docstr: This function checks whether the result summarisation option is correct given the inputs and explainer setup.
  
  Parameters
  ----------
  summarise_result, cat_vars_start_idx, cat_vars_enc_dim
      See :py:meth:`alibi.exapliners.shap_wrappers.TreeShap.explain` documentation.
code: def _check_result_summarisation(
      self,
      summarise_result: bool,
      cat_vars_start_idx: Sequence[int],
      cat_vars_enc_dim: Sequence[int],
  ):
      """
      This function checks whether the result summarisation option is correct given the inputs and explainer setup.
  
      Parameters
      ----------
      summarise_result, cat_vars_start_idx, cat_vars_enc_dim
          See :py:meth:`alibi.exapliners.shap_wrappers.TreeShap.explain` documentation.
      """
  
      self.summarise_result = summarise_result
      if not cat_vars_start_idx or not cat_vars_enc_dim:
          logger.warning(
              "Results cannot be summarised as either the"
              "start indices for categorical variables or"
              "the encoding dimensions were not passed!"
          )
          self.summarise_result = False
  
imports: import copy
  import logging
  from functools import partial
  from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
  import numpy
  import pandas
  import shap
  import shap.utils._legacy
  from scipy import sparse
  from scipy.special import expit
  from shap import KernelExplainer
  from alibi.api.defaults import DEFAULT_DATA_KERNEL_SHAP, DEFAULT_DATA_TREE_SHAP, DEFAULT_META_KERNEL_SHAP, DEFAULT_META_TREE_SHAP
  from alibi.api.interfaces import Explainer, Explanation, FitMixin
  from alibi.utils.wrappers import methdispatch
label_desc: Use image node_id 11 for calling the TreeShap obj's underlying member method code with example usage: obj._check_result_summarisation(summarise_result, cat_vars_start_idx, cat_vars_enc_dim) without return types