
Analyze growth patterns from FB4 results
Source:R/15.1-analysis-extraction.R
analyze_growth_patterns.RdExtracts and analyzes growth patterns from FB4 simulation results. Calculates growth rates, efficiency metrics, and provides uncertainty estimates when available.
Value
A named list with at minimum method (character),
has_uncertainty (logical), individual_id, and
initial_weight (numeric, g). The following growth metrics are
included as sub-lists each with estimate, se, ci_lower,
and ci_upper: final_weight (g), total_growth (g),
and relative_growth (%). When simulation duration is available,
daily_growth_rate (g/day) and specific_growth_rate
(%/day) are appended. For fitted methods a p_value sub-list
(estimate, se) is also included; for hierarchical
population-level calls, n_individuals (integer) is added.
Examples
# \donttest{
data(fish4_parameters)
sp <- fish4_parameters[["Oncorhynchus tshawytscha"]]$life_stages$adult
info <- fish4_parameters[["Oncorhynchus tshawytscha"]]$species_info
bio <- Bioenergetic(
species_params = sp,
species_info = info,
environmental_data = list(
temperature = data.frame(Day = 1:30, Temperature = rep(12, 30))
),
diet_data = list(
proportions = data.frame(Day = 1:30, Prey1 = 1.0),
energies = data.frame(Day = 1:30, Prey1 = 5000),
prey_names = "Prey1"
),
simulation_settings = list(initial_weight = 100, duration = 30)
)
#> Bioenergetic object created for: Oncorhynchus tshawytscha
bio$species_params$predator$ED_ini <- 5000
bio$species_params$predator$ED_end <- 5500
result <- run_fb4(bio, strategy = "direct", p_value = 0.5, verbose = FALSE)
#> Validation warnings:
#> Missing optional parameters (will be calculated): CG1, CG2
#> Object is ready for simulation
#> Validation warnings:
#> Missing optional parameters (will be calculated): CG1, CG2
#> Object is ready for simulation
#> Processing species parameters...
#> Processing temporal data...
#> No indigestible fraction data provided, using default 0% for all prey (FB4 default)
#> Processing simulation settings...
#> Simulation data preparation complete. Ready for simulation.
growth <- analyze_growth_patterns(result)
# }