所以我最近修改了我在 StackOverflow 上找到的一些代码，以根据用户输入创建动态数量的图。但是，我现在无法弄清楚如何将所有这些动态图保存在一个文件中。当我在 downloadHandler 中使用 ggsave() 时，它只保存最后生成的图，因为这些图是在 for 循环内部、观察函数内部创建的。我尝试将 for 循环保存为一个单独的函数并保存它而不是最后一个绘图，我尝试将 observe() 保存为一个函数并在 ggsave() 中调用它，但没有任何效果。知道如何将所有生成的图保存到一个文件中吗？
ui <- fluidPanel(
sidebarLayout(
sidebarPanel(
#this is the input widget for dataset selection
selectInput(inputId = "dataset_selec",
label = "Choose which Dataset to explore:",
choices = list("NK AD Dataset (Zhang, 2020)",
"APPPS1 Dataset (Van Hove, 2019)",
"Aging T Cell Dataset (Dulken, 2019)"),
selected = "APPPS1 Dataset (Van Hove, 2019)"))
mainPanel(
fluidRow(
column(4,
textInput(inputId = "gene_fp",
label = "Enter gene(s) of interest here, separated by commas: ")
),
column(4,
br(),
checkboxInput("split_fp", "Split the graph?")
),
column(4,
conditionalPanel(condition = "input.split_fp == true",
#display choices to split by
selectInput(inputId = "metadata_split_fp",
label = "Choose how to split the Seurat data: ",
choices = list("Genotype", "Timepoint")))
)
),
#ask users if they want to split the graphs
br(),
fluidRow(
column(4,
textInput("save_name_fp",
label = "Enter a file name: ")
),
column(4,
conditionalPanel(condition = "input.save_name_fp.length > 0",
selectInput("fp_device",
label = "Select file type: ",
choices = list("PNG", "JPEG", "PDF", "TIFF",
"BMP", "SVG")))
),
column(4,
br(),
conditionalPanel(condition = "input.save_name_fp.length > 0",
downloadButton("fp_save", label = "Save Feature Plot"))
)
),
#plot the actual plot
uiOutput("fp_plots")
)
)
)
server <- function(input, output, session) {
datasetInput <- reactive({
switch(input$dataset_selec,
"NK AD Dataset (Zhang, 2020)" = nk_data,
"APPPS1 Dataset (Van Hove, 2019)" = appps1_data,
"Aging T Cell Dataset (Dulken, 2019)" = tcellinfil_data)
})
output$fp_plots <- renderUI({
#validate is to prevent an error message from being displayed when a gene hasn't been entered yet
validate(
need(input$gene_fp !="", "Please enter a gene.")
)
fp_genes <- input$gene_fp
fp_genes <- gsub(" ", "", fp_genes)
fp_genes <- unlist(strsplit(fp_genes, split = ","))
n <- length(fp_genes)
plot_output_list <- lapply(1:n, function(i) {
plotname <- paste("plot", i, sep = "")
if (input$split_fp == TRUE) {plotOutput(plotname, height = 580, width = 1100)}
else {plotOutput(plotname, height = 580, width = 550)}
})
do.call(tagList, plot_output_list)
})
#Here, we take the input of genes, and turn it into a character vector, so that we can iterate
#over it. This needs to be under observe({}) because it involves an input.
#Next, we iterate through the list of genes using a for loop, and within that for loop we assign
#the plots that we want to be displayed to each plotname, which is also sequentially created within
#this for loop, and assign it to the tagList we generated earlier. Basically, we're adding objects to
#list of names we made earlier.
#This needs to be under local({}) control, otherwise each graph doesn't get its own number,
#because of when renderPlot is evaluated
observe({
fp_genes <- input$gene_fp
fp_genes <- gsub(" ", "", fp_genes)
fp_genes <- unlist(strsplit(fp_genes, split = ","))
for (i in 1:length(fp_genes)) {
local({
plotname <- paste("plot", i, sep = "")
gene <- fp_genes[i]
output[[plotname]] <- renderPlot({
if (input$split_fp == TRUE) {FeaturePlot(datasetInput(), features = gene, split.by = input$metadata_split_fp)}
else {FeaturePlot(datasetInput(), features = gene)}
})
})
}
})
output$fp_save <- downloadHandler(
filename = function() {
paste(input$save_name_fp, tolower(input$fp_device), sep = ".")
},
content = function(file) {
ggsave(file, device = tolower(input$fp_device))
}
)
}