exporting to GCS as large mosaics

export_spp_gee2gcs.R

@@ -18,11 +18,11 @@ if (!"librarian" %in% installed.packages())
 
 # devtools::install_bitbucket("bklamer/rcrypt")  # aquamapsdata dependency
 librarian::shelf(
-  raquamaps/aquamapsdata, dplyr, ggplot2, glue, here, jsonlite,
+  raquamaps/aquamapsdata, dplyr, ggplot2, fs, glue, here, jsonlite,
   leaflet, leaflet.extras2, listviewer,
   purrr, raster, rgee, reticulate, scales, sf, 
   #shiny, 
-  stringr, tibble, tidyr)
+  stringr, terra, tibble, tidyr)
 select = dplyr::select
 source(here("sp-map/functions.R"))
 
@@ -57,5 +57,92 @@ source(here("sp-map/functions.R"))
 am_db <- default_db("sqlite")  # ~/.config/aquamaps/am.db
 
 # list of species
-am_spp <- get_am_spp()
+am_spp <- get_am_spp() |> 
+  arrange(SpeciesID)
+
+# sample for export
+spp_ids <- am_spp$SpeciesID[1:10]
+
+# source(here("sp-map/functions.R"))
+lst_spp_info <- lapply(spp_ids, get_sp_info)
+
+lst_spp_coarse <- map(lst_spp_info, calc_im_sp_coarse)
+
+im_spp <- ee$ImageCollection(lst_spp_coarse)$toBands()$rename(spp_ids)
+# im_spp$bandNames()$getInfo()
+
+prj_im       <- im_spp$projection()
+# crs_im       <- im_spp$projection()$crs()$getInfo()           # "EPSG:4326"
+# transform_im <- im_spp$projection()$transform()       # "PARAM_MT[\"Affine\", \n  PARAMETER[\"num_row\", 3], \n  PARAMETER[\"num_col\", 3]]"
+ply_globe    <- ee$Geometry$BBox(-180,-89.9999,180,89.9999)$transform("EPSG:4326", 0.001)
+
+ic_gebco <- ee$ImageCollection("projects/sat-io/open-datasets/gebco/gebco_sub-ice-topo")
+im_am    <- ee$Image("projects/eq-am-fine/assets/sdmpredictors/am-hcaf_v1-simple")
+
+prj_fine   <- ic_gebco$first()$projection()$getInfo()
+prj_coarse <- im_am$projection()$getInfo()
+
+# export as GeoTIFF (not cloud-optimized)
+task_im_spp <- ee_image_to_gcs(
+  image          = im_spp,
+  description    = "im-spp10-coarse-not-cog-v03_to_gcs",
+  bucket         = "sdm-env_gebco-global",
+  fileNamePrefix = "im-spp10-coarse_v03",
+  crs            = prj_coarse$crs(),
+  scale          = prj_coarse$nominalScale()$getInfo(), # v3: with scale
+  # crsTransform   = cat(prj_coarse$transform()$getInfo()),
+  # https://github.com/r-spatial/rgee/blob/219d84917300ca378f395d75a4372fbbeefba73b/R/ee_download.R#L335C4-L336
+  #  @param crsTransform A comma-separated string of 6 numbers describing
+  #    the affine transform of the coordinate reference system of the exported
+  # crsTransform  = "3,3,0.5,-180.0,-0.5,90.0",
+  # list(PARAM_MT = list(
+  #   Affine = list(
+  #     PARAMETER = list(
+  #       num_row = 3)))), 
+  #          PARAMETER["num_col", 3], 
+  #          PARAMETER["elt_0_0", 0.5], 
+  #          PARAMETER["elt_0_2", -180.0], 
+  #          PARAMETER["elt_1_1", -0.5], 
+  #          PARAMETER["elt_1_2", 90.0]]
+  # crsTransform   = prj_im$transform(), # v01: commented out
+  maxPixels      = 1e13,
+  region         = ply_globe,
+  skipEmptyTiles = TRUE,
+  fileFormat     = 'GeoTIFF')  # 25 min for single on EE
+task_im_spp$start()
+ee_monitoring(task_im_spp)
+# ID: TLMWVPWDQAS5N22KXDSSWX7I
+# Phase: Completed
+# Runtime: 7s (started 2023-09-21 11:16:21 -0700)
+# Attempted 1 time
+# Batch compute usage: 4.4424 EECU-seconds
+
+
+lst_spp_info <- lapply(spp_ids, get_sp_info)
+
+lst_spp_f <- map(lst_spp_info, calc_im_sp_fine)
+
+im_spp_f <- ee$ImageCollection(lst_spp_f)$toBands()$rename(spp_ids)
+# im_spp$bandNames()$getInfo()
+
+task_im_spp <- ee_image_to_gcs(
+  image          = im_spp_f,
+  description    = "im-spp10-fine-not-cog-v08_to_gcs", # without region
+  bucket         = "sdm-env_gebco-global",
+  fileNamePrefix = "im-spp10-fine-not-cog_v08",
+  # crs            = prj_im$crs(),
+  # crsTransform   = prj_fine$transform()$getInfo(), # v01: commented out
+  # "PARAM_MT[\"Affine\", \n  PARAMETER[\"num_row\", 3], \n  PARAMETER[\"num_col\", 3]]"
+  crs            = prj_fine$crs,
+  crsTransform   = prj_fine$transform,
+  # scale          = prj_coarse$nominalScale()$getInfo(), # v3: with scale
+  # scale          = 111319.5/240,
+  maxPixels      = 1e13,
+  region         = ply_globe,
+  # skipEmptyTiles = TRUE,
+  fileFormat     = 'GeoTIFF')  # 25 min for single on EE
+task_im_spp$start()
+ee_monitoring(task_im_spp)
+# im-spp10-fine-not-cog-v03_to_gcs
+#   ERROR in Earth Engine servers: Unable to transform edge (360.000000, 76.000000 to 359.999802, 76.000000) from EPSG:4326 PLANAR [0.5, 0.0, 0.0, 0.0, -0.5, 0.0] to EPSG:4326.
 

sp-map/functions.R

@@ -219,8 +219,7 @@ get_am_spp <- function(){
   am_spp <- tbl(am_db, "speciesoccursum_r") |> 
     select(
       SpeciesID, SpecCode, Genus, Species) |> 
-
-  distinct() |> 
+    distinct() |> 
     collect() |> 
     mutate(
       sp_sci = glue("{Genus} {Species}")) |> 
@@ -232,16 +231,33 @@ get_am_spp <- function(){
   # am_spp$Order   |> unique() |> length()   #    298
 }
 
-get_sp_info <- function(sp_code){
+get_sp_info <- function(sp_key){
+  # sp_key matches hspen_r.Speccode if numeric, otherwise
+  #                hspen_r.SpeciesID
+
+  # TODO:
+  # - look at speciesoccursum_r.StockDefs multiple stock definitions / lifestage per sp?
+  #   tbl(am_db, "speciesoccursum_r")
+
+  if (is.numeric(sp_key)){
+    d_hspen <- tbl(am_db, "hspen_r") |> 
+      filter(Speccode == !!sp_key) |>
+      collect() |> 
+      # TODO: filter by sp_id vs sp_code
+      #   eg sp_code == 46802: 
+      #     "sp_scientific": ["Ammodytoides gilli", "Isopora palifera"]
+      #     "sp_id"        : ["Fis-138579"        , "W-Scl-730686"]
+      slice(1)
+  } else {
+    d_hspen <- tbl(am_db, "hspen_r") |> 
+      filter(SpeciesID == !!sp_key) |>
+      collect() |> 
+      slice(1)
+  }
 
-  d_hspen <- tbl(am_db, "hspen_r") |> 
-    filter(Speccode == !!sp_code) |>
-    collect() |> 
-    # TODO: filter by sp_id vs sp_code
-    #   eg sp_code == 46802: 
-    #     "sp_scientific": ["Ammodytoides gilli", "Isopora palifera"]
-    #     "sp_id"        : ["Fis-138579"        , "W-Scl-730686"]
-    slice(1)
+  # browser()
+
+  message(glue("sp_key: {sp_key}"))
 
   vars_yes <- d_hspen |> 
     select(ends_with("YN")) |> 
@@ -280,8 +296,8 @@ get_sp_info <- function(sp_code){
 
   sp_info <- list()
 
-  d_sp <- am_spp |> 
-    filter(SpecCode == sp_code)
+  d_sp <- tbl(am_db, "speciesoccursum_r") |> 
+    filter(SpeciesID == d_hspen$SpeciesID)
   sp_info["sp_scientific"] <- list(d_sp$sp_sci)
   sp_info["sp_code"]       <- list(d_sp$SpecCode)
   sp_info["sp_id"]         <- list(d_sp$SpeciesID)