title: TypeError when indexing numpy array using numba
body: <p>I need to sum up elements in a 1D <code>numpy</code> array (below: <code>data</code>) based on another array with information on class memberships (<code>labels</code>). I use <code>numba</code>in the code below to speed it up. However, If I dot not explicitly cast with <code>int()</code> in the line <code>ret[int(find(labels, g))] += y</code>, I reveice an error message:</p>
  
  <p><code>TypeError: unsupported array index type ?int64</code></p>
  
  <p>Is there a better workaround that explicit casting?</p>
  
  <pre><code>import numpy as np
  from numba import jit
  
  labels = np.array([45, 85, 99, 89, 45, 86, 348, 764])
  n = int(1e3)
  data = np.random.random(n)
  groups = np.random.choice(a=labels, size=n, replace=True)
  
  @jit(nopython=True)
  def find(seq, value):
      for ct, x in enumerate(seq):
          if x == value:
              return ct
  
  @jit(nopython=True)
  def subsumNumba(data, groups, labels):
      ret = np.zeros(len(labels))
      for y, g in zip(data, groups):
          # not working without casting with int()
          ret[int(find(labels, g))] += y
      return ret
  </code></pre>