Displaying 4 results from an estimated 4 matches for "smoothscattercalcdensity".
2015 Feb 18
0
smoothScatter() and the KernSmooth package
...gc=yeastGC[sub])))
>
> MDPlot(data,c(1,3))
Error in loadNamespace(name) : there is no package called ?KernSmooth?
Calls: MDPlot ... tryCatch -> tryCatchList -> tryCatchOne -> <Anonymous>
Execution halted
I looked at the code in smoothScatter and there is a call to
grDevices:::.smoothScatterCalcDensity(), which in turn calls
KernSmooth::bkde2D().
This gets fixed by adding KernSmooth as suggested package in EDASeq.
I was able to reproduce this issue (and the fix) in a small R package:
https://github.com/drisso/rmini/tree/smooth
I have a few questions: isn't it unusual the way smoothScatter...
2010 Feb 06
1
Why does smoothScatter clip when xlim and ylim increased?
Hi:
Is there a way to get smoothScatter to not clip when I increase the xlim and
ylim parameters?
Consider the following example:
set.seed(17)
x1<-rnorm(100)
x2<-rnorm(100)
smoothScatter(x1,x2)
#Now if I increase xlim and ylim notice that the plot seems to be clipped at
the former xlim, and ylim boundaries:
smoothScatter(x1,x2, xlim=c(-5,5), ylim=c(-5,5))
Thanks.
Jen
sessionInfo()
R
2009 Apr 22
1
reversing xlim, ylim in smoothScatter
....R in the lines :
x <- x[ xlim[1] <= x[,1] & x[,1] <=xlim[2], ] (line number 25)
and
x <- x[ ylim[1] <= x[,2] & x[,2] <= ylim[2], ] (line number 31)
This results in a x being NA if ylim[1] > ylim[2] which results in an error on executing
map <- grDevices:::.smoothScatterCalcDensity(x, nbin, bandwidth)
To counter this problem, I replaced the above two lines by :
x <-x [min(xlim) <= x[,1] & x[,1] <= max(xlim), ]
and
x <- x[min(ylim) <= x[,2] & x[,2] <= max(ylim), ]
and now smoothscatter reverses axes properly if xlim and/or ylim are provided with r...
2010 Apr 19
1
densCols: what are the computed densities and how to create a legend
Hi,
I'm using the densCols function for a scatterplot and cannot figure out 1) how to extract the computed densities, and 2) how to create a legend based that represents the upper and lower ranges of the densities.
For example:
movers.den <- densCols(move$x, move$y)
table(movers.den)
#08306B #083775 #083B7C #083D7E #3989C1 #3F8FC4
28 22 101 25