parameters: (self, 
                   model_name : str, 
                   model_charge_map : List[float],
                   sys_charge_map : List[float], 
                   ewald_h : float = 1, 
                   ewald_beta : float = 1
      )
docstring: Constructor
docstring_summary: Constructor
docstring_tokens: Constructor
function: def __init__(self, 
                   model_name : str, 
                   model_charge_map : List[float],
                   sys_charge_map : List[float], 
                   ewald_h : float = 1, 
                   ewald_beta : float = 1
      ) -> None:
          """
          Constructor 
          """
          # the dipole model is loaded with prefix 'dipole_charge'
          self.modifier_prefix = 'dipole_charge'
          # init dipole model
          DeepDipole.__init__(self, 
                              model_name, 
                              load_prefix = self.modifier_prefix, 
                              default_tf_graph = True)
          self.model_name = model_name
          self.model_charge_map = model_charge_map
          self.sys_charge_map = sys_charge_map
          self.sel_type = list(self.get_sel_type())
          # init ewald recp
          self.ewald_h = ewald_h
          self.ewald_beta = ewald_beta
          self.er = EwaldRecp(self.ewald_h, self.ewald_beta)
          # dimension of dipole
          self.ext_dim = 3
          self.t_ndesc  = self.graph.get_tensor_by_name(os.path.join(self.modifier_prefix, 'descrpt_attr/ndescrpt:0'))
          self.t_sela  = self.graph.get_tensor_by_name(os.path.join(self.modifier_prefix, 'descrpt_attr/sel:0'))
          [self.ndescrpt, self.sel_a] = run_sess(self.sess, [self.t_ndesc, self.t_sela])
          self.sel_r = [ 0 for ii in range(len(self.sel_a)) ]
          self.nnei_a = np.cumsum(self.sel_a)[-1]
          self.nnei_r = np.cumsum(self.sel_r)[-1]
          self.nnei = self.nnei_a + self.nnei_r
          self.ndescrpt_a = self.nnei_a * 4
          self.ndescrpt_r = self.nnei_r * 1
          assert(self.ndescrpt == self.ndescrpt_a + self.ndescrpt_r)
          self.force = None
          self.ntypes = len(self.sel_a)
function_tokens: def __init__ ( self , model_name : str , model_charge_map : List [ float ] , sys_charge_map : List [ float ] , ewald_h : float = 1 , ewald_beta : float = 1 ) -> None : # the dipole model is loaded with prefix 'dipole_charge' self . modifier_prefix = 'dipole_charge' # init dipole model DeepDipole . __init__ ( self , model_name , load_prefix = self . modifier_prefix , default_tf_graph = True ) self . model_name = model_name self . model_charge_map = model_charge_map self . sys_charge_map = sys_charge_map self . sel_type = list ( self . get_sel_type ( ) ) # init ewald recp self . ewald_h = ewald_h self . ewald_beta = ewald_beta self . er = EwaldRecp ( self . ewald_h , self . ewald_beta ) # dimension of dipole self . ext_dim = 3 self . t_ndesc = self . graph . get_tensor_by_name ( os . path . join ( self . modifier_prefix , 'descrpt_attr/ndescrpt:0' ) ) self . t_sela = self . graph . get_tensor_by_name ( os . path . join ( self . modifier_prefix , 'descrpt_attr/sel:0' ) ) [ self . ndescrpt , self . sel_a ] = run_sess ( self . sess , [ self . t_ndesc , self . t_sela ] ) self . sel_r = [ 0 for ii in range ( len ( self . sel_a ) ) ] self . nnei_a = np . cumsum ( self . sel_a ) [ - 1 ] self . nnei_r = np . cumsum ( self . sel_r ) [ - 1 ] self . nnei = self . nnei_a + self . nnei_r self . ndescrpt_a = self . nnei_a * 4 self . ndescrpt_r = self . nnei_r * 1 assert ( self . ndescrpt == self . ndescrpt_a + self . ndescrpt_r ) self . force = None self . ntypes = len ( self . sel_a )