Save plots created by for-loop to individual folders with the same name in R

Question

I'm working with time series data for species counts that I need to plot and save to individual folders that have already been created. My code makes 1 plot for each species in order of species rank (ranking of most abundant to least). This is also the naming scheme of each plot file and the folders. I need help telling R to save each plot to the right folder. The for-loop is taken from my other script for making heatmaps. I've tried to adapt it for plotting my time series code, but I get this error:

Error in getPlot1(data = dataList[[run]], folder_name[run], fileName = paste0(file.path(folder_name[run]),  : 
  unused arguments (folder_name[run], fileName = paste0(file.path(folder_name[run]), "/", filenameVal[run]))

My code:

library(ggprism)
library(dplyr)
library(ggplot2)

setwd('C:/Users/.../CSV')

dat <- read.csv('Epifauna - Zero_counts_&_Env._data.csv')

make_summary=function(data,spToSum) {
  newdat <- filter(data,common_name %in% spToSum)
  cdata2 <- plyr::ddply(newdat, c("CYR", "Season"), summarise,
                        N    = length(num),
                        n_mean = mean(num),
                        n_median = median(num),
                        sd   = sd(num),
                        se   = sd / sqrt(N))
  cdata2 <- cdata2 %>% mutate(CYR=ifelse(Season=="WET",CYR+0.5,CYR))
}


interleave <- function(x,y){
  lx <- length(x)
  ly <- length(y)
  n <- max(lx,ly)
  as.vector(rbind(rep(x, length.out=n), rep(y, length.out=n)))
}


CYR <- seq(2005,2021.5,0.5)
labs <- interleave(seq(2005,2021,by=1), "")

  
getPlot1<-function(data)  {
  ggplot(data, aes(x = CYR, y = n_mean, color = Season)) +
    annotate(geom = "rect", xmin = 2010, xmax = 2010.25, ymin = -Inf, ymax = Inf,
             fill = "lightblue", colour = NA, alpha = 0.4) +
    annotate(geom = "rect", xmin = 2013.5, xmax = 2013.75, ymin = -Inf, ymax = Inf,
             fill = "lightgreen", colour = NA, alpha = 0.4) +
    annotate(geom = "rect", xmin = 2017.5, xmax = 2017.75, ymin = -Inf, ymax = Inf,
             fill = "#E0E0E0", colour = NA, alpha = 0.4) +
    annotate(geom = "rect", xmin = 2011.5, xmax = 2011.75, ymin = -Inf, ymax = Inf,
             fill = "pink", colour = NA, alpha = 0.4) +
    annotate(geom = "rect", xmin = 2015.5, xmax = 2015.75, ymin = -Inf, ymax = Inf,
             fill = "pink", colour = NA, alpha = 0.4) +
    annotate(geom = "rect", xmin = 2018.5, xmax = 2018.75, ymin = -Inf, ymax = Inf,
             fill = "orange", colour = NA, alpha = 0.2) +
    geom_errorbar(aes(ymin=n_mean-se, ymax=n_mean+se), 
                  width=.2, 
                  color = "black") +
    geom_point(color = "black",
               shape = 21, 
               size = 3,
               aes(fill = Season)) +
    ylim(0, NA) + 
    scale_fill_manual(values=c("white", "#C0C0C0")) + 
    scale_x_continuous(breaks= CYR, labels = labs) +
    theme(panel.border = element_rect(fill = NA, color = "black"),
          panel.background = element_blank(), 
          panel.grid.major = element_blank(),
          panel.grid.minor = element_blank()) +
    labs(x= NULL, y = "Mean count") +
    ggtitle(common) +
    theme(plot.title = element_text(hjust = 0.5)) +
    theme(axis.text.y = element_text(size = 10, face = "bold")) +
    theme(axis.text.x = element_text(size = 8, face = "bold")) + 
    theme(axis.title = element_text(size = 14, face = "bold"))
}

spSummary<- dat %>% group_by(common_name) %>%
  summarize(total.number=sum(num,na.rm=TRUE),
            observations=length(num[num>0 &!is.na(num)])) %>%
  arrange(-total.number)



splist<-spSummary$common_name[spSummary$observations>=1]
length(splist)

setwd('.../Epifauna') # Location of 154 folders with naming scheme

# Folder names: "1. Rainwater Killifish", "2. Zostera Shrimp", etc...
# Number preceding name is abundance rank

dataList<-list()
filenameVal<-paste0(1:length(splist),". ",splist," - time_series_plot.png")
folder_name<-paste0(1:length(splist),". ",splist)

  
for(run in 1:length(splist)) {
  dataList[[run]]<-make_summary(dat,splist[run])
  # dir.create(file.path(folder_name[run]), recursive = TRUE) # Code that created folders
  getPlot1(data=dataList[[run]],folder_name[run], fileName=paste0(file.path(folder_name[run]), "/", filenameVal[run]))
  print(paste(run,splist[run]))
}

Data (CYR = Calendar year 2005-2021, Season = DRY/WET):

> head(dat, 10)
    CYR Season                    common_name num
1  2005    DRY                 Sergeant Major   10
2  2005    DRY                     Lined Sole   0
3  2005    DRY                       Bonefish   0
4  2005    DRY Snapping Shrimp (A. angulosus)   6
5  2005    DRY Snapping Shrimp (A armillatus)   0
6  2005    DRY     Snapping Shrimp (A carlae)   0
7  2005    DRY      Estuarine Snapping Shrimp   1
8  2005    DRY        Bigclaw Snapping Shrimp   0
9  2005    WET      Grass Shrimp (A normanni)   1
10 2006    WET      Grass Shrimp (A nuttingi)   0

You get this error because your function takes only one argument `data` while you call it with multiple arguments, i.e. folder_name and fileName. Also your code contains no code to actually save the plot. Maybe you want to have a look at [Save multiple ggplots using a for loop](https://stackoverflow.com/questions/26034177/save-multiple-ggplots-using-a-for-loop) — stefan, Jul 28 '22 at 16:41
@MichaelRoswell, not sure. I have that function in my code, but I use to create the folders with my other heatmap code (I therefore commented it out here). Will it also direct the plots to go in the right place? — Nate, Jul 28 '22 at 17:12
@Nate, check out `?dir.create`. This is how you can create a new directory from R. If you need to name both files and folders programatically, you'll probably need to create the `path` argument as a function of the input data somehow. — Michael Roswell, Jul 28 '22 at 17:14
Ok. And I'm just naming the files. Folders have already been made. — Nate, Jul 28 '22 at 17:16

score 0 · Accepted Answer · answered Jul 28 '22 at 22:02

Got it to work:

library(ggprism)
library(dplyr) # for the %>% use
library(ggplot2)




setwd('C:.../CSV')

dat <- read.csv('Epifauna - Zero_counts_&_Env._data.csv')

MakeSummary=function(data,spToSum) {
  newdat <- filter(data,common_name %in% spToSum)
  cdata2 <- plyr::ddply(newdat, c("CYR", "Season"), summarise,
                        N    = length(num),
                        n_mean = mean(num),
                        n_median = median(num),
                        sd   = sd(num),
                        se   = sd / sqrt(N))
  cdata2 <- cdata2 %>% mutate(CYR=ifelse(Season=="WET",CYR+0.5,CYR))
}


interleave <- function(x,y){
  lx <- length(x)
  ly <- length(y)
  n <- max(lx,ly)
  as.vector(rbind(rep(x, length.out=n), rep(y, length.out=n)))
}


CYR <- seq(2005,2021.5,0.5)
labs <- interleave(seq(2005,2021,by=1), "")


getPlot1<-function(data)  {
  ggplot(data, aes(x = CYR, y = n_mean, color = Season)) +
    annotate(geom = "rect", xmin = 2010, xmax = 2010.25, ymin = -Inf, ymax = Inf,
             fill = "lightblue", colour = NA, alpha = 0.4) +
    annotate(geom = "rect", xmin = 2013.5, xmax = 2013.75, ymin = -Inf, ymax = Inf,
             fill = "lightgreen", colour = NA, alpha = 0.4) +
    annotate(geom = "rect", xmin = 2017.5, xmax = 2017.75, ymin = -Inf, ymax = Inf,
             fill = "#E0E0E0", colour = NA, alpha = 0.4) +
    annotate(geom = "rect", xmin = 2011.5, xmax = 2011.75, ymin = -Inf, ymax = Inf,
             fill = "pink", colour = NA, alpha = 0.4) +
    annotate(geom = "rect", xmin = 2015.5, xmax = 2015.75, ymin = -Inf, ymax = Inf,
             fill = "pink", colour = NA, alpha = 0.4) +
    annotate(geom = "rect", xmin = 2018.5, xmax = 2018.75, ymin = -Inf, ymax = Inf,
             fill = "orange", colour = NA, alpha = 0.2) +
    # geom_line(aes(y = n_mean), size = 1) + # Connect points
    geom_errorbar(aes(ymin=n_mean-se, ymax=n_mean+se), 
                  width=.2, 
                  color = "black") +
    geom_point(color = "black",
               shape = 21, 
               size = 3,
               aes(fill = Season)) +
    ylim(0, NA) + 
    scale_fill_manual(values=c("white", "#C0C0C0")) + 
    scale_x_continuous(breaks= CYR, labels = labs) +
    theme(panel.border = element_rect(fill = NA, color = "black"),
          panel.background = element_blank(), 
          panel.grid.major = element_blank(),
          panel.grid.minor = element_blank()) +
    labs(x= NULL, y = "Mean count") +
    theme(plot.title = element_text(hjust = 0.5)) +
    theme(axis.text.y = element_text(size = 10, face = "bold")) +
    theme(axis.text.x = element_text(size = 8, face = "bold")) + 
    theme(axis.title = element_text(size = 14, face = "bold"))
}

spSummary<- dat %>% group_by(common_name) %>%
  summarize(total.number=sum(num,na.rm=TRUE),
            observations=length(num[num>0 &!is.na(num)])) %>%
  arrange(-total.number)


splist<-spSummary$common_name[spSummary$observations>=1]
length(splist)

setwd('.../Epifauna')

dataList<-list()
filenameVal<-paste0(1:length(splist),". ",splist," - time_series_plot.png")
folder_name<-paste0(1:length(splist),". ",splist)


for(run in 1:length(splist)) {
  dataList[[run]]<-MakeSummary(dat,splist[run])
  if(!dir.exists(file.path(folder_name[run]))) dir.create(file.path(folder_name[run]), recursive = TRUE)
  plot1<-getPlot1(data=dataList[[run]])
  png(paste0(file.path(folder_name[run]), "/", filenameVal[run]), height = 5, width=7, units = "in", res = 600)
  print(plot1)
  dev.off()
  print(paste(run,splist[run]))
}

Save plots created by for-loop to individual folders with the same name in R

1 Answers1