Last updated on 2025-12-07 07:50:45 CET.
| Package | ERROR | WARN | NOTE | OK |
|---|---|---|---|---|
| FastRet | 5 | 8 | ||
| metabodecon | 1 | 3 | 9 | |
| toscmask | 13 | |||
| toscutil | 1 | 12 |
Current CRAN status: ERROR: 5, OK: 8
Version: 1.1.4
Check: package dependencies
Result: ERROR
Packages required but not available: 'DT', 'rcdk', 'shinybusy', 'xlsx'
Packages suggested but not available for checking:
'devtools', 'knitr', 'languageserver', 'lintr', 'pkgdown',
'rmarkdown', 'usethis'
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’ [65s/142s]
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 11:34:54.34<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-03 11:34:54.35<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-03 11:34:56.18<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-03 11:34:56.18<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-03 11:34:56.26<1b>[0m Starting model Adjustment
> test-plot_frm.R: <1b>[1;30m2025-12-03 11:34:56.26<1b>[0m dim(original_data): 442 x 126
> test-plot_frm.R: <1b>[1;30m2025-12-03 11:34:56.26<1b>[0m dim(new_data): 25 x 3
> test-plot_frm.R: <1b>[1;30m2025-12-03 11:34:57.05<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-plot_frm.R: <1b>[1;30m2025-12-03 11:34:57.05<1b>[0m nfolds: 5
> test-plot_frm.R: <1b>[1;30m2025-12-03 11:34:57.05<1b>[0m Preprocessing data
> test-plot_frm.R: <1b>[1;30m2025-12-03 11:34:57.14<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 11:34:57.16<1b>[0m Estimating performance of adjusted model in CV
> test-plot_frm.R: <1b>[1;30m2025-12-03 11:34:57.66<1b>[0m Fitting adjustment model on full new data set
> test-plot_frm.R: <1b>[1;30m2025-12-03 11:34:57.68<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:58.80<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:58.82<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:58.82<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:58.82<1b>[0m predictors: 1, 2
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:58.82<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:58.82<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:58.87<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2)
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:58.89<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:59.24<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:59.27<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:59.27<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:59.27<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:59.27<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:59.27<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:59.27<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:59.27<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:34:59.35<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 11:34:59.37<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:35:00.33<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-03 11:35:00.37<1b>[0m Returning adjusted frm object
> test-selective_measuring.R: <1b>[1;30m2025-12-03 11:35:01.45<1b>[0m Starting Selective Measuring
> test-selective_measuring.R: <1b>[1;30m2025-12-03 11:35:01.45<1b>[0m Preprocessing input data
> test-selective_measuring.R: <1b>[1;30m2025-12-03 11:35:01.45<1b>[0m Mocking is enabled for 'preprocess_data'. Returning 'mockdata/RPCD_prepro.rds'.
> test-selective_measuring.R: <1b>[1;30m2025-12-03 11:35:01.48<1b>[0m Standardizing features
> test-selective_measuring.R: <1b>[1;30m2025-12-03 11:35:01.52<1b>[0m Training Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-03 11:35:01.53<1b>[0m Fitting Ridge model
> test-selective_measuring.R: <1b>[1;30m2025-12-03 11:35:04.75<1b>[0m End training
> test-selective_measuring.R: <1b>[1;30m2025-12-03 11:35:04.76<1b>[0m Scaling features by coefficients of Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-03 11:35:05.04<1b>[0m Applying PAM clustering
> test-selective_measuring.R: <1b>[1;30m2025-12-03 11:35:10.56<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’ [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' [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
> 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:
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.12<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.12<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
Saving _problems/test-fit_gbtree-8.R
Saving _problems/test-fit_gbtree-16.R
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.39<1b>[0m Starting training of a lasso model
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.39<1b>[0m Parallel processing is not supported on Windows. Setting `nw` to 1.
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.39<1b>[0m Mocking is enabled. Returning 'mockdata/lasso_model.rds'
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.40<1b>[0m Starting model Adjustment
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.40<1b>[0m dim(original_data): 442 x 126
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.40<1b>[0m dim(new_data): 25 x 3
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.53<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.53<1b>[0m nfolds: 5
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.53<1b>[0m Preprocessing data
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.56<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.57<1b>[0m Estimating performance of adjusted model in CV
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.65<1b>[0m Fitting adjustment model on full new data set
> test-plot_frm.R: <1b>[1;30m2025-12-05 07:38:19.66<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;30m2025-12-05 07:38:20.35<1b>[0m Starting Selective Measuring
> test-selective_measuring.R: <1b>[1;30m2025-12-05 07:38:20.35<1b>[0m Preprocessing input data
> test-selective_measuring.R: <1b>[1;30m2025-12-05 07:38:20.35<1b>[0m Mocking is enabled for 'preprocess_data'. Returning 'mockdata/RPCD_prepro.rds'.
> test-selective_measuring.R: <1b>[1;30m2025-12-05 07:38:20.35<1b>[0m Standardizing features
> test-selective_measuring.R: <1b>[1;30m2025-12-05 07:38:20.36<1b>[0m Training Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-05 07:38:20.36<1b>[0m Fitting Ridge model
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.73<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.73<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.73<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.73<1b>[0m predictors: 1, 2
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.73<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.73<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.74<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2)
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.74<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.83<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.83<1b>[0m Returning adjusted frm object
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.83<1b>[0m Starting model Adjustment
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.83<1b>[0m dim(original_data): 442 x 126
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.83<1b>[0m dim(new_data): 25 x 3
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.83<1b>[0m predictors: 1, 2, 3, 4, 5, 6
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.83<1b>[0m nfolds: 5
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.83<1b>[0m Preprocessing data
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.84<1b>[0m Formula: RT_ADJ ~ RT + I(RT^2) + I(RT^3) + log(RT) + exp(RT) + sqrt(RT)
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.84<1b>[0m Estimating performance of adjusted model in CV
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.91<1b>[0m Fitting adjustment model on full new data set
> test-adjust_frm.R: <1b>[1;30m2025-12-05 07:38:20.91<1b>[0m Returning adjusted frm object
> test-selective_measuring.R: <1b>[1;30m2025-12-05 07:38:21.00<1b>[0m End training
> test-selective_measuring.R: <1b>[1;30m2025-12-05 07:38:21.00<1b>[0m Scaling features by coefficients of Ridge Regression model
> test-selective_measuring.R: <1b>[1;30m2025-12-05 07:38:21.01<1b>[0m Applying PAM clustering
> test-selective_measuring.R: <1b>[1;30m2025-12-05 07:38:21.62<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
Current CRAN status: WARN: 1, NOTE: 3, OK: 9
Version: 1.6.2
Check: package dependencies
Result: WARN
Cannot process vignettes
Packages suggested but not available for checking:
'covr', 'devtools', 'knitr', 'mdrb', 'rmarkdown', 'usethis'
VignetteBuilder package required for checking but not installed: ‘knitr’
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.6.2
Check: package vignettes
Result: NOTE
Package has ‘vignettes’ subdirectory but apparently no vignettes.
Perhaps the ‘VignetteBuilder’ information is missing from the
DESCRIPTION file?
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.6.2
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘mdrb’
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Current CRAN status: OK: 13
Current CRAN status: ERROR: 1, OK: 12
Version: 2.8.0
Check: examples
Result: ERROR
Running examples in ‘toscutil-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: update_docstring
> ### Title: Update docstring for a Function
> ### Aliases: update_docstring
> ### Keywords: doc
>
> ### ** Examples
>
> uri <- system.file("testfiles/funcs.R", package = "toscutil")
> func <- "f4"
> update_docstring(uri, func)
Error in get_formals(uri, content, func) :
Package 'languageserver' is required for parsing formals. Please install first.
Calls: update_docstring -> get_formals
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 2.8.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [1s/2s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(toscutil)
>
> test_check("toscutil")
Saving _problems/test-update_docstring-4.R
[ FAIL 1 | WARN 0 | SKIP 0 | PASS 45 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-update_docstring.R:4:5'): update_docstring works ───────────────
Error in `get_formals(uri, content, func)`: Package 'languageserver' is required for parsing formals. Please install first.
Backtrace:
▆
1. └─toscutil::update_docstring(uri, "f2") at test-update_docstring.R:4:5
2. └─toscutil::get_formals(uri, content, func)
[ FAIL 1 | WARN 0 | SKIP 0 | PASS 45 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc