title: Python3 - Computationally efficient correlation between matrix and array
body: <p>I'd like to correlate the columns of an mxn matrix with a 1xm array. This should give me an 1xn array back. At the moment I am doing this a bit clumsy with:</p>
  
  <p><code>c = np.corrcoef(X, y)[:-1,-1]</code></p>
  
  <p>I find the correlations I want here in the last column and with the last row/column corresponding to the correlation the array have with it self (so r = 1.0).</p>
  
  <p>This is fine, but however, I need to do this on quite big matrices and that is  basically when it becomes too computationally heavy and my computer gives up. </p>
  
  <p><strong>For example the largest matrix I am doing this for has the size</strong>:</p>
  
  <p>48x290400 (= X) and 48x1 (=y), where I want to end up with 290400 r-values</p>
  
  <p>This works fine in Matlab, but not in python using np.corrcoef. Anyone got a good solution for this?</p>
  
  <p>Cheers
  Daniel</p>