将相对丰度添加到文件名

Question

我下面的代码为我的数据集中的每个物种绘制了一个图，但我想知道是否有一种方法可以将相对丰度添加到每个文件名的开头。（即，最丰富的物种文件“1_speciesA..”，第二丰富的物种是“2_speciesB..”，等等）。

data <- structure(list(year = c(2019, 2019, 2019, 2019, 2019, 2019, 2019, 
                        2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 
                        2019, 2019, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 
                        2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020
), season = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
                        2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 
                        1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("dry", 
                                                                                            "wet"), class = "factor"), site = structure(c(1L, 1L, 2L, 2L, 
                                                                                                                                          3L, 3L, 4L, 4L, 5L, 5L, 1L, 1L, 2L, 2L, 3L, 3L, 4L, 4L, 5L, 5L, 
                                                                                                                                          1L, 1L, 2L, 2L, 3L, 3L, 4L, 4L, 5L, 5L, 1L, 1L, 2L, 2L, 3L, 3L, 
                                                                                                                                          4L, 4L, 5L, 5L), .Label = c("1", "2", "3", "4", "5"), class = "factor"), 
common_name = structure(c(1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
                          1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
                          2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
                          1L, 2L), .Label = c("Hardhead silverside", "Sailfin molly"
                          ), class = "factor"), num = c(0, 1, 0, 12, 0, 12, 0, 7, 0, 
                                                        13, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
                                                        0, 0, 6, 0, 2, 0, 2, 0, 15, 0, 3, 0)), class = "data.frame", row.names = c(NA, 
                                                                                                                                   -40L))


allcommon <- unique(data$common_name)


#All species
for(common in allcommon){
  
  # Select species
  sp <- subset(data,common_name == common,
               select = c(year,
                          season,
                          site,
                          common_name,
                          num))
  
  cdata2 <- plyr::ddply(sp, c("year", "season"), summarise,
                        N    = length(num),
                        n_mean = mean(num),
                        n_median = median(num),
                        sd   = sd(num),
                        se   = sd / sqrt(N))
  
  cdata2 <-cdata2 %>% mutate(year=ifelse(season=="wet",year+0.5,year))
  
  ggplot(cdata2, aes(x = year, y = n_mean, color = season)) +
    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)) +
    scale_x_continuous(breaks=c(2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2018,2019,2020)) +
    labs(x= NULL, y = "Mean count") +
    ggtitle(common)
  
  setwd('E:/.../Trend plots/Test')
  
  ggsave(paste0(common, "- IBBEAM_trend_plot.png"), 
         height = 5, width=7, units = "in")
}

Answer 1

您可以像这样在 for 循环之前计算物种等级：

abund <- aggregate(num ~ common_name, data = data, FUN = sum)
abund <- abund[order(abund$num,decreasing = TRUE), ]
abund$rank <- 1:nrow(abund)
abund
#>           common_name num rank
#> 2       Sailfin molly  45    1
#> 1 Hardhead silverside  28    2

然后用排名值更新您的 ggsave() 文件名：

  ggsave(
    paste0(abund[abund$common_name == common,"rank"], "_", common, "_IBBEAM_trend_plot.png"), 
    height = 5, width=7, units = "in")

将相对丰度添加到文件名

Add relative abundance to file name

for-loop

r

unique

ggplot2

ggsave