title: Augmenting a matrix in Python using numpy
body: <p>I'm trying to augment a matrix to solve an equation, yet have been unable to. And yes, I saw the "Augment a matrix in NumPy" question; it is not what I need.</p>
  
  <p>So my problem: create an augmented matrix [ A <strong>b1</strong> <strong>b2</strong> ]</p>
  
  <pre><code>import numpy
  a = numpy.array([[1,2],[5,12]])
  b1 = numpy.array([-1,3]).T
  b2 = numpy.array([1,-5]).T
  </code></pre>
  
  <p>I've tried the numpy.concatenate function, returns </p>
  
  <blockquote>
    <p>ValueError: all the input arrays must have same number of dimensions</p>
  </blockquote>
  
  <p>Is there a way to augment the matrix, such that I have one array of</p>
  
  <blockquote>
    <p>[ 1 2 -1  1</p>
    
    <p>5 12 3 -5 ]</p>
  </blockquote>
  
  <p>If anyone knows, please inform me! Note that I was doing this in the IPython notebook</p>
  
  <p>(btw, I know that I can't row reduce it with Numpy, it's a university problem, and just was doing the rest in IPython)</p>
  
  <p>Thanks
  Matt</p>