Merge branch 'dev' of https://github.com/e-sensing/sits into feat/dev-sits

Author: OldLipe

R/api_data.R

@@ -97,8 +97,22 @@
             multicores = multicores,
             progress = progress
         )
-        # save base data
-        ts_tbl[["base_data"]] <- base_tbl[["time_series"]]
+        # prepare output data
+        base_tbl <- base_tbl |>
+                        dplyr::select("longitude", "latitude", "time_series") |>
+                        dplyr::rename("base_data" = "time_series")
+        # Assuming `ts_tbl` as the source of truth, the size of the following
+        # `join` must be the same as the current `ts_tbl`.
+        ts_tbl_size <- nrow(ts_tbl)
+        # joining samples data from cube and base_cube by longitude / latitude
+        ts_tbl <- dplyr::left_join(
+            x = ts_tbl,
+            y = base_tbl,
+            by = c("longitude", "latitude")
+        ) |>
+            tidyr::drop_na()
+        # checking samples consistency
+        .data_check(ts_tbl_size, nrow(ts_tbl))
         # add base class
         class(ts_tbl) <- c("sits_base", class(ts_tbl))
     }

R/api_segments.R

@@ -157,7 +157,7 @@
         block = block
     )
     # Get tile bands
-    tile_bands <- .tile_bands(
+    tile_bands <- .tile_bands.raster_cube(
         tile = tile,
         add_cloud = FALSE
     )
@@ -406,76 +406,3 @@
     class(samples) <- c("sits", class(samples))
     return(samples)
 }
-
-#' @title Split tile bands for extraction of values inside segments
-#' @name .segments_split_tile_bands
-#' @keywords internal
-#' @noRd
-#' @param tile   input tile
-#' @param bands  bands where data will be extracted
-#'
-#' @return tibble with band-files pairs
-#'
-.segments_split_tile_bands <- function(tile, bands) {
-    tile_bands <- purrr::map(bands, function(band) {
-        band_files <- .fi_filter_bands(.fi(tile), band)[["path"]]
-        tibble::tibble(
-            band = band,
-            files = list(band_files),
-            segs_path = .segments_path(tile),
-            params = list(.tile_band_conf(tile, band))
-        )
-    })
-    tile_bands <- dplyr::bind_rows(tile_bands)
-    return(tile_bands)
-}
-#' @title Split tile bands for extraction of values inside segments
-#' @name .segments_split_tile_bands_list
-#' @keywords internal
-#' @noRd
-#' @param tile   input tile
-#' @param bands  bands where data will be extracted
-#' @param segments large set of segments
-#' @param n_iterations number of parts to break the segments
-#' @param output_dir directory to write the segments
-#' @return list of tibbles with band-files pairs
-#'
-.segments_split_tile_bands_list <- function(tile,
-                                            bands,
-                                            segments,
-                                            n_iterations,
-                                            output_dir) {
-
-    segments[["group"]] <- rep(
-        seq_len(n_iterations), each = ceiling(nrow(segments) / n_iterations)
-    )[seq_len(nrow(segments))]
-
-    segments_lst <- dplyr::group_split(
-        dplyr::group_by(segments, .data[["group"]])
-    )
-    segment_files <- purrr::map_chr(segments_lst, function(seg_part) {
-        # Block file name
-        hash_bundle <- digest::digest(seg_part, algo = "md5")
-        seg_file <- .file_path(
-            paste0(hash_bundle, "_segments"),
-            ext = "gpkg",
-            output_dir = output_dir
-        )
-        .vector_write_vec(seg_part, seg_file)
-        return(seg_file)
-    })
-    seg_tile_band_lst <- purrr::map(segment_files, function(seg_file) {
-        tile_bands <- purrr::map(bands, function(band) {
-            band_files <- .fi_filter_bands(.fi(tile), band)[["path"]]
-            tibble::tibble(
-                band = band,
-                files = list(band_files),
-                segs_path = seg_file,
-                params = list(.tile_band_conf(tile, band))
-            )
-        })
-        seg_tile_band <- dplyr::bind_rows(tile_bands)
-        return(seg_tile_band)
-    })
-    return(seg_tile_band_lst)
-}

inst/extdata/sources/config_source_mpc.yml

@@ -128,7 +128,7 @@ sources:
                         resolution    : 30
                         data_type     : "FLT4S"
                         missing_value : -32768
-                        minimum_value : 0
+                        minimum_value : -32767
                         maximum_value : 65534
                         scale_factor  : 1
                         offset_value  : 0

tests/testthat/test-segmentation.R

@@ -200,7 +200,7 @@ test_that("Segmentation of large files",{
         seg_fn = sits_slic(
             step = 50,
             iter = 10,
-            minarea = 100
+            minarea = 50
         ),
         output_dir = output_dir,
         multicores = 4,