IDW parameters in R

I want to perform IDW interpolation using R using the idw command from the gstat package. I have this data:

#settings
library(gstat)
library(dplyr)
library(sp)
library(tidyr)

id_rep <- rep(c(1,2), 20)
f <- rep(c(930,930.2), each=20)
perc <- rep(c(90, 80), each=10)
x <- sample(1:50, 40)
y <- sample(50:100, 40)
E <- runif(40)
df <- data.frame(id_rep, perc, x,y, f, E)
df_split <- split(df, list(df$id_rep, df$perc, df$f), drop = TRUE, sep="_")

#grid
x.range <- range(df$x)
y.range <- range(df$y)

grid <- expand.grid(x = seq(x.range[1], x.range[2], by=1), 
                       y = seq(y.range[1], y.range[2], by=1))
coordinates(grid) <- ~x + y

#interpolation
lst_interp_idw <- lapply(df_split, function(X) {

   coordinates(X) <- ~x + y
    E_idw <- idw(E~ 1, X, grid, idp=1, nmax=3) %>% as.data.frame()

   df_interp <- select(E_idw, x,y,E_pred=var1.pred)
   df_interp
})

  df_interp_idw <- bind_rows(lst_interp_idw, .id = "interact") %>%
  separate(interact, c("id_rep", "perc", "f"), sep = "\\_")

Now I want to perform each run with different idp and nmax parameters within certain values (idp from 1 to 3 by 0.5, and nmax 3 to 6 by 1) and get out a data frame with columns for each combination of idp and nmax values. I try with two for loops but it doesn't work.

EDIT the code that doesn't work is:

idp = seq(from = 1, to = 3, by = 0.5)
nmax = seq(from = 3, to = 6, by = 1)

...
for(i in idp) {
  for(j in nmax)
{ E_idw= idw(E ~ 1, X, grid, nmax = i, idp = j)
  }
} 
...

Solution

Here is a way how to store the result of every iteration in a list.

#settings
#install.packages("gstat")
library(gstat)
library(dplyr)
library(sp)
library(tidyr)

id_rep <- rep(c(1,2), 20)
f <- rep(c(930,930.2), each=20)
perc <- rep(c(90, 80), each=10)
x <- sample(1:50, 40)
y <- sample(50:100, 40)
E <- runif(40)
df <- data.frame(id_rep, perc, x,y, f, E)
df_split <- split(df, list(df$id_rep, df$perc, df$f), drop = TRUE, sep="_")

#grid
x.range <- range(df$x)
y.range <- range(df$y)

grid <- expand.grid(x = seq(x.range[1], x.range[2], by=1), 
                    y = seq(y.range[1], y.range[2], by=1))
coordinates(grid) <- ~x + y

# ==============================================
# NEW function
# ==============================================

idp = seq(from = 1, to = 3, by = 0.5)
nmax = seq(from = 3, to = 6, by = 1)

#interpolation
lst_interp_idw <- lapply(df_split, function(X) {

  coordinates(X) <- ~x + y

  df_interp <- vector(length(idp)*length(nmax), mode = "list" )

  k <- 0

  for(i in idp) {

    for(j in nmax) {

      print(paste(i, j))

      # Iterator
      k <- k + 1

      E_idw= idw(E ~ 1, X, grid, nmax = i, idp = j) %>% as.data.frame()

      df_interp[[k]] <- select(E_idw, x,y,E_pred=var1.pred)

    }
  }

  return(df_interp)
})

# ==============================================

Some plausibility checks (lapply is applied to 8 list elements and 20 variations are calculated):

length(lst_interp_idw) # 8
length(lst_interp_idw[[1]]) #20
length(lst_interp_idw[[1]]) #20

It should be easy for you to adapt the last line of your code

df_interp_idw <- bind_rows(lst_interp_idw, .id = "interact") %>%
  separate(interact, c("id_rep", "perc", "f"), sep = "\\_")

to format the output in the desired format. This highly depends on how you want to present the different interpolation alternatives.