title: Numpy: Generate multiple random samples from parameter arrays
body: <p>I have three parameter arrays, each containing n parameter values. Now I need to draw m independent samples using the same parameter settings, and I was wondering if there is an efficient way of doing this?</p>
  
  <p>Example:</p>
  
  <pre><code>p1 = [1, 2, 3, 4], p2 = [4,4,4,4], p3 = [6,7,7,5]
  </code></pre>
  
  <p>One sample would be generated as:</p>
  
  <pre><code>np.random.triangular(left=p1, mode=p2, right=p3)
  </code></pre>
  
  <p>resulting in</p>
  
  <pre><code>[3, 6, 3, 4.5]
  </code></pre>
  
  <p>But I would like to get m of those, in a single ndarray ideally.</p>
  
  <p>A solution could of course be to initiate a sample ndarray of size [n, m] and fill each column using a loop. However, generating all random values simultaneously is generally quicker, hence I would like to figure out if that's possible.</p>
  
  <p>NOTE:
  adding the parameter 'size=(n,m)' does not work for array valued parameter values</p>