1. R語言運行效率分析_小結（2）

小結（2）

以上用到了9個方法實現一個問題，在實現的過程當中試驗數據量爲n=10。獲得不一樣方法所用的平均耗時間大小。每種方法在計算平均耗時的重複次數爲N =100。固然上述的每一個方法測試的數據量儘管相同，但因爲（1）數據內容不盡相同，（2）因爲測試耗時的時候後臺打開的程序多少不一樣（CPU和內存任務量不一樣），（3）每種方法所處理的內容不盡相同。這些都對所測試的結果產生影響。爲此，爲了減少這些影響，本節主要經過 增長數據量大小（n）（也能夠增長重複次數（N ），本例沒加以討論） 來估測每種方法的優劣。另外，爲了具備可比性，如下統計結果均爲處理單個數據所消耗的時間。時間單位爲微秒（microsecond）

自定義函數（1）

計算這9個函數處理n個數據分別所用的平均時間（N爲重複次數）

#n爲隨機化月份數據向量的長度，N爲計算每一個函數平均重複的次數
methods_time<-function(n,N){
  month<-month_digital(n)
  Month_for_if         <-microbenchmark(Month_name_for_if         (month),times=N,unit="us")#milliseconds
  Month_for_if_else    <-microbenchmark(Month_name_for_if_else    (month),times=N,unit="us")
  Month_for_ifelse     <-microbenchmark(Month_name_for_ifelse     (month),times=N,unit="us")
  Month_for_switch     <-microbenchmark(Month_name_for_switch     (month),times=N,unit="us")
  Month_which          <-microbenchmark(Month_name_which          (month),times=N,unit="us")
  Month_join           <-microbenchmark(Month_name_join           (month),times=N,unit="us")
  Month_ddply          <-microbenchmark(Month_name_ddply          (month),times=N,unit="us")
  Month_str_replace_all<-microbenchmark(Month_name_str_replace_all(month),times=N,unit="us")
  
  Season_for_if         <-microbenchmark(Season_name_for_if         (month),times=N,unit="us")
  Season_for_if_else    <-microbenchmark(Season_name_for_if_else    (month),times=N,unit="us")
  Season_for_ifelse     <-microbenchmark(Season_name_for_ifelse     (month),times=N,unit="us")
  Season_for_switch     <-microbenchmark(Season_name_for_switch     (month),times=N,unit="us")
  Season_which          <-microbenchmark(Season_name_which          (month),times=N,unit="us")
  Season_join           <-microbenchmark(Season_name_join           (month),times=N,unit="us")
  Season_ddply          <-microbenchmark(Season_name_ddply          (month),times=N,unit="us")
  Season_str_replace_all<-microbenchmark(Season_name_str_replace_all(month),times=N,unit="us")
  
  result_for_if         <-microbenchmark(result_for_if         (month),times=N,unit="us")
  result_for_if_else    <-microbenchmark(result_for_if_else    (month),times=N,unit="us")
  result_for_ifelse     <-microbenchmark(result_for_ifelse     (month),times=N,unit="us")
  result_for_switch     <-microbenchmark(result_for_switch     (month),times=N,unit="us")
  result_which          <-microbenchmark(result_which          (month),times=N,unit="us")
  result_join           <-microbenchmark(result_join           (month),times=N,unit="us")
  result_ddply          <-microbenchmark(result_ddply          (month),times=N,unit="us")
  result_str_replace_all<-microbenchmark(result_str_replace_all(month),times=N,unit="us")
  
  Month<-c(summary(Month_for_if)$mean,
           summary(Month_for_if_else)$mean,
           summary(Month_for_ifelse)$mean,
           summary(Month_for_switch)$mean,
           summary(Month_which)$mean,
           summary(Month_join)$mean,
           summary(Month_ddply)$mean,
           summary(Month_str_replace_all)$mean)
  Season<-c(summary(Season_for_if)$mean,
            summary(Season_for_if_else)$mean,
            summary(Season_for_ifelse)$mean,
            summary(Season_for_switch)$mean,
            summary(Season_which)$mean,
            summary(Season_join)$mean,
            summary(Season_ddply)$mean,
            summary(Season_str_replace_all)$mean)
  All<-c(summary(result_for_if)$mean,
         summary(result_for_if_else)$mean,
         summary(result_for_ifelse)$mean,
         summary(result_for_switch)$mean,
         summary(result_which)$mean,
         summary(result_join)$mean,
         summary(result_ddply)$mean,
         summary(result_str_replace_all)$mean)
  df<-data.frame(Month/n,Season/n,All/n)
  colnames(df)<-c("Month","Season","All")
  df$Type<-c("for_if","for_if_else","for_ifelse","for_switch","which","join","ddply","result_str_replace")
  df$n<-n
  df$N<-N
  return(select(df,Type,n,N,everything()))
}

自定義函數（2）

調用上述函數，處理月份數據爲100，200，300，……，1000時，所須要的平均時間

result<-data.frame(Type=as.character(),n=as.integer(),N=as.integer(),
                    Month=as.integer(),Season=as.integer(),All=as.integer())
foreach (i= seq(100,1000,100)) %dopar% {
  tmp<-methods_time(i,100)
  result<-rbind(result,tmp)
  cat(paste0(i,"\n"))
}
write.csv(tmp,"/home/xh/300G/tmp/result.csv")

(未完！待續……)