This function allows you extract the proportions of the iterations for which c, n and p are the limiting element in the model.

limitation(mod, plot = TRUE)

Arguments

mod

Model output from cnp_model_mcmc().

plot

Argument to specify if results should be shown in a plot.

Value

Returns a data frame with:

tl

Total length, in cm

nutrient

c, n or p

prop_lim

the proportion of iterations for which there is limitation by the element

Examples

library(fishflux)
mod <- cnp_model_mcmc(TL = 5, param = list(Qc_m = 40, Qn_m = 10, Qp_m = 4,
                                           Dc_sd = 0.1, Dn_sd = 0.05, Dp_sd = 0.05))
#> Warning: not inputting certain parameters may give wrong results
#> Warning: adding standard values for ac_m
#> Warning: adding standard values for an_m
#> Warning: adding standard values for ap_m
#> Warning: adding standard values for Dc_m
#> Warning: adding standard values for Dn_m
#> Warning: adding standard values for Dp_m
#> Warning: adding standard values for linf_m
#> Warning: adding standard values for k_m
#> Warning: adding standard values for t0_m
#> Warning: adding standard values for theta_m
#> Warning: adding standard values for r_m
#> Warning: adding standard values for h_m
#> Warning: adding standard values for lwa_m
#> Warning: adding standard values for lwb_m
#> Warning: adding standard values for mdw_m
#> Warning: adding standard values for v_m
#> Warning: adding standard values for F0nz_m
#> Warning: adding standard values for F0pz_m
#> Warning: adding standard values for alpha_m
#> Warning: adding standard values for f0_m
#> Warning: adding standard values for lt_sd
#> Warning: adding standard values for ac_sd
#> Warning: adding standard values for an_sd
#> Warning: adding standard values for ap_sd
#> Warning: adding standard values for linf_sd
#> Warning: adding standard values for k_sd
#> Warning: adding standard values for t0_sd
#> Warning: adding standard values for theta_sd
#> Warning: adding standard values for r_sd
#> Warning: adding standard values for h_sd
#> Warning: adding standard values for lwa_sd
#> Warning: adding standard values for lwb_sd
#> Warning: adding standard values for mdw_sd
#> Warning: adding standard values for v_sd
#> Warning: adding standard values for F0nz_sd
#> Warning: adding standard values for F0pz_sd
#> Warning: adding standard values for Qc_sd
#> Warning: adding standard values for Qn_sd
#> Warning: adding standard values for Qp_sd
#> Warning: adding standard values for alpha_sd
#> Warning: adding standard values for f0_sd
#> 
#> SAMPLING FOR MODEL 'cnpmodelmcmc' NOW (CHAIN 1).
#> Chain 1: Iteration:   1 / 1000 [  0%]  (Sampling)
#> Chain 1: Iteration: 100 / 1000 [ 10%]  (Sampling)
#> Chain 1: Iteration: 200 / 1000 [ 20%]  (Sampling)
#> Chain 1: Iteration: 300 / 1000 [ 30%]  (Sampling)
#> Chain 1: Iteration: 400 / 1000 [ 40%]  (Sampling)
#> Chain 1: Iteration: 500 / 1000 [ 50%]  (Sampling)
#> Chain 1: Iteration: 600 / 1000 [ 60%]  (Sampling)
#> Chain 1: Iteration: 700 / 1000 [ 70%]  (Sampling)
#> Chain 1: Iteration: 800 / 1000 [ 80%]  (Sampling)
#> Chain 1: Iteration: 900 / 1000 [ 90%]  (Sampling)
#> Chain 1: Iteration: 1000 / 1000 [100%]  (Sampling)
#> Chain 1: 
#> Chain 1:  Elapsed Time: 0 seconds (Warm-up)
#> Chain 1:                0.01482 seconds (Sampling)
#> Chain 1:                0.01482 seconds (Total)
#> Chain 1: 
limitation(mod)
#> geom_path: Each group consists of only one observation. Do you need to adjust
#> the group aesthetic?

#>   tl nutrient prop_lim
#> 1  5        c    0.000
#> 2  5        n    0.634
#> 3  5        p    0.366