在目录中创建文件夹，然后将文件保存在新文件夹中

Question

我有相当复杂的代码来创建热图，但一个简单的目标。使用循环，而不是将所有热图文件打印到一个文件夹中新创建的文件夹（打印映射“ a” to png and Map“ in in in in in in in infold” a“ a”等...）？

以下代码通过对象“ splist”中的所有唯一名称，为每个名称创建热图，然后将所有热图打印到同一文件夹。我将如何纠正它，以便将每个热图文件放入自己的文件夹中？如果我的代码不起作用，任何热图样式都可以使用任何示例数据，我只希望使用我制作的循环为每个文件创建单独的文件夹。

GetMatrix=function(data,spToSum) {
 newdat<-filter(data,common_name %in% spToSum)
 matrixdat<-dcast(newdat, site ~ year_season, value.var="num", fun.aggregate = sum)
 matrixdat$site <- as.character(matrixdat$site)
 matrixdat <- matrixdat[order(nchar(matrixdat$site), matrixdat$site)]
 matrixdat <- matrixdat %>% remove_rownames %>% column_to_rownames(var="site") # col to row names
 as.matrix(matrixdat)
}

PlotHeatMap <- Heatmap(as.matrix(round(log(data+1), digits = 1)),
               cluster_rows = FALSE,
               cluster_columns = FALSE,
               na_col = "black",
               column_title = "Year/Season",
               row_title = "Site",
               heatmap_legend_param = list(title = "ln(x+1)"))

dataList<-list()
filenameVal<-paste0(1:length(splist),splist," - NotClustered.png")
doClusterVal<-FALSE

setwd('C:/...')

# Prints the maps
for(run in 1:length(splist)) {
 dataList[[run]]<-GetMatrix(filter(dat,CYR>=2005),splist[run])  
 PlotHeatMap(data=dataList[[run]],splist[run],fileName=filenameVal[run],doCluster=doClusterVal)
 dir.create(file.path(splist[run]), recursive = TRUE)
 print(paste(run,splist[run]))
}

# common_name = fish/shrimp/crab name
# num = count
# site = location #
# CYR = calendar year
# Season = wet/dry season

随机选择10行数据：

> dput(dat)
structure(list(common_name = c("Mojarra spp", "Chub spp", "Glass Shrimp", 
"Lined Sole", "Pink Shrimp", "Iridescent Shrimp", "Giant Decorator crab", 
"Longnose Spider Crab", "Pearl Blenny", "Banded Killifish"), 
    num = c(4L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), site = c(4L, 
    1L, 47L, 5L, 10L, 18L, 22L, 3L, 42L, 19L), CYR = c(2017L, 
    2012L, 2013L, 2019L, 2008L, 2019L, 2009L, 2009L, 2014L, 2015L
    ), Season = c("WET", "WET", "WET", "DRY", "WET", "DRY", "DRY", 
    "DRY", "DRY", "DRY"), year_season = c("2017_WET", "2012_WET", 
    "2013_WET", "2019_DRY", "2008_WET", "2019_DRY", "2009_DRY", 
    "2009_DRY", "2014_DRY", "2015_DRY")), row.names = c(175919L, 
114959L, 124359L, 204205L, 53943L, 207868L, 61123L, 64762L, 130625L, 
148966L), class = "data.frame")