deepcopy(scf_input_data)
bands_input_data["control"].update({"calculation": "bands"})
inputs = {
"scf": {
"input_data": scf_input_data,
"kpts": (4, 4, 4),
"computer": "localhost",
"metadata": metadata
},
"find_kponits_path": {
"computer": "localhost",
"metadata": metadata
},
"bands": {
"input_data": bands_input_data,
"computer": "localhost",
"metadata": metadata
},
}
#------------------------- Set the inputs -------------------------
wg = bands_workgraph(atoms=atoms,
pw_command="mpirun -np 1 pw.x",
pseudopotentials=pseudopotentials,
pseudo_dir=pseudo_dir,
inputs=inputs,
density=10,
run_relax=True,
run_scf=True,
)
#------------------------- Submit the calculation -------------------
wg.submit(wait=True, timeout=200)
WorkGraph process created, PK: 21550
[3]:
<WorkChainNode: uuid: 3a643249-7320-4624-9b2d-4f44f85c23dc (pk: 21550) (aiida_workgraph.engine.workgraph.WorkGraphEngine)>
Plot the band structure
[4]:
from ase.spectrum.band_structure import BandStructure
import numpy as np
data = wg.tasks["bands"].outputs["results"].value.value
eigenvalues = np.array([np.array(data['eigenvalues'][0])])
kpts = wg.tasks["find_kponits_path"].outputs["result"].value.value
bs = BandStructure(path=kpts, energies=eigenvalues)
bs.plot()
[4]:
<AxesSubplot:ylabel='energies [eV]'>