fix examples

R/sits_classify.R

@@ -133,14 +133,16 @@
 #'         ml_model = rf_model,
 #'         output_dir = tempdir(),
 #'         n_sam_pol = 20,
-#'         multicores = 4
+#'         multicores = 4,
+#'         version = "segs_classify"
 #'     )
 #'     # Create a labelled vector cube
 #'     class_segs <- sits_label_classification(
 #'         cube = probs_segs,
 #'         output_dir = tempdir(),
 #'         multicores = 2,
-#'         memsize = 4
+#'         memsize = 4,
+#'         version = "segs_classify"
 #'     )
 #'     # plot class_segs
 #'     plot(class_segs)

R/sits_plot.R

@@ -1380,8 +1380,6 @@ plot.som_map <- function(x, y, ..., type = "codes", band = 1) {
 #'     xgb_model <- sits_train(samples_modis_ndvi,
 #'         ml_method = sits_xgboost()
 #'     )
-#'     # plot the model
-#'     plot(xgb_model)
 #' }
 #' @export
 #'

R/sits_segmentation.R

@@ -209,20 +209,23 @@ sits_segment <- function(cube,
 #'     # segment the vector cube
 #'     segments <- sits_segment(
 #'         cube = cube,
-#'         output_dir = tempdir()
+#'         output_dir = tempdir(),
+#'         version = "slic-demo"
 #'     )
 #'     # create a classification model
 #'     rfor_model <- sits_train(samples_modis_ndvi, sits_rfor())
 #'     # classify the segments
 #'     seg_probs <- sits_classify(
 #'         data = segments,
 #'         ml_model = rfor_model,
-#'         output_dir = tempdir()
+#'         output_dir = tempdir(),
+#'         version = "slic-demo"
 #'     )
 #'     # label the probability segments
 #'     seg_label <- sits_label_classification(
 #'         cube = seg_probs,
-#'         output_dir = tempdir()
+#'         output_dir = tempdir(),
+#'         version = "slic-demo"
 #'     )
 #' }
 #' @export