code: def test_linear_interpolation_correct(get_time_series: Callable):
      """Linear interpolation can fill in the gaps correctly even gaps are placed
      at the beginning or at the end of time series (and other cases)
      """
      gap_arr = get_time_series()
      simple_gapfill = SimpleGapFiller(gap_value=-100)
      without_gap_linear = simple_gapfill.linear_interpolation(gap_arr)
  
      assert len(np.ravel(np.argwhere(without_gap_linear == -100))) == 0
  
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 15 for calling a global function with example usage: test_linear_interpolation_correct(get_time_series) without return types