Related
I am hoping someone can help me with the formating from phylo.to.plot() or suggest another method that can produce a similar output.
I have followed tutorial(s) here to produce an output but it seems difficult to alter the resulting figures.
Briefly these are my questions. I will expand further below.
How to plot a subregion of a "WorldHires" map, not entire region?
Change the shape of the points on the map, but maintain the colour?
Add gradient of continuous variable to map
Reproducible example:
Here is a very basic tree with some randomly assigned geographic locations
myTree <- ape::read.tree(text='((A, B), ((C, D), (E, F)));')
plot(myTree)
# It needs to be rooted for `phylo.to.map()` to work
myTree$branch.length = NULL
rooted_cladogram = ape::compute.brlen(myTree)
# Sample information
Sample <- c("A","B","C","D","E","F")
coords <- matrix(c(56.001966,57.069417,50.70228, 51.836213, 54.678997, 54.67831,-5.636926,-2.47805,-3.8975018, -2.235444,-3.4392211, -1.751833), nrow=6, ncol=2)
rownames(coords) <- Sample
head(coords)
## Plot phylo.to.map
obj<-phylo.to.map(rooted_cladogram,coords,database="worldHires", regions="UK",plot=FALSE,xlim=c(-11,3), ylim=c(49,59),direction="rightwards")
plot(obj,direction="rightwards",fsize=0.5,cex.points=c(0,1), lwd=c(3,1),ftype="i")
Plot output here:
Question 1: How do I plot a subregion of a "WorldHires" map, not the entire region?
I would like to only have mainland Britain which is a subregion of the "UK" in the WorldHires database. To access it normally I would do:
map1 <- ggplot2::map_data(map = "worldHires", region = c("UK"),xlim=c(-11,3), ylim=c(49,59))
GB <- subset(map1, subregion=="Great Britain")
# Plot
GB_plot<- ggplot(GB )+
geom_polygon(aes(x = long, y = lat, group = group), fill = "white", colour = "black")+
theme_classic()+
theme(axis.line=element_blank(),
axis.text=element_blank(),
axis.ticks=element_blank(),
axis.title=element_blank(),
panel.border = element_blank())
Which looks like this:
I have tried but it ignore the subregion argument.
obj<-phylo.to.map(ttree,coords,database="worldHires", regions="UK", subregion="Great Britain",plot=FALSE,xlim=c(-11,3), ylim=c(49,59),direction="rightwards")
Is there a way to provide it directly with a map instead of using WorldHires?
Question 2: How do I change the shape of the points on the map but keep maintain the colour?
I want to use shapes on the map to indicate the 3 major clade on my tree geographically. However, when I add a pch argument in, it correctly changes the shapes but the points then become black instead of following the colour that they were before. The lines from the tree to the map maintain the colour, it is just the points themselves that seem to turn black.
This is how I have tried to change the shape of the points:
# Original code - points
cols <-setNames(colorRampPalette(RColorBrewer::brewer.pal(n=6, name="Dark2"))(Ntip(myTree)),myTree$tip.label)
obj<-phylo.to.map(rooted_cladogram,coords,database="worldHires", regions="UK",plot=FALSE,xlim=c(-11,3), ylim=c(49,59),direction="rightwards")
plot(obj,direction="rightwards",fsize=0.5,cex.points=c(0,1), colors=cols,lwd=c(3,1),ftype="i")
Point and lines are coloured. I would like to change the shape of points
# Code to change points = but points are no longer coloured
shapes <- c(rep(2,2),rep(1,2),rep(0,2))
obj<-phylo.to.map(rooted_cladogram,coords,database="worldHires", regions="UK",plot=FALSE,xlim=c(-11,3), ylim=c(49,59),direction="rightwards")
plot(obj,direction="rightwards",fsize=0.5,cex.points=c(0,1), colors=cols,pch=shapes,lwd=c(3,1),ftype="i")
Output: The shapes are changed but they are no longer coloured in:
Question 3: How do I add a gradient to the map?
Given this fake dataset, how to I create a smoothed gradient of the value variable?
Any help and advice on this would be very much appreciated.
It would also be useful to know how to change the size of points
Thank you very much in advance,
Eve
I improved (somewhat) on my comments by using the map you made in your question. Here's the code:
library(mapdata)
library(phytools)
library(ggplot2)
myTree <- ape::read.tree(text='((A, B), ((C, D), (E, F)));')
plot(myTree)
# It needs to be rooted for `phylo.to.map()` to work
myTree$branch.length = NULL
rooted_cladogram = ape::compute.brlen(myTree)
# Sample information
Sample <- c("A","B","C","D","E","F")
coords <- matrix(
c(56.001966,
57.069417,
50.70228,
51.836213,
54.678997,
54.67831,
-5.636926,
-2.47805,
-3.8975018,
-2.235444,
-3.4392211,
-1.751833),
nrow=6,
ncol=2)
rownames(coords) <- Sample
head(coords)
obj <- phylo.to.map(
rooted_cladogram,
coords,
database="worldHires",
regions="UK",
plot=FALSE,
xlim=c(-11,3),
ylim=c(49,59),
direction="rightwards")
# Disable default map
obj2 <- obj
obj2$map$x <- obj$map$x[1]
obj2$map$y <- obj$map$y[1]
# Set plot parameters
cols <- setNames(
colorRampPalette(
RColorBrewer::brewer.pal(n=6, name="Dark2"))(Ntip(myTree)),myTree$tip.label)
shapes <- c(rep(2,2),rep(1,2),rep(0,2))
sizes <- c(1, 2, 3, 4, 5, 6)
# Plot phylomap
plot(
obj2,
direction="rightwards",
fsize=0.5,
cex.points=0,
colors=cols,
pch=shapes,
lwd=c(3,1),
ftype="i")
# Plot new map area that only includes GB
uk <- map_data(
map = "worldHires",
region = "UK")
gb <- uk[uk$subregion == "Great Britain",]
points(x = gb$long,
y = gb$lat,
cex = 0.001)
# Plot points on map
points(
x = coords[,2],
y = coords[,1],
pch = shapes,
col = cols,
cex = sizes)
e: Use sf object instead of points to illustrate GB. It is tough to provide more advice beyond this on how to add symbology for your spatially varying variable, but sf is popular and very well documented, e.g. https://r-spatial.github.io/sf/articles/sf5.html. Let me know if you have any other questions!
ee: Added lines to plot name and symbol on tips.
eee: Added gradient dataset to map.
library(phytools)
library(mapdata)
library(ggplot2)
library(sf)
myTree <- ape::read.tree(text='((A, B), ((C, D), (E, F)));')
plot(myTree)
# It needs to be rooted for `phylo.to.map()` to work
myTree$branch.length = NULL
rooted_cladogram = ape::compute.brlen(myTree)
# Sample information
Sample <- c("A","B","C","D","E","F")
coords <- matrix(c(56.001966,57.069417,50.70228, 51.836213, 54.678997, 54.67831,-5.636926,-2.47805,-3.8975018, -2.235444,-3.4392211, -1.751833), nrow=6, ncol=2)
rownames(coords) <- Sample
head(coords)
obj <- phylo.to.map(
rooted_cladogram,
coords,
database="worldHires",
regions="UK",
plot=FALSE,
xlim=c(-11,3),
ylim=c(49,59),
direction="rightwards")
# Disable default map
obj2 <- obj
obj2$map$x <- obj$map$x[1]
obj2$map$y <- obj$map$y[1]
## Plot tree portion of map
# Set plot parameters
cols <- setNames(
colorRampPalette(
RColorBrewer::brewer.pal(n=6, name="Dark2"))(Ntip(myTree)),myTree$tip.label)
shapes <- c(rep(2,2),rep(1,2),rep(0,2))
sizes <- c(1, 2, 3, 4, 5, 6)
# Plot phylomap
plot(
obj2,
direction="rightwards",
fsize=0.5,
cex.points=0,
colors=cols,
pch=shapes,
lwd=c(3,1),
ftype="i")
tiplabels(pch=shapes, col=cols, cex=0.7, offset = 0.2)
tiplabels(text=myTree$tip.label, col=cols, cex=0.7, bg = NA, frame = NA, offset = 0.2)
## Plot GB portion of map
# Plot new map area that only includes GB
uk <- map_data(map = "worldHires", region = "UK")
gb <- uk[uk$subregion == "Great Britain",]
# Convert GB to sf object
gb_sf <- st_as_sf(gb, coords = c("long", "lat"))
# Covert to polygon
gb_poly <- st_sf(
aggregate(
x = gb_sf$geometry,
by = list(gb_sf$region),
FUN = function(x){st_cast(st_combine(x), "POLYGON")}))
# Add polygon to map
plot(gb_poly, col = NA, add = TRUE)
## Load and format gradient data as sf object
# Load data
g <- read.csv("gradient_data.txt", sep = " ", na.strings = c("NA", " "))
# Check for, then remove NAs
table(is.na(g))
g2 <- g[!is.na(g$Lng),]
# For demonstration purposes, make dataset easier to manage
# Delete this sampling line to use the full dataset
g2 <- g2[sample(1:nrow(g2), size = 1000),]
# Create sf point object
gpt <- st_as_sf(g2, coords = c("Lng", "Lat"))
## Set symbology and plot
# Cut data into 5 groups based on "value"
groups <- cut(gpt$value,
breaks = seq(min(gpt$value), max(gpt$value), len = 5),
include.lowest = TRUE)
# Set colors
gpt$colors <- colorRampPalette(c("yellow", "red"))(5)[groups]
# Plot
plot(gpt$geometry, pch = 16, col = gpt$colors, add = TRUE)
## Optional legend for gradient data
# Order labels and colors for the legend
lev <- levels(groups)
# Used rev() here to make colors in correct order
fil <- rev(levels(as.factor(gpt$colors)))
legend("topright", legend = lev, fill = fil, add = TRUE)
## Plot sample points on GB
# Plot points on map
points(
x = coords[,2],
y = coords[,1],
pch = shapes,
col = cols,
cex = sizes)
see here for more info on gradient symbology and legends: R: Gradient plot on a shapefile
I am trying to plot in R a raster layer with lines/polygon objects in R and each time I fail miserably with errors. I tried to do this in base R, ggplot2 and using levelplot but can't get the right result.
Source data can be found here.
What I need to do in the plot (all in one plot) is to:
1) zoom in a certain area defined as NIG. T
2) Display raster r values on a scale with cuts intervals.
3) Plot the country boundaries(shpAfr in base R and ggplot2 or world.outlines.spin levelplot). 4) Finally, include shpWater polygon layer (with col="blue" fill and contours).
library(raster)
library(maptools)
library(rasterVis)
library(viridis)
library(sf)
library(rgdal)
library(ggplot2)
r <- raster("raster_example.tif")
crs(r) <- "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +to wgs84=0,0,0"
NIG <- c(2,14.5,4,14)
Reg_name <- "Nigeria"
shpAfr <- readOGR(dsn="Africa.shp")
proj4string(shpAfr) # describes data’s current coordinate reference system
#st_read(system.file("shape/nc.shp", package="sf"))
# Import water polygon
shpWater <- readOGR(dsn="waterbodies_africa.shp")
shpWater.count <- nrow(shpWater#data)
shpWater$id <- 1:shpWater.count
shpWater.fort <- fortify(shpWater, region='id')
# Import Africa admin map
shpAfr <- readOGR(dsn="Africa.shp")
shpAfr.count <- nrow(shpAfr#data)
shpAfr$id <- 1:shpAfr.count
shpAfr.fort <- fortify(shpAfr, region='id')
# Set colour intervals for plotting:
cuts=seq(0,1,0.1) #set breaks
Trying in base R, my problem is I can get the water shape fill in the right colour (fill and contour should be blue). If I try to plot both wrld_simpl and shpWater as polygon() I get into even bigger troubles.
plot(r, xlim = NIG[1:2], ylim = NIG[3:4],
breaks=cuts, col = rev(plasma(11)))
lines(wrld_simpl,lwd = 1.5)
lines(shpWater, col="blue") # works but cannot fill the polygon
polygon(shpWater, col = "blue", border = "blue") # getting error here
Error in as.double(y) :
cannot coerce type 'S4' to vector of type 'double'
Ok, so now I try ggplot2, but I can't find a way to include a raster here without getting an error.
lon <- seq(r#extent#xmin,r#extent#xmax,
(r#extent#xmax-r#extent#xmin)/r#ncols)
lat <- seq(r#extent#ymin,r#extent#ymax,
(r#extent#ymax-r#extent#ymin)/r#nrows)
Plot1 <- ggplot()+
geom_polygon(aes(x = long, y = lat, group=id),
data = shpAfr.fort, color ="grey27", fill ="grey",
alpha = .4, size = .2)+
geom_raster(data = test, aes(fill=values))+ ## here it goes bad
#geom_tile(data=test_df, aes(x=x, y=y, fill=value), alpha=0.8) +
#scale_fill_viridis() +
geom_polygon(aes(x = long, y = lat, group=id),
data = shpWater.fort, color ="lightskyblue2", fill ="lightskyblue2",
size = .2)+coord_equal()+
theme_minimal()+
coord_map(xlim = Region[[3]][1:2],ylim = Region[[3]][3:4])
plot(Plot1)
Finally, I tried the levelplot and AGAIN failed.
mapTheme <- rasterTheme(region = rev(brewer.pal(10, "RdBu")))
# Get world outlines:
world.outlines <- map("world", plot=FALSE)
world.outlines.sp <- map2SpatialLines(world.outlines, proj4string = CRS("+proj=longlat"))
# Plot raster and polygon:
Plot2 <- levelplot(r,par.settings = mapTheme,pretty=TRUE,margin = F,
xlim = NIG[1:2],ylim = NIG[3:4],
col.regions=colorRampPalette(c("light blue","blue", "red")),
main=paste0("test")) + layer(sp.lines(world.outlines.sp, col = "black", lwd = 0.5))
plot(Plot2 + layer(sp.lines(world.outlines.sp, col = "black", lwd = 0.5))
#Error: Attempted to create layer with no stat.
My results so far:
1) first image does not have the polygons filled with blue
2) second image has clearly world outlines not in the right location
:
You would have probably have had answers a lot earlier if you had made a simple reprex, e.g. like this
library(raster)
r <- raster(res=1/12)
values(r) <- sample(100, ncell(r), replace=TRUE)
filename <- system.file("external/lux.shp", package="raster")
v <- shapefile(filename)
zoom in a certain area
One way to zoom is to use crop (alternatively use the ext argument in plot)
x <- crop(r, v)
Display raster r values on a scale with cuts intervals
cuts <- c(0,20,60,100)
plot(x, breaks=cuts, col=rainbow(3))
or
y <- cut(x, cuts)
Plot the country boundaries
lines(v)
Finally, include polygon layer (with col="blue" fill and contours).
plot(v[c(1,3),], col="blue", border="red", lwd=2, add=TRUE)
6 months later but I feel this question. My two thoughts are (1) I have had luck with plotting geom_sf and geom_stars together. You have to change your raster to a df before changing to a geom_stars. and (2) regardless of method, you need all datasets in the same projection - check with crs() and set all to the same with st_transform()
I didn't actually test this with your data but something like:
make raster into a df
test.df = as.data.frame (test, xy=TRUE) # Convert to data.frame, keeping the
coordinates
class(test.df)
convert to geom_stars
test.stars = st_as_stars(test.df)
try your plot
Plot1 <- ggplot()+
geom_stars(data = test, aes(fill=values))+ #need to plot raster first I think?
scale_fill_identity( name = "", breaks = cuts,labels = "")+
geom_sf(data = shpAfr.fort, color ="grey27", size = .2)+
geom_sf(data = shpWater.fort, color ="lightskyblue2", fill
="lightskyblue2", size = .2)+
theme_minimal()+
coord_sf( xlim = NIG[1:2], ylim = NIG[3:4]),expand = FALSE)
Plot1
I'm trying to plot two maps side by side using sf::plot and I can't manage to get it to work. There is two problems, the first one is that the plots are made on top of each other instead of side by side and the second is that I lose the legend.
Here is a example and more explanations.
library(sf)
library(dplyr)
# preparing the shapefile
nc <- st_read(system.file("gpkg/nc.gpkg", package="sf"), quiet = TRUE) %>%
select(AREA, PERIMETER) %>%
mutate(AREA = as.factor(AREA<median(AREA)))
If I plot every field independently:
plot(nc[,1])
plot(nc[,2])
Both images are nice, with a legend and all, but I want both on the same panel. sf::plot offers this feature built in as explained in https://r-spatial.github.io/sf/articles/sf5.html#geometry-with-attributes-sf:
plot(nc)
I lose the legend and they are on top of each other instead of side by side. In ?plot you can read:
For more control over individual maps, set parameter mfrow with par
prior to plotting, and plot single maps one by one.
But when I do, it doesn't work:
par(mfrow=c(1,2))
plot(nc[,1])
plot(nc[,2])
par(mfrow=c(1,1))
Any idea how to plot 2 maps side by side with sf?
Finally, it was a problem in the documentation. To be able to use par with sf::plot you need to do either:
par(mfrow=c(1,2))
plot(st_geometry(nc[,1]))
plot(st_geometry(nc[,2]))
par(mfrow=c(1,1))
or
par(mfrow=c(1,2))
plot(nc[,1], key.pos = NULL, reset = FALSE)
plot(nc[,2], key.pos = NULL, reset = FALSE)
par(mfrow=c(1,1))
However, you lose the colors in the first case and lose the legend in both cases. You have to manage it yourself manually.
see: https://github.com/r-spatial/sf/issues/877
I didn`t found the solution in sf package. I found this that probably works fine for you
library(ggplot2)
area<-ggplot() + geom_sf(data = nc[,1], aes(fill = AREA))
perim<-ggplot() + geom_sf(data = nc[,2], aes(fill = PERIMETER))
gridExtra::grid.arrange(area,perim,nrow=1)
To add to #Bastien's answer, you can add a legend manually. Here's a simple function that will add a continuous legend using the leaflet and plotrix libraries:
addLegendToSFPlot <- function(values = c(0, 1), labels = c("Low", "High"),
palette = c("blue", "red"), ...){
# Get the axis limits and calculate size
axisLimits <- par()$usr
xLength <- axisLimits[2] - axisLimits[1]
yLength <- axisLimits[4] - axisLimits[3]
# Define the colour palette
colourPalette <- leaflet::colorNumeric(palette, range(values))
# Add the legend
plotrix::color.legend(xl=axisLimits[2] - 0.1*xLength, xr=axisLimits[2],
yb=axisLimits[3], yt=axisLimits[3] + 0.1 * yLength,
legend = labels, rect.col = colourPalette(values),
gradient="y", ...)
}
To use the above function with #Bastien's code:
# Load required libraries
library(sf) # Working spatial data
library(dplyr) # Processing data
library(leaflet) # Has neat colour palette function
library(plotrix) # Adding sf like legend to plot
# Get and set plotting window dimensions
mfrowCurrent <- par()$mfrow
par(mfrow=c(1,2))
# Add sf plot with legend
plot(nc[,1], key.pos = NULL, reset = FALSE)
addLegendToSFPlot(values = c(0, 1),
labels = c("False", "True"),
palette = c("lightseagreen", "orange"))
# Add sf plot with legend
plot(nc[,2], key.pos = NULL, reset = FALSE)
valueRange <- range(nc[, 2, drop = TRUE])
addLegendToSFPlot(values = seq(from = valueRange[1], to = valueRange[2], length.out = 5),
labels = c("Low", "", "Medium", "", "High"),
palette = c("blue", "purple", "red", "yellow"))
# Reset plotting window dimensions
par(mfrow=mfrowCurrent)
I have a SpatialPolygonsDataFrame with 213 Ecoregions to plot.
My issue is that I'm not able to organize the legend in a way that I could indeed read the legend. I'm new to r and I've been trying this for 2 days now, I feel really stupid... I wonder if anyone could give me some hint on how to achieve this goal.
#### Download and unzip ecoregions ####
#the reference for this ecoregions data: https://doi.org/10.1093/biosci/bix014
#Don't forget to change the path to a path of your own
dir_eco<-"C:/Users/thai/Desktop/Ecologicos/w2"
download.file("https://storage.googleapis.com/teow2016/Ecoregions2017.zip",
file.path(paste0(dir_eco,"/","Ecoregions2017.zip",sep="")))
unzip("Ecoregions2017.zip")
#Read this shapefile
#install.packages("rgdal")
library(rgdal)
ecoreg_shp<- readOGR("Ecoregions2017.shp")
#Crop to a smaller extent
xmin=-120; xmax=-35; ymin=-60; ymin2=-40; ymax=35
limits2 <- c(xmin, xmax, ymin2, ymax) # Just from mexico to Uruguay.
ecoreg_shp<-crop(ecoreg_shp,limits2)
# Color palette - one color for each attribute level
n <- 213
color = grDevices::colors()[grep('gr(a|e)y', grDevices::colors(), invert = T)]
# pie(rep(1,n), col=sample(color, n)) #just to take a look at the colors
col_samp<-sample(color, n)
ecoreg_shp#data$COLOR<-col_samp #put the colors in the polygons data frame
#Plot
png(file="29_ecoreg2.png", width=3000, height=3000, units="px", res=300)
par(mar=c(50,0.3,1.5,0),pty="s")
spplot(ecoreg_shp, zcol = "ECO_NAME", col.regions = ecoreg_shp#data$COLOR,
colorkey = list(space = "bottom", height = 1))
dev.off()
Now, this is how this plot looks like:
I've managed to put this legend at the right of the map, but gets also too overlayed... I've tried to do colorkey = FALSE and set a separate legend...
#Plot the map with no legend
spplot(ecoreg_shp, zcol = "ECO_NAME", col.regions = ecoreg_shp#data$COLOR,
colorkey = FALSE)
#Now, just the legend
legend("bottom",legend=ecoreg_shp#data$ECO_NAME,fill=ecoreg_shp#data$COLOR, ncol=3)
But doesn't work.. I get a message that plot.new has not been called yet
I've managed to do a lot of things with the legend, but I can't make it good... Like the legend item below the map in 2 or 3 columns in a long figure... Actually doesn't matter the format at all, I just wanted to be able to make a good figure. Can anyone point me in some direction? I'm trying to learn ggplot2, but I don't know r enough yet for using such a difficult package.
Thank you in advance, any tip is much appreciated.
As said in the comments, you will not really be able to distinguish between colors. You should define a classification with multiple levels and choose similar colors for similar ecoregions.
Nevertheless, you can create an image only for this long legend as follows. I used a reproducible example as I do not have your dataset but I use the same names as yours so that you can directly use the script:
library(sp)
library(rgdal)
n <- 213
dsn <- system.file("vectors", package = "rgdal")[1]
ecoreg_shp <- readOGR(dsn = dsn, layer = "cities")
ecoreg_shp <- ecoreg_shp[1:n,]
# Color palette - one color for each attribute level
color <- grDevices::colors()[grep('gr(a|e)y', grDevices::colors(), invert = T)]
col_samp <- sample(color, n)
ecoreg_shp#data$COLOR <- col_samp #put the colors in the polygons data frame
ecoreg_shp#data$ECO_NAME <- ecoreg_shp#data$NAME
# Define a grid to plot the legend
grid.dim <- c(45, 5)
ecoreg_shp#data$ROW <- rep(rev(1:grid.dim[1]), by = grid.dim[2], length.out = n)
ecoreg_shp#data$COL <- rep(1:grid.dim[2], each = grid.dim[1], length.out = n)
# Plot the legend
png(file = "legend.png",
width = 21, height = 29.7,
units = "cm", res = 300)
par(mai = c(0, 0, 0, 0))
plot(ecoreg_shp#data$COL,
ecoreg_shp#data$ROW,
pch = 22, cex = 2,
bg = ecoreg_shp#data$COLOR,
xlim = c(0.8, grid.dim[2] + 1),
xaxs = "i")
text(ecoreg_shp#data$COL,
ecoreg_shp#data$ROW,
ecoreg_shp#data$ECO_NAME,
pos = 4, cex = 0.75)
dev.off()
The result:
I found many resources on how to draw Venn diagrams in R. Stack Overflow has a lot of them. However, I still can't draw my diagrams the way I want. Take the following code as an example:
library("VennDiagram")
A <- 1:4
B <- 3:6
d <- list(A, B)
vp <- venn.diagram(d, fill = c("white", "white"), alpha = 1, filename = NULL,
category.names=c("A", "B"))
grid.draw(vp)
I want the intersection between the sets to be red. However, if I change any of the white colors to red, I get the following:
vp_red <- venn.diagram(d, fill = c("red", "white"), alpha = 1, filename = NULL,
category.names=c("A", "B"))
grid.draw(vp_red)
That's not quite what I want. I want only the intersection to be red. If I change the alpha, this is what I get:
vp_alpha <- venn.diagram(d, fill = c("red", "white"), alpha = 0.5, filename = NULL,
category.names=c("A", "B"))
grid.draw(vp_alpha)
Now I have pink in my intersection. This is not what I want as well. What I want is something like this image from Wikipedia:
How can I do this? Maybe VennDiagram package can't do it and I need some other package, but I've been testing different ways to do it, and I'm not being able to find a solution.
I will show two different possibilities. In the first example, polyclip::polyclip is used to get the intersection. In the second example, circles are converted to sp::SpatialPolygons and we get the intersection using rgeos::gIntersection. Then we re-plot the circles and fill the intersecting area.
The resulting object when using venn.diagram is
"of class gList containing the grid objects that make up the diagram"
Thus, in both cases we can grab relevant data from "vp". First, check the structure and list the grobs of the object:
str(vp)
grid.ls()
# GRID.polygon.234
# GRID.polygon.235
# GRID.polygon.236 <~~ these are the empty circles
# GRID.polygon.237 <~~ $ col : chr "black"; $ fill: chr "transparent"
# GRID.text.238 <~~ labels
# GRID.text.239
# GRID.text.240
# GRID.text.241
# GRID.text.242
1. polyclip
Grab x- and y-values, and put them in the format required for polyclip:
A <- list(list(x = as.vector(vp[[3]][[1]]), y = as.vector(vp[[3]][[2]])))
B <- list(list(x = as.vector(vp[[4]][[1]]), y = as.vector(vp[[4]][[2]])))
Find intersection:
library(polyclip)
AintB <- polyclip(A, B)
Grab labels:
ix <- sapply(vp, function(x) grepl("text", x$name, fixed = TRUE))
labs <- do.call(rbind.data.frame, lapply(vp[ix], `[`, c("x", "y", "label")))
Plot it!
plot(c(0, 1), c(0, 1), type = "n", axes = FALSE, xlab = "", ylab = "")
polygon(A[[1]])
polygon(B[[1]])
polygon(AintB[[1]], col = "red")
text(x = labs$x, y = labs$y, labels = labs$label)
2. SpatialPolygons and gIntersection
Grab the coordinates of the circles:
# grab x- and y-values from first circle
x1 <- vp[[3]][["x"]]
y1 <- vp[[3]][["y"]]
# grab x- and y-values from second circle
x2 <- vp[[4]][["x"]]
y2 <- vp[[4]][["y"]]
Convert points to SpatialPolygons and find their intersection:
library(sp)
library(rgeos)
p1 <- SpatialPolygons(list(Polygons(list(Polygon(cbind(x1, y1))), ID = 1)))
p2 <- SpatialPolygons(list(Polygons(list(Polygon(cbind(x2, y2))), ID = 2)))
ip <- gIntersection(p1, p2)
Plot it!
# plot circles
plot(p1, xlim = range(c(x1, x2)), ylim = range(c(y1, y2)))
plot(p2, add = TRUE)
# plot intersection
plot(ip, add = TRUE, col = "red")
# add labels (see above)
text(x = labs$x, y = labs$y, labels = labs$label)
I'm quite sure you could work directly on the grobs using clipping functions in grid or gridSVG package.
It's very easy in eulerr R package
library(eulerr)
plot(euler(c("A"=5,"B"=4,"A&B"=2)),quantities = TRUE,fills=c("white","white","red"))
euler set colours