code: def gap_time_series_first_gap_enough_length():
      """
      First element in array is a gap but time series length enough for model
      training
      """
      ts = [-100.0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
      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 1 for calling a global function with example usage: gap_time_series_first_gap_enough_length() and returns: np