R Under development (unstable) (2024-04-23 r86473 ucrt) -- "Unsuffered Consequences"
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> attach(asNamespace("epigrowthfit"))
> library(methods)
> library(tools)
> options(warn = 2L, error = if (interactive()) recover)
> 
> o.1 <- egf_cache("egf-1.rds")
> o.2 <- egf_cache("egf-2.rds")
> 
> 
> ## egf_has_random ######################################################
> 
> e <- new.env()
> e[["data"]] <- list()
> o <- list(tmb_out = list(env = e))
> class(o) <- "egf"
> 
> e[["data"]][["Z"]] <- matrix(0, 3L, 3L)
> stopifnot( egf_has_random(o))
> 
> e[["data"]][["Z"]] <- matrix(0, 3L, 0L)
> stopifnot(!egf_has_random(o))
> 
> 
> ## egf_has_converged ###################################################
> 
> o <- list(optimizer_out = list(convergence = 0L),
+           value = 100,
+           gradient = runif(10L, -0.5, 0.5),
+           hessian = TRUE)
> class(o) <- c("egf", "list") # "list" only for dispatch to within.list
> 
> stopifnot(exprs = {
+ 	egf_has_converged(o)
+ 	!egf_has_converged(within(o, optimizer_out[["convergence"]] <- 1L))
+ 	!egf_has_converged(within(o, value <- NaN))
+ 	!egf_has_converged(within(o, gradient[1L] <- 10))
+ 	!egf_has_converged(within(o, hessian <- FALSE))
+ 	is.na(egf_has_converged(within(o, hessian <- NA)))
+ })
> 
> 
> ## egf_par_expand   ####################################################
> ## egf_par_condense ####################################################
> 
> t.2 <- o.2[["tmb_out"]]
> p.2 <- t.2[["env"]][["last.par.best"]]
> 
> p.2e <- egf_par_expand(t.2, p.2)
> p.2ec <- egf_par_condense(t.2, p.2e)
> 
> len <- c(table(factor(names(p.2), levels = c("beta", "theta", "b"))))
> 
> stopifnot(exprs = {
+ 	all.equal(p.2e, structure(c(p.2[1:4], theta = 0, p.2[-(1:4)]),
+ 	                          len = len + c(0L, 1L, 0L), names = NULL))
+ 	all.equal(p.2ec, structure(p.2, len = len, names = NULL))
+ })
> 
> 
> ## egf_report   ########################################################
> ## egf_adreport ########################################################
> 
> identical. <-
+ function(x, y, ...) {
+ 	x[["env"]] <- y[["env"]] <- NULL
+ 	identical(x, y, ...)
+ }
> 
> r.1 <- o.1[["tmb_out"]][["env"]][[".__egf__."]][["report"]]
> r.1. <- egf_report(o.1)
> stopifnot(identical.(r.1., r.1))
> 
> o.1[["tmb_out"]][["env"]][[".__egf__."]][["report"]] <- NULL
> r.1. <- egf_report(o.1)
> stopifnot(identical.(r.1., r.1))
> 
> r.1 <- o.1[["tmb_out"]][["env"]][[".__egf__."]][["adreport"]]
> r.1. <- egf_adreport(o.1)
> stopifnot(identical.(r.1., r.1))
> 
> o.1[["tmb_out"]][["env"]][[".__egf__."]][["adreport"]] <- NULL
> assertCondition(r.1. <- egf_adreport(o.1), "message")
computing a Hessian matrix ...
> stopifnot(identical.(r.1., r.1))
> 
> 
> ## egf_cache ###########################################################
> 
> ## see example("egf_cache")
> 
> proc.time()
   user  system elapsed 
   1.93    0.25    2.15