---
title: "Script to refit models and extract coefficients for unstandardised data"
author: "Rachel Mawer"
date: "2023-11-29"
output: 
  html_document:
    toc: true
    toc_float: true
    theme: cerulean
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = F,message=F)

#main packages #delete/add as needed
library(dplyr)
library(ggplot2)
library(knitr)
library(ggpubr)
library(plotly)
library(pracma) #for standard error
library(reactable)
library(stringr)
library(amt)
```

## About

In this file, all final models for all fish and states are read in and refitted with the unstandardised data - e.g. model structure obtained is reused.

Resulting coefficients are saved as a file for use in simulations.

```{r read in file names etc}

fish_ids <- list.files("ssf modelling - file per fish")

files <- list.files("ssf modelling - file per fish",full.names = T)
files <- files[!grepl("coeffs",files)] #remove the non fish folder

#og data files
data_files <- list.files("data/final ssf + hmm df",full.names = T)

save_loc <- "unstandardised ssf model outputs"

```

```{r run the loop}
#loop to do everything

i <- 1
z <- 1

for(i in 1:length(files)){
  fish_id <- fish_ids[i]
  fish_files <- list.files(files[i],full.names = T)
  fish_files <- fish_files[grepl("final",fish_files)]
  
  fish_data_files <-data_files[grepl(fish_id,data_files)]
  
  for(z in 1:length(fish_files)){
    model <- readRDS(fish_files[z]) #get model
    data <- read.csv(fish_data_files[z]) #get data
    
    state <- data$state %>% unique()
    #extract model formula
    frm_part <- as.character(model$formula)[3] %>% str_remove_all("_strdised") %>% str_remove_all("\n")
    frm <- paste("case_ ~",frm_part) %>% as.formula()

    new_mod <- fit_issf(formula = frm,data=data)
    coefs <- summary(new_mod)$coefficients %>% as.data.frame() %>% tibble::rownames_to_column("params")
    coefs$fish_id <- fish_id
    coefs$state <- state
    coefs$species <- unique(data$species)
    
    if(z==1){
      fish_coefs <- coefs
    } else{
      fish_coefs <- bind_rows(fish_coefs,coefs)
    }
  }
  if(i==1){
    all_coefs <- fish_coefs
  }else{
    all_coefs <- bind_rows(all_coefs,fish_coefs)
  }
}

write.csv(all_coefs,"FINAL RESULTS/all_coefs_both_states_UNSTANDARDISED.csv",row.names=F)
```

```{r data loc pooled}

fish_ids <- list.files("ssf modelling - file per fish - pooled")

files <- list.files("ssf modelling - file per fish - pooled",full.names = T)
files <- files[!grepl("coeffs",files)] #remove the non fish folder

#og data files
data_files <- list.files("data/SSF dataframes",full.names = T)

```

```{r and for the both states data}
#loop to do everything

i <- 1
z <- 1

for(i in 1:length(files)){
  fish_id <- fish_ids[i]
  fish_files <- list.files(files[i],full.names = T)
  fish_files <- fish_files[grepl("final",fish_files)]
  
  fish_data_files <-data_files[grepl(fish_id,data_files)]

    model <- readRDS(fish_files) #get model

    data <- read.csv(fish_data_files) #get data
    
    #extract model formula
    frm_part <- as.character(model$formula)[3] %>% str_remove_all("_strdised") %>% str_remove_all("\n")
    frm <- paste("case_ ~",frm_part) %>% as.formula()
    #need to save name
    
    new_mod <- fit_issf(formula = frm,data=data)
    coefs <- summary(new_mod)$coefficients %>% as.data.frame() %>% tibble::rownames_to_column("params")
    coefs$fish_id <- fish_id
    coefs$state <- "pooled"
    coefs$species <- unique(data$species)
    
    fish_coefs <- coefs
    
  if(i==1){
    all_coefs <- fish_coefs
  }else{
    all_coefs <- bind_rows(all_coefs,fish_coefs)
  }
}


write.csv(all_coefs,"FINAL RESULTS/all_coefs_pooled_UNSTANDARDISED.csv",row.names=F)
```