title: Speedup scipy griddata for multiple interpolations between two irregular grids
body: <p>I have several values that are defined on the same irregular grid <code>(x, y, z)</code> that I want to interpolate onto a new grid <code>(x1, y1, z1)</code>. i.e., I have <code>f(x, y, z), g(x, y, z), h(x, y, z)</code> and I want to calculate <code>f(x1, y1, z1), g(x1, y1, z1), h(x1, y1, z1)</code>. </p>
  
  <p>At the moment I am doing this using <code>scipy.interpolate.griddata</code> and it works well. However, because I have to perform each interpolation separately and there are many points, it is quite slow, with a great deal of duplication in the calculation (i.e finding which points are closest, setting up the grids etc...).</p>
  
  <p>Is there a way to speedup the calculation and reduce the duplicated calculations? i.e something along the lines of defining the two grids, then changing the values for the interpolation?</p>