diff pca_raster.r @ 0:9adccd3da70c draft default tip

planemo upload for repository https://github.com/Marie59/Sentinel_2A/srs_tools commit b32737c1642aa02cc672534e42c5cb4abe0cd3e7

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pca_raster.r	Mon Jan 09 13:37:37 2023 +0000
@@ -0,0 +1,75 @@
+#Rscript
+
+###########################################
+##    Getting PCA raster   ##
+###########################################
+
+#####Packages : stars
+#               utils
+#               biodivmapr
+#               raster
+#               sf
+#               mapview
+#               leafpop
+#               RColorBrewer
+#               labdsv
+#               rgdal
+#               ggplot2
+#               gridExtra
+## remotes::install_github("jbferet/biodivMapR")
+#####Load arguments
+
+args <- commandArgs(trailingOnly = TRUE)
+
+#####Import the S2 data
+
+if (length(args) < 1) {
+    stop("This tool needs at least 1 argument")
+}else {
+    data_raster <- args[1]
+    rasterheader <- args[2]
+    data <- args[3]
+    typepca <- as.character(args[4])
+    source(args[5])
+}
+
+################################################################################
+##              DEFINE PARAMETERS FOR DATASET TO BE PROCESSED                 ##
+################################################################################
+# expected to be in ENVI HDR
+
+if (data_raster == "") {
+  #Create a directory where to unzip your folder of data
+  dir.create("data_dir")
+  unzip(data, exdir = "data_dir")
+  # Path to raster
+  data_raster <- list.files("data_dir/results/Reflectance", pattern = "_Refl")
+  input_image_file <- file.path("data_dir/results/Reflectance", data_raster[1])
+  input_header_file <- file.path("data_dir/results/Reflectance", data_raster[2])
+
+} else {
+  input_image_file <- file.path(getwd(), data_raster, fsep = "/")
+  input_header_file <- file.path(getwd(), rasterheader, fsep = "/")
+}
+
+################################################################################
+##                              PROCESS IMAGE                                 ##
+################################################################################
+# 1- Filter data in order to discard non vegetated / shaded / cloudy pixels
+print("PERFORM PCA ON RASTER")
+pca_output <- biodivMapR::perform_PCA(Input_Image_File = input_image_file, Input_Mask_File = input_mask_file,
+                          Output_Dir = output_dir, TypePCA = typepca, FilterPCA = filterpca, nbCPU = nbcpu, MaxRAM = maxram)
+
+
+pca_path <- file.path(output_dir, basename(data_raster), typepca, "PCA", "OutputPCA_8_PCs")
+pca_raster <- raster::raster(pca_path)
+get_pca <- convert_raster(pca_raster)
+
+colnames(get_pca) <- c("PCA", "longitude", "latitude")
+plot_indices(get_pca, titre = "PCA")
+
+write.table(get_pca, file = "PCA.tabular", sep = "\t", dec = ".", na = " ", row.names = FALSE, col.names = TRUE, quote = FALSE)
+#### Get the raster layer files
+pca_files <- file.path("RESULTS", basename(data_raster), typepca, "PCA")
+to_dir_short <- output_dir
+file.copy(pca_files, to_dir_short) #copy files from long to short paths