revdep/checks.noindex/waywiser/old/waywiser.Rcheck/tests/testthat/_snaps/srr-ww_global_geary_pvalue.md

In AFIT-R/vip: Variable Importance Plots

srr: expected failures for ww_global_geary_pvalue

Code
  ww_global_geary_pvalue_vec(worldclim_predicted$response, tail(
    worldclim_predicted$predicted, -1), worldclim_weights)
Condition
  Error in `yardstick_vec()`:
  ! Length of `truth` (10000) and `estimate` (9999) must match.

Code
  ww_global_geary_pvalue_vec(tail(worldclim_predicted$response, -1),
  worldclim_predicted$predicted, worldclim_weights)
Condition
  Error in `yardstick_vec()`:
  ! Length of `truth` (9999) and `estimate` (10000) must match.

Code
  ww_global_geary_pvalue(worldclim_predicted, predicted, response)
Condition
  Error in `ww_global_geary_pvalue()`:
  ! `truth` must be numeric.

Code
  ww_global_geary_pvalue(worldclim_predicted, response, predicted)
Condition
  Error in `ww_global_geary_pvalue()`:
  ! `estimate` must be numeric.

Code
  ww_global_geary_pvalue_vec(worldclim_predicted$response, worldclim_predicted$
    predicted, worldclim_weights)
Condition
  Error in `yardstick_vec()`:
  ! `estimate` must be numeric.

Code
  ww_global_geary_pvalue_vec(worldclim_predicted$predicted, worldclim_predicted$
    response, worldclim_weights)
Condition
  Error in `yardstick_vec()`:
  ! `truth` must be numeric.

Code
  ww_global_geary_pvalue(worldclim_predicted, response, predicted)
Condition
  Error in `ww_global_geary_pvalue()`:
  ! `estimate` must be numeric.

Code
  ww_global_geary_pvalue(worldclim_predicted, predicted, response)
Condition
  Error in `ww_global_geary_pvalue()`:
  ! `truth` must be numeric.

Code
  ww_global_geary_pvalue(worldclim_predicted, predicted, response)$.estimate
Condition
  Error in `spatial_yardstick_df()`:
  ! Missing values in data.
  i waywiser can't handle missing data for functions that use spatial weights.

Code
  ww_global_geary_pvalue(worldclim_predicted, response, predicted)$.estimate
Condition
  Error in `spatial_yardstick_df()`:
  ! Missing values in data.
  i waywiser can't handle missing data for functions that use spatial weights.

Code
  ww_global_geary_pvalue_vec(worldclim_predicted$predicted, worldclim_predicted$
    response, worldclim_weights)
Condition
  Error in `spatial_yardstick_vec()`:
  ! Missing values in data.
  i waywiser can't handle missing data for functions that use spatial weights.

Code
  ww_global_geary_pvalue_vec(worldclim_predicted$response, worldclim_predicted$
    predicted, worldclim_weights)
Condition
  Error in `spatial_yardstick_vec()`:
  ! Missing values in data.
  i waywiser can't handle missing data for functions that use spatial weights.

Code
  ww_global_geary_pvalue_vec(numeric(), numeric(), structure(list(), class = "listw"))
Condition
  Error in `yardstick_vec()`:
  ! 0 non-missing values were passed to `truth`.

Code
  ww_global_geary_pvalue(head(worldclim_predicted, 0), response, predicted,
  structure(list(), class = "listw"))
Condition
  Error in `ww_global_geary_pvalue()`:
  ! 0 non-missing values were passed to `truth`.

Code
  ww_global_geary_pvalue(head(worldclim_predicted, 0), predicted, response,
  structure(list(), class = "listw"))
Condition
  Error in `ww_global_geary_pvalue()`:
  ! 0 non-missing values were passed to `truth`.

Code
  ww_global_geary_pvalue_vec(NA_real_, NA_real_, structure(list(neighbours = 1),
  class = "listw"))
Condition
  Error in `spatial_yardstick_vec()`:
  ! Missing values in data.
  i waywiser can't handle missing data for functions that use spatial weights.

Code
  ww_global_geary_pvalue(worldclim_predicted, response, predicted)$.estimate
Condition
  Error in `spatial_yardstick_df()`:
  ! Missing values in data.
  i waywiser can't handle missing data for functions that use spatial weights.

Code
  ww_global_geary_pvalue(worldclim_predicted, predicted, response)$.estimate
Condition
  Error in `spatial_yardstick_df()`:
  ! Missing values in data.
  i waywiser can't handle missing data for functions that use spatial weights.

Code
  ww_global_geary_pvalue_vec(worldclim_simulation$response, worldclim_simulation$
    response, worldclim_weights)
Output
  [1] NA

Code
  ww_global_geary_pvalue(worldclim_simulation, response, response)
Output
  # A tibble: 1 x 3
    .metric             .estimator .estimate
    <chr>               <chr>          <dbl>
  1 global_geary_pvalue standard          NA

other generic srr standards

Code
  withr::with_seed(123, ww_global_geary_pvalue(worldclim_loaded, bio13, bio19))
Output
  # A tibble: 1 x 3
    .metric             .estimator .estimate
    <chr>               <chr>          <dbl>
  1 global_geary_pvalue standard           0

Code
  withr::with_seed(123, ww_global_geary_pvalue(worldclim_loaded, bio13, bio19))
Output
  # A tibble: 1 x 3
    .metric             .estimator .estimate
    <chr>               <chr>          <dbl>
  1 global_geary_pvalue standard           0

Code
  withr::with_seed(123, ww_global_geary_pvalue_vec(worldclim_loaded$bio13,
  worldclim_loaded$bio19, worldclim_weights))
Output
  [1] 0

Code
  withr::with_seed(123, ww_global_geary_pvalue_vec(worldclim_loaded$bio13,
  worldclim_loaded$bio19, worldclim_weights))
Output
  [1] 0

Code
  withr::with_seed(123, ww_global_geary_pvalue(worldclim_loaded, bio13, bio19))
Output
  # A tibble: 1 x 3
    .metric             .estimator .estimate
    <chr>               <chr>          <dbl>
  1 global_geary_pvalue standard           0

Code
  withr::with_seed(123, ww_global_geary_pvalue(worldclim_loaded, bio13, bio19,
    function(data) ww_build_weights(ww_make_point_neighbors(data, k = 5))))
Output
  # A tibble: 1 x 3
    .metric             .estimator .estimate
    <chr>               <chr>          <dbl>
  1 global_geary_pvalue standard           0

Code
  withr::with_seed(123, ww_global_geary_pvalue_vec(worldclim_loaded$bio13,
  worldclim_loaded$bio19, other_weights))
Output
  [1] 0

Code
  withr::with_seed(123, ww_global_geary_pvalue_vec(worldclim_loaded$bio13,
  worldclim_loaded$bio19, other_weights))
Output
  [1] 0

AFIT-R/vip documentation built on Aug. 22, 2023, 8:59 a.m.