title: Mayavi How to do Delaunay Triangulation with xz data instead of xy data
body: <p>I am trying to plot some experimental data and I am facing a problem with the triangulation as explained more lengthily <a href="https://stackoverflow.com/questions/20979274/bad-automatic-triangulation-with-mayavi-for-coloring-a-surface-known-only-by-its">here</a>. I figure out that the solution might be to change the grid from a xy to xz one and use the y as the elevation. </p>
  
  <p>Howevever I haven't information about such possibility. So is there a way to do so, maybe by using some masks or some filters to just invert the y and z columns for the triangulation?</p>
  
  <p>Here is a basic code:</p>
  
  <pre><code>import numpy
  from mayavi import mlab
  
  X2 = numpy.array([0, 0, 1, 1])
  Y2 = numpy.array([0.5, 0.45, 1, 0.5])
  Z2 = numpy.array([0, 1, 0.5,0])
  
  fig = mlab.figure(1, bgcolor=(1, 1, 1), fgcolor=(0.5, 0.5, 0.5))
  # Define the points in 3D space
  # including color code based on Z coordinate.
  pts = mlab.points3d(X2, Y2, Z2, Y2, colormap='jet')
  # Triangulate based on X, Y with Delaunay 2D algorithm.
  # Save resulting triangulation.
  mesh = mlab.pipeline.delaunay2d(pts)
  # Remove the point representation from the plot
  pts.remove()
  # Draw a surface based on the triangulation
  surf = mlab.pipeline.surface(mesh, colormap='jet')
  
  # Simple plot.
  mlab.outline(extent=(0,1,0,1,0,1))
  mlab.axes(extent=(0,1,0,1,0,1))
  mlab.show()
  </code></pre>