I noticed some weird behavior when resizing the plot window. Consider
library(sp)
library(rgeos)
library(raster)
rst.test <- raster(nrows=300, ncols=300, xmn=-150, xmx=150, ymn=-150, ymx=150, crs="NA")
sap.krog300 <- SpatialPoints(coordinates(matrix(c(0,0), ncol = 2)))
sap.krog300 <- gBuffer(spgeom = sap.krog300, width = 100, quadsegs = 20)
shrunk <- gBuffer(spgeom = sap.krog300, width = -30)
shrunk <- rasterize(x = shrunk, y = rst.test)
shrunk.coords <- xyFromCell(object = rst.test, cell = which(shrunk[] == 1))
plot(shrunk)
points(shrunk.coords, pch = "+")
If you resize the window, plotted points get different extent compared to the underlying raster. If you resize the window and plot shrunk and shrunk.coords again, the plot turns out fine. Can anyone explain this?
If you plot directly with the RasterLayer method for plot the resize problem does not occur.
## gives an error, but still plots
raster:::.imageplot(shrunk)
points(shrunk.coords, pch = ".")
So it must be something in the original plot call before the .imageplot method is called.
showMethods("plot", classes = "RasterLayer", includeDefs = TRUE)
It does occur if we call raster:::.plotraster directly, and this is the function that calls raster:::.imageplot:
raster:::.plotraster(shrunk, col = rev(terrain.colors(255)), maxpixels = 5e+05)
points(shrunk.coords, pch = ".")
It is actually in the axis labels, not the image itself. See with this, this plots faithfully on resize:
raster:::.imageplot(shrunk)
abline(h = c(-80, 80), v = c(-80, 80))
But do it like this, and the lines are no longer at [-80, 80] after resize:
plot(shrunk)
abline(h = c(-80, 80), v = c(-80, 80))
So it is actually the points plotted after the raster that are showing incorrectly: the plot method keeps the aspect ratio fixed, so widening the plot doesn't "stretch" out the raster circle to an ellipse. But, it does something to the points that are added afterwards so the calls to par() must not be handled correctly (probably in raster:::.imageplot).
Another way of seeing the problem is to show that axis() does not know the space being used by the plot, which is the same problem you see when overplotting:
plot(shrunk)
axis(1, pos = 1)
When you resize the x-axis length the two axes are no longer synchronized.
Because you have a raster, try replacing plot() with image(). I had the same problem but this solved it for me.
Related
I am using library VennDiagram to plot venn diagrams. But this function does not have a functionality to add legend and set names are displayed on or close to the sets themselves.
library(VennDiagram)
x <- list(c(1,2,3,4,5),c(4,5,6,7,8,9,10))
venn.diagram(x,filename="test.png",fill=c("#80b1d3","#b3de69"),
category.names=c("A","B"),height=500,width=500,res=150)
And with many sets, overplotting names is an issue and I would like to have a legend instead. The function is built on grid graphics and I have no idea how grid plotting works. But, I am attempting to add a legend anyway.
Looking into the venn.diagram function, I find that final plotted object is grob.list and it is a gList object and its plotted using grid.draw().
png(filename = filename, height = height, width = width,
units = units, res = resolution)
grid.draw(grob.list)
dev.off()
I figured out that I could create a legend by modifying the venn.diagram function with the code below.
cols <- c("#80b1d3","#b3de69")
lg <- legendGrob(labels=category.names, pch=rep(19,length(category.names)),
gp=gpar(col=cols, fill="gray"),byrow=TRUE)
Draw the object lg
png(filename = filename, height = height, width = width,
units = units, res = resolution)
grid.draw(lg)
dev.off()
to get a legend
How do I put the venn diagram (gList) and the legend (gTree,grob) together in a usable way? I am hoping to get something like base plot style:
or the ggplot style
If you are allowed to use other packages than VennDiagram, I suggest the following code using the eulerr package:
library(eulerr)
vd <- euler(c(A = 5, B = 3, "A&B" = 2))
plot(vd, counts = TRUE,lwd = 2,
fill=c("#80b1d3","#b3de69"),
opacity = .7,
key = list( space= "right", columns=1))
with key you define the legend location and appearance.
If you want to continue using the VennDiagram package and learn a bit of grid on the way:
Prepare diagram and legend
library(VennDiagram)
x <- list(c(1,2,3,4,5),c(4,5,6,7,8,9,10))
diag <- venn.diagram(x,NULL,fill=c("#80b1d3","#b3de69"),
category.names=c("A","B"),height=500,width=500,res=150)
cols <- c("#80b1d3","#b3de69")
lg <- legendGrob(labels=c("A","B"), pch=rep(19,length(c("A","B"))),
gp=gpar(col=cols, fill="gray"),
byrow=TRUE)
Transform the diagram to a gTree
(I'd love to find a better way if anyone knows one)
library(gridExtra)
g <- gTree(children = gList(diag))
Plot the two gTrees side by side
gridExtra::grid.arrange(g, lg, ncol = 2, widths = c(4,1))
Or one above the other
grid.arrange(g, lg, nrow = 2, heights = c(4,1))
I have found a solution as well, but the venn diagram region is not square aspect ratio. And the legend is not spaced ideally.
library(gridGraphics)
png("test.png",height=600,width=600)
grab_grob <- function(){grid.echo();grid.grab()}
grid.draw(diag)
g <- grab_grob()
grid.arrange(g,lg,ncol=2,widths=grid::unit(c(0.7,0.3),"npc"))
dev.off()
In R, it is possible to hold a device, draw the picture, and then flush the device to render the graphics. This is useful for very complex plots with thousands of data points, color gradients etc since without holding, the device would be refreshed after each plotting operation. It works quite well.
However, once the plot is in place, any window operation such as a resize will cause the plot to be refreshed -- however, this time without holding and flushing the device, but plotting the plot elements one by one and refreshing the display each time. This is extremely annoying.
Clearly, I could call manually dev.hold before resizing the window, but this is not a real solution.
Is there a way of telling R that the device should be put on hold for operations such as resize?
As indicated by Dan Slone and gdkrmr viable option is to use intermediate raster file to plot complex graphics.
The flow is the follows:
Save plot to png file.
Plot the image into the screen device.
After this there will be no problems with refreshing and resizing.
Please see the code below:
# plotting through png
plot.png <- function(x, y) {
require(png)
tmp <- tempfile()
png(tmp, width = 1920, height = 1080)
plot(x, y, type = "l")
dev.off()
ima <- readPNG(tmp)
op <- par(mar = rep(0, 4))
plot(NULL, xlim = c(0, 100), ylim = c(0, 100), xaxs = "i", yaxs = "i")
rasterImage(ima, 0, 0, 100, 100, interpolate = TRUE)
par(op)
unlink(tmp)
}
t <- 1:1e3
x <- t * sin(t)
y <- t * cos(t)
# without buffering
# plot(x, y, type = "l")
# with buffering in high-res PNG-file
plot.png(x, y)
Ouput:
I have a grid and I want to produce a map out of this grid with some map elements (scale, north arrow, etc). I have no problem drawing the grid and the coloring I need, but the additional map elements won't show on the map. I tried putting first=TRUE to the sp.layout argument according to the sp manual, but still no success.
I reproduced the issue with the integrated meuse dataset, so you may just copy&paste that code. I use those package versions: lattice_0.20-33 and sp_1.2-0
library(sp)
library(lattice) # required for trellis.par.set():
trellis.par.set(sp.theme()) # sets color ramp to bpy.colors()
alphaChannelSupported = function() {
!is.na(match(names(dev.cur()), c("pdf")))
}
data(meuse)
coordinates(meuse)=~x+y
data(meuse.riv)
library(gstat, pos = match(paste("package", "sp", sep=":"), search()) + 1)
data(meuse.grid)
coordinates(meuse.grid) = ~x+y
gridded(meuse.grid) = TRUE
v.uk = variogram(log(zinc)~sqrt(dist), meuse)
uk.model = fit.variogram(v.uk, vgm(1, "Exp", 300, 1))
meuse[["ff"]] = factor(meuse[["ffreq"]])
meuse.grid[["ff"]] = factor(meuse.grid[["ffreq"]])
zn.uk = krige(log(zinc)~sqrt(dist), meuse, meuse.grid, model = uk.model)
zn.uk[["se"]] = sqrt(zn.uk[["var1.var"]])
meuse.sr = SpatialPolygons(list(Polygons(list(Polygon(meuse.riv)),"meuse.riv")))
rv = list("sp.polygons", meuse.sr, fill = "lightblue")
sampling = list("sp.points", meuse.riv, color = "black")
scale = list("SpatialPolygonsRescale", layout.scale.bar(),
offset = c(180500,329800), scale = 500, fill=c("transparent","black"), which = 4)
text1 = list("sp.text", c(180500,329900), "0", cex = .5, which = 4)
text2 = list("sp.text", c(181000,329900), "500 m", cex = .5, which = 4)
arrow = list("SpatialPolygonsRescale", layout.north.arrow(),
offset = c(181300,329800),
scale = 400, which = 4)
library(RColorBrewer)
library(lattice)
trellis.par.set(sp.theme())
precip.pal <- colorRampPalette(brewer.pal(7, name="Blues"))
spplot(zn.uk, "var1.pred",
sp.layout = list(rv, sampling, scale, text1, text2),
main = "log(zinc); universal kriging standard errors",
col.regions=precip.pal,
contour=TRUE,
col='black',
pretty=TRUE,
scales=list(draw = TRUE),
labels=TRUE)
And that's how it looks...all naked:
So my questions:
Where is the scale bar, north arrow, etc hiding? Did I miss something? Every example I could find on the internet looks similar to that. On my own dataset I can see the scale bar and north arrow being drawn at first, but as soon as the grid is rendered, it superimposes the additional map elements (except for the scale text, that is shown on the map - not the bar and north arrow for some reason I don't seem to comprehend).
The error message appearing on the map just shows when I try to add the sampling locations sampling = list("sp.points", meuse.riv, color = "black"). Without this entry, the map shows without error, but also without additional map elements. How can I show the sampling points on the map (e.g. in circles whose size depends on the absolute value of this sampling point)?
This bothered me for many, many hours by now and I can't find any solution to this. In Bivand et al's textbook (2013) "Applied Spatial Data Analysis with R" I could read the following entry:
The order of items in the sp.layout argument matters; in principle objects
are drawn in the order they appear. By default, when the object of spplot has
points or lines, sp.layout items are drawn before the points to allow grids
and polygons drawn as a background. For grids and polygons, sp.layout
items are drawn afterwards (so the item will not be overdrawn by the grid
and/or polygon). For grids, adding a list element first = TRUE ensures that
the item is drawn before the grid is drawn (e.g. when filled polygons are added). Transparency may help when combining layers; it is available for the
PDF device and several other devices.
Function sp.theme returns a lattice theme that can be useful for plots
made by spplot; use trellis.par.set(sp.theme()) after a device is opened
or changed to make this effective.
However, also with this additional information I wasn't able to solve this problem. Glad for any hint!
The elements you miss are being drawn in panel four, which does not exist, so are not being drawn. Try removing the which = 4.
meuse.riv in your example is a matrix, which causes the error message, but should be a SpatialPoints object, so create sampling by:
sampling = list("sp.points", SpatialPoints(meuse.riv), color = "black")
When working from examples, my advice is to choose examples as close as possible to what you need, and only change one thing at a time.
I am trying to write a function that will produce what I regard as a real dot plot (unlike the Cleveland variety, I require a univariate scatterplot with the dots stacked for (nearly) equal values). I have come close:
In this illustration, the dots you see are actually rotated text strings of lower-case "o"s. It is done this way because I need the dot spacing to stay constant if the plot is re-scaled. However, I'd like something better than lower-case "o"s, for example, filled dots instead of circles. This could be done if I could access the font that is used for the standard plotting symbols (pch = 1:25 in the plot function and relatives). Then I could make a text string with that font and get what's needed. Does anybody know how to do that?
PS - No, a histogram with lots of bins is not an acceptable substitute.
I did find a way to get the desired dot plot using low-level graphics parameters (namely "usr", the actual user coordinates of the plotting area, and "cxy", the character size). The recordGraphics() function wraps the part that needs to be changed when the graph is resized. Here's the function:
dot.plot = function(x, pch = 16, bins = 50, spacing = 1, xlab, ...) {
if(missing(xlab))
xlab = as.character(substitute(x))
# determine dot positions
inc = diff(pretty(x, n = bins)[1:2])
freq = table(inc * round(x / inc, 0))
xx = rep(as.numeric(names(freq)), freq)
yy = unlist(lapply(freq, seq_len))
# make the order of the dots the same as the order of the data
idx = seq_along(x)
idx[order(x)] = idx
xx = xx[idx]
yy = yy[idx]
# make a blank plot
plot(xx, yy, type = "n", axes = FALSE, xlab = xlab, ylab = "")
# draw scale
axis(1)
ylow = par("usr")[3]
abline(h = ylow) # extend to full width
# draw points and support resizing
recordGraphics({
yinc = 0.5 * spacing * par("cxy")[2]
points(xx, ylow + yinc * (yy - .5), pch = pch, ...)
},
list(),
environment(NULL))
invisible()
}
The spacing argument may be used if you want a tighter or looser gap between dots. An example...
with(iris, dot.plot(Sepal.Length, col = as.numeric(Species)))
This is a better solution than trying to do it with text, but also a little bit scary because of the warnings you see in the documentation for recordGraphics
Hoping for some pointers or some experiences insight as i'm literally losing my mind over this, been trying for 2 full days to set up the right values to have a function spit out clean simple line plots from the gbm.plot function (packages dismo & gbm).
Here's where I start. bty=n in par to turn off the box & leave me with only left & bottom axes. Gbm.plot typically spits out one plot per explanatory variable, so usually 6 plots etc, but I'm tweaking it to do one per variable & looping it. I've removed the loop & lots of other code so it's easy to see what's going on.
png(filename = "whatever.png",width=4*480, height=4*480, units="px", pointsize=80, bg="white", res = NA, family="", type="cairo-png")
par(mar=c(2.6,2,0.4,0.5), fig=c(0,1,0.1,1), las=1, bty="n", mgp=c(1.6,0.5,0))
gbm.plot(my_gbm_model,
n.plots=1,
plot.layout = c(1,1),
y.label = "",
write.title=F,
variable.no = 1, #this is part of the multiple plots thing, calls the explanatory variable
lwd=8, #this controls the width of the main result line ONLY
rug=F)
dev.off()
So this is what the starting condition looks like. Aim: make the axes & ticks thicker. That's it.
Putting "lwd=20" in par does nothing.
Adding axes=F into gbm.plot() turns the axes and their numbers off. So I conclude that the control of these axes is handled by gbm.plot, not par. Here's where it get's frustrating and crap. Accepted wisdom from searches says that lwd should control this but it only controls the wiggly centre line as per my note above. So maybe I could add axis(side=1, lwd=8) into gbm.plot() ?
It runs but inexplicably adds a smoother! (which is very thin & hard to see on the web but it's there, I promise). It adds these warnings:
In if (smooth & is.vector(predictors[[j]])) { ... :
the condition has length > 1 and only the first element will be used
Fine, R's going to be a dick for seemingly no reason, I'll keep plugging the leaks as they come up. New code with axis as before and now smoother turned off:
png(filename = "whatever.png",width=4*480, height=4*480, units="px", pointsize=80, bg="white", res = NA, family="", type="cairo-png")
par(mar=c(2.6,2,0.4,0.5), fig=c(0,1,0.1,1), las=1, bty="n", mgp=c(1.6,0.5,0))
gbm.plot(my_gbm_model,
n.plots=1,
plot.layout = c(1,1),
y.label = "",
write.title=F,
variable.no = 1,
lwd=8,
rug=F,
smooth=F,
axis(side=1,lwd=8))
dev.off()
Gives error:
Error in axis(side = 1, lwd = 8) : plot.new has not been called yet
So it's CLEARLY drawing axes within plot since I can't affect the axes from par and I can turn them off in plot. I can do what I want and make one axis bold, but that results in a smoother and warnings. I can turn the smoother off, but then it fails because it says plot.new hadn't been called. And this doesn't even account for the other axis I have to deal with, which also causes the plot.new failure if I call 2 axis sequentially and allow the smoother.
Am I the butt of a big joke here, or am I missing something obvious? It took me long enough to work out that par is supposed to be before all plots unless you're outputting them with png etc in which case it has to be between png & plot - unbelievably this info isn't in ?par. I know I'm going off topic by ranting, sorry, but yeah, 2 full days. Has this been everyone's experience of plotting in R?
I'm going to open the vodka in the freezer. I appreciate I've not put the full reproducible code here, apologies, I can do if absolutely necessary, but it's such a huge timesuck to get to reproducible stage and I'm hoping someone can see a basic logical/coding failure screaming out at them from what I've given.
Thanks guys.
EDIT: reproducibility
core data csv: https://drive.google.com/file/d/0B6LsdZetdypkWnBJVDJ5U3l4UFU
(I've tried to make these data reproducible before and I can't work out how to do so)
samples<-read.csv("data.csv", header = TRUE, row.names=NULL)
my_gbm_model<-gbm.step(data=samples, gbm.x=1:6, gbm.y=7, family = "bernoulli", tree.complexity = 2, learning.rate = 0.01, bag.fraction = 0.5))
Here's what will widen your axis ticks:
..... , lwd.ticks=4 , ...
I predict on the basis of no testing because I keep getting errors with what limited code you have provided) that it will get handled correctly in either gbm.plot or in a subsequent axis call. There will need to be a subsequent axis call, two of them in fact (because as you noted 'lwd' gets passed around indiscriminately):
png(filename = "whatever.png",width=4*480, height=4*480, units="px", pointsize=80, bg="white", res = NA, family="", type="cairo-png")
par(mar=c(2.6,2,0.4,0.5), fig=c(0,1,0.1,1), las=1, bty="n", mgp=c(1.6,0.5,0))
gbm.plot(my_gbm_model,
n.plots=1,
plot.layout = c(1,1),
y.label = "",
write.title=F,
variable.no = 1,
lwd=8,
rug=F,
smooth=F, axes="F",
axis(side=1,lwd=8))
axis(1, lwd.ticks=4, lwd=4)
# the only way to prevent `lwd` from also affecting plot line
axis(2, lwd.ticks=4, lwd=4)
dev.off()
This is what I see with a simple example:
png(); Speed <- cars$speed
Distance <- cars$dist
plot(Speed, Distance,
panel.first = lines(stats::lowess(Speed, Distance), lty = "dashed"),
pch = 0, cex = 1.2, col = "blue", axes=FALSE)
axis(1, lwd.ticks=4, lwd=4)
axis(2, lwd.ticks=4, lwd=4)
dev.off()