code: def gap_time_series_complicated_gaps_configuration():
      """
      Generate complicated case for time series gap filling. Array also contain
      np.nan values
      """
      ts = [
          -100.0,
          1,
          2,
          3,
          4,
          5,
          6,
          7,
          8,
          9,
          10,
          11,
          12,
          13,
          14,
          15,
          16,
          -100.0,
          np.nan,
          19,
          20,
          21,
          22,
          23,
          24,
          25,
          26,
          -100.0,
          28,
          29,
          30,
          31,
      ]
      return np.array(ts, dtype=float)
  
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 10 for calling a global function with example usage: gap_time_series_complicated_gaps_configuration() and returns: np