from nexus import generate_physical_system
from nexus import generate_pwscf
from nexus import generate_pw2qmcpack
from nexus import generate_qmcpack, vmc
from structure import *
settings(pseudo_dir='../../pseudopotentials',
status_only=0,
generate_only=0,
sleep=3,
machine='ws16')
#Input structure
dia = generate_physical_system(units='A',
axes=[[1.785, 1.785, 0.], [0., 1.785, 1.785],
[1.785, 0., 1.785]],
elem=['C', 'C'],
pos=[[0., 0., 0.], [0.8925, 0.8925, 0.8925]],
C=4)
#Standardized Primitive cell -- run rest of the calculations on this cell
dia2_structure = get_primitive_cell(structure=dia.structure)['structure']
dia2_kpath = get_kpath(structure=dia2_structure)
#get_band_tiling and get_kpath require "SeeK-path" python3 libraries
dia2 = generate_physical_system(
structure=dia2_structure,
kgrid=(4, 4, 4),
kshift=(0, 0, 0),
C=4,
)
pseudo_dir = '../../pseudopotentials',# directory with all pseudopotentials
sleep = 3, # check on runs every 'sleep' seconds
generate_only = 0, # only make input files
status_only = 0, # only show status of runs
machine = 'ws16', # local machine is 16 core workstation
)
# generate the graphene physical system
graphene = generate_physical_system(
lattice = 'hexagonal', # hexagonal cell shape
cell = 'primitive', # primitive cell
centering = 'P', # primitive basis centering
constants = (2.462,10.0), # a,c constants
units = 'A', # in Angstrom
atoms = ('C','C'), # C primitive atoms
basis = [[ 0 , 0 , 0], # basis vectors
[2./3,1./3, 0]],
tiling = (2,2,1), # tiling of primitive cell
kgrid = (1,1,1), # Monkhorst-Pack grid
kshift = (.5,.5,.5), # and shift
C = 4 # C has 4 valence electrons
)
# scf run produces charge density
scf = generate_pwscf(
# nexus inputs
identifier = 'scf', # identifier/file prefix
path = 'graphene/scf', # directory for scf run
job = job(cores=16), # run on 16 cores
pseudos = ['C.BFD.upf'], # pwscf PP file
system = graphene, # run graphene
from nexus import generate_pyscf
from nexus import generate_pyscf_to_afqmc
from nexus import generate_qmcpack
from qmcpack_input import back_propagation, onerdm
settings(
results='',
sleep=3,
machine='ws16',
)
system = generate_physical_system(
units='A',
elem_pos='''
C 0.00000000 0.00000000 0.00000000
H 0.00000000 0.00000000 1.10850000
H 1.04510382 0.00000000 -0.36950000
H -0.52255191 0.90508646 -0.36950000
H -0.52255191 -0.90508646 -0.36950000
''',
)
scf = generate_pyscf(
identifier='scf',
path='rhf',
job=job(serial=True),
template='./scf_template.py',
system=system,
mole=obj(basis='sto-3g', ),
checkpoint=True,
)
scf_job = job(nodes=1,minutes=30,presub=pwscf_modules,app='pw.x')
conv_job = job(cores=1,minutes=30,presub=pwscf_modules,app='pw2qmcpack.x')
qmc_job = job(nodes=1,threads=4,minutes=30,presub=qmcpack_modules,app='qmcpack')
else:
print 'no jobs for machine!'
exit()
#end if
dia16 = generate_physical_system(
units = 'A',
axes = [[ 1.785, 1.785, 0. ],
[ 0. , 1.785, 1.785],
[ 1.785, 0. , 1.785]],
elem = ['C','C'],
pos = [[ 0. , 0. , 0. ],
[ 0.8925, 0.8925, 0.8925]],
tiling = (2,2,2),
kgrid = (1,1,1),
kshift = (0,0,0),
C = 4
)
scf = generate_pwscf(
identifier = 'scf',
path = 'diamond/scf',
job = scf_job,
input_type = 'generic',
calculation = 'scf',
input_dft = 'lda',
ecutwfc = 200,
# specify k-point grids
kgrids = [(2, 2, 2), (3, 3, 3)]
sims = []
first = True
for kgrid in kgrids:
ks = '{0}{1}{2}'.format(*kgrid)
# create conventional cell tiled from primitive one
bcc_Be = generate_physical_system(lattice='cubic',
cell='primitive',
centering='I',
atoms='Be',
constants=3.490,
units='A',
net_charge=0,
net_spin=0,
Be=2,
tiling=[[a, b, c], [d, e, f], [g, h, i]],
kgrid=kgrid,
kshift=(.5, .5, .5))
# scf run to generate converged charge density
if first:
scf = generate_pwscf(identifier='scf',
path=directory + '/scf',
job=dft_job,
input_type='scf',
system=bcc_Be,
spin_polarized=False,
pseudos=dft_pps,
settings(
pseudo_dir = '../pseudopotentials',
status_only = 0,
generate_only = 0,
sleep = 3,
machine = 'ws16'
)
dia16 = generate_physical_system(
units = 'A',
axes = [[ 1.785, 1.785, 0. ],
[ 0. , 1.785, 1.785],
[ 1.785, 0. , 1.785]],
elem = ['C','C'],
pos = [[ 0. , 0. , 0. ],
[ 0.8925, 0.8925, 0.8925]],
tiling = (2,2,2),
kgrid = (1,1,1),
kshift = (0,0,0),
C = 4
)
scf = generate_pwscf(
identifier = 'scf',
path = 'diamond/scf',
job = Job(cores=16,app='pw.x'),
input_type = 'generic',
calculation = 'scf',
input_dft = 'lda',
ecutwfc = 200,
scf_job = job(app=pwscf, serial=True)
p2q_job = job(app=pw2qmcpack, serial=True)
opt_job = job(threads=4, app=qmcpack, serial=True)
dmc_job = job(threads=4, app=qmcpack, serial=True)
# System To Be Simulated
structure = read_structure('H2O.xyz')
structure.bounding_box(box='cubic', scale=1.5)
structure.add_kmesh(
kgrid=(1, 1, 1),
kshift=(0, 0, 0),
)
H2O_molecule = generate_physical_system(
structure=structure,
net_charge=0,
net_spin=0,
O=6,
H=1,
)
# DFT SCF To Generate Converged Density
scf = generate_pwscf(
identifier='scf',
path='.',
job=scf_job,
input_type='scf',
system=H2O_molecule,
pseudos=dft_pps,
ecut=50,
ecutrho=400,
conv_thr=1.0e-5,
settings(
pseudo_dir = './pseudopotentials',# directory with all pseudopotentials
sleep = 3, # check on runs every 'sleep' seconds
generate_only = 0, # only make input files
status_only = 0, # only show status of runs
machine = 'node16', # local machine is 16 core workstation
)
#generate the graphene physical system
graphene = generate_physical_system(
structure = 'graphite_aa', # graphite keyword
cell = 'hex', # hexagonal cell shape
tiling = (2,2,1), # tiling of primitive cell
constants = (2.462,10.0), # a,c constants
units = 'A', # in Angstrom
kgrid = (1,1,1), # Monkhorst-Pack grid
kshift = (.5,.5,.5), # and shift
C = 4 # C has 4 valence electrons
)
#generate the simulations for the qmc workflow
qsims = standard_qmc(
# subdirectory of runs
directory = 'graphene_test',
# description of the physical system
system = graphene,
pseudos = ['C.BFD.upf', # pwscf PP file
'C.BFD.xml'], # qmcpack PP file
# job parameters
from nexus import run_project
# set global parameters of nexus
settings(
pseudo_dir='../pseudopotentials', # directory with pseudopotentials
generate_only=0, # only write input files, T/F
status_only=0, # only show run status, T/F
machine='ws16' # local machine is 16 core workstation
)
# describe the physical system
T_system = generate_physical_system( # make the physical system
structure='./Ge_T_16.xyz', # out of the T interstitial structure
axes=[
[5.66, 5.66, 0.], # specify cell axes (in Angstrom)
[0., 5.66, 5.66],
[5.66, 0., 5.66]
],
Ge=4, # pseudo-Ge has 4 valence electrons
)
# specify MP k-point grids for successive relaxations
supercell_kgrids = [
(1, 1, 1), # 1 k-point
(2, 2, 2), # 8 k-points
(4, 4, 4), # 64 k-points
(6, 6, 6)
] # 216 k-points
# describe the relaxation calculations
# and link them together into a simulation cascade
#! /usr/bin/env python3
from nexus import settings,job,run_project,obj
from nexus import generate_physical_system
from nexus import generate_pyscf
from nexus import generate_pyscf_to_afqmc
from nexus import generate_qmcpack
settings(
results = '',
sleep = 3,
machine = 'ws16',
)
system = generate_physical_system(
units = 'A',
elem_pos = 'Ne 0 0 0',
)
scf = generate_pyscf(
identifier = 'scf',
path = 'rhf',
job = job(serial=True),
template = './scf_template.py',
system = system,
mole = obj(
verbose = 4,
basis = 'aug-cc-pvdz',
),
checkpoint = True,
)
user = '******'
)
scf_presub = '''
export HDF5_USE_FILE_LOCKING=FALSE
module unload cray-libsci
module load cray-hdf5
#module load python/3.7-anaconda-2019.10
source activate myenv
module list
'''
system = generate_physical_system(
structure = 'geom.xyz',
Be = 2, # Zeff=7 for ccECP
H = 1,
net_spin = 0, # 2S
net_charge = 0,
)
sims = []
# perform Hartree-Fock
scf = generate_pyscf(
identifier = 'scf', # log output goes to scf.out
path = 'scf', # directory to run in
job = job(serial=True, nodes=4, queue='debug', hours=0.5, constraint='knl', presub=scf_presub),
#job = job(serial=True, nodes=1, threads=4, presub=scf_presub),
template = 'scf_guess/scf_template.py', # pyscf template file
system = system,
mole = obj( # used to make Mole() inputs
verbose = 4,
units = 'A',
axes = [[ 1.785, 1.785, 0. ],
[ 0. , 1.785, 1.785],
[ 1.785, 0. , 1.785]],
elem = ['C','C'],
pos = [[ 0. , 0. , 0. ],
[ 0.8925, 0.8925, 0.8925]],
use_prim = True, # Use SeeK-path library to identify prim cell
tiling = [3,1,3], # Tile the cell
kgrid = (1,1,1),
kshift = (0,0,0), # Assumes we study transitions from Gamma. For non-gamma tilings, use kshift appropriately
C = 4,
)
dia = generate_physical_system(
**dia_inputs
)
dia_plus = generate_physical_system(
net_charge = 1,
net_spin = 1,
**dia_inputs
)
dia_minus = generate_physical_system(
net_charge = -1,
net_spin = -1,
**dia_inputs
)
scf = generate_pwscf(
timestep = 0.01,
nonlocalmoves = True
)
]
# create opt & DMC sim's for each bond length
sims = []
scale = 1.00
directory = 'scale_'+str(scale)
# make stretched/compressed dimer
dimer = generate_physical_system(
type = 'dimer', # dimer selected
dimer = ('O','O'), # atoms in dimer
separation = 1.2074*scale, # dimer bond length
Lbox = 15.0, # box size
units = 'A', # Angstrom units
net_spin = 2, # Nup-Ndown = 2
O = 6 # O has 6 val. electrons
)
# describe scf run
scf = generate_pwscf(
identifier = 'scf',
path = directory,
system = dimer,
job = Job(cores=16),
input_type = 'scf',
pseudos = ['O.BFD.upf'],
input_dft = 'lda',
ecut = 200,
# pos : corresponding atomic positions in cartesian coordinates
# kgrid : Monkhorst-Pack grid
# kshift : Monkhorst-Pack shift (between 0 and 0.5)
# net_charge : system charge in units of e
# net_spin : # of up spins - # of down spins
# C = 4 : (pseudo) carbon has 4 valence electrons
my_system = generate_physical_system(
units='A',
axes=[[3.57000000e+00, 0.00000000e+00, 0.00000000e+00],
[0.00000000e+00, 3.57000000e+00, 0.00000000e+00],
[0.00000000e+00, 0.00000000e+00, 3.57000000e+00]],
elem=['C', 'C', 'C', 'C', 'C', 'C', 'C', 'C'],
pos=[[0.00000000e+00, 0.00000000e+00, 0.00000000e+00],
[8.92500000e-01, 8.92500000e-01, 8.92500000e-01],
[0.00000000e+00, 1.78500000e+00, 1.78500000e+00],
[8.92500000e-01, 2.67750000e+00, 2.67750000e+00],
[1.78500000e+00, 0.00000000e+00, 1.78500000e+00],
[2.67750000e+00, 8.92500000e-01, 2.67750000e+00],
[1.78500000e+00, 1.78500000e+00, 0.00000000e+00],
[2.67750000e+00, 2.67750000e+00, 8.92500000e-01]],
kgrid=(1, 1, 1),
kshift=(0, 0, 0),
net_charge=0,
net_spin=0,
C=4 # one line like this for each atomic species
)
my_bconds = 'ppp' # ppp/nnn for periodic/open BC's in QMC
# if nnn, center atoms about (a1+a2+a3)/2
sims = []
from nexus import generate_pyscf_to_afqmc
from nexus import generate_qmcpack
settings(
results='',
sleep=3,
machine='ws16',
)
a = 3.6
system = generate_physical_system(
units='A',
axes=[[0, a / 2, a / 2], [a / 2, 0, a / 2], [a / 2, a / 2, 0]],
elem=('C', 'C'),
pos=[[0, 0, 0], [a / 4, a / 4, a / 4]],
tiling=(2, 2, 2),
kgrid=(1, 1, 1),
kshift=(0, 0, 0),
)
scf = generate_pyscf(
identifier='scf',
path='rhf',
job=job(serial=True),
template='./scf_template.py',
system=system,
cell=obj(
basis='gth-szv',
pseudo='gth-pade',
mesh=[25, 25, 25],
from nexus import generate_physical_system
from nexus import generate_quantum_package
# note: you must source the QP config file before running this script
# source /home/ubuntu/apps/qp2/quantum_package.rc
settings(
results='',
status_only=0,
generate_only=0,
sleep=3,
machine='ws16',
qprc='/home/ubuntu/apps/qp2/quantum_package.rc',
)
scf_job = job(cores=16, threads=16)
system = generate_physical_system(structure='H2O.xyz', )
scf = generate_quantum_package(
identifier='hf', # log output goes to hf.out
path='h2o_ae_hf', # directory to run in
job=scf_job,
system=system,
prefix='h2o', # create/use h2o.ezfio
run_type='scf', # qprun scf h2o.ezfio
ao_basis='cc-pvtz', # use cc-pvtz basis
)
run_project()
# run geometry optimization, scf, and polarization
# for all BFO cells
for strain in strains:
for shear in shears:
path = 'st_{0:4.3f}_sh_{1:4.3f}/'.format(strain, shear)
# strain and shearing cell parameters
a = 7.80 * (1. - strain)
c = shear * a
k = 0.0348994967 * c
# physical system for strained cell
system = generate_physical_system(
axes=[[a, 0, 0], [0, a, 0], [k, 0, c]],
elem=24 * ['O'] + 8 * ['Fe'] + 8 * ['Bi'],
posu=loadtxt('BFO_upos.dat'),
units='A',
kgrid=(2, 2, 2),
kshift=(0, 0, 0))
# geometry relaxation run
geo = generate_vasp(
# standard inputs
identifier='geo',
path=path,
job=vjob,
system=system,
# vasp inputs
ibrion=2,
isif=2,
ediffg=1e-6,
def mworkflow(shared_qe, params, sims):
for i in params_defaults.keys():
if i not in params:
setattr(params, i, params_defaults[i])
#end if
#end if
if params.j3:
if params.code == 'gpu':
print "GPU code and j3 not possible yet"
exit()
#end if
#end if
if params.excitation is not None:
params.twistnum = 0
########################
#DMC and VMC parameters#
########################
samples = 25600 #25600
vmcblocks = 100
dmcblocks = 300
dmceqblocks = 200
dmcwalkers = 1024 # For cades it is multiplied by 2
vmcdt = 0.3
if params.vmc:
vmcblocks = 9000
vmcdt = 0.3
dmcblocks = 1
dmceqblocks = 1
#end if
#############################
# Machine specific variables#
#############################
if params.machine == 'cades':
minnodes = 1
scf_nodes = 2
scf_hours = 48
p2q_nodes = scf_nodes
p2q_hours = 1
qeapp = 'pw.x -npool 4 '
if params.dft_grid == (1, 1, 1):
scf_nodes = 1
qeapp = 'pw.x'
#end if
qe_presub = 'module purge; module load PE-intel/3.0; module load hdf5_parallel/1.10.3'
opt_nodes = 4
opt_hours = 12
dmcnodespertwist = 0.5
dmc_hours = 24
qmc_threads = 18
walkers = qmc_threads
blocks = samples / (walkers * opt_nodes)
params.code = 'cpu'
qmcapp = ' qmcpack_cades_cpu_comp_SoA'
qmc_presub = 'module purge; module load PE-intel'
opt_job = Job(nodes=opt_nodes,
hours=opt_hours,
threads=qmc_threads,
app=qmcapp,
presub=qmc_presub)
elif params.machine == 'titan' or params.machine == 'eos':
minnodes = 1
dmcwalkers *= 2
scf_nodes = 8
scf_hours = 2
p2q_nodes = scf_nodes
p2q_hours = 1
qeapp = 'pw.x -npool 4 '
qe_presub = ''
if params.machine == 'eos':
opt_nodes = 16
opt_hours = 2
qmc_threads = 16
walkers = qmc_threads
blocks = samples / (walkers * opt_nodes)
params.code = 'cpu'
qmcapp = '/ccs/home/kayahan/SOFTWARE/qmcpack/eos/qmcpack/qmcpack_eos_cpu_comp_SoA'
qmc_presub = ''
params.rundmc = False
elif params.machine == 'titan':
if params.code == 'cpu':
dmcwalkers *= 2
vmcblocks = 50
opt_nodes = 16
opt_hours = 2
dmcnodespertwist = 32
dmc_hours = 6
qmc_threads = 16
walkers = qmc_threads
blocks = samples / (walkers * opt_nodes)
qmcapp = '/ccs/home/kayahan/SOFTWARE/qmcpack/titan/qmcpack/qmcpack_titan_cpu_comp_SoA'
qmc_presub = ''
params.rundmc = True
elif params.code == 'gpu':
dmcwalkers *= 8
opt_nodes = 4
opt_hours = 4
dmcnodespertwist = 8
dmc_hours = 1.5
qmc_threads = 16
walkers = qmc_threads
blocks = samples / (walkers * opt_nodes)
qmcapp = '/ccs/home/kayahan/SOFTWARE/qmcpack/titan/qmcpack/qmcpack_titan_gpu_comp_SoA'
qmc_presub = 'module load cudatoolkit'
#end if
#end if
opt_job = Job(nodes=opt_nodes,
hours=opt_hours,
threads=qmc_threads,
app=qmcapp,
presub=qmc_presub)
elif params.machine == 'cetus' or params.machine == 'mira':
if params.machine == 'cetus':
minnodes = 128
opt_hours = 1
dmc_hours = 1
elif params.machine == 'mira':
minnodes = 128
dmc_hours = 1
dmc_hours = 1
#end if
scf_nodes = 128
scf_hours = 1
p2q_nodes = 128
p2q_hours = 1
qeapp = 'pw.x'
qe_presub = ''
opt_nodes = 128.0
opt_nodes = np.round(opt_nodes / minnodes) * minnodes
dmcnodespertwist = 18
qmc_threads = 16
walkers = qmc_threads
qmc_processes_per_node = 16
blocks = samples / (walkers * opt_nodes)
params.code = 'cpu'
qmcapp = 'qmcpack'
qmc_presub = ''
opt_job = Job(nodes=opt_nodes,
hours=opt_hours,
threads=qmc_threads,
processes_per_node=qmc_processes_per_node,
app=qmcapp,
presub=qmc_presub)
elif params.machine == 'summit':
dmcwalkers *= 8
minnodes = 1
scf_nodes = 2
scf_hours = 24
p2q_nodes = 2
p2q_hours = 1
qeapp = 'pw.x -npool 4 '
if params.dft_grid == (1, 1, 1):
scf_nodes = 1
qeapp = 'pw.x'
#end if
qe_presub = 'module purge; module load PE-intel/3.0'
opt_nodes = 4
opt_hours = 4
dmcnodespertwist = 8
dmc_hours = 6
qmc_threads = 42
walkers = qmc_threads
blocks = samples / (walkers * opt_nodes)
qmcapp = '/ccs/home/kayahan/SOFTWARE/qmcpack/summit/qmcpack/build_summit_comp/bin/qmcpack'
else:
print "Machine is not defined!"
exit()
#end if
scf_job = Job(nodes=scf_nodes,
hours=scf_hours,
app=qeapp,
presub=qe_presub)
p2q_job = Job(nodes=p2q_nodes,
hours=p2q_hours,
app='pw2qmcpack.x -npool 4 ',
presub=qe_presub)
if params.big or params.qp:
dmcblocks *= 4
dmcnodespertwist *= 1
dmc_hours *= 2
dmcwalkers *= 2
#end if
shared_qe.wf_collect = False
shared_qe.nosym = True
shared_qe.job = scf_job
shared_qe.pseudos = params.dft_pps
if params.tot_mag is not None:
shared_qe.tot_magnetization = params.tot_mag
#end if
if params.two_u:
ulist = [params.ulist[0]]
else:
ulist = params.ulist
#end if
shared_relax = shared_qe.copy()
# qmcs list to possibly bundle all DMC calculations
qmcs = []
scf_ks_energy = 0
for u in ulist:
if u != 0.:
shared_qe.hubbard_u = obj()
shared_relax.hubbard_u = obj()
for inum, i in enumerate(params.uatoms):
if params.two_u:
setattr(shared_qe.hubbard_u, i, params.ulist[inum])
else:
setattr(shared_qe.hubbard_u, i, u)
setattr(shared_relax.hubbard_u, i, params.relax_u)
#end if
#end for
#end if
scf_inf = None
scf_path = './scf-u-' + str(u) + '-inf'
if params.relax:
shared_relax = shared_qe.copy()
shared_relax['ion_dynamics'] = 'bfgs'
shared_relax['cell_dynamics'] = 'bfgs'
shared_relax['calculation'] = 'vc-relax'
shared_relax['conv_thr'] = 10e-6
shared_relax['forc_conv_thr'] = 0.001
shared_relax['input_DFT'] = params.relax_functional
shared_relax.nosym = True
coarse_relax = generate_pwscf(
identifier='scf',
path='./coarse_relax-u-' + str(params.relax_u) + '-inf',
electron_maxstep=params.electron_maxstep,
nogamma=True,
system=params.system,
kgrid=params.dft_grid,
**shared_relax)
sims.append(coarse_relax)
shared_relax['conv_thr'] = 10e-8
shared_relax['forc_conv_thr'] = 0.001
fine_relax = generate_pwscf(
identifier='scf',
path='./fine_relax-u-' + str(params.relax_u) + '-inf',
electron_maxstep=params.electron_maxstep,
nogamma=True,
system=params.system,
kgrid=params.dft_grid,
dependencies=(coarse_relax, 'structure'),
**shared_relax)
sims.append(fine_relax)
scf_inf = generate_pwscf(
identifier='scf',
path=scf_path,
electron_maxstep=params.electron_maxstep,
nogamma=True,
system=params.system,
#nosym = True,
kgrid=params.dft_grid,
calculation='scf',
dependencies=(fine_relax, 'structure'),
**shared_qe)
#pdb.set_trace()
else:
scf_inf = generate_pwscf(
identifier='scf',
path=scf_path,
electron_maxstep=params.electron_maxstep,
nogamma=True,
system=params.system,
#nosym = True,
kgrid=params.dft_grid,
calculation='scf',
**shared_qe)
sims.append(scf_inf)
if params.nscf_only is True:
params.tilings = []
params.vmc_opt = False
params.qmc = False
if params.print_ke_corr:
scf_dir = scf_inf.remdir
pwscf_output = scf_inf.input.control.outdir
datafile_xml = scf_dir + '/' + pwscf_output + '/pwscf.save/data-file-schema.xml'
if os.path.isfile(datafile_xml):
xmltree = minidom.parse(datafile_xml)
ks_energies = xmltree.getElementsByTagName("ks_energies")
eig_tot = 0
for kpt in ks_energies:
w = float(
kpt.getElementsByTagName('k_point')[0].getAttribute(
'weight'))
eigs = np.array(kpt.getElementsByTagName('eigenvalues')
[0].firstChild.nodeValue.split(' '),
dtype='f')
occs = np.array(
kpt.getElementsByTagName(
'occupations')[0].firstChild.nodeValue.split(' '),
dtype='f') #Non-integer occupations from DFT
eig_tot += w * sum(
eigs * occs) / 2 #Divide by two for both spins
#end for
print scf_dir, "e_tot eigenvalues in Ha ", eig_tot / 2
if scf_ks_energy == 0:
scf_ks_energy = eig_tot / 2
#end if
#end if
for tl_num, tl in enumerate(params.tilings):
for k in params.qmc_grids:
knum = k[1] * k[2] * k[0]
if params.relax:
relax = fine_relax #prim = scf_inf.load_analyzer_image().input_structure.copy()
print 'Make sure the previous run is loaded to results!'
#scf_inf.system.structure
else:
relax = scf_inf
prim = params.system.structure.copy()
#system = params.system
prim.clear_kpoints()
super = prim.tile(tl)
tl_np = np.array(tl)
tl_det = int(np.abs(np.linalg.det(tl_np)) + 0.001)
if params.natoms is not None:
natoms = tl_det * params.natoms
else:
natoms = len(super.elem)
#end if
if params.rcut:
rcut = params.rcut[tl_num]
else:
rcut = super.rwigner() - 0.00001
#end if
if params.tot_mag is not None and params.qp is False:
system = generate_physical_system(
structure=prim,
tiling=tl,
kgrid=k,
kshift=params.kshift, #(0, 0, 0),
net_charge=params.charge,
net_spin=params.tot_mag,
use_prim=False,
**params.system.valency)
elif params.qp is False:
system = generate_physical_system(
structure=prim,
tiling=tl,
kgrid=k,
shift=params.kshift, #(0, 0, 0),
net_charge=params.charge,
**params.system.valency)
else:
system = generate_physical_system(
structure=prim,
tiling=tl,
kgrid=k,
kshift=params.kshift, #(0, 0, 0),
use_prim=False,
**params.system.valency)
#end if
# DFT NSCF To Generate Wave Function At Specified K-points
if params.dft_grid == params.qmc_grids[0] and len(
params.qmc_grids) == 1:
params.nscf_skip = True
if not params.nscf_skip:
if params.relax:
nscf_dep = [(scf_inf, 'charge_density'),
(relax, 'structure')]
else:
nscf_dep = [(scf_inf, 'charge_density')]
#end if
nscf_path = './nscf-u-' + str(u) + '-' + str(
knum) + '-' + str(natoms)
p2q_path = nscf_path
nscf = generate_pwscf(
identifier='nscf',
path=nscf_path,
system=system,
#nosym = True,
nogamma=True,
dependencies=nscf_dep,
calculation='nscf',
**shared_qe)
sims.append(nscf)
if params.relax:
p2q_dep = [(nscf, 'orbitals'), (relax, 'structure')]
else:
p2q_dep = [(nscf, 'orbitals')]
#end if
else:
p2q_path = scf_path
if params.relax:
p2q_dep = [(scf_inf, 'orbitals'), (relax, 'structure')]
else:
p2q_dep = [(scf_inf, 'orbitals')]
#end if
#end if
# Convert DFT Wavefunction Into HDF5 File For QMCPACK
p2q = generate_pw2qmcpack(
identifier='p2q',
path=p2q_path,
job=p2q_job,
write_psir=False,
dependencies=p2q_dep,
)
sims.append(p2q)
if params.print_ke_corr and not params.nscf_skip:
import h5py
nscf_dir = nscf.remdir
pwscf_output = nscf.input.control.outdir
h5_file = nscf_dir + '/' + pwscf_output + '/pwscf.pwscf.h5'
#Assume equal weight for all k-points
eig_tot = 0
nkpts = 0
if os.path.isfile(h5_file):
f = h5py.File(h5_file, 'r+')
nelect = f['electrons']['number_of_electrons'][:]
for group_e in f['electrons'].keys():
if group_e.startswith('kpoint'):
nkpts += 1
f_temp = f['electrons'][group_e]
for group_k in f_temp.keys():
k_s_eig = [0]
w = 0
if group_k.startswith('spin_0'):
k_s_eig = f_temp[group_k][
'eigenvalues'][:]
k_s_eig = k_s_eig[0:nelect[
0]] #fixed occupations from the number of electrons
w = f_temp['weight'][0]
elif group_k.startswith('spin_1'):
k_s_eig = f_temp[group_k][
'eigenvalues'][:]
k_s_eig = k_s_eig[0:nelect[1]]
w = f_temp['weight'][0]
#pdb.set_trace()
#end if
eig_tot += sum(k_s_eig) * w / 2
#end for
#end if
#end fof
print nscf_dir, "e_tot eigenvalues in Ha", eig_tot / 2 - scf_ks_energy, "wigner " + str(
system['structure'].rwigner())
#end if
#end if
# DFT is complete, rest is QMC
# change here for other AFM atoms
system.rename(Co1='Co', Co2='Co', Co3='Co', folded=False)
system.rename(Ni1='Ni', Ni2='Ni', Ni3='Ni', folded=False)
# VMC Optimization
linopt1 = linear(
energy=0.0, # 0.95
unreweightedvariance=1.0,
reweightedvariance=0.0, # 0.05
timestep=0.3,
samples=samples,
walkers=walkers,
warmupsteps=10,
blocks=blocks,
steps=1,
substeps=10,
maxweight=1e9,
gpu=True,
minmethod='OneShiftOnly',
minwalkers=0.01,
usebuffer=True,
exp0=-6,
bigchange=10.0,
alloweddifference=1e-04,
stepsize=0.15,
nstabilizers=1,
)
# Quasiparticle calculation
if params.qp:
etot = system.particles.down_electron.count + system.particles.up_electron.count
upe = (etot + params.tot_mag * tl_det) / 2 - params.charge
downe = etot - params.charge - upe
system.particles.down_electron.count = downe
system.particles.up_electron.count = upe
#end if
# 1. VMC optimization is requested
# 2. VMC optimization is done on the first element uf ulist
# 3. VMC optimization is done on the first element of qmc_grids
if params.vmc_opt and u == params.ulist[
0] and k == params.qmc_grids[0]:
# VMC Variance minimization
opt_varmin = generate_qmcpack(
identifier='opt-varmin',
path='./opt-u-' + str(u) + '-' + str(natoms) +
'-varmin-' + str(params.j),
job=opt_job,
input_type='basic',
system=system,
spin_polarized=True, # jtk: needs this
meshfactor=1.0,
hybrid_rcut=params.hybrid_rcut,
hybrid_lmax=params.hybrid_lmax,
#spline_radius = params.spline_radius,
twistnum=params.twistnum,
#bconds = 'ppp',
pseudos=params.qmc_pps,
jastrows=[('J1', 'bspline', params.j, rcut),
('J2', 'bspline', params.j, rcut, 'init',
'zero')],
calculations=[
loop(max=6, qmc=linopt1),
loop(max=6, qmc=linopt1)
],
dependencies=(p2q, 'orbitals'))
sims.append(opt_varmin)
# QMC Optimization Parameters - Finer Sampling Set -- Energy Minimization
linopt2 = linopt1.copy()
linopt2.minwalkers = 0.5
linopt2.energy = 0.95
linopt2.unreweightedvariance = 0.0
linopt2.reweightedvariance = 0.05
linopt3 = linopt2.copy()
linopt3.minwalkers = 0.5
##
emin_dep = []
# Use preliminary optimization step made of two steps
if not params.nopre:
preopt_emin = generate_qmcpack(
identifier='opt-emin',
path='./preopt-u-' + str(u) + '-' + str(natoms) +
'-emin-' + str(params.j),
job=opt_job,
input_type='basic',
system=system,
spin_polarized=True, # jtk: needs this
meshfactor=params.meshfactor,
hybrid_rcut=params.hybrid_rcut,
hybrid_lmax=params.hybrid_lmax,
#spline_radius = params.spline_radius,
twistnum=params.twistnum,
#bconds = 'ppp',
pseudos=params.qmc_pps,
jastrows=[],
calculations=[loop(max=2, qmc=linopt2)],
dependencies=[(p2q, 'orbitals'),
(opt_varmin, 'jastrow')])
sims.append(preopt_emin)
emin_dep = preopt_emin
else:
emin_dep = opt_varmin
#end if
opt_emin = generate_qmcpack(
identifier='opt-emin',
path='./opt-u-' + str(u) + '-' + str(natoms) +
'-emin-' + str(params.j),
job=opt_job,
input_type='basic',
system=system,
spin_polarized=True, # jtk: needs this
meshfactor=params.meshfactor,
hybrid_rcut=params.hybrid_rcut,
hybrid_lmax=params.hybrid_lmax,
#spline_radius = params.spline_radius,
twistnum=params.twistnum,
#bconds = 'ppp',
pseudos=params.qmc_pps,
jastrows=[],
calculations=[
loop(max=4, qmc=linopt2),
loop(max=4, qmc=linopt3)
],
dependencies=[(p2q, 'orbitals'),
(emin_dep, 'jastrow')])
sims.append(opt_emin)
# 3-body jastrows
if params.j3:
j3_dep = []
linopt2.walkers = 16
linopt2.blocks = linopt2.blocks * 2
linopt2.samples = linopt1.samples * 2
j3_rcut = min(system['structure'].rwigner() - 0.0001,
4.0)
if not params.nopre:
preopt_emin_J3 = generate_qmcpack(
identifier='opt-emin-J3',
path='./preopt-u-' + str(u) + '-' +
str(natoms) + '-emin-J3-' + str(params.j),
job=opt_job,
input_type='basic',
system=system,
spin_polarized=True, # jtk: needs this
meshfactor=params.meshfactor,
hybrid_rcut=params.hybrid_rcut,
hybrid_lmax=params.hybrid_lmax,
#spline_radius = params.spline_radius,
twistnum=params.twistnum,
#bconds = 'ppp',
pseudos=params.qmc_pps,
jastrows=[('J3', 'polynomial', 3, 3, j3_rcut)],
calculations=[loop(max=2, qmc=linopt2)],
dependencies=[(p2q, 'orbitals'),
(opt_emin, 'jastrow')])
sims.append(preopt_emin_J3)
j3_dep = preopt_emin_J3
else:
j3_dep = opt_emin
#end if
opt_emin_J3 = generate_qmcpack(
identifier='opt-emin-J3',
path='./opt-u-' + str(u) + '-' + str(natoms) +
'-emin-J3-' + str(params.j),
job=opt_job,
input_type='basic',
system=system,
spin_polarized=True, # jtk: needs this
meshfactor=params.meshfactor,
hybrid_rcut=params.hybrid_rcut,
hybrid_lmax=params.hybrid_lmax,
#spline_radius = params.spline_radius,
twistnum=params.twistnum,
#bconds = 'ppp',
pseudos=params.qmc_pps,
jastrows=[('J3', 'polynomial', 3, 3, j3_rcut)],
calculations=[
loop(max=4, qmc=linopt2),
loop(max=4, qmc=linopt2)
],
dependencies=[(p2q, 'orbitals'),
(j3_dep, 'jastrow')])
sims.append(opt_emin_J3)
#end if
#end if
# VMC is complete, run DMC
dmc_nodes = np.round(
np.ceil(knum * dmcnodespertwist) / minnodes) * minnodes
dmc_job = Job(nodes=int(dmc_nodes),
hours=dmc_hours,
threads=qmc_threads,
app=qmcapp,
presub=qmc_presub)
# Add any future estimators here
from qmcpack_input import spindensity, skall, density
if params.density is not None:
est = [spindensity(grid=params.density)]
else:
est = None
#end if
#Initial VMC calculation to generate walkers for DMC
calculations = [
vmc(
warmupsteps=25,
blocks=vmcblocks,
steps=1,
stepsbetweensamples=1,
walkers=walkers,
timestep=vmcdt,
substeps=4,
samplesperthread=int(dmcwalkers /
(dmcnodespertwist * walkers)),
),
# dmc(
# warmupsteps =0,
# blocks =dmceqblocks/4,
# steps =5,
# timestep =0.04,
# nonlocalmoves=params.tmoves,
# ),
# dmc(
# warmupsteps =0,
# blocks =dmceqblocks/4,
# steps =5,
# timestep =0.02,
# nonlocalmoves=params.tmoves,
# ),
]
# Scan over timesteps
if params.timesteps is None:
params.timesteps = [0.01]
#end if
for t in params.timesteps:
calculations.append(
dmc(
warmupsteps=dmceqblocks / 2,
blocks=int(dmcblocks / (np.sqrt(t) * 10)),
steps=10,
timestep=t,
nonlocalmoves=params.tmoves,
))
#end for
# Prepanding name for the path
pathpre = 'dmc'
if params.vmc:
pathpre = 'vmc'
#end if
deps = [(p2q, 'orbitals')]
has_jastrow = False
# 3-body jastrow calculation with VMC or DMC
if params.j3:
has_jastrow = True
# add j3 dependenciies
if params.vmc_opt:
deps.append((opt_emin_J3, 'jastrow'))
#end if
if params.tmoves:
path = './' + pathpre + '-j3-tm-u-' + str(
u) + '-' + str(knum) + '-' + str(natoms)
else:
path = './' + pathpre + '-j3-nl-u-' + str(
u) + '-' + str(knum) + '-' + str(natoms)
#end if
#end if
# 2-body jastrow calculation with VMC or DMC
if params.j2:
has_jastrow = True
#add j2 dependencies
if params.vmc_opt:
deps.append((opt_emin, 'jastrow'))
#end if
if params.tmoves:
path = './' + pathpre + '-j2-tm-u-' + str(
u) + '-' + str(knum) + '-' + str(natoms)
else:
path = './' + pathpre + '-j2-nl-u-' + str(
u) + '-' + str(knum) + '-' + str(natoms)
#end if
#end if
# No jastrow calculation with VMC or DMC
if not has_jastrow:
if params.tmoves:
path = './' + pathpre + '-j0-tm-u-' + str(
u) + '-' + str(knum) + '-' + str(natoms)
else:
path = './' + pathpre + '-j0-nl-u-' + str(
u) + '-' + str(knum) + '-' + str(natoms)
#end if
#end if
det_format = 'new'
# Optical excitation
if params.excitation is not None:
path += '_' + params.excitation[
0] + '_' + params.excitation[1].replace(" ", "_")
det_format = 'old'
#end if
# Charged cell
if params.charge != 0:
path += '_' + str(params.charge)
#end if
if params.qmc:
qmc = generate_qmcpack(seed=params.seed,
skip_submit=params.qmc_skip_submit,
det_format=det_format,
identifier=pathpre,
path=path,
job=dmc_job,
input_type='basic',
system=system,
estimators=est,
meshfactor=params.meshfactor,
hybrid_rcut=params.hybrid_rcut,
hybrid_lmax=params.hybrid_lmax,
excitation=params.excitation,
pseudos=params.qmc_pps,
jastrows=[],
spin_polarized=True,
calculations=calculations,
dependencies=deps)
qmcs.append(qmc)
#end if
#end if
#end for
#end for
if params.bundle:
from bundle import bundle
qmcb = bundle(qmcs)
sims.append(qmcb)
else:
sims = sims + qmcs
return sims
#general settings for nexus
settings(
pseudo_dir='./pseudopotentials', # directory with all pseudopotentials
sleep=3, # check on runs every 'sleep' seconds
generate_only=0, # only make input files
status_only=0, # only show status of runs
machine='node16', # local machine is 16 core workstation
)
#generate the graphene physical system
graphene = generate_physical_system(
structure='graphite_aa', # graphite keyword
cell='hex', # hexagonal cell shape
tiling=(2, 2, 1), # tiling of primitive cell
constants=(2.462, 10.0), # a,c constants
units='A', # in Angstrom
kgrid=(1, 1, 1), # Monkhorst-Pack grid
kshift=(.5, .5, .5), # and shift
C=4 # C has 4 valence electrons
)
#generate the simulations for the qmc workflow
qsims = standard_qmc(
# subdirectory of runs
directory='graphene_test',
# description of the physical system
system=graphene,
pseudos=[
'C.BFD.upf', # pwscf PP file
'C.BFD.xml'
], # qmcpack PP file
vesta = get_machine('vesta') # allow one job at a time (lab only)
vesta.queue_size = 2
#end if
# create DFT, OPT, & DMC sim's for each bond length
sims = []
scales = [1.00, 0.90, 0.925, 0.95, 0.975, 1.025, 1.05, 1.075, 1.10]
for scale in scales:
directory = 'scale_' + str(scale)
# make stretched/compressed dimer
dimer = generate_physical_system(
type='dimer',
dimer=('O', 'O'),
separation=1.2074 * scale,
Lbox=10.0, # use 15.0 or so for production
units='A',
net_spin=2,
O=6,
)
# describe DFT run
dft = generate_pwscf(
identifier='dft',
path=directory,
job=dftjob,
system=dimer,
input_type='scf',
pseudos=['O.BFD.upf'],
input_dft='lda',
ecut=300,
# job details
dft_job = job(nodes=1, minutes=20, queue="qmcpack", app=pwscf)
p2q_job = job(cores=1, minutes=20, queue="qmcpack", app=pw2qmcpack)
qmc_job = job(nodes=32, minutes=20, threads=16, queue="qmcpack", app=qmcpack)
# create 2 atom sheet of graphene
graphene = generate_physical_system(
axes=[[9.30501148, 0.00000000, 0.0000000],
[-4.6525058, 8.05837632, 0.0000000],
[0.00000000, 0.00000000, 15.0000000]],
elem=['C', 'C', 'C', 'C', 'C', 'C', 'C', 'C'],
pos=[[0.00000000, 0.00000000, 7.50000000],
[2.32625287, 1.34306272, 7.50000000],
[4.65250574, 0.00000000, 7.50000000],
[6.97875861, 1.34306272, 7.50000000],
[-2.32625290, 4.02918816, 7.50000000],
[-0.00000003, 5.37225088, 7.50000000],
[2.32625284, 4.02918816, 7.50000000],
[4.65250571, 5.37225088, 7.50000000]],
units='B',
kgrid=(1, 1, 1),
kshift=(0, 0, 0),
net_charge=0,
net_spin=0,
C=4)
sims = []
# scf run to generate converged charge density
scf = generate_pwscf(identifier='scf',
path=directory + '/scf',
results = '',
status_only = 0,
generate_only = 0,
sleep = 3,
machine = 'ws16',
qprc = '/home/ubuntu/apps/qp2/quantum_package.rc',
)
# define run details
qp_job = job(cores=16,threads=16)
c4q_job = job(cores=1)
qmc_job = job(cores=16,threads=16)
# read in structure for oxygen dimer
dimer = generate_physical_system(
structure = './O2.xyz',
net_spin = 2,
)
# path, job, system details are shared across runs
qp_shared = dict(
path = 'O_dimer/selci',
job = qp_job,
system = dimer,
prefix = 'fci', # single shared ezfio
)
# run Hartree-Fock
scf = generate_quantum_package(
identifier = 'scf',
run_type = 'scf',
ao_basis = 'aug-cc-pvdz',
from nexus import generate_physical_system
from nexus import generate_pwscf_input
# generate using keywords + system
# read structure from file
s = read_structure('VO2_M1_afm.xsf')
s.elem[0] = 'V1' # set AFM pattern
s.elem[1] = 'V2'
s.elem[2] = 'V1'
s.elem[3] = 'V2'
# create physical system from structure
vo2 = generate_physical_system(
structure=s,
V1=13,
V2=13,
O=6,
)
# generate pwscf input
pw = generate_pwscf_input(
selector='generic',
calculation='scf',
disk_io='low',
verbosity='high',
wf_collect=True,
input_dft='lda',
hubbard_u=obj(V1=3.5, V2=3.5),
ecutwfc=350,
bandfac=1.3,
nosym=True,
jobs = get_taito_configs()
cubic_box_size=[10.0]
x=1.0*cubic_box_size[0]
d=1.2074 # nuclei separation in Angstrom
scfs=[]
ind=0
O2 = generate_physical_system(
units = 'A',
axes = [[ x, 0.0 , 0.0 ],
[ 0., x , 0.0 ],
[ 0., 0. , x ]],
elem = ['O','O'],
pos = [[ x/2-d/2 , x/2 , x/2 ],
[ x/2+d/2 , x/2 , x/2 ]],
net_spin = 0,
tiling = (1,1,1),
kgrid = (1,1,1), # scf kgrid given below to enable symmetries
kshift = (0,0,0),
O = 6,
)
scf = generate_pwscf(
identifier = 'scf',
path = 'scf'+str(ind),
job = jobs['scf'],
input_type = 'generic',
calculation = 'scf',
input_dft = 'lda',
for kgtid in [(1,1,1), (2,2,2), (3,3,3)]:
timestep = 0.01,
nonlocalmoves = True
)
]
# create opt & DMC sim's for each bond length
sims = []
scale = 1.00
directory = 'scale_'+str(scale)
# make stretched/compressed dimer
dimer = generate_physical_system(
type = 'dimer', # dimer selected
dimer = ('O','O'), # atoms in dimer
separation = 1.2074*scale, # dimer bond length
Lbox = 15.0, # box size
units = 'A', # Angstrom units
net_spin = 2, # Nup-Ndown = 2
O = 6 # O has 6 val. electrons
)
# describe scf run
scf = generate_pwscf(
identifier = 'scf',
path = directory,
system = dimer,
job = Job(cores=16),
input_type = 'scf',
pseudos = ['O.BFD.upf'],
input_dft = 'lda',
ecut = 200,
from nexus import generate_qmcpack
settings(
pseudo_dir='../../pseudopotentials',
results='',
sleep=3,
machine='ws16',
)
system = generate_physical_system(
units='A',
axes='''1.785 1.785 0.000
0.000 1.785 1.785
1.785 0.000 1.785''',
elem_pos='''
C 0.0000 0.0000 0.0000
C 0.8925 0.8925 0.8925
''',
tiling=[[1, -1, 1], [1, 1, -1], [-1, 1, 1]],
kgrid=(1, 1, 1),
kshift=(0, 0, 0),
C=4,
)
scf = generate_pwscf(
identifier='scf',
path='diamond/scf',
job=job(cores=16, app='pw.x'),
input_type='generic',
calculation='scf',
input_dft='lda',
ecutwfc=200,
'''
rhf_runs = []
x = np.linspace(-1.5,1.5,32)
z = np.linspace(-1.0,2.0,32)
for i in range(len(x)):
for j in range(len(z)):
myid = "x%2.5f_z%2.5f" % (x[i],z[j])
struct = Structure(elem=['H','C','N'],
pos=[[x[i],0,z[j]],
[0,0,-CH],
[0,0,-(CH+CN)]]
,units='A')
system = generate_physical_system(
structure = struct,
net_charge = 0,
net_spin = 0
)
rhf_inputs = obj(
identifier = myid + 'rhf',
scftyp = 'rhf',
gbasis = basis,
ispher = 1,
runtyp = 'energy',
coord = 'unique',
system = system,
dirscf = True, # use ram for speed
job = gms_job,
)
rhf = generate_gamess(
path = myid+'/rhf',
for scaling in scalings:
dia16_struct = generate_structure(
units='A',
axes=[[1.785, 1.785, 0.], [0., 1.785, 1.785], [1.785, 0., 1.785]],
elem=['C', 'C'],
pos=[[0., 0., 0.], [0.8925, 0.8925, 0.8925]],
tiling=(2, 2, 2),
kgrid=(1, 1, 1),
kshift=(0, 0, 0),
)
dia16_struct.rescale(scaling)
dia16 = generate_physical_system(structure=dia16_struct, C=4)
basepath = 'diamond/scale_{0:3.2f}'.format(scaling)
scf = generate_pwscf(
identifier='scf',
path=basepath + '/scf',
job=scf_job,
input_type='generic',
calculation='scf',
input_dft='lda',
ecutwfc=200,
conv_thr=1e-8,
nosym=True,
wf_collect=True,
system=dia16,
scf_job = job(app=pwscf,serial=True)
nscf_job = job(app=pwscf,serial=True)
p2q_job = job(app=pw2qmcpack,serial=True)
opt_job = job(threads=4,app=qmcpack,serial=True)
dmc_job = job(threads=4,app=qmcpack,serial=True)
# System To Be Simulated
rocksalt_LiH = generate_physical_system(
lattice = 'cubic',
cell = 'primitive',
centering = 'F',
atoms = ('Li','H'),
basis = [[0.0,0.0,0.0],
[0.5,0.5,0.5]],
basis_vectors = 'conventional',
constants = 7.1,
units = 'B',
kgrid = (1,1,1),
kshift = (0,0,0),
net_charge = 0,
net_spin = 0,
Li = 1,
H = 1,
)
# DFT SCF To Generate Converged Density
scf = generate_pwscf(
identifier = 'scf',
path = '.',
job = scf_job,
input_type = 'scf',
results = '',
runs = 'diamond_runs',
status_only = 0,
generate_only = 0,
sleep = 3,
machine = 'ws16'
)
#Input structure
dia = generate_physical_system(
units = 'A',
axes = [[ 1.785, 1.785, 0. ],
[ 0. , 1.785, 1.785],
[ 1.785, 0. , 1.785]],
elem = ['C','C'],
pos = [[ 0. , 0. , 0. ],
[ 0.8925, 0.8925, 0.8925]],
use_prim = True, # Use SeeK-path library to identify prim cell
tiling = [3,1,3], # Tile the cell
kgrid = (1,1,1),
kshift = (0,0,0), # Assumes we study transitions from Gamma. For non-gamma tilings, use kshift appropriately
C = 4
)
scf = generate_pwscf(
identifier = 'scf',
path = 'scf',
job = job(cores=16,app='pw.x'),
input_type = 'generic',
calculation = 'scf',
nspin = 2,
input_dft = 'lda',
# read in the xyz file
structure = read_structure('c20.cage.xyz')
# place a bounding box around the structure
structure.bounding_box(
box='cubic', # cube shaped cell
scale=1.5 # 50% extra space
)
# make it a gamma point cell
structure.add_kmesh(
kgrid=(1, 1, 1), # Monkhorst-Pack grid
kshift=(0, 0, 0) # and shift
)
# add electronic information
c20 = generate_physical_system(
structure=structure, # C20 structure
net_charge=0, # net charge in units of e
net_spin=0, # net spin in units of e-spin
C=4, # C has 4 valence electrons
)
# scf run produces charge density
scf = generate_pwscf(
# nexus inputs
identifier='scf', # identifier/file prefix
path='c20/scf', # directory for scf run
job=job(cores=16), # run on 16 cores
pseudos=['C.BFD.upf'], # pwscf PP file
system=c20, # run c20
# input format selector
input_type='scf', # scf, nscf, relax, or generic
# pwscf input parameters
input_dft='lda', # dft functional
generate_only = 0,
sleep = 3,
machine = 'ws16',
ericfmt = '/your/path/to/ericfmt.dat'
)
gms_job = job(cores=16,app='gamess.x')
h2o = generate_physical_system(
# full atomic/electronic structure
elem = ['O','H','H'],
pos = [[0.000000, 0.000000, 0.000000],
[0.000000,-0.757160, 0.586260],
[0.000000, 0.757160, 0.586260]],
units = 'A', # Angstroms
net_spin = 0, # multiplicity=1, nup-ndown=0
O = 6, # Zeff=6 for BFD ECP
H = 1, # Zeff=1 for BFD ECP
# C2v symmetry structure
folded_elem = ['O','H'],
folded_pos = [[0.000000, 0.000000, 0.000000],
[0.000000, 0.757160, 0.586260]],
)
rhf = generate_gamess(
identifier = 'rhf',
path = 'pp_cisd',
job = gms_job,
system = h2o,
pseudos = ['O.BFD_V5Z.gms','H.BFD_V5Z_ANO.gms'],
scftyp = 'rohf',
status_only=1,
machine='cades',
account='qmc')
#CHANGE_HERE_ONLY#
######################################################################
########################## Change here only ##########################`
#STRUCTURE
prim = read_structure('POSCAR')
prim.frozen = None
ph = generate_physical_system(structure=prim.copy(),
Li=1,
Ni=18,
O=6,
net_spin=1)
mag = [0.7]
tot_mag = 1
#######################################################################
########################## Change here only ##########################
shared_scf = obj(
input_type='generic',
occupations='smearing',
smearing='gaussian',
degauss=0.005,
tot_magnetization=tot_mag,
####################
from nexus import generate_physical_system
from nexus import generate_pwscf
from nexus import generate_pw2qmcpack
from nexus import generate_qmcpack, vmc
from structure import *
settings(pseudo_dir='../../pseudopotentials',
status_only=0,
generate_only=0,
sleep=3,
machine='ws16')
#Input structure
dia = generate_physical_system(units='A',
axes=[[1.785, 1.785, 0.], [0., 1.785, 1.785],
[1.785, 0., 1.785]],
elem=['C', 'C'],
pos=[[0., 0., 0.], [0.8925, 0.8925, 0.8925]],
C=4)
#Standardized Primitive cell -- run rest of the calculations on this cell
dia2_structure = get_primitive_cell(structure=dia.structure)['structure']
#get_band_tiling requires "SeeK-path" python3 libraries
dia2 = generate_physical_system(
structure=dia2_structure,
kgrid=(1, 1, 1),
kshift=(
0, 0, 0
), # Assumes we study transitions from Gamma. For non-gamma tilings, use kshift appropriately
tiling=[3, 1, 3],
C=4,
sleep = 3, # check on runs every 'sleep' seconds
generate_only = 0, # only make input files
status_only = 0, # only show status of runs
machine = 'ws16', # local machine is 16 core workstation
)
# generate the graphene physical system
graphene = generate_physical_system(
lattice = 'hexagonal', # hexagonal cell shape
cell = 'primitive', # primitive cell
centering = 'P', # primitive basis centering
constants = (2.462,10.0), # a,c constants
units = 'A', # in Angstrom
atoms = ('C','C'), # C primitive atoms
basis = [[ 0 , 0 , 0], # basis vectors
[2./3,1./3, 0]],
tiling = (2,2,1), # tiling of primitive cell
kgrid = (1,1,1), # Monkhorst-Pack grid
kshift = (.5,.5,.5), # and shift
C = 4 # C has 4 valence electrons
)
# list of simulations in workflow
sims = []
# scf run produces charge density
scf = generate_pwscf(
# nexus inputs
identifier = 'scf', # identifier/file prefix
