Gradient of 2D splines on irregular grid


I’m looking to (1) interpolate data where the x-axis is a log-spaced grid, the y-axis is a regular spaced grid and there is an array A(x,y) recording the function values in each point; and (2) take the gradient of the resulting interpolated function.

I’ve been looking at different packages, e.g. Dierckx and Interpolations. But Dierckx doesn’t support gradients above 1 dimension and Interpolations only support linear interpolations for irregular grids, and hence the derivatives will not be well-defined.

Is there a different package that will let me do the above?

Thanks alot.

You could use a (smoothing) interpolation on a sufficiently fine numerical grid (e.g. GitHub - gher-uliege/DIVAnd.jl: DIVAnd performs an n-dimensional variational analysis of arbitrarily located observations) and then just perform a simple finite difference on this high-resolution grid.


In other words, x = \exp(z) where z = \log(x) is on a regularly spaced grid? So then you can use a method for a regular grid in z,y to interpolate the function B(z,y), from which you can compute A(x,y) = B(e^z, y) and hence \nabla A = ((1/x) \partial B/\partial z, \partial B/\partial y).

Alternatively, whenever your data is on a product of two grids, even if the grids are irregular, you can do a sequence of two 1d interpolations

  1. for each x value construct an interpolant in the y coordinate.
  2. you now have a sequence of interpolation coefficients c (at each x) — interpolate these in the x grid to get an interpolated coefficient c(x).
  3. for any arbitrary (x,y), first interpolate the coefficients c(x) at this x, then use those interpolated coefficients to evaluate at y.
  4. For an a