Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(fig.width = 6,
fig.height = 6,
fig.align = "center",
warning = FALSE,
message = FALSE,
echo = TRUE,
eval = FALSE)
## -----------------------------------------------------------------------------
#
# files = c(system.file('vignette_data/Alberta_Wolves.csv', package = "CopernicusDEM"),
# system.file('vignette_data/Mountain_caribou.csv', package = "CopernicusDEM"))
#
#
# leafgl_data = tmap_data = list()
#
#
# for (FILE in files) {
#
# cat(glue::glue("Processing of the '{basename(FILE)}' file ..."), '\n')
#
# dtbl = data.table::fread(FILE, header = TRUE, stringsAsFactors = FALSE)
# cols = c('location-long', 'location-lat', 'timestamp', 'individual-local-identifier',
# 'individual-taxon-canonical-name')
#
# dtbl_subs = dtbl[, ..cols]
# colnames(dtbl_subs) = c('longitude', 'latitude', 'timestamp', 'individual_local_identifier',
# 'individual-taxon-canonical-name')
#
# leafgl_data[[unique(dtbl_subs$`individual-taxon-canonical-name`)]] = dtbl_subs
#
# dtbl_subs_sf = sf::st_as_sf(dtbl_subs, coords = c("longitude", "latitude"), crs = 4326)
#
# sf_rst_ext = fitbitViz::extend_AOI_buffer(dat_gps_tcx = dtbl_subs_sf,
# buffer_in_meters = 250,
# CRS = 4326,
# verbose = TRUE)
#
# #................................................................
# # Download the Copernicus DEM 30m elevation data because it has
# # a better resolution, it takes a bit longer to download because
# # the .tif file size is bigger
# #...............................................................
#
# dem_dir = tempdir()
#
# dem30 = CopernicusDEM::aoi_geom_save_tif_matches(sf_or_file = sf_rst_ext$sfc_obj,
# dir_save_tifs = dem_dir,
# resolution = 30,
# crs_value = 4326,
# threads = parallel::detectCores(),
# verbose = TRUE)
#
# TIF = list.files(dem_dir, pattern = '.tif', full.names = TRUE)
#
# if (length(TIF) > 1) {
#
# #....................................................
# # create a .VRT file if I have more than 1 .tif files
# #....................................................
#
# file_out = file.path(dem_dir, 'VRT_mosaic_FILE.vrt')
#
# vrt_dem30 = CopernicusDEM::create_VRT_from_dir(dir_tifs = dem_dir,
# output_path_VRT = file_out,
# verbose = TRUE)
# }
#
# if (length(TIF) == 1) {
#
# #..................................................
# # if I have a single .tif file keep the first index
# #..................................................
#
# file_out = TIF[1]
# }
#
# raysh_rst = fitbitViz::crop_DEM(tif_or_vrt_dem_file = file_out,
# sf_buffer_obj = sf_rst_ext$sfc_obj,
# CRS = 4326,
# digits = 6,
# verbose = TRUE)
#
# # convert to character to receive the correct labels in the 'tmap' object
# dtbl_subs_sf$individual_local_identifier = as.character(dtbl_subs_sf$individual_local_identifier)
#
# # open with interactive viewer
# tmap::tmap_mode("view")
#
# map_coords = tmap::tm_shape(shp = dtbl_subs_sf) +
# tmap::tm_dots(col = 'individual_local_identifier')
#
# map_coords = map_coords + tmap::tm_shape(shp = raysh_rst, is.master = FALSE, name = 'Elevation') +
# tmap::tm_raster(alpha = 0.65, legend.reverse = TRUE)
#
# tmap_data[[unique(dtbl_subs$`individual-taxon-canonical-name`)]] = map_coords
# }
#
## ----echo = FALSE-------------------------------------------------------------
#
# #..........................................................................................
# # options to save the 'tmap' object:
# #
# # 1st. As an .html file which is approx. 9 MB
# # 2nd. As an .RDS object which saves the raster data too and it's approx. 98 MB
# # 3rd. Open in browser and take a screenshot and save the .png image
# #
# # Regarding the 1st. option an .html file can be loaded in an Rmarkdown file and
# # viewed on a web browser using 'iframe' in the following way:
# #
# # <iframe width='1000px' height='1000px' src='/home/lampros/Downloads/delete_vig.html' >
# # <p>Your browser does not support iframes</p>
# # </iframe>
# #
# # see: https://stackoverflow.com/a/54637781/8302386
# # https://stackoverflow.com/a/36525111/8302386
# #..........................................................................................
#
## -----------------------------------------------------------------------------
#
# #.....................................
# # create the 'leafGl' of both datasets
# #.....................................
#
# dtbl_all = rbind(leafgl_data$`Canis lupus`, leafgl_data$`Rangifer tarandus`)
#
# # see the number of observations for each animal
# table(dtbl_all$`individual-taxon-canonical-name`)
#
# # create an 'sf' object of both data.tables
# dat_gps_tcx = sf::st_as_sf(dtbl_all, coords = c("longitude", "latitude"), crs = 4326)
#
# lft = leaflet::leaflet()
# lft = leaflet::addProviderTiles(map = lft, provider = leaflet::providers$OpenTopoMap)
#
# lft = leafgl::addGlPoints(map = lft,
# data = dat_gps_tcx,
# opacity = 1.0,
# fillColor = 'individual-taxon-canonical-name',
# popup = 'individual-taxon-canonical-name')
# lft
#
## -----------------------------------------------------------------------------
#
# tmap_data$`Rangifer tarandus` # caribou
#
## -----------------------------------------------------------------------------
#
# tmap_data$`Canis lupus` # wolves
#
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