How to convert array to data.table in R and back?

Question

is this the most straightforward way to convert an array into a data.table?

require(data.table)
require(ggplot2)

# this returns a data.tabl         


        

Answer 1

depening on your desired output (since you are tryning to convert multiple dimension into a 'flat' table), here is a possible solution using the plyr-package:

plyr's adply takes a array, and retuns a data.frame that you can easily convert to a data.table

library(plyr)
dt <- setDT( adply( aaa, c(1,2) ) )

    X1 X2         V1          V2
 1:  1  1 -0.5869804  1.30996405
 2:  2  1  1.3398003  1.87641841
 3:  3  1 -0.3268114 -0.12771971
 4:  1  2  0.8966523 -1.38669407
 5:  2  2 -0.4612773 -1.48036434
 6:  3  2 -0.6798351 -0.09369933
 7:  1  3  0.1311092  0.40458169
 8:  2  3 -1.7098850  0.39616792
 9:  3  3 -0.4589561 -1.14020015
10:  1  4  0.5348955 -0.25779528
11:  2  4  0.7099319  0.19067120
12:  3  4 -0.1545822 -0.75378610

Answer 2

convert the data.table back into the original array

Here a quick and dirty solution

DT2 = as.data.table(aaa)
aaa2= array(dim = dim(aaa))
invisible(DT2[, aaa2[V1, V2, V3] <<- value, .(V1,V2,V3)])
all.equal(aaa,aaa2) # TRUE

Answer 3

only works for versions 1.11.4 and 1.11.2 but not for some earlier versions

both approaches essentially return the same data.table but with A=1, B=2, C=3 in your second approach, and rows ordered in different ways. so the second approach is the way to go.

DT2 <- as.data.table(aaa)
head(DT2)
#   V1 V2 V3       value
#1:  1  1  1  0.32337516
#2:  1  1  2  1.59189589
#3:  1  2  1 -1.48751756
#4:  1  2  2 -0.86749305
#5:  1  3  1  0.01017255
#6:  1  3  2  2.66571093

#compare
DT[order(Freq), ]
#and 
DT2[order(value), ]