I believe both ApproXD.jl and Dierckx.jl need Julia 0.3, while Julia Studio is still stuck on 0.2. That is why you can't install them. Until Julia Studio gets updated to 0.3 you might be better off using something like IJulia or Juno.
On Friday, November 7, 2014 7:48:41 PM UTC+2, ewing...@gmail.com wrote: > > I'm new to Julia as of this week :-) I'm working through some old > homework problems as a way to learn the language. > > I've gotten stuck on splines. I don't want the even-spacing limitation of > Grid.jl (though the problem I'm working on *does* have even spacing!), and > I can't figure out how to use BSplines.jl. ApproXD.jl and Dierckx.jl don't > show up in the package list in Julia Studio, nor does the Splines.jl > package mentioned in this thread, so I don't know how to install them. > > I like what I can see of BSplines.jl, but there is essentially zero > documentation. From the newbie perspective, giving documentation (a few > examples) would seem the easiest solution. Can someone help me on this? > > In my particular case, I end up with 2 vectors: > lRe=[0.0,1.0,2.0,3.0,4.0,5.0] # log10 of Reynolds numbers > > Cd=[0.04,0.28,0.73,0.74,0.64,0.61] # corresponding coeff of discharge > > > Other parts of the code work out successively changing Reynolds number; > then I need to interpolate to get a coefficient of discharge. Shouldn't be > difficult, but a few hours with BSplines.jl didn't get me there :-( > > Any suggestions? > many thanks, > Toby > > > On Wednesday, October 29, 2014 9:50:29 AM UTC-5, Peter Simon wrote: >> >> Also, check out ApproXD.jl <https://github.com/floswald/ApproXD.jl> which >> is designed for efficient high dimensional interpolation. >> >> --Peter >> >> On Wednesday, October 29, 2014 5:32:07 AM UTC-7, Tim Holy wrote: >>> >>> Grid should be able to do this. Best is to try it and see how it works >>> out. >>> >>> --Tim >>> >>> On Wednesday, October 29, 2014 04:03:19 AM Nils Gudat wrote: >>> > Since we seem to have a lot of experts on interpolation in Julia in >>> this >>> > thread, can I just ask a general question: I'm trying to interpolate >>> values >>> > of a function for which I only know the values at some gridpoints in >>> six >>> > dimensions. What would be the best way to do this given that I need >>> the >>> > interpolation to be fast, as I have to interpolate millions of times? >>> > >>> > I realize that this is a fairly general question, but I'd appreciate >>> any >>> > pointers as to what the interpolation capabilities of Julia are! >>> > >>> > Thanks, >>> > Nils >>> >>>