code: def generate_data(nitem, nfeat=2, dim=10, labeldim=1, base='item'):
      
      import numpy as np
  
      # A list of item names
      items = [base + '_' + str(i) for i in range(nitem)]
  
      # A list of features arrays
      features = [np.random.randn(nfeat, dim) for _ in range(nitem)]
  
      # A list on 1D or 2D times arrays
      if labeldim == 1:
          labels = [np.linspace(0, 1, nfeat)] * nitem
      else:
          t = np.linspace(0, 1, nfeat)
          labels = [np.array([t+i for i in range(labeldim)])] * nitem
  
      # Format data as required by the writer
      return h5f.Data(items, labels, features, check=True)
docs: Returns a randomly generated h5f.Data instance.
  
      - nitem is the number of items to generate.
      - nfeat is the number of features to generate for each item.
      - dim is the dimension of the features vectors.
      - base is the items basename
      - labeldim is the dimension of the labels vectors.