title: Numpy structured array fails basic numpy operations
body: <p>I wish to manipulate <strong>named</strong> numpy arrays (add, multiply, concatenate, ...)</p>
  
  <p>I defined structured arrays:</p>
  
  <pre><code>types=[('name1', int), ('name2', float)]
  a = np.array([2, 3.3], dtype=types)
  b = np.array([4, 5.35], dtype=types)
  </code></pre>
  
  <p>a and b are created such that</p>
  
  <pre><code>a
  array([(2, 2. ), (3, 3.3)], dtype=[('name1', '&lt;i8'), ('name2', '&lt;f8')])
  </code></pre>
  
  <p>but I really want <code>a['name1']</code> to be just 2, not <code>array([2, 3])</code></p>
  
  <p>Similarly, I want <code>a['name2']</code> to be just 3.3</p>
  
  <p>This way I could sum <code>c=a+b</code>, which is expected to be an array of length 2, where <code>c['name1']</code> is 6 and <code>c['name2']</code> is 8.65</p>
  
  <p>How can I do that? </p>