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[英]R - How to convert this nested for loop into an lapply function that can mutate a list
[英]how to convert a nested loop to lapply in r
我有一個名為“dahak”的列表,其中包含 1 到 10 之間的 30000 個數字。我想用列表中的所有數字檢查每個數字,如果兩個數字相等,則將數字 1 附加到 weight_list,如果兩個數字不相等然后計算它們的差異並將其存儲為 x 並將 x 附加到 weight_list。 這是代碼:
for(j in 1:num_nodes){
for (k in 1:num_nodes){
if(j==k){
weight_list <- c(weight_list,0)
}
else if(as.numeric(dahak[j])==as.numeric(dahak[k])){
weight_list <- c(weight_list,1)
}
else if(as.numeric(dahak[j])!=as.numeric(dahak[k])){
x = 1 - (abs(as.numeric(dahak[j]) - as.numeric(dahak[k])) / 10)
weight_list <- c(weight_list,x)
}
}
}
如何優化此代碼? 我怎么能用 lapply 做到這一點?
聽起來您想創建一個 30,000 x 30,000 的矩陣。 這也聽起來像dahak
是一個向量而不是一個列表。 如果這真的是您想要做的,您可以簡化您的邏輯並像這樣進行矢量化;
get_weights <- function(x) 1 - abs(x - as.numeric(dahak))/10
weights <- do.call(rbind, lapply(as.numeric(dahak), get_weights)) - diag(length(dahak))
使用與@ThomasIsCoding 相同的虛擬數據,我得到:
weights
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15]
#> [1,] 0.0 0.9 0.7 0.3 1.0 0.4 0.3 0.6 0.6 0.8 1.0 0.9 0.6 0.9 0.5
#> [2,] 0.9 0.0 0.8 0.4 0.9 0.5 0.4 0.7 0.7 0.7 0.9 0.8 0.7 1.0 0.6
#> [3,] 0.7 0.8 0.0 0.6 0.7 0.7 0.6 0.9 0.9 0.5 0.7 0.6 0.9 0.8 0.8
#> [4,] 0.3 0.4 0.6 0.0 0.3 0.9 1.0 0.7 0.7 0.1 0.3 0.2 0.7 0.4 0.8
#> [5,] 1.0 0.9 0.7 0.3 0.0 0.4 0.3 0.6 0.6 0.8 1.0 0.9 0.6 0.9 0.5
#> [6,] 0.4 0.5 0.7 0.9 0.4 0.0 0.9 0.8 0.8 0.2 0.4 0.3 0.8 0.5 0.9
#> [7,] 0.3 0.4 0.6 1.0 0.3 0.9 0.0 0.7 0.7 0.1 0.3 0.2 0.7 0.4 0.8
#> [8,] 0.6 0.7 0.9 0.7 0.6 0.8 0.7 0.0 1.0 0.4 0.6 0.5 1.0 0.7 0.9
#> [9,] 0.6 0.7 0.9 0.7 0.6 0.8 0.7 1.0 0.0 0.4 0.6 0.5 1.0 0.7 0.9
#> [10,] 0.8 0.7 0.5 0.1 0.8 0.2 0.1 0.4 0.4 0.0 0.8 0.9 0.4 0.7 0.3
#> [11,] 1.0 0.9 0.7 0.3 1.0 0.4 0.3 0.6 0.6 0.8 0.0 0.9 0.6 0.9 0.5
#> [12,] 0.9 0.8 0.6 0.2 0.9 0.3 0.2 0.5 0.5 0.9 0.9 0.0 0.5 0.8 0.4
#> [13,] 0.6 0.7 0.9 0.7 0.6 0.8 0.7 1.0 1.0 0.4 0.6 0.5 0.0 0.7 0.9
#> [14,] 0.9 1.0 0.8 0.4 0.9 0.5 0.4 0.7 0.7 0.7 0.9 0.8 0.7 0.0 0.6
#> [15,] 0.5 0.6 0.8 0.8 0.5 0.9 0.8 0.9 0.9 0.3 0.5 0.4 0.9 0.6 0.0
我想這可能是您正在尋找的簡化,其中使用了outer
和ifelse
。
下面是一個帶有虛擬數據的例子:
set.seed(1)
num_nodes <- 15
dahak <- sample(10,num_nodes,replace = TRUE)
如果你想要一個維度為weigth_list
的num_nodes
矩陣,那么你可以嘗試
weight_list <- (u<-ifelse((z<-abs(outer(dahak,dahak,FUN = "-")))!=0,1-z/10,1))-diag(diag(u))
以至於
> weight_list
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15]
[1,] 0.0 0.5 0.8 0.2 0.3 0.8 0.3 0.4 0.2 0.6 0.6 0.9 0.7 0.9 0.8
[2,] 0.5 0.0 0.7 0.7 0.8 0.7 0.8 0.9 0.7 0.9 0.9 0.4 0.8 0.4 0.7
[3,] 0.8 0.7 0.0 0.4 0.5 1.0 0.5 0.6 0.4 0.8 0.8 0.7 0.9 0.7 1.0
[4,] 0.2 0.7 0.4 0.0 0.9 0.4 0.9 0.8 1.0 0.6 0.6 0.1 0.5 0.1 0.4
[5,] 0.3 0.8 0.5 0.9 0.0 0.5 1.0 0.9 0.9 0.7 0.7 0.2 0.6 0.2 0.5
[6,] 0.8 0.7 1.0 0.4 0.5 0.0 0.5 0.6 0.4 0.8 0.8 0.7 0.9 0.7 1.0
[7,] 0.3 0.8 0.5 0.9 1.0 0.5 0.0 0.9 0.9 0.7 0.7 0.2 0.6 0.2 0.5
[8,] 0.4 0.9 0.6 0.8 0.9 0.6 0.9 0.0 0.8 0.8 0.8 0.3 0.7 0.3 0.6
[9,] 0.2 0.7 0.4 1.0 0.9 0.4 0.9 0.8 0.0 0.6 0.6 0.1 0.5 0.1 0.4
[10,] 0.6 0.9 0.8 0.6 0.7 0.8 0.7 0.8 0.6 0.0 1.0 0.5 0.9 0.5 0.8
[11,] 0.6 0.9 0.8 0.6 0.7 0.8 0.7 0.8 0.6 1.0 0.0 0.5 0.9 0.5 0.8
[12,] 0.9 0.4 0.7 0.1 0.2 0.7 0.2 0.3 0.1 0.5 0.5 0.0 0.6 1.0 0.7
[13,] 0.7 0.8 0.9 0.5 0.6 0.9 0.6 0.7 0.5 0.9 0.9 0.6 0.0 0.6 0.9
[14,] 0.9 0.4 0.7 0.1 0.2 0.7 0.2 0.3 0.1 0.5 0.5 1.0 0.6 0.0 0.7
[15,] 0.8 0.7 1.0 0.4 0.5 1.0 0.5 0.6 0.4 0.8 0.8 0.7 0.9 0.7 0.0
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