similar to: reversing xlim, ylim in smoothScatter

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

Hi, I have been trying to plot density plots using the example on: http://addictedtor.free.fr/graphiques/graphcode.php?graph=139 I used to use this function, but I cannot get any old code or even the example to work. library("geneplotter") require("RColorBrewer") x1 <- matrix(rnorm(1e4), ncol=2) x2 <- matrix(rnorm(1e4, mean=3, sd=1.5), ncol=2) x <-

Hello, I'm having some trouble getting a good result for a smoothScatter plot. I have some data that I want to log-plot, but when I use smoothScatter the result is not correct. The problem seems to be that with the log="x" argument smoothScatter calculates the bins linearly, so the plot will be skewed towards the right. See for example:

Dear R-devel, my Bioconductor EDASeq package has a function MDPlot that uses the smoothScatter() function from the graphics package. When I test this package on travis-ci.org (R CMD check) I get the following error (which I don't get on my machine nor on the Bioconductor build system). * checking examples ... ERROR Running examples in ?EDASeq-Ex.R? failed The error most likely occurred in:

Hello, I have a few questions, regarding the smoothScatter function. I have a scatter plot with more than 500,000 data points for two samples. So, I am wanting to display the density in colors to convince people that my good correlation coefficient is not due to an "influential point effect" and plus, I also want to make my scatter plot look pretty. Anyway ... I have been able to

Hello, I am attempting to use smoothScatter to plot a heatmap of locations of events in an x-y axis. When I plot the heatmap without passing xlim and ylim parameters, it fills the plot area but the perspective is a bit skewed. I would like to standardize these plots to a uniform window size that does not depend on the range of values in the dataframe. However, when I resize the plot using xlim or

Hi, I want to make a plot similar to sm1 (attached). The code I tried is: dcols <- densCols(x,y) smoothScatter(x,y, col = dcols, pch=20,xlab="A",ylab="B") abline(h=0, col="red") But it turned out to be s1 (attached) with big dots. I was wondering if anything wrong with my code. Thanks,Zhengyu -------------- next part -------------- A non-text

On Tue, 18-Dec-2007 at 11:21AM -0500, James W. MacDonald wrote: |> Duncan Murdoch wrote: |> > Yes, I agree. (As an aside, there's actually a capital S in |> > smoothScatter(), and it's a bit of a pain to install, because |> > geneplotter depends on something that depends on DBI, which is not so |> > easily available these days.) |> |> Somehow I always

Dear all, I am using the smoothScatter function in base R for a plot - Lab.palette.both <- colorRampPalette(c("darkblue","lightblue","red","yellow"), space = "Lab") smoothScatter(X24fresh.sorted[,c(13,10)], colramp = Lab.palette.both) I understand that my yellow colored points represent highest density, red lower, lightblue even lower etc.

Hello everybody, I'm here with a question concerning obtaining a greographical map with a smmothed scatterplot overlaying the intersted regions. My data are a set of opints, represented by long, lat coordinates. As far as the map is concerned, a shp file of Europe without countries borders (only coastal outlines) with the limits at lat 35N-60N long 15W-30E. Until now, I was only able to

I'm working with a large dataset - large enough that when I do a scatter plot the points all blur together, so I want to plot their density by color - a heat map or something like that. I've used smoothScatter for tasks like this, but the problem is that my current dataset really only looks good on a log-log scale. When I do the following command smoothScatter( data,

Hello R help list I have been using the smoothScatter function within the "geneplotter" package to make some graphs using a Sweave Rnw script called via Rscript in a DOS/Windows batch file. The Rscript will ultimately be called by a web service with time-out constraints, hence things need to run as swiftly as possible. The geneplotter package is currently loaded each time R is invoked

Hello everybody, I'm trying to understand how to draw a smoothed scatterplot on a geographic map with R. Have a dataframe with point locations (long, lat) and was able to simply plot these points on a shp map by using the maptools package. However, instead of having simply the raw points on the map, I would like to have a "smoothed" scatterplot of the same superimposed on the map.

Dear R users, I like to plot a matrix A which looks like this: ,1 ,2 ,3 ,4 1, 1 10 100 1000 2, 0.5 0.2 1.0 4.3 3, 0.1 0.2 0.3 0.5 ..... where the 1st row is representing the X-axis values. The subsequent rows should be plotted on the y-axis. I would prefer to use the smoothScatter plotting function of the geneplotter package, but to begin with R I'd be happy to use

Dear listers, After activating the name space for my bioconductor package (prada) I successfully ran R CMD check. However when loading the package in R and running the examples the imported function brewer.pal from package RColorBrewer is not found. I can directly call brewer.pal from the RColorBrewer name space typing RColorBrewer::brewer.pal, but it is not imported into my prada name space. When

Dear listers, After activating the name space for my bioconductor package (prada) I successfully ran R CMD check. However when loading the package in R and running the examples the imported function brewer.pal from package RColorBrewer is not found. I can directly call brewer.pal from the RColorBrewer name space typing RColorBrewer::brewer.pal, but it is not imported into my prada name space. When

 Dear Madame or Sir,I am having a problem in combining density-smoothed scatterplot matrices with a plot of kernel destiny estimations of each dimension plotted on the respective field of the diagonal.I have tried following approach using the package "sm" for the kernel density estimation, as well as "MASS" respectively:pairs(myTable[, 1:4],panel=function(x,y, ...){

dear all, I am writing a sweave documentation for my analysis, and I am plotting huge scatter plot data for microarray. unlucly this take a lot of resource to my pc because of the quality of the image which is to high (I see the PC get stuck for each single spot). how can I overcome this problem? is there a way to make lighter image? john [[alternative HTML version deleted]]

Dear all, I am running something similar to this short example: library("lattice") library("geneplotter") X=matrix(cbind(1:100,100:1,c(1:50,50:1)),ncol=3) Y=matrix(cbind(1:100,1:100,1:100),ncol=3) names=1:3 dummy.df = data.frame(names = factor(names, levels = names), x = seq_along(names), y = seq_along(names)) xyplot(y ~ x | names, dummy.df, xlim = c(1,100),

Hello UseRs, I need help on how to plot several raster images (such as those obtained from a kernel-smoothed intensity function) in a layout such as that obtained from the lattice package. I would like to obtain something such as obtained from using the "levelplot" or "xyplot" in lattice. I currently use: >par(mfrow=c(3,3) to set the workspace, but the resulting plots