title: Efficient way of taking Logarithm function in a sparse matrix
body: <p>I have a big sparse matrix. I want to take <code>log4</code> for all element in that sparse matrix. </p>
  
  <p>I try to use <code>numpy.log()</code> but it doesn't work with matrices. </p>
  
  <p>I can also take logarithm row by row. Then I crush old row with a new one.</p>
  
  <pre><code># Assume A is a sparse matrix (Linked List Format) with float values as data
  # It is only for one row
  
  import numpy as np
  c = np.log(A.getrow(0)) / numpy.log(4)
  A[0, :] = c
  </code></pre>
  
  <p>This was not as quick as I'd expected. Is there a faster way to do this? </p>