resolve green ci

[shajoezhu]

close #1282

[github-actions[bot]]

Unit Tests Summary

    1 files     83 suites   1m 11s :stopwatch:   851 tests   839 :white_check_mark:  12 :zzz: 0 :x: 1 828 runs  1 150 :white_check_mark: 678 :zzz: 0 :x:

Results for commit a1e53fcb.

:recycle: This comment has been updated with latest results.

[github-actions[bot]]

Unit Test Performance Difference

Test Suite	$Status$	Time on main	$±Time$	$±Tests$	$±Skipped$	$±Failures$	$±Errors$
analyze_vars_in_cols	💔	$2.38$	$+3.22$	$+17$	$-7$	$0$	$0$
count_occurrences	💔	$0.72$	$+1.60$	$+10$	$-8$	$0$	$0$
summarize_coxreg	💔	$3.09$	$+2.39$	$+13$	$-13$	$0$	$0$
summarize_num_patients	💔	$1.02$	$+1.37$	$+18$	$-16$	$0$	$0$
utils_rtables	💔	$3.18$	$+1.15$	$+16$	$-19$	$0$	$0$

Additional test case details

| Test Suite | $Status$ | Time on `main` | $±Time$ | Test Case | |:-----|:----:|:----:|:----:|:-----| | analyze_vars_in_cols | 💔 | $0.47$ | $+1.46$ | summarize_works_with_nested_analyze |

Results for commit 00f21333697f56b2e059638e27a64de64f2508c8

♻️ This comment has been updated with latest results.

[github-actions[bot]]

Code Coverage Summary

Filename                                   Stmts    Miss  Cover    Missing
---------------------------------------  -------  ------  -------  ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
R/abnormal_by_baseline.R                      65       0  100.00%
R/abnormal_by_marked.R                        55       5  90.91%   92-96
R/abnormal_by_worst_grade_worsen.R           116       3  97.41%   262-264
R/abnormal_by_worst_grade.R                   60       0  100.00%
R/abnormal.R                                  43       0  100.00%
R/analyze_variables.R                        166       2  98.80%   492, 632
R/analyze_vars_in_cols.R                     176      13  92.61%   178, 221, 235-236, 244-252
R/bland_altman.R                              92       1  98.91%   43
R/combination_function.R                       9       0  100.00%
R/compare_variables.R                         84       2  97.62%   255, 314
R/control_incidence_rate.R                    10       0  100.00%
R/control_logistic.R                           7       0  100.00%
R/control_step.R                              23       1  95.65%   58
R/control_survival.R                          15       0  100.00%
R/count_cumulative.R                          50       1  98.00%   73
R/count_missed_doses.R                        34       0  100.00%
R/count_occurrences_by_grade.R               113       1  99.12%   166
R/count_occurrences.R                        115       1  99.13%   115
R/count_patients_events_in_cols.R             67       1  98.51%   59
R/count_patients_with_event.R                 47       0  100.00%
R/count_patients_with_flags.R                 58       0  100.00%
R/count_values.R                              27       0  100.00%
R/cox_regression_inter.R                     154       0  100.00%
R/cox_regression.R                           161       0  100.00%
R/coxph.R                                    167       7  95.81%   191-195, 238, 253, 261, 267-268
R/d_pkparam.R                                406       0  100.00%
R/decorate_grob.R                            113       0  100.00%
R/desctools_binom_diff.R                     621      64  89.69%   53, 88-89, 125-126, 129, 199, 223-232, 264, 266, 286, 290, 294, 298, 353, 356, 359, 362, 422, 430, 439, 444-447, 454, 457, 466, 469, 516-517, 519-520, 522-523, 525-526, 593, 604-616, 620, 663, 676, 680
R/df_explicit_na.R                            30       0  100.00%
R/estimate_multinomial_rsp.R                  50       1  98.00%   64
R/estimate_proportion.R                      205      11  94.63%   82-89, 93, 98, 319, 485
R/fit_rsp_step.R                              36       0  100.00%
R/fit_survival_step.R                         36       0  100.00%
R/formatting_functions.R                     183       2  98.91%   143, 278
R/g_forest.R                                 585      59  89.91%   241, 253-256, 261-262, 278, 288-291, 336-339, 346, 415, 502, 515, 519-520, 525-526, 539, 555, 602, 633, 708, 717, 723, 742, 797-817, 820, 831, 850, 905, 908, 1043-1048
R/g_ipp.R                                    133       0  100.00%
R/g_km.R                                     350      57  83.71%   286-289, 308-310, 364-367, 401, 429, 433-476, 483-487
R/g_lineplot.R                               243      22  90.95%   196, 370-377, 416-426, 518, 526
R/g_step.R                                    68       1  98.53%   109
R/g_waterfall.R                               47       0  100.00%
R/h_adsl_adlb_merge_using_worst_flag.R        73       0  100.00%
R/h_biomarkers_subgroups.R                    46       0  100.00%
R/h_cox_regression.R                         110       0  100.00%
R/h_km.R                                     508      41  91.93%   137, 189-194, 287, 378, 380-381, 392-394, 413, 420-421, 423-425, 433-435, 460, 465-468, 651-654, 1108-1119
R/h_logistic_regression.R                    468       3  99.36%   203-204, 273
R/h_map_for_count_abnormal.R                  54       0  100.00%
R/h_pkparam_sort.R                            15       0  100.00%
R/h_response_biomarkers_subgroups.R           90      12  86.67%   50-55, 107-112
R/h_response_subgroups.R                     178      18  89.89%   257-270, 329-334
R/h_stack_by_baskets.R                        64       1  98.44%   89
R/h_step.R                                   180       0  100.00%
R/h_survival_biomarkers_subgroups.R           88       6  93.18%   111-116
R/h_survival_duration_subgroups.R            207      18  91.30%   259-271, 336-341
R/imputation_rule.R                           17       0  100.00%
R/incidence_rate.R                           100       7  93.00%   47-54
R/logistic_regression.R                      102       0  100.00%
R/missing_data.R                              21       3  85.71%   32, 66, 76
R/odds_ratio.R                               109       0  100.00%
R/prop_diff_test.R                            91       0  100.00%
R/prop_diff.R                                265      15  94.34%   69-72, 104, 289-296, 439, 604
R/prune_occurrences.R                         57       0  100.00%
R/response_biomarkers_subgroups.R             69       6  91.30%   196-201
R/response_subgroups.R                       213       8  96.24%   100-105, 260-261
R/riskdiff.R                                  65       5  92.31%   102-105, 114
R/rtables_access.R                            38       0  100.00%
R/score_occurrences.R                         20       1  95.00%   124
R/split_cols_by_groups.R                      49       0  100.00%
R/stat.R                                      59       0  100.00%
R/summarize_ancova.R                         106       2  98.11%   182, 187
R/summarize_change.R                          30       0  100.00%
R/summarize_colvars.R                         10       0  100.00%
R/summarize_coxreg.R                         172       0  100.00%
R/summarize_glm_count.R                      209       3  98.56%   192-193, 489
R/summarize_num_patients.R                    94       4  95.74%   116-118, 265
R/summarize_patients_exposure_in_cols.R       96       1  98.96%   55
R/survival_biomarkers_subgroups.R             78       6  92.31%   117-122
R/survival_coxph_pairwise.R                   79      11  86.08%   50-51, 63-71
R/survival_duration_subgroups.R              211       6  97.16%   124-129
R/survival_time.R                             79       0  100.00%
R/survival_timepoint.R                       113       7  93.81%   124-130
R/utils_checkmate.R                           68       0  100.00%
R/utils_default_stats_formats_labels.R       124       0  100.00%
R/utils_factor.R                             109       2  98.17%   84, 302
R/utils_ggplot.R                             110       0  100.00%
R/utils_grid.R                               126       5  96.03%   164, 279-286
R/utils_rtables.R                            100       4  96.00%   39, 46, 403-404
R/utils_split_funs.R                          52       2  96.15%   82, 94
R/utils.R                                    141       7  95.04%   118, 121, 124, 128, 137-138, 332
TOTAL                                      10483     459  95.62%

Diff against main

Filename        Stmts    Miss  Cover
------------  -------  ------  -------
R/g_forest.R        0      -1  +0.17%
TOTAL               0      -1  +0.01%

Results for commit: a1e53fcb2f23fc3dc392c149aaa5ebe6c5d42ae8

Minimum allowed coverage is 80%

:recycle: This comment has been updated with latest results

[shajoezhu]

I don't really want to drop "nestcolor::theme_nest()" from the g_lineplot default option, reason being this is primarily used by roche, and the nest default values are set for a reason,

I don't want to replace the usage of nestcolor either, feel like this is going backwards, and adding code that we have to maintain in tern ...

one possibility is to move nestcolor from suggests to import @pawelru @khatril , what do you guys think?

[pawelru]

so my comment was only about individual unit test I'm totally with you when it comes to the examples and the functionality as a whole

[shajoezhu]

block this PR by https://github.com/insightsengineering/tern/pull/1311

[shajoezhu]

let's merge this in, and come back to resolve the green ci issue in future PRs