code: def test_gap_filling_ts_with_no_gaps():
      """If array doesn't contain gaps, algorithm should return source array"""
      no_gap_arr = np.array([1, 1, 2, 3, 4, -50, 6, 7, 8])
  
      simple_gapfill = SimpleGapFiller(gap_value=-100)
      without_gap = simple_gapfill.local_poly_approximation(no_gap_arr)
  
      assert tuple(without_gap) == tuple(no_gap_arr)
  
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 12 for calling a global function with example usage: test_gap_filling_ts_with_no_gaps() without return types