Last updated on 2025-12-05 09:50:00 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.3.1 | 2.61 | 149.85 | 152.46 | OK | |
| r-devel-linux-x86_64-debian-gcc | 0.3.1 | 1.92 | 101.23 | 103.15 | OK | |
| r-devel-linux-x86_64-fedora-clang | 0.4.0 | 12.00 | 240.30 | 252.30 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 0.4.0 | 30.00 | 270.10 | 300.10 | ERROR | |
| r-devel-windows-x86_64 | 0.3.1 | 5.00 | 166.00 | 171.00 | OK | |
| r-patched-linux-x86_64 | 0.3.1 | 2.21 | 144.91 | 147.12 | OK | |
| r-release-linux-x86_64 | 0.3.1 | 2.39 | 146.91 | 149.30 | OK | |
| r-release-macos-arm64 | 0.4.0 | 1.00 | 51.00 | 52.00 | ERROR | |
| r-release-macos-x86_64 | 0.4.0 | 4.00 | 217.00 | 221.00 | ERROR | |
| r-release-windows-x86_64 | 0.3.1 | 5.00 | 166.00 | 171.00 | OK | |
| r-oldrel-macos-arm64 | 0.4.0 | 1.00 | 56.00 | 57.00 | ERROR | |
| r-oldrel-macos-x86_64 | 0.4.0 | 4.00 | 221.00 | 225.00 | ERROR | |
| r-oldrel-windows-x86_64 | 0.4.0 | 9.00 | 246.00 | 255.00 | OK |
Version: 0.4.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [194s/351s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(orbital)
>
> test_check("orbital")
Loading required package: parsnip
Saving _problems/test-model-xgboost-17.R
Saving _problems/test-model-xgboost-18.R
Saving _problems/test-model-xgboost-23.R
Saving _problems/test-model-xgboost-35.R
Saving _problems/test-model-xgboost-65.R
Saving _problems/test-model-xgboost-66.R
Saving _problems/test-model-xgboost-67.R
Saving _problems/test-model-xgboost-78.R
Saving _problems/test-model-xgboost-90.R
Saving _problems/test-model-xgboost-131.R
Saving _problems/test-model-xgboost-132.R
Saving _problems/test-model-xgboost-133.R
Saving _problems/test-model-xgboost-134.R
Saving _problems/test-model-xgboost-146.R
Saving _problems/test-model-xgboost-158.R
[ FAIL 15 | WARN 2 | SKIP 113 | PASS 370 ]
══ Skipped tests (113) ═════════════════════════════════════════════════════════
• On CRAN (69): 'test-adjust_equivocal_zone.R:36:1',
'test-adjust_equivocal_zone.R:155:3', 'test-adjust_numeric_range.R:123:3',
'test-adjust_predictions_custom.R:98:3',
'test-adjust_probability_threshold.R:34:1',
'test-adjust_probability_threshold.R:148:3', 'test-augment.R:41:3',
'test-dt.R:1:1', 'test-orbital.R:62:1', 'test-orbital.R:93:1',
'test-orbital.R:117:1', 'test-orbital.R:127:1', 'test-orbital.R:134:1',
'test-parsnip.R:1:1', 'test-parsnip.R:48:1', 'test-parsnip.R:63:1',
'test-recipes.R:1:1', 'test-show_query.R:7:3', 'test-sql.R:1:1',
'test-step_adasyn.R:20:1', 'test-step_adasyn.R:83:3',
'test-step_adasyn.R:111:3', 'test-step_bin2factor.R:79:3',
'test-step_boxcox.R:77:3', 'test-step_bsmote.R:20:1',
'test-step_bsmote.R:83:3', 'test-step_center.R:77:3',
'test-step_discretize.R:128:3', 'test-step_downsample.R:20:1',
'test-step_downsample.R:83:3', 'test-step_dummy.R:108:3',
'test-step_impute_mean.R:80:3', 'test-step_impute_median.R:81:3',
'test-step_impute_mode.R:93:3', 'test-step_indicate_na.R:83:3',
'test-step_intercept.R:67:3', 'test-step_inverse.R:94:3',
'test-step_lag.R:63:3', 'test-step_lencode_bayes.R:101:3',
'test-step_lencode_glm.R:96:3', 'test-step_lencode_mixed.R:104:3',
'test-step_log.R:94:3', 'test-step_mutate.R:77:3',
'test-step_nearmiss.R:20:1', 'test-step_nearmiss.R:83:3',
'test-step_normalize.R:77:3', 'test-step_novel.R:99:3',
'test-step_other.R:101:3', 'test-step_pca.R:152:3',
'test-step_pca_sparse.R:133:3', 'test-step_pca_sparse_bayes.R:118:3',
'test-step_pca_truncated.R:111:3', 'test-step_range.R:94:3',
'test-step_ratio.R:88:3', 'test-step_rename.R:77:3', 'test-step_rose.R:20:1',
'test-step_rose.R:83:3', 'test-step_scale.R:77:3', 'test-step_smote.R:20:1',
'test-step_smote.R:83:3', 'test-step_smotenc.R:20:1',
'test-step_smotenc.R:83:3', 'test-step_sqrt.R:77:3',
'test-step_tomek.R:20:1', 'test-step_tomek.R:83:3',
'test-step_unknown.R:97:3', 'test-step_upsample.R:20:1',
'test-step_upsample.R:83:3', 'test-workflows.R:1:1'
• empty test (2): 'test-augment.R:31:1', 'test-augment.R:111:1'
• is.na(testthat_spark_env_version()) is TRUE (42):
'test-adjust_equivocal_zone.R:113:3', 'test-adjust_numeric_range.R:96:3',
'test-adjust_predictions_custom.R:68:3',
'test-adjust_probability_threshold.R:109:3', 'test-step_adasyn.R:57:3',
'test-step_bin2factor.R:56:3', 'test-step_boxcox.R:54:3',
'test-step_bsmote.R:57:3', 'test-step_center.R:54:3',
'test-step_discretize.R:102:3', 'test-step_downsample.R:57:3',
'test-step_dummy.R:82:3', 'test-step_impute_mean.R:56:3',
'test-step_impute_median.R:57:3', 'test-step_impute_mode.R:63:3',
'test-step_indicate_na.R:59:3', 'test-step_intercept.R:44:3',
'test-step_inverse.R:71:3', 'test-step_lencode_bayes.R:73:3',
'test-step_lencode_glm.R:69:3', 'test-step_lencode_mixed.R:75:3',
'test-step_log.R:71:3', 'test-step_mutate.R:54:3',
'test-step_nearmiss.R:57:3', 'test-step_normalize.R:54:3',
'test-step_novel.R:71:3', 'test-step_other.R:73:3', 'test-step_pca.R:128:3',
'test-step_pca_sparse.R:106:3', 'test-step_pca_sparse_bayes.R:90:3',
'test-step_pca_truncated.R:84:3', 'test-step_range.R:71:3',
'test-step_ratio.R:62:3', 'test-step_rename.R:54:3', 'test-step_rose.R:57:3',
'test-step_scale.R:54:3', 'test-step_smote.R:57:3',
'test-step_smotenc.R:57:3', 'test-step_sqrt.R:54:3',
'test-step_tomek.R:57:3', 'test-step_unknown.R:67:3',
'test-step_upsample.R:57:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Failure ('test-model-xgboost.R:17:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds` to have names ".pred_class".
Differences:
`actual`:
`expected`: ".pred_class"
── Failure ('test-model-xgboost.R:18:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds$.pred_class` to have type "character".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:20:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds$.pred_class` to be identical to `as.character(exps$.pred_class)`.
Differences:
`actual` is NULL
`expected` is a character vector ('0', '0', '1', '1', '0', ...)
── Error ('test-model-xgboost.R:35:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = "class") at test-model-xgboost.R:35:3
2. └─orbital:::orbital.model_fit(bt_fit, type = "class")
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
── Failure ('test-model-xgboost.R:65:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds` to have names `c(".pred_0", ".pred_1")`.
Differences:
`actual`:
`expected`: ".pred_0" ".pred_1"
── Failure ('test-model-xgboost.R:66:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds$.pred_0` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:67:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds$.pred_1` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:74:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds` to equal `exps`.
Differences:
`actual` is length 0
`expected` is length 2
`names(actual)`:
`names(expected)`: ".pred_0" ".pred_1"
`actual$.pred_0` is absent
`expected$.pred_0` is a double vector (0.536467909812927, 0.536467909812927, 0.100352562963963, 0.209237098693848, 0.94028639793396, ...)
`actual$.pred_1` is absent
`expected$.pred_1` is a double vector (0.463532090187073, 0.463532090187073, 0.899647437036037, 0.790762901306152, 0.05971360206604, ...)
── Error ('test-model-xgboost.R:90:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = "prob") at test-model-xgboost.R:90:3
2. └─orbital:::orbital.model_fit(bt_fit, type = "prob")
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
── Failure ('test-model-xgboost.R:131:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds` to have names `c(".pred_class", ".pred_0", ".pred_1")`.
Differences:
`actual`:
`expected`: ".pred_class" ".pred_0" ".pred_1"
── Failure ('test-model-xgboost.R:132:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_class` to have type "character".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:133:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_0` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:134:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_1` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:142:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds` to equal `exps`.
Differences:
`actual` is length 0
`expected` is length 3
`names(actual)`:
`names(expected)`: ".pred_class" ".pred_0" ".pred_1"
`actual$.pred_class` is absent
`expected$.pred_class` is a character vector ('0', '0', '1', '1', '0', ...)
`actual$.pred_0` is absent
`expected$.pred_0` is a double vector (0.536467909812927, 0.536467909812927, 0.100352562963963, 0.209237098693848, 0.94028639793396, ...)
`actual$.pred_1` is absent
`expected$.pred_1` is a double vector (0.463532090187073, 0.463532090187073, 0.899647437036037, 0.790762901306152, 0.05971360206604, ...)
── Error ('test-model-xgboost.R:158:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = c("class", "prob")) at test-model-xgboost.R:158:3
2. └─orbital:::orbital.model_fit(bt_fit, type = c("class", "prob"))
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
[ FAIL 15 | WARN 2 | SKIP 113 | PASS 370 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.4.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [26s/28s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(orbital)
>
> test_check("orbital")
Loading required package: parsnip
Saving _problems/test-model-xgboost-17.R
Saving _problems/test-model-xgboost-18.R
Saving _problems/test-model-xgboost-23.R
Saving _problems/test-model-xgboost-35.R
Saving _problems/test-model-xgboost-65.R
Saving _problems/test-model-xgboost-66.R
Saving _problems/test-model-xgboost-67.R
Saving _problems/test-model-xgboost-78.R
Saving _problems/test-model-xgboost-90.R
Saving _problems/test-model-xgboost-131.R
Saving _problems/test-model-xgboost-132.R
Saving _problems/test-model-xgboost-133.R
Saving _problems/test-model-xgboost-134.R
Saving _problems/test-model-xgboost-146.R
Saving _problems/test-model-xgboost-158.R
[ FAIL 15 | WARN 2 | SKIP 113 | PASS 370 ]
══ Skipped tests (113) ═════════════════════════════════════════════════════════
• On CRAN (69): 'test-adjust_equivocal_zone.R:36:1',
'test-adjust_equivocal_zone.R:155:3', 'test-adjust_numeric_range.R:123:3',
'test-adjust_predictions_custom.R:98:3',
'test-adjust_probability_threshold.R:34:1',
'test-adjust_probability_threshold.R:148:3', 'test-augment.R:41:3',
'test-dt.R:1:1', 'test-orbital.R:62:1', 'test-orbital.R:93:1',
'test-orbital.R:117:1', 'test-orbital.R:127:1', 'test-orbital.R:134:1',
'test-parsnip.R:1:1', 'test-parsnip.R:48:1', 'test-parsnip.R:63:1',
'test-recipes.R:1:1', 'test-show_query.R:7:3', 'test-sql.R:1:1',
'test-step_adasyn.R:20:1', 'test-step_adasyn.R:83:3',
'test-step_adasyn.R:111:3', 'test-step_bin2factor.R:79:3',
'test-step_boxcox.R:77:3', 'test-step_bsmote.R:20:1',
'test-step_bsmote.R:83:3', 'test-step_center.R:77:3',
'test-step_discretize.R:128:3', 'test-step_downsample.R:20:1',
'test-step_downsample.R:83:3', 'test-step_dummy.R:108:3',
'test-step_impute_mean.R:80:3', 'test-step_impute_median.R:81:3',
'test-step_impute_mode.R:93:3', 'test-step_indicate_na.R:83:3',
'test-step_intercept.R:67:3', 'test-step_inverse.R:94:3',
'test-step_lag.R:63:3', 'test-step_lencode_bayes.R:101:3',
'test-step_lencode_glm.R:96:3', 'test-step_lencode_mixed.R:104:3',
'test-step_log.R:94:3', 'test-step_mutate.R:77:3',
'test-step_nearmiss.R:20:1', 'test-step_nearmiss.R:83:3',
'test-step_normalize.R:77:3', 'test-step_novel.R:99:3',
'test-step_other.R:101:3', 'test-step_pca.R:152:3',
'test-step_pca_sparse.R:133:3', 'test-step_pca_sparse_bayes.R:118:3',
'test-step_pca_truncated.R:111:3', 'test-step_range.R:94:3',
'test-step_ratio.R:88:3', 'test-step_rename.R:77:3', 'test-step_rose.R:20:1',
'test-step_rose.R:83:3', 'test-step_scale.R:77:3', 'test-step_smote.R:20:1',
'test-step_smote.R:83:3', 'test-step_smotenc.R:20:1',
'test-step_smotenc.R:83:3', 'test-step_sqrt.R:77:3',
'test-step_tomek.R:20:1', 'test-step_tomek.R:83:3',
'test-step_unknown.R:97:3', 'test-step_upsample.R:20:1',
'test-step_upsample.R:83:3', 'test-workflows.R:1:1'
• empty test (2): 'test-augment.R:31:1', 'test-augment.R:111:1'
• is.na(testthat_spark_env_version()) is TRUE (42):
'test-adjust_equivocal_zone.R:113:3', 'test-adjust_numeric_range.R:96:3',
'test-adjust_predictions_custom.R:68:3',
'test-adjust_probability_threshold.R:109:3', 'test-step_adasyn.R:57:3',
'test-step_bin2factor.R:56:3', 'test-step_boxcox.R:54:3',
'test-step_bsmote.R:57:3', 'test-step_center.R:54:3',
'test-step_discretize.R:102:3', 'test-step_downsample.R:57:3',
'test-step_dummy.R:82:3', 'test-step_impute_mean.R:56:3',
'test-step_impute_median.R:57:3', 'test-step_impute_mode.R:63:3',
'test-step_indicate_na.R:59:3', 'test-step_intercept.R:44:3',
'test-step_inverse.R:71:3', 'test-step_lencode_bayes.R:73:3',
'test-step_lencode_glm.R:69:3', 'test-step_lencode_mixed.R:75:3',
'test-step_log.R:71:3', 'test-step_mutate.R:54:3',
'test-step_nearmiss.R:57:3', 'test-step_normalize.R:54:3',
'test-step_novel.R:71:3', 'test-step_other.R:73:3', 'test-step_pca.R:128:3',
'test-step_pca_sparse.R:106:3', 'test-step_pca_sparse_bayes.R:90:3',
'test-step_pca_truncated.R:84:3', 'test-step_range.R:71:3',
'test-step_ratio.R:62:3', 'test-step_rename.R:54:3', 'test-step_rose.R:57:3',
'test-step_scale.R:54:3', 'test-step_smote.R:57:3',
'test-step_smotenc.R:57:3', 'test-step_sqrt.R:54:3',
'test-step_tomek.R:57:3', 'test-step_unknown.R:67:3',
'test-step_upsample.R:57:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Failure ('test-model-xgboost.R:17:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds` to have names ".pred_class".
Differences:
`actual`:
`expected`: ".pred_class"
── Failure ('test-model-xgboost.R:18:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds$.pred_class` to have type "character".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:20:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds$.pred_class` to be identical to `as.character(exps$.pred_class)`.
Differences:
`actual` is NULL
`expected` is a character vector ('0', '0', '1', '1', '0', ...)
── Error ('test-model-xgboost.R:35:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = "class") at test-model-xgboost.R:35:3
2. └─orbital:::orbital.model_fit(bt_fit, type = "class")
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
── Failure ('test-model-xgboost.R:65:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds` to have names `c(".pred_0", ".pred_1")`.
Differences:
`actual`:
`expected`: ".pred_0" ".pred_1"
── Failure ('test-model-xgboost.R:66:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds$.pred_0` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:67:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds$.pred_1` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:74:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds` to equal `exps`.
Differences:
`actual` is length 0
`expected` is length 2
`names(actual)`:
`names(expected)`: ".pred_0" ".pred_1"
`actual$.pred_0` is absent
`expected$.pred_0` is a double vector (0.536467909812927, 0.536467909812927, 0.100352562963963, 0.209237098693848, 0.94028639793396, ...)
`actual$.pred_1` is absent
`expected$.pred_1` is a double vector (0.463532090187073, 0.463532090187073, 0.899647437036037, 0.790762901306152, 0.05971360206604, ...)
── Error ('test-model-xgboost.R:90:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = "prob") at test-model-xgboost.R:90:3
2. └─orbital:::orbital.model_fit(bt_fit, type = "prob")
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
── Failure ('test-model-xgboost.R:131:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds` to have names `c(".pred_class", ".pred_0", ".pred_1")`.
Differences:
`actual`:
`expected`: ".pred_class" ".pred_0" ".pred_1"
── Failure ('test-model-xgboost.R:132:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_class` to have type "character".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:133:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_0` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:134:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_1` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:142:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds` to equal `exps`.
Differences:
`actual` is length 0
`expected` is length 3
`names(actual)`:
`names(expected)`: ".pred_class" ".pred_0" ".pred_1"
`actual$.pred_class` is absent
`expected$.pred_class` is a character vector ('0', '0', '1', '1', '0', ...)
`actual$.pred_0` is absent
`expected$.pred_0` is a double vector (0.536467909812927, 0.536467909812927, 0.100352562963963, 0.209237098693848, 0.94028639793396, ...)
`actual$.pred_1` is absent
`expected$.pred_1` is a double vector (0.463532090187073, 0.463532090187073, 0.899647437036037, 0.790762901306152, 0.05971360206604, ...)
── Error ('test-model-xgboost.R:158:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = c("class", "prob")) at test-model-xgboost.R:158:3
2. └─orbital:::orbital.model_fit(bt_fit, type = c("class", "prob"))
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
[ FAIL 15 | WARN 2 | SKIP 113 | PASS 370 ]
Error:
! Test failures.
Execution halted
Flavor: r-release-macos-arm64
Version: 0.4.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [84s/138s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(orbital)
>
> test_check("orbital")
Loading required package: parsnip
Saving _problems/test-model-xgboost-17.R
Saving _problems/test-model-xgboost-18.R
Saving _problems/test-model-xgboost-23.R
Saving _problems/test-model-xgboost-35.R
Saving _problems/test-model-xgboost-65.R
Saving _problems/test-model-xgboost-66.R
Saving _problems/test-model-xgboost-67.R
Saving _problems/test-model-xgboost-78.R
Saving _problems/test-model-xgboost-90.R
Saving _problems/test-model-xgboost-131.R
Saving _problems/test-model-xgboost-132.R
Saving _problems/test-model-xgboost-133.R
Saving _problems/test-model-xgboost-134.R
Saving _problems/test-model-xgboost-146.R
Saving _problems/test-model-xgboost-158.R
[ FAIL 15 | WARN 2 | SKIP 113 | PASS 370 ]
══ Skipped tests (113) ═════════════════════════════════════════════════════════
• On CRAN (69): 'test-adjust_equivocal_zone.R:36:1',
'test-adjust_equivocal_zone.R:155:3', 'test-adjust_numeric_range.R:123:3',
'test-adjust_predictions_custom.R:98:3',
'test-adjust_probability_threshold.R:34:1',
'test-adjust_probability_threshold.R:148:3', 'test-augment.R:41:3',
'test-dt.R:1:1', 'test-orbital.R:62:1', 'test-orbital.R:93:1',
'test-orbital.R:117:1', 'test-orbital.R:127:1', 'test-orbital.R:134:1',
'test-parsnip.R:1:1', 'test-parsnip.R:48:1', 'test-parsnip.R:63:1',
'test-recipes.R:1:1', 'test-show_query.R:7:3', 'test-sql.R:1:1',
'test-step_adasyn.R:20:1', 'test-step_adasyn.R:83:3',
'test-step_adasyn.R:111:3', 'test-step_bin2factor.R:79:3',
'test-step_boxcox.R:77:3', 'test-step_bsmote.R:20:1',
'test-step_bsmote.R:83:3', 'test-step_center.R:77:3',
'test-step_discretize.R:128:3', 'test-step_downsample.R:20:1',
'test-step_downsample.R:83:3', 'test-step_dummy.R:108:3',
'test-step_impute_mean.R:80:3', 'test-step_impute_median.R:81:3',
'test-step_impute_mode.R:93:3', 'test-step_indicate_na.R:83:3',
'test-step_intercept.R:67:3', 'test-step_inverse.R:94:3',
'test-step_lag.R:63:3', 'test-step_lencode_bayes.R:101:3',
'test-step_lencode_glm.R:96:3', 'test-step_lencode_mixed.R:104:3',
'test-step_log.R:94:3', 'test-step_mutate.R:77:3',
'test-step_nearmiss.R:20:1', 'test-step_nearmiss.R:83:3',
'test-step_normalize.R:77:3', 'test-step_novel.R:99:3',
'test-step_other.R:101:3', 'test-step_pca.R:152:3',
'test-step_pca_sparse.R:133:3', 'test-step_pca_sparse_bayes.R:118:3',
'test-step_pca_truncated.R:111:3', 'test-step_range.R:94:3',
'test-step_ratio.R:88:3', 'test-step_rename.R:77:3', 'test-step_rose.R:20:1',
'test-step_rose.R:83:3', 'test-step_scale.R:77:3', 'test-step_smote.R:20:1',
'test-step_smote.R:83:3', 'test-step_smotenc.R:20:1',
'test-step_smotenc.R:83:3', 'test-step_sqrt.R:77:3',
'test-step_tomek.R:20:1', 'test-step_tomek.R:83:3',
'test-step_unknown.R:97:3', 'test-step_upsample.R:20:1',
'test-step_upsample.R:83:3', 'test-workflows.R:1:1'
• empty test (2): 'test-augment.R:31:1', 'test-augment.R:111:1'
• is.na(testthat_spark_env_version()) is TRUE (42):
'test-adjust_equivocal_zone.R:113:3', 'test-adjust_numeric_range.R:96:3',
'test-adjust_predictions_custom.R:68:3',
'test-adjust_probability_threshold.R:109:3', 'test-step_adasyn.R:57:3',
'test-step_bin2factor.R:56:3', 'test-step_boxcox.R:54:3',
'test-step_bsmote.R:57:3', 'test-step_center.R:54:3',
'test-step_discretize.R:102:3', 'test-step_downsample.R:57:3',
'test-step_dummy.R:82:3', 'test-step_impute_mean.R:56:3',
'test-step_impute_median.R:57:3', 'test-step_impute_mode.R:63:3',
'test-step_indicate_na.R:59:3', 'test-step_intercept.R:44:3',
'test-step_inverse.R:71:3', 'test-step_lencode_bayes.R:73:3',
'test-step_lencode_glm.R:69:3', 'test-step_lencode_mixed.R:75:3',
'test-step_log.R:71:3', 'test-step_mutate.R:54:3',
'test-step_nearmiss.R:57:3', 'test-step_normalize.R:54:3',
'test-step_novel.R:71:3', 'test-step_other.R:73:3', 'test-step_pca.R:128:3',
'test-step_pca_sparse.R:106:3', 'test-step_pca_sparse_bayes.R:90:3',
'test-step_pca_truncated.R:84:3', 'test-step_range.R:71:3',
'test-step_ratio.R:62:3', 'test-step_rename.R:54:3', 'test-step_rose.R:57:3',
'test-step_scale.R:54:3', 'test-step_smote.R:57:3',
'test-step_smotenc.R:57:3', 'test-step_sqrt.R:54:3',
'test-step_tomek.R:57:3', 'test-step_unknown.R:67:3',
'test-step_upsample.R:57:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Failure ('test-model-xgboost.R:17:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds` to have names ".pred_class".
Differences:
`actual`:
`expected`: ".pred_class"
── Failure ('test-model-xgboost.R:18:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds$.pred_class` to have type "character".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:20:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds$.pred_class` to be identical to `as.character(exps$.pred_class)`.
Differences:
`actual` is NULL
`expected` is a character vector ('0', '0', '1', '1', '0', ...)
── Error ('test-model-xgboost.R:35:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = "class") at test-model-xgboost.R:35:3
2. └─orbital:::orbital.model_fit(bt_fit, type = "class")
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
── Failure ('test-model-xgboost.R:65:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds` to have names `c(".pred_0", ".pred_1")`.
Differences:
`actual`:
`expected`: ".pred_0" ".pred_1"
── Failure ('test-model-xgboost.R:66:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds$.pred_0` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:67:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds$.pred_1` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:74:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds` to equal `exps`.
Differences:
`actual` is length 0
`expected` is length 2
`names(actual)`:
`names(expected)`: ".pred_0" ".pred_1"
`actual$.pred_0` is absent
`expected$.pred_0` is a double vector (0.536467909812927, 0.536467909812927, 0.100352562963963, 0.209237098693848, 0.94028639793396, ...)
`actual$.pred_1` is absent
`expected$.pred_1` is a double vector (0.463532090187073, 0.463532090187073, 0.899647437036037, 0.790762901306152, 0.05971360206604, ...)
── Error ('test-model-xgboost.R:90:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = "prob") at test-model-xgboost.R:90:3
2. └─orbital:::orbital.model_fit(bt_fit, type = "prob")
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
── Failure ('test-model-xgboost.R:131:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds` to have names `c(".pred_class", ".pred_0", ".pred_1")`.
Differences:
`actual`:
`expected`: ".pred_class" ".pred_0" ".pred_1"
── Failure ('test-model-xgboost.R:132:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_class` to have type "character".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:133:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_0` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:134:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_1` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:142:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds` to equal `exps`.
Differences:
`actual` is length 0
`expected` is length 3
`names(actual)`:
`names(expected)`: ".pred_class" ".pred_0" ".pred_1"
`actual$.pred_class` is absent
`expected$.pred_class` is a character vector ('0', '0', '1', '1', '0', ...)
`actual$.pred_0` is absent
`expected$.pred_0` is a double vector (0.536467909812927, 0.536467909812927, 0.100352562963963, 0.209237098693848, 0.94028639793396, ...)
`actual$.pred_1` is absent
`expected$.pred_1` is a double vector (0.463532090187073, 0.463532090187073, 0.899647437036037, 0.790762901306152, 0.05971360206604, ...)
── Error ('test-model-xgboost.R:158:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = c("class", "prob")) at test-model-xgboost.R:158:3
2. └─orbital:::orbital.model_fit(bt_fit, type = c("class", "prob"))
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
[ FAIL 15 | WARN 2 | SKIP 113 | PASS 370 ]
Error:
! Test failures.
Execution halted
Flavor: r-release-macos-x86_64
Version: 0.4.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [25s/31s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(orbital)
>
> test_check("orbital")
Loading required package: parsnip
Saving _problems/test-model-xgboost-17.R
Saving _problems/test-model-xgboost-18.R
Saving _problems/test-model-xgboost-23.R
Saving _problems/test-model-xgboost-35.R
Saving _problems/test-model-xgboost-65.R
Saving _problems/test-model-xgboost-66.R
Saving _problems/test-model-xgboost-67.R
Saving _problems/test-model-xgboost-78.R
Saving _problems/test-model-xgboost-90.R
Saving _problems/test-model-xgboost-131.R
Saving _problems/test-model-xgboost-132.R
Saving _problems/test-model-xgboost-133.R
Saving _problems/test-model-xgboost-134.R
Saving _problems/test-model-xgboost-146.R
Saving _problems/test-model-xgboost-158.R
[ FAIL 15 | WARN 2 | SKIP 113 | PASS 370 ]
══ Skipped tests (113) ═════════════════════════════════════════════════════════
• On CRAN (69): 'test-adjust_equivocal_zone.R:36:1',
'test-adjust_equivocal_zone.R:155:3', 'test-adjust_numeric_range.R:123:3',
'test-adjust_predictions_custom.R:98:3',
'test-adjust_probability_threshold.R:34:1',
'test-adjust_probability_threshold.R:148:3', 'test-augment.R:41:3',
'test-dt.R:1:1', 'test-orbital.R:62:1', 'test-orbital.R:93:1',
'test-orbital.R:117:1', 'test-orbital.R:127:1', 'test-orbital.R:134:1',
'test-parsnip.R:1:1', 'test-parsnip.R:48:1', 'test-parsnip.R:63:1',
'test-recipes.R:1:1', 'test-show_query.R:7:3', 'test-sql.R:1:1',
'test-step_adasyn.R:20:1', 'test-step_adasyn.R:83:3',
'test-step_adasyn.R:111:3', 'test-step_bin2factor.R:79:3',
'test-step_boxcox.R:77:3', 'test-step_bsmote.R:20:1',
'test-step_bsmote.R:83:3', 'test-step_center.R:77:3',
'test-step_discretize.R:128:3', 'test-step_downsample.R:20:1',
'test-step_downsample.R:83:3', 'test-step_dummy.R:108:3',
'test-step_impute_mean.R:80:3', 'test-step_impute_median.R:81:3',
'test-step_impute_mode.R:93:3', 'test-step_indicate_na.R:83:3',
'test-step_intercept.R:67:3', 'test-step_inverse.R:94:3',
'test-step_lag.R:63:3', 'test-step_lencode_bayes.R:101:3',
'test-step_lencode_glm.R:96:3', 'test-step_lencode_mixed.R:104:3',
'test-step_log.R:94:3', 'test-step_mutate.R:77:3',
'test-step_nearmiss.R:20:1', 'test-step_nearmiss.R:83:3',
'test-step_normalize.R:77:3', 'test-step_novel.R:99:3',
'test-step_other.R:101:3', 'test-step_pca.R:152:3',
'test-step_pca_sparse.R:133:3', 'test-step_pca_sparse_bayes.R:118:3',
'test-step_pca_truncated.R:111:3', 'test-step_range.R:94:3',
'test-step_ratio.R:88:3', 'test-step_rename.R:77:3', 'test-step_rose.R:20:1',
'test-step_rose.R:83:3', 'test-step_scale.R:77:3', 'test-step_smote.R:20:1',
'test-step_smote.R:83:3', 'test-step_smotenc.R:20:1',
'test-step_smotenc.R:83:3', 'test-step_sqrt.R:77:3',
'test-step_tomek.R:20:1', 'test-step_tomek.R:83:3',
'test-step_unknown.R:97:3', 'test-step_upsample.R:20:1',
'test-step_upsample.R:83:3', 'test-workflows.R:1:1'
• empty test (2): 'test-augment.R:31:1', 'test-augment.R:111:1'
• is.na(testthat_spark_env_version()) is TRUE (42):
'test-adjust_equivocal_zone.R:113:3', 'test-adjust_numeric_range.R:96:3',
'test-adjust_predictions_custom.R:68:3',
'test-adjust_probability_threshold.R:109:3', 'test-step_adasyn.R:57:3',
'test-step_bin2factor.R:56:3', 'test-step_boxcox.R:54:3',
'test-step_bsmote.R:57:3', 'test-step_center.R:54:3',
'test-step_discretize.R:102:3', 'test-step_downsample.R:57:3',
'test-step_dummy.R:82:3', 'test-step_impute_mean.R:56:3',
'test-step_impute_median.R:57:3', 'test-step_impute_mode.R:63:3',
'test-step_indicate_na.R:59:3', 'test-step_intercept.R:44:3',
'test-step_inverse.R:71:3', 'test-step_lencode_bayes.R:73:3',
'test-step_lencode_glm.R:69:3', 'test-step_lencode_mixed.R:75:3',
'test-step_log.R:71:3', 'test-step_mutate.R:54:3',
'test-step_nearmiss.R:57:3', 'test-step_normalize.R:54:3',
'test-step_novel.R:71:3', 'test-step_other.R:73:3', 'test-step_pca.R:128:3',
'test-step_pca_sparse.R:106:3', 'test-step_pca_sparse_bayes.R:90:3',
'test-step_pca_truncated.R:84:3', 'test-step_range.R:71:3',
'test-step_ratio.R:62:3', 'test-step_rename.R:54:3', 'test-step_rose.R:57:3',
'test-step_scale.R:54:3', 'test-step_smote.R:57:3',
'test-step_smotenc.R:57:3', 'test-step_sqrt.R:54:3',
'test-step_tomek.R:57:3', 'test-step_unknown.R:67:3',
'test-step_upsample.R:57:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Failure ('test-model-xgboost.R:17:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds` to have names ".pred_class".
Differences:
`actual`:
`expected`: ".pred_class"
── Failure ('test-model-xgboost.R:18:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds$.pred_class` to have type "character".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:20:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds$.pred_class` to be identical to `as.character(exps$.pred_class)`.
Differences:
`actual` is NULL
`expected` is a character vector ('0', '0', '1', '1', '0', ...)
── Error ('test-model-xgboost.R:35:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = "class") at test-model-xgboost.R:35:3
2. └─orbital:::orbital.model_fit(bt_fit, type = "class")
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
── Failure ('test-model-xgboost.R:65:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds` to have names `c(".pred_0", ".pred_1")`.
Differences:
`actual`:
`expected`: ".pred_0" ".pred_1"
── Failure ('test-model-xgboost.R:66:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds$.pred_0` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:67:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds$.pred_1` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:74:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds` to equal `exps`.
Differences:
`actual` is length 0
`expected` is length 2
`names(actual)`:
`names(expected)`: ".pred_0" ".pred_1"
`actual$.pred_0` is absent
`expected$.pred_0` is a double vector (0.536467909812927, 0.536467909812927, 0.100352562963963, 0.209237098693848, 0.94028639793396, ...)
`actual$.pred_1` is absent
`expected$.pred_1` is a double vector (0.463532090187073, 0.463532090187073, 0.899647437036037, 0.790762901306152, 0.05971360206604, ...)
── Error ('test-model-xgboost.R:90:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = "prob") at test-model-xgboost.R:90:3
2. └─orbital:::orbital.model_fit(bt_fit, type = "prob")
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
── Failure ('test-model-xgboost.R:131:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds` to have names `c(".pred_class", ".pred_0", ".pred_1")`.
Differences:
`actual`:
`expected`: ".pred_class" ".pred_0" ".pred_1"
── Failure ('test-model-xgboost.R:132:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_class` to have type "character".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:133:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_0` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:134:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_1` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:142:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds` to equal `exps`.
Differences:
`actual` is length 0
`expected` is length 3
`names(actual)`:
`names(expected)`: ".pred_class" ".pred_0" ".pred_1"
`actual$.pred_class` is absent
`expected$.pred_class` is a character vector ('0', '0', '1', '1', '0', ...)
`actual$.pred_0` is absent
`expected$.pred_0` is a double vector (0.536467909812927, 0.536467909812927, 0.100352562963963, 0.209237098693848, 0.94028639793396, ...)
`actual$.pred_1` is absent
`expected$.pred_1` is a double vector (0.463532090187073, 0.463532090187073, 0.899647437036037, 0.790762901306152, 0.05971360206604, ...)
── Error ('test-model-xgboost.R:158:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = c("class", "prob")) at test-model-xgboost.R:158:3
2. └─orbital:::orbital.model_fit(bt_fit, type = c("class", "prob"))
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
[ FAIL 15 | WARN 2 | SKIP 113 | PASS 370 ]
Error:
! Test failures.
Execution halted
Flavor: r-oldrel-macos-arm64
Version: 0.4.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [80s/137s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(orbital)
>
> test_check("orbital")
Loading required package: parsnip
Saving _problems/test-model-xgboost-17.R
Saving _problems/test-model-xgboost-18.R
Saving _problems/test-model-xgboost-23.R
Saving _problems/test-model-xgboost-35.R
Saving _problems/test-model-xgboost-65.R
Saving _problems/test-model-xgboost-66.R
Saving _problems/test-model-xgboost-67.R
Saving _problems/test-model-xgboost-78.R
Saving _problems/test-model-xgboost-90.R
Saving _problems/test-model-xgboost-131.R
Saving _problems/test-model-xgboost-132.R
Saving _problems/test-model-xgboost-133.R
Saving _problems/test-model-xgboost-134.R
Saving _problems/test-model-xgboost-146.R
Saving _problems/test-model-xgboost-158.R
[ FAIL 15 | WARN 2 | SKIP 113 | PASS 370 ]
══ Skipped tests (113) ═════════════════════════════════════════════════════════
• On CRAN (69): 'test-adjust_equivocal_zone.R:36:1',
'test-adjust_equivocal_zone.R:155:3', 'test-adjust_numeric_range.R:123:3',
'test-adjust_predictions_custom.R:98:3',
'test-adjust_probability_threshold.R:34:1',
'test-adjust_probability_threshold.R:148:3', 'test-augment.R:41:3',
'test-dt.R:1:1', 'test-orbital.R:62:1', 'test-orbital.R:93:1',
'test-orbital.R:117:1', 'test-orbital.R:127:1', 'test-orbital.R:134:1',
'test-parsnip.R:1:1', 'test-parsnip.R:48:1', 'test-parsnip.R:63:1',
'test-recipes.R:1:1', 'test-show_query.R:7:3', 'test-sql.R:1:1',
'test-step_adasyn.R:20:1', 'test-step_adasyn.R:83:3',
'test-step_adasyn.R:111:3', 'test-step_bin2factor.R:79:3',
'test-step_boxcox.R:77:3', 'test-step_bsmote.R:20:1',
'test-step_bsmote.R:83:3', 'test-step_center.R:77:3',
'test-step_discretize.R:128:3', 'test-step_downsample.R:20:1',
'test-step_downsample.R:83:3', 'test-step_dummy.R:108:3',
'test-step_impute_mean.R:80:3', 'test-step_impute_median.R:81:3',
'test-step_impute_mode.R:93:3', 'test-step_indicate_na.R:83:3',
'test-step_intercept.R:67:3', 'test-step_inverse.R:94:3',
'test-step_lag.R:63:3', 'test-step_lencode_bayes.R:101:3',
'test-step_lencode_glm.R:96:3', 'test-step_lencode_mixed.R:104:3',
'test-step_log.R:94:3', 'test-step_mutate.R:77:3',
'test-step_nearmiss.R:20:1', 'test-step_nearmiss.R:83:3',
'test-step_normalize.R:77:3', 'test-step_novel.R:99:3',
'test-step_other.R:101:3', 'test-step_pca.R:152:3',
'test-step_pca_sparse.R:133:3', 'test-step_pca_sparse_bayes.R:118:3',
'test-step_pca_truncated.R:111:3', 'test-step_range.R:94:3',
'test-step_ratio.R:88:3', 'test-step_rename.R:77:3', 'test-step_rose.R:20:1',
'test-step_rose.R:83:3', 'test-step_scale.R:77:3', 'test-step_smote.R:20:1',
'test-step_smote.R:83:3', 'test-step_smotenc.R:20:1',
'test-step_smotenc.R:83:3', 'test-step_sqrt.R:77:3',
'test-step_tomek.R:20:1', 'test-step_tomek.R:83:3',
'test-step_unknown.R:97:3', 'test-step_upsample.R:20:1',
'test-step_upsample.R:83:3', 'test-workflows.R:1:1'
• empty test (2): 'test-augment.R:31:1', 'test-augment.R:111:1'
• is.na(testthat_spark_env_version()) is TRUE (42):
'test-adjust_equivocal_zone.R:113:3', 'test-adjust_numeric_range.R:96:3',
'test-adjust_predictions_custom.R:68:3',
'test-adjust_probability_threshold.R:109:3', 'test-step_adasyn.R:57:3',
'test-step_bin2factor.R:56:3', 'test-step_boxcox.R:54:3',
'test-step_bsmote.R:57:3', 'test-step_center.R:54:3',
'test-step_discretize.R:102:3', 'test-step_downsample.R:57:3',
'test-step_dummy.R:82:3', 'test-step_impute_mean.R:56:3',
'test-step_impute_median.R:57:3', 'test-step_impute_mode.R:63:3',
'test-step_indicate_na.R:59:3', 'test-step_intercept.R:44:3',
'test-step_inverse.R:71:3', 'test-step_lencode_bayes.R:73:3',
'test-step_lencode_glm.R:69:3', 'test-step_lencode_mixed.R:75:3',
'test-step_log.R:71:3', 'test-step_mutate.R:54:3',
'test-step_nearmiss.R:57:3', 'test-step_normalize.R:54:3',
'test-step_novel.R:71:3', 'test-step_other.R:73:3', 'test-step_pca.R:128:3',
'test-step_pca_sparse.R:106:3', 'test-step_pca_sparse_bayes.R:90:3',
'test-step_pca_truncated.R:84:3', 'test-step_range.R:71:3',
'test-step_ratio.R:62:3', 'test-step_rename.R:54:3', 'test-step_rose.R:57:3',
'test-step_scale.R:54:3', 'test-step_smote.R:57:3',
'test-step_smotenc.R:57:3', 'test-step_sqrt.R:54:3',
'test-step_tomek.R:57:3', 'test-step_unknown.R:67:3',
'test-step_upsample.R:57:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Failure ('test-model-xgboost.R:17:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds` to have names ".pred_class".
Differences:
`actual`:
`expected`: ".pred_class"
── Failure ('test-model-xgboost.R:18:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds$.pred_class` to have type "character".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:20:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Expected `preds$.pred_class` to be identical to `as.character(exps$.pred_class)`.
Differences:
`actual` is NULL
`expected` is a character vector ('0', '0', '1', '1', '0', ...)
── Error ('test-model-xgboost.R:35:3'): boost_tree(), objective = binary:logistic, works with type = class ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = "class") at test-model-xgboost.R:35:3
2. └─orbital:::orbital.model_fit(bt_fit, type = "class")
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
── Failure ('test-model-xgboost.R:65:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds` to have names `c(".pred_0", ".pred_1")`.
Differences:
`actual`:
`expected`: ".pred_0" ".pred_1"
── Failure ('test-model-xgboost.R:66:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds$.pred_0` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:67:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds$.pred_1` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:74:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Expected `preds` to equal `exps`.
Differences:
`actual` is length 0
`expected` is length 2
`names(actual)`:
`names(expected)`: ".pred_0" ".pred_1"
`actual$.pred_0` is absent
`expected$.pred_0` is a double vector (0.536467909812927, 0.536467909812927, 0.100352562963963, 0.209237098693848, 0.94028639793396, ...)
`actual$.pred_1` is absent
`expected$.pred_1` is a double vector (0.463532090187073, 0.463532090187073, 0.899647437036037, 0.790762901306152, 0.05971360206604, ...)
── Error ('test-model-xgboost.R:90:3'): boost_tree(), objective = binary:logistic, works with type = prob ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = "prob") at test-model-xgboost.R:90:3
2. └─orbital:::orbital.model_fit(bt_fit, type = "prob")
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
── Failure ('test-model-xgboost.R:131:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds` to have names `c(".pred_class", ".pred_0", ".pred_1")`.
Differences:
`actual`:
`expected`: ".pred_class" ".pred_0" ".pred_1"
── Failure ('test-model-xgboost.R:132:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_class` to have type "character".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:133:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_0` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:134:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds$.pred_1` to have type "double".
Actual type: "NULL"
── Failure ('test-model-xgboost.R:142:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Expected `preds` to equal `exps`.
Differences:
`actual` is length 0
`expected` is length 3
`names(actual)`:
`names(expected)`: ".pred_class" ".pred_0" ".pred_1"
`actual$.pred_class` is absent
`expected$.pred_class` is a character vector ('0', '0', '1', '1', '0', ...)
`actual$.pred_0` is absent
`expected$.pred_0` is a double vector (0.536467909812927, 0.536467909812927, 0.100352562963963, 0.209237098693848, 0.94028639793396, ...)
`actual$.pred_1` is absent
`expected$.pred_1` is a double vector (0.463532090187073, 0.463532090187073, 0.899647437036037, 0.790762901306152, 0.05971360206604, ...)
── Error ('test-model-xgboost.R:158:3'): boost_tree(), objective = binary:logistic, works with type = c(class, prob) ──
Error in `build_fit_formula_xgb(parsedmodel)`: Only objectives "binary:logistic", "reg:squarederror", "reg:logistic", "binary:logitraw" are supported yet.
Backtrace:
▆
1. ├─orbital::orbital(bt_fit, type = c("class", "prob")) at test-model-xgboost.R:158:3
2. └─orbital:::orbital.model_fit(bt_fit, type = c("class", "prob"))
3. ├─base::tryCatch(...)
4. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
5. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
6. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
7. ├─tidypredict::tidypredict_fit(x)
8. └─tidypredict:::tidypredict_fit._xgb.Booster(x)
9. ├─tidypredict::tidypredict_fit(model$fit)
10. └─tidypredict:::tidypredict_fit.xgb.Booster(model$fit)
11. └─tidypredict:::build_fit_formula_xgb(parsedmodel)
12. └─cli::cli_abort("Only objectives {.val binary:logistic}, {.val reg:squarederror},\n {.val reg:logistic}, {.val binary:logitraw} are supported yet.")
13. └─rlang::abort(...)
[ FAIL 15 | WARN 2 | SKIP 113 | PASS 370 ]
Error:
! Test failures.
Execution halted
Flavor: r-oldrel-macos-x86_64