I have a 3D plot using RGL. I would like to make identical plots using color to highlight the distribution of some variable. To do this I would like to have identical plots, how do I find and set the orientation of a plot?
Once I make a preliminary plot, I move it around to find a nice display angle and I would like to save that angle and incorporate it into future plotting scripts. Anyone have a suggestion on how to do this?
library(rgl)
plot3d(iris)
#play with the plot to find a good angle
#save the angle for future plots
Ben's comment basically answers your question; this just applies expand.dots to what he wrote ;)
## In an inital session:
library(rgl)
plot3d(iris)
## Now move the image around to an orientation you like
## Save RGL parameters to a list object
pp <- par3d(no.readonly=TRUE)
## Save the list to a text file
dput(pp, file="irisView.R", control = "all")
.......
## Then, in a later session, to recreate the plot just as you had it:
library(rgl)
pp <- dget("irisView.R")
plot3d(iris)
par3d(pp)
Related
I am working on a 3D scatter plot using rgl package in R, with multiple colors for different series. I was wondering if there would be a way to plot a 4th dimension by controlling the size of spheres.
I know it's possible with plotly ("bubble plot") : https://plot.ly/r/3d-scatter-plots/, but Plotly starts to flicker when dealing with lots of datapoints. Can the same result be achieved using Rgl?
set.seed(101)
dd <- data.frame(x=rnorm(100),y=rnorm(100),z=rnorm(100),
c=rnorm(100),s=rnorm(100))
Scaling function (I tweaked to keep the values strictly in (0,1), don't know if that's really necessary):
ss <- function(x) scale(x,center=min(x)-0.01,scale=diff(range(x))+0.02)
library(rgl)
Define colours (there may be a better way to do this ...)
cvec <- apply(colorRamp(c("red","blue"))(ss(dd$c))/255,1,
function(x) rgb(x[1],x[2],x[3]))
The picture (need type="s" to get spheres)
with(dd,plot3d(x,y,z,type="s",radius=ss(s), col=cvec))
In R, I have a raster object generated from a kernel density analysis using the ks package. I convert this into a raster object (from the raster package) and try to draw that raster object to a PNG using plot(). I want the png to have exactly one pixel for every pixel in the raster object. Simple enough, right? By default of course, I get all sorts of extraneous junk added to the plot. I can remove most of this using the various settings in plot() or par(), but no matter what I do, I don't seem able to get rid of the space formerly taken up by the legend on the right side of the plot.
library('ks')
library('raster')
# generate the data
set.seed(1)
x = matrix(rnorm(1000,1,0.5),500)
xpix = 100
ypix = 100
# calculate the density function
k = kde(
x,
H=matrix(c(0.1,0,0,0.1),2),
xmin=c(0,0),
xmax=c(1,1),
gridsize=c(xpix,ypix)
)
# convert to raster
r = raster(k)
# plot the image to PNG
png('file.png',width=xpix,height=ypix)
par(
mar=c(0,0,0,0),
bty='n',
bg='black',
plt=c(0,1,0,1)
)
plot(
r,
legend=FALSE,
axes=FALSE,
plt=c(0,1,0,1)
)
# see that 'plt' did not change
print(par())
dev.off()
If I check par before closing the device, I can see that the 'plt' value is not what I set it to; it shows the right margin, where the plotting area has been nudged over to make space for the non-legend. Sample code is above, and the image it generates is linked to here.
Incidentally, I was able to achieve the correct effect with the image() function instead of plot(), though that introduced it's own problems, namely that transparency no longer worked. Can I solve this with plot()? It's very frustrating that I'm so close but just can't seem to change the size of the plot area! I don't want to use another graphics package if there is any way to make the base function work.
For educational purpose I'm trying to plot a singel horizontal "numberline" with some datapoints with labels in R. I came this far;
library(plotrix)
source("spread.labels.R")
plot(0:100,axes=FALSE,type="n",xlab="",ylab="")
axis(1,pos=0)
spread.labels(c(5,5,50,60,70,90),rep(0,6),ony=FALSE,
labels=c("5","5","50","60","70","90"),
offsets=rep(20,6))
This gave me a numberline with smaller lines pointing up to (and a little bit "in") the labels from where the datapoints should lie on the numberline - but without the points itself. Can anyone give me additional or alternative R-codes for solving thess problems:
- datapoints itself still missing are not plotted,
- and labels maybe not evenly divided over the whole numberline,
- and lines come into the labels and not merely point to the labels
Thank a lot,
Benjamin Telkamp
I usually like to create plots using primitive base R graphics functions, such as points(), segments(), lines(), abline(), rect(), polygon(), text(), and mtext(). You can easily create curves (e.g. for circles) and more complex shapes using segments() and lines() across granular coordinate vectors that you define yourself. For example, see Plot angle between vectors. This provides much more control over the plot elements you create, however, it often takes more work and careful coding than more "pre-packaged" solutions, so it's a tradeoff.
For your case, it sounds to me like you're happy with what spread.labels() is trying to do, you just want the following changes:
add point symbols at the labelled points.
prevent overlap between labels and lines.
Here's how this can be done:
## define plot data
xlim <- c(0,100);
ylim <- c(0,100);
px <- c(5,5,50,60,70,90);
py <- c(0,0,0,0,0,0);
lx.buf <- 5;
lx <- seq(xlim[1]+lx.buf,xlim[2]-lx.buf,len=length(px));
ly <- 20;
## create basic plot outline
par(xaxs='i',yaxs='i',mar=c(5,1,1,1));
plot(NA,xlim=xlim,ylim=ylim,axes=F,ann=F);
axis(1);
## plot elements
segments(px,py,lx,ly);
points(px,py,pch=16,xpd=NA);
text(lx,ly,px,pos=3);
I have been building a small GUI for climate analysis using gWidgets in R. Progress has been slow but steady until I hit a problem trying to display my raster stack of results using spplot().
The issue is that only the first raster in the stack is plotted and the rest are not. This issue occurs regardless if:
I produce the plot using a handler within the GUI.
If the plot is produced using a handler within a addHandlerChanged/addHandlerClicked function.
If the plot is loaded to the GUI directly from the R console.
As above but using using levelplot().
If plot() is used, results are displayed correctly but only the first 16 are displayed (I have 24 graphs) and the scales are not merged producing difficulty in interpreting the results.
Here is some example code to illustrate the issue:
require(gWidgets)
require(raster)
## create example GUI plot area
win = gwindow("Graph test")
nb = gnotebook(container=win,expand=T)
plots = ggraphicsnotebook(container=nb)
## create raster stack
rs=list()
for(i in 1:24){
rs1=raster()
rs1[]=rnorm(3600)
rs[i]=rs1
}
rs=stack(rs)
## attempt to plot stack
spplot(rs) ##plot is not produced correctly with only the first raster plotted
##compare this to plotting in a normal window
windows()
spplot(rs)
Here is an example of the expected plot (left) and the actual (right) using the above code.
If anybody has any ideas how to get around this or any alternative plotting options for raster stacks I would love to hear them.
(please note that similar results are produced if I open a separate window using windows() within the GUI or if I use levelplot())
Cheers
To those who may be interested. After 3.5 years and a many trials, including recordPlot(), the gridGraphics package and imager::capture.plot(), the only solution that I found was to save the graph as an image and then plot it in the window using rasterImage()
require(gWidgets)
require(gWidgetsRGtk2)
require(RGtk2)
require(raster)
require(png)
options(guiToolkit="RGtk2")
## create raster stack
rs=list()
for(i in 1:24){
rs1=raster(nrow=2,ncol=2)
rs1[]=rnorm(4)
rs[i]=rs1
}
rs=stack(rs)
##save plot as png
png("out.png")
spplot(rs)
dev.off()
img = readPNG("out.png")
## create example GUI plot area
win = gwindow("Graph test")
nb = gnotebook(container=win,expand=T)
plots = ggraphicsnotebook(container=nb)
##plot
par(mar=rep(0,4))
plot(1, type="n", axes=F, xlab="", ylab="")
usr = par("usr")
rasterImage(img, usr[1], usr[3], usr[2], usr[4])
I have a data.frame of x/y/z points. I know how to make a 3d scatterplot using the rgl package but I would like to connect each point in the scatterplot to make a wireframe or surface plot.
This code returns the scatter plot
library(rgl)
Data <- expand.grid(x=seq(0,10),y=seq(0,10))
Data$z <- Data$x^2+Data$y^2
plot3d(Data)
While this code returns a blank graph:
plot3d(Data,type='wire')
I can make the plot I want with lattice:
library(lattice)
wireframe(z~x+y,Data)
I can even make it rotate:
library(TeachingDemos)
rotate.wireframe(z~x+y,Data)
But I prefer rgl over lattice because it renders much quicker and lets you rotate the plot with the mouse.
Whats the proper way to make a wireframe plot in rgl?
The surface drawing plot function in rgl is persp3d and like base::persp, it needs a matrix as input to the z argument
zmat <- matrix(Data$z, 11,11)
persp3d(x=seq(0,10), y=seq(0,10), z=zmat)
I did spin this graphic a bit before capturing it with a screen grabbing program I use: