Merge pull request #799 from e-sensing/dev

Pre-release 1.1.0

Author: rolfsimoes

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: sits
 Type: Package
-Version: 1.0.1
+Version: 1.1.0
 Title: Satellite Image Time Series Analysis for Earth Observation Data Cubes
 Authors@R: c(person('Rolf', 'Simoes', role = c('aut'), email = '[email protected]'),
              person('Gilberto', 'Camara', role = c('aut', 'cre'), email = '[email protected]'),
@@ -68,6 +68,7 @@ Suggests:
     dendextend,
     dtwclust,
     dtwSat (>= 0.2.7),
+    DiagrammeR,
     digest,
     e1071,
     FNN,
@@ -83,11 +84,12 @@ Suggests:
     mgcv,
     openxlsx,
     randomForest,
+    randomForestExplainer,
     RcppArmadillo (>= 0.11),
     scales,
     stars (>= 0.5),
     testthat (>= 3.1.3),
-    torchopt(>= 0.1.1),
+    torchopt(>= 0.1.2),
     xgboost,
     zoo
 Config/testthat/edition: 3
@@ -132,6 +134,7 @@ Collate:
     'sits_lighttae.R'
     'sits_machine_learning.R'
     'sits_merge.R'
+    'sits_mixture_model.R'
     'sits_mlp.R'
     'sits_parallel.R'
     'sits_patterns.R'
@@ -156,7 +159,8 @@ Collate:
     'sits_source_api_bdc.R'
     'sits_source_api_deafrica.R'
     'sits_source_api_local.R'
-    'sits_source_api_mspc.R'
+    'sits_source_api_mpc.R'
+    'sits_source_api_sdc.R'
     'sits_source_api_stac.R'
     'sits_source_api_usgs.R'
     'sits_space_time_operations.R'

NAMESPACE

@@ -5,10 +5,11 @@ S3method("sits_labels<-",sits)
 S3method(.cube_is_regular,default)
 S3method(.cube_is_regular,raster_cube)
 S3method(.cube_token_generator,default)
-S3method(.cube_token_generator,mspc_cube)
+S3method(.cube_token_generator,mpc_cube)
 S3method(.raster_check_package,terra)
 S3method(.raster_col,terra)
 S3method(.raster_crop,terra)
+S3method(.raster_crop_metadata,terra)
 S3method(.raster_crs,terra)
 S3method(.raster_data_type,terra)
 S3method(.raster_extract,terra)
@@ -41,48 +42,56 @@ S3method(.sits_rename_bands,sits)
 S3method(.sits_roi_bbox,ll)
 S3method(.sits_roi_bbox,sf)
 S3method(.sits_roi_bbox,xy)
-S3method(.source_collection_access_test,mspc_cube)
+S3method(.source_collection_access_test,mpc_cube)
 S3method(.source_collection_access_test,stac_cube)
 S3method(.source_collection_access_test,usgs_cube)
 S3method(.source_cube,stac_cube)
 S3method(.source_item_get_bands,stac_cube)
+S3method(.source_item_get_cloud_cover,sdc_cube)
 S3method(.source_item_get_cloud_cover,stac_cube)
 S3method(.source_item_get_date,stac_cube)
 S3method(.source_item_get_hrefs,bdc_cube)
+S3method(.source_item_get_hrefs,sdc_cube)
 S3method(.source_item_get_hrefs,stac_cube)
 S3method(.source_item_get_hrefs,usgs_cube)
 S3method(.source_items_bands_select,stac_cube)
 S3method(.source_items_cube,stac_cube)
 S3method(.source_items_fid,stac_cube)
-S3method(.source_items_new,"mspc_cube_landsat-8-c2-l2")
-S3method(.source_items_new,"mspc_cube_sentinel-2-l2a")
+S3method(.source_items_new,"mpc_cube_landsat-c2-l2")
+S3method(.source_items_new,"mpc_cube_sentinel-2-l2a")
 S3method(.source_items_new,aws_cube)
 S3method(.source_items_new,bdc_cube)
 S3method(.source_items_new,deafrica_cube)
+S3method(.source_items_new,sdc_cube)
 S3method(.source_items_new,usgs_cube)
-S3method(.source_items_tile,"mspc_cube_landsat-8-c2-l2")
-S3method(.source_items_tile,"mspc_cube_sentinel-2-l2a")
+S3method(.source_items_tile,"mpc_cube_landsat-c2-l2")
+S3method(.source_items_tile,"mpc_cube_sentinel-2-l2a")
 S3method(.source_items_tile,aws_cube)
 S3method(.source_items_tile,bdc_cube)
 S3method(.source_items_tile,deafrica_cube)
+S3method(.source_items_tile,sdc_cube)
 S3method(.source_items_tile,usgs_cube)
 S3method(plot,classified_image)
 S3method(plot,geo_distances)
 S3method(plot,patterns)
 S3method(plot,predicted)
 S3method(plot,probs_cube)
 S3method(plot,raster_cube)
+S3method(plot,rfor_model)
 S3method(plot,sits)
 S3method(plot,som_evaluate_cluster)
 S3method(plot,som_map)
 S3method(plot,torch_model)
 S3method(plot,uncertainty_cube)
+S3method(plot,xgb_model)
 S3method(print,sits_area_assessment)
 S3method(print,sits_assessment)
 S3method(sits_accuracy,classified_image)
 S3method(sits_accuracy,sits)
 S3method(sits_apply,raster_cube)
 S3method(sits_apply,sits)
+S3method(sits_as_sf,raster_cube)
+S3method(sits_as_sf,sits)
 S3method(sits_bands,patterns)
 S3method(sits_bands,sits)
 S3method(sits_bands,sits_cube)
@@ -137,7 +146,6 @@ export(.sits_parse_roi_cube)
 export(.sits_roi_sf_to_geojson)
 export(sits_accuracy)
 export(sits_accuracy_summary)
-export(sits_active_tests)
 export(sits_apply)
 export(sits_as_sf)
 export(sits_bands)
@@ -146,7 +154,7 @@ export(sits_classify)
 export(sits_cluster_clean)
 export(sits_cluster_dendro)
 export(sits_cluster_frequency)
-export(sits_confidence_samples)
+export(sits_confidence_sampling)
 export(sits_config)
 export(sits_config_show)
 export(sits_cube)
@@ -163,13 +171,15 @@ export(sits_labels_summary)
 export(sits_lighttae)
 export(sits_list_collections)
 export(sits_merge)
+export(sits_mixture_model)
 export(sits_mlp)
 export(sits_patterns)
 export(sits_reduce_imbalance)
 export(sits_regularize)
 export(sits_resnet)
 export(sits_rfor)
 export(sits_run_examples)
+export(sits_run_tests)
 export(sits_sample)
 export(sits_select)
 export(sits_sgolay)
@@ -202,4 +212,5 @@ importFrom(dplyr,.data)
 importFrom(lubridate,"%m+%")
 importFrom(lubridate,"%within%")
 importFrom(magrittr,"%>%")
+importFrom(utils,read.csv)
 useDynLib(sits, .registration = TRUE)

NEWS.md

@@ -1,12 +1,28 @@
 # SITS Release History
 
+# What's new in SITS version 1.1.0
+
+### New features in SITS version 1.1.0
+* Introduced support to kernel functions in `sits_apply`
+* Introduced new function `sits_mixture_model` for spectral mixture analysis
+* Support for the Swiss Data Cube ([swissdatacube.org](https://www.swissdatacube.org/))
+* Support for mosaic visualization in `sits_view`
+* Introduced new function `sits_as_sf` to convert sits objects to sf
+* Export images as [COG](https://www.cogeo.org/) in `sits_regularize`
+* Add `roi` parameter in `sits_regularize` function
+* Add `crs` parameter in `sits_get_data`
+* Change Microsoft Planetary Computer source name to `"MPC"`
+* Fix several bugs and improve performance
+
 # What's new in SITS version 1.0.0
 * Available on CRAN.
 
 ### New features in SITS version 1.0.0
 * Hotfix to improve `sits_whittaker()` function to process cube.
 * Update documentation to match CRAN standards
 
+# What's new in SITS version  0.17.0
+
 ### New features in SITS version 0.17.0
 * Introduced new classifier model `sits_lighttae()`
 (Lightweight Temporal Self-Attention)

R/RcppExports.R

@@ -17,6 +17,10 @@ entropy_probs <- function(mtx, n) {
     .Call(`_sits_entropy_probs`, mtx, n)
 }
 
+kernel_fun <- function(data, band, img_nrow, img_ncol, window_size, fun) {
+    .Call(`_sits_kernel_fun`, data, band, img_nrow, img_ncol, window_size, fun)
+}
+
 least_probs <- function(mtx, n) {
     .Call(`_sits_least_probs`, mtx, n)
 }
@@ -33,6 +37,10 @@ margin_probs <- function(mtx, n) {
     .Call(`_sits_margin_probs`, mtx, n)
 }
 
+nnls_solver <- function(x, A, iterate = 400L, tolerance = 0.000001) {
+    .Call(`_sits_nnls_solver`, x, A, iterate, tolerance)
+}
+
 normalize_data <- function(data, min, max) {
     .Call(`_sits_normalize_data`, data, min, max)
 }
@@ -41,6 +49,18 @@ ratio_probs <- function(mtx, n) {
     .Call(`_sits_ratio_probs`, mtx, n)
 }
 
+max_sampling <- function(data, band, img_nrow, img_ncol, window_size) {
+    .Call(`_sits_max_sampling`, data, band, img_nrow, img_ncol, window_size)
+}
+
+smooth_sg <- function(data, f_res, p, n) {
+    .Call(`_sits_smooth_sg`, data, f_res, p, n)
+}
+
+smooth_sg_mtx <- function(data, f_res, p, n) {
+    .Call(`_sits_smooth_sg_mtx`, data, f_res, p, n)
+}
+
 smooth_whit <- function(data, lambda, length) {
     .Call(`_sits_smooth_whit`, data, lambda, length)
 }

R/sits_accuracy.R

@@ -448,13 +448,13 @@ sits_accuracy_summary <- function(x,
     )
 
     overall_text <- c(
-        paste(overall["Accuracy"]), accuracy_ci, "",
+        paste(overall["Accuracy"]), accuracy_ci,
         paste(overall["Kappa"])
     )
 
-    overall_names <- c("Accuracy", "95% CI", "", "Kappa")
+    overall_names <- c("Accuracy", "95% CI", "Kappa")
 
-    cat("\nOverall Statistics\n")
+    cat("Overall Statistics")
     overall_names <- ifelse(overall_names == "",
         "",
         paste(overall_names, ":")