def __init__(self, cell, kpts=numpy.zeros((1, 3))):
self.cell = cell
self.stdout = cell.stdout
self.verbose = cell.verbose
self.max_memory = cell.max_memory
self.kpts = kpts # default is gamma point
self.kpts_band = None
self.auxbasis = None
if cell.dimension == 0:
self.eta = 0.2
self.gs = cell.gs
else:
ke_cutoff = tools.gs_to_cutoff(cell.lattice_vectors(), cell.gs)
ke_cutoff = ke_cutoff[:cell.dimension].min()
self.eta = min(
aft.estimate_eta_for_ke_cutoff(cell, ke_cutoff,
cell.precision),
estimate_eta(cell, cell.precision))
ke_cutoff = aft.estimate_ke_cutoff_for_eta(cell, self.eta,
cell.precision)
self.gs = tools.cutoff_to_gs(cell.lattice_vectors(), ke_cutoff)
self.gs[cell.dimension:] = cell.gs[cell.dimension:]
# Not input options
self.exxdiv = None # to mimic KRHF/KUHF object in function get_coulG
self.auxcell = None
self.blockdim = 240
self.linear_dep_threshold = LINEAR_DEP_THR
self._j_only = False
# If _cderi_to_save is specified, the 3C-integral tensor will be saved in this file.
self._cderi_to_save = tempfile.NamedTemporaryFile(dir=lib.param.TMPDIR)
# If _cderi is specified, the 3C-integral tensor will be read from this file
self._cderi = None
self._keys = set(self.__dict__.keys())
def __init__(self, cell, kpts=numpy.zeros((1, 3))):
self.cell = cell
self.stdout = cell.stdout
self.verbose = cell.verbose
self.max_memory = cell.max_memory
self.kpts = kpts # default is gamma point
self.kpts_band = None
self._auxbasis = None
# Search for optimized eta and mesh here.
if cell.dimension == 0:
self.eta = 0.2
self.mesh = cell.mesh
else:
ke_cutoff = tools.mesh_to_cutoff(cell.lattice_vectors(), cell.mesh)
ke_cutoff = ke_cutoff[:cell.dimension].min()
eta_cell = aft.estimate_eta_for_ke_cutoff(cell, ke_cutoff,
cell.precision)
eta_guess = estimate_eta(cell, cell.precision)
if eta_cell < eta_guess:
self.eta = eta_cell
# TODO? Round off mesh to the nearest odd numbers.
# Odd number of grids is preferred because even number of
# grids may break the conjugation symmetry between the
# k-points k and -k.
#?self.mesh = [(n//2)*2+1 for n in cell.mesh]
self.mesh = cell.mesh
else:
self.eta = eta_guess
ke_cutoff = aft.estimate_ke_cutoff_for_eta(
cell, self.eta, cell.precision)
self.mesh = tools.cutoff_to_mesh(cell.lattice_vectors(),
ke_cutoff)
if cell.dimension < 2 or cell.low_dim_ft_type == 'inf_vacuum':
self.mesh[cell.dimension:] = cell.mesh[cell.dimension:]
# exp_to_discard to remove diffused fitting functions. The diffused
# fitting functions may cause linear dependency in DF metric. Removing
# the fitting functions whose exponents are smaller than exp_to_discard
# can improve the linear dependency issue. However, this parameter
# affects the quality of the auxiliary basis. The default value of
# this parameter was set to 0.2 in v1.5.1 or older and was changed to
# 0 since v1.5.2.
self.exp_to_discard = cell.exp_to_discard
# The following attributes are not input options.
self.exxdiv = None # to mimic KRHF/KUHF object in function get_coulG
self.auxcell = None
self.blockdim = getattr(__config__, 'pbc_df_df_DF_blockdim', 240)
self.linear_dep_threshold = LINEAR_DEP_THR
self._j_only = False
# If _cderi_to_save is specified, the 3C-integral tensor will be saved in this file.
self._cderi_to_save = tempfile.NamedTemporaryFile(dir=lib.param.TMPDIR)
# If _cderi is specified, the 3C-integral tensor will be read from this file
self._cderi = None
self._keys = set(self.__dict__.keys())
def __init__(self, cell, kpts=numpy.zeros((1,3))):
self.cell = cell
self.stdout = cell.stdout
self.verbose = cell.verbose
self.max_memory = cell.max_memory
self.kpts = kpts # default is gamma point
self.kpts_band = None
self._auxbasis = None
# Search for optimized eta and mesh here.
if cell.dimension == 0:
self.eta = 0.2
self.mesh = cell.mesh
else:
ke_cutoff = tools.mesh_to_cutoff(cell.lattice_vectors(), cell.mesh)
ke_cutoff = ke_cutoff[:cell.dimension].min()
eta_cell = aft.estimate_eta_for_ke_cutoff(cell, ke_cutoff, cell.precision)
eta_guess = estimate_eta(cell, cell.precision)
if eta_cell < eta_guess:
self.eta = eta_cell
# TODO? Round off mesh to the nearest odd numbers.
# Odd number of grids is preferred because even number of
# grids may break the conjugation symmetry between the
# k-points k and -k.
#?self.mesh = [(n//2)*2+1 for n in cell.mesh]
self.mesh = cell.mesh
else:
self.eta = eta_guess
ke_cutoff = aft.estimate_ke_cutoff_for_eta(cell, self.eta, cell.precision)
self.mesh = tools.cutoff_to_mesh(cell.lattice_vectors(), ke_cutoff)
if cell.dimension < 2 or cell.low_dim_ft_type == 'inf_vacuum':
self.mesh[cell.dimension:] = cell.mesh[cell.dimension:]
# exp_to_discard to remove diffused fitting functions. The diffused
# fitting functions may cause linear dependency in DF metric. Removing
# the fitting functions whose exponents are smaller than exp_to_discard
# can improve the linear dependency issue. However, this parameter
# affects the quality of the auxiliary basis. The default value of
# this parameter was set to 0.2 in v1.5.1 or older and was changed to
# 0 since v1.5.2.
self.exp_to_discard = cell.exp_to_discard
# The following attributes are not input options.
self.exxdiv = None # to mimic KRHF/KUHF object in function get_coulG
self.auxcell = None
self.blockdim = getattr(__config__, 'pbc_df_df_DF_blockdim', 240)
self.linear_dep_threshold = LINEAR_DEP_THR
self._j_only = False
# If _cderi_to_save is specified, the 3C-integral tensor will be saved in this file.
self._cderi_to_save = tempfile.NamedTemporaryFile(dir=lib.param.TMPDIR)
# If _cderi is specified, the 3C-integral tensor will be read from this file
self._cderi = None
self._keys = set(self.__dict__.keys())
def __init__(self, cell, kpts=numpy.zeros((1, 3))):
self.cell = cell
self.stdout = cell.stdout
self.verbose = cell.verbose
self.max_memory = cell.max_memory
self.kpts = kpts # default is gamma point
self.kpts_band = None
self.gs = cell.gs
self.auxbasis = None
self.eta = estimate_eta(cell, cell.precision)
# Not input options
self.exxdiv = None # to mimic KRHF/KUHF object in function get_coulG
self.auxcell = None
self.blockdim = 256
self._j_only = False
self._cderi_file = tempfile.NamedTemporaryFile(dir=lib.param.TMPDIR)
self._cderi = None
self._keys = set(self.__dict__.keys())
