plotlsirm (version 0.1.3)

vec_mat_dist: Euclidean distance from a single vector to each row of a matrix

Description

Calculates the Euclidean distance between a reference vector v and every row of a matrix mat. This is a thin wrapper around rowSums() and avoids an explicit loop, so it is fast even for large matrices.

Usage

vec_mat_dist(v, mat)

Value

A numeric vector of length n containing the Euclidean distance between v and each corresponding row of mat.

Arguments

v

Numeric vector of length d. The reference point in d-dimensional space.

mat

Numeric matrix with n rows and d columns. Each row is treated as a point whose distance from v is to be computed. The number of columns in mat must match length(v).

Details

Internally the function replicates v into an \(n \times d\) matrix, subtracts it from mat, squares the element-wise differences, sums across columns, and finally takes the square root, i.e. $$d_i = \sqrt{\sum_{k=1}^d (m_{ik} - v_k)^2}$$ for each row i. Because the computation is fully vectorised it is considerably faster than a simple apply() or a for-loop implementation.

Examples

# Two-dimensional example
v   <- c(0, 0)
mat <- matrix(c(1, 0,
                0, 2,
                3, 4),
              ncol = 2, byrow = TRUE)

vec_mat_dist(v, mat)
#> [1] 1 2 5