R：使用第二个栅格堆栈中的图层替换栅格堆栈中的多个图层

Question

我有一个栅格堆栈，需要用其他堆栈中的图层替换它包含的某些图层。

我想解决方案非常简单直接，但到目前为止我无法找到它。

给你重复的例子，这里是我试图做：

library(raster) 

# create some raster 
r1 <- raster(nrows=10, ncols=10, xmn=0, xmx=10, ymn = 0, ymx = 10) 
r1[] <- sample(1:100, 100, replace = TRUE) 

r2 <- raster(nrows=10, ncols=10, xmn=0, xmx=10, ymn = 0, ymx = 10) 
r2[] <- sample(1:100, 100, replace = TRUE) 

r3 <- raster(nrows=10, ncols=10, xmn=0, xmx=10, ymn = 0, ymx = 10) 
r3[] <- sample(1:100, 100, replace = TRUE) 

r4<- raster(nrows=10, ncols=10, xmn=0, xmx=10, ymn = 0, ymx = 10) 
r4[] <- sample(1:100, 100, replace = TRUE) 

# put the raster into a stack 
r_stack <- stack(r1, r2, r3, r4) 

#calculate the mean of the raster 
r_mean <- mean(r_stack) 

# What I would like to do is to subtract the mean from some of the 
# raster in the stack (layers_to_replace), but not from all, and to    
# replace the raster in the stack with the new difference. 
# For example I would like to replace the second and fourth layer with  
# the difference. 
l_replace <- c(2, 4) 

# Note: I place the difference into a second stack for the sake 
# of the example as my original data comes in a second stack 
rep_stack <- r_stack[[l_replace]] - r_mean 

r_stack[[l_replace]] <- rep_stack 

不幸的是这种方法是行不通的，并引发以下错误：

Error in v[] <- value : incompatible types (from S4 to logical) in subassignment type fix 
In addition: Warning messages: 
1: In if (i < 1) { : the condition has length > 1 and only the first element will be used 
2: In if (i > nl + 1) { : the condition has length > 1 and only the first element will be used 
3: In if (i > nl) { : the condition has length > 1 and only the first element will be used 

如何任何想法要解决这个问题将更受欢迎。

Answer 1

这应该工作：

for(ind in seq(along = l_replace)) r_stack[[l_replace[ind]]][] <- rep_stack[[ind]][] 

r_stack 
class  : RasterStack 
dimensions : 10, 10, 100, 4 (nrow, ncol, ncell, nlayers) 
resolution : 1, 1 (x, y) 
extent  : 0, 10, 0, 10 (xmin, xmax, ymin, ymax) 
coord. ref. : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 
names  : layer.1, layer.2, layer.3, layer.4 
min values : 1.00, -54.25, 2.00, -54.25 
max values : 100.0, 51.5, 100.0, 51.5 

或者，不知何故，可读性更强：

for(ind in seq(along = l_replace)){ 
    setValues(r_stack, getValues(rep_stack[[ind]]), layer = l_replace[ind]) 
}