3d density plot

Hi Nabeil,

I'm not sure I understand what you'd like to accomplish, but perhaps
the following will be helpful:

example(kde2d, package='MASS')


hth,

Kingsford Jones

Dear all.



I am new to R so I am probably asking something that will be sneered at.




I am moving 100 "particles" in both x,y dimensions and would like to
plot the density of particles at each Cartesian coordinate.



I can simply use:



plot(density(positionX)

plot(density(positionY)



to produce the relevant density of particles at either an X or a Y
point, however how would it be possible to overlay the densities so that
I obtain a density at a particular coordinate.



An mock example of what I am currently doing is



posX ? ?<- matrix (nrow=101,ncol=100,data=0)

posY ? ? <- matrix (nrow=101,ncol=100,data=0)



posX[1,]<-50

posY[1,]<-40



for (j in 1:100) {

posX[j+1,]<- posX[j,]+(runif(100)-0.5)

posY[j+1,]<- posY[j,]+(runif(100)-0.5)



}



matplot(posX,posY,type="l")

plot(density((posY[,j])))

plot(density((posX[,j])))



Simply I would like to know the density of particles at coordinates of
the matplot.

From the example given the density of particles at 50,40 will be higher

than at the edges. But to quantifiably see this would be an advantage.





Any help?



I hope that is understandable.



Many thanks


? ? ? ?[[alternative HTML version deleted]]

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Here is a solution using ggplot2 

Positions <- expand.grid(Run = seq_len(100), ID = seq_len(101))
Positions$X <- runif(nrow(Positions), -.5, .5)
Positions$Y <- runif(nrow(Positions), -.5, .5)
Positions[Positions$ID == 1, c("X", "Y")] <- Positions[Positions$ID == 1, c("X", "Y")] + matrix(c(50, 40), ncol = 2, nrow = 100, byrow = TRUE)
library(plyr)
Positions <- ddply(Positions, "Run", function(x){
	x <- x[order(x$ID), ]
	x$X <- cumsum(x$X)
	x$Y <- cumsum(x$Y)
	x
})
library(ggplot2)
ggplot(Positions, aes(x = X, y = Y)) + geom_density2d()

HTH,

Thierry


----------------------------------------------------------------------------
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be
www.inbo.be

To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey

-----Oorspronkelijk bericht-----
Van: r-sig-ecology-bounces at r-project.org [mailto:r-sig-ecology-bounces at r-project.org] Namens Kingsford Jones
Verzonden: zaterdag 20 juni 2009 0:05
Aan: Nabeil Salama
CC: r-sig-ecology at r-project.org
Onderwerp: Re: [R-sig-eco] 3d density plot

Hi Nabeil,

I'm not sure I understand what you'd like to accomplish, but perhaps the following will be helpful:

example(kde2d, package='MASS')


hth,

Kingsford Jones

Dear all.



I am new to R so I am probably asking something that will be sneered at.




I am moving 100 "particles" in both x,y dimensions and would like to 
plot the density of particles at each Cartesian coordinate.



I can simply use:



plot(density(positionX)

plot(density(positionY)



to produce the relevant density of particles at either an X or a Y 
point, however how would it be possible to overlay the densities so 
that I obtain a density at a particular coordinate.



An mock example of what I am currently doing is



posX ? ?<- matrix (nrow=101,ncol=100,data=0)

posY ? ? <- matrix (nrow=101,ncol=100,data=0)



posX[1,]<-50

posY[1,]<-40



for (j in 1:100) {

posX[j+1,]<- posX[j,]+(runif(100)-0.5)

posY[j+1,]<- posY[j,]+(runif(100)-0.5)



}



matplot(posX,posY,type="l")

plot(density((posY[,j])))

plot(density((posX[,j])))



Simply I would like to know the density of particles at coordinates of 
the matplot.

From the example given the density of particles at 50,40 will be 
higher

than at the edges. But to quantifiably see this would be an advantage.





Any help?



I hope that is understandable.



Many thanks


? ? ? ?[[alternative HTML version deleted]]

_______________________________________________
R-sig-ecology mailing list
R-sig-ecology at r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-ecology

_______________________________________________
R-sig-ecology mailing list
R-sig-ecology at r-project.org
https://stat.ethz.ch/mailman/listinfo/r-sig-ecology

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