问如何优化if、else和else条件中的代码

EN

library(dplyr)
library(tidyverse)
library(lubridate)

df1 <- structure(
  list(date1= c("2021-06-28","2021-06-28","2021-06-28","2021-06-28"),
       date2 = c("2021-06-23","2021-06-24","2021-06-30","2021-07-01"),
       DTT= c("Hol","Hol","Hol",0),
       Week= c("Wednesday","Thursday","Wednesday","Thursday"),
       Category = c("ABC","FDE","ABC","FDE"),
       DR1 = c(4,1,1,2),
       DR01 = c(4,1,2,3), DR02= c(4,2,0,2),DR03= c(9,5,0,1),
       DR04 = c(5,4,3,2),DR05 = c(5,4,0,2)),
  class = "data.frame", row.names = c(NA, -4L))

dmda<-"2021-07-01"
CategoryChosse<-"FDE"
DTest<-"0"
Wk<-"Thursday"

Dx<-subset(df1,df1$date2<df1$date1)

x<-Dx %>% select(starts_with("DR0"))

x<-cbind(Dx, setNames(Dx$DR1 - x, paste0(names(x), "_PV")))

PV<-select(x, date2,Week, Category, DTT, DR1, ends_with("PV"))


if(any(PV$DTT == DTest & PV$Week== Wk, na.rm = TRUE)) {
  
  med<-PV %>%
    group_by(Category,Week,DTT) %>%
    summarize(across(ends_with("PV"), median))
  
  SPV<-df1%>%
    inner_join(med, by = c('Category', 'Week','DTT')) %>%
    mutate(across(matches("^DR0\\d+$"), ~.x + 
                    get(paste0(cur_column(), '_PV')),
                  .names = '{col}_{col}_PV')) %>%
    select(date1:Category, DR01_DR01_PV:last_col())
  
  SPV <- SPV %>%
    filter(date2 == dmda, Category == CategoryChosse, DTT==DTest)  
  
} 

else if(!(any(PV$DTT == DTest & PV$Week== Wk, na.rm = TRUE))) {
  
  med<-PV %>%
    group_by(Week) %>%
    summarize(across(ends_with("PV"), median))
  
  SPV<-df1%>%
    inner_join(med, by = c('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 <- SPV %>%
    filter(date2 == dmda)  
  
} 

else {
  
  med<-PV %>%
    group_by(Category,Week) %>%
    summarize(across(ends_with("PV"), median))
  
  
  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 <- SPV %>%
    filter(date2 == dmda, Category == CategoryChosse)
}