code: def make_toy_2d_problem():
      """Make a toy classification problem out of numpy arrays."""
      X_train_class1 = np.random.uniform(-1, 1, size=(20, 100))
      y_train_class1 = np.zeros(
          20,
      )
      X_train_class2 = np.random.uniform(-0.9, 1.1, size=(20, 100))
      y_train_class2 = np.ones(
          20,
      )
      X_train = np.concatenate((X_train_class1, X_train_class2), axis=0)
      y_train = np.concatenate((y_train_class1, y_train_class2))
  
      X_test_class1 = np.random.uniform(-1, 1, size=(20, 100))
      y_test_class1 = np.zeros(
          20,
      )
      X_test_class2 = np.random.uniform(-0.9, 1.1, size=(20, 100))
      y_test_class2 = np.ones(
          20,
      )
      X_test = np.concatenate((X_test_class1, X_test_class2), axis=0)
      y_test = np.concatenate((y_test_class1, y_test_class2))
      return X_train, y_train, X_test, y_test
  
file_path: sktime/sktime/_contrib/classification_examples.py
imports: import numpy
  import pandas
  from sklearn.ensemble import RandomForestClassifier
  from sktime.classification.dictionary_based import BOSSEnsemble, ContractableBOSS
  from sktime.datasets import load_unit_test
label_desc: Use image node_id 2 for calling a global function with example usage: make_toy_2d_problem() and returns: X_train,  y_train,  X_test,  y_test