add faceting variable to g_lineplot. add code to maintain factor levels. #1226

ayogasekaram · 2024-04-12T22:01:11Z

github-actions · 2024-04-12T22:07:41Z

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%   78-82
R/abnormal_by_worst_grade_worsen.R           116       3  97.41%   242-244
R/abnormal_by_worst_grade.R                   60       0  100.00%
R/abnormal.R                                  43       0  100.00%
R/analyze_variables.R                        162       3  98.15%   488, 512, 628
R/analyze_vars_in_cols.R                     176      33  81.25%   179, 202-207, 222, 236-237, 245-253, 259-265, 344-350
R/bland_altman.R                              92       1  98.91%   43
R/combination_function.R                       9       0  100.00%
R/compare_variables.R                         84       5  94.05%   130-134, 246, 305
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%   67
R/count_missed_doses.R                        34       0  100.00%
R/count_occurrences_by_grade.R               113       5  95.58%   101, 151-153, 156
R/count_occurrences.R                        115       1  99.13%   108
R/count_patients_events_in_cols.R             67       1  98.51%   53
R/count_patients_with_event.R                 47       0  100.00%
R/count_patients_with_flags.R                 58       4  93.10%   56-57, 62-63
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                            173      40  76.88%   235-266, 326-328, 339, 360-397
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%   63
R/estimate_proportion.R                      205      12  94.15%   78-85, 89, 94, 315, 481, 587
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     429  26.67%   184-187, 190-193, 196-202, 205-208, 211-214, 241, 253-256, 261-262, 276, 278, 288-291, 336-339, 346, 415, 495-1048
R/g_ipp.R                                    133       0  100.00%
R/g_km.R                                     350      57  83.71%   288-291, 310-312, 366-369, 403, 431, 435-478, 485-489
R/g_lineplot.R                               224      34  84.82%   175, 188, 224, 257-260, 336-343, 361-362, 373-383, 475, 481, 483, 532-533, 537-538
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                    45       0  100.00%
R/h_cox_regression.R                         110       0  100.00%
R/h_km.R                                     509     352  30.84%   137, 189-194, 287, 368-1005, 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       2  88.24%   54-55
R/incidence_rate.R                            96       7  92.71%   44-51
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      16  93.96%   62-65, 97, 282-289, 432, 492, 597
R/prune_occurrences.R                         57      10  82.46%   138-142, 188-192
R/response_biomarkers_subgroups.R             68       6  91.18%   189-194
R/response_subgroups.R                       192      10  94.79%   95-100, 276, 324-326
R/riskdiff.R                                  59       7  88.14%   102-105, 114, 124-125
R/rtables_access.R                            38       4  89.47%   159-162
R/score_occurrences.R                         20       1  95.00%   124
R/split_cols_by_groups.R                      49       0  100.00%
R/stat.R                                      59       3  94.92%   73-74, 129
R/summarize_ancova.R                         104       2  98.08%   172, 177
R/summarize_change.R                          30       0  100.00%
R/summarize_colvars.R                         10       0  100.00%
R/summarize_coxreg.R                         172       2  98.84%   203, 430
R/summarize_glm_count.R                      195      27  86.15%   206, 224-256, 301-302
R/summarize_num_patients.R                    93       5  94.62%   108-110, 244-245
R/summarize_patients_exposure_in_cols.R       96       1  98.96%   42
R/survival_biomarkers_subgroups.R             70       6  91.43%   112-117
R/survival_coxph_pairwise.R                   79      11  86.08%   45-46, 58-66
R/survival_duration_subgroups.R              191       6  96.86%   119-124
R/survival_time.R                             79       0  100.00%
R/survival_timepoint.R                       113       7  93.81%   120-126
R/utils_checkmate.R                           68       0  100.00%
R/utils_default_stats_formats_labels.R       116       1  99.14%   72
R/utils_factor.R                             109       2  98.17%   84, 302
R/utils_ggplot.R                             110       1  99.09%   54
R/utils_grid.R                               126       5  96.03%   164, 279-286
R/utils_rtables.R                            100       9  91.00%   39, 46, 51, 58-62, 403-404
R/utils_split_funs.R                          52       2  96.15%   82, 94
R/utils.R                                    141      10  92.91%   92, 94, 98, 118, 121, 124, 128, 137-138, 332
TOTAL                                      10435    1286  87.68%

Diff against main

Filename          Stmts    Miss  Cover
--------------  -------  ------  -------
R/g_lineplot.R      +15       0  +1.09%
TOTAL               +15       0  +0.02%

Results for commit: 867d907

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

github-actions · 2024-04-12T22:10:24Z

Unit Test Performance Difference

Additional test case details

Test Suite	$Status$	Time on `main`	$±Time$	Test Case
g_lineplot	👶		$+0.24$	g_lineplot_works_with_facet_var_specified

Results for commit df8e348

♻️ This comment has been updated with latest results.

github-actions · 2024-04-15T20:40:37Z

CLA Assistant Lite bot ✅ All contributors have signed the CLA

edelarua · 2024-04-15T20:42:30Z

I have read the CLA Document and I hereby sign the CLA

github-actions · 2024-04-15T20:48:00Z

Unit Tests Summary

1 files 83 suites 1m 10s ⏱️
825 tests 792 ✅ 33 💤 0 ❌
1 743 runs 1 074 ✅ 669 💤 0 ❌

Results for commit 867d907.

♻️ This comment has been updated with latest results.

edelarua

Hi @ayogasekaram,

Thanks for working on this! I generated the updated test snapshots so we can compare the results. It looks pretty good so far, just a few questions from me:

I'm not sure if this is a problem, but I think something you changed affected the y limits (which caused a slight change to 2 of the snapshots). Was this intentional?
Now that there is an option to facet, plots could potentially be much more squished together horizontally (which you can see in the new test snapshot). Do you think we should also add a parameter to rotate the x-axis labels for in these cases?

ayogasekaram · 2024-04-16T12:49:25Z

I have read the CLA Document and I hereby sign the CLA

…entation.

edelarua

Lgtm!

legrasv · 2024-04-16T14:01:13Z

Approved.

add faceting variable to g_lineplot. add code to maintain factor levels.

40cbd9a

ayogasekaram added the sme label Apr 12, 2024

[skip style] [skip vbump] Restyle files

dd511fc

ayogasekaram requested a review from legrasv April 12, 2024 22:07

shajoezhu mentioned this pull request Apr 15, 2024

preping new cran release 0.9.4 #1205

Closed

34 tasks

Update test snapshots, doc fix

56f9ac6

edelarua self-requested a review April 15, 2024 20:40

Merge branch 'main' into 1212_update_legend@main

9e92526

edelarua requested changes Apr 15, 2024

View reviewed changes

ayogasekaram added 3 commits April 16, 2024 13:36

update to pass lint check. add facet_var to control_line_plot docum…

3f337dd

…entation.

change for lint check

a1abfd7

add nolint

867d907

edelarua approved these changes Apr 16, 2024

View reviewed changes

legrasv closed this Apr 16, 2024

github-actions bot locked and limited conversation to collaborators Apr 16, 2024

legrasv reopened this Apr 16, 2024

ayogasekaram merged commit 5561946 into main Apr 16, 2024
55 checks passed

ayogasekaram deleted the 1212_update_legend@main branch April 16, 2024 15:08

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add faceting variable to g_lineplot. add code to maintain factor levels. #1226

add faceting variable to g_lineplot. add code to maintain factor levels. #1226

ayogasekaram commented Apr 12, 2024

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legrasv commented Apr 16, 2024

add faceting variable to g_lineplot. add code to maintain factor levels. #1226

add faceting variable to g_lineplot. add code to maintain factor levels. #1226

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Code Coverage Summary

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Unit Test Performance Difference

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