mortality vs mortality_total and custom output

[vbartolino]

A question more than an issue:
what's the difference between mortality and mortality_totalin fit$stock.prey?

I also wonder if/how a user can "customise" the output (similarly to the old printfiles).

[lentinj]

what's the difference between mortality and mortality_totalin fit$stock.prey?

AFAICS the former is for fleets, the latter for biological consumption / predators:

gadgetutils/R/g3_fit.R

Lines 532 to 561 in 3b0e24d

	## Stock prey - fleet consumption first
	stock.prey <-
	fleet_reports %>%
	dplyr::filter(fleet %in% fleet_names) %>%
	dplyr::group_by(.data$year, .data$step, .data$area, .data$stock, .data$age) %>%
	dplyr::summarise(number_consumed = sum(.data$number_consumed),
	biomass_consumed = sum(.data$biomass_consumed), .groups = 'drop') %>%
	dplyr::mutate(age = gsub('age', '', .data$age) %>% as.numeric()) %>%
	dplyr::left_join(stock.std %>%
	dplyr::select(.data$year, .data$step, .data$area, .data$stock, .data$age, .data$number),
	by = c("year", "step", "area", "stock", "age")) %>%
	dplyr::mutate(mortality = -log(1 - .data$number_consumed / .data$number)/step_size) %>%
	tidyr::replace_na(list(mortality = 0))
	## Add in biological consumption if included in model
	if (length(fleet_names) < length(pred_names)){
	stock.prey <-
	stock.prey %>%
	dplyr::left_join(
	fleet_reports %>%
	dplyr::group_by(.data$year, .data$step, .data$area, .data$stock, .data$age) %>%
	dplyr::summarise(number_consumed_total = sum(.data$number_consumed),
	biomass_consumed_total = sum(.data$biomass_consumed), .groups = 'drop') %>%
	dplyr::mutate(age = gsub('age', '', .data$age) %>% as.numeric()),
	by = c('year','step','area','stock','age')) %>%
	dplyr::mutate(mortality_total = -log(1 - .data$number_consumed_total / .data$number)/step_size) %>%
	tidyr::replace_na(list(mortality_total = 0))
	}

I also wonder if/how a user can "customise" the output (similarly to the old printfiles).

What would you like to generate? Using g3_array_agg() on the g3 report I'm hoping would meet most needs, something like this say:

obj.fn <- g3_tmb_adfun(tmb_model, params.proj, Type = "Fun")
r <- obj.fn$report()
g3_array_agg(r$detail_rin_imm_hunt.rin__cons, c("year"))

[vbartolino]

AFAICS the former is for fleets, the latter for biological consumption / predators:

do I understand correctly that background mortality from g3a_naturalmortality is not included in mortality_total? that's perfectly fine, but useful to know as users may want to visualise all the three sources of mortality:
M1 (background) + M2 (predation) + F (fishing)

[lentinj]

do I understand correctly that background mortality from g3a_naturalmortality is not included in mortality_total?

Correct, mortality is fishing+predation mortality. I don't remember including g3a_naturalmortality coming up before, and it's not something that gets reported by g3 currently.

The cheating answer to get M1+M2+F would be to compare abundance to the following timestep. But obviously this would only work at high levels of aggregation (otherwise you have to account for ageing, maturity, etc).

[willbutler42]

A question more than an issue: what's the difference between mortality and mortality_totalin fit$stock.prey?

I also wonder if/how a user can "customise" the output (similarly to the old printfiles).

@vbartolino "Mortality" is, as Jamie mentioned, for fleets alone... however, "mortality_total" is for fleets and natural predators combined.

Regarding customisation, no options exist within g3_fit at the moment. To calculate F over a specified age-range we re-calculate it from stock.full externally atm, but this would be a fairly simple option for g3_fit, something along the lines of:
https://github.com/gadget-framework/rgadget/blob/master/R/gadgetfit.R#L316