code: def test_ts_from_array():
      df = pd.read_csv(
          fedot_project_root().joinpath(
              "test/data/simple_sea_level.csv"
          )
      )
      train_array = np.array(df["Level"])
  
      task = Task(
          TaskTypesEnum.ts_forecasting,
          TsForecastingParams(forecast_length=250),
      )
      data = ApiDataProcessor(task).define_data(
          features=train_array, target="target"
      )
      assert np.array_equal(data.target, data.features)
  
file_path: FEDOT/test/unit/api/test_main_api.py
imports: import numpy
  import pandas
  import pytest
  from fedot import Fedot
  from fedot.api.api_utils.api_data import ApiDataProcessor
  from fedot.core.data.data import InputData
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.core.utils import fedot_project_root
  from test.data.datasets import data_with_binary_features_and_categorical_target, get_dataset, load_categorical_multidata, get_split_data_paths, get_split_data, get_multimodal_ts_data, load_categorical_unimodal
label_desc: Use image node_id 8 for calling a global function with example usage: test_ts_from_array() without return types