Probably the wrong place to post this, but I couldn't find a julia-diff list :)
I'm having stability issues computing the derivative of functions I only know on (non-uniform) grids. For example, I have a grid of x (I can't choose this) and the associated values of y = f(x). I've tried a few different things: - using different kinds of finite difference schemes - Fitting the data with many types of approximating functions (interpolating cubic B-splines, chebyshev polynomials, smoothing cubic splines, shape preserving quadratic hermite polynomial splines, ect.) For one of the functions I have this (x, y) data for, I also happen to have data on the first derivative of y. All the methods I've tried do terribly at approximating this derivative. I'm looking for a more reliable alternative, even if it is expensive to compute. Do any of the differentiation experts here have any suggestions or good references I can look to for how I might achieve better stability in this situation? I'm happy to code up a new algorithm we haven't implemented yet if someone knows about one. Thanks! On Thursday, June 26, 2014 at 12:26:52 AM UTC-4, Miles Lubin wrote: > > This is still a work in progress, but ahead of JuliaCon I'd like to > announce JuliaDiff, a github organization and website ( > http://www.juliadiff.org/) for packages related to computing derivatives. > This includes packages based on automatic differentiation. If you've never > heard of AD, check out the intro paragraph on the website. This is a field > where I believe the technical features of Julia really make it easier than > ever before to implement advanced techniques efficiently and (mostly) > transparently to the user, see, for example, the autodiff keyword in Optim > which enables computation of exact gradients of user-provided "black box" > functions. I'm looking forward to continued development, collaboration, and > contributions to JuliaDiff. Thanks to Theodore Papamarkou for the impetus > in creating this organization. > > Miles > > P.S. We're accepting logo submissions. >
