I want to plot SpatialPolygonsDataFrame as a semi-transparent main object (with legend on the right), but I want to plot yet additional raster (hillshade) as a background - just to make nicer map. I would need something like:
spplot(polygons, sp.layout = list(list("raster", myRaster)))
but looking at ?spplot, it doesn't seem to be possible to specify the raster in sp.layout. I can't specify the raster as the main object, because the main object are the polygons dataFrame, whose value scale I want to plot in the legend on the right side.
How is it possible to plot an additional raster in spplot?
Here's one way to do it. There's probably a neater way to achieve it without plotting the polygon object twice, though...
library(sp)
library(rasterVis)
r <- raster(nrow=18, ncol=36)
r[] <- runif(ncell(r)) * 10
r[r > 8] <- NA
pol <- rasterToPolygons(r, function(x) x > 6)
spplot(pol) + levelplot(r) + spplot(pol)
Or alternatively:
library(latticeExtra)
spplot(pol) + spplot(r) + spplot(pol)
EDIT
As per the comment by #OscarPerpiñán, a better way to do this is:
spplot(pol) + as.layer(spplot(r), under = TRUE)
Related
I want to overlay two raster objects.
I asked the question(Raster overlay visualization in rasterVis package: How the Significant raster images are represented as point marks?).
I refer to the #thiagoveloso'answer from this(Adding stippling to image/contour plot).
But the display is not what I wanted. It's not obvious and beautiful. If I try to change the shape or size of the mark, it will take a long long long time to draw or become weird.
Here is my code:
library(raster)
library(rasterVis)
rm(list = ls())
MK<-raster("C:/e_Zs——trend.tif")
### MK<1.96 set value to NA
fun <- function(x) { x[x<3] <- NA; return(x) }
MK<-calc(MK,fun = fun)
## load trend
Trend<- raster("C:/e_slope_trend.tif")
# And this is the key step:
# Converting the "mask" raster to spatial points
r.mask <- rasterToPoints(MK, spatial=TRUE)
plot(r.mask,cex=0.01)
# Plot
levelplot(Trend, margin=NA,par.settings=RdBuTheme) +
latticeExtra::layer(sp.points(r.mask, pch=100, cex=0.1, alpha=0.3,col="Black"))
I want to draw a fig,like:
And the fig like:
If i change the cex=0.5,it will lke:
If I change the shape of the mark, it will do so long... So. get any idea?
There are questions out there about the fact that ggplot2 can't plot polygon shapes that have holes.
That is because, if the order of points is not OK, the end graph looks bad, usually with clipping/trimming lines inside the donut shape.
I have read a lot about how order matters, but I am not able to step forward.
I have a SpatialPolygonsDataFrame with 26 features (comes from raster::rasterToPolygons(dissolve=T)) and I want to plot it with ggplot.
Here's what happens -
r3.pol <- rasterToPolygons(r3, dissolve=T)
r3.df <- fortify(r3.pol)
names(r3.df) <- c('x','y','order','hole','piece','ID','group')
p <- ggplot(r3.df)
p <- p + geom_polygon(mapping=aes(x=x,y=y,group=ID), fill='red')
p <- p + coord_equal()
I see this output:
While it should be like so, with plot(r3.pol):
How can I make this work?
I tried for hours but I am not able to reorder r3.df.
Also, can the information in r3.df$hole be helpful? It is returned by the function fortify for points that are holes (I think).
Side question: how can I give you my r3.pol SpatialPolygonsDataFrame, so that you can try yourself? I remember seeing long, reproducible "dumps" of objects here, but I don't know how to do it.
I saved the polygons data frame here. Was not able to save it using dput, sorry. You can fetch it using load.
I suggest to install the package "ggpolypath" and use geom_polypath instead of geom_polygon. Works for me.
My temporary solution is: ##$% polygons, and use the raster package.
Namely:
r <- raster(x=extent(r3.pol), crs=crs(r3.pol)) # empty raster from r3.pol
res(r) <- 250 # set a decent resolution (depends on your extent)
r <- setValues(r, 1) # fill r with ones
r <- mask(r, r3.pol) # clip r with the shape polygons
And now plot it as you would do with any raster with ggplot. The rasterVis package might come helpful here, but I'm not using it, so:
rdf <- data.frame(rasterToPoints(r))
p <- ggplot(rdf) + geom_raster(mapping=aes(x=x, y=y), fill='red')
p <- p + coord_equal()
And here it goes.
Alternatively, you can create the raster with rasterize, so the raster will hold the polygons values (in my case, just an integer):
r <- raster(x=extent(r3.pol), crs=crs(r3.pol))
res(r) <- 250
r <- rasterize(r3.pol, r)
rdf <- data.frame(rasterToPoints(r))
p <- ggplot(rdf) + geom_raster(mapping=aes(x=x, y=y, fill=factor(layer)))
p <- p + coord_equal()
If someone comes up with a decent solution for geom_polygon, probably involving re-ordering of the polygons data frame, I'll be glad to consider it.
I have a raster object with a large number of attributes, and I would like to plot the spatial data in R and colour code it by a certain attribute. I have not been able to work out how to use the information of a particular attribute to achieve this. So far I have successfully extracted the attribute of choice using factorValues(), but I cannot determine how to now incorporate this information into the plot() function. I tried using the ratify() and level() functions mentioned in the raster package documentation, but I don’t understand how the simplified online examples can be adapted for a raster with multiple attributes.
Any advice on how to achieve this would be greatly appreciated.
# read in shapefile
shp = readOGR(".", "grid")
#convert to raster
r = raster(extent(shp))
res(r) = c(1,0.5)
ra = rasterize(shp, r)
#crop raster to desired extent
rcrop = crop(ra, extent(-12, 2, 29, 51))
# extract attribute value of interest
f = factorValues(rcrop, 1:420, layer=1, att=17, append.names=FALSE)
# here there are 420 cells in the raster and I am interested in plotting values of attribute 17 of the raster (this is currently a numeric attribute, not a factor)
#extra code to set attribute as the level to use for plotting colours???
rcrop = ratify(rcrop)
rat = levels(rcrop)[[1]] #this just extras row IDs..not what I want
#…
### plot: I want to plot the grid using 7 colours (I would ideally like to specify the breaks myself)
require(RColorBrewer)
cols = brewer.pal(7,"YlGnBu")
#set breaks
brks = seq(min(minValue(rcrop)),max(maxValue(rcrop),7))
#plot
plot(rcrop, breaks=brks, col=cols, axis.arg=arg)
The following is pretty hacky (and may perform poorly for large rasters), but I'm not sure if there's a way to link col.regions to a specified attribute.
rasterVis::levelplot does a nice job of labelling colour ramps corresponding to factor rasters, and while it provides an att argument allowing you to specify which attribute you're interested in, this seems to only modify the labelling of the ramp. Raster cell values control how the colour ramp is mapped to the raster, so it seems to me that we need to modify the cell values themselves. Maybe #OscarPerpiñán will chime in here to prove me wrong :)
We can create a simple function to substitute the original cell values with whichever attribute we want:
switch_att <- function(r, att) {
r[] <- levels(r)[[1]][values(r), att]
r
}
Let's download and import a small example polygon dataset from Natural Earth:
library(rasterVis)
library(rgdal)
require(RColorBrewer)
download.file(file.path('http://www.naturalearthdata.com',
'http//www.naturalearthdata.com/download/110m/cultural',
'ne_110m_admin_0_countries.zip'),
f <- tempfile())
unzip(f, exdir=tempdir())
shp <- readOGR(tempdir(), 'ne_110m_admin_0_countries')
rasterize the vector data:
r <- rasterize(shp, raster(raster(extent(shp), res=c(1, 1))))
And create some plots with levelplot:
levelplot(switch_att(r, 'continent'), col.regions=brewer.pal(8, 'Set2')) +
layer(sp.polygons(shp, lwd=0.5))
levelplot(switch_att(r, 'economy'), par.settings=BuRdTheme) +
layer(sp.polygons(shp, lwd=0.5))
EDIT
With Oscar's update to rasterVis, the switch_att hack above is no longer necessary.
devtools::install_github('oscarperpinan/rastervis')
levelplot(r, att='continent', col.regions=brewer.pal(8, 'Set2')) +
layer(sp.polygons(shp, lwd=0.5))
will produce the same figure as the first one above.
I have 10 lat and long points. With the code below, I can plot the coordinates, draw arrows in the order of their sequence and out-put a gif file that shows navigation order.
So far I was able to do this only with plot {graphics} function. because arrow {graphics} and saveGIF{animation} only seems to work with the plot function. I am wondering if its possible to this a more appropriate library such as ggmap (edit: I had mistakenly said ggplot), googleVis and etc.
library(graphics)
library(animation)
lat <- c(34.083398,34.072467,34.030237,34.597334,34.587142,34.488386,33.443484,33.946902,33.062739,32.273711,32.272611)
lon <- c(-107.907107,-106.893156,-107.971542,-105.225107,-105.13397,-103.196355,-104.52479,-103.655698,-106.0156,-107.71744,-107.713977)
coords = data.frame(lat,lon)
x <- coords$lat ; y <- coords$lon
s <- seq(length(x)-1) # one shorter than data
saveGIF({
for(s in 1:length(x)){
plot(x,y)
arrows(x[s], y[s], x[s+1], y[s+1], col = 1:s)
}
})
Yes, just remember to wrap your ggplot calls in print so they produce output. Toy example:
data=data.frame(i=1:100,x=runif(100),y=runif(100))
saveGIF({for(i in 2:100){print(ggplot(data[1:i,],aes(x=x,y=y))+geom_point())}})
Just write your code to produce each frame with ggplot2 functions and wrap in print. What did you try?
I would like to include a sequence of concentric circles as a grid in a plot of points. The goal is to give the viewer an idea of which points in the plot have approximately the same magnitude.
I created a hack to do this:
add_circle_grid <- function(g,ncirc = 10){
gb <- ggplot_build(g)
xl <- gb$panel$ranges[[1]]$x.range
yl <- gb$panel$ranges[[1]]$y.range
rmax = sqrt(max(xl)^2+max(yl)^2)
theta=seq(from=0,by=.01,to=2*pi)
for(n in 1:ncirc){
r <- n*rmax/ncirc
circle <- data.frame(x=r*sin(theta),y=r*cos(theta))
g<- g+geom_path(data=circle,aes(x=x,y=y),alpha=.2)
}
return(g+xlim(xl)+ylim(yl))
}
xy<-data.frame(x=rnorm(100),y=rnorm(100))
ggplot(xy,aes(x,y))+geom_point()
ggg<-add_circle_grid(ggplot(xy,aes(x,y))+geom_point())
print(ggg)
But I was wondering if there is a more ggplot way to do this. I also considered using polar coordinates but it does not allow me to set x- and y-limits in the same way.
Finally, I wouldn't mind little text labels indicating the radius of each circle.
EDIT
Perhaps this is asking too much but there are two other things that I would like.
The axis limits should stay the same (which can be done via ggplot_build)
Can this work with facets? As far as I can tell you would need to somehow figure out the facets if I want to add the circles dynamically.
set.seed(1)
xy <- data.frame(x=rnorm(100),y=rnorm(100))
rmax = sqrt(max(xy$x)^2+max(xy$y)^2)
theta=seq(from=0,by=.01,to=2*pi)
ncirc=10
dat.circ = do.call(rbind,
lapply(seq_len(ncirc),function(n){
r <- n*rmax/ncirc
data.frame(x=r*sin(theta),y=r*cos(theta),r=round(r,2))
}))
rr <- unique(dat.circ$r)
dat.text=data.frame(x=rr*cos(30),y=rr*sin(30),label=rr)
library(ggplot2)
ggplot(xy,aes(x,y))+
geom_point() +
geom_path(data=dat.circ,alpha=.2,aes(group=factor(r))) +
geom_text(data=dat.text,aes(label=rr),vjust=-1)
How about this with ggplot2 and grid:
require(ggplot2)
require(grid)
x<-(runif(100)-0.5)*4
y<-(runif(100)-0.5)*4
circ_rads<-seq(0.25,2,0.25)
qplot(x,y)+
lapply(circ_rads,FUN=function(x)annotation_custom(circleGrob(gp=gpar(fill="transparent",color="black")),-x,x,-x,x))+
geom_text(aes(x=0,y=circ_rads+0.1,label=circ_rads)) + coord_fixed(ratio = 1)