match gdptools weight method

R/calculate_area_intersection_weights.R

@@ -154,10 +154,10 @@ calculate_area_intersection_weights <- function(x, y, normalize, allow_lonlat =
                             areaWeight = "areaWeight_x_y")
 
   } else {
-    
-    # for normalized, we sum the intersection area by the total target intersection area
-    int <- ungroup(mutate(group_by(int, vary), 
-                          totalArea_y = sum(.data$area_intersection)))
+
+    # for normalized, we sum the intersection area by the total target area
+    int <- left_join(int, data.frame(vary = y$vary, 
+                                     totalArea_y = as.numeric(sf::st_area(y))), by = "vary")
 
     int <- areal::aw_weight(int, 
                             areaVar = "area_intersection",

tests/testthat/test_area_weighted.R

@@ -179,7 +179,8 @@ test_that("extended_example", {
 
     (y_x_norm <- calculate_area_intersection_weights(y, x, normalize = TRUE))
 
-    expect_true(all(dplyr::summarize(dplyr::group_by(y_x_norm, idx), w = sum(w))$w == 1))
+    expect_equal(dplyr::summarize(dplyr::group_by(y_x_norm, idx), w = sum(w))$w,
+                 c(1, .25, .5, .5))
 
     # and to use these in an area weighted sum we need the area of each polygon in 
     # the source data (x)
@@ -190,7 +191,7 @@ test_that("extended_example", {
         dplyr::mutate(val = ifelse(is.na(w), NA, val)) |>
         dplyr::group_by(idx) |> # group so we get one row per `x`
         # now we weight by the percent of the area from each polygon in `x` per polygon in `y`
-        dplyr::mutate(new_val = sum( (val * w), na.rm = TRUE )))
+        dplyr::mutate(new_val = sum( (val * w), na.rm = TRUE ) / sum(w, na.rm = TRUE)))
 
     # summarize to show the result
     (z_y_x_norm <- dplyr::summarise(z_y_x_norm, new_val = unique(new_val)))