tgstat (version 2.3.28)

tgs_knn: Returns k highest values of each column

Description

Returns k highest values of each column.

Usage

tgs_knn(x, knn, diag = FALSE, threshold = 0)

Value

A sparse matrix in a data frame format with 'col1', 'col2', 'val' and 'rank' columns. 'col1' and 'col2' represent the column and the row number of 'x'.

Arguments

x

numeric matrix or data frame (see below)

knn

the number of highest values returned per column

diag

if 'F' values of row 'i' and col 'j' are skipped for each i == j

threshold

filter out values lower than threshold

Details

'tgs_knn' returns the highest 'knn' values of each column of 'x' (if 'x' is a matrix). 'x' can be also a sparse matrix given in a data frame of 'col', 'row', 'value' format.

'NA' and 'Inf' values are skipped as well as the values below 'threshold'. If 'diag' is 'F' values of the diagonal (row == col) are skipped too.

Examples

# \donttest{
# Note: all the available CPU cores might be used

set.seed(seed = 1)
rows <- 100
cols <- 1000
vals <- sample(1:(rows * cols / 2), rows * cols, replace = TRUE)
m <- matrix(vals, nrow = rows, ncol = cols)
m[sample(1:(rows * cols), rows * cols / 1000)] <- NA
r <- tgs_knn(m, 3)
# }

# \dontshow{
options(tgs_use.blas = FALSE)
options(tgs_max.processes = 1)

set.seed(seed = 1)
rows <- 100
cols <- 100
vals <- sample(1:(rows * cols / 2), rows * cols, replace = TRUE)
m <- matrix(vals, nrow = rows, ncol = cols)
m[sample(1:(rows * cols), rows * cols / 1000)] <- NA
r <- tgs_knn(m, 3)
# }