138 lines
4 KiB
R
138 lines
4 KiB
R
# nolint start: commented_code_linter, line_length_linter,object_usage_linter.
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library(sf)
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library(terra)
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library(tidyverse)
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library(lubridate)
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library(exactextractr)
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library(readxl)
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# Vang alle command line argumenten op
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args <- commandArgs(trailingOnly = TRUE)
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# Controleer of er ten minste één argument is doorgegeven
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if (length(args) == 0) {
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stop("Geen argumenten doorgegeven aan het script")
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}
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# Converteer het eerste argument naar een numerieke waarde
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end_date <- as.Date(args[1])
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if (is.na(end_date)) {
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end_date <- lubridate::dmy("28-08-2024")
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}
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offset <- as.numeric(args[2])
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# Controleer of weeks_ago een geldig getal is
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if (is.na(offset)) {
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# stop("Het argument is geen geldig getal")
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offset <- 7
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}
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week <- week(end_date)
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# Converteer het tweede argument naar een string waarde
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project_dir <- as.character(args[3])
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# Controleer of data_dir een geldige waarde is
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if (!is.character(project_dir)) {
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project_dir <- "chemba"
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}
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new_project_question = FALSE
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source("parameters_project.R")
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source("ci_extraction_utils.R")
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dates <- date_list(end_date, offset)
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print(dates)
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raster_files <- list.files(planet_tif_folder,full.names = T, pattern = ".tif")
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filtered_files <- map(dates$days_filter, ~ raster_files[grepl(pattern = .x, x = raster_files)]) %>%
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compact() %>%
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flatten_chr()
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# Remove files that do not exist
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existing_files <- filtered_files[file.exists(filtered_files)]
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# Check if the list of existing files is empty
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if (length(existing_files) == 0) {
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message("No files exist for the given date(s).")
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stop("Terminating script.")
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}
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# Continue with the rest of the script
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print(existing_files)
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vrt_list <- list()
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for (file in existing_files) {
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v_crop <- create_mask_and_crop(file, field_boundaries, merged_final)
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emtpy_or_full <- global(v_crop, "notNA")
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vrt_file <- here(daily_vrt, paste0(tools::file_path_sans_ext(basename(file)), ".vrt"))
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if(emtpy_or_full[1,] > 100){
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vrt_list[vrt_file] <- vrt_file
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}else{
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file.remove(vrt_file)
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}
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message(file, " processed")
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gc()
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}
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raster_files_NEW <- list.files(merged_final,full.names = T, pattern = ".tif")
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# Define the path to the file
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file_path <- here(cumulative_CI_vals_dir, "combined_CI_data.rds")
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# Check if the file exists
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if (!file.exists(file_path)) {
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# File does not exist, create it with all available data
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print("combined_CI_data.rds does not exist. Preparing combined_CI_data.rds file for all available images.")
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# Extract data from all raster files
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walk(raster_files_NEW, extract_rasters_daily, field_geojson = field_boundaries, quadrants = FALSE, daily_CI_vals_dir)
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# Combine all extracted data
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extracted_values <- list.files(here(daily_CI_vals_dir), full.names = TRUE)
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pivot_stats <- extracted_values %>%
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map(readRDS) %>% list_rbind() %>%
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group_by(sub_field)
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# Save the combined data to the file
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saveRDS(pivot_stats, file_path)
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print("All CI values extracted from all historic images and saved to combined_CI_data.rds.")
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} else {
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# File exists, add new data
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print("combined_CI_data.rds exists, adding the latest image data to the table.")
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# Filter and process the latest data
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filtered_files <- map(dates$days_filter, ~ raster_files_NEW[grepl(pattern = .x, x = raster_files_NEW)]) %>%
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compact() %>%
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flatten_chr()
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walk(filtered_files, extract_rasters_daily, field_geojson = field_boundaries, quadrants = TRUE, daily_CI_vals_dir)
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# Extract new values
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extracted_values <- list.files(daily_CI_vals_dir, full.names = TRUE)
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extracted_values <- map(dates$days_filter, ~ extracted_values[grepl(pattern = .x, x = extracted_values)]) %>%
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compact() %>%
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flatten_chr()
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pivot_stats <- extracted_values %>%
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map(readRDS) %>% list_rbind() %>%
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group_by(sub_field)
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# Load existing data and append new data
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combined_CI_data <- readRDS(file_path)
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pivot_stats2 <- bind_rows(pivot_stats, combined_CI_data)
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# Save the updated combined data
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saveRDS(pivot_stats2, file_path)
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print("All CI values extracted from the latest images and added to combined_CI_data.rds.")
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}
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