title: How to convert python list of points to numpy image array?
body: <p>I have a python list of points (x/y coordinates):</p>
  
  <pre><code>   [(200, 245), (344, 248), (125, 34), ...]
  </code></pre>
  
  <p>It represents a contour on a 2d plane. I would like to use some numpy/scipy algorithms for smoothing, interpolation etc. They normally require numpy array as input. For example <a href="http://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.interpolation.zoom.html" rel="noreferrer"><code>scipy.ndimage.interpolation.zoom</code></a>. </p>
  
  <p>What is the simplest way to get the right numpy array from my list of points?</p>
  
  <p><strong>EDIT:</strong> I added the word "image" to my question, hope it is clear now, I am really sorry, if it was somehow misleading. Example of what I meant (points to binary image array).</p>
  
  <p>Input: </p>
  
  <pre><code>[(0, 0), (2, 0), (2, 1)]
  </code></pre>
  
  <p>Output: </p>
  
  <pre><code>[[0, 0, 1],
   [1, 0, 1]]
  </code></pre>
  
  <p>Rounding the accepted answer here is the <strong>working sample</strong>:</p>
  
  <pre><code>import numpy as np
  
  coordinates = [(0, 0), (2, 0), (2, 1)]
  
  x, y = [i[0] for i in coordinates], [i[1] for i in coordinates]
  max_x, max_y = max(x), max(y)
  
  image = np.zeros((max_y + 1, max_x + 1))
  
  for i in range(len(coordinates)):
      image[max_y - y[i], x[i]] = 1
  </code></pre>