R/nlcg.R

In rHanso: An R Implementation of Hybrid Algorithm for Non-Smooth Optimization (HANSO)

nlcg <- function(fn, gr, nvar = 0, nstart = 10, x0 = NULL, upper = 1, lower = 0, H0 = NULL, maxit = 1000, 
  fvalquit = -Inf, prtlevel = 0, version = "C", normtol = 1e-06, xnormquit = Inf, evaldist = 1e-04, ngrad = 0, 
  scale = 1, wolfe1 = 1e-04, wolfe2 = 0.5, quitLSfail = TRUE, strongwolfe = 1) {
  if (!is.null(x0)) {
    
    if (class(x0) == "numeric") {
      x0 <- t(x0)
      nstart <- 1
      nvar = length(x0)
    } else if (class(x0) == "matrix") {
      nvar <- nrow(x0)
      nstart <- ncol(x0)
    } else stop("unknown initial value matrix, please enter a numeric vector or matrix")
  } else {
    nstart <- 10
    M <- matrix(runif(nvar * nstart), nrow = nvar, ncol = nstart)
    x0 <- (upper - lower) * M + lower
  }
  
  
  x <- matrix(NA, nvar, nstart)
  f <- c()
  g <- matrix(NA, nvar, nstart)
  frec <- list()
  alpharec <- list()
  message <- list()
  for (run in 1:nstart) {
    tmp <- nlcg1run(fn, gr, x0[, run], H0, maxit, fvalquit, strongwolfe, version, prtlevel, normtol, 
      xnormquit, evaldist, ngrad, scale, wolfe1, wolfe2, quitLSfail)
    # print(tmp)
    x[, run] <- tmp$x
    f[run] <- tmp$f
    g[, run] <- tmp$g
    frec[[run]] <- tmp$frec
    alpharec[[run]] <- tmp$alpharec
    message[[run]] <- tmp$message
  }
  list(x = x, f = f, g = g, frec = frec, alpharec = alpharec, message = message)
}