code: def features_normal_cov_toeplitz(
      n_samples: int = 200,
      n_features: int = 30,
      cov_corr: float = 0.5,
      dtype="float64",
  ):
      """Normal features generator with toeplitz covariance
  
      An example of features obtained as samples of a centered Gaussian
      vector with a toeplitz covariance matrix
  
      Parameters
      ----------
      n_samples : `int`, default=200
          Number of samples
  
      n_features : `int`, default=30
          Number of features
  
      cov_corr : `float`, default=0.5
          correlation coefficient of the Toeplitz correlation matrix
  
      dtype : `{'float64', 'float32'}`, default='float64'
          Type of the arrays used.
  
      Returns
      -------
      output : `numpy.ndarray`, shape=(n_samples, n_features)
          n_samples realization of a Gaussian vector with the described
          covariance
  
      """
      cov = toeplitz(cov_corr ** np.arange(0, n_features))
      features = np.random.multivariate_normal(
          np.zeros(n_features), cov, size=n_samples
      )
      if dtype != "float64":
          return features.astype(dtype)
      return features
  
imports: import numpy
  from scipy.linalg.special_matrices import toeplitz
label_desc: Use image node_id 2 for calling a global function with example usage: features_normal_cov_toeplitz(n_samples, n_features, cov_corr, dtype) and returns: features, features