Methods to replace or transform a subset of a
supported mutable object
using
pass-by-reference semantics.
Usage
ii_set(x, ...)
ii2_set(x, ...)
ss_set(x, ...)
ss2_set(x, ...)
# Default S3 method
ii_set(
x,
i = NULL,
inv = FALSE,
...,
rp,
tf,
chkdup = getOption("squarebrackets.chkdup", FALSE)
)
# Default S3 method
ss_set(
x,
s = NULL,
d = 1:ndim(x),
inv = FALSE,
...,
rp,
tf,
chkdup = getOption("squarebrackets.chkdup", FALSE)
)
# Default S3 method
ii2_set(x, ...)
# S3 method for class 'data.table'
ss2_set(
x,
s = NULL,
d = 1:2,
obs = NULL,
vars = NULL,
inv = FALSE,
...,
rp,
tf,
chkdup = getOption("squarebrackets.chkdup", FALSE),
.lapply = lapply
)Arguments
- x
a variable belonging to one of the supported mutable classes.
- ...
- i, s, d, obs, vars, inv
See squarebrackets_indx_args.
An empty index selection leaves the original object unchanged.- rp, tf, .lapply
- chkdup
![[for performance: set to FALSE]](figures/for_performance-set_to_FALSE-red.svg)
Value
Returns: VOID. This method modifies the object by reference.
Do not use assignments like x <- ii_set(x, ...).
Since this function returns void, you'll just get NULL.
Details
Transform or Replace
Specifying argument tf will transform the subset.
Specifying rp will replace the subset.
One cannot specify both tf and rp. It's either one set or the other.
Examples
# mutatomic objects ====
gen_mat <- function() {
obj <- as.mutatomic(matrix(1:16, ncol = 4))
colnames(obj) <- c("a", "b", "c", "a")
return(obj)
}
obj <- obj2 <- gen_mat()
print(obj)
#> a b c a
#> [1,] 1 5 9 13
#> [2,] 2 6 10 14
#> [3,] 3 7 11 15
#> [4,] 4 8 12 16
#> mutatomic
#> typeof: integer
ss_set(obj, n(1:3), 1:ndim(obj), rp = -1:-9)
print(obj2)
#> a b c a
#> [1,] -1 -4 -7 13
#> [2,] -2 -5 -8 14
#> [3,] -3 -6 -9 15
#> [4,] 4 8 12 16
#> mutatomic
#> typeof: integer
# above is like x[1:3, 1:3] <- -1:-9, but using pass-by-reference
obj <- obj2 <- gen_mat()
obj
#> a b c a
#> [1,] 1 5 9 13
#> [2,] 2 6 10 14
#> [3,] 3 7 11 15
#> [4,] 4 8 12 16
#> mutatomic
#> typeof: integer
ii_set(obj, i = \(x) x <= 5, rp = -1:-5)
#> coercing replacement to integer
print(obj2)
#> a b c a
#> [1,] -1 -5 9 13
#> [2,] -2 6 10 14
#> [3,] -3 7 11 15
#> [4,] -4 8 12 16
#> mutatomic
#> typeof: integer
# above is like x[x <= 5] <- -1:-5, but using pass-by-reference
obj <- obj2 <- gen_mat()
obj
#> a b c a
#> [1,] 1 5 9 13
#> [2,] 2 6 10 14
#> [3,] 3 7 11 15
#> [4,] 4 8 12 16
#> mutatomic
#> typeof: integer
ss_set(obj, n("a"), 2L, rp = cbind(-1:-4, -5:-8))
print(obj2)
#> a b c a
#> [1,] -1 5 9 -5
#> [2,] -2 6 10 -6
#> [3,] -3 7 11 -7
#> [4,] -4 8 12 -8
#> mutatomic
#> typeof: integer
# above is like x[, "a"] <- cbind(-1:-4, -5:-8), but using pass-by-reference
obj <- obj2 <- gen_mat()
obj
#> a b c a
#> [1,] 1 5 9 13
#> [2,] 2 6 10 14
#> [3,] 3 7 11 15
#> [4,] 4 8 12 16
#> mutatomic
#> typeof: integer
ss_set(obj, n(1:3), 1:ndim(obj), tf = \(x) -x)
print(obj2)
#> a b c a
#> [1,] -1 -5 -9 13
#> [2,] -2 -6 -10 14
#> [3,] -3 -7 -11 15
#> [4,] 4 8 12 16
#> mutatomic
#> typeof: integer
# above is like x[1:3, 1:3] <- -1 * x[1:3, 1:3], but using pass-by-reference
obj <- obj2 <- gen_mat()
obj
#> a b c a
#> [1,] 1 5 9 13
#> [2,] 2 6 10 14
#> [3,] 3 7 11 15
#> [4,] 4 8 12 16
#> mutatomic
#> typeof: integer
ii_set(obj, i = \(x) x <= 5, tf = \(x) -x)
#> coercing replacement to integer
print(obj2)
#> a b c a
#> [1,] -1 -5 9 13
#> [2,] -2 6 10 14
#> [3,] -3 7 11 15
#> [4,] -4 8 12 16
#> mutatomic
#> typeof: integer
# above is like x[x <= 5] <- -1 * x[x <= 5], but using pass-by-reference
obj <- obj2 <- gen_mat()
obj
#> a b c a
#> [1,] 1 5 9 13
#> [2,] 2 6 10 14
#> [3,] 3 7 11 15
#> [4,] 4 8 12 16
#> mutatomic
#> typeof: integer
ss_set(obj, n("a"), 2L, tf = \(x) -x)
obj2
#> a b c a
#> [1,] -1 5 9 -13
#> [2,] -2 6 10 -14
#> [3,] -3 7 11 -15
#> [4,] -4 8 12 -16
#> mutatomic
#> typeof: integer
# above is like x[, "a"] <- -1 * x[, "a"], but using pass-by-reference
gen_array <- function() {
as.mutatomic(array(1:64, c(4,4,3)))
}
obj <- obj2 <- gen_array()
obj
#> , , 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1 5 9 13
#> [2,] 2 6 10 14
#> [3,] 3 7 11 15
#> [4,] 4 8 12 16
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 17 21 25 29
#> [2,] 18 22 26 30
#> [3,] 19 23 27 31
#> [4,] 20 24 28 32
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 33 37 41 45
#> [2,] 34 38 42 46
#> [3,] 35 39 43 47
#> [4,] 36 40 44 48
#>
#> mutatomic
#> typeof: integer
ss_set(obj, n(1:3, 1:2, c(1, 3)), 1:3, rp = -1:-12)
#> coercing replacement to integer
print(obj2)
#> , , 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] -1 -4 9 13
#> [2,] -2 -5 10 14
#> [3,] -3 -6 11 15
#> [4,] 4 8 12 16
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 17 21 25 29
#> [2,] 18 22 26 30
#> [3,] 19 23 27 31
#> [4,] 20 24 28 32
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] -7 -10 41 45
#> [2,] -8 -11 42 46
#> [3,] -9 -12 43 47
#> [4,] 36 40 44 48
#>
#> mutatomic
#> typeof: integer
# above is like x[1:3, , 1:2] <- -1:-12, but using pass-by-reference
obj <- obj2 <- gen_array()
obj
#> , , 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1 5 9 13
#> [2,] 2 6 10 14
#> [3,] 3 7 11 15
#> [4,] 4 8 12 16
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 17 21 25 29
#> [2,] 18 22 26 30
#> [3,] 19 23 27 31
#> [4,] 20 24 28 32
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 33 37 41 45
#> [2,] 34 38 42 46
#> [3,] 35 39 43 47
#> [4,] 36 40 44 48
#>
#> mutatomic
#> typeof: integer
ii_set(obj, i = \(x)x <= 5, rp = -1:-5)
#> coercing replacement to integer
print(obj2)
#> , , 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] -1 -5 9 13
#> [2,] -2 6 10 14
#> [3,] -3 7 11 15
#> [4,] -4 8 12 16
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 17 21 25 29
#> [2,] 18 22 26 30
#> [3,] 19 23 27 31
#> [4,] 20 24 28 32
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 33 37 41 45
#> [2,] 34 38 42 46
#> [3,] 35 39 43 47
#> [4,] 36 40 44 48
#>
#> mutatomic
#> typeof: integer
# above is like x[x <= 5] <- -1:-5, but using pass-by-reference
#############################################################################
# data.table ====
obj <- data.table::data.table(a = 1:10, b = letters[1:10], c = 11:20, d = factor(letters[1:10]))
str(obj) # notice that columns "a" and "c" are INTEGER (`int`)
#> Classes 'data.table' and 'data.frame': 10 obs. of 4 variables:
#> $ a: int 1 2 3 4 5 6 7 8 9 10
#> $ b: chr "a" "b" "c" "d" ...
#> $ c: int 11 12 13 14 15 16 17 18 19 20
#> $ d: Factor w/ 10 levels "a","b","c","d",..: 1 2 3 4 5 6 7 8 9 10
#> - attr(*, ".internal.selfref")=<externalptr>
ss2_set(
obj, obs = ~ (a >= 2) & (c <= 17), vars = is.numeric,
tf = sqrt # WARNING: sqrt() results in `dbl`, but columns are `int`, so decimals lost
)
#> Warning: 1.414214 (type 'double') at RHS position 1 out-of-range(NA) or truncated (precision lost) when assigning to type 'integer' (column 1 named 'a')
#> Warning: 3.464102 (type 'double') at RHS position 1 out-of-range(NA) or truncated (precision lost) when assigning to type 'integer' (column 3 named 'c')
print(obj)
#> a b c d
#> <int> <char> <int> <fctr>
#> 1: 1 a 11 a
#> 2: 1 b 3 b
#> 3: 1 c 3 c
#> 4: 2 d 3 d
#> 5: 2 e 3 e
#> 6: 2 f 4 f
#> 7: 2 g 4 g
#> 8: 8 h 18 h
#> 9: 9 i 19 i
#> 10: 10 j 20 j
obj <- data.table::data.table(a = 1:10, b = letters[1:10], c = 11:20, d = factor(letters[1:10]))
dt_setcoe(obj, vars = is.numeric, v = as.numeric)
str(obj)
#> Classes 'data.table' and 'data.frame': 10 obs. of 4 variables:
#> $ a: num 1 2 3 4 5 6 7 8 9 10
#> $ b: chr "a" "b" "c" "d" ...
#> $ c: num 11 12 13 14 15 16 17 18 19 20
#> $ d: Factor w/ 10 levels "a","b","c","d",..: 1 2 3 4 5 6 7 8 9 10
#> - attr(*, ".internal.selfref")=<externalptr>
ss2_set(obj,
obs = ~ (a >= 2) & (c <= 17), vars = is.numeric,
tf = sqrt # SAFE: coercion performed by dt_setcoe(); so no warnings
)
print(obj)
#> a b c d
#> <num> <char> <num> <fctr>
#> 1: 1.000000 a 11.000000 a
#> 2: 1.414214 b 3.464102 b
#> 3: 1.732051 c 3.605551 c
#> 4: 2.000000 d 3.741657 d
#> 5: 2.236068 e 3.872983 e
#> 6: 2.449490 f 4.000000 f
#> 7: 2.645751 g 4.123106 g
#> 8: 8.000000 h 18.000000 h
#> 9: 9.000000 i 19.000000 i
#> 10: 10.000000 j 20.000000 j
obj <- data.table::data.table(a = 1:10, b = letters[1:10], c = 11:20, d = factor(letters[1:10]))
str(obj) # notice that columns "a" and "c" are INTEGER (`int`)
#> Classes 'data.table' and 'data.frame': 10 obs. of 4 variables:
#> $ a: int 1 2 3 4 5 6 7 8 9 10
#> $ b: chr "a" "b" "c" "d" ...
#> $ c: int 11 12 13 14 15 16 17 18 19 20
#> $ d: Factor w/ 10 levels "a","b","c","d",..: 1 2 3 4 5 6 7 8 9 10
#> - attr(*, ".internal.selfref")=<externalptr>
ss2_set(
obj, vars = is.numeric,
tf = sqrt # SAFE: row=NULL & obs = NULL, so coercion performed
)
str(obj)
#> Classes 'data.table' and 'data.frame': 10 obs. of 4 variables:
#> $ a: num 1 1.41 1.73 2 2.24 ...
#> $ b: chr "a" "b" "c" "d" ...
#> $ c: num 3.32 3.46 3.61 3.74 3.87 ...
#> $ d: Factor w/ 10 levels "a","b","c","d",..: 1 2 3 4 5 6 7 8 9 10
#> - attr(*, ".internal.selfref")=<externalptr>