am-env_to_ee.qmd

---
title: "Upload AquaMaps 1/2° env rasters to Earth Engine"
format: html
editor: visual
editor_options: 
  chunk_output_type: console
---

```{r}
# libraries ----
Sys.setenv(
  EARTHENGINE_GCLOUD = "/usr/bin/gcloud",
  EARTHENGINE_PYTHON = "/opt/venv/rgee/bin/python",
  EARTHENGINE_ENV    = "rgee")

if (!"librarian" %in% installed.packages())
  install.packages("librarian")

librarian::shelf(
  raquamaps/aquamapsdata, 
  dplyr, glue, here, 
  rgee, sf, terra)

# variables & paths -----
tif  <- here("data/am-hcaf_v1-simple.tif")
```

```{r}
# aquamaps database ----
am_db <- default_db("sqlite")  # ~/.config/aquamaps/am.db

# get aquamaps table of env values ----
d <- am_hcaf() |> 
  select(
    hcaf_id   = ID,
    ctr_lon   = CenterLong,
    ctr_lat   = CenterLat,
    FAOArea   = FAOAreaM,
    Depth     = DepthMean,
    Temp      = SSTAnMean,  # surface; TODO: bottom
    Salinity  = SalinityMean,
    PrimProd  = PrimProdMean,
    IceCon    = IceConAnn) |> 
  collect()

# raster template ----
# range(d$ctr_lon)  # -179.75  179.75
# range(d$ctr_lat)  # - 78.25   89.75
r_template <- rast(
  xmin       = min(d$ctr_lon) - 0.25,
  xmax       = max(d$ctr_lon) + 0.25,
  ymin       = min(d$ctr_lat) - 0.25,
  ymax       = max(d$ctr_lat) + 0.25,
  resolution = c(0.5, 0.5),
  crs = "epsg:4326")

# data frame to points ----
p <- d |>
  st_as_sf(
    coords = c("ctr_lon", "ctr_lat"),
    remove = F,
    crs    = 4326) |> 
  arrange(ctr_lon, ctr_lat)
# p[1:25,] |> 
#   mapview::mapView()

# points to raster ----
get_r <- function(v){
  r <- rasterize(p, r_template, field = v)
  names(r) <- v
  r
}

r <- NULL
for (v in names(d)){
  message(glue("v: {v}"))
  
  if (is.null(r)){
    r <- get_r(v)
  } else {
    r <- rast(list(r, get_r(v)))
  }
}

# plot(r["ctr_lat"])
writeRaster(r, tif, overwrite=T)
```

```{r}
gcs_bucket <- "eq-am-fine"

r <- rast(tif)

Sys.setenv(
  "GCS_DEFAULT_BUCKET" = gcs_bucket,
  "GCS_AUTH_FILE"      = "/share/data/eq-am-fine-98c68d6f5f96.json")
librarian::shelf(
  googleCloudStorageR, jsonlite,
  offshorewindhabitat/offhabr, purrr)

# gcs_delete_object(basename(tif))
gcs_upload(
  file = tif,
  name = basename(tif))

gcs_update_object_acl(
  basename(tif), entity_type = "allUsers")

# gcs_to_gee(
#   gcs_name     = basename(tif),
#   gcs_bucket   = gcs_bucket,
#   gee_asset    = "users/ben-ecoquants/aquamaps-downscaled",
#   missing_data = NA)
# https://github.com/offshorewindhabitat/offhabr/blob/ac5bb1491ff2a6e6475a2f5d08c9b093af961a9a/R/gcloud.R#L51-L77
gcs_name     = basename(tif)
gcs_bucket   = gcs_bucket
gee_asset    = "projects/eq-am-fine/assets/sdmpredictors"
gee_name     = fs::path_ext_remove(gcs_name)
properties   = list(
  commments = "only sea surface Temp(erature)")

f_json <- tempfile(fileext = ".json")
properties_json <- toJSON(properties, pretty=T, auto_unbox=T)

bands_categorical <- c("hcaf_id", "FAOArea")
bands_json <- tibble(
  id = names(r)) |> 
  mutate(
   tileset_band_index = 0:(n() - 1),
   pyramiding_policy  = map_chr(
     id, 
     \(x) ifelse(
       x %in% bands_categorical,
       "MODE",
       "MEAN"))) |> 
  toJSON(pretty=T, auto_unbox=T) # cat(bands_json)

glue(
  '{{
       "name": "{gee_asset}/{gee_name}",
       "tilesets":[{{"sources":[{{"uris":["gs://{gcs_bucket}/{gcs_name}"]}}]}}],
       "pyramidingPolicy":"MEAN",
       "bands": {bands_json},
       "properties": {properties_json}
    }}') |>
  writeLines(f_json)
# readLines(f_json) |> cat()

cmd <- glue::glue("/opt/venv/rgee/bin/earthengine upload image --manifest '{f_json}'")
system(cmd)

```