summary.Rmd

---
title: "EBS pollock models"
author: "Ianelli"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    social: menu
    source_code: embed
    vertical_layout: fill
    theme: 
      version: 4
      bootswatch: minty
editor_options: 
  chunk_output_type: console
---

```{r setup, include=FALSE}
library(flexdashboard)
library(plotly)
library(r4ss)
library(tidyverse)
library(here)
library(ggridges)

getwd()
loadup<-FALSE
if (loadup){
  source("GetResults.R")
  r1 <- ss_run<-SS_obj()
  ra <- SS_obj(SS_output(dir = here("ss","noramp"),verbose=FALSE),src="noramp") 
  r2 <- SS_obj(SS_output(dir = here("ss","mod")),src="mod")  
  r3 <- SS_obj(SS_output(dir = here("ss","mix")),src="mix")  
  r4 <- SS_obj(SS_output(dir = here("ss","high")),src="high")  
  #r5 <- SS_obj(SS_output(dir = here("ss","autocor")),src="autocor")  
  ss_sel <- rbind(r1$sel,r2$sel,r3$sel,r4$sel)#,r5$sel)
  #compute_matrix_summary(sel[,2:16])
  gp_run<-gp_obj()
  am_run<-AMAK_obj()
  pm_run<-pm_obj()
  load(here("SAM","poll23","run","model2.RData"))
  sam_run <- SAM_obj()
  all_sel <- rbind(sam_run$sel,pm_run$sel,am_run$sel,ss_run$sel,gp_run$sel)
  all_ts <- rbind( sam_run$ts,pm_run$ts,am_run$ts,ss_run$ts,gp_run$ts)
} else {
  load(here("compares.Rdata"))
}

```

Platforms
=======================================================================

Column {.tabset}
-----------------------------------------------------------------------

### Selectivity

```{r}
p<-Plot_Sel() + ggthemes::theme_few(base_size=11)
p

```


### Selectivity by age

```{r}
p <- Plot_Sel_age()
ggplotly(p)
```

### SSB

```{r}

p<- Plot_SSB()
ggplotly(p)

```

### Stock recruitment relationship

```{r}

p<- Plot_SRR()
ggplotly(p)

```

SS runs
=======================================================================

Column {.tabset}
-----------------------------------------------------------------------
### Run description

Runs with different selectivity assumptions where:     
  - **base**: selectivity at age allowed to vary (sigma penalty=0.7)     
  - **high**: selectivity at age constrained (sigma penalty=0.05)     
  - **mod**: selectivity at age moderately constrained (sigma penalty=0.4)     
  - **mix**: selectivity at age moderately constrained for middle ages, high for older ages, loose for younger ages      

### Selectivity

```{r echo=FALSE}
ss_sel <- rbind(r1$sel,r2$sel,r3$sel,r4$sel)#,r5$sel)
p1 <- Plot_Sel(ss_sel)
p1
```


### Selectivity at age
```{r echo=FALSE}
p1  <- Plot_Sel_age(ss_sel)
ggplotly(p1)
```

### SSB and recruitment

```{r echo=FALSE}
ss_ts  <- rbind(r1$ts,r2$ts,r3$ts,r4$ts)#,r5$sel)
p1 <- Plot_SSB(ss_ts)
ggplotly(p1)
```


With and w/o ramp
=======================================================================


### SSB and recruitment

```{r, echo=FALSE, warning=FALSE, message=FALSE}
# Get results w/ and w/o  ramp
df <- rbind(r1$ts,ra$ts)
  p1  <- df |> filter(Year<2024,Year>1953) |> ggplot(aes( x=Year, y= value,color=source)) + 
    geom_line(stat='identity') + geom_point(stat='identity') +
    ggthemes::theme_few() + ylab("SSB") + xlab("Year") +
    ylim(0,NA) + facet_grid(type~.,scales="free_y")  
  ggplotly(p1)
  
```