diff alpha_beta.r @ 0:5cae678042ec 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/alpha_beta.r	Mon Jan 09 13:36:33 2023 +0000
@@ -0,0 +1,142 @@
+#Rscript
+
+###########################################
+##    Mapping alpha and beta diversity   ##
+###########################################
+
+#####Packages : stars
+#               utils
+#               biodivmapr
+#               raster
+#               sf
+#               mapview
+#               leafpop
+#               RColorBrewer
+#               labdsv
+#               rgdal
+#               ggplot2
+#               gridExtra
+
+#####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]
+    # type of PCA:
+    # PCA: no rescaling of the data
+    # SPCA: rescaling of the data
+    typepca <- as.character(args[4])
+    alpha <- as.logical(args[5])
+    beta <- as.logical(args[6])
+    funct <- as.logical(args[7])
+    all <- as.logical(args[8])
+    nbcpu <- as.integer(args[9])
+    source(args[10])
+}
+
+################################################################################
+##              DEFINE PARAMETERS FOR DATASET TO BE PROCESSED                 ##
+################################################################################
+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_files <- pca_output$PCA_Files
+pix_per_partition <- pca_output$Pix_Per_Partition
+nb_partitions <- pca_output$nb_partitions
+# path for the updated mask
+input_mask_file <- pca_output$MaskPath
+
+
+selected_pcs <- seq(1, dim(raster::stack(input_image_file))[3])
+
+selected_pcs <- all(selected_pcs)
+################################################################################
+##                      MAP ALPHA AND BETA DIVERSITY                          ##
+################################################################################
+print("MAP SPECTRAL SPECIES")
+
+kmeans_info <- biodivMapR::map_spectral_species(Input_Image_File = input_image_file, Output_Dir = output_dir, PCA_Files = pca_files, Input_Mask_File = input_mask_file, SelectedPCs = selected_pcs, Pix_Per_Partition = pix_per_partition, nb_partitions = nb_partitions, TypePCA = typepca, nbCPU = nbcpu, MaxRAM = maxram, nbclusters = nbclusters)
+
+image_name <- tools::file_path_sans_ext(basename(input_image_file))
+if (alpha == TRUE || beta == TRUE || all == TRUE) {
+## alpha
+  print("MAP ALPHA DIVERSITY")
+  index_alpha <- c("Shannon")
+  alpha_div <- biodivMapR::map_alpha_div(Input_Image_File = input_image_file, Output_Dir = output_dir, TypePCA = typepca, window_size = window_size, nbCPU = nbcpu, MaxRAM = maxram, Index_Alpha = index_alpha, nbclusters = nbclusters, FullRes = TRUE, LowRes = FALSE, MapSTD = FALSE)
+
+  alpha_zip <- file.path(output_dir, image_name, typepca, "ALPHA", "Shannon_10_Fullres.zip")
+  alpha_path <- file.path(output_dir, image_name, typepca, "ALPHA")
+  unzip(alpha_zip, exdir = alpha_path)
+  alpha_path <- file.path(output_dir, image_name, typepca, "ALPHA", "Shannon_10_Fullres")
+  alpha_raster <- raster::raster(alpha_path)
+  get_alpha <- convert_raster(alpha_raster)
+
+ if (alpha == TRUE || all == TRUE) {
+   colnames(get_alpha) <- c("Alpha", "longitude", "latitude")
+   plot_indices(get_alpha, titre = "Alpha")
+
+   write.table(get_alpha, file = "alpha.tabular", sep = "\t", dec = ".", na = " ", row.names = FALSE, col.names = TRUE, quote = FALSE)
+}
+  if (beta == TRUE || all == TRUE) {
+## beta
+  print("MAP BETA DIVERSITY")
+  beta_div <- biodivMapR::map_beta_div(Input_Image_File = input_image_file, Output_Dir = output_dir, TypePCA = typepca, window_size = window_size, nb_partitions = nb_partitions, nbCPU = nbcpu, MaxRAM = maxram, nbclusters = nbclusters)
+
+  beta_path <- file.path(output_dir, image_name, typepca, "BETA", "BetaDiversity_BCdiss_PCO_10")
+  beta_raster <- raster::raster(beta_path)
+  get_beta <- convert_raster(beta_raster)
+
+  colnames(get_beta) <- c("Beta", "longitude", "latitude")
+  plot_indices(get_beta, titre = "Beta")
+
+  write.table(get_beta, file = "beta.tabular", sep = "\t", dec = ".", na = " ", row.names = FALSE, col.names = TRUE, quote = FALSE)
+  }
+}
+
+
+################################################################################
+##          COMPUTE ALPHA AND BETA DIVERSITY FROM FIELD PLOTS                 ##
+################################################################################
+
+if (funct == TRUE || all == TRUE) {
+  mapper <- biodivMapR::map_functional_div(Original_Image_File = input_image_file, Functional_File = pca_files,  Selected_Features = selected_pcs, Output_Dir = output_dir, window_size = window_size, nbCPU = nbcpu, MaxRAM = maxram, TypePCA = typepca, FullRes = TRUE, LowRes = FALSE, MapSTD = FALSE)
+
+  funct_zip <- file.path(output_dir, image_name, typepca, "FUNCTIONAL", "FunctionalDiversity_Map_MeanFilter_Fullres.zip")
+  funct_path <- file.path(output_dir, image_name, typepca, "FUNCTIONAL")
+  unzip(funct_zip, exdir = funct_path)
+  funct_path <- file.path(output_dir, image_name, typepca, "FUNCTIONAL", "FunctionalDiversity_Map_MeanFilter_Fullres")
+  funct_raster <- raster::raster(funct_path)
+  get_funct <- convert_raster(funct_raster)
+
+  colnames(get_funct) <- c("Functionnal", "longitude", "latitude")
+  plot_indices(get_funct, titre = "Functionnal")
+
+  write.table(get_funct, file = "Functionnal.tabular", sep = "\t", dec = ".", na = " ", row.names = FALSE, col.names = TRUE, quote = FALSE)
+}