Использование data.table
...
library(data.table)
grid <- expand.grid(
x1 = seq(0, 100)
, x2 = seq(0, 100)
, x3 = seq(0, 100)
)
setDT(grid)
res <- grid[grid[, rowSums(.SD) == 100], ]
res[, summation := rowSums(.SD)]
Результат:
> res[, unique(summation)]
[1] 100
Это также можно сделать в base
, но data.table
быстрее:
library(data.table)
grid <- expand.grid(
x1 = seq(0, 100)
, x2 = seq(0, 100)
, x3 = seq(0, 100)
)
grid2 <- expand.grid(
x1 = seq(0, 100)
, x2 = seq(0, 100)
, x3 = seq(0, 100)
)
setDT(grid)
microbenchmark::microbenchmark(
data.table = {
res <- grid[grid[, rowSums(.SD) == 100], ]
},
base = {
res2 <- grid2[rowSums(grid2) == 100, ]
}
)
Unit: milliseconds
expr min lq mean median uq max neval cld
data.table 59.41157 89.6700 109.0462 107.7415 124.2675 183.9730 100 a
base 65.70521 109.6471 154.1312 125.4238 156.9168 611.0169 100 b