code: def test_get_array_with_gaps():
      """
      Checking whether omissions with the correct values are generated in
      the right places
      """
      for gap_dict, gap_value in zip(
          [{10: 10}, {50: 20}], [-10.0, -100.0]
      ):
          arr_with_gaps, _ = get_array_with_gaps(gap_dict, gap_value)
  
          start_gaps = list(gap_dict.keys())
          index_to_check = start_gaps[0]
  
          assert arr_with_gaps[index_to_check] == gap_value
  
imports: import numpy
  import pytest
  from sklearn.metrics import mean_squared_error
  from typing import Callable
  from examples.simple.time_series_forecasting.gapfilling import get_array_with_gaps
  from fedot.utilities.ts_gapfilling import ModelGapFiller, SimpleGapFiller
  from test.unit.tasks.test_forecasting import get_simple_ts_pipeline
label_desc: Use image node_id 11 for calling a global function with example usage: test_get_array_with_gaps() without return types