inst/doc/multi-scale-assessment.R

In waywiser: Ergonomic Methods for Assessing Spatial Models

## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval = rlang::is_installed("ggplot2") && rlang::is_installed("tigris") && !(!interactive() && !isTRUE(as.logical(Sys.getenv("NOT_CRAN", "false"))))
)

## ----setup, include=FALSE-----------------------------------------------------
# ggplot2::theme_set(ggplot2::theme_minimal())

## -----------------------------------------------------------------------------
# library(sf)
# library(tidyr)
# library(dplyr)
# library(waywiser)
# invisible(
#   sf_proj_search_paths(
#     file.path(tools::R_user_dir("waywiser", "data"))
#   )
# )
# invisible(sf_proj_network(TRUE))

## -----------------------------------------------------------------------------
# library(ggplot2)
# 
# ny_trees %>%
#   ggplot() +
#   geom_sf(aes(color = agb), alpha = 0.4) +
#   scale_color_distiller(palette = "Greens", direction = 1)

## -----------------------------------------------------------------------------
# agb_lm <- lm(agb ~ n_trees, ny_trees)
# ny_trees$predicted <- predict(agb_lm, ny_trees)

## -----------------------------------------------------------------------------
# cell_sizes <- seq(10, 100, 10) * 1000
# ny_multi_scale <- ww_multi_scale(
#   ny_trees,
#   agb,
#   predicted,
#   cellsize = cell_sizes
# )
# 
# ny_multi_scale

## -----------------------------------------------------------------------------
# ny_multi_scale %>%
#   unnest(.grid_args) %>%
#   ggplot(aes(x = cellsize, y = .estimate, color = .metric)) +
#   geom_line()

## -----------------------------------------------------------------------------
# ny_multi_scale$.grid[[9]] %>%
#   filter(!is.na(.estimate)) %>%
#   ggplot(aes(fill = .estimate)) +
#   geom_sf() +
#   scale_fill_distiller(palette = "Greens", direction = 1)

## ----message=FALSE, results='hide', warning=FALSE, eval=FALSE-----------------
# suppressPackageStartupMessages(library(tigris))
# 
# ny_block_groups <- block_groups("NY")
# ny_county_subdivisions <- county_subdivisions("NY")
# ny_counties <- counties("NY")
# 
# ny_division_assessment <- ww_multi_scale(
#   ny_trees,
#   agb,
#   predicted,
#   grids = list(
#     ny_block_groups,
#     ny_county_subdivisions,
#     ny_counties
#   )
# )
# 
# ny_division_assessment %>%
#   mutate(
#     division = rep(c("Block group", "County subdivision", "County"), each = 2)
#   ) %>%
#   ggplot(aes(x = division, y = .estimate, fill = .metric)) +
#   geom_col(position = position_dodge())