NEWbackground_points_code.qmd

---
title: "background_points"
format: html
editor: visual
---

## Code for creating background points

## Hallie's function

```{r}
get_enviro_data <- function(var) {
  #This is an example! Not the final!
  layercodes <- var
  env <- sdmpredictors::load_layers(layercodes, equalarea = FALSE)
  #Crop
  env <- st_as_stars(env)
  extent <- st_bbox(c(xmin = vars$lonmin, xmax = vars$lonmax, ymin = vars$latmin, ymax = vars$latmax), crs = st_crs(env))
  rc <- st_crop(x = env, y = extent)
  return(rc)
}
```

## Use Hallie's function to get background points

```{r}
library(stars)
library(sf)
library(sdmpredictors)
library(dplyr)
library(mapview)

bbox <- list(lonmin = -71, lonmax = -64, latmin = 42, latmax = 45)
var <- c("BO_nitrate")

get_enviro_data <- function(var, bbox, nsamp = 1000, save_csv = FALSE, file_path = "background_points.csv") {
  # Load the specified environmental layers
  env <- sdmpredictors::load_layers(var, equalarea = FALSE)
  
  # Convert to stars object
  env_stars <- st_as_stars(env)
  
  # Create a bounding box with CRS
  extent <- st_bbox(c(xmin = bbox$lonmin, xmax = bbox$lonmax, ymin = bbox$latmin, ymax = bbox$latmax), crs = st_crs(env_stars))
  bbox_sf <- st_as_sfc(extent)
  
  # Crop the environmental data to the bounding box
  cropped_env <- st_crop(env_stars, bbox_sf)
  
  # Generate random background points within the bounding box
  set.seed(42)  # For reproducibility
  random_points <- st_sample(bbox_sf, size = nsamp)
  
  # Convert points to a data frame and then to an sf object
  random_points_sf <- st_as_sf(as.data.frame(st_coordinates(random_points)), coords = c("X", "Y"), crs = st_crs(env_stars))
  
  # Crop the points to the extent of the environmental layer
  cropped_points <- st_intersection(random_points_sf, st_as_sf(cropped_env, as_points = FALSE, merge = TRUE))
  
  # Optionally save cropped points to CSV
  if (save_csv) {
    write.csv(st_coordinates(cropped_points), file = file_path, row.names = FALSE)
  }
  
  # Return the cropped environmental data and cropped background points
  return(list(cropped_env = cropped_env, background_points = cropped_points))
}

result <- get_enviro_data(var = var, bbox = bbox, nsamp = 1000, save_csv = TRUE, file_path = "cropped_background_points.csv")

# Access the cropped environmental data
cropped_env <- result$cropped_env

# Access the cropped background points
background_points_sf <- result$background_points

# Visualize the cropped background points
mapview(background_points_sf, col.regions = "gray")

```