用R将矩阵划分为N个相等大小的块 [英] Partition matrix into N equally-sized chunks with R
问题描述
如何用R将矩阵或数据帧划分为N个大小相等的块?我想水平切割矩阵或数据框.
How can I partition a matrix or dataframe into N equally-sized chunks with R? I want to cut the matrix or dataframe horizontally.
例如,给定:
r = 8
c = 10
number_of_chunks = 4
data = matrix(seq(r*c), nrow = r, ncol=c)
>>> data
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 9 17 25 33 41 49 57 65 73
[2,] 2 10 18 26 34 42 50 58 66 74
[3,] 3 11 19 27 35 43 51 59 67 75
[4,] 4 12 20 28 36 44 52 60 68 76
[5,] 5 13 21 29 37 45 53 61 69 77
[6,] 6 14 22 30 38 46 54 62 70 78
[7,] 7 15 23 31 39 47 55 63 71 79
[8,] 8 16 24 32 40 48 56 64 72 80
我想将data
切成4个元素的列表:
I would like to have to cut data
into a list of 4 elements:
元素1:
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 9 17 25 33 41 49 57 65 73
[2,] 2 10 18 26 34 42 50 58 66 74
元素2:
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[3,] 3 11 19 27 35 43 51 59 67 75
[4,] 4 12 20 28 36 44 52 60 68 76
元素3:
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[5,] 5 13 21 29 37 45 53 61 69 77
[6,] 6 14 22 30 38 46 54 62 70 78
元素4:
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[7,] 7 15 23 31 39 47 55 63 71 79
[8,] 8 16 24 32 40 48 56 64 72 80
在python中使用numpy时,我可以使用 numpy.array_split
.
With numpy in python, I can use numpy.array_split
.
推荐答案
这是在基数R中的尝试.使用pretty
计算行序列的漂亮"切割值.用cut
对行号的序列进行分类,并使用split
返回在切割值处分割的序列的列表.最后,使用lapply
浏览拆分行值的列表,并使用[
提取矩阵子集.
Here's an attempt in base R. Calculate "pretty" cut values for the sequence of rows using pretty
. Categorized the sequence of row numbers with cut
and return a list of the the sequence split at the cut values with split
. Finally, run through a list of the split row values using lapply
extract the matrix subsets with [
.
lapply(split(seq_len(nrow(data)),
cut(seq_len(nrow(data)), pretty(seq_len(nrow(data)), number_of_chunks))),
function(x) data[x, ])
$`(0,2]`
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 9 17 25 33 41 49 57 65 73
[2,] 2 10 18 26 34 42 50 58 66 74
$`(2,4]`
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 3 11 19 27 35 43 51 59 67 75
[2,] 4 12 20 28 36 44 52 60 68 76
$`(4,6]`
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 5 13 21 29 37 45 53 61 69 77
[2,] 6 14 22 30 38 46 54 62 70 78
$`(6,8]`
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7 15 23 31 39 47 55 63 71 79
[2,] 8 16 24 32 40 48 56 64 72 80
将其滚动为一个函数:
array_split <- function(data, number_of_chunks) {
rowIdx <- seq_len(nrow(data))
lapply(split(rowIdx, cut(rowIdx, pretty(rowIdx, number_of_chunks))), function(x) data[x, ])
}
然后,您可以使用
array_split(data=data, number_of_chunks=number_of_chunks)
返回与上面相同的结果.
to return the same result as above.
@ user20650建议的一个很好的简化是
A nice simplification suggested by @user20650 is
split.data.frame(data,
cut(seq_len(nrow(data)), pretty(seq_len(nrow(data)), number_of_chunks)))
令我惊讶的是,split.data.frame
当第一个参数是矩阵时会返回一个矩阵列表.
A surprise to me, split.data.frame
returns a list of matrices when its first argument is a matrix.
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