Last updated on 2025-12-19 14:50:20 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.1.4 | 17.00 | 181.57 | 198.57 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 1.3.0 | 3.29 | 54.68 | 57.97 | OK | |
| r-devel-linux-x86_64-fedora-clang | 1.3.0 | 8.00 | 126.55 | 134.55 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 1.3.0 | 125.68 | OK | |||
| r-devel-windows-x86_64 | 1.3.0 | 7.00 | 101.00 | 108.00 | OK | |
| r-patched-linux-x86_64 | 1.1.4 | 17.22 | 171.71 | 188.93 | ERROR | |
| r-release-linux-x86_64 | 1.1.4 | 16.72 | 172.51 | 189.23 | ERROR | |
| r-release-macos-arm64 | 1.3.0 | OK | ||||
| r-release-macos-x86_64 | 1.3.0 | 3.00 | 76.00 | 79.00 | OK | |
| r-release-windows-x86_64 | 1.3.0 | 10.00 | 88.00 | 98.00 | OK | |
| r-oldrel-macos-arm64 | 1.3.0 | 1.00 | 26.00 | 27.00 | OK | |
| r-oldrel-macos-x86_64 | 1.3.0 | 3.00 | 86.00 | 89.00 | OK | |
| r-oldrel-windows-x86_64 | 1.3.0 | 12.00 | 106.00 | 118.00 | OK |
Version: 1.1.4
Check: tests
Result: ERROR
Running ‘testthat.R’ [38s/27s]
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(FastRet)
>
> test_check("FastRet")
Starting 2 test processes.
Saving _problems/test-train_frm-gbtree-11.R
Saving _problems/test-fit_gbtree-8.R
Saving _problems/test-fit_gbtree-16.R
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.25<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.25<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.40<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.41<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.41<1b>[0m Starting model Adjustment
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.41<1b>[0m dim(original_data): 442 x 126
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.41<1b>[0m dim(new_data): 25 x 3
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.53<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.53<1b>[0m nfolds: 5
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.53<1b>[0m Preprocessing data
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.54<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.54<1b>[0m Estimating performance of adjusted model in CV
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.61<1b>[0m Fitting adjustment model on full new data set
> test-plot_frm.R: <1b>[1;30m2025-12-08 17:21:11.61<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.86<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.86<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.86<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.86<1b>[0m predictors: 1, 2
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.86<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.86<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.87<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2)
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.87<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.92<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.92<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.92<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.92<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.92<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.93<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.93<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.93<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.93<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:11.93<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:12.00<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-08 17:21:12.00<1b>[0m Returning adjusted frm object
> test-selective_measuring.R: <1b>[1;30m2025-12-08 17:21:12.31<1b>[0m Starting Selective Measuring
> test-selective_measuring.R: <1b>[1;30m2025-12-08 17:21:12.31<1b>[0m Preprocessing input data
> test-selective_measuring.R: <1b>[1;30m2025-12-08 17:21:12.32<1b>[0m Mocking is enabled for 'preprocess_data'. Returning 'mockdata/RPCD_prepro.rds'.
> test-selective_measuring.R: <1b>[1;30m2025-12-08 17:21:12.32<1b>[0m Standardizing features
> test-selective_measuring.R: <1b>[1;30m2025-12-08 17:21:12.33<1b>[0m Training Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-08 17:21:12.33<1b>[0m Fitting Ridge model
> test-selective_measuring.R: <1b>[1;30m2025-12-08 17:21:12.70<1b>[0m End training
> test-selective_measuring.R: <1b>[1;30m2025-12-08 17:21:12.70<1b>[0m Scaling features by coefficients of Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-08 17:21:12.71<1b>[0m Applying PAM clustering
> test-selective_measuring.R: <1b>[1;30m2025-12-08 17:21:13.18<1b>[0m Returning clustering results
[ FAIL 3 | WARN 5 | SKIP 0 | PASS 19 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-train_frm-gbtree.R:5:5'): train_frm works if `method == "GBTree"` ──
<subscriptOutOfBoundsError/error/condition>
Error in `FUN(X[[i]], ...)`: subscript out of bounds
Backtrace:
▆
1. └─FastRet::train_frm(...) at test-train_frm-gbtree.R:5:5
2. └─base::lapply(tmp, "[[", 2)
── Error ('test-fit_gbtree.R:8:5'): fit.gbtrees works as expected ──────────────
Error in `begin_iteration:end_iteration`: argument of length 0
Backtrace:
▆
1. └─FastRet:::fit_gbtree(df, verbose = 0) at test-fit_gbtree.R:8:5
2. └─FastRet:::fit_gbtree_grid(...)
3. └─xgboost::xgb.train(...)
── Error ('test-fit_gbtree.R:16:5'): fit.gbtrees works for data from reverse phase column ──
Error in `begin_iteration:end_iteration`: argument of length 0
Backtrace:
▆
1. └─FastRet:::fit_gbtree(df, verbose = 0) at test-fit_gbtree.R:16:5
2. └─FastRet:::fit_gbtree_grid(...)
3. └─xgboost::xgb.train(...)
[ FAIL 3 | WARN 5 | SKIP 0 | PASS 19 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.1.4
Check: tests
Result: ERROR
Running ‘testthat.R’ [36s/24s]
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(FastRet)
>
> test_check("FastRet")
Starting 2 test processes.
Saving _problems/test-train_frm-gbtree-11.R
Saving _problems/test-fit_gbtree-8.R
Saving _problems/test-fit_gbtree-16.R
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.03<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.03<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.25<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.25<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.25<1b>[0m Starting model Adjustment
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.25<1b>[0m dim(original_data): 442 x 126
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.26<1b>[0m dim(new_data): 25 x 3
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.36<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.36<1b>[0m nfolds: 5
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.36<1b>[0m Preprocessing data
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.37<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.37<1b>[0m Estimating performance of adjusted model in CV
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.43<1b>[0m Fitting adjustment model on full new data set
> test-plot_frm.R: <1b>[1;30m2025-12-17 05:44:00.43<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.68<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.68<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.68<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.68<1b>[0m predictors: 1, 2
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.68<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.68<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.69<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2)
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.69<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.74<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.74<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.74<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.74<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.74<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.74<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.74<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.74<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.75<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.75<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.81<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-17 05:44:00.81<1b>[0m Returning adjusted frm object
> test-selective_measuring.R: <1b>[1;30m2025-12-17 05:44:01.16<1b>[0m Starting Selective Measuring
> test-selective_measuring.R: <1b>[1;30m2025-12-17 05:44:01.16<1b>[0m Preprocessing input data
> test-selective_measuring.R: <1b>[1;30m2025-12-17 05:44:01.16<1b>[0m Mocking is enabled for 'preprocess_data'. Returning 'mockdata/RPCD_prepro.rds'.
> test-selective_measuring.R: <1b>[1;30m2025-12-17 05:44:01.17<1b>[0m Standardizing features
> test-selective_measuring.R: <1b>[1;30m2025-12-17 05:44:01.17<1b>[0m Training Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-17 05:44:01.18<1b>[0m Fitting Ridge model
> test-selective_measuring.R: <1b>[1;30m2025-12-17 05:44:01.53<1b>[0m End training
> test-selective_measuring.R: <1b>[1;30m2025-12-17 05:44:01.53<1b>[0m Scaling features by coefficients of Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-17 05:44:01.54<1b>[0m Applying PAM clustering
> test-selective_measuring.R: <1b>[1;30m2025-12-17 05:44:02.01<1b>[0m Returning clustering results
[ FAIL 3 | WARN 5 | SKIP 0 | PASS 19 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-train_frm-gbtree.R:5:5'): train_frm works if `method == "GBTree"` ──
<subscriptOutOfBoundsError/error/condition>
Error in `FUN(X[[i]], ...)`: subscript out of bounds
Backtrace:
▆
1. └─FastRet::train_frm(...) at test-train_frm-gbtree.R:5:5
2. └─base::lapply(tmp, "[[", 2)
── Error ('test-fit_gbtree.R:8:5'): fit.gbtrees works as expected ──────────────
Error in `begin_iteration:end_iteration`: argument of length 0
Backtrace:
▆
1. └─FastRet:::fit_gbtree(df, verbose = 0) at test-fit_gbtree.R:8:5
2. └─FastRet:::fit_gbtree_grid(...)
3. └─xgboost::xgb.train(...)
── Error ('test-fit_gbtree.R:16:5'): fit.gbtrees works for data from reverse phase column ──
Error in `begin_iteration:end_iteration`: argument of length 0
Backtrace:
▆
1. └─FastRet:::fit_gbtree(df, verbose = 0) at test-fit_gbtree.R:16:5
2. └─FastRet:::fit_gbtree_grid(...)
3. └─xgboost::xgb.train(...)
[ FAIL 3 | WARN 5 | SKIP 0 | PASS 19 ]
Error:
! Test failures.
Execution halted
Flavor: r-patched-linux-x86_64
Version: 1.1.4
Check: tests
Result: ERROR
Running ‘testthat.R’ [38s/25s]
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(FastRet)
>
> test_check("FastRet")
Starting 2 test processes.
Saving _problems/test-train_frm-gbtree-11.R
Saving _problems/test-fit_gbtree-8.R
Saving _problems/test-fit_gbtree-16.R
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:56.73<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:56.73<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:56.91<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:56.91<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:56.91<1b>[0m Starting model Adjustment
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:56.91<1b>[0m dim(original_data): 442 x 126
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:56.91<1b>[0m dim(new_data): 25 x 3
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:57.02<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:57.02<1b>[0m nfolds: 5
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:57.02<1b>[0m Preprocessing data
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:57.03<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:57.04<1b>[0m Estimating performance of adjusted model in CV
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:57.11<1b>[0m Fitting adjustment model on full new data set
> test-plot_frm.R: <1b>[1;30m2025-12-13 05:33:57.11<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.39<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.39<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.39<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.39<1b>[0m predictors: 1, 2
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.39<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.39<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.40<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2)
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.40<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.45<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.45<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.45<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.45<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.45<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.45<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.45<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.45<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.46<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.46<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.52<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-13 05:33:57.52<1b>[0m Returning adjusted frm object
> test-selective_measuring.R: <1b>[1;30m2025-12-13 05:33:57.75<1b>[0m Starting Selective Measuring
> test-selective_measuring.R: <1b>[1;30m2025-12-13 05:33:57.75<1b>[0m Preprocessing input data
> test-selective_measuring.R: <1b>[1;30m2025-12-13 05:33:57.75<1b>[0m Mocking is enabled for 'preprocess_data'. Returning 'mockdata/RPCD_prepro.rds'.
> test-selective_measuring.R: <1b>[1;30m2025-12-13 05:33:57.76<1b>[0m Standardizing features
> test-selective_measuring.R: <1b>[1;30m2025-12-13 05:33:57.76<1b>[0m Training Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-13 05:33:57.76<1b>[0m Fitting Ridge model
> test-selective_measuring.R: <1b>[1;30m2025-12-13 05:33:58.24<1b>[0m End training
> test-selective_measuring.R: <1b>[1;30m2025-12-13 05:33:58.24<1b>[0m Scaling features by coefficients of Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-13 05:33:58.25<1b>[0m Applying PAM clustering
> test-selective_measuring.R: <1b>[1;30m2025-12-13 05:33:58.71<1b>[0m Returning clustering results
[ FAIL 3 | WARN 5 | SKIP 0 | PASS 19 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-train_frm-gbtree.R:5:5'): train_frm works if `method == "GBTree"` ──
<subscriptOutOfBoundsError/error/condition>
Error in `FUN(X[[i]], ...)`: subscript out of bounds
Backtrace:
▆
1. └─FastRet::train_frm(...) at test-train_frm-gbtree.R:5:5
2. └─base::lapply(tmp, "[[", 2)
── Error ('test-fit_gbtree.R:8:5'): fit.gbtrees works as expected ──────────────
Error in `begin_iteration:end_iteration`: argument of length 0
Backtrace:
▆
1. └─FastRet:::fit_gbtree(df, verbose = 0) at test-fit_gbtree.R:8:5
2. └─FastRet:::fit_gbtree_grid(...)
3. └─xgboost::xgb.train(...)
── Error ('test-fit_gbtree.R:16:5'): fit.gbtrees works for data from reverse phase column ──
Error in `begin_iteration:end_iteration`: argument of length 0
Backtrace:
▆
1. └─FastRet:::fit_gbtree(df, verbose = 0) at test-fit_gbtree.R:16:5
2. └─FastRet:::fit_gbtree_grid(...)
3. └─xgboost::xgb.train(...)
[ FAIL 3 | WARN 5 | SKIP 0 | PASS 19 ]
Error:
! Test failures.
Execution halted
Flavor: r-release-linux-x86_64