---
title: Introduction to artfishr package
output:
  rmarkdown::html_vignette:
    toc: true
    toc_depth: 2
vignette: >
  %\VignetteIndexEntry{Introduction to artfishr}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}

---


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

This vignette provides a general introduction to the [artfishr](https://github.com/fdiwg/artfishr) package and guides users through the available documentation.

## Installation

The R [artfishr](https://github.com/fdiwg/artfishr) can be installed from **Github**. 

As prerequisites, packages `remotes` and `vrule` should be installed.

* Package `remotes` can be installed from CRAN using:

```{r, eval=FALSE}
install.packages("remotes", repos = "https://cloud.r-project.org")
```

* Package [vrule](https://github.com/fdiwg/vrule) should be installed from GitHub using `remotes`:

```{r, eval=FALSE}
remotes::install_github("fdiwg/vrule")
```

Once the `remotes` and `vrule` packages have been installed, the `artfishr` package can be installed using:

```{r, eval=FALSE}
remotes::install_github("fdiwg/artfishr")
```

Once installed, `artfishr` can be loaded using `library(artfishr)` or `require(artfishr)`

## Data Requirements and Validation

For detailed information on the required input datasets and validation procedures, see:
`vignette("artfishr_02_data-requirements-validation")`

## Using `artfishr` for Small-Scale Fisheries Estimation

Full tutorial: `vignette("artfishr_03_workflow")`

## Statistical framework of the ARTFISH methodology

See: `vignette("artfishr_04_methodology")`

## Artfish visualisations

See: `vignette("artfishr_05_visualisation")`

## Exemple of use

```{r, eval=FALSE}
# Load sample datasets
active_vessels <- read.csv(system.file("extdata/samples/active_vessels.csv", package = "artfishr"))
effort <- read.csv(system.file("extdata/samples/effort_fisher_interview.csv", package = "artfishr"))
landings <- read.csv(system.file("extdata/samples/landings.csv", package = "artfishr"))
active_days <- read.csv(system.file("extdata/samples/active_days.csv", package = "artfishr"))

# Validate data 
validate_input_datasets(
  active_vessels = active_vessels,
  effort = effort,
  effort_source = "fisher_interview",
  landings = landings,
  active_days = active_days
)

#Run artfish
report <- artfishr::compute_report(
  active_vessels = active_vessels,
  effort = effort,
  effort_source = "fisher_interview",
  active_days = active_days,
  active_vessels_strategy = "closest",
  landings = landings,
  minor_strata = "minor_stratum"
)

#See result
str(report, max.level = 1)

```