What is most efficient way to replace all zeros in matrix with NAs?
What I do:
my_matrix[my_matrix==0] <- NA
I need it for recommender system (recommenderlab). Filling NAs take same time as building recommender system.
EDIT 1:
dim(my_matrix) ~ 500000x500
Where zeros are ~90%.
Answers and a benchmark
my_matrix <- matrix(1:5e5, ncol=50)
my_matrix[4000:5000, 3:10] <- 0
library(microbenchmark)
microbenchmark(
insubset = my_matrix[my_matrix %in% 0],
replace1 = replace(my_matrix, my_matrix %in% 0, NA),
replace2 = replace(my_matrix, which( my_matrix==0), NA),
Aleksandro = my_matrix[my_matrix==0] <- NA,
excloperator = my_matrix[!my_matrix] <- NA,
is.na = is.na(my_matrix) <- which(my_matrix == 0)
)
Unit: milliseconds
expr min lq mean median uq max neval
insubset 22.579762 22.890431 26.197510 23.453346 25.210976 151.957848 100
replace1 21.630386 23.621707 27.573375 25.643425 26.225683 104.389554 100
replace2 3.979487 4.069095 4.872796 4.159493 6.449839 8.887427 100
Aleksandro 12.787962 13.100210 14.837055 13.689376 14.098338 96.258866 100
excloperator 11.894246 12.275969 13.541593 13.011391 15.144429 17.307862 100
is.na 7.642823 8.901978 15.7352 9.342954 10.13166 68.31235 100
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