title: numpy: efficiently reading a large array
body: <p>I have a binary file that contains a dense <code>n*m</code> matrix of 32-bit floats. What's the most efficient way to read it into a Fortran-ordered <code>numpy</code> array?</p>
  
  <p>The file is multi-gigabyte in size. I get to control the format, but it must be compact (i.e. about <code>4*n*m</code> bytes in length) and must be easy to produce from non-Python code.</p>
  
  <p><strong>edit</strong>: It is imperative that the method produces a Fortran-ordered matrix directly (due to the size of the data, I can't afford to create a C-ordered matrix and then transform it into a separate Fortran-ordered copy.)</p>