In gadget-framework/rgadget: Tools to Create and Maintain Gadget Models

library(magrittr)
library(tibble)
library(Rgadget)
library(mfdb)

gd <- tempdir()

codimm <- 
  gadgetstock('codimm',gd,missingOkay = TRUE) %>%
  gadget_update('stock',
                minage = 1,
                maxage = 10,
                minlength = 4,
                maxlength = 130,
                dl = 2) %>%
  ## does"something" updates should also allow for other names, e.g. doesrenew -> recruitment etc..
  gadget_update('doesgrow',  
                ## 1) some error catching would be useful here to ensure that the inputs are valid
                ## i.e. make sure that the variables declared are valid
                ## 2) the following could be set as default values for this component, although 
                ## one might want to add the the name of the stock to the variable (like 'codimm.Linf') 
                growthfunction = 'lengthvbsimple',
                growthparameters = c(linf='#Linf',k='( * 0.001 #k)', '#walpha','#wbeta'),
                beta='(* 10 #bbin)', 
                maxlengthgroupgrowth=15) %>%
  gadget_update('naturalmortality',   
                ## here it would be useful to be able to call parameters defined above akin to dplyr::mutate  
                ## default value should be 0.2 repeated for all ages
                c(0.5,  0.35, 0.2, 0.2,  0.2, 0.2, 0.2, 0.2, 0.2, 0.3)) %>%
  gadget_update('refweight',
                ## would be useful to have an option to have just alpha and beta from the relationship 
                ## W=alpha*L^beta 
                ## also just supply a normal data.frame
                data=data_frame(length=seq(4,130,2),mean=6.5e-6*length^3.07)
  ) %>% 
  gadget_update('iseaten',1) %>% 
  gadget_update('doesmature', 
                maturityfunction = 'continuous',
                maturestocksandratios = 'codmat 1',
                coefficients = '( * 0.001 #cod.mat1) #cod.mat2 0 0') %>% 
  gadget_update('doesmove',
                transitionstockandratios = 'codmat 1',
                transitionstep = 4) %>% 
  gadget_update('doesrenew',
                ## year-step-area-age-number-mean-stddev-a-b
                normalparam = data_frame(year=1960:2016,
                                         step=1,
                                         area=1,
                                         age=1,
                                         number=sprintf('(* #cod.rec.scale #cod.rec.%s)',year),
                                         mean = to.gadget.formulae(quote(Linf * (1 - exp(-1 * (0.001 * k) * (1 - (1 + log(1 - recl/Linf)/(0.001 * k))))))),
                                         stddev=to.gadget.formulae(quote(cod.recl.sd)),
                                         alpha = '#walpha',
                                         beta = '#wbeta'))



codmat <- 
  gadgetstock('codmat',gd,missingOkay = TRUE) %>%
  gadget_update('stock',
                minage = 3,
                maxage = 12,
                minlength = 20,
                maxlength = 140,
                dl = 2) %>%
  ## does"something" updates should also allow for other names, e.g. doesrenew -> recruitment etc..
  gadget_update('doesgrow',  
                ## 1) some error catching would be useful here to ensure that the inputs are valid
                ## i.e. make sure that the variables declared are valid
                ## 2) the following could be set as default values for this component, although 
                ## one might want to add the the name of the stock to the variable (like 'codimm.Linf') 
                growthfunction = 'lengthvbsimple',
                growthparameters = c(linf='#Linf',k='( * 0.001 #k)', '#walpha','#wbeta'),
                beta='(* 10 #bbin)', 
                maxlengthgroupgrowth=15) %>%
  gadget_update('naturalmortality',   
                ## here it would be useful to be able to call parameters defined above akin to dplyr::mutate  
                ## default value should be 0.2 repeated for all ages
                c(0.2,  0.2,    0.2,    0.2,    0.2,    0.2,    0.2,    0.3,    0.5,    0.7)) %>%
  gadget_update('refweight',
                ## would be useful to have an option to have just alpha and beta from the relationship 
                ## W=alpha*L^beta 
                ## also just supply a normal data.frame 
                data=data_frame(length=seq(20,140,2),mean=3.5e-6*length^3.22)
  ) %>% 
  gadget_update('iseaten',1)