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())