[SciPy-User] another interpolation question

[Pauli Virtanen]

On Thu, 17 Feb 2011 13:51:55 -0500, Bryan Woods wrote:

> Yes.
> 
> The idea is that I am using a nested model where I have an outer domain
> with fixed latitude / longitude coordinates and I want to downscale the
> data from that outer domain onto a finer inner domain which is contained
> inside of the outer domain.
> 
> All the interpolation that I see seeing is to interpolate randomly
> spaced data onto a fixed grid. I am looking to reproject data from and
> to fixed grids. Ideally a function that looks something like:
> 
> z_fine[x_fine|:,y_fine|:] = interp2d(x[:], y[:], z[x|:,y|:], x_fine[:],
> y_fine[:])

Yes, we have something like this, but apparently it isn't listed in the 
docs (aargh!).

Try

# some random data
from numpy import *
x = linspace(0, 1, 20)
y = linspace(0, 3, 30)
z = sin(x)[:,None] * cos(y)[None,:]
x_fine = linspace(0, 1, 200)
y_fine = linspace(0, 3, 140)

from scipy.interpolate import RectBivariateSpline
interp = RectBivariateSpline(x, y, z)
z_fine	= interp(x_fine, y_fine)