DEV: playing around with PSD

Ref: #6

dev/verification/PSD/compare_pds.R

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+library(stars)
+library(purrr)
+library(here)
+library(glue)
+library(stringr)
+library(tidyverse)
+library(radialpsd)
+
+
+# helpers ----------------------------------------------------------------------
+# pad_to_square <- function(m, pad = 0) {
+#     dim_m <- dim(m)
+#     maxdim <- max(dim_m)
+#     out <- matrix(pad, nrow = maxdim, ncol = maxdim)
+#     start <- floor((maxdim - dim_m) / 2)
+#     end <- start + dim_m
+#     start <- start + 1
+#     out[start[1]:end[1], start[2]:end[2]] <- m
+#     out
+# }
+
+truncate_to_square <- function(m) {
+    dim_m <- dim(m)
+    mindim <- min(dim_m)
+    start <- floor((dim_m - mindim) / 2)
+    end <- start + mindim
+    start <- start + 1
+    m[start[1]:end[1], start[2]:end[2]]
+}
+
+replace_na <- function(m, replacement = 0) {
+    m[is.na(m)] <- replacement
+    m
+}
+
+# main -------------------------------------------------------------------------
+
+dothis <- function(lead_time) {
+    lead_time <- str_pad(lead_time, 2, pad = "0")
+
+    # load datasets (crop a bit as SAMOS baseline has some values NA around)
+    cerra <- read_stars(here(glue("dat/TESTING/PREPROCESSED/CERRA/t2m_cerra_{lead_time}.nc"))) %>%
+        setNames("cerra") %>%
+        .[1, 3:238,6:160]
+    downscaled <- read_stars(here(glue("dat/TESTING/SAMOS/postprocessed/samos-postprocessed_{lead_time}.nc"))) %>%
+        setNames("samos") %>%
+        .[1, 3:238,6:160]
+
+    timesteps <- seq_len(dim(cerra)["time"])
+
+    # loop over timesteps and calculate psd
+    psd_cerra <- list()
+    psd_ds <- list()
+
+    for (i in seq_along(timesteps)){
+        psd_cerra[[i]] <- radial.psd(replace_na(truncate_to_square(as.matrix(units::drop_units(cerra[[1]][,,timesteps[i]])))), plot = FALSE)#, scaled = FALSE, normalized = FALSE)
+        psd_ds[[i]] <- radial.psd(replace_na(truncate_to_square(as.matrix(downscaled[[1]][,,timesteps[i]]))), plot = FALSE)#, scaled = FALSE, normalized = FALSE)
+    }
+
+    # common dataframe
+    plotdat <- bind_rows(list(
+        cerra = psd_cerra |>
+            setNames(timesteps) |>
+            bind_rows(.id = "timesteps"),
+        samos = psd_ds|>
+            setNames(timesteps) |>
+            bind_rows(.id = "timesteps")
+    ), .id = "dataset")
+
+    # plot
+    plotdat %>%
+        ggplot(aes(x = log(wavenumber), y = log(r_spectrum), color = dataset)) + 
+        stat_smooth(
+            geom="ribbon",
+            aes(ymax = after_stat(y) + 1,
+                ymin = after_stat(y) - 1,
+                fill = dataset),
+            alpha = 0.1, linetype = 0
+        ) +
+        geom_smooth(se = FALSE)+
+        theme_minimal()
+
+    ggsave(here(glue("plt/PSD/radialPSD_samos_leadtime{lead_time}.pdf")))
+}
+
+lead_times <- seq(0, 21, by = 3)
+walk(lead_times, dothis)