title: Efficient slicing of matrices using matrix multiplication, with Python, NumPy, SciPy
body: <p>I want to reshape a 2d <code>scipy.sparse.csr.csr_matrix</code>(let us call it <code>A</code>) to a 2d <code>numpy.ndarray</code> (let us call this <code>B</code>).</p>
  
  <p><code>A</code> could be</p>
  
  <pre><code>&gt;shape(A)
  (90, 10)
  </code></pre>
  
  <p>then 
  <code>B</code> should be</p>
  
  <pre><code>&gt;shape(B)
  (9,10)
  </code></pre>
  
  <p>where each 10 rows of <code>A</code> would be reshaped in a new new value, namely the maximum of this window and column. The column operator is not working on this unhashable type of a sparse matrix. How can I get this <code>B</code> by using matrix multiplications?</p>