Arg-K-min reduction

Arg-K-min reduction for LazyTensor objects.

Usage

argKmin(x, K, index)

argKmin_reduction(x, K, index)

Arguments

x

a LazyTensor or a ComplexLazyTensor.

K

An integer corresponding to the number of minimal values required.

index

a character corresponding to the reduction dimension that should be either "i" or "j" to specify whether if the reduction is indexed by "i" or "j".

Value

A matrix corresponding to the argKmin reduction.

Details

If x is a LazyTensor or a ComplexLazyTensor, argKmin(x, K, index) will:

• if index = "i", return the indices of the K minimal values of x over the i indexes.

• if index = "j", return the indices of the K minimal values of x over the j indexes.

Note: Run browseVignettes("rkeops") to access the vignettes and find details about this function in the "RKeOps LazyTensor" vignette, at section "Reductions".

Author

Chloe Serre-Combe, Amelie Vernay

Examples

if (FALSE) {
x <- matrix(runif(150 * 3), 150, 3) # arbitrary R matrix, 150 rows, 3 columns
x_i <- LazyTensor(x, index = 'i')   # creating LazyTensor from matrix x, 
                                    # indexed by 'i'
K <- 2
argkmin_x <- argKmin(x_i, K, "i")   # argKmin reduction 
                                    # indexed by 'i'

}
if (FALSE) {
x <- matrix(runif(150 * 3), 150, 3) # arbitrary R matrix, 150 rows, 3 columns
x_i <- LazyTensor(x, index = 'i')   # creating LazyTensor from matrix x, 
                                    # indexed by 'i'
K <- 2
argkmin_red_x <- argKmin_reduction(x_i, K, "i")  # argKmin reduction 
                                                 # indexed by 'i'
}