code: def __init__(
      self,
      method,
      n_bins,
      split_pt_dict,
      bin_col,
      transform_method,
      category_col,
      error_rate,
      adjustment_factor,
  ):
      self.method = method
      self.n_bins = n_bins
      # cols to be binned
      self.bin_col = bin_col
      # cols to be treated as categorical feature
      self.category_col = category_col
      self.transform_method = transform_method
      self.relative_error = error_rate
      self.adjustment_factor = adjustment_factor
      self._manual_split_pt_dict = split_pt_dict
      # {col_name: [split_pts]}, ordered by split_pts
      self._split_pt_dict = None
      self._bin_idx_dict = None
      # {col_name: [bin_num]}, ordered by split_pts
      self._bin_count_dict = None
      # {col_name: [woe]}, ordered by split_pts, for transform
      self._woe_dict = None
      # for prediction transform
      self._train_woe_dict = None
      # {col_name: {"iv_array": [], "woe": [], "event_count": []...}}
      self._metrics_summary = None
      self._host_metrics_summary = None
      self._train_metrics_summary = None
      self._train_host_metrics_summary = None
  
imports: import logging
  import numpy
  import pandas
  from fate.arch import Context
  from fate.arch.histogram import HistogramBuilder
  from ..abc.module import HeteroModule, Module
label_desc: Use image node_id 1 to create a new StandardBinning object from inherited base classes: Module with example: obj = StandardBinning(method, n_bins, split_pt_dict, bin_col, transform_method, category_col, error_rate, adjustment_factor)