Fix vector cube bugs

R/api_classify.R

@@ -596,7 +596,8 @@
         prediction <- .classify_ts_gpu(
             pred = pred,
             ml_model = ml_model,
-            gpu_memory = gpu_memory)
+            gpu_memory = gpu_memory
+        )
     else
         prediction <- .classify_ts_cpu(
             pred = pred,
@@ -651,6 +652,8 @@
         values <- .pred_features(pred_part)
         # Classify
         values <- ml_model(values)
+        # normalize and calibrate values
+        values <- .ml_normalize(ml_model, values)
         # Return classification
         values <- tibble::as_tibble(values)
         values
@@ -691,8 +694,10 @@
         values <- .pred_features(pred_part)
         # Classify
         values <- ml_model(values)
+        # normalize and calibrate values
+        values <- .ml_normalize(ml_model, values)
         # Return classification
-        values <- tibble::tibble(data.frame(values))
+        values <- tibble::as_tibble(values)
         # Clean GPU memory
         .ml_gpu_clean(ml_model)
         return(values)

R/api_ml_model.R

@@ -119,8 +119,10 @@
 #' @export
 #'
 .ml_normalize.torch_model <- function(ml_model, values){
+    column_names <- colnames(values)
     values[is.na(values)] <- 0
     values <- softmax(values)
+    colnames(values) <- column_names
     return(values)
 }
 #' @export

R/api_tile.R

@@ -1465,7 +1465,8 @@ NULL
         x = r_obj,
         y = segments,
         fun = NULL,
-        include_cols = "pol_id"
+        include_cols = "pol_id",
+        progress = FALSE
     )
     values <- dplyr::bind_rows(values)
     values <- dplyr::select(values, -"coverage_fraction")

R/sits_classify.R

@@ -437,7 +437,7 @@ sits_classify.segs_cube <- function(data,
         proc_bloat <- .conf("processing_bloat_gpu")
     }
     # avoid memory race in Apple MPS
-    if(.torch_mps_enabled(ml_model)){
+    if (.torch_mps_enabled(ml_model)) {
         memsize <- 1
         gpu_memory <- 1
     }

R/sits_plot.R

@@ -836,6 +836,8 @@ plot.vector_cube <- function(x, ...,
             sf_seg   = sf_seg,
             seg_color = seg_color,
             line_width = line_width,
+            first_quantile = first_quantile,
+            last_quantile = last_quantile,
             scale = scale,
             max_cog_size = max_cog_size,
             tmap_params = tmap_params

inst/extdata/config_internals.yml

@@ -125,6 +125,13 @@ default_values       :
         maximum_value: 1.7014118346015974e+37
         offset_value : 0
         scale_factor : 1
+    FLT8S            :
+        data_type    : "FLT8S"
+        missing_value: -3.402823466385288e+37
+        minimum_value: -3.402823466385288e+37
+        maximum_value: 1.7014118346015974e+37
+        offset_value : 0
+        scale_factor : 1
 
 # Derived cube definitions
 derived_cube         :