R Under development (unstable) (2024-07-01 r86857 ucrt) -- "Unsuffered Consequences"
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Platform: x86_64-w64-mingw32/x64

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> library(unittest)
> if (!interactive()) options(warn=2, error = function() { sink(stderr()) ; traceback(3) ; q(status = 1) })
> 
> library(gadget3)
> 
> actions <- list()
> area_names <- g3_areas(c('AA', 'BB', 'CC'))
> 
> st_imm_f <- g3_stock(c(species = "fish", maturity = 'imm', sex = 'f'), seq(5L, 25L, 5)) |>
+   g3s_livesonareas(area_names["AA"]) |>
+   g3s_age(1L, 5L)
> st_imm_m <- g3_stock(c(species = "fish", maturity = 'imm', sex = 'm'), seq(5L, 25L, 5)) |>
+   g3s_livesonareas(area_names["AA"]) |>
+   g3s_age(1L, 5L)
> st_mat <- g3_stock(c(species = "fish", maturity = 'mat'), seq(5L, 25L, 5)) |>
+   g3s_livesonareas(area_names["AA"]) |>
+   g3s_age(3L, 10L)
> 
> actions <- list(
+   g3a_time(
+     1980, 1995,
+     step_lengths = c(6L, 6L)),
+   g3a_initialconditions(st_imm_f, quote( 0 * stock__midlen ), quote( 0 * stock__midlen )),
+   g3a_initialconditions(st_imm_m, quote( 0 * stock__midlen ), quote( 0 * stock__midlen )),
+   g3a_initialconditions_normalcv(st_mat),
+   g3a_spawn(
+     st_mat,
+     recruitment_f = g3a_spawn_recruitment_bevertonholt(
+       mu = g3_parameterized('spawn_mu', value = 5, by_year = TRUE),
+       lambda = g3_parameterized("spawn_lambda", value = 1, by_stock = TRUE) ),
+     proportion_f = g3_suitability_exponentiall50(),
+     output_stocks = list(st_imm_f, st_imm_m),
+     output_ratios = list(
+       st_imm_f = quote( g3_param('spawn_ratio', value = 0.5) ),
+       st_imm_m = quote( 1 - g3_param('spawn_ratio', value = 0.5) )),
+     run_f = quote( cur_step == 1 ) ),
+   g3a_age(st_imm_f),
+   g3a_age(st_imm_m),
+   g3a_age(st_mat) )
> 
> # Compile model
> model_fn <- g3_to_r(c(actions, list(
+   g3a_report_history(actions, c(
+       '__offspringnum$',
+       '__num$',
+       '__wgt$' )))))
> if (nzchar(Sys.getenv('G3_TEST_TMB'))) {
+   model_cpp <- g3_to_tmb(c(actions, list(
+     g3a_report_history(actions, c(
+         '__offspringnum$',
+         '__num$',
+         '__wgt$' )))))
+     # model_cpp <- edit(model_cpp)
+     model_tmb <- g3_tmb_adfun(model_cpp, compile_flags = c("-O0", "-g"))
+ } else {
+     writeLines("# skip: not compiling TMB model")
+ }
# skip: not compiling TMB model
> 
> estimate_l50 <- g3_stock_def(st_mat, "midlen")[[length(g3_stock_def(st_mat, "midlen")) / 2]]
> estimate_linf <- max(g3_stock_def(st_mat, "midlen"))
> 
> for (spawn_ratio in runif(5)) ok_group(paste0("spawn_ratio: ", spawn_ratio), {
+   attr(model_fn, 'parameter_template') |>
+     g3_init_val("*.Linf", estimate_linf, spread = 0.2) |>
+     g3_init_val("*.walpha", 0.01, optimise = FALSE) |>
+     g3_init_val("*.wbeta", 3, optimise = FALSE) |>
+ 
+     g3_init_val("*.*.l50", estimate_l50, spread = 0.25) |>
+     g3_init_val("spawn_ratio", spawn_ratio) |>
+ 
+     identity() -> params
+ 
+   r <- attributes(model_fn(params))
+   num_spawn <- colSums(r$hist_fish_mat__offspringnum, dims = 3)
+   num_m <- colSums(r$hist_fish_imm_m__num, dims = 3)
+   num_f <- colSums(r$hist_fish_imm_f__num, dims = 3)
+ 
+   ok(ut_cmp_equal(
+     cumsum(num_spawn * (1 - spawn_ratio)),
+     num_m,
+     tolerance = 1e-8), "hist_fish_imm_m__num: Cumulative proportion of __offspringnum")
+   ok(ut_cmp_equal(
+     cumsum(num_spawn * spawn_ratio),
+     num_f,
+     tolerance = 1e-8), "hist_fish_imm_f__num: Cumulatve proportion of __offspringnum")
+ 
+     if (nzchar(Sys.getenv('G3_TEST_TMB'))) {
+         param_template <- attr(model_cpp, "parameter_template")
+         param_template$value <- params[param_template$switch]
+         gadget3:::ut_tmb_r_compare(model_fn, model_tmb, param_template)
+     }
+ })
# spawn_ratio: 0.726525562815368
ok - hist_fish_imm_m__num: Cumulative proportion of __offspringnum
ok - hist_fish_imm_f__num: Cumulatve proportion of __offspringnum
# spawn_ratio: 0.971573524875566
ok - hist_fish_imm_m__num: Cumulative proportion of __offspringnum
ok - hist_fish_imm_f__num: Cumulatve proportion of __offspringnum
# spawn_ratio: 0.155931616434827
ok - hist_fish_imm_m__num: Cumulative proportion of __offspringnum
ok - hist_fish_imm_f__num: Cumulatve proportion of __offspringnum
# spawn_ratio: 0.118809117702767
ok - hist_fish_imm_m__num: Cumulative proportion of __offspringnum
ok - hist_fish_imm_f__num: Cumulatve proportion of __offspringnum
# spawn_ratio: 0.223352167988196
ok - hist_fish_imm_m__num: Cumulative proportion of __offspringnum
ok - hist_fish_imm_f__num: Cumulatve proportion of __offspringnum
> 
> proc.time()
   user  system elapsed 
   1.37    0.12    1.46 
# Looks like you passed all 10 tests.