## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) options(rmarkdown.html_vignette.check_title = FALSE) ## ----setup, echo = FALSE------------------------------------------------------ library(optistock) ## ---- cpf_curve, fig.height = 4, fig.width = 7, echo = FALSE------------------ curve( cost_per_fish( time_at_stocking = x, time_at_rec = 1000, n_recruits_desired = 200, cost_fun = linear_total_cost, cost_fun_args = list(int = 20, beta = 0.01), mort_fun = exp_mort, mort_fun_args = list( m_init = 0.001, m_inf = 0.0001, alpha = 0.05, t_scale = 200 ) ), 0, 1000, xlab = "Time (days)", ylab = "Cost-per-fish ($)" ) ## ---- cpf_curve_code, fig.height = 4, fig.width = 7, eval = FALSE------------- # curve( # cost_per_fish( # time_at_stocking = x, # time_at_rec = 1000, # n_recruits_desired = 200, # cost_fun = linear_total_cost, # cost_fun_args = list(int = 20, beta = 0.01), # mort_fun = exp_mort, # mort_fun_args = list( # m_init = 0.001, m_inf = 0.0001, alpha = 0.05, t_scale = 200 # ) # ), # 0, 1000, # xlab = "Time (days)", ylab = "Cost-per-fish ($)" # ) ## ---- fig.height = 4, fig.width = 7------------------------------------------- time <- 1:1000 linf <- 50 k <- 0.4 / 365 t0 <- -0.5 * 365 len_at_age <- vbgf(time, linf, k, t0) plot(len_at_age ~ time, type = "l", xlab = "Age (days)", ylab = "Length") ## ---- fig.height = 4, fig.width = 7------------------------------------------- age_at_len <- inv_vb(len_at_age, linf, k, t0) plot(age_at_len ~ len_at_age, type = "l", xlab = "Length", ylab = "Age (days)") ## ---- mortality_curves, fig.height = 4, fig.width = 7------------------------- curve( exp_mort(x, m_init = 0.5, m_inf = 0.05, alpha = 0.05, t_scale = 200), 0, 1000, xlab = "Time (days)", ylab = "M" ) curve( decreasing_mort(x, m_init = 0.5, m_inf = 0.05, alpha = 0.99), 0, 1000, xlab = "Time (days)", ylab = "M" ) ## ---- linear_total_cost, fig.height = 4, fig.width = 7------------------------ recruits <- 1 int <- 1.2 beta <- 0.05 curve( linear_total_cost(x, recruits, int, beta), 0, 1000, xlab = "Time (days)", ylab = "Cost ($)" ) ## ---- total_daily_cost, fig.height = 4, fig.width = 7------------------------- init_cost <- 0.01 time_slope <- 0.01 time_exp <- 1.05 rec_slope <- 1 rec_exp <- 1 curve( total_daily_cost(x, recruits, init_cost, time_slope, time_exp, rec_slope, rec_exp), 0, 1000, xlab = "Time (days)", ylab = "Cost ($)" )