Last updated on 2025-12-12 21:49:54 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 | 1.1.4 | 0.36 | 2.62 | 2.98 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.1.4 | 31.00 | 301.45 | 332.45 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 1.1.4 | 30.00 | 291.81 | 321.81 | ERROR | |
| r-devel-windows-x86_64 | 1.1.4 | 19.00 | 155.00 | 174.00 | ERROR | |
| r-patched-linux-x86_64 | 1.1.4 | 15.86 | 174.52 | 190.38 | ERROR | |
| r-release-linux-x86_64 | 1.1.4 | 16.13 | 173.79 | 189.92 | ERROR | |
| r-release-macos-arm64 | 1.1.4 | OK | ||||
| r-release-macos-x86_64 | 1.1.4 | 11.00 | 154.00 | 165.00 | OK | |
| r-release-windows-x86_64 | 1.1.4 | 18.00 | 156.00 | 174.00 | OK | |
| r-oldrel-macos-arm64 | 1.1.4 | OK | ||||
| r-oldrel-macos-x86_64 | 1.1.4 | 10.00 | 152.00 | 162.00 | OK | |
| r-oldrel-windows-x86_64 | 1.1.4 | 25.00 | 201.00 | 226.00 | ERROR |
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: package dependencies
Result: ERROR
Packages required but not available: 'rcdk', 'xlsx'
See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.1.4
Check: tests
Result: ERROR
Running ‘testthat.R’ [65s/112s]
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;30m2025-12-03 10:48:47.27<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-03 10:48:47.27<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-03 10:48:47.89<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-03 10:48:47.89<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-03 10:48:47.94<1b>[0m Starting model Adjustment
> test-plot_frm.R: <1b>[1;30m2025-12-03 10:48:47.95<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.00<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.00<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.00<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.00<1b>[0m predictors: 1, 2
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.00<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.00<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.03<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2)
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.04<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.21<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.22<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.22<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.22<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.22<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.22<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.22<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.22<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.25<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.26<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.43<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-03 10:48:48.44<1b>[0m Returning adjusted frm object
> test-selective_measuring.R: <1b>[1;30m2025-12-03 10:48:49.33<1b>[0m Starting Selective Measuring
> test-selective_measuring.R: <1b>[1;30m2025-12-03 10:48:49.34<1b>[0m Preprocessing input data
> test-selective_measuring.R: <1b>[1;30m2025-12-03 10:48:49.34<1b>[0m Mocking is enabled for 'preprocess_data'. Returning 'mockdata/RPCD_prepro.rds'.
> test-selective_measuring.R: <1b>[1;30m2025-12-03 10:48:49.39<1b>[0m Standardizing features
> test-selective_measuring.R: <1b>[1;30m2025-12-03 10:48:49.43<1b>[0m Training Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-03 10:48:49.44<1b>[0m Fitting Ridge model
> test-selective_measuring.R: <1b>[1;30m2025-12-03 10:48:51.27<1b>[0m End training
> test-selective_measuring.R: <1b>[1;30m2025-12-03 10:48:51.27<1b>[0m Scaling features by coefficients of Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-03 10:48:51.29<1b>[0m Applying PAM clustering
> test-selective_measuring.R: <1b>[1;30m2025-12-03 10:48:52.16<1b>[0m Returning clustering results
> test-plot_frm.R: <1b>[1;30m2025-12-03 10:48:47.95<1b>[0m dim(new_data): 25 x 3
> test-plot_frm.R: <1b>[1;30m2025-12-03 10:48:53.23<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-plot_frm.R: <1b>[1;30m2025-12-03 10:48:53.23<1b>[0m nfolds: 5
> test-plot_frm.R: <1b>[1;30m2025-12-03 10:48:53.23<1b>[0m Preprocessing data
> test-plot_frm.R: <1b>[1;30m2025-12-03 10:48:53.28<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-plot_frm.R: <1b>[1;30m2025-12-03 10:48:53.29<1b>[0m Estimating performance of adjusted model in CV
> test-plot_frm.R: <1b>[1;30m2025-12-03 10:48:53.69<1b>[0m Fitting adjustment model on full new data set
> test-plot_frm.R: <1b>[1;30m2025-12-03 10:48:53.72<1b>[0m Returning adjusted frm object
[ 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-fedora-clang
Version: 1.1.4
Check: tests
Result: ERROR
Running ‘testthat.R’ [66s/126s]
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;30m2025-12-11 21:29:12.84<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-11 21:29:12.85<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-11 21:29:13.13<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-11 21:29:13.14<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-11 21:29:13.15<1b>[0m Starting model Adjustment
> test-plot_frm.R: <1b>[1;30m2025-12-11 21:29:13.15<1b>[0m dim(original_data): 442 x 126
> test-plot_frm.R: <1b>[1;30m2025-12-11 21:29:13.16<1b>[0m dim(new_data): 25 x 3
> test-plot_frm.R: <1b>[1;30m2025-12-11 21:29:16.40<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-plot_frm.R: <1b>[1;30m2025-12-11 21:29:16.40<1b>[0m nfolds: 5
> test-plot_frm.R: <1b>[1;30m2025-12-11 21:29:16.41<1b>[0m Preprocessing data
> test-plot_frm.R: <1b>[1;30m2025-12-11 21:29:16.43<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-plot_frm.R: <1b>[1;30m2025-12-11 21:29:16.43<1b>[0m Estimating performance of adjusted model in CV
> test-plot_frm.R: <1b>[1;30m2025-12-11 21:29:16.55<1b>[0m Fitting adjustment model on full new data set
> test-plot_frm.R: <1b>[1;30m2025-12-11 21:29:16.55<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.10<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.11<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.11<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.11<1b>[0m predictors: 1, 2
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.11<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.11<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.16<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2)
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.17<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.56<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.57<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.57<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.57<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.57<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.57<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.57<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.57<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.62<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.64<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.97<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-11 21:29:17.98<1b>[0m Returning adjusted frm object
> test-selective_measuring.R: <1b>[1;30m2025-12-11 21:29:18.05<1b>[0m Starting Selective Measuring
> test-selective_measuring.R: <1b>[1;30m2025-12-11 21:29:18.05<1b>[0m Preprocessing input data
> test-selective_measuring.R: <1b>[1;30m2025-12-11 21:29:18.05<1b>[0m Mocking is enabled for 'preprocess_data'. Returning 'mockdata/RPCD_prepro.rds'.
> test-selective_measuring.R: <1b>[1;30m2025-12-11 21:29:18.09<1b>[0m Standardizing features
> test-selective_measuring.R: <1b>[1;30m2025-12-11 21:29:18.15<1b>[0m Training Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-11 21:29:18.15<1b>[0m Fitting Ridge model
> test-selective_measuring.R: <1b>[1;30m2025-12-11 21:29:19.60<1b>[0m End training
> test-selective_measuring.R: <1b>[1;30m2025-12-11 21:29:19.61<1b>[0m Scaling features by coefficients of Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-11 21:29:19.64<1b>[0m Applying PAM clustering
> test-selective_measuring.R: <1b>[1;30m2025-12-11 21:29:22.75<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-fedora-gcc
Version: 1.1.4
Check: tests
Result: ERROR
Running 'testthat.R' [17s]
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
> test-read_rp_xlsx.R: WARNING: An illegal reflective access operation has occurred
> test-read_rp_xlsx.R: WARNING: Illegal reflective access by org.apache.poi.openxml4j.util.ZipSecureFile (file:/D:/RCompile/CRANpkg/lib/4.6/xlsxjars/java/poi-ooxml-3.13-20150929.jar) to field java.io.FilterInputStream.in
> test-read_rp_xlsx.R: WARNING: Please consider reporting this to the maintainers of org.apache.poi.openxml4j.util.ZipSecureFile
> test-read_rp_xlsx.R: WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
> test-read_rp_xlsx.R: WARNING: All illegal access operations will be denied in a future release
> test-read_rp_xlsx.R:
Saving _problems/test-fit_gbtree-8.R
Saving _problems/test-fit_gbtree-16.R
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:10.77<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:10.77<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:10.99<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:10.99<1b>[0m Parallel processing is not supported on Windows. Setting `nw` to 1.
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:10.99<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:11.00<1b>[0m Starting model Adjustment
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:11.00<1b>[0m dim(original_data): 442 x 126
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:11.00<1b>[0m dim(new_data): 25 x 3
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:11.07<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:11.07<1b>[0m nfolds: 5
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:11.07<1b>[0m Preprocessing data
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:11.08<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:11.08<1b>[0m Estimating performance of adjusted model in CV
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:11.11<1b>[0m Fitting adjustment model on full new data set
> test-plot_frm.R: <1b>[1;30m2025-12-07 08:25:11.11<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.36<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.36<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.36<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.36<1b>[0m predictors: 1, 2
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.36<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.36<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.37<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2)
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.37<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.41<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.41<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.41<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.41<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.41<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.41<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.41<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.41<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.42<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.42<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.47<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-07 08:25:11.47<1b>[0m Returning adjusted frm object
> test-selective_measuring.R: <1b>[1;30m2025-12-07 08:25:11.72<1b>[0m Starting Selective Measuring
> test-selective_measuring.R: <1b>[1;30m2025-12-07 08:25:11.72<1b>[0m Preprocessing input data
> test-selective_measuring.R: <1b>[1;30m2025-12-07 08:25:11.72<1b>[0m Mocking is enabled for 'preprocess_data'. Returning 'mockdata/RPCD_prepro.rds'.
> test-selective_measuring.R: <1b>[1;30m2025-12-07 08:25:11.73<1b>[0m Standardizing features
> test-selective_measuring.R: <1b>[1;30m2025-12-07 08:25:11.73<1b>[0m Training Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-07 08:25:11.74<1b>[0m Fitting Ridge model
> test-read_rpadj_xlsx.R: WARNING: An illegal reflective access operation has occurred
> test-read_rpadj_xlsx.R: WARNING: Illegal reflective access by org.apache.poi.openxml4j.util.ZipSecureFile (file:/D:/RCompile/CRANpkg/lib/4.6/xlsxjars/java/poi-ooxml-3.13-20150929.jar) to field java.io.FilterInputStream.in
> test-read_rpadj_xlsx.R: WARNING: Please consider reporting this to the maintainers of org.apache.poi.openxml4j.util.ZipSecureFile
> test-read_rpadj_xlsx.R: WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
> test-read_rpadj_xlsx.R: WARNING: All illegal access operations will be denied in a future release
> test-read_rpadj_xlsx.R:
> test-selective_measuring.R: <1b>[1;30m2025-12-07 08:25:12.22<1b>[0m End training
> test-selective_measuring.R: <1b>[1;30m2025-12-07 08:25:12.22<1b>[0m Scaling features by coefficients of Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-07 08:25:12.24<1b>[0m Applying PAM clustering
> test-selective_measuring.R: <1b>[1;30m2025-12-07 08:25:12.56<1b>[0m Returning clustering results
[ FAIL 3 | WARN 3 | SKIP 0 | PASS 19 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-train_frm-gbtree.R:5:5'): train_frm works if `method == "GBTree"` ──
Error in `begin_iteration:end_iteration`: argument of length 0
Backtrace:
▆
1. └─FastRet::train_frm(...) at test-train_frm-gbtree.R:5:5
2. └─parallel::mclapply(...)
3. └─base::lapply(X, FUN, ...)
4. └─FastRet (local) FUN(X[[i]], ...)
5. └─FastRet (local) fit(df[train, ], verbose = 0)
6. └─FastRet:::fit_gbtree_grid(...)
7. └─xgboost::xgb.train(...)
── 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 3 | SKIP 0 | PASS 19 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-windows-x86_64
Version: 1.1.4
Check: tests
Result: ERROR
Running ‘testthat.R’ [40s/26s]
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;30m2025-12-10 05:35:56.29<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-10 05:35:56.29<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-10 05:35:56.45<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-10 05:35:56.45<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-10 05:35:56.45<1b>[0m Starting model Adjustment
> test-plot_frm.R: <1b>[1;30m2025-12-10 05:35:56.45<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.90<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.90<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.90<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.90<1b>[0m predictors: 1, 2
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.90<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.90<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.91<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2)
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.91<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.97<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.98<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.98<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.98<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.98<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.98<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.98<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.98<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.98<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:56.99<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:57.04<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-10 05:35:57.04<1b>[0m Returning adjusted frm object
> test-plot_frm.R: <1b>[1;30m2025-12-10 05:35:56.45<1b>[0m dim(new_data): 25 x 3
> test-plot_frm.R: <1b>[1;30m2025-12-10 05:35:57.51<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-plot_frm.R: <1b>[1;30m2025-12-10 05:35:57.51<1b>[0m nfolds: 5
> test-plot_frm.R: <1b>[1;30m2025-12-10 05:35:57.51<1b>[0m Preprocessing data
> test-plot_frm.R: <1b>[1;30m2025-12-10 05:35:57.52<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-plot_frm.R: <1b>[1;30m2025-12-10 05:35:57.52<1b>[0m Estimating performance of adjusted model in CV
> test-selective_measuring.R: <1b>[1;30m2025-12-10 05:35:57.50<1b>[0m Starting Selective Measuring
> test-selective_measuring.R: <1b>[1;30m2025-12-10 05:35:57.50<1b>[0m Preprocessing input data
> test-selective_measuring.R: <1b>[1;30m2025-12-10 05:35:57.50<1b>[0m Mocking is enabled for 'preprocess_data'. Returning 'mockdata/RPCD_prepro.rds'.
> test-selective_measuring.R: <1b>[1;30m2025-12-10 05:35:57.50<1b>[0m Standardizing features
> test-selective_measuring.R: <1b>[1;30m2025-12-10 05:35:57.51<1b>[0m Training Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-10 05:35:57.51<1b>[0m Fitting Ridge model
> test-plot_frm.R: <1b>[1;30m2025-12-10 05:35:57.60<1b>[0m Fitting adjustment model on full new data set
> test-plot_frm.R: <1b>[1;30m2025-12-10 05:35:57.60<1b>[0m Returning adjusted frm object
> test-selective_measuring.R: <1b>[1;30m2025-12-10 05:35:57.94<1b>[0m End training
> test-selective_measuring.R: <1b>[1;30m2025-12-10 05:35:57.94<1b>[0m Scaling features by coefficients of Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-10 05:35:57.95<1b>[0m Applying PAM clustering
> test-selective_measuring.R: <1b>[1;30m2025-12-10 05:35:58.46<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’ [39s/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;30m2025-12-06 05:24:31.82<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-06 05:24:31.82<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-06 05:24:31.97<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-06 05:24:31.97<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-06 05:24:31.98<1b>[0m Starting model Adjustment
> test-plot_frm.R: <1b>[1;30m2025-12-06 05:24:31.98<1b>[0m dim(original_data): 442 x 126
> test-plot_frm.R: <1b>[1;30m2025-12-06 05:24:31.98<1b>[0m dim(new_data): 25 x 3
> test-plot_frm.R: <1b>[1;30m2025-12-06 05:24:32.07<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-plot_frm.R: <1b>[1;30m2025-12-06 05:24:32.07<1b>[0m nfolds: 5
> test-plot_frm.R: <1b>[1;30m2025-12-06 05:24:32.08<1b>[0m Preprocessing data
> test-plot_frm.R: <1b>[1;30m2025-12-06 05:24:32.08<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-plot_frm.R: <1b>[1;30m2025-12-06 05:24:32.09<1b>[0m Estimating performance of adjusted model in CV
> test-plot_frm.R: <1b>[1;30m2025-12-06 05:24:32.15<1b>[0m Fitting adjustment model on full new data set
> test-plot_frm.R: <1b>[1;30m2025-12-06 05:24:32.15<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.46<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.46<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.46<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.46<1b>[0m predictors: 1, 2
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.46<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.46<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.47<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2)
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.47<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.53<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.53<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.53<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.53<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.53<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.53<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.53<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.53<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.53<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.54<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.60<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-06 05:24:32.60<1b>[0m Returning adjusted frm object
> test-selective_measuring.R: <1b>[1;30m2025-12-06 05:24:32.90<1b>[0m Starting Selective Measuring
> test-selective_measuring.R: <1b>[1;30m2025-12-06 05:24:32.90<1b>[0m Preprocessing input data
> test-selective_measuring.R: <1b>[1;30m2025-12-06 05:24:32.90<1b>[0m Mocking is enabled for 'preprocess_data'. Returning 'mockdata/RPCD_prepro.rds'.
> test-selective_measuring.R: <1b>[1;30m2025-12-06 05:24:32.90<1b>[0m Standardizing features
> test-selective_measuring.R: <1b>[1;30m2025-12-06 05:24:32.91<1b>[0m Training Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-06 05:24:32.91<1b>[0m Fitting Ridge model
> test-selective_measuring.R: <1b>[1;30m2025-12-06 05:24:33.43<1b>[0m End training
> test-selective_measuring.R: <1b>[1;30m2025-12-06 05:24:33.43<1b>[0m Scaling features by coefficients of Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-06 05:24:33.44<1b>[0m Applying PAM clustering
> test-selective_measuring.R: <1b>[1;30m2025-12-06 05:24:33.77<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
Version: 1.1.4
Check: tests
Result: ERROR
Running 'testthat.R' [22s]
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
> test-read_rp_xlsx.R: WARNING: An illegal reflective access operation has occurred
> test-read_rp_xlsx.R: WARNING: Illegal reflective access by org.apache.poi.openxml4j.util.ZipSecureFile (file:/D:/RCompile/CRANpkg/lib/4.4/xlsxjars/java/poi-ooxml-3.13-20150929.jar) to field java.io.FilterInputStream.in
> test-read_rp_xlsx.R: WARNING: Please consider reporting this to the maintainers of org.apache.poi.openxml4j.util.ZipSecureFile
> test-read_rp_xlsx.R: WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
> test-read_rp_xlsx.R: WARNING: All illegal access operations will be denied in a future release
> test-read_rp_xlsx.R:
Saving _problems/test-fit_gbtree-8.R
Saving _problems/test-fit_gbtree-16.R
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.14<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.14<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.43<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.43<1b>[0m Parallel processing is not supported on Windows. Setting `nw` to 1.
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.43<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.43<1b>[0m Starting model Adjustment
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.43<1b>[0m dim(original_data): 442 x 126
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.43<1b>[0m dim(new_data): 25 x 3
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.55<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.55<1b>[0m nfolds: 5
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.55<1b>[0m Preprocessing data
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.56<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 09:13:31.56<1b>[0m Estimating performance of adjusted model in CV
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.61<1b>[0m Fitting adjustment model on full new data set
> test-plot_frm.R: <1b>[1;30m2025-12-08 09:13:31.61<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: WARNING: An illegal reflective access operation has occurred
> test-adjust_frm.R: WARNING: Illegal reflective access by org.apache.poi.openxml4j.util.ZipSecureFile (file:/D:/RCompile/CRANpkg/lib/4.4/xlsxjars/java/poi-ooxml-3.13-20150929.jar) to field java.io.FilterInputStream.in
> test-adjust_frm.R: WARNING: Please consider reporting this to the maintainers of org.apache.poi.openxml4j.util.ZipSecureFile
> test-adjust_frm.R: WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
> test-adjust_frm.R: WARNING: All illegal access operations will be denied in a future release
> test-adjust_frm.R:
> test-selective_measuring.R: <1b>[1;30m2025-12-08 09:13:32.28<1b>[0m Starting Selective Measuring
> test-selective_measuring.R: <1b>[1;30m2025-12-08 09:13:32.28<1b>[0m Preprocessing input data
> test-selective_measuring.R: <1b>[1;30m2025-12-08 09:13:32.28<1b>[0m Mocking is enabled for 'preprocess_data'. Returning 'mockdata/RPCD_prepro.rds'.
> test-selective_measuring.R: <1b>[1;30m2025-12-08 09:13:32.29<1b>[0m Standardizing features
> test-selective_measuring.R: <1b>[1;30m2025-12-08 09:13:32.30<1b>[0m Training Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-08 09:13:32.30<1b>[0m Fitting Ridge model
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.71<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.71<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.71<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.71<1b>[0m predictors: 1, 2
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.71<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.71<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.72<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2)
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.72<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.78<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.78<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.78<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.78<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.79<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.79<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.79<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.79<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.79<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 09:13:32.80<1b>[0m Estimating performance of adjusted model in CV
> test-selective_measuring.R: <1b>[1;30m2025-12-08 09:13:32.80<1b>[0m End training
> test-selective_measuring.R: <1b>[1;30m2025-12-08 09:13:32.80<1b>[0m Scaling features by coefficients of Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-08 09:13:32.82<1b>[0m Applying PAM clustering
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.86<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-08 09:13:32.86<1b>[0m Returning adjusted frm object
> test-selective_measuring.R: <1b>[1;30m2025-12-08 09:13:33.51<1b>[0m Returning clustering results
[ FAIL 3 | WARN 3 | SKIP 0 | PASS 19 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-train_frm-gbtree.R:5:5'): train_frm works if `method == "GBTree"` ──
Error in `begin_iteration:end_iteration`: argument of length 0
Backtrace:
▆
1. └─FastRet::train_frm(...) at test-train_frm-gbtree.R:5:5
2. └─parallel::mclapply(...)
3. └─base::lapply(X, FUN, ...)
4. └─FastRet (local) FUN(X[[i]], ...)
5. └─FastRet (local) fit(df[train, ], verbose = 0)
6. └─FastRet:::fit_gbtree_grid(...)
7. └─xgboost::xgb.train(...)
── 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 3 | SKIP 0 | PASS 19 ]
Error:
! Test failures.
Execution halted
Flavor: r-oldrel-windows-x86_64
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