On Dec 5, 2013, at 4:02 PM, Jun Shen wrote: > Thanks again, Duncan. Please allow me to ask one more question. Is it > possible to generate a contour plot overlaying with the plot3d() plot? >
This is not going to give you the kewl rotation capabilities that `rgl` offers but you might be interested in the potential of the 'plot3d' package from Karline Soetaert of NIOZ-Yerseke, The Netherlands. (She also is also part of the team that gave us the very nice ODE package, 'deSolve' and co-wrote the accompanying book. I found it interesting to read that she is a biologist, while co-authors are mathematicians.) http://cran.rstudio.com/web/packages/plot3D/vignettes/plot3D.pdf See Figures 2 and 8 http://cran.rstudio.com/web/packages/plot3D/vignettes/volcano.pdf The second one has the catchy title: "Fifty ways to draw a volcano using package plot3D" You may find that the examples that drew the 4 examples in Figure 7 would give you something useful. > Jun > > > On Thu, Dec 5, 2013 at 11:08 AM, Duncan Murdoch > <murdoch.dun...@gmail.com>wrote: > >> On 05/12/2013 10:33 AM, Jun Shen wrote: >> >>> Hi Federico/Duncan/David/Bert, >>> >>> Thank you for your thoughtful comments and it's a great learning >>> experience. I can see the critical point here is to find a right function >>> to make the prediction. So I was thinking to start with "loess". However >>> the predict.loess gave me an error as follows >>> >>> Error in `$<-.data.frame`(`*tmp*`, "z", value = c(0.417071766265867, >>> 0.433916401753023, : >>> replacement has 20 rows, data has 400 >>> >>> Here is the code I tried. Thank you for your help again! >>> >>> Jun >>> ===================================== >>> >>> x<-runif(20) >>> y<-runif(20) >>> z<-runif(20) >>> >>> library(rgl) >>> plot3d(x,y,z) >>> >>> loess(z~x+y,control=loess.control(surface='direct'), >>> span=.5,degree=2)->fit.loess >>> >>> xnew <- seq(min(x), max(x), len=20) >>> ynew <- seq(min(y), max(y), len=20) >>> >>> df <- expand.grid(x = xnew, y = ynew) >>> >>> df$z<-predict(fit.loess,newdata=df) >>> >> >> After the error, use traceback() to find which function called >> `$<-.data.frame`. It shows that it was your final assignment >> >> df$z<-predict(fit.loess,newdata=df) >> >> >> which causes the error, because the predict function returns a matrix. So >> you can get the plot using >> >> surface3d(xnew, ynew, predict(fit.loess,newdata=df), col="gray") >> >> You may want >> >> aspect3d(1,1,1) >> >> afterwards; loess isn't so good at extrapolation. Or you may want to set >> predictions to NA outside the convex hull of your data. (I'm not sure >> which function is easiest to calculate that, but here's one way: >> >> hullx <- x[chull(x,y)] >> hully <- y[chull(x,y)] >> keep <- sp::point.in.polygon(df$x, df$y, hullx, hully) >> znew <- predict(fit.loess,newdata=df) >> znew[!keep] <- NA >> plot3d(x,y,z) >> surface3d(xnew, ynew, znew, col="gray") >> aspect3d(1,1,1) >> >> >> David Winsemius Alameda, CA, USA ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
