一层循环：
data1<-matrix(c(1:15),nrow = 5, ncol=3, byrow=TRUE)
data1
sum_my<-function(x){
   sum(x)
}
col.sums <- apply(data1, 2, sum_my)
col.sums
row.sums <- apply(data1, 1, sum_my)
row.sums
# sum_my can be changed into any function using column or row as input

########### For example
### correlation with a vector
data1<-matrix(c(1:15),nrow = 5, ncol=3, byrow=TRUE)
data1
data_4cor <- c(1,3,2)
sum_cor<-function(x){
   cor(x,data_4cor)
}

row.cor <- apply(data1, 1, sum_cor)
row.cor
##########


二层循环：
（数据框）
data2<-as.data.frame(data1)
x <- data2
y <- data2
bl <- lapply(x, function(u){
            lapply(y, function(v){
                        # function(u,v) # Function with column from x and column from y as inputs
                        cor(u,v) # As an example
                    })
        })
out = matrix(unlist(bl), ncol=ncol(y), byrow=T)
out

（向量）
data3<- c(1:9)
x <- data3
y <- data3
bl <- lapply(x, function(u){
            lapply(y, function(v){
                        sum(u,v) # Function with each data from x and column from y as inputs
                    })
        })
out = matrix(unlist(bl), ncol=length(y), byrow=T)
out




转载本文请联系原作者获取授权，同时请注明本文来自薛良交科学网博客。
链接地址：https://m.sciencenet.cn/blog-285393-585860.html

上一篇：R & Bioconductor Manual
下一篇：Online Plant Comparative Genomics Tools