knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
suppressMessages(library(dplyr)) suppressMessages(library(ggplot2)) suppressMessages(library(magrittr)) suppressMessages(library(purrr)) suppressMessages(library(raster)) suppressMessages(library(sits.prodes)) suppressMessages(library(stringr))
# Get maps in_dir <- "/home/alber/Documents/data/experiments/prodes_reproduction/03_classify/confusion_dl_rf_svm/byte" brick_raw_dir <- "/home/alber/shared/brick_raw" img_tb <- in_dir %>% list.files(pattern = "rep_prodes_[0-9]{2}_[0-9]{6}_[0-9]{4}_(smooth_3x3_n10|smooth_5x5_n10|smooth_7x7_n10|smooth_9x9_n10|smooth_11x11_n10|no_smooth).tif", full.names = TRUE) %>% tibble::enframe(name = NULL) %>% dplyr::rename(file_path = "value") %>% dplyr::mutate(file_name = basename(file_path), experiment = stringr::str_extract(file_name, "rep_prodes_[0-9]{2}"), scene = stringr::str_extract(file_name, "_[0-9]{6}_") %>% stringr::str_sub(2, -2), pyear = stringr::str_extract(file_name, "_[0-9]{4}_") %>% stringr::str_sub(2, -2), smooth = stringr::str_extract(file_name, "smooth_[0-9]+x[0-9]+_n[0-9]+")) %>% dplyr::mutate(smooth = ifelse(is.na(smooth), "no_smooth", smooth)) %>% dplyr::arrange(experiment, scene, smooth, pyear) %>% # dplyr::filter(experiment == "rep_prodes_40", scene == "226064", smooth == "smooth_11x11_n10")
my_experiment <- "" my_scene <- "" my_pyear <- "" my_smooth <- "" for (rid in seq_along(img_tb$file_path)) { if (img_tb$experiment[[rid]] != my_experiment) { my_experiment <- img_tb$experiment[[rid]] cat("\n\n") ; cat(paste0("## ", my_experiment), "\n") } if (img_tb$smooth[[rid]] != my_smooth) { my_smooth <- img_tb$smooth[[rid]] cat("\n\n") ; cat(paste0("### ", my_smooth), "\n") } if (img_tb$scene[[rid]] != my_scene) { my_scene <- img_tb$scene[[rid]] cat("\n\n") ; cat(paste0("#### ", my_scene), "\n") } if (img_tb$pyear[[rid]] != my_pyear) { my_pyear <- img_tb$pyear[[rid]] cat("\n\n") ; cat(paste0("##### ", my_pyear), "\n") } break_points <- seq(-0.5, 1.5) colors <- c("red", "darkolivegreen4", "blue") img_tb %>% dplyr::slice(rid) %>% dplyr::pull(file_path) %>% raster::raster() %>% plot(breaks = break_points, col = colors) }
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