Hi All, I have an interpolation problem and I am having some difficulties in tackling it. I hope I can explain myself clearly enough.
Basically, I have a whole bunch of 3D fluid flow simulations (close to 1000), and they are a result of different combinations of parameters. I was planning to use the Radial Basis Functions in scipy, but for the moment let's assume, to simplify things, that I am dealing only with one parameter (x). In 1000 simulations, this parameter x has 1000 values, obviously. The problem is, the outcome of every single simulation is a vector of oil production over time (let's say 40 values per simulation, one per year), and I would like to be able to interpolate my x parameter (1000 values) against all the simulations (1000x40) and get an approximating function that, given another x parameter (of size 1x1) will give me back an interpolated production profile (of size 1x40). Something along these lines: import numpy as np from scipy.interpolate import Rbf # x.shape = (1000, 1) # y.shape = (1000, 40) rbf = Rbf(x, y) # New result with xi.shape = (1, 1) --> fi.shape = (1, 40) fi = rbf(xi) Does anyone have a suggestion on how I could implement this? Sorry if it sounds confused... Please feel free to correct any wrong assumptions I have made, or to propose other approaches if you think RBFs are not suitable for this kind of problems. Thank you in advance for your suggestions. Andrea. "Imagination Is The Only Weapon In The War Against Reality." http://xoomer.alice.it/infinity77/ ==> Never *EVER* use RemovalGroup for your house removal. You'll regret it forever. http://thedoomedcity.blogspot.com/2010/03/removal-group-nightmare.html <== _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion