Zachary Pincus <zachary.pincus <at> yale.edu> writes:
scipy.ndimage.map_coordinates() performs b-spline interpolation of regularly-spaced data
my data are pairs of numbers, like complex numbers. I can't see a way of processing them.
(spline order 0-5, with several options for boundary conditions). The syntax can seem a bit tricky at first, and you need to watch out for ringing artifacts at sharp transitions (as these are interpolating splines), but it should do the trick.
Zach
Thanks, Zach, but I tried all the routines in interpolate, ndimage and signal, and all of these only seem to use use one-dimensional values. Using the routines in ndimage, I can easily have a 3D array of floats and interpolate at arbitrary 3D coordinates, but this is not what I want. I want multidimensional values, not coordinates. My coordinates are plain 2D x,y coordinates, but the values defined over them are pairs of numbers. My data would look something like: (V1,V2) (V1,V2) .... (V1,V2) (V1,V2) (V1,V2) .... (V1,V2) ... (V1,V2) (V1,V2) .... (V1,V2) (a 2D matrix of pairs) I'd expect a spline coefficient matrix of the same shape (C1,C2) (C1,C2) ... (C1,C2) (C1,C2) (C1,C2) ... (C1,C2) ... (C1,C2) (C1,C2) ... (C1,C2) and, when interpolating at (x,y) I'd like a result (I0,I1) (a single pair) Kay