当R中未知的维度时，将矢量结果从循环存储到矩阵中

I want to store the vector result from a loop into a matrix, but I do not know the number of rows. For example, the following code will illustrate what I want to do:

我想将循环中的矢量结果存储到矩阵中,但我不知道行数。例如,以下代码将说明我想要做的事情:

result_final <- c()
for (i in 1:5){
   n <- sample(1:5,1) #get the number of rows for this iteration
   result_this_time <- matrix(0,n,3) #generate a matrix with row number 
                                     #are unknown before running the iteration
   #combine all the results from each iteration together 
   if (i == 1) result_final <- result_this_time
       else result_final <- rbind(result_final,result_this_time)
    }
result_final

The above code works for me. The problem is that it is a little complex. As you can see, when I use c() to generate the new vector, I do not have to indicate the length of vector. The code test1 <- c();test1[3]<-1 will not report any error, but the codetest2 <- matrix();test2[3,3]<-1 will report an error as refer to wrong subscript. So I wonder is there anyway that I can create a "matrix" that I do not have to explicitly indicate the rows of matrix(just like to create a vector using c()) in order to get rid of if statement.

上面的代码适合我。问题是它有点复杂。如您所见,当我使用c()生成新向量时,我不必指示向量的长度。代码test1 < - c(); test1 [3] < - 1不会报告任何错误,但codetest2 < - matrix(); test2 [3,3] < - 1将报告错误,因为它引用了错误的下标。所以我想知道无论如何我可以创建一个“矩阵”,我没有必要明确指出矩阵的行(就像使用c()创建一个向量)以摆脱if语句。

2 个解决方案

#1

Similar to the answer above, create a list to store your results and then bind them together.

与上面的答案类似,创建一个列表来存储您的结果,然后将它们绑定在一起。

result_list <- list()
for(i in 1:5){
  n <- sample(1:5, 1)
  result_list[[i]] <- matrix(0, n, 3)
}
result_final <- do.call(rbind, result_list)

#2

I'd do using lapply(). The outer lapply() controls the overall repetition while the inner lapply() does the number of rows assigned by n. do.call() is used to simplify and bind (rbind()) the elements. A comparison is made to the original code below.

我会使用lapply()。外部lapply()控制整体重复,而内部lapply()执行由n指定的行数。 do.call()用于简化和绑定(rbind())元素。与下面的原始代码进行比较。

set.seed(1237)
# outer loop controls overall repetition
do.call(rbind, lapply(1:5, function(x) {
  n <- sample(1:5, 1)
  # inner loop control individual rows by n
  do.call(rbind, lapply(1:n, function(y) rbind(rep(0, 3))))
}))
[,1] [,2] [,3]
[1,]    0    0    0
[2,]    0    0    0
[3,]    0    0    0
[4,]    0    0    0
[5,]    0    0    0
[6,]    0    0    0
[7,]    0    0    0
[8,]    0    0    0
[9,]    0    0    0
[10,]    0    0    0

set.seed(1237)
result_final <- c()
for (i in 1:5){
  n <- sample(1:5,1) #get the number of rows for this iteration
  result_this_time <- matrix(0,n,3) #generate a matrix with row number 
  #are unknown before running the iteration
  #combine all the results from each iteration together 
  if (i == 1) result_final <- result_this_time
  else result_final <- rbind(result_final,result_this_time)
}
result_final
[,1] [,2] [,3]
[1,]    0    0    0
[2,]    0    0    0
[3,]    0    0    0
[4,]    0    0    0
[5,]    0    0    0
[6,]    0    0    0
[7,]    0    0    0
[8,]    0    0    0
[9,]    0    0    0
[10,]    0    0    0