code: def test_data_convert_dt_indexes_correct():
      """Test is datetime indexes converted correctly.
      Pipeline is needed to save last indexes of train part"""
      train_data, test_data = get_ts_data_with_dt_idx()
      train_pred_data = deepcopy(train_data)
      # old non int indexes
      old_train_data_idx = copy(train_data.idx)
      old_train_pred_data_idx = copy(train_pred_data.idx)
      old_test_data_idx = copy(test_data.idx)
      # pipeline object need to save last_fit_idx
      dummy_pipeline = Pipeline(PipelineNode("сut"))
      train_data = train_data.convert_non_int_indexes_for_fit(
          dummy_pipeline
      )
      train_pred_data = (
          train_pred_data.convert_non_int_indexes_for_predict(
              dummy_pipeline
          )
      )
      test_data = test_data.convert_non_int_indexes_for_predict(
          dummy_pipeline
      )
      # check is new integer indexes correct (now we know order of indexes)
      assert train_data.idx[-1] == train_pred_data.idx[-1]
      assert train_data.idx[-1] == test_data.idx[0] - 1
      # check is non integer indexes equal
      assert np.all(
          train_data.supplementary_data.non_int_idx
          == old_train_data_idx
      )
      assert np.all(
          train_pred_data.supplementary_data.non_int_idx
          == old_train_pred_data_idx
      )
      assert np.all(
          test_data.supplementary_data.non_int_idx == old_test_data_idx
      )
  
imports: import os
  from copy import deepcopy, copy
  import numpy
  import pandas
  import pytest
  from sklearn.datasets import load_iris
  from fedot.core.data.data import InputData, get_df_from_csv
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.core.utils import fedot_project_root
  from test.unit.tasks.test_forecasting import get_ts_data_with_dt_idx
label_desc: Use image node_id 10 for calling a global function with example usage: test_data_convert_dt_indexes_correct() without return types