Derek Corcoran - 4 months ago 21

R Question

I have two populations A and B distributed spatially with one character Z, I want to be able to make an hexbin substracting the proportion of the character in each hexbin. Here I have the code for two theoretical populations A and B

`library(hexbin)`

library(ggplot2)

set.seed(2)

xA <- rnorm(1000)

set.seed(3)

yA <- rnorm(1000)

set.seed(4)

zA <- sample(c(1, 0), 20, replace = TRUE, prob = c(0.2, 0.8))

hbinA <- hexbin(xA, yA, xbins = 40, IDs = TRUE)

A <- data.frame(x = xA, y = yA, z = zA)

set.seed(5)

xB <- rnorm(1000)

set.seed(6)

yB <- rnorm(1000)

set.seed(7)

zB <- sample(c(1, 0), 20, replace = TRUE, prob = c(0.4, 0.6))

hbinB <- hexbin(xB, yB, xbins = 40, IDs = TRUE)

B <- data.frame(x = xB, y = yB, z = zB)

ggplot(A, aes(x, y, z = z)) + stat_summary_hex(fun = function(z) sum(z)/length(z), alpha = 0.8) +

scale_fill_gradientn(colours = c("blue","red")) +

guides(alpha = FALSE, size = FALSE)

ggplot(B, aes(x, y, z = z)) + stat_summary_hex(fun = function(z) sum(z)/length(z), alpha = 0.8) +

scale_fill_gradientn (colours = c("blue","red")) +

guides(alpha = FALSE, size = FALSE)

here is the two resulting graphs

My goal is to make a third graph with hexbins with the values of the difference between hexbins at the same coordinates but I don't even know how to start to do it, I have done something similar in the raster Package, but I need it as hexbins

Thanks a lot

Answer

You need to make sure that both plots use the exact same binning. In order to achieve this, I think it is best to do the binning beforehand and then plot the results with stat_identity / geom_hex. With the variables from your code sample you ca do:

```
## find the bounds for the complete data
xbnds <- range(c(A$x, B$x))
ybnds <- range(c(A$y, B$y))
nbins <- 30
# function to make a data.frame for geom_hex that can be used with stat_identity
makeHexData <- function(df) {
h <- hexbin(df$x, df$y, nbins, xbnds = xbnds, ybnds = ybnds, IDs = TRUE)
data.frame(hcell2xy(h),
z = tapply(df$z, h@cID, FUN = function(z) sum(z)/length(z)),
cid = h@cell)
}
Ahex <- makeHexData(A)
Bhex <- makeHexData(B)
## not all cells are present in each binning, we need to merge by cellID
byCell <- merge(Ahex, Bhex, by = "cid", all = T)
## when calculating the difference empty cells should count as 0
byCell$z.x[is.na(byCell$z.x)] <- 0
byCell$z.y[is.na(byCell$z.y)] <- 0
## make a "difference" data.frame
Diff <- data.frame(x = ifelse(is.na(byCell$x.x), byCell$x.y, byCell$x.x),
y = ifelse(is.na(byCell$y.x), byCell$y.y, byCell$y.x),
z = byCell$z.x - byCell$z.y)
## plot the results
ggplot(Ahex) +
geom_hex(aes(x = x, y = y, fill = z),
stat = "identity", alpha = 0.8) +
scale_fill_gradientn (colours = c("blue","red")) +
guides(alpha = FALSE, size = FALSE)
ggplot(Bhex) +
geom_hex(aes(x = x, y = y, fill = z),
stat = "identity", alpha = 0.8) +
scale_fill_gradientn (colours = c("blue","red")) +
guides(alpha = FALSE, size = FALSE)
ggplot(Diff) +
geom_hex(aes(x = x, y = y, fill = z),
stat = "identity", alpha = 0.8) +
scale_fill_gradientn (colours = c("blue","red")) +
guides(alpha = FALSE, size = FALSE)
```