code: def calculate_target_value(
      self, model_type, grid, feat_types, cls_idx
  ):
      def get_onehot_value(j):
          return np.argmax(
              grid[: self.data_gen.DUMMY_ONEHOT_LENGTH]
              if j == 0
              else grid[-self.data_gen.DUMMY_ONEHOT_LENGTH :]
          )
  
      def get_value(j, feat_type, is_regression=True):
          if is_regression:
              if feat_type == "onehot":
                  return get_onehot_value(j)
              else:
                  return grid[j] if j == 0 else grid[-j]
          else:
              if feat_type == "onehot":
                  return (
                      get_onehot_value(j) + 1
                  ) / self.data_gen.DUMMY_ONEHOT_LENGTH
              else:
                  return 1
  
      if model_type == "regression":
          target_value = sum(
              [
                  get_value(j, feat_type)
                  for j, feat_type in enumerate(feat_types)
              ]
          )
      else:
          pos_value = np.prod(
              [
                  get_value(j, feat_type, is_regression=False)
                  for j, feat_type in enumerate(feat_types)
              ]
          )
          if model_type == "binary":
              target_value = pos_value
          else:
              target_value = (
                  pos_value
                  if cls_idx == 0
                  else (1 - pos_value)
                  / (self.data_gen.DUMMY_MULTI_CLASSES - 1)
              )
  
      return target_value
  
imports: import numpy
  import pytest
  import copy
  from abc import abstractmethod
  from pdpbox.pdp import PDPResult, PDPIsolate, PDPInteract
  from pdpbox.utils import FeatureInfo, _make_list
  from conftest import DummyModel, PlotTestBase
label_desc: Use image node_id 3 for calling the TestPDPInteract obj's underlying member method code with example usage: obj.calculate_target_value(model_type, grid, feat_types, cls_idx) and returns: target_value, np, get_onehot_value, unknown, unknown, int