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In a longer script I have to multiply the length of a vector A (2614) with the numbers of rows of a dataframe B (1456000). If I do that directly with length(A) * nrow(B) I get the message NAs produced by integer overflow although there's no problem when I multiply the same numbers: 

2614 * 1456000 
[1] 3805984000

The only way to get the multiplication to work is round(length(A)) * nrow(B) or length(A) * round(nrow(B)). But the numbers produced by length and nrow must be integers anyhow! Moreover, I tested this with the following function suggested on the help page for the function is.integer...

is.wholenumber <- function(x, tol = .Machine$double.eps^0.5) abs(x-round(x)) < tol

... and of course, they ARE integers. So why do I need the crutches "round" here? Very puzzling... Somebody has got an idea what's going on in the background?

user7417
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1 Answers1

14

Hopefully a graphic representation of what is happening....

2614 * 1456000
#[1] 3805984000

##  Integers are actually represented as doubles
class( 2614 * 1456000 )
#[1] "numeric"

#  Force numbers to be integers
2614L * 1456000L
#[1] NA
#Warning message:
#In 2614L * 1456000L : NAs produced by integer overflow

##  And the result is an integer with overflow warning
class( 2614L * 1456000L )
#[1] "integer"
#Warning message:
#In 2614L * 1456000L : NAs produced by integer overflow

2614 * 1456000 is a numeric because both the operands are actually of class numeric. The overflow occurs because both nrow and length return integer's and hence the result is an integer but the result exceeds the maximum size representable by the integer class (+/-2*10^9). A numeric or double can hold 2e-308 to 2e+308. So to solve your problem, just use as.numeric(length(A)) or as.double(length(A)).

Simon O'Hanlon
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