I have written the following code to plot my xy data on a set of re-scaleable axes, the values contained in pointSize are the correctly scaled vertical/horizontal diameters of the point I want at each plotted coordinate. How do I go about getting this to work? Right now I am just plotting points with whatever scaling is used by default in geom_point(aes(size)) and the points don't scale with the axes. Once I rescale the axes with coord_cartesian I want the plotted points to increase/decrease relative to the axes accordingly.
For example, if the point size is say 5, that means I want the horizontal and vertical diameter of the point to be 5 relative to the axes regardless of specified xyScaling.
EDIT: min in pointSize should have been min = 0, not min = -10
Minimal reproducible code:
# Sample size & x-y axes plot boundaries
sampleSize <- 100
# Set scale factor of x-y axes
xyScaling <- 1
# Set to false once sampled to rescale axis with same distributions
resample <- TRUE
if (resample == TRUE){
xSample <- replicate(sampleSize, runif(1, min = -sampleSize/2, max = sampleSize/2))
ySample <- replicate(sampleSize, runif(1, min = -sampleSize/2, max = sampleSize/2))
pointSize <- replicate(sampleSize, runif(1, min = 0, max = 10))
}
sampleDataFrame <- data.frame(xSample, ySample, pointSize)
samplePlot <- ggplot(sampleDataFrame, aes(xSample, ySample))
samplePlot +
geom_point(data = sampleDataFrame, aes(size = sampleDataFrame$pointSize[])) +
coord_cartesian(xlim = c((xyScaling*(-sampleSize/2)),(xyScaling*(sampleSize/2))),
ylim = c((xyScaling*(-sampleSize/2)),(xyScaling*(sampleSize/2)))) +
xlab("x") +
ylab("y") +
scale_size_identity(guide=FALSE)
EDIT: So I almost managed to solve the problem by using geom_rect, the following code does what I want with the caveat that the points are rectangles as opposed to ellipses/circles, I couldn't get this to work with ellipses, if anyone could guide me to the right function I would be very grateful.
sampleDataFrame <- data.frame(xSample, ySample, pointSize)
samplePlot <- ggplot(sampleDataFrame)
samplePlot +
geom_point(aes(xSample, ySample, size = 0)) +
geom_rect(aes(xmin = xSample-(pointSize/2), xmax = xSample+(pointSize/2), ymin = ySample-(pointSize/2), ymax = ySample+(pointSize/2))) +
coord_cartesian(xlim = c((xyScaling*(-sampleSize/2)),(xyScaling*(sampleSize/2))),
ylim = c((xyScaling*(-sampleSize/2)),(xyScaling*(sampleSize/2)))) +
xlab("x") +
ylab("y") +
scale_size_identity(guide=FALSE)
this has been suggested in the past , but I don't think it got implemented. One problem is that circles are only circular in the special case of cartesian coordinates with unit aspect ratio. The easiest workaround is probably to create a data.frame with xy positions describing circles (ellipses) and draw these as polygons.
library(gridExtra)
library(ggplot2)
circle <- polygon_regular(50)
pointy_points <- function(x, y, size){
do.call(rbind, mapply(function(x,y,size,id)
data.frame(x=size*circle[,1]+x, y=size*circle[,2]+y, id=id),
x=x,y=y, size=size, id=seq_along(x), SIMPLIFY=FALSE))
}
test <- pointy_points(1:10, 1:10, size=seq(0.2, 1, length.out=10))
ggplot(test, aes(x,y,group=id, fill=id)) + geom_polygon()
You could try to edit the points at the lowest-level, but it's quite fiddly,
library(ggplot2); library(grid)
p <- qplot(1:10, 1:10, size=I(10))
g <- ggplotGrob(p)
points <- g$grobs[[4]][["children"]][[2]]
g$grobs[[4]][["children"]][[2]] <-
editGrob(points, size = convertUnit(points$size, unitTo = "npc"))
grid.newpage()
grid.draw(g)
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