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# Description: This script is used to download HLS data from NASA's Earthdata
# STAC API and build a cloud-free composite image.

# ----- Functions -----

# band mapping for HLS SL data
#' @return a named character vector of band mappings for HLS SL data
hlssl_band_mapping <- function() {
  c(
    B01 = "A", B02 = "B", B03 = "G", B04 = "R",

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#' @title Get administritive outlines for a country
#' @description using the geoBoundaires API, get the administritive polygon(s)
#' for a country
#' @param country character vector: a country name
#' @param admin_level character vector: the admin level to download
#' @param quiet logical, should st_read be quiet?
#' @return sf object of the outlines
#' @details check out the documentation for the geoboundaries API at:
#' geoBoundaries.org
#'

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#' Buffer a point along a terrain surface.
#'
#' @param dtm A SpatRaster Digital Terrain Model
#' @param pnts A SpatVector of points
#' @param .dist Numeric - the buffer distance.
#' @param .res Numeric - approximate resampling resolution of the (internally
#' calculated) cost raster.
#' @param .smooth Logical default FALSE. Should the output buffer be smoothed using `smoothr::smooth`?
#' @param .method The smoothing method to use - see `smoothr::smooth` for details.
#' @param ... Passed to `smoothr::smooth` for eg. to control smoothness.

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#https://twitter.com/AnalyticalEdge/status/1582206425585324034

library(ggplot2)
library(stars)
library(sf)
library(dplyr)
library(plotly)

.d <- dim(volcano)

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#' download drive files from dribble with path column
#'
#' @param x a dribble with path column
#' @param .overwrite logical. Should files be overwritten
#' 
#' @return The original input dribble
#' @noRd
drive_down_files <- function(x, .overwrite = TRUE) {
  

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library(tibble)
library(purrr)

t1 <- tibble(`C1 Template` = sample(c(166:180), 10),
             `C2 Template` = sample(c(120:130), 10))

t1
#> # A tibble: 10 × 2
#>    `C1 Template` `C2 Template`

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 library(raster)
#> Loading required package: sp
#> Warning: no function found corresponding to methods exports from 'raster' for:
#> 'area'
 
 circ_matrix <- function(n){
   if (!n %% 2){
     stop("n must be an odd number.")
   } 

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library(vapour)
library(sf)
#> Linking to GEOS 3.10.2, GDAL 3.4.3, PROJ 8.2.0; sf_use_s2() is TRUE
#> WARNING: different compile-time and runtime versions for GEOS found:
#> Linked against: 3.10.2-CAPI-1.16.0 compiled against: 3.10.1-CAPI-1.16.0
#> It is probably a good idea to reinstall sf, and maybe rgeos and rgdal too
library(rstac)

mpc_dem <- function(aoi, src = c("cop-dem-glo-30", "alos-dem")) {

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library(sf)
library(dplyr)
library(mapview)
mapviewOptions(fgb = FALSE)
plts <- read_sf('data/PlotData/KuamutLocations.shp') 
pnts <- read_sf("data/Kuamut_2022_NewGPS_Points_Shapefiles/PlotCentre.shp")

pnts_clean <- pnts %>% 
  filter(is.na(NUMBER)|NUMBER!=100) %>%
  mutate(nearest = st_nearest_feature(., plts),

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#' Customise style of a targets-derived visNetwork object
#'
#' @param v object class "visNetwork" from either `tar_visnetwork` or `tar_glimpse` 
#' @param colors character vector of length 1 or 3. Hex colour codes to define: 
#' Up to Date, Errored and Outdated targets (in that order). If an object from 
#' `tar_glimpse` is provided, only the first colour is used to fill the nodes.
#' @param shapes a character vector of length 3. any of the following: diamond, 
#' dot, star, triangle, triangleDown, hexagon, square.
#' @param background character - Hex colour codes to define the background
#' @param leg_shape_col character - Hex colour code. for tar_visnetwork an