sk_mat2vec: Column-vectorization indices

In snapKrig: Fast Kriging and Geostatistics on Grids with Kronecker Covariance

Column-vectorization indices

Description

Maps matrix indices i, j to a single vectorized index, k

Usage

sk_mat2vec(ij, gdim, simplified = TRUE)

Arguments

ij	n x 2 matrix, the row and column indices
gdim	integer (or vector with first element equal to) the number of rows in the matrix
simplified,	if FALSE, the function returns an n x 1 matrix

Details

Column vectorization (as in base::as.vector) builds a length(mn) vector by stacking the columns of an m X n matrix, with the leftmost column appearing first in the vector and the rightmost column last. Matrix element i,j gets mapped to element k = i + m * (j-1) in the vector. This function returns that index.

ij can be a matrix or a list of length-n vectors 'i' and 'j', or a vector representing a single point at the given row (i) and column (j) number (in that order).

gdim should either be an integer number of rows in the matrix, or a vector of the form c(ni, nj) (the return value of dim for example) in which case its first element is used.

Value

integer vector, the vectorized ij indices

See Also

Other indexing functions: sk_rescale(), sk_sub_find(), sk_sub_idx(), sk_vec2mat()

Examples

# define matrix dimensions and look up a specific index
gdim = c(4, 5)
ij = c(i=3, j=2)
sk_mat2vec(ij, gdim)

# display all matrix indices in column-vectorized order
gyx = expand.grid(i=seq(gdim[1]), j=seq(gdim[2]))
result = sk_mat2vec(gyx, gdim)
data.frame(k=result, gyx)

snapKrig documentation built on May 31, 2023, 6:34 p.m.