title: Points left out when nearby in scipy.spatial.Delaunay
body: <p>I am noticing an unexplained behaviour when comparing scipy's (0.9.0) and matplotlib's (1.0.1) Delaunay triangulation routines. My points are UTM coordinates stored in <code>numpy.array([[easting, northing], [easting, northing], [easting, northing]])</code>. Scipy's edges are missing some of my points, while matplotlib's are all there. Is there a fix, or am I doing something wrong?</p>
  
  <pre><code>import scipy
  import numpy
  from scipy.spatial import Delaunay
  import matplotlib.delaunay
  
  
  def delaunay_edges(points):
      d = scipy.spatial.Delaunay(points)
      s = d.vertices
      return numpy.vstack((s[:,:2], s[:,1:], s[:,::-2]))
  
  
  def delaunay_edges_matplotlib(points):
          cens, edges, tri, neig = matplotlib.delaunay.delaunay(points[:,0], points[:,1])
          return edges
  
  
  points = numpy.array([[500000.25, 6220000.25],[500000.5, 6220000.5],[500001.0, 6220001.0],[500002.0, 6220003.0],[500003.0, 6220005.0]])
  
  edges1 = delaunay_edges(points)
  edges2 = delaunay_edges_matplotlib(points)
  
  numpy.unique(edges1).shape # Some points missing, presumably nearby ones
  numpy.unique(edges2).shape # Includes all points
  </code></pre>