After learning about the options for working with sparse matrices in R, I want to use the Matrix package to create a sparse matrix from the following data frame and have all other elements be NA
.
s r d
1 1089 3772 1
2 1109 190 1
3 1109 2460 1
4 1109 3071 2
5 1109 3618 1
6 1109 38 7
I know I can create a sparse matrix with the following, accessing elements as usual:
> library(Matrix)
> Y <- sparseMatrix(s,r,x=d)
> Y[1089,3772]
[1] 1
> Y[1,1]
[1] 0
but if I want to have the default value to be NA, I tried the following:
M <- Matrix(NA,max(s),max(r),sparse=TRUE)
for (i in 1:nrow(X))
M[s[i],r[i]] <- d[i]
and got this error
Error in checkSlotAssignment(object, name, value) :
assignment of an object of class "numeric" is not valid for slot "x" in an object of class "lgCMatrix"; is(value, "logical") is not TRUE
Not only that, I find that one takes much longer to access to elements.
> system.time(Y[3,3])
user system elapsed
0.000 0.000 0.003
> system.time(M[3,3])
user system elapsed
0.660 0.032 0.995
How should I be creating this matrix? Why is one matrix so much slower to work with?
Here's the code snippet for the above data:
X <- structure(list(s = c(1089, 1109, 1109, 1109, 1109, 1109), r = c(3772,
190, 2460, 3071, 3618, 38), d = c(1, 1, 1, 2, 1, 7)), .Names = c("s",
"r", "d"), row.names = c(NA, 6L), class = "data.frame")