title: python compare each point of two correlation matrix
body: <p>I have n observation of m variables for two different groups.
  I created two correlation matrices using np.corrcoeff (normalized correlation coefficients), one for each group. </p>
  
  <p>I end up with 2 n X n matrices. Each square of the matrices being a mean correlation coefficient for a given group. </p>
  
  <p>Then I want to compare those two matrices. 
  Is there a python function to do this ? 
  I would like to: 
  - compare both matrices just to know if there is differences between them (overall)
  - compare each square of the matrices and end up with a correlation matrix     showing the significant differences between both matrices  </p>
  
  <p>For the second point, I would like to do a t-test or an anova (to include additional confounding factors). The problem is that my correlation matrix are already mean so I would need to use the formula (and the standard deviation). </p>
  
  <p>Is there an easy way to do this ? </p>