Description Usage Arguments Details Parallelization Hash function Examples
Hash R objects to 32bit integers
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 |
x |
Object to hash |
... |
Arguments to be passed to other methods. In particular, for the default method,
these arguments are passed to |
recursive |
hash each element separately? |
what |
Hash the string or the pointer to the string (faster, but not reproducible over R sessions) |
nthread |
maximum number of threads used. |
The default method serialize
s the input to a single
raw
vector which is then hashed to a single signed
integer. This is also true for character
vectors when
recursive=FALSE
. When recursive=TRUE
each element of a
character
vector is hashed separately, based on the underlying
char
representation in C
.
On systems supporting openMP, this function is able to use multiple cores. By default, a sensible number of cores is chosen. See the entry on OpenMP Support in the writing R extensions manual to check whether your system supports it.
The hash function used is Paul Hsieh's' SuperFastHash
function which is
described on his website.
As the title of the algorithm suggests, this hashing algorithm is not aimed to
be used as a secure hash, and it is probably a bad idea to use it for that purpose.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | # hash some complicated R object (not a list).
m <- lm(height ~ weight, data=women)
hash(m)
# hash a character vector element by element:
x <- c("Call any vegetable"
, "and the chances are good"
, "that the vegetable will respond to you")
hash(x)
# hash a character vector as one object:
hash(x, recursive=FALSE)
# hash a list recursively
L <- strsplit(x," ")
hash(L)
# recursive really means recursive, so nested lists are recursed over:
L <- list(
x = 10
, y = list(
foo = "bob"
, bar = lm(Sepal.Width ~ Sepal.Length, data=iris)
)
)
hash(L)
hash(L,recursive=FALSE)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.