title: What is the faster way to find the maximum along axis on a symetrical matrix in numpy
body: <p>Suppose I have a symetrical numpy array as follows:</p>
  <pre class="lang-py prettyprint-override"><code>import numpy as np
  
  N = 10000
  b = np.random.random_integers(-2000,2000,size=(N,N))
  b_symm = (b + b.T)/2
  </code></pre>
  <p>what is the most efficient algorithm to find the maximum for each row ? (like np.amax(axis=1))</p>