title: Python memory mapping
body: <p>I am working with big data and i have matrices with size like 2000x100000, so in order to to work faster i tried using the numpy.memmap to avoid storing in memory this large matrices due to the RAM limitations. The problem is that when i store the same matrix in 2 variables, i.e One with numpy.load and in the other with np.memmap, the contents are not the same. Is this normal? I am using the same data type in memmap as in my data. Example:</p>
  
  <pre><code>A1 = numpy.load('mydata.npy')
  A2 = numpy.memmap('mydata.npy',dtype=numpy.float64, mode='r', shape=(2000,2000))
  A1[0,0] = 0
  A2[0,0] = 1.8758506894003703e-309
  </code></pre>
  
  <p>That's the contents of the first element of the array in both cases. The correct one is the value 0 but i am getting this weird number by using the memmap. 
  Thank you.</p>