docstr: Unit test check_consistency_postprocessing
code: def test_check_postprocessing_1(self):
      """
      Unit test check_consistency_postprocessing
      """
      x = pd.DataFrame(
          [[1, 2], [3, 4]],
          columns=["Col1", "Col2"],
          index=["Id1", "Id2"],
      )
      columns_dict = {0: "Col1", 1: "Col2"}
      features_types = {
          features: str(x[features].dtypes) for features in x.columns
      }
      postprocessing1 = {0: {"Error": "suffix", "rule": " t"}}
      postprocessing2 = {0: {"type": "Error", "rule": " t"}}
      postprocessing3 = {0: {"type": "suffix", "Error": " t"}}
      postprocessing4 = {0: {"type": "suffix", "rule": " "}}
      postprocessing5 = {0: {"type": "case", "rule": "lower"}}
      postprocessing6 = {0: {"type": "case", "rule": "Error"}}
      with self.assertRaises(ValueError):
          check_postprocessing(features_types, postprocessing1)
          check_postprocessing(features_types, postprocessing2)
          check_postprocessing(features_types, postprocessing3)
          check_postprocessing(features_types, postprocessing4)
          check_postprocessing(features_types, postprocessing5)
          check_postprocessing(features_types, postprocessing6)
  
imports: import unittest
  import pytest
  import pandas
  import numpy
  import category_encoders
  from shapash.utils.check import check_preprocessing, check_model, check_label_dict, check_mask_params, check_y, check_contribution_object, check_preprocessing_options, check_postprocessing, check_consistency_model_features, check_consistency_model_label, check_additional_data
  from sklearn.compose import ColumnTransformer
  import sklearn.preprocessing
  import types
  import sklearn.ensemble
  import sklearn.svm
  import sklearn.linear_model
  import xgboost
  import lightgbm
  import catboost
label_desc: Use image node_id 24 for calling the TestCheck obj's underlying member method code with example usage: obj.test_check_postprocessing_1() without return types