---
title: "Cropping and subseting your presence absence matrix"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{cropping-and-subseting-your-presence-absence-matrix}
  %\VignetteEncoding{UTF-8}
  %\VignetteEngine{knitr::rmarkdown}
editor_options: 
  chunk_output_type: console
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(fig.height = 5, fig.width = 10, fig.align = 'center')
```

In this guide, we'll dive into the technique of subsetting or cropping a `PresenceAbsence` object.

To accomplish this task, we'll use the `lets.subsetPAM` function. Just let the function know which species you want to keep and provide the `PresenceAbsence` object as input.

```{r, message=FALSE, warning=FALSE}
# Package
library(letsR)

# Data
data("PAM")

names <- PAM$Species_name[1:20] # keep only the first 20 names
PAM_subset <- lets.subsetPAM(PAM, names)
par(mfrow = c(1, 2))
plot(PAM, main = "All species")
plot(PAM_subset, main = "Subset")
```

You might also find it useful to crop your `PresenceAbsence` object to a specific region using a shapefile. The `lets.pamcrop` function offers a straightforward method to achieve this. For instance, let's crop our Presence-Absence Matrix (PAM) to the borders of Brazil.
```{r}
data(wrld_simpl)  # World map
data(PAM)
Brazil <- wrld_simpl[wrld_simpl$NAME == "Brazil", ]  # Brazil (polygon)
PAM_crop <- lets.pamcrop(PAM, Brazil, remove.sp = TRUE)
par(mfrow = c(1, 2))
plot(PAM, main = "South America")
plot(PAM_crop, xlab = "Longitude", ylab = "Latitude",
     main = "Phyllomedusa species richness (Brazil crop)")
plot(sf::st_geometry(wrld_simpl), add = TRUE)

```

**To cite letsR in publications use:**
*Bruno Vilela and Fabricio Villalobos (2015). letsR: a new R package for data handling and analysis in macroecology. Methods in Ecology and Evolution. DOI: 10.1111/2041-210X.12401*