new functions

NAMESPACE

@@ -1,5 +1,7 @@
 # Generated by roxygen2: do not edit by hand
 
 export(align_events)
+export(merge_normalized_differences)
+export(normalized_difference)
 export(read_appeears)
 export(read_ml_data)

R/merge_normalized_differences.R

@@ -0,0 +1,57 @@
+
+#' Merge / calculate difference ratios
+#'
+#' Calculate normalized difference ratios
+#' for all possible "sur_refl" band combinations
+#'
+#' @param ml_df a machine learning data frame with "sur_refl" prefix column
+#'  names apply the band ratios to
+#'
+#' @return A machine learning data frame with normalized band ratios appended
+#' @export
+
+merge_normalized_differences <- function(ml_df){
+
+  # split out surface reflectance values
+  sur_refl <- ml_df |>
+    dplyr::select(
+      starts_with("sur_refl")
+    )
+
+  # calculate all normalized difference ratios
+  ndr <- lapply(names(sur_refl), function(band){
+
+    # split out reference band
+    band_1 <- sur_refl |>
+      dplyr::select(
+        all_of(band)
+      )
+
+    # mutate over all other collumns
+    df <- sur_refl |>
+      dplyr::select(
+        !all_of(band)
+      )
+
+    # wrangle all column names
+    cols <- gsub("sur_refl_", "", names(df))
+    ref_col <- gsub("sur_refl_", "", names(band_1))
+
+    df <- df |>
+      dplyr::transmute_all(
+        function(x){as.vector(normalized_difference(band_1, x))}
+      )
+
+    # add clean column names
+    colnames(df) <- paste(ref_col, cols, sep = "_")
+    return(df)
+  })
+
+  # bind columns in one big tibble
+  ndr <- dplyr::bind_cols(ndr)
+
+  # merge with original data
+  ml_df <- bind_cols(ml_df, ndr)
+}
+
+

R/normalized_difference.R

@@ -0,0 +1,16 @@
+
+#' Normalized difference
+#'
+#' Calculates normalized difference for two (arbitrary) bands. The difference
+#' is taken as band 1 - band 2
+#'
+#' @param band_1 first band
+#' @param band_2 second band
+#'
+#' @return normalized difference index for two bands
+#' @export
+
+normalized_difference <- function(band_1, band_2){
+  ndr <- (band_1 - band_2)/(band_1 + band_2)
+  as.matrix(ndr)
+}