title: interpolating 4D data
body: <p>I have a set of GPS stations, whose coordinates I know (x,y,z), and for each station, I also have an error (e). These stations are of course unevenly spaced, otherwise it would be too easy. The thing is, in order to compute my error e for a station, I have only used said station, but I also want to take the others into account.</p>
  
  <p>My problem is: given a set of unevenly spaced (x,y,z,e) points, how can I interpolate e in function of the spatial distance between points?
  The interpolation would need not to be exact, since I am recalculating e on points where I already have it.
  Also, I am looking for something cleaner than inverse distance or likewise stuff. Splines would be nice, for example.</p>
  
  <p>From what I have read, the splev function of the scipy.interpolate package seems to do the trick, but I cannot understand how it works or what I am supposed to give it as arguments.</p>
  
  <p>I someone could either explain how this is supposed to work, or point me to another method, it would be great.</p>