R语言调用现有函数仅获取coef_val值不生成绘图的实现方法

以下两种方案均不需要重写完整的新函数，可满足仅获取返回值不触发绘图的需求：

方案1：临时重定向绘图输出到空设备（完全无需修改原f1代码） #

调用函数前开启空图形设备，所有绘图输出会直接被丢弃，调用结束后关闭空设备恢复默认绘图能力即可：

# 开启空PDF设备，不生成实际文件
pdf(file = NULL)
# 调用函数获取返回值
coef_res <- f1(Test, "2021-07-01", "ABC")
# 关闭空设备，恢复默认绘图输出
dev.off()

# 查看结果
print(coef_res)

如果同时需要屏蔽函数可能输出的其他文字内容，可在调用前后加上sink(nullfile())和sink()。

方案2：给原函数新增绘图开关参数（仅修改少量代码，兼容原有调用逻辑） #

不需要重构整个函数，仅给f1加一个默认开启的绘图开关，把绘图代码包裹在判断逻辑内即可，原有调用方式不受影响，需要屏蔽绘图时传参关闭即可：

f1 <- function(df1, dmda, CategoryChosse, draw_plot = TRUE) {
  
  # 原有数据处理逻辑完全保留，不需要修改
  x<-df1 %>% select(starts_with("DR0"))
  
  x<-cbind(df1, setNames(df1$DR1 - x, paste0(names(x), "_PV")))
  PV<-select(x, date2,Week, Category, DR1, ends_with("PV"))
  
  med<-PV %>%
    group_by(Category,Week) %>%
    summarize(across(ends_with("PV"), median),.groups = 'drop')
  
  SPV<-df1%>%
    inner_join(med, by = c('Category', 'Week')) %>%
    mutate(across(matches("^DR0\\d+$"), ~.x + 
                    get(paste0(cur_column(), '_PV')),
                  .names = '{col}_{col}_PV')) %>%
    select(date1:Category, DR01_DR01_PV:last_col())
  
  SPV<-data.frame(SPV)
  
  mat1 <- df1 %>%
    filter(date2 == dmda, Category == CategoryChosse) %>%
    select(starts_with("DR0")) %>%
    pivot_longer(cols = everything()) %>%
    arrange(desc(row_number())) %>%
    mutate(cs = cumsum(value)) %>%
    filter(cs == 0) %>%
    pull(name)
  
  (dropnames <- paste0(mat1,"_",mat1, "_PV"))
  
  datas<-SPV %>%
    filter(date2 == ymd(dmda)) %>%
    group_by(Category) %>%
    summarize(across(starts_with("DR0"), sum),.groups = 'drop') %>%
    pivot_longer(cols= -Category, names_pattern = "DR0(.+)", values_to = "val") %>%
    mutate(name = readr::parse_number(name))
  colnames(datas)[-1]<-c("Days","Numbers")
  
  if(as.Date(dmda) < min(as.Date(df1$date1))){
    datas <- datas %>% 
      group_by(Category) %>% 
      slice(1:max(Days)+1) %>%
      ungroup
  }else{
    datas <- datas %>% 
      group_by(Category) %>% 
      slice((as.Date(dmda) - min(as.Date(df1$date1) [
        df1$Category == first(Category)])):max(Days)+1) %>%
      ungroup
  }
  
  # 仅在draw_plot为TRUE时执行绘图逻辑
  model <- nls(Numbers ~ b1*Days^2+b2,start = list(b1 = 0,b2 = 0),data = datas, algorithm = "port")
  coef_val<-coef(model)[2]
  if (draw_plot) {
    plot(Numbers ~ Days,  xlim= c(0,45), ylim= c(0,30),
         xaxs='i',data = datas,main = paste0(dmda, "-", CategoryChosse))
    new.data <- data.frame(Days = with(datas, seq(min(Days),max(Days),len = 45)))
    new.data <- rbind(0, new.data)
    lines(new.data$Days,predict(model,newdata = new.data),lwd=2)
    points(0, coef_val, col="red",pch=19,cex = 2,xpd=TRUE)
  }
  
  return(coef_val)
}

不需要绘图时的调用方式：

coef_res <- f1(Test, "2021-07-01", "ABC", draw_plot = FALSE)

内容的提问来源于stack exchange，提问作者user16774617