Grid Interpolation

[bransonf]

I think interpolating to grids is a frequent enough use case to warrant its own function. Below is a reprex of what I'm imagining.

# Helper Function to make grid from shape
# Requires that data is projected and that units are known

vars <- c("B02001_001E","B02001_003E")

test <- tidycensus::get_acs("tract", vars, output = "wide", state = "MO", county = 510, geometry = TRUE) %>%
  dplyr::transmute(black_pop = B02001_003E/B02001_001E,
            tid = row_number()) %>%
  sf::st_transform(102696)

make_grid <- function(.data){

  # find units of object
  units <- st_crs(.data, parameters = TRUE)$units_gdal

  # error if not projected
  if(units == "degree"){
    stop("Data must be projected to interpolate to grid squares")
  }

  cellsize <- switch (units,
    "Foot_US" = c(3280.84,3280.84), # Feet to Sq KM
    "Meter" = c(1000, 1000)
  ) # Will return NULL if no matches, need to implement more possible GDAL Units

  # make grid and clip to full boundary of data
  grid <- sf::st_make_grid(.data, cellsize, square = TRUE) %>%
    sf::st_intersection(sf::st_union(.data))

  # coerce to sf/df and add unique ID
  grid %<>% sf::st_sf() %>% dplyr::mutate(gid = dplyr::row_number())

  return(grid)
}

grid <- make_grid(test)
out <- areal::aw_interpolate(grid, "gid", test, "tid", weight = "sum", output = "sf", intensive = "black_pop")

Definitely needs refinement to implement, and the reason aw_interpolate is external to the function is because I could not get NSE to play nicely from within the function. Very neat too is that you can change from square to hexagons by setting square = FALSE

[chris-prener]

I think I'd prefer to keep these separate, but I'd be open to included some wrapped tessellation tools - pass in a county shape file and convert it to a grid or hexagons, and then the end user could pipe that into areal::aw_interpolate(). How would that be @bransonf ?

[bransonf]

In that case I'll make a PR in a few hours.

[chris-prener]

Sounds great @bransonf !