code: def test_check_subspace_points(self):
      # 1D array
      np.testing.assert_equal(
          [True], check_subspace_points(np.array([0.5, 0.5]))
      )
      bounds_cont_base = np.array([0.0, 1.0])
      X_cont = np.array([[0.5, 0.8], [-0.2, 0.2], [-0.7, 0.3]])
      np.testing.assert_equal(
          check_subspace_points(X_cont), [True] * len(X_cont)
      )
      cont_dims = np.arange(X_cont.shape[-1])
  
      with self.assertRaises(ValueError):
          # bounds_cont missing
          check_subspace_points(X_cont, cont_dims=cont_dims)
  
      with self.assertRaises(ValueError):
          # bounds_cont does not match
          check_subspace_points(
              X_cont, cont_dims=cont_dims, bounds_cont=bounds_cont_base
          )
  
      bounds_cont = np.tile(bounds_cont_base, [X_cont.shape[-1], 1])
  
      np.testing.assert_equal(
          check_subspace_points(
              X_cont, cont_dims=cont_dims, bounds_cont=bounds_cont
          ),
          [True, False, False],
      )
      np.testing.assert_equal(
          check_subspace_points(
              X_cont,
              cont_dims=cont_dims,
              bounds_cont=bounds_cont,
              expand_bound=True,
          ),
          [True, True, False],
      )
  
      # categorical hps
      X_cat = np.array([[0, 1], [2, 1], [1, 4]])
      cat_dims = np.arange(X_cat.shape[-1])
  
      bounds_cat = [(0, 2), (1, 4)]
  
      with self.assertRaises(ValueError):
          # bounds_cont missing
          check_subspace_points(X_cat, cat_dims=cat_dims)
  
      with self.assertRaises(ValueError):
          # bounds_cat doe not match
          check_subspace_points(
              X_cat, cat_dims=cat_dims, bounds_cat=[(0, 1)]
          )
  
      np.testing.assert_equal(
          check_subspace_points(
              X_cat, cat_dims=cat_dims, bounds_cat=bounds_cat
          ),
          [True, True, False],
      )
  
      # cat + cont
      X_mix = np.hstack([X_cont, X_cat])
      cat_dims += len(cont_dims)
      ss_mix = check_subspace_points(
          X_mix,
          cont_dims=cont_dims,
          cat_dims=cat_dims,
          bounds_cont=bounds_cont,
          bounds_cat=bounds_cat,
      )
      np.testing.assert_equal(ss_mix, [True, False, False])
  
imports: import unittest
  import numpy
  from ConfigSpace import ConfigurationSpace, EqualsCondition
  from ConfigSpace.hyperparameters import CategoricalHyperparameter, Constant, OrdinalHyperparameter, UniformFloatHyperparameter, UniformIntegerHyperparameter
  from smac.model.utils import check_subspace_points, get_types
label_desc: Use image node_id 1 for calling a global function with example usage: test_check_subspace_points() without return types