---
title: "Using Staninside"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Using Staninside}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

```{r setup}
library(staninside)
```

# Motivation

'Stan' is a powerful language and using R (and specifically 'rstan') as glue to allow R users to easily interface existing models.
Sometimes a user might wish to use a different backend ('CmdStanR') or examine and modify the written 'Stan' code directly.
This package seeks to allow users the ability to:

* Build R packages that are not pre-compiled by 'rstan'
* Allow users to use 'CmdStanR' in their R packages
* Allow users to easily see the 'Stan' code within packages

## Building a Stan Package

### Package Infrastructure

If a package developer were to build a package with 'staninside', they first could create the package directory in the usual ways.

Next, to build the appropriate structure the author could call

```r
temp_dir <- tempdir()
setup_stan_package(loc = temp_dir)
```

This function will create the following directory tree:

```
.
├── inst
│   ├── stan
│   │   ├── base.stan
│   │   ├── data
│   │   ├── functions
│   │   ├── parameters

```
This provides the user with a structure to use when building their 'Stan' programs.
For complicated programs, it is sometimes useful to break up the 'Stan' code blocks into separate files stored in sub-directories. 
These separate `.stan` files can then be accessed within the 'Stan' code with the following syntax:

```stan
# include functions/my_functions.stan
```
### Model Fitting

Generally speaking, there will be some function in an R package that will fit the data to a model. 
In order to facilitate this fitting with a 'CmdStanR' backend, a process like that below could be used.
Note that this model assumes that 'cmdstanr' is installed, though this could be replaced with other ways of calling 'Stan' (e.g., 'rstan').

```r

fit_my_data <- function(my_data){
    requireNamespace("mypackage")
    local_location <- rappdirs::user_cache_dir(appname = "my_package")

    if (length(list.files(local_location, pattern = ".stan")) > 1) {
        cli::cli_alert_info("Using cached Stan models")
        cli::cli_alert_info(
        "Use `staninside::clear_stan_cache('mypackage')` if you need to refresh")
    } else {
        cli::cli_alert_info("Copying Stan models to cache")
        staninside::copy_models(pkgname = "mypackage", local_location = local_location)
        cli::cli_alert_success("Models copied!")
    }
    
    model_file_path <- file.path(local_location, paste0("base", ".stan"))
    mod <- cmdstanr::cmdstan_model(model_file_path)
        
    fit <- mod$sample(data = my_data)
   
    return(fit)
}

```

You now can call `fit_my_data` to fit your model.
The underlying 'Stan' code is stored in the user cache directory and will be compiled on the first model fitting operation.