code: def sample(self, num_samples=1):
      samples = np.zeros([num_samples, len(self.types)], dtype=np.float)
  
      if self.fully_dimensional:
          sample_indices = np.random.choice(
              self.data.shape[0], size=num_samples
          )
  
      else:
          sample_indices = None
  
      for i, k in enumerate(self.kernels):
          samples[:, i] = k.sample(sample_indices, num_samples)
  
      return samples
  
file_path: auptimizer/src/aup/Proposer/hpbandster/optimizers/kde/mvkde.py
imports: import numpy
  import scipy.optimize
  import ConfigSpace
  from hpbandster.optimizers.kde.kernels import Gaussian, AitchisonAitken, WangRyzinOrdinal, WangRyzinInteger
label_desc: Use image node_id 9 for calling the MultivariateKDE obj's underlying member method code with example usage: obj.sample(num_samples) and returns: samples