title: numpy dtype ValueError: invalid shape in fixed-type tuple - how can I get around it?
body: <p>I use a custom datatype, e.g. <code>datatype = np.dtype('({:n},{:n})f4'.format(10000,100000))</code> to read data from a binary file using </p>
  
  <pre><code>np.fromfile(filename, dtype=datatype)
  </code></pre>
  
  <p>However, defining the datatype using np.dtype gives an error for large datasets, as in the example datatype above:</p>
  
  <pre><code>ValueError: invalid shape in fixed-type tuple: dtype size in bytes must fit into a C int
  </code></pre>
  
  <p>Initializing an array of that size is no problem: <code>a=np.zeros((10000,100000))</code>.
  So my question is: Where does that limitation come from and how can I get around it? I can of course use a loop and read chunks at a time, but maybe there is a more elegant way?</p>