code: def test_data_merge_ts_different_forecast_lengths():
      output_short = get_output_timeseries(
          len_forecast=5, for_predict=True
      )
      output_long = get_output_timeseries(
          len_forecast=12, for_predict=True
      )
      outputs = [output_short, output_long]
  
      merged_data = DataMerger.get(outputs).merge()
  
      assert np.equal(merged_data.idx, output_short.idx).all()
      assert merged_data.features.shape == (
          output_short.predict.shape[0],
          2,
      )
  
file_path: FEDOT/test/unit/data/test_data_merge_ts.py
imports: from itertools import product
  import numpy
  import pytest
  from fedot.core.data.data import OutputData
  from fedot.core.data.merge.data_merger import DataMerger
  from fedot.core.pipelines.pipeline_builder import PipelineBuilder
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.utilities.synth_dataset_generator import generate_synthetic_data
  from test.unit.data_operations.test_data_operations_implementations import get_time_series
label_desc: Use image node_id 8 for calling a global function with example usage: test_data_merge_ts_different_forecast_lengths() without return types