def test_pbc_wfs():
"""
Ensure that the wave function objects are consistent in several situations.
"""
from pyscf.pbc import lib, gto, scf
from pyqmc.supercell import get_supercell
from pyqmc.slater import Slater
from pyqmc.multiplywf import MultiplyWF
from pyqmc import default_jastrow
import pyqmc
mol = gto.M(
atom="H 0. 0. 0.; H 1. 1. 1.",
basis="sto-3g",
unit="bohr",
a=(np.ones((3, 3)) - np.eye(3)) * 4,
)
mf = scf.KRKS(mol, mol.make_kpts((2, 2, 2))).run()
# mf_rohf = scf.KROKS(mol).run()
# mf_uhf = scf.KUKS(mol).run()
epsilon = 1e-5
nconf = 10
supercell = get_supercell(mol, S=(np.ones((3, 3)) - 2 * np.eye(3)))
epos = pyqmc.initial_guess(supercell, nconf)
# For multislaterpbc
# kinds = 0, 3, 5, 6 # G, X, Y, Z
# d1 = {kind: [0] for kind in kinds}
# d2 = d1.copy()
# d2.update({0: [], 3: [0, 1]})
# detwt = [2 ** 0.5, 2 ** 0.5]
# occup = [[d1, d2], [d1]]
# map_dets = [[0, 1], [0, 0]]
for wf in [
MultiplyWF(Slater(supercell, mf), default_jastrow(supercell)[0]),
Slater(supercell, mf),
]:
for k in wf.parameters:
if "mo_coeff" not in k and k != "det_coeff":
wf.parameters[k] = np.random.rand(*wf.parameters[k].shape)
_, epos = pyqmc.vmc(wf, epos, nblocks=1, nsteps=2, tstep=1) # move off node
for fname, func in zip(
["gradient", "laplacian", "pgradient"],
[
testwf.test_wf_gradient,
testwf.test_wf_laplacian,
testwf.test_wf_pgradient,
],
):
err = []
for delta in [1e-4, 1e-5, 1e-6, 1e-7, 1e-8]:
err.append(func(wf, epos, delta))
print(type(wf), fname, min(err))
assert min(err) < epsilon
for k, item in testwf.test_updateinternals(wf, epos).items():
print(k, item)
assert item < epsilon
def test_pbc_wfs():
"""
Ensure that the wave function objects are consistent in several situations.
"""
from pyscf.pbc import lib, gto, scf
from pyqmc.slaterpbc import PySCFSlaterPBC, get_supercell
from pyqmc.jastrowspin import JastrowSpin
from pyqmc.multiplywf import MultiplyWF
from pyqmc.coord import OpenConfigs
import pyqmc
mol = gto.M(atom="H 0. 0. 0.; H 1. 1. 1.",
basis="sto-3g",
unit="bohr",
a=np.eye(3) * 4)
mf = scf.KRKS(mol).run()
# mf_rohf = scf.KROKS(mol).run()
# mf_uhf = scf.KUKS(mol).run()
epsilon = 1e-5
nconf = 10
supercell = get_supercell(mol, S=np.eye(3))
epos = pyqmc.initial_guess(supercell, nconf)
for wf in [
MultiplyWF(PySCFSlaterPBC(supercell, mf), JastrowSpin(mol)),
PySCFSlaterPBC(supercell, mf),
# PySCFSlaterPBC(supercell, mf_uhf),
# PySCFSlaterPBC(supercell, mf_rohf),
]:
for k in wf.parameters:
if k != "mo_coeff":
wf.parameters[k] = np.random.rand(*wf.parameters[k].shape)
for fname, func in zip(
["gradient", "laplacian", "pgradient"],
[
testwf.test_wf_gradient,
testwf.test_wf_laplacian,
testwf.test_wf_pgradient,
],
):
err = []
for delta in [1e-4, 1e-5, 1e-6, 1e-7, 1e-8]:
err.append(func(wf, epos, delta)[0])
print(fname, min(err))
assert min(err) < epsilon
for k, item in testwf.test_updateinternals(wf, epos).items():
print(k, item)
assert item < epsilon
def test_info_functions_pbc():
from pyscf.pbc import gto, scf
from pyqmc.supercell import get_supercell
mol = gto.Cell(atom="He 0.00 0.00 0.00",
basis="gth-szv",
pseudo="gth-pade",
unit="B")
mol.a = 5.61 * np.eye(3)
mol.build()
mf = scf.KRKS(mol, kpts=mol.make_kpts([2, 2, 2])) # .density_fit()
ehf = mf.kernel()
supercell = get_supercell(mol, 2 * np.eye(3))
kinds = [0, 1]
dm_orbs = [mf.mo_coeff[i][:, :2] for i in kinds]
wf, to_opt = pyqmc.default_sj(mol, mf)
accumulators = {
"pgrad": pyqmc.gradient_generator(mol, wf, to_opt, ewald_gmax=10),
"obdm": OBDMAccumulator(mol, dm_orbs, kpts=mf.kpts[kinds]),
"Sq": pyqmc.accumulators.SqAccumulator(mol.lattice_vectors()),
}
info_functions(mol, wf, accumulators)