code: def test_kind_tsfresh_extractor():
      """Test extractor returns an array of expected num of cols."""
      X, y = load_arrow_head(return_X_y=True)
      X_train, X_test, y_train, y_test = train_test_split(X, y)
      features_to_calc = [
          "dim_0__quantile__q_0.6",
          "dim_0__longest_strike_above_mean",
          "dim_0__variance",
      ]
      ts_custom = TSFreshFeatureExtractor(
          kind_to_fc_parameters=features_to_calc,
          disable_progressbar=True,
      )
      Xts_custom = ts_custom.fit_transform(X_train)
      assert Xts_custom.shape[1] == len(features_to_calc)
  
file_path: sktime/sktime/transformations/panel/tests/test_tsfresh.py
imports: import numpy
  import pytest
  from sklearn.model_selection import train_test_split
  from sktime.datasets import load_arrow_head
  from sktime.datatypes import convert
  from sktime.tests.test_switch import run_test_for_class
  from sktime.transformations.panel.tsfresh import TSFreshFeatureExtractor
  from sktime.utils._testing.panel import make_classification_problem
label_desc: Use image node_id 3 for calling a global function with example usage: test_kind_tsfresh_extractor() without return types