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,
conv_thr=1e-7,
mixing_beta=.7,
nosym=True,
wf_collect=True,
)
sims.append(dft)
# describe orbital conversion run
p2q = generate_pw2qmcpack(
identifier='p2q',
path=directory,
job=p2qjob,
write_psir=False,
dependencies=(dft, 'orbitals'),
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
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,
input_dft='lda',
ecut=200,
conv_thr=1e-8,
mixing_beta=.7,
nosym=False,
wf_collect=False,
kgrid=(8, 8, 8),
kshift=(0, 0, 0))
sims.append(scf)
#end if
# nscf run to generate orbitals
nscf = generate_pwscf(identifier='nscf',
path=directory + '/nscf_' + ks,
job=dft_job,
input_type='nscf',
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 = []
# scf run to generate orbitals
scf = generate_pwscf(
identifier='scf',
path=my_project_name,
job=dftjob,
input_type='scf',
system=my_system,
pseudos=my_dft_pps,
input_dft='lda',
ecut=200, # PW energy cutoff in Ry
conv_thr=1e-8,
mixing_beta=.7,
nosym=True,
wf_collect=True)
sims.append(scf)
# conversion step to create h5 file with orbitals
p2q = generate_pw2qmcpack(identifier='p2q',
path=my_project_name,
job=p2qjob,
write_psir=False,
dependencies=(scf, 'orbitals'))
sims.append(p2q)
# list of simulations in workflow
sims = []
# 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
# input format selector
input_type = 'scf', # scf, nscf, relax, or generic
# pwscf input parameters
input_dft = 'lda', # dft functional
ecut = 150 , # planewave energy cutoff (Ry)
conv_thr = 1e-6, # scf convergence threshold (Ry)
mixing_beta = .7, # charge mixing factor
kgrid = (8,8,8), # MP grid of primitive cell
kshift = (1,1,1), # to converge charge density
wf_collect = False, # don't collect orbitals
use_folded = True # use primitive rep of graphene
)
sims.append(scf)
# nscf run to produce orbitals for jastrow optimization
nscf_opt = generate_pwscf(
# nexus inputs
identifier = 'nscf', # identifier/file prefix
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,
conv_thr=1e-8,
system=system,
pseudos=['C.BFD.upf'],
kgrid=(4, 4, 4),
kshift=(0, 0, 0),
)
nscf = generate_pwscf(
identifier='nscf',
path='diamond/nscf',
job=job(cores=16, app='pw.x'),
input_type='generic',
calculation='nscf',
input_dft='lda',
ecutwfc=200,
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
# input format selector
input_type = 'scf', # scf, nscf, relax, or generic
# pwscf input parameters
input_dft = 'lda', # dft functional
ecut = 150 , # planewave energy cutoff (Ry)
conv_thr = 1e-6, # scf convergence threshold (Ry)
mixing_beta = .7, # charge mixing factor
kgrid = (8,8,8), # MP grid of primitive cell
kshift = (1,1,1), # to converge charge density
wf_collect = False, # don't collect orbitals
use_folded = True, # use primitive rep of graphene
)
# nscf run to produce orbitals for jastrow optimization
nscf_opt = generate_pwscf(
# nexus inputs
identifier = 'nscf', # identifier/file prefix
path = 'graphene/nscf_opt', # directory for nscf run
)
# list of simulations in workflow
sims = []
# 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
ecut = 150 , # planewave energy cutoff (Ry)
conv_thr = 1e-6, # scf convergence threshold (Ry)
mixing_beta = .7, # charge mixing factor
nosym = True, # don't use symmetry
wf_collect = True, # write out orbitals
)
sims.append(scf)
# orbital conversion job for opt and dmc
p2q = generate_pw2qmcpack(
# nexus inputs
identifier = 'p2q',
path = 'c20/nscf',
net_charge = 0,
net_spin = 0,
O = 6,
H = 1,
)
sims = []
# 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,
mixing_beta = 0.7,
mixing_mode = 'local-TF',
degauss = 0.001
)
sims.append(scf)
# Convert DFT Wavefunction Into HDF5 File For QMCPACK
p2q = generate_pw2qmcpack(
identifier = 'p2q',
path = '.',
job = p2q_job,
write_psir = False,
dependencies = (scf,'orbitals')
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)
# most familiar
scf = generate_pwscf(
# Nexus Simulation class inputs
identifier='scf',
path='diamond/scf',
job=job(cores=16, app='pw.x'),
# PwscfInput class inputs
input_type='generic',
calculation='scf',
input_dft='lda',
ecutwfc=200,
conv_thr=1e-8,
nosym=True,
wf_collect=True,
system=dia16, # shared by Simulation/PwscfInput
pseudos=['C.BFD.upf'], # shared by Simulation/PwscfInput
)
print
print '===================='
print 'overview of contents'
print '===================='
print repr(scf.input) # PwscfInput class
#equivalent to the above
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,
conv_thr = 1e-7,
mixing_beta = .7,
nosym = True,
wf_collect = True
)
sims.append(scf)
# describe orbital conversion
p2q = generate_pw2qmcpack(
identifier = 'p2q',
path = directory,
job = Job(cores=1),
write_psir = False,
dependencies = (scf,'orbitals')
(4,4,4), # 64 k-points
(6,6,6)] # 216 k-points
# describe the relaxation calculations
# and link them together into a simulation cascade
relaxations = [] # list of relax simulation objects
for kgrid in supercell_kgrids: # loop over supercell kgrids
relax = generate_pwscf( # make each relax simulation
identifier = 'relax', # file prefix
# run directory
path = 'relax/kgrid_{0}{1}{2}'.format(*kgrid),
job = Job(cores=16), # will run with mpirun -np 16
input_type = 'relax', # this is a relax calculation
input_dft = 'pbe', # PBE functional
ecut = 50, # 50 Ry planewave cutoff
conv_thr = 1e-6, # convergence threshold
kgrid = kgrid, # supercell k-point grid
kshift = (1,1,1), # grid centered at supercell L point
pseudos = ['Ge.pbe-kjpaw.UPF'], # PBE pseudopotential
system = T_system # the interstitial system
)
# link together the simulation cascade
# current relax gets structure from previous
if len(relaxations)>0: # if it exists
relax.depends(relaxations[-1],'structure')
#end if
relaxations.append(relax) # add relax simulation to the list
#end for
# twist-mesh used for qmc
dia16.structure.add_symmetrized_kmesh(kgrid=(2,2,2),kshift=(0,0,0))
number_of_ks_orbs = 11
scf = generate_pwscf(
identifier = 'scf',
path = 'scf',
job = job(cores=1,app='pw.x',hours=1),
input_type = 'generic',
calculation = 'scf',
nspin = 2,
tot_magnetization = 0,
nbnd = number_of_ks_orbs,
input_dft = 'lda',
ecutwfc = 200,
conv_thr = 1e-8,
nosym = False,
wf_collect = False,
system = dia16,
kgrid = scf_kg,
kshift = (0,0,0),
pseudos = ['C.BFD.upf'],
)
nscf = generate_pwscf(
identifier = 'nscf',
path = 'nscf',
job = job(cores=1,app='pw.x',hours=1),
input_type = 'generic',
s.write('d16vac.xsf')
dia16vac = generate_physical_system(
structure = s,
C = 4,
)
print b+'net charge:',dia16vac.net_charge
scf = generate_pwscf(
identifier = 'scf',
path = 'diamond/scf',
job = scf_job,
input_type = 'generic',
calculation = 'scf',
input_dft = 'lda',
ecutwfc = 200,
mixing_beta = 0.2,
degauss = 0.01,
conv_thr = 1e-6,
system = dia16vac,
kgrid = (3,3,3),
kshift = (0,0,0),
pseudos = ['C.BFD.upf'],
)
print b+'scf directory:',scf.locdir
si = scf.input
print b+'scf input data\n',si
print b+'scf input file\n',si.write()
pm = run_project()
print b+'status after execute:'
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,
conv_thr = 1e-8,
nosym = True,
wf_collect = True,
system = dia16,
pseudos = ['C.BFD.upf'],
)
conv = generate_pw2qmcpack(
identifier = 'conv',
path = 'diamond/scf',
job = Job(cores=1,app='pw2qmcpack.x'),
write_psir = False,
dependencies = (scf,'orbitals')
)
(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
relaxations = [] # list of relax simulation objects
for kgrid in supercell_kgrids: # loop over supercell kgrids
relax = generate_pwscf( # make each relax simulation
identifier='relax', # file prefix
# run directory
path='relax/kgrid_{0}{1}{2}'.format(*kgrid),
job=Job(cores=16), # will run with mpirun -np 16
input_type='relax', # this is a relax calculation
input_dft='pbe', # PBE functional
ecut=50, # 50 Ry planewave cutoff
conv_thr=1e-6, # convergence threshold
kgrid=kgrid, # supercell k-point grid
kshift=(1, 1, 1), # grid centered at supercell L point
pseudos=['Ge.pbe-kjpaw.UPF'], # PBE pseudopotential
system=T_system # the interstitial system
)
# link together the simulation cascade
# current relax gets structure from previous
if len(relaxations) > 0: # if it exists
relax.depends(relaxations[-1], 'structure')
#end if
relaxations.append(relax) # add relax simulation to the list
#end for
# perform the simulations
[ 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)]:
ecutwfc = 200,
conv_thr = 1e-8,
nosym = True,
wf_collect = True,
system = O2,
# kgrid = (1,1,1),
pseudos = ['O.BFD.upf'],
ind += 1
)
scfs.append(scf)
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,
conv_thr = 1e-7,
mixing_beta = .7,
nosym = True,
wf_collect = True
)
sims.append(scf)
# describe orbital conversion
p2q = generate_pw2qmcpack(
identifier = 'p2q',
path = directory,
job = Job(cores=1),
write_psir = False,
dependencies = (scf,'orbitals')
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,
pseudos=['C.BFD.upf'],
)
conv = generate_pw2qmcpack(
identifier='conv',
path=basepath + '/scf',
job=conv_job,
write_psir=False,
dependencies=(scf, 'orbitals'),
)
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',
system = rocksalt_LiH,
pseudos = dft_pps,
ecut = 450,
ecutrho = 1800,
conv_thr = 1.0e-10,
mixing_beta = 0.7,
kgrid = (7,7,7),
kshift = (1,1,1),
)
# DFT NSCF To Generate Wave Function At Specified K-points
nscf = generate_pwscf(
identifier = 'nscf',
path = '.',
job = nscf_job,
input_type = 'nscf',
system = rocksalt_LiH,
pseudos = dft_pps,
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',
ecutwfc = 200,
conv_thr = 1e-8,
nosym = False,
wf_collect = False,
system = dia,
kgrid = (4,4,4),
kshift = (0,0,0),
tot_magnetization = 0,
pseudos = ['C.BFD.upf'],
)
nscf = generate_pwscf(
identifier = 'nscf',
path = 'nscf',
job = job(cores=16,app='pw.x'),
input_type = 'generic',
calculation = 'nscf',
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
ecut=150, # planewave energy cutoff (Ry)
conv_thr=1e-6, # scf convergence threshold (Ry)
mixing_beta=.7, # charge mixing factor
nosym=True, # don't use symmetry
wf_collect=True, # write out orbitals
)
# orbital conversion job for opt and dmc
p2q = generate_pw2qmcpack(
# nexus inputs
identifier='p2q',
path='c20/nscf',
job=job(cores=1),
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,
)
scf = generate_pwscf(
identifier='scf',
path='diamond/scf',
job=job(nodes=1, app='pw.x', hours=1),
input_type='generic',
calculation='scf',
nspin=2,
input_dft='lda',
ecutwfc=200,
conv_thr=1e-8,
nosym=True,
wf_collect=True,
system=dia2,
tot_magnetization=0,
pseudos=['C.BFD.upf'],
)
nscf = generate_pwscf(
identifier='nscf',
path='diamond/nscf',
job=job(nodes=1, app='pw.x', hours=1),
input_type='generic',
calculation='nscf',
input_dft='lda',
[ 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',
job = jobs['scf'],
input_type = 'generic',
calculation = 'scf',
input_dft = 'lda',
ecutwfc = 200,
conv_thr = 1e-8,
nosym = True,
wf_collect = True,
system = O2,
kgrid = (1,1,1),
pseudos = ['O.BFD.upf'],
)
run_project(scf)