title: Scikit-learn train_test_split with indices
body: <p>How do I get the original indices of the data when using train_test_split()?</p>
  
  <p>What I have is the following</p>
  
  <pre><code>from sklearn.cross_validation import train_test_split
  import numpy as np
  data = np.reshape(np.randn(20),(10,2)) # 10 training examples
  labels = np.random.randint(2, size=10) # 10 labels
  x1, x2, y1, y2 = train_test_split(data, labels, size=0.2)
  </code></pre>
  
  <p>But this does not give the indices of the original data. 
  One workaround is to add the indices to data (e.g. <code>data = [(i, d) for i, d in enumerate(data)]</code>) and then pass them inside <code>train_test_split</code> and then expand again. 
  Are there any cleaner solutions?</p>