---
title: "Running a subnational level single-country model with custom data"
output: 
  rmarkdown::html_vignette:
       toc: true
vignette: >
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteIndexEntry{Running a subnational level single-country model with custom data}
  %\usepackage[UTF-8]{inputenc}
---


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


## Load your library

```{r, include=TRUE, message=FALSE, eval=FALSE}
library(mcmsupply)
library(dplyr)
set.seed(1209)
```

## Try to use unsuitable data. The `get_data` function throws an error indicating that the Method column is missing from the custom user-supplied data.

```{r, include=TRUE, message=FALSE, warning=FALSE, error=TRUE}

cleaned_data <- get_data(national=FALSE, local=TRUE, 
                         surveydata_filepath = "~/Documents/R/mcmsupply/inst/data-raw/my_custom_subnational_data_bad.xlsx",
                         mycountry="Ethiopia")
```


## Load the suitable data 

```{r, include=TRUE, message=FALSE, warning=FALSE, eval=FALSE}

cleaned_data <- get_data(national=FALSE, local=TRUE, 
                         surveydata_filepath = "~/Documents/R/mcmsupply/inst/data-raw/my_custom_subnational_data_good.xlsx",
                         mycountry="Ethiopia")
```


## Get the JAGS model inputs and the cleaned data

```{r, include=TRUE, message=FALSE, warning=FALSE, eval=FALSE}
pkg_data <- get_modelinputs(startyear=1990, endyear=2025.5,
                            nsegments=12, raw_data = cleaned_data)

```


## Run JAGS model and get posterior point estimates with uncertainty

```{r, include=TRUE, message=FALSE, eval=FALSE}
mod <- run_jags_model(jagsdata = pkg_data, jagsparams = NULL,
                      n_iter = 40000, n_burnin = 10000, n_thin = 15)
```


## Plot posterior point estimates with uncertainty

```{r, include=TRUE, message=FALSE, eval=FALSE}
plots <- plot_estimates(jagsdata = pkg_data, model_output = mod)
```


## Pull out estimates that you are particularly interested in

```{r, include=TRUE, message=FALSE, eval=FALSE}
estimates_2018 <- pull_estimates(model_output = mod, country = 'Ethiopia', year=2018)

head(estimates_2018)
```