optimize_indicator_matrix: Optimize Binary Indicator Matrix with Row Uniformity

In stnava/ANTsR: ANTs in R: Quantification Tools for Biomedical Images

Optimize Binary Indicator Matrix with Row Uniformity

Description

This function optimizes the sum of the matrix 'm * I', where 'I' is a binary indicator matrix with the constraint that each column may have only one non-zero entry. It ensures that the distribution of 1's is uniform across rows, softens the constraint to avoid infinite loops, and includes an optional verbose output to report the progress of the optimization.

Usage

optimize_indicator_matrix(
  m,
  max_iter = 1000,
  tol = 0.000001,
  preprocess = TRUE,
  verbose = FALSE
)

Arguments

m	A numeric matrix to optimize.
max_iter	The maximum number of iterations to avoid infinite loops. Default is 1000.
tol	A numeric value representing the tolerance for convergence. If the change in the objective function is less than this value, the loop stops. Default is 1e-6.
preprocess	Logical. If TRUE, flips the sign of each row where the entries are predominantly negative.
verbose	Logical. If TRUE, reports the objective value and convergence progress at each iteration.

Value

'm * I'

Examples

set.seed(123)
m <- matrix(rnorm(500), nrow = 5)
result <- optimize_indicator_matrix(m, max_iter = 1000, tol = 1e-6, verbose = TRUE)
print(result)

stnava/ANTsR documentation built on April 13, 2025, 4:10 a.m.