Question

我想将列表对象转换为zoo，然后在rollapply对象上应用zoo。下面重现的简短示例（我有90,000个这样的文件要处理，使用UNIX :)）。假设我的列表有两个数据帧。

1）我想将每个数据帧中的日期转换为以下格式：

dates <- as.Date(paste0(mylist$year, "-", mylist$month, "-", mylist$day), format="%Y-%m-%d")

z <- zoo(mylist, order.by=mylist[,1])

我理解lapply可以做到这一点但我尝试没有成功。

获得zoo对象后，我想使用rollapply：

library(hydroTSM)#for daily2annual function but aggregate can do 

    x.3max <- rollapply(data=zooobject, width=3, FUN=sum, fill=NA, partial= TRUE,
                         align="center")
    # Maximum value per year of 3-day total rainfall for each one of the simulations
    z.3max.annual <- daily2annual(z.3max,  FUN=max,na.rm=TRUE)#dates=1

上面的代码是什么，它在zooobject的数据帧的每一列上设置了一个3天的窗口，并对值进行求和。提取3天总计每年的最大值。

      mylist<- list(a,a)
mylist<-lapply(mylist, function(x) x[x[["Month"]] %in% c(12,1,2),])# extract data for DJF for individual sites


    library(zoo)
       a= structure(list(Year = c(1975L, 1975L, 1975L, 1975L, 1975L, 1975L
), Month = c(1L, 1L, 1L, 1L, 1L, 1L), Site = structure(c(1L, 
1L, 1L, 1L, 1L, 1L), .Label = "G100", class = "factor"), Day = 1:6, 
    sim01 = c(28.49, 29.04, 27.62, 28.43, 28.69, 29.16), sim02 = c(29.49, 
    30.04, 28.62, 29.43, 29.69, 30.16), sim03 = c(30.49, 31.04, 
    29.62, 30.43, 30.69, 31.16), sim04 = c(31.49, 32.04, 30.62, 
    31.43, 31.69, 32.16), sim05 = c(32.49, 33.04, 31.62, 32.43, 
    32.69, 33.16), sim06 = c(33.49, 34.04, 32.62, 33.43, 33.69, 
    34.16), sim07 = c(34.49, 35.04, 33.62, 34.43, 34.69, 35.16
    ), sim08 = c(35.49, 36.04, 34.62, 35.43, 35.69, 36.16), sim09 = c(36.49, 
    37.04, 35.62, 36.43, 36.69, 37.16), sim10 = c(37.49, 38.04, 
    36.62, 37.43, 37.69, 38.16), sim11 = c(38.49, 39.04, 37.62, 
    38.43, 38.69, 39.16), sim12 = c(39.49, 40.04, 38.62, 39.43, 
    39.69, 40.16), sim13 = c(40.49, 41.04, 39.62, 40.43, 40.69, 
    41.16), sim14 = c(41.49, 42.04, 40.62, 41.43, 41.69, 42.16
    ), sim15 = c(42.49, 43.04, 41.62, 42.43, 42.69, 43.16), sim16 = c(43.49, 
    44.04, 42.62, 43.43, 43.69, 44.16), sim17 = c(44.49, 45.04, 
    43.62, 44.43, 44.69, 45.16), sim18 = c(45.49, 46.04, 44.62, 
    45.43, 45.69, 46.16), sim19 = c(46.49, 47.04, 45.62, 46.43, 
    46.69, 47.16), sim20 = c(47.49, 48.04, 46.62, 47.43, 47.69, 
    48.16)), .Names = c("Year", "Month", "Site", "Day", "sim01", 
"sim02", "sim03", "sim04", "sim05", "sim06", "sim07", "sim08", 
"sim09", "sim10", "sim11", "sim12", "sim13", "sim14", "sim15", 
"sim16", "sim17", "sim18", "sim19", "sim20"), row.names = c(NA, 
6L), class = "data.frame")

输出应类似于：

Year Site Sim01... 
1975 G100 ...
1976 G100 ...
1977 G100 ...

只需要c（12,1,2）个月的值。

Answer 1

这会生成一个动物园对象列表Lz，然后对列表中给出rollapply的每个组件执行L2。最后L3汇总了一年中每列的max。

library(zoo)

mylist <- list(a, a) # a is given at bottom of question

Lz <- lapply(mylist, read.zoo, index = 1:3, format = "%Y %m %d")
L2 <- lapply(Lz, rollapply, 3, sum, partial = TRUE)
L3 <- lapply(L2, function(z) aggregate(z, as.numeric(format(time(z), "%Y")), max))

，并提供：

> L3

[[1]]
     sim01 sim02 sim03 sim04 sim05  sim06  sim07  sim08  sim09  sim10  sim11
1975 86.28 89.28 92.28 95.28 98.28 101.28 104.28 107.28 110.28 113.28 116.28
      sim12  sim13  sim14  sim15  sim16  sim17  sim18  sim19  sim20
1975 119.28 122.28 125.28 128.28 131.28 134.28 137.28 140.28 143.28

[[2]]
     sim01 sim02 sim03 sim04 sim05  sim06  sim07  sim08  sim09  sim10  sim11
1975 86.28 89.28 92.28 95.28 98.28 101.28 104.28 107.28 110.28 113.28 116.28
      sim12  sim13  sim14  sim15  sim16  sim17  sim18  sim19  sim20
1975 119.28 122.28 125.28 128.28 131.28 134.28 137.28 140.28 143.28

Answer 2

解决

lst1 <- lapply(list.files(pattern=".csv"),function(x) read.table(x,header=TRUE,sep="")) # read all files and data and replace -999.9 with NA

lst2<-lapply(lst1, function(x) x[x[["Month"]] %in% c(6,7,8),])#c(6,7,8) extract data for DJF for individual sites
names(lst2)<-list.files(pattern=".csv")
lapply(lst2,tail,4)
lst3<-lapply(lst2, function(x) x[!(names(x) %in% c("Site"))])
Lz <- lapply(lst3, read.zoo, index = 1:3, format = "%Y %m %d")

L2 <- lapply(Lz, rollapply, 3, sum, partial = TRUE)
L3 <- lapply(L2, function(z) aggregate(z, as.numeric(format(time(z), "%Y")), max))

mapply(
  write.table,
  x=L3, file=paste(names(L3), "csv", sep="."),
  MoreArgs=list(row.names=FALSE, sep=",")
) # write files to folder keeping the list names as file names

将List转换为zoo并在List上使用rollapply

2 个答案: