Batch 1 #1403

Melkiades · 2025-02-28T17:59:27Z

Fixes part of #1381 and #1249 and #1390

Melkiades

@edelarua I think we can merge this, your PR and then refactor riskdiff if we deem it necessary. I think the behavior there is strange. I would prefer adding a subfunction to a_* functions to deal with that cases. I manage to get a weird hybrid on the other PR but it is better to have a clean slate with most recent updates

github-actions · 2025-02-28T18:59:36Z

Unit Tests Summary

1 files 85 suites 1m 17s ⏱️
878 tests 868 ✅ 10 💤 0 ❌
1 907 runs 1 210 ✅ 697 💤 0 ❌

Results for commit fb453fb.

♻️ This comment has been updated with latest results.

github-actions · 2025-02-28T18:59:41Z

Unit Test Performance Difference

Additional test case details

Test Suite	$Status$	Time on `main`	$±Time$	Test Case
count_cumulative	👶		$+0.05$	Testing_label_behavior_when_s__forecasts_label_attributes
count_missed_doses	💀	$0.02$	$-0.02$	s_count_nonmissing_also_works_with_character_input
count_missed_doses	💀	$0.02$	$-0.02$	s_count_nonmissing_works_with_numeric_input

Results for commit 82ad2e8

♻️ This comment has been updated with latest results.

github-actions · 2025-03-03T15:45:49Z

Code Coverage Summary

Filename                                   Stmts    Miss  Cover    Missing
---------------------------------------  -------  ------  -------  ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
R/abnormal_by_baseline.R                     101       3  97.03%   242, 244-245
R/abnormal_by_marked.R                        88       8  90.91%   94-98, 281, 283-284
R/abnormal_by_worst_grade.R                   94       3  96.81%   215, 217-218
R/abnormal_lab_worsen_by_baseline.R          159      10  93.71%   205-208, 213, 215-216, 459-461
R/abnormal.R                                  78       2  97.44%   222, 224
R/analyze_variables.R                        287       5  98.26%   587-590, 778
R/analyze_vars_in_cols.R                     178      14  92.13%   178, 221, 235-236, 238, 246-254
R/bland_altman.R                              92       1  98.91%   46
R/combination_function.R                       9       0  100.00%
R/compare_variables.R                         35       0  100.00%
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                         115       4  96.52%   74, 270-271, 273
R/count_missed_doses.R                        89       4  95.51%   206-209
R/count_occurrences_by_grade.R               163       5  96.93%   178, 386, 388, 465, 467
R/count_occurrences.R                        131       8  93.89%   119, 262-264, 330-333
R/count_patients_events_in_cols.R             67       1  98.51%   60
R/count_patients_with_event.R                 73       2  97.26%   220, 223
R/count_patients_with_flags.R                 93       2  97.85%   234, 236
R/count_values.R                              61       2  96.72%   193, 196
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                  86       4  95.35%   65, 212, 214-215
R/estimate_proportion.R                      229       7  96.94%   84, 95, 236, 238-239, 370, 536
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%   141, 276
R/g_forest.R                                 585      60  89.74%   240, 252-255, 260-261, 275, 277, 287-290, 335-338, 345, 414, 501, 514, 518-519, 524-525, 538, 554, 601, 630, 705, 714, 720, 739, 794-814, 817, 828, 847, 902, 905, 1040-1045
R/g_ipp.R                                    133       0  100.00%
R/g_km.R                                     350      57  83.71%   285-288, 307-309, 363-366, 400, 428, 432-475, 482-486
R/g_lineplot.R                               260      22  91.54%   204, 378-385, 424-434, 543, 551
R/g_step.R                                    68       1  98.53%   108
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                    91      23  74.73%   40-42, 84-103
R/h_cox_regression.R                         110       0  100.00%
R/h_incidence_rate.R                          45       0  100.00%
R/h_km.R                                     509      41  91.94%   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           77      12  84.42%   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           73       6  91.78%   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                           103       7  93.20%   68-73, 242
R/logistic_regression.R                      102       0  100.00%
R/missing_data.R                              21       3  85.71%   32, 66, 76
R/odds_ratio.R                               157       4  97.45%   270-273
R/prop_diff_test.R                           144       2  98.61%   230, 232
R/prop_diff.R                                318      17  94.65%   71-74, 106, 299, 301, 373-380, 523, 688
R/prune_occurrences.R                         57       0  100.00%
R/response_biomarkers_subgroups.R            124      10  91.94%   88-91, 270-275
R/response_subgroups.R                       247      16  93.52%   100-105, 271-275, 280, 282-283, 310-311
R/riskdiff.R                                  65       4  93.85%   94-97
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                         142       2  98.59%   316-317
R/summarize_change.R                          71       3  95.77%   175, 177-178
R/summarize_colvars.R                         13       1  92.31%   75
R/summarize_coxreg.R                         172       0  100.00%
R/summarize_glm_count.R                      269      10  96.28%   129-130, 202-203, 459-463, 596
R/summarize_num_patients.R                   115       9  92.17%   122-124, 244-245, 247, 329-330, 332
R/summarize_patients_exposure_in_cols.R      155       7  95.48%   58, 232-233, 237, 357-358, 362
R/survival_biomarkers_subgroups.R            136      10  92.65%   117-122, 228-231
R/survival_coxph_pairwise.R                  124       5  95.97%   52-53, 248, 250-251
R/survival_duration_subgroups.R              245      15  93.88%   124-129, 268-273, 286, 288-289
R/survival_time.R                            120       1  99.17%   251
R/survival_timepoint.R                       153       2  98.69%   302, 304
R/utils_checkmate.R                           68       0  100.00%
R/utils_default_stats_formats_labels.R       186       0  100.00%
R/utils_factor.R                              87       1  98.85%   99
R/utils_ggplot.R                             110       0  100.00%
R/utils_grid.R                               126       5  96.03%   164, 279-286
R/utils_rtables.R                            125       9  92.80%   39, 46, 405-406, 528-532
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                                      11908     574  95.18%

Diff against main

Filename                                  Stmts    Miss  Cover
--------------------------------------  -------  ------  --------
R/count_cumulative.R                        +56      +3  -1.78%
R/count_missed_doses.R                      +53      +4  -4.49%
R/prop_diff_test.R                          +53      +2  -1.39%
R/prop_diff.R                               +53      +2  +0.31%
R/utils_default_stats_formats_labels.R       +8       0  +100.00%
TOTAL                                      +223     +11  -0.00%

Results for commit: 60bc5c0

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

edelarua

Hi @Melkiades,

Great work!! I just have a few comments/suggestions but otherwise everything looks good :)

R/count_cumulative.R

R/count_missed_doses.R

R/prop_diff.R

R/prop_diff_test.R

R/count_missed_doses.R

R/count_cumulative.R

R/utils_default_stats_formats_labels.R

tests/testthat/test-count_cumulative.R

R/utils_default_stats_formats_labels.R

edelarua

This looks good to me! Just one typo I saw but otherwise whenever you're ready you can test on scda.test & then merge.

R/utils_default_stats_formats_labels.R

Co-authored-by: Emily de la Rua <emily.de_la_rua@contractors.roche.com> Signed-off-by: Davide Garolini <dgarolini@gmail.com>

Melkiades added 2 commits February 28, 2025 18:55

init

7a10d3f

test correction

b997596

Melkiades added the sme label Feb 28, 2025

This was linked to issues Feb 28, 2025

export tern:::as_factor_keep_attributes #1249

Closed

R CMD CHECK note #1390

Closed

[skip roxygen] [skip vbump] Roxygen Man Pages Auto Update

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Melkiades commented Feb 28, 2025

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Melkiades added 3 commits February 28, 2025 19:08

news

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fixes

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fix snaps

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edelarua and others added 2 commits February 28, 2025 16:50

Merge branch 'main' into 1381_batch_1_no_riskdiff@main

17f409e

fix

5c71300

Melkiades requested a review from edelarua March 3, 2025 17:01

add

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Melkiades changed the title ~~Batch 1 initial part~~ Batch 1 Mar 4, 2025

Melkiades added 2 commits March 4, 2025 11:57

fix lint

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fix

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edelarua requested changes Mar 5, 2025

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Melkiades and others added 3 commits March 5, 2025 10:06

changes after review

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Merge branch 'main' into 1381_batch_1_no_riskdiff@main

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fix

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Melkiades commented Mar 7, 2025

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Melkiades commented Mar 7, 2025

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edelarua approved these changes Mar 7, 2025

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Melkiades and others added 2 commits March 10, 2025 16:22

Apply suggestions from code review

60bc5c0

Co-authored-by: Emily de la Rua <emily.de_la_rua@contractors.roche.com> Signed-off-by: Davide Garolini <dgarolini@gmail.com>

fix

fb453fb

Melkiades enabled auto-merge (squash) March 10, 2025 15:41

Melkiades merged commit 2f31365 into main Mar 10, 2025
27 checks passed

Melkiades deleted the 1381_batch_1_no_riskdiff@main branch March 10, 2025 15:50

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edelarua linked an issue Mar 10, 2025 that may be closed by this pull request

Retire make_afun() - Batch 1 #1381

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