title: hierarchical clustering on correlations in Python scipy/numpy?
body: <p>How can I run hierarchical clustering on a correlation matrix in <code>scipy</code>/<code>numpy</code>?  I have a matrix of 100 rows by 9 columns, and I'd like to hierarchically cluster by correlations of each entry across the 9 conditions.  I'd like to use 1-pearson correlation as the distances for clustering.  Assuming I have a <code>numpy</code> array <code>X</code> that contains the 100 x 9 matrix, how can I do this?</p>
  
  <p>I tried using hcluster, based on this example:</p>
  
  <pre><code>Y=pdist(X, 'seuclidean')
  Z=linkage(Y, 'single')
  dendrogram(Z, color_threshold=0)
  </code></pre>
  
  <p>However, <code>pdist</code> is not what I want, since that's a euclidean distance.  Any ideas?</p>
  
  <p>thanks.</p>