Symbolic weighted squared distance binary operation for LazyTensor
objects.
Arguments
- x
A
vector
of numeric values or a scalar value.- y
a
LazyTensor
, aComplexLazyTensor
, a vector of numeric values, or a scalar value.- s
a
LazyTensor
, aComplexLazyTensor
, a vector of numeric values, or a scalar value.
Details
weightedsqdist(x, y, s)
returns a LazyTensor
that encodes,
symbolically, the weighted squared distance of a vector x
with weights
stored in the LazyTensor s
, same as weightedsqnorm(x - y, s)
.
Note: x
, y
and s
should all have the same inner dimension.
Note: Run browseVignettes("rkeops")
to access the vignettes and find
details about this function in the "RKeOps LazyTensor" vignette, at
section "Simple vector operations".
Examples
if (FALSE) {
x <- matrix(runif(100 * 3), 100, 3) # arbitrary R matrix, 100 rows, 3 columns
y <- matrix(runif(100 * 3), 100, 3) # arbitrary R matrix, 100 rows, 3 columns
s <- matrix(runif(100 * 3), 100, 3) # arbitrary R matrix, 100 rows, 3 columns
x_i <- LazyTensor(x, index = 'i') # creating LazyTensor from matrix x,
# indexed by 'i'
y_j <- LazyTensor(y, index = 'j') # creating LazyTensor from matrix y,
# indexed by 'j'
s_i <- LazyTensor(s, index = 'i') # creating LazyTensor from matrix s,
# indexed by 'i'
wsqd_xy <- weightedsqdist(x_i, y_j, s_i) # symbolic matrix
}