The 4.1.2 R version leads to some issues with ggplot-CodePudding

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()

CodePudding user response：

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.