code: def test_feature_selection_of_single_features():
      for task_type in [
          TaskTypesEnum.classification,
          TaskTypesEnum.regression,
      ]:
          model_names = OperationTypesRepository(
              operation_type="data_operation"
          ).suitable_operation(
              tags=["feature_selection"], task_type=task_type
          )
  
          task = Task(task_type)
  
          for data_operation in model_names:
              node_data_operation = PipelineNode(data_operation)
  
              assert node_data_operation.fitted_operation is None
  
              # Fit and predict for pipeline
              train_input = get_single_feature_data(task)
              node_data_operation.fit(train_input)
              predicted_output = node_data_operation.predict(
                  train_input
              )
              predicted = predicted_output.predict
  
              assert node_data_operation.fitted_operation is not None
              assert predicted.shape == train_input.features.shape
  
imports: import os
  import numpy
  import pytest
  from examples.simple.classification.classification_with_tuning import get_classification_dataset
  from examples.simple.regression.regression_with_tuning import get_regression_dataset
  from examples.simple.time_series_forecasting.gapfilling import generate_synthetic_data
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.data.supplementary_data import SupplementaryData
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_imbalanced_class import ResampleImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_transformations import ImputationImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.ts_transformations import CutImplementation, LaggedTransformationImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.operation_types_repository import OperationTypesRepository
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.preprocessing.data_types import TYPE_TO_ID
  from test.unit.preprocessing.test_preprocessing_through_api import data_with_only_categorical_features
label_desc: Use image node_id 19 for calling a global function with example usage: test_feature_selection_of_single_features() without return types