code: def _parse_relational_arff(data):
      X_data = np.asarray(data[0])
      n_samples = len(X_data)
      X, y = [], []
  
      if X_data[0][0].dtype.names is None:
          for i in range(n_samples):
              X_sample = np.asarray(
                  [X_data[i][name] for name in X_data[i].dtype.names]
              )
              X.append(X_sample.T)
              y.append(X_data[i][1])
      else:
          for i in range(n_samples):
              X_sample = np.asarray(
                  [
                      X_data[i][0][name]
                      for name in X_data[i][0].dtype.names
                  ]
              )
              X.append(X_sample.T)
              y.append(X_data[i][1])
  
      X = np.asarray(X).astype("float64")
      y = np.asarray(y)
  
      try:
          y = y.astype("float64").astype("int64")
      except ValueError:
          y = y.astype(str)
  
      return X, y
  
file_path: pyts/pyts/datasets/uea.py
imports: import numpy
  import os
  import pickle
  from scipy.io.arff import loadarff
  from sklearn.utils import Bunch
  from urllib.request import urlretrieve
  import zipfile
label_desc: Use image node_id 6 for calling a global function with example usage: _parse_relational_arff(data) and returns: X,  y