R Under development (unstable) (2024-05-16 r86559 ucrt) -- "Unsuffered Consequences"
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Platform: x86_64-w64-mingw32/x64

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> if (!(requireNamespace("adaptivetau") && requireNamespace("deSolve")))
+ 	q("no")
Loading required namespace: adaptivetau
Loading required namespace: deSolve
> 
> library(fastbeta)
> options(warn = 2L, error = if (interactive()) utils::recover)
> 
> beta <- function (t, a = 1e-01, b = 1e-05) b * (1 + a * sinpi(t / 26))
> nu   <- function (t) 1e+03
> mu   <- function (t) 1e-03
> 
> sigma <- 0.5
> gamma <- 0.5
> delta <- 0
> 
> m <- 1L
> n <- 1L
> p <- m + n + 2L
> init <- fastbeta:::seir.ee(beta(0), nu(0), mu(0), sigma, gamma, delta, m, n)
> 
> stopifnot(exprs = {
+ 	is.double(init)
+ 	length(init) == p
+ 	!anyNA(init)
+ 	min(init) >= 0
+ 	all.equal(sum(init), nu(0) / mu(0))
+ })
> 
> init <- trunc(init)
> 
> length.out <- 250L
> prob <- 0.1
> delay <- diff(stats::pgamma(0L:8L, 2.5))
> 
> ## At the very least, these should not signal warnings or
> ## errors unexpectedly, and the compiled and uncompiled
> ## code should generate equal results
> 
> seir2 <-
+ function (stochastic, useCompiled)
+ {
+ 	set.seed(0L)
+ 	seir(length.out, beta, nu, mu, sigma, gamma, delta, init, m, n,
+ 	     stochastic, prob, delay, useCompiled)
+ }
> 
> L <- .mapply(seir2,
+              list(stochastic  = c(FALSE,  TRUE, FALSE, TRUE),
+                   useCompiled = c(FALSE, FALSE,  TRUE, TRUE)),
+              NULL)
> dim(L) <- c(2L, 2L)
> 
> X <- L[[1L, 1L]]
> 
> stopifnot(exprs = {
+ 	all.equal(L[, 1L], L[, 2L], tolerance = 1/sum(init))
+ 	is.double(X)
+ 	stats::is.mts(X)
+ 	identical(dim(X), c(length.out, p + 3L))
+ 	identical(dimnames(X), list(NULL, rep.int(c("S", "E", "I", "R", "Z", "B", "Z.obs"), c(1L, m, n, 1L, 1L, 1L, 1L))))
+ 	identical(stats::tsp(X), c(0, length.out - 1, 1))
+ 	!anyNA(X[-1L, ])
+ 	min(0, X, na.rm = TRUE) >= 0
+ })
> 
> if (grDevices::dev.interactive(TRUE))
+ 	plot(X)
> 
> tools::assertError(seir(0L, beta, nu, mu, sigma, gamma, delta, init, m, n))
> 
> proc.time()
   user  system elapsed 
   0.28    0.10    0.37