[R] tcltk command to figure out which widget is on focus (or clicked)
Hi, I'm making an interface, where a Tcl/Tk window have few listbox widgets. I need to select separate parameters from separate listboxes. It is clear how to get cursor selection value, once you know which listbox widget you clicked. The problem is I can't figure out which one tcltk command to use to get an information which listbox widget is in focus (or clicked). Thank you, Vlad __ R-help@stat.math.ethz.ch 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.
[R] tcltk command to figure out which widget in active or in focus
Hi, I'm making an interface, where a Tcl/Tk window have few listbox widgets. I need to select separate parameters from separate listboxes. It is clear how to get cursor selection value, once you know which listbox widget you clicked. The problem is I can't figure out which one tcltk command to use to get an information which listbox widget I clicked. Thank you, Vlad __ R-help@stat.math.ethz.ch 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.
[R] running median and smoothing splines for robust surface fitting
Hi, Are there any multidimenstional versions of runmed() and smooth.spline() functions? I need to fit surface into quite noisy 3D data. Below is an example (2D) of kind of fittings I do. Thank you, Vlad #=generating complex x,y dataset with gaussian uniform noise== x - seq(1:1) x2 - rep(NA,2*length(x)) y2 - rep(NA,2*length(x)) x2[seq(1,length(x2),2)] - x x2[seq(2,length(x2),2)] - x y2[seq(1,length(x2),2)] - sin(4*pi*x/length(x)) + rnorm(length(x)) y2[seq(2,length(x2),2)] - runif(length(x),min=-5,max=5) #=== #=robust smooth fit=== y3 - runmed(y2,51,endrule=median) #first round of running median y4 - smooth.spline(x2,y3,df=10) #second round of smoothing splines #=== #=ploting data== plot(x2,y2,pch=19,cex=0.1) points(x2,y3,col=red,pch=19,cex=0.1) #running median points(y4,col=green,pch=19,cex=0.1) #smoothing splines #=== __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
