The waywiser from ropensci

Local functions don't make a ton of sense with NA values

Right now, data with NA values are handled incorrectly by local functions. Should think about what na_rm would actually mean in this context and consider replacing with na_action instead

ww_multi_scale.sf requires unquoted column names

waywiser::ww_multi_scale(
  waywiser::ny_trees,
  n_trees,
  agb,
  n = 10
)
#> # A tibble: 2 × 6
#>   .metric .estimator .estimate .grid_args       .grid          .notes          
#>   <chr>   <chr>          <dbl> <list>           <list>         <list>          
#> 1 rmse    standard      10105. <tibble [1 × 1]> <sf [100 × 5]> <tibble [0 × 2]>
#> 2 mae     standard       9154. <tibble [1 × 1]> <sf [100 × 5]> <tibble [0 × 2]>

waywiser::ww_multi_scale(
  waywiser::ny_trees,
  n_trees,
  "agb",
  n = 10
)
#> Warning: There were 55 warnings in `dplyr::summarise()`.
#> The first warning was:
#> ℹ In argument: `.estimate = rlang::exec(.env[["aggregation_function"]],
#>   "agb")`.
#> ℹ In group 1: `grid_cell_idx = 8`.
#> Caused by warning in `mean.default()`:
#> ! argument is not numeric or logical: returning NA
#> ℹ Run `dplyr::last_dplyr_warnings()` to see the 54 remaining warnings.
#> # A tibble: 2 × 6
#>   .metric .estimator .estimate .grid_args       .grid          .notes          
#>   <chr>   <chr>          <dbl> <list>           <list>         <list>          
#> 1 rmse    standard         NaN <tibble [1 × 1]> <sf [100 × 5]> <tibble [0 × 2]>
#> 2 mae     standard         NaN <tibble [1 × 1]> <sf [100 × 5]> <tibble [0 × 2]>

waywiser::ww_multi_scale(
  waywiser::ny_trees,
  "n_trees",
  agb,
  n = 10
)
#> Warning: There were 55 warnings in `dplyr::summarise()`.
#> The first warning was:
#> ℹ In argument: `.truth = rlang::exec(.env[["aggregation_function"]],
#>   "n_trees")`.
#> ℹ In group 1: `grid_cell_idx = 8`.
#> Caused by warning in `mean.default()`:
#> ! argument is not numeric or logical: returning NA
#> ℹ Run `dplyr::last_dplyr_warnings()` to see the 54 remaining warnings.
#> # A tibble: 2 × 6
#>   .metric .estimator .estimate .grid_args       .grid          .notes          
#>   <chr>   <chr>          <dbl> <list>           <list>         <list>          
#> 1 rmse    standard         NaN <tibble [1 × 1]> <sf [100 × 5]> <tibble [0 × 2]>
#> 2 mae     standard         NaN <tibble [1 × 1]> <sf [100 × 5]> <tibble [0 × 2]>

waywiser::ww_multi_scale(
  waywiser::ny_trees,
  "n_trees",
  "agb",
  n = 10
)
#> Warning: There were 110 warnings in `dplyr::summarise()`.
#> The first warning was:
#> ℹ In argument: `.truth = rlang::exec(.env[["aggregation_function"]],
#>   "n_trees")`.
#> ℹ In group 1: `grid_cell_idx = 8`.
#> Caused by warning in `mean.default()`:
#> ! argument is not numeric or logical: returning NA
#> ℹ Run `dplyr::last_dplyr_warnings()` to see the 109 remaining warnings.
#> # A tibble: 2 × 6
#>   .metric .estimator .estimate .grid_args       .grid          .notes          
#>   <chr>   <chr>          <dbl> <list>           <list>         <list>          
#> 1 rmse    standard         NaN <tibble [1 × 1]> <sf [100 × 5]> <tibble [0 × 2]>
#> 2 mae     standard         NaN <tibble [1 × 1]> <sf [100 × 5]> <tibble [0 × 2]>

^{Created on 2023-06-09 with reprex v2.0.2}

This really should work either way

Release waywiser 0.4.2

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Accepted 🎉
usethis::use_github_release()
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Upkeep for waywiser

Pre-history

usethis::use_readme_rmd()
usethis::use_roxygen_md()
usethis::use_github_links()
usethis::use_pkgdown_github_pages()
usethis::use_tidy_github_labels()
usethis::use_tidy_style()
usethis::use_tidy_description()
urlchecker::url_check()

2020

usethis::use_package_doc()
Consider letting usethis manage your @importFrom directives here.
usethis::use_import_from() is handy for this.
usethis::use_testthat(3) and upgrade to 3e, testthat 3e vignette
Align the names of R/ files and test/ files for workflow happiness.
The docs for usethis::use_r() include a helpful script.
usethis::rename_files() may be be useful.

2021

usethis::use_tidy_dependencies()
usethis::use_tidy_github_actions() and update artisanal actions to use setup-r-dependencies
Remove check environments section from cran-comments.md
Bump required R version in DESCRIPTION to 3.5
Use lifecycle instead of artisanal deprecation messages, as described in Communicate lifecycle changes in your functions
Make sure RStudio appears in Authors@R of DESCRIPTION like so, if appropriate:
person("RStudio", role = c("cph", "fnd"))

2022

usethis::use_tidy_coc()
Handle and close any still-open master --> main issues
Update README badges, instructions in r-lib/usethis#1594
Update errors to rlang 1.0.0. Helpful guides:
https://rlang.r-lib.org/reference/topic-error-call.html
https://rlang.r-lib.org/reference/topic-error-chaining.html
https://rlang.r-lib.org/reference/topic-condition-formatting.html
Update pkgdown site using instructions at https://tidytemplate.tidyverse.org
Ensure pkgdown development is mode: auto in pkgdown config
Re-publish released site; see How to update a released site
Update lifecycle badges with more accessible SVGs: usethis::use_lifecycle()

2023

Necessary:

Update copyright holder in DESCRIPTION: person(given = "Posit Software, PBC", role = c("cph", "fnd"))
Run devtools::document() to re-generate package-level help topic with DESCRIPTION changes
Double check license file uses '[package] authors' as copyright holder. Run use_mit_license()
Update logo (https://github.com/rstudio/hex-stickers); run use_tidy_logo()
usethis::use_tidy_coc()
Modernize citation files; see updated use_citation()
usethis::use_tidy_github_actions()

Optional:

Review 2022 checklist to see if you completed the pkgdown updates
Prefer pak::pak("org/pkg") over devtools::install_github("org/pkg") in README
Consider running use_tidy_dependencies() and/or replace compat files with use_standalone()
use_standalone("r-lib/rlang", "types-check") instead of home grown argument checkers
Add alt-text to pictures, plots, etc; see https://posit.co/blog/knitr-fig-alt/ for examples

ww_multi_scale() should give friendlier errors when arguments are missing

waywiser::ww_multi_scale(waywiser::ny_trees, n = 2)
#> Error in `data[[truth_var]]` at waywiser/R/multi_scale.R:383:2:
#> ! Can't extract column with `truth_var`.
#> ✖ Subscript `truth_var` must be size 1, not 0.
#> Backtrace:
#>      ▆
#>   1. ├─waywiser::ww_multi_scale(waywiser::ny_trees, n = 2)
#>   2. └─waywiser:::ww_multi_scale.sf(waywiser::ny_trees, n = 2) at waywiser/R/multi_scale.R:158:4
#>   3.   ├─data[[truth_var]] at waywiser/R/multi_scale.R:383:2
#>   4.   └─tibble:::`[[.tbl_df`(data, truth_var) at waywiser/R/multi_scale.R:383:2
#>   5.     └─tibble:::tbl_subset2(x, j = i, j_arg = substitute(i))
#>   6.       └─tibble:::vectbl_as_col_location2(...)
#>   7.         ├─tibble:::subclass_col_index_errors(...)
#>   8.         │ └─base::withCallingHandlers(...)
#>   9.         └─vctrs::vec_as_location2(j, n, names, call = call)
#>  10.           └─vctrs:::result_get(...)
#>  11.             └─rlang::cnd_signal(x$err)
waywiser::ww_multi_scale(waywiser::ny_trees, agb, n = 2)
#> Error in `data[[estimate_var]]` at waywiser/R/multi_scale.R:387:2:
#> ! Can't extract column with `estimate_var`.
#> ✖ Subscript `estimate_var` must be size 1, not 0.
#> Backtrace:
#>      ▆
#>   1. ├─waywiser::ww_multi_scale(waywiser::ny_trees, agb, n = 2)
#>   2. └─waywiser:::ww_multi_scale.sf(waywiser::ny_trees, agb, n = 2) at waywiser/R/multi_scale.R:158:4
#>   3.   ├─data[[estimate_var]] at waywiser/R/multi_scale.R:387:2
#>   4.   └─tibble:::`[[.tbl_df`(data, estimate_var) at waywiser/R/multi_scale.R:387:2
#>   5.     └─tibble:::tbl_subset2(x, j = i, j_arg = substitute(i))
#>   6.       └─tibble:::vectbl_as_col_location2(...)
#>   7.         ├─tibble:::subclass_col_index_errors(...)
#>   8.         │ └─base::withCallingHandlers(...)
#>   9.         └─vctrs::vec_as_location2(j, n, names, call = call)
#>  10.           └─vctrs:::result_get(...)
#>  11.             └─rlang::cnd_signal(x$err)

^{Created on 2023-06-14 with reprex v2.0.2}

Release waywiser 0.4.0

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Right now, most test objects are stored within large test_that() calls, which makes updating individual test objects a pain. Since most of the tests in this package are generated automatically anyway, it would be fantastic to break each element out into its own test_that() call so they might be more easily updated.

Release waywiser 0.5.1

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`ww_multi_scale()` should support multi-class AUC, PR AUC, etc

Because ww_multi_scale() only takes one estimate column, and passes ... to sf::st_make_grid(), there's currently no way to pass multiple columns of probability estimates to yardstick functions. This means we can't do multi-class class probability functions at the moment.

It would be nice for at least the sf method to support this. Not sure what the interface would look like, though, since dots are already in use. Maybe a probabilities argument that accepts a list?

ww_multi_scale returns an error for categorical rasters

Hi @mikemahoney218 -- I am trying to incorporate waywiser for examples in a paper about spatial patterns comparison. The ww_multi_scale() function works fine for continuous rasters (however, it gives some CRSs warnings), but errors for categorical ones. Is this expected?

library(terra)
library(waywiser)
library(landscapemetrics)
cell_sizes = seq(10, 100, 10) * 1000
l1 = rast(landscape)
l2 = l1
clc_multi_scale = ww_multi_scale(truth = l1, estimate = l2,
                                 metrics = list(yardstick::precision), 
                                 cellsize = cell_sizes)
#> Error in `metric_set()`:
#> ! Failed to compute `<clss_mtr>()`.
#> Caused by error:
#> ! Must select at least one item.
clc_multi_scale
#> Error in eval(expr, envir, enclos): object 'clc_multi_scale' not found

count columns for sf multi-scale are incorrect when column names are quoted

pts <- sf::st_sample(
  sf::st_as_sfc(
    sf::st_bbox(
      c(xmin = 1327326, ymin = 2175524, xmax = 1971106, ymax = 2651347),
      crs = 5072
    )
  ),
  500
)
  
pts <- sf::st_as_sf(pts)
pts$truth <- rnorm(500, 123, 35)
pts$estimate <- rnorm(500, 123, 39)

cellsizes <- units::set_units(seq(20, 100, 10), "km")

waywiser::ww_multi_scale(
  pts,
  truth,
  estimate,
  cellsize = cellsizes,
  square = FALSE,
  metrics = yardstick::rmse
)$.grid |> 
  lapply(\(x) unique(x$.truth_count))
#> [[1]]
#> [1] NA  1  2  3  4
#> 
#> [[2]]
#> [1] NA  1  2  3  4  5  7
#> 
#> [[3]]
#> [1] NA  1  2  3  4  5  6  7
#> 
#> [[4]]
#> [1] NA  2  1  4  3  6  5 10  7
#> 
#> [[5]]
#>  [1] NA  2  4  3  5  7  1  8  9  6 10
#> 
#> [[6]]
#>  [1] NA  1  2  5  3  8  7  6 10  4 12 13 11  9
#> 
#> [[7]]
#>  [1] NA  2  5  3  6 10 13  1  7  8 11  4 12  9 15
#> 
#> [[8]]
#>  [1] NA  1  2  7  4 12  9 15 13  5 10  6 14 11 16  8 18 17
#> 
#> [[9]]
#>  [1] NA  1  2  8  5 15 11  7 16 20  9 10 13 18 12 19  4 24 14 17

waywiser::ww_multi_scale(
  pts,
  "truth",
  "estimate",
  cellsize = cellsizes,
  square = FALSE,
  metrics = yardstick::rmse
)$.grid |> 
  lapply(\(x) unique(x$.truth_count))
#> [[1]]
#> [1] NA  1
#> 
#> [[2]]
#> [1] NA  1
#> 
#> [[3]]
#> [1] NA  1
#> 
#> [[4]]
#> [1] NA  1
#> 
#> [[5]]
#> [1] NA  1
#> 
#> [[6]]
#> [1] NA  1
#> 
#> [[7]]
#> [1] NA  1
#> 
#> [[8]]
#> [1] NA  1
#> 
#> [[9]]
#> [1] NA  1

^{Created on 2023-10-15 with reprex v2.0.2}

Release waywiser 0.5.0

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Release waywiser 0.3.0

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Consider adding `.by` to `ww_multi_scale()`

dplyr functions (including summarise() and mutate(), among others) now have an argument, .by, which allows for per-operation grouping, removing the need for group_by() in simple pipelines. It'd be nice for ww_multi_scale() to support the same (for the sf method; raster methods don't support grouping, and probably never will), such that these calls were equivalent:

ww_multi_scale(
      dplyr::group_by(ames_sf, Neighborhood),
      Sale_Price,
      predictions,
      n = list(
        c(10, 10),
        c(1, 1)
      ),
      square = FALSE
    )

ww_multi_scale(
      ames_sf,
      Sale_Price,
      predictions,
      n = list(
        c(10, 10),
        c(1, 1)
      ),
      square = FALSE,
    .by = Neighborhood
    )

For what it's worth, note that dplyr errors when trying to mix group_by() and .by:

> dplyr::group_by(iris, Species) |> dplyr::summarise(m = mean(Sepal.Length), .by = Species)
Error in `dplyr::summarise()`:
! Can't supply `.by` when `.data` is a grouped data frame.
Run `rlang::last_trace()` to see where the error occurred.

Release waywiser 0.4.1

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Release waywiser 0.6.0

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Release waywiser 0.2.0

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Release waywiser 0.5.2

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Accepted 🎉
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Rewrite README

This package is now much bigger than it was last version, which is great, but the docs don't match. Should update the docs.

Release waywiser 0.1.0

First release:

usethis::use_cran_comments()
Update (aspirational) install instructions in README
Proofread Title: and Description:
Check that all exported functions have @return and @examples
Check that Authors@R: includes a copyright holder (role 'cph')
Check licensing of included files
Review https://github.com/DavisVaughan/extrachecks

Prepare for release:

git pull
Check if any deprecation processes should be advanced, as described in Gradual deprecation
devtools::build_readme()
urlchecker::url_check()
devtools::check(remote = TRUE, manual = TRUE)
devtools::check_win_devel()
rhub::check_for_cran()
git push
Draft blog post

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