ruut/R/pk_lisame_polygoonid.R

#' Piirkonnale andmebaasides olevate polügoonide lisamine
#'
#' Etteantud piirkonna geomeetrilise piirjoone ('piir') ja selle joone piirikasti ('bb') järele leitakse nende aladega kaetud polügoonid. Andmed salvestatakse postgis andmebaasi.
#'
#' @param obj str Objekti nimi. Edaspidi on oluline ainult see nimi. Piirkonna geomeetrilist joont ei ole vaja lisada.
#' @param conf A list() of configuration variables. Default values \code{\link[ruut]{get_config}}.
#' @return Uute andmebaasi kihtide 'piir_...' ja 'bb_...' loomine.
#' @seealso [sf::st_read()], [sf::write_sf()],[sf::st_transform()],[ruut::pk_sellest_alustame_db_loomist()],[ruut::pk_lisame_ruudustikud()] ,[ruut::pk_lisame_polygoonid()],[ruut::pk_lisame_jooned()],[ruut::pk_lisame_punktid()],[ruut::pk_teisendame_polygoone()],[ruut::pk_teisendame_jooni()],[ruut::pk_teisendame_punkte()]
#' @keywords postgis, boundary box, EPSG:3301
#' @export
#' @examples
#' \dontrun{
#'
#' obj <- "marja"
#' pk_lisame_polygoonid(obj = obj, conf = NULL)
#'
#' # Layers list.
#' ruut::db_schema_tablenames(conf = conf)
#' }
pk_lisame_polygoonid <- function(obj = NULL, conf = NULL) {
  ## ------------- muutujad ja teisendused ---------------
  vars <- ajutised_muutujad(pk = NULL, obj, conf)
  obj <- vars$obj
  piir <- vars$pk
  conf <- vars$conf
  ## Konfiguratsiooni muutujale väärtuste omistamine, kui seda pole antud.
  if (!any("a00_piir" %in% ruut::db_schema_tablenames(conf = conf))) {
    cat("\nAndmebaas loomata. Palun funktsiooniga ruut::pk_sellest_alustame_db_loomist() andmebaasi loomist.\n")
    return(NULL)
  }

  ## Algorithm
  # ruut::qgis_algorithm_search_by_word(str = "extract")
  # algorithm <- "native:extractbylocation"
  # cat(ruut::qgis_show_help(algorithm = algorithm))

  ## -------------------- Loop -----------------------
  intersect_layers <- c("a00_bb2") # c("piir", "bb", "bb2")
  andmed <- data.frame("schema" = character(0), "table" = character(0))
  andmed <- rbind(andmed, data.frame("schema" = "osm_shp", "table" = "landuse_a"))
  andmed <- rbind(andmed, data.frame("schema" = "maaamet", "table" = "asustusyksus"))
  andmed <- rbind(andmed, data.frame("schema" = "maaamet", "table" = "shp_katastriyksus"))
  andmed <- rbind(andmed, data.frame("schema" = "osm_shp", "table" = "buildings_a"))
  andmed <- rbind(andmed, data.frame("schema" = "osm_shp", "table" = "water_a"))
  andmed <- rbind(andmed, data.frame("schema" = "osm_shp", "table" = "pofw_a"))
  andmed <- rbind(andmed, data.frame("schema" = "osm_shp", "table" = "pois_a"))
  andmed <- rbind(andmed, data.frame("schema" = "osm_shp", "table" = "natural_a"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_201_meri_a_dissolved"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_202_seisuveekogu_a_dissolved"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_203_vooluveekogu_a_dissolved"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_301_muu_kolvik_a"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_301_muu_kolvik_ka"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_302_ou_a"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_303_haritav_maa_a"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_304_lage_a"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_305_puittaimestik_a_dissolved"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_306_margala_a_dissolved"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_306_margala_ka"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_307_turbavali_a"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_401_hoone_ka"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_403_muu_rajatis_ka"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_404_maaalune_hoone_ka"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_501_tee_a"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "e_505_liikluskorralduslik_rajatis_ka"))
  andmed <- rbind(andmed, data.frame("schema" = "eesti", "table" = "mullakaart"))


  for (intersect in intersect_layers) {
    conf$table <- intersect
    conf$schema <- obj
    intersect_layer <- ruut::construct_to_gpkg_output_postgres_str(conf = conf, geometry_type = "Polygon", srid = 3301, checkPrimaryKeyUnicity = TRUE, key = "id")

    for (i in 1:nrow(andmed)) {
      if (andmed$schema[i] %in% c("teeregister_wfs")) geom <- "geometry" else geom <- "geom"
      conf$table <- andmed$table[i]
      conf$schema <- andmed$schema[i]
      input <- ruut::construct_to_gpkg_output_postgres_str(
        conf = conf, geometry_type = "Polygon", srid = 3301,
        checkPrimaryKeyUnicity = TRUE, key = "id", geometry_field = geom
      )
      ## Andmebaasi tabeli nimi: 2 esimest tähte tuleb schema nimest millest on andmed võetud, siis '_a_' s.o 'area' mis tähistab polügoone.
      conf$table <- sprintf("%s_a_%s", strtrim(as.character(andmed$schema[i]), 2), andmed$table[i])
      conf$schema <- obj
      output <- ruut::construct_to_gpkg_output_postgres_str(conf = conf, geometry_field = "geom", geometry_type = NULL, srid = 3301, checkPrimaryKeyUnicity = FALSE, key = "id")
      str <- paste0("{ 'INPUT' : '", input, "', 'INPUT_FIELDS' : [], 'OUTPUT' : '", output, "', 'OVERLAY' : '", intersect_layer, "', 'OVERLAY_FIELDS' : [], 'OVERLAY_FIELDS_PREFIX' : '' }")
      algorithm <- "native:intersection"
      cmd <- ruut::construct_qgis_output_result_to_better_format(str = str, algorithm = algorithm)
      cat(sprintf("\n%s\n\n", cmd))
      system(cmd)

      ## Filtreerime mõned andmetabelid eraldi alamkihtideks
      if (andmed$table[i] == "landuse_a") {
        parent_table <- sprintf("%s_a_%s", strtrim(as.character(andmed$schema[i]), 2), andmed$table[i])
        conn <- ruut::db_connect(conf = conf)
        landuse_a <- unique(as.data.frame(sf::st_read(dsn = conn, layer = c(conf$schema, parent_table), as_tibble = T))[, c("code", "fclass")])
        for (k in 1:nrow(landuse_a)) {
          table_suffix <- landuse_a$fclass[k]
          conf$table <- parent_table
          conf$schema <- obj
          input <- ruut::construct_to_gpkg_output_postgres_str(conf = conf, geometry_type = "MultiPolygon", srid = 3301, checkPrimaryKeyUnicity = TRUE, key = "id")
          # sf::st_read(dsn = conn, layer = c(conf$schema, parent_table))
          conf$table <- sprintf("%s_%s", parent_table, table_suffix)
          output <- ruut::construct_to_gpkg_output_postgres_str(conf = conf, geometry_field = "geom", geometry_type = "Polygon", srid = 3301, checkPrimaryKeyUnicity = FALSE, key = "id")
          str <- paste0("{ 'INPUT' : '", input, "', 'INTERSECT' : '", intersect_layer, "', 'OUTPUT' : '", output, "', FIELD : 'code', OPERATOR : 0, VALUE : '", landuse_a$code[k], "' }")
          algorithm <- "native:extractbyattribute"
          cmd <- ruut::construct_qgis_output_result_to_better_format(str = str, algorithm = algorithm)
          cat(sprintf("\n%s\n", cmd))
          system(cmd)
        }
      }
      ## Filtreerime mõned andmetabelid eraldi alamkihtideks
      if (andmed$table[i] == "e_401_hoone_ka") {
        parent_table <- sprintf("%s_a_%s", strtrim(as.character(andmed$schema[i]), 2), andmed$table[i])
        conn <- ruut::db_connect(conf = conf)
        alamobjektid <- unique(as.data.frame(sf::st_read(dsn = conn, layer = c(conf$schema, parent_table), as_tibble = T))[, c("kood", "tyyp")])
        for (k in 1:nrow(alamobjektid)) {
          table_suffix <- alamobjektid$tyyp[k]
          conf$table <- parent_table
          conf$schema <- obj
          input <- ruut::construct_to_gpkg_output_postgres_str(conf = conf, geometry_type = "MultiPolygon", srid = 3301, checkPrimaryKeyUnicity = TRUE, key = "id")
          # sf::st_read(dsn = conn, layer = c(conf$schema, parent_table))
          conf$table <- sprintf("%s_%s", parent_table, table_suffix)
          output <- ruut::construct_to_gpkg_output_postgres_str(conf = conf, geometry_field = "geom", geometry_type = "Polygon", srid = 3301, checkPrimaryKeyUnicity = FALSE, key = "id")
          str <- paste0("{ 'INPUT' : '", input, "', 'INTERSECT' : '", intersect_layer, "', 'OUTPUT' : '", output, "', FIELD : 'tyyp', OPERATOR : 0, VALUE : '", alamobjektid$tyyp[k], "' }")
          algorithm <- "native:extractbyattribute"
          cmd <- ruut::construct_qgis_output_result_to_better_format(str = str, algorithm = algorithm)
          cat(sprintf("\n%s\n", cmd))
          system(cmd)
          ## ----------- lisame tsentroidid -----------
          conf$table <- sprintf("%s_%s", parent_table, table_suffix)
          conf$schema <- obj
          input <- ruut::construct_to_gpkg_output_postgres_str(conf = conf, geometry_type = "MultiPolygon", srid = 3301, checkPrimaryKeyUnicity = TRUE, key = "id")
          conf$table <- sprintf("%s_%s_p", parent_table, table_suffix)
          output <- ruut::construct_to_gpkg_output_postgres_str(conf = conf, geometry_field = "geom", geometry_type = "Polygon", srid = 3301, checkPrimaryKeyUnicity = FALSE, key = "id")
          str <- sprintf("{ 'ALL_PARTS' : False, 'INPUT' : '%s', 'OUTPUT' : '%s' }", input, output)
          # ruut::qgis_algorithm_search_by_word("centroid")
          algorithm <- "native:centroids"
          # ruut::qgis_show_help(algorithm = algorithm)
          cmd <- ruut::construct_qgis_output_result_to_better_format(str = str, algorithm = algorithm)
          cat(sprintf("\n%s\n", cmd))
          system(cmd)
        }
      }
    }
  }
  ## Layers list
  conf$schema <- obj
  ruut::db_schema_tablenames(conf = conf)
  sf::st_layers(dsn = vars$tmp_gpkg_file)
}