Created
September 7, 2024 14:08
-
-
Save JosiahParry/ad3d591738b3e284c590f8b35f10bd5a to your computer and use it in GitHub Desktop.
spatial lag categorical development
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| # remotes::install_github("simonpcouch/forested") | |
| library(dplyr) | |
| library(sfdep) | |
| library(spdep) | |
| trees <- forested::forested |> | |
| sf::st_as_sf(coords = c("lon", "lat"), crs = 4326) | |
| k <- ceiling(nrow(trees)^(1/3)) | |
| nb <- st_knn(trees, k) | |
| wt <- st_kernel_weights(nb, trees, "gaussian", adaptive = TRUE) | |
| listw <- nb2listw(nb, wt, "B") | |
| glimpse(trees) | |
| table(trees$land_type) | |
| # sum of the weights for each class | |
| lag_categorical_weighted_sum <- function(f, listw) { | |
| f_levs <- levels(f) | |
| n_cats <- length(f_levs) | |
| n_row <- length(f) | |
| cols <- setNames( | |
| replicate(n_cats, double(n_row), FALSE), | |
| cat_names | |
| ) | |
| idx <- rep.int(1:n_row, lengths(listw$weights)) | |
| fj <- f[unlist(listw$neighbours)] | |
| wj <- unlist(listw$weights) | |
| res <- hardhat::weighted_table( | |
| from = as.factor(idx), | |
| fj, | |
| weights = wj | |
| ) | |
| # row standardize it | |
| res <- as.data.frame(res / rowSums(res)) | |
| # clean column names | |
| colnames(res) <- heck::to_snek_case(colnames(res)) | |
| # add tbl and data.frame class | |
| class(res) <- c("tbl", "data.frame") | |
| # return | |
| res | |
| } | |
| lag_categorical_weighted_sum(trees$land_type, listw) | |
| data.frame(f = f[nb[[1]]], wt = wt[[1]]) |> | |
| group_by(f) |> summarise(v = sum(wt)) | |
| lag_categorical_most_freq <- function(f, listw, weighted = TRUE) { | |
| } | |
| cols <- list(barren = NULL, non_tree_vegetation = NULL, tree = NULL) | |
| f <- rnorm(100) | |
| vctrs::new_data_frame( | |
| cols, | |
| n = length(f), | |
| class = "tbl" | |
| ) |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment