title: How to add matrix and vector column-wise?
body: <p>Consider the following:</p>
  
  <pre><code>&gt;&gt;&gt; matrix = numpy.array([[1, 2, 3],
  ...                       [4, 5, 6],
  ...                       [7, 8, 9]])
  &gt;&gt;&gt; vector = numpy.array([10, 20, 30])
  &gt;&gt;&gt; matrix + vector
  array([[11, 22, 33],
         [14, 25, 36],
         [17, 28, 39]])
  </code></pre>
  
  <p>This adds the vector and the matrix <em>row-wise</em> (i.e. each row being added the vector).</p>
  
  <p>How to perform the same <em>column-wise</em>? The result should be</p>
  
  <pre><code>&gt;&gt;&gt; ???
  array([[11, 12, 13],
         [24, 25, 26],
         [37, 38, 39]])
  </code></pre>
  
  <p>I'm aware that I can use</p>
  
  <pre><code>&gt;&gt;&gt; (matrix.T + vector).T
  array([[11, 12, 13],
         [24, 25, 26],
         [37, 38, 39]])
  </code></pre>
  
  <p>However I have many such additions and using this double transposition will make the code quite unreadable. Is there a way to configure ndarrays such that they will perform addition along the first axis (instead of the last)?</p>