I have a list of df Measurements_l for which I used to work with lapply and a function containing ggplot to plot each list :
Measurements_l <- split(Measurements,list(Measurements$Sample.type,Measurements$Site), drop=TRUE)
lapply(names(Measurements_l), function(i){
ggplot(Measurements_l[[i]], aes(Date, Activity, group = Nuclides, col = as.factor(Nuclides))) +
geom_line() +
geom_point() +
facet_grid(rows = vars(Locality)) +
xlab("Date") +
ylab(paste("Concentration in", Measurements_l[[ i ]]$Measuring.Unit[ 1 ])) +
theme(legend.title=element_blank(),
guides(col=guide_legend(ncol=1)) +
ggsave(paste(i, ".png", sep = ""), dpi = 600, width = 30, height = 22, units = "cm")
})
dev.off()
With the latest R version (4.1.2), I got some issues :
Error in `ggplot_add()`:
! Can't add `ggsave(paste(i, ".png", sep = ""), dpi = 600, width = 30, height = 20, ` to a ggplot object.
* Can't add ` units = "cm")` to a ggplot object.
Run `rlang::last_error()` to see where the error occurred.
Called from: signal_abort(cnd, .file)
Browse[1]> dev.off()
Error during wrapup: cannot shut down device 1 (the null device)
Error: no more error handlers available (recursive errors?); invoking 'abort' restart
ggsave being included in my ggplot function, I do not know how to tackle this issue. Any idea ? I do not want to rewrite all my functions in all my scripts because of this newer version.
Moreover, why is it no longer possible to use "cm" units to a ggplot object ?
REPRODUCIBLE EXAMPLE (leading to 4 graphs)
Measurements
Locality Sample Nuclides Activity Measuring Unit Date
PARIS MILK I-131 1 BQ/L 2010
PARIS MILK I-131 2 BQ/L 2020
PARIS WATER I-131 3 BQ/L 2010
PARIS WATER I-131 4 BQ/L 2020
BRUSSELS MILK I-131 5 BQ/L 2010
BRUSSELS MILK I-131 6 BQ/L 2020
BRUSSELS WATER I-131 7 BQ/L 2010
BRUSSELS WATER I-131 8 BQ/L 2020
Measurements_l <- split(Measurements,list(Measurements$Sample,Measurements$Locality), drop=TRUE)
lapply(names(Measurements_l), function(i){
ggplot(Measurements_l[[i]], aes(Date, Activity, group = Nuclides, col = as.factor(Nuclides))) +
geom_line() +
geom_point() +
facet_grid(rows = vars(Locality)) +
ggsave(paste(i, ".png", sep = ""), dpi = 600, width = 30, height = 22, units = "cm")
})
dev.off()
The following, which I had suggested in the comments, works for me:
library(ggplot2)
Measurements <- data.frame(
Locality = rep(c("PARIS", "BRUSSELS"), each = 4),
Sample = rep(rep(c("MILK", "WATER"), each = 2), 2),
Nuclides = "I-131",
Activity = 1:8,
Measuring_Unit = "BQ/L",
Date = rep(c(2010, 2020), 4)
)
Measurements_l <- split(Measurements,list(Measurements$Sample,Measurements$Locality), drop=TRUE)
lapply(names(Measurements_l), function(i){
g <- ggplot(Measurements_l[[i]],
aes(Date, Activity, group = Nuclides, col = as.factor(Nuclides))) +
geom_line() +
geom_point() +
facet_grid(rows = vars(Locality))
ggsave(paste(i, ".png", sep = ""), plot = g,
dpi = 600, width = 30, height = 22, units = "cm")
})
It yields 4 plots with the names 'WATER.BRUSSELS.png', 'WATER.PARIS.png', 'MILK.BRUSSELS.png' and 'MILK.PARIS.png' in the working directory.