如何计算矩阵列表中特定行的总和

Question

I have data in matrices and the matrices are stored in a list, and I want the sum of the a specific row in each matrix.

some example data

A1<-matrix(0:9, nrow=5, ncol=2)
A2<-matrix(10:19, nrow=5, ncol = 2)
A3<-matrix(20:29, nrow=5, ncol = 2)
Mylist<-list(A1, A2, A3)

I can get the sum of all rows in each matrix with

lapply(Mylist, function(x) apply(x, 1, sum) )

but I only want the sum of a specific row, could be row 1, could be row 4, depending on what I want to look at. I know I can read it off of the results I generate with the code above but I want a cleaner solution that only gives me the results. Thanks

Answer 1

You can use purrr:map() .

If you know the output type (in this case, seems to be all integers), you can be more specific, like map_int() . With map() you'll get a list back, with a specific map version, like map_int() , you get a vector back instead.

library(tidyverse)

ix <- 3 # let's say we want the sum of the third row

map_int(Mylist, ~sum(.x[ix, ]))
[1] 9 29 49

If the row index you care about changes per matrix, you can use map2() instead, which takes two inputs of the same length:

ixs <- c(1, 2, 3)

map2_int(Mylist, ixs, ~sum(.x[.y, ]))
[1]  5 27 49

Alternately, if you need to work in base R, you can just take the desired index (here, ix ) of sum() , you don't need apply() inside lapply() :

lapply(Mylist, function(x) sum(x[ix, ]))

[[1]]
[1] 9

[[2]]
[1] 29

[[3]]
[1] 49

Answer 2

one.row.sum <- function(df, row.num) lapply(Mylist, function(df) sum(df[row.num, ]))

one.row.sum(Mylist, 1)
[[1]]
[1] 5

[[2]]
[1] 25

[[3]]
[1] 45