2D summary plot with counts as labels-CodePudding

The

But when I combine both I loose the summary:

ggplot(dat) aes(x = lon, y = lat, z = value) stat_summary_hex(bins = 5, fun = "mean", geom = "hex") stat_binhex(aes(label = ..count..), bins = 5, geom = "text")

I can achieve the opposite, counts as color and summary as labels:

ggplot(dat, aes(lon, lat, z = value)) geom_hex(bins = 5) stat_summary_hex(aes(label=..value..), bins = 5, fun = function(x) round(mean(x), 3), geom = "text")

CodePudding user response：

The problem here is that both plots share the same legend scale.

As the scales ranges are different : 0-40 vs -1.5 - 0.5, the biggest range makes values of the smallest range appear with (almost) the same color.

This is why displaying count as color works, but the opposite doesn't seem to work.

As an illustration, if you rescale the mean calculation, colors variations are visible:

rescaled_mean <- function(x) mean(x)*40 ggplot(dat) aes(x = lon, y = lat, z = value) stat_summary_hex(bins = 5, fun = "rescaled_mean", geom = "hex") stat_binhex(aes(label = ..count..), bins = 5, geom = "text") theme_bw()

CodePudding user response：

While writing the question, which took some hours of testing, I found a solution: adding a fill=NULL, or fill=mean(value) in the text one gives me what I want. Below the code and their resulting plots; the only difference is the label of the legend.

But it feels very hacky, so I would appreciate a better solution.

ggplot(dat) aes(x = lon, y = lat, z = value) stat_summary_hex(bins = 5, fun = "mean", geom = "hex") stat_binhex(aes(label = ..count.., fill = NULL), bins = 5, geom = "text") theme_bw() ggplot(dat) aes(x = lon, y = lat, z = value) stat_summary_hex(bins = 5, fun = "mean", geom = "hex") stat_binhex(aes(label = ..count.., fill = mean(value)), bins = 5, geom = "text") theme_bw()

CodePudding user response：

You could use an alternate approach of pre-assigning the hex bins prior to ggplot, here using dplyr and hexbin (which I think is what ggplot2 uses under the hood for stat_summary_hex).

library(dplyr) # Adapted from https://unconj.ca/blog/custom-hexbin-functions-with-ggplot.html # Calculate bins, which are assigned into a custom hexbin object dat_hex <- hexbin::hexbin(dat$lon, dat$lat, xbins = 5, IDs = TRUE) # extract x, y, cell#, count, and mean value for each hex dat_hex_df <- data.frame(hexbin::hcell2xy(dat_hex), cell = dat_hex@cell, count = dat_hex@count) %>% left_join(dat %>% bind_cols(cell = dat_hex@cID) %>% group_by(cell) %>% summarize(val_mean = mean(value)))

With that collected, the ggplot2 part is simpler:

ggplot(dat_hex_df, aes(x, y, fill = val_mean, label = count)) geom_hex(stat = "identity") geom_text()