def fast_newton(mf,
mo_coeff=None,
mo_occ=None,
dm0=None,
auxbasis=None,
projectbasis=None,
**newton_kwargs):
'''Wrap function to quickly setup and call Newton solver.
Newton solver attributes [max_cycle_inner, max_stepsize, ah_start_tol,
ah_conv_tol, ah_grad_trust_region, ...] can be passed through **newton_kwargs.
'''
import copy
from pyscf.lib import logger
from pyscf import df
if auxbasis is None:
auxbasis = df.addons.aug_etb_for_dfbasis(mf.mol, 'ahlrichs', beta=2.5)
if projectbasis:
mf1 = newton(mf)
pmol = mf1.mol = newton_ah.project_mol(mf.mol, projectbasis)
mf1 = density_fit(mf1, auxbasis)
else:
mf1 = density_fit(newton(mf), auxbasis)
mf1.direct_scf_tol = 1e-7
if hasattr(mf, 'grids'):
from pyscf.dft import gen_grid
approx_grids = gen_grid.Grids(mf.mol)
approx_grids.verbose = 0
approx_grids.level = max(0, mf.grids.level - 2)
mf1.grids = approx_grids
approx_numint = copy.copy(mf._numint)
mf1._numint = approx_numint
for key in newton_kwargs:
setattr(mf1, key, newton_kwargs[key])
if mo_coeff is None or mo_occ is None:
mo_coeff, mo_occ = mf.mo_coeff, mf.mo_occ
if dm0 is not None:
mo_coeff, mo_occ = mf1.from_dm(dm0)
elif mo_coeff is None or mo_occ is None:
logger.note(
mf, '========================================================')
logger.note(
mf, 'Generating initial guess with DIIS-SCF for newton solver')
logger.note(
mf, '========================================================')
if projectbasis:
mf0 = copy.copy(mf)
mf0.mol = pmol
mf0 = density_fit(mf0, auxbasis)
else:
mf0 = density_fit(mf, auxbasis)
mf0.direct_scf_tol = 1e-7
mf0.conv_tol = 3.
mf0.conv_tol_grad = 1.
if mf0.level_shift == 0:
mf0.level_shift = .2
if hasattr(mf, 'grids'):
mf0.grids = approx_grids
mf0._numint = approx_numint
# Note: by setting small_rho_cutoff, dft.get_veff function may overwrite
# approx_grids and approx_numint. It will further changes the corresponding
# mf1 grids and _numint. If inital guess dm0 or mo_coeff/mo_occ were given,
# dft.get_veff are not executed so that more grid points may be found in
# approx_grids.
mf0.small_rho_cutoff = mf.small_rho_cutoff * 10
mf0.kernel()
mo_coeff, mo_occ = mf0.mo_coeff, mf0.mo_occ
if projectbasis:
if mo_occ.ndim == 2:
mo_coeff = (project_mo_nr2nr(pmol, mo_coeff[0], mf.mol),
project_mo_nr2nr(pmol, mo_coeff[1], mf.mol))
else:
mo_coeff = project_mo_nr2nr(pmol, mo_coeff, mf.mol)
mo_coeff, mo_occ = mf1.from_dm(mf.make_rdm1(mo_coeff, mo_occ))
logger.note(mf, '============================')
logger.note(mf, 'Generating initial guess end')
logger.note(mf, '============================')
mf1.kernel(mo_coeff, mo_occ)
mf.converged = mf1.converged
mf.e_tot = mf1.e_tot
mf.mo_energy = mf1.mo_energy
mf.mo_coeff = mf1.mo_coeff
mf.mo_occ = mf1.mo_occ
mf = copy.copy(mf)
def mf_kernel(*args, **kwargs):
logger.warn(
mf,
"fast_newton is a wrap function to quickly setup and call Newton solver. "
"There's no need to call kernel function again for fast_newton.")
del (mf.kernel) # warn once and remove circular depdence
return mf.e_tot
mf.kernel = mf_kernel
return mf
def fast_newton(mf, mo_coeff=None, mo_occ=None, dm0=None,
auxbasis=None, projectbasis=None, **newton_kwargs):
'''Wrap function to quickly setup and call Newton solver.
Newton solver attributes [max_cycle_inner, max_stepsize, ah_start_tol,
ah_conv_tol, ah_grad_trust_region, ...] can be passed through **newton_kwargs.
'''
import copy
from pyscf.lib import logger
from pyscf import df
if auxbasis is None:
auxbasis = df.addons.aug_etb_for_dfbasis(mf.mol, 'ahlrichs', beta=2.5)
if projectbasis:
mf1 = newton(mf)
pmol = mf1.mol = newton_ah.project_mol(mf.mol, projectbasis)
mf1 = density_fit(mf1, auxbasis)
else:
mf1 = density_fit(newton(mf), auxbasis)
mf1.direct_scf_tol = 1e-7
if hasattr(mf, 'grids'):
from pyscf.dft import gen_grid
approx_grids = gen_grid.Grids(mf.mol)
approx_grids.verbose = 0
approx_grids.level = 0
mf1.grids = approx_grids
approx_numint = copy.copy(mf._numint)
mf1._numint = approx_numint
for key in newton_kwargs:
setattr(mf1, key, newton_kwargs[key])
if mo_coeff is None or mo_occ is None:
mo_coeff, mo_occ = mf.mo_coeff, mf.mo_occ
if dm0 is not None:
mo_coeff, mo_occ = mf1.from_dm(dm0)
elif mo_coeff is None or mo_occ is None:
logger.note(mf, '========================================================')
logger.note(mf, 'Generating initial guess with DIIS-SCF for newton solver')
logger.note(mf, '========================================================')
if projectbasis:
mf0 = copy.copy(mf)
mf0.mol = pmol
mf0 = density_fit(mf0, auxbasis)
else:
mf0 = density_fit(mf, auxbasis)
mf0.direct_scf_tol = 1e-7
mf0.conv_tol = 3.
mf0.conv_tol_grad = 1.
if mf0.level_shift == 0:
mf0.level_shift = .2
if hasattr(mf, 'grids'):
mf0.grids = approx_grids
mf0._numint = approx_numint
# Note: by setting small_rho_cutoff, dft.get_veff function may overwrite
# approx_grids and approx_numint. It will further changes the corresponding
# mf1 grids and _numint. If inital guess dm0 or mo_coeff/mo_occ were given,
# dft.get_veff are not executed so that more grid points may be found in
# approx_grids.
mf0.small_rho_cutoff = 1e-5
mf0.kernel()
mo_coeff, mo_occ = mf0.mo_coeff, mf0.mo_occ
if projectbasis:
if mo_occ.ndim == 2:
mo_coeff =(project_mo_nr2nr(pmol, mo_coeff[0], mf.mol),
project_mo_nr2nr(pmol, mo_coeff[1], mf.mol))
else:
mo_coeff = project_mo_nr2nr(pmol, mo_coeff, mf.mol)
mo_coeff, mo_occ = mf1.from_dm(mf.make_rdm1(mo_coeff,mo_occ))
logger.note(mf, '============================')
logger.note(mf, 'Generating initial guess end')
logger.note(mf, '============================')
mf1.kernel(mo_coeff, mo_occ)
mf.converged = mf1.converged
mf.e_tot = mf1.e_tot
mf.mo_energy = mf1.mo_energy
mf.mo_coeff = mf1.mo_coeff
mf.mo_occ = mf1.mo_occ
def mf_kernel(*args, **kwargs):
logger.warn(mf, "fast_newton is a wrap function to quickly setup and call Newton solver. "
"There's no need to call kernel function again for fast_newton.")
del(mf.kernel) # warn once and remove circular depdence
return mf.e_tot
mf.kernel = mf_kernel
return mf