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Merged Jim's changes to growth transition matrix
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@smartell
smartell committed Jan 15, 2015
2 parents 941ddbd + abc28c9 commit ca33d6d
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Showing 8 changed files with 958 additions and 217 deletions.
11 changes: 8 additions & 3 deletions Rsrc/R/plot-recruitment.R
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Expand Up @@ -23,9 +23,14 @@ plot_recruitment <- function(replist){
#' @return Plot of predicted recruitment compared across models
#' @author Cole Monnahan Kelli Johnson
#' @export
plot_models_recruitment <- function(data, modnames){
recs <- lapply(data, get_recruitment)
df <- do.call("rbind", Map(cbind, recs, modname = modnames))
plot_models_recruitment <- function(data, modnames=NULL ){
if (is.null(modnames))
modnames = paste("Model ",1:length(data))
if (length(data)!=length(modnames))
stop("Holy moly, unequal object lengths")

recs <- lapply(data, get_recruitment)
df <- do.call("rbind", Map(cbind, recs, modname = modnames))

p <- ggplot(df,aes(x=factor(year),y=exp(log_rec), group=modname, colour=modname))
p <- p + geom_line(stat = "identity", alpha=0.4)
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4 changes: 2 additions & 2 deletions Rsrc/R/plot-sizetransition.R
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Expand Up @@ -5,9 +5,9 @@
#' @export
plot_sizetransition <- function(replist){
A <- replist
df <- data.frame(stm = A$size_transition)
df <- data.frame(stm = A$size_transition_M,stm_f = A$size_transition_F)
colnames(df) <- A$mid_points
nrow <- dim(A$size_transition)[2]
nrow <- dim(A$size_transition_M)[2]
df$sex <- c(rep(1,length=nrow),rep(2,length=nrow))
df$col <- A$mid_points
mdf <- melt(df,id=c("sex","col"))
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139 changes: 139 additions & 0 deletions examples/bbrkc/bbrkc_ss.ctl
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@@ -0,0 +1,139 @@
# Model 1, fixed multinomial sample sizes
# —————————————————————————————————————————————————————————————————————————————————————— #
# Controls for leading parameter vector theta
# LEGEND FOR PRIOR:
# 0 -> uniform
# 1 -> normal
# 2 -> lognormal
# 3 -> beta
# 4 -> gamma
# —————————————————————————————————————————————————————————————————————————————————————— #
# ntheta
7
# —————————————————————————————————————————————————————————————————————————————————————— #
# ival lb ub phz prior p1 p2 # parameter #
# —————————————————————————————————————————————————————————————————————————————————————— #
0.18 0.01 1 -2 2 0.18 0.04 # M
7.0 -10 20 -1 1 3.0 5.0 # logR0
7.0 -10 20 2 1 3.0 5.0 # logR1
7.0 -10 20 2 1 3.0 5.0 # logRbar
72.5 55 100 -4 1 72.5 7.25 # Recruitment Expected Value
0.40 0.1 5 -3 0 0.1 5 # Recruitment scale (variance component)
-0.51 -10 0.75 -4 0 -10 0.75 # ln(sigma_R)
## ———————————————————————————————————————————————————————————————————————————————————— ##

## ———————————————————————————————————————————————————————————————————————————————————— ##
## GROWTH PARAM CONTROLS ##
## nGrwth
## ##
## Two lines for each parameter if split sex, one line if not ##
## ———————————————————————————————————————————————————————————————————————————————————— ##
# ival lb ub phz prior p1 p2 # parameter #
# —————————————————————————————————————————————————————————————————————————————————————— #
17.5 10.0 30.0 3 0 0.0 20.0 # alpha males or combined
0.10 0.0 0.5 3 0 0.0 10.0 # beta males or combined
6.0 1.0 30.0 3 0 0.0 3.0 # gscale males or combined
115. 65.0 165.0 2 0 0.0 3.0 # molt_mu males or combined
0.2 0.0 1.0 3 0 0.0 3.0 # molt_cv males or combined
# ———————————————————————————————————————————————————————————————————————————————————— ##

## ———————————————————————————————————————————————————————————————————————————————————— ##
## SELECTIVITY CONTROLS ##
## -Each gear must have a selectivity and a retention selectivity ##
## LEGEND sel_type:1=coefficients,2=logistic,3=logistic95 ##
## Index: use +ve for selectivity, -ve for retention
## sex dep: 0 for sex-independent, 1 for sex-dependent.
## ———————————————————————————————————————————————————————————————————————————————————— ##
## ivector for number of year blocks or nodes ##
## Gear-1 Gear-2 Gear-3 Gear-4
1 1 2 1 #Selectivity blocks
1 1 1 1 #Retention blocks
1 0 0 0 #male retention flag (0 -> no, 1 -> yes)
## ———————————————————————————————————————————————————————————————————————————————————— ##
## sel sel sel sex size year phz start end ##
## Index type mu sd dep nodes nodes mirror lam1 lam2 lam3 | block block ##
## ———————————————————————————————————————————————————————————————————————————————————— ##
## Selectivity P(capture of all sizes)
1 3 95 140 0 1 1 2 12.5 12.5 12.5 1975 2014
2 3 110 150 0 1 1 -2 12.5 12.5 12.5 1975 2014
3 2 90 10 0 1 1 2 12.5 12.5 12.5 1975 1981
3 2 90 10 0 1 1 2 12.5 12.5 12.5 1982 2014
4 2 70 10 0 1 1 -2 12.5 12.5 12.5 1975 2014
## ———————————————————————————————————————————————————————————————————————————————————— ##
## Retained
-1 2 135 2 0 1 1 -2 12.5 12.5 12.5 1975 2014
-2 2 95 10 0 1 1 -2 12.5 12.5 12.5 1975 2014
-3 2 90 10 0 1 1 -2 12.5 12.5 12.5 1975 2014
-4 2 90 10 0 1 1 -2 12.5 12.5 12.5 1975 2014
## ———————————————————————————————————————————————————————————————————————————————————— ##

## ———————————————————————————————————————————————————————————————————————————————————— ##
## PRIORS FOR CATCHABILITY
## TYPE: 0 = UNINFORMATIVE, 1 - NORMAL (log-space), 2 = time-varying (nyi)
## ———————————————————————————————————————————————————————————————————————————————————— ##
## SURVEYS/INDICES ONLY
## NMFS BSFRF
## TYPE Mean_q SD_q
1 0.896 0.13
0 0.001 0.01
## ———————————————————————————————————————————————————————————————————————————————————— ##
## ———————————————————————————————————————————————————————————————————————————————————— ##
## PENALTIES FOR AVERAGE FISHING MORTALITY RATE FOR EACH GEAR
## ———————————————————————————————————————————————————————————————————————————————————— ##
## Trap Trawl NMFS BSFRF
## Mean_F STD_PHZ1 STD_PHZ2 PHZ
0.20 0.10 1.10 1
0.10 0.10 1.10 1
0.00 2.00 2.00 -1
0.00 2.00 2.00 -1
## ———————————————————————————————————————————————————————————————————————————————————— ##

## ———————————————————————————————————————————————————————————————————————————————————— ##
## OPTIONS FOR SIZE COMPOSTION DATA (COLUMN FOR EACH MATRIX)
## LIKELIHOOD OPTIONS:
## -1) multinomial with estimated/fixed sample size
## -2) robust_multi. Robust approximation to multinomial
## -3) logistic normal (NIY)
## -4) multivariate-t (NIY)
## AUTOTAIL COMPRESSION:
## - pmin is the cumulative proportion used in tail compression.
## ———————————————————————————————————————————————————————————————————————————————————— ##
1 1 1 1 1 1 # 2 2 2 # Type of likelihood.
0 0 0 0 0 0 # 0 0 0 # Auto tail compression (pmin)
-4 -4 -4 -4 -4 -4 # -4 -4 -4 # Phz for estimating effective sample size (if appl.)
## ———————————————————————————————————————————————————————————————————————————————————— ##

## ———————————————————————————————————————————————————————————————————————————————————— ##
## TIME VARYING NATURAL MORTALIIY RATES ##
## ———————————————————————————————————————————————————————————————————————————————————— ##
## TYPE:
## 0 = constant natural mortality
## 1 = Random walk (deviates constrained by variance in M)
## 2 = Cubic Spline (deviates constrained by nodes & node-placement)
## 3 = Blocked changes (deviates constrained by variance AT specific knots)
3
## Phase of estimation
3
## STDEV in m_dev for Random walk
0.60
## Number of nodes for cubic spline or number of step-changes for option 3
2
## Year position of the knots (vector must be equal to the number of nodes)
1980 1985



## ———————————————————————————————————————————————————————————————————————————————————— ##
## OTHER CONTROLS
## ———————————————————————————————————————————————————————————————————————————————————— ##
3 # Estimated rec_dev phase
0 # VERBOSE FLAG (0 = off, 1 = on, 2 = objective func)
0 # INITIALIZE MODEL AT UNFISHED RECRUITS (0=FALSE, 1=TRUE)
1984 # First year for average recruitment for Bspr calculation.
2014 # Last year for average recruitment for Bspr calculation.
0.35 # Target SPR ratio for Bmsy proxy.
1 # Gear index for SPR calculations (i.e., directed fishery).
1 # Lambda (proportion of mature male biomass for SPR reference points.)
1 # Use empirical molt increment data (0=FALSE, 1=TRUE)
## EOF
9999
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