I have a 3D dataset:
data = data.frame(
x = rep( c(0.1, 0.2, 0.3, 0.4, 0.5), each=5),
y = rep( c(1, 2, 3, 4, 5), 5)
)
data$z = runif(
25,
min = (data$x*data$y - 0.1 * (data$x*data$y)),
max = (data$x*data$y + 0.1 * (data$x*data$y))
)
data
str(data)
And I want to plot it, but the built-in-functions of R alwyas give the error
increasing 'x' and 'y' values expected
# ### 3D Plots ######################################################
# built-in function always give the error
# "increasing 'x' and 'y' values expected"
demo(image)
image(x = data$x, y = data$y, z = data$z)
demo(persp)
persp(data$x,data$y,data$z)
contour(data$x,data$y,data$z)
When I searched on the internet, I found that this message happens when combinations of X and Y values are not unique. But here they are unique.
I tried some other libraries and there it works without problems. But I don't like the default style of the plots (the built-in functions should fulfill my expectations).
# ### 3D Scatterplot ######################################################
# Nice plots without surface maps?
install.packages("scatterplot3d", dependencies = TRUE)
library(scatterplot3d)
scatterplot3d(x = data$x, y = data$y, z = data$z)
# ### 3D Scatterplot ######################################################
# Only to play around?
install.packages("rgl", dependencies = TRUE)
library(rgl)
plot3d(x = data$x, y = data$y, z = data$z)
lines3d(x = data$x, y = data$y, z = data$z)
surface3d(x = data$x, y = data$y, z = data$z)
Why are my datasets not accepted by the built-in functions?
I think the following code is close to what you want
x <- c(0.1, 0.2, 0.3, 0.4, 0.5)
y <- c(1, 2, 3, 4, 5)
zfun <- function(a,b) {a*b * ( 0.9 + 0.2*runif(a*b) )}
z <- outer(x, y, FUN="zfun")
It gives data like this (note that x
and y
are both increasing)
> x
[1] 0.1 0.2 0.3 0.4 0.5
> y
[1] 1 2 3 4 5
> z
[,1] [,2] [,3] [,4] [,5]
[1,] 0.1037159 0.2123455 0.3244514 0.4106079 0.4777380
[2,] 0.2144338 0.4109414 0.5586709 0.7623481 0.9683732
[3,] 0.3138063 0.6015035 0.8308649 1.2713930 1.5498939
[4,] 0.4023375 0.8500672 1.3052275 1.4541517 1.9398106
[5,] 0.5146506 1.0295172 1.5257186 2.1753611 2.5046223
and a graph like
persp(x, y, z)
Adding to the solutions of others, I'd like to suggest using the plotly
package for R
, as this has worked well for me.
Below, I'm using the reformatted dataset suggested above, from xyz-tripplets to axis vectors x and y and a matrix z:
x <- 1:5/10
y <- 1:5
z <- x %o% y
z <- z + .2*z*runif(25) - .1*z
library(plotly)
plot_ly(x=x,y=y,z=z, type="surface")
The rendered surface can be rotated and scaled using the mouse. This works fairly well in RStudio.
You can also try it with the built-in volcano
dataset from R
:
plot_ly(z=volcano, type="surface")
Not sure why the code above did not work for the library rgl
, but the following link has a great example with the same library.
Run the code in R and you will obtain a beautiful 3d plot that you can turn around in all angles.
http://statisticsr.blogspot.de/2008/10/some-r-functions.html
########################################################################
## another example of 3d plot from my personal reserach, use rgl library
########################################################################
# 3D visualization device system
library(rgl);
data(volcano)
dim(volcano)
peak.height <- volcano;
ppm.index <- (1:nrow(volcano));
sample.index <- (1:ncol(volcano));
zlim <- range(peak.height)
zlen <- zlim[2] - zlim[1] + 1
colorlut <- terrain.colors(zlen) # height color lookup table
col <- colorlut[(peak.height-zlim[1]+1)] # assign colors to heights for each point
open3d()
ppm.index1 <- ppm.index*zlim[2]/max(ppm.index);
sample.index1 <- sample.index*zlim[2]/max(sample.index)
title.name <- paste("plot3d ", "volcano", sep = "");
surface3d(ppm.index1, sample.index1, peak.height, color=col, back="lines", main = title.name);
grid3d(c("x", "y+", "z"), n =20)
sample.name <- paste("col.", 1:ncol(volcano), sep="");
sample.label <- as.integer(seq(1, length(sample.name), length = 5));
axis3d('y+',at = sample.index1[sample.label], sample.name[sample.label], cex = 0.3);
axis3d('y',at = sample.index1[sample.label], sample.name[sample.label], cex = 0.3)
axis3d('z',pos=c(0, 0, NA))
ppm.label <- as.integer(seq(1, length(ppm.index), length = 10));
axes3d('x', at=c(ppm.index1[ppm.label], 0, 0), abs(round(ppm.index[ppm.label], 2)), cex = 0.3);
title3d(main = title.name, sub = "test", xlab = "ppm", ylab = "samples", zlab = "peak")
rgl.bringtotop();
I use the lattice
package for almost everything I plot in R and it has a corresponing plot to persp
called wireframe
. Let data
be the way Sven defined it.
wireframe(z ~ x * y, data=data)
Or how about this (modification of fig 6.3 in Deepanyan Sarkar's book):
p <- wireframe(z ~ x * y, data=data)
npanel <- c(4, 2)
rotx <- c(-50, -80)
rotz <- seq(30, 300, length = npanel[1]+1)
update(p[rep(1, prod(npanel))], layout = npanel,
panel = function(..., screen) {
panel.wireframe(..., screen = list(z = rotz[current.column()],
x = rotx[current.row()]))
})
Since this post continues to draw attention I want to add the OpenGL way to make 3-d plots too (as suggested by @tucson below). First we need to reformat the dataset from xyz-tripplets to axis vectors x
and y
and a matrix z
.
x <- 1:5/10
y <- 1:5
z <- x %o% y
z <- z + .2*z*runif(25) - .1*z
library(rgl)
persp3d(x, y, z, col="skyblue")
This image can be freely rotated and scaled using the mouse, or modified with additional commands, and when you are happy with it you save it using rgl.snapshot
.
rgl.snapshot("myplot.png")
Source: Stackoverflow.com