fix plot

Author: gilbertocamara

.github/.gitignore

@@ -0,0 +1,95 @@
+# R-hub's generic GitHub Actions workflow file. It's canonical location is at
+# https://github.com/r-hub/actions/blob/v1/workflows/rhub.yaml
+# You can update this file to a newer version using the rhub2 package:
+#
+# rhub::rhub_setup()
+#
+# It is unlikely that you need to modify this file manually.
+
+name: R-hub
+run-name: "${{ github.event.inputs.id }}: ${{ github.event.inputs.name || format('Manually run by {0}', github.triggering_actor) }}"
+
+on:
+  workflow_dispatch:
+    inputs:
+      config:
+        description: 'A comma separated list of R-hub platforms to use.'
+        type: string
+        default: 'linux,windows,macos'
+      name:
+        description: 'Run name. You can leave this empty now.'
+        type: string
+      id:
+        description: 'Unique ID. You can leave this empty now.'
+        type: string
+
+jobs:
+
+  setup:
+    runs-on: ubuntu-latest
+    outputs:
+      containers: ${{ steps.rhub-setup.outputs.containers }}
+      platforms: ${{ steps.rhub-setup.outputs.platforms }}
+
+    steps:
+    # NO NEED TO CHECKOUT HERE
+    - uses: r-hub/actions/setup@v1
+      with:
+        config: ${{ github.event.inputs.config }}
+      id: rhub-setup
+
+  linux-containers:
+    needs: setup
+    if: ${{ needs.setup.outputs.containers != '[]' }}
+    runs-on: ubuntu-latest
+    name: ${{ matrix.config.label }}
+    strategy:
+      fail-fast: false
+      matrix:
+        config: ${{ fromJson(needs.setup.outputs.containers) }}
+    container:
+      image: ${{ matrix.config.container }}
+
+    steps:
+      - uses: r-hub/actions/checkout@v1
+      - uses: r-hub/actions/platform-info@v1
+        with:
+          token: ${{ secrets.RHUB_TOKEN }}
+          job-config: ${{ matrix.config.job-config }}
+      - uses: r-hub/actions/setup-deps@v1
+        with:
+          token: ${{ secrets.RHUB_TOKEN }}
+          job-config: ${{ matrix.config.job-config }}
+      - uses: r-hub/actions/run-check@v1
+        with:
+          token: ${{ secrets.RHUB_TOKEN }}
+          job-config: ${{ matrix.config.job-config }}
+
+  other-platforms:
+    needs: setup
+    if: ${{ needs.setup.outputs.platforms != '[]' }}
+    runs-on: ${{ matrix.config.os }}
+    name: ${{ matrix.config.label }}
+    strategy:
+      fail-fast: false
+      matrix:
+        config: ${{ fromJson(needs.setup.outputs.platforms) }}
+
+    steps:
+      - uses: r-hub/actions/checkout@v1
+      - uses: r-hub/actions/setup-r@v1
+        with:
+          job-config: ${{ matrix.config.job-config }}
+          token: ${{ secrets.RHUB_TOKEN }}
+      - uses: r-hub/actions/platform-info@v1
+        with:
+          token: ${{ secrets.RHUB_TOKEN }}
+          job-config: ${{ matrix.config.job-config }}
+      - uses: r-hub/actions/setup-deps@v1
+        with:
+          job-config: ${{ matrix.config.job-config }}
+          token: ${{ secrets.RHUB_TOKEN }}
+      - uses: r-hub/actions/run-check@v1
+        with:
+          job-config: ${{ matrix.config.job-config }}
+          token: ${{ secrets.RHUB_TOKEN }}

.github/workflows/rhub.yaml

@@ -27,7 +27,7 @@ Description: An end-to-end toolkit for land use and land cover classification
     random forests, extreme gradient boosting, multi-layer perceptrons,
     temporal convolutional neural networks proposed by Pelletier et al (2019) <doi:10.3390/rs11050523>, 
     residual networks by Fawaz et al (2019) <doi:10.1007/s10618-019-00619-1>, and temporal attention encoders
-    by Garnot and Landrieu (2020) <doi:10.48550/arXiv.2007.00586de>.
+    by Garnot and Landrieu (2020) <doi:10.48550/arXiv.2007.00586>.
     Performs efficient classification of big Earth observation data cubes and includes 
     functions for post-classification smoothing based on Bayesian inference, and 
     methods for uncertainty assessment. Enables best
@@ -138,6 +138,7 @@ Collate:
     'api_gdal.R'
     'api_gdalcubes.R'
     'api_jobs.R'
+    'api_kohonen.R'
     'api_label_class.R'
     'api_merge.R'
     'api_mixture_model.R'

DESCRIPTION

@@ -93,6 +93,10 @@ S3method(.data_get_ts,raster_cube)
 S3method(.gc_arrange_images,raster_cube)
 S3method(.mosaic_split_band_date,derived_cube)
 S3method(.mosaic_split_band_date,raster_cube)
+S3method(.opensearch_cdse_extract_tile,RTC)
+S3method(.opensearch_cdse_extract_tile,S2MSI2A)
+S3method(.opensearch_cdse_search,RTC)
+S3method(.opensearch_cdse_search,S2MSI2A)
 S3method(.raster_check_package,terra)
 S3method(.raster_col,terra)
 S3method(.raster_crop,terra)
@@ -355,6 +359,7 @@ S3method(sits_labels,sits_model)
 S3method(sits_labels_summary,sits)
 S3method(sits_merge,default)
 S3method(sits_merge,raster_cube)
+S3method(sits_merge,sar_cube)
 S3method(sits_merge,sits)
 S3method(sits_mixture_model,default)
 S3method(sits_mixture_model,derived_cube)
@@ -413,7 +418,6 @@ S3method(summary,sits_accuracy)
 S3method(summary,sits_area_accuracy)
 export("sits_bands<-")
 export("sits_labels<-")
-export(.mpc_clean_token_cache)
 export(impute_linear)
 export(sits_accuracy)
 export(sits_accuracy_summary)

NAMESPACE

@@ -37,8 +37,32 @@ C_kernel_modal <- function(x, ncols, nrows, band, window_size) {
     .Call(`_sits_C_kernel_modal`, x, ncols, nrows, band, window_size)
 }
 
-dtw <- function() {
-    .Call(`_sits_dtw`)
+kohonen_dtw <- function() {
+    .Call(`_sits_kohonen_dtw`)
+}
+
+kohonen_euclidean <- function() {
+    .Call(`_sits_kohonen_euclidean`)
+}
+
+kohonen_object_distances <- function(data, numVars, numNAs, distanceFunction, weights) {
+    .Call(`_sits_kohonen_object_distances`, data, numVars, numNAs, distanceFunction, weights)
+}
+
+RcppMap <- function(data, numVars, numNAs, codes, weights, distanceFunction) {
+    .Call(`_sits_RcppMap`, data, numVars, numNAs, codes, weights, distanceFunction)
+}
+
+RcppSupersom <- function(data, codes, numVars, weights, distanceFunction, numNAs, neighbourhoodDistances, alphas, radii, numEpochs) {
+    .Call(`_sits_RcppSupersom`, data, codes, numVars, weights, distanceFunction, numNAs, neighbourhoodDistances, alphas, radii, numEpochs)
+}
+
+RcppBatchSupersom <- function(data, codes, numVars, weights, distanceFunction, numNAs, neighbourhoodDistances, radii, numEpochs) {
+    .Call(`_sits_RcppBatchSupersom`, data, codes, numVars, weights, distanceFunction, numNAs, neighbourhoodDistances, radii, numEpochs)
+}
+
+RcppParallelBatchSupersom <- function(data, codes, numVars, weights, distanceFunction, numNAs, neighbourhoodDistances, radii, numEpochs, numCores) {
+    .Call(`_sits_RcppParallelBatchSupersom`, data, codes, numVars, weights, distanceFunction, numNAs, neighbourhoodDistances, radii, numEpochs, numCores)
 }
 
 C_label_max_prob <- function(x) {
@@ -141,14 +165,6 @@ C_temp_iqr <- function(mtx) {
     .Call(`_sits_C_temp_iqr`, mtx)
 }
 
-rlang_env_unlock <- function(env) {
-    invisible(.Call(`_sits_rlang_env_unlock`, env))
-}
-
-rlang_env_lock <- function(env) {
-    invisible(.Call(`_sits_rlang_env_lock`, env))
-}
-
 C_max_sampling <- function(x, nrows, ncols, window_size) {
     .Call(`_sits_C_max_sampling`, x, nrows, ncols, window_size)
 }