update g_lineplot snaps

[pawelru]

fix errors reported on ocean integration tests (both valid and nonvalid)

✖ | 2       1 | g_lineplot [2.6s]                                               
  ────────────────────────────────────────────────────────────────────────────────
  Failure ('test-g_lineplot.R:27:3'): g_lineplot works with custom settings and statistics table
  Snapshot of `testcase` to 'g_lineplot/g-lineplot-w-stats.svg' has changed
  * Download and unzip run artifact
  * Copy 'tests/testthat/_snaps/g_lineplot/g-lineplot-w-stats.new.svg' to local test directory
  * Run `testthat::snapshot_review('g_lineplot/')` to review changes
  Backtrace:
   1. vdiffr::expect_doppelganger(title = "g_lineplot_w_stats", fig = g_lineplot_w_stats)
        at test-g_lineplot.R:27:2
   3. testthat::expect_snapshot_file(...)
  
  Failure ('test-g_lineplot.R:43:3'): g_lineplot works with cohort_id specified
  Snapshot of `testcase` to 'g_lineplot/g-lineplot-cohorts.svg' has changed
  * Download and unzip run artifact
  * Copy 'tests/testthat/_snaps/g_lineplot/g-lineplot-cohorts.new.svg' to local test directory
  * Run `testthat::snapshot_review('g_lineplot/')` to review changes
  Backtrace:
   1. vdiffr::expect_doppelganger(title = "g_lineplot_cohorts", fig = g_lineplot_cohorts)
        at test-g_lineplot.R:43:2
   3. testthat::expect_snapshot_file(...)

I just re-run the tests and accepted updates for erroneous test cases. Those diffs are actually good. Interestingly I got more diff than just g-lineplot (that is: test-g_km.R and test-decorate_grob.R but those are probably due to my local setup as we don't have any other failures reported for those files so I haven't included them

[github-actions]

Code Coverage Summary

Filename                                   Stmts    Miss  Cover    Missing
---------------------------------------  -------  ------  -------  ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
R/abnormal_by_baseline.R                      68       2  97.06%   78-79
R/abnormal_by_marked.R                        55       5  90.91%   78-82
R/abnormal_by_worst_grade_worsen.R           116       3  97.41%   240-242
R/abnormal_by_worst_grade.R                   60       0  100.00%
R/abnormal.R                                  43       0  100.00%
R/analyze_variables.R                        190      10  94.74%   489-490, 506, 530, 686-687, 692-693, 711-712
R/analyze_vars_in_cols.R                     179      35  80.45%   168-169, 184, 207-212, 227, 241-242, 250-258, 264-270, 349-355
R/combination_function.R                       9       0  100.00%
R/compare_variables.R                        124      17  86.29%   131-135, 247, 325-334, 389-390, 396
R/control_incidence_rate.R                    20       8  60.00%   32-35, 38-41
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               107       4  96.26%   144-146, 149
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, 239, 254, 262, 268-269
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, 482, 588
R/fit_rsp_step.R                              36       0  100.00%
R/fit_survival_step.R                         36       0  100.00%
R/formatting_functions.R                     181       3  98.34%   145, 155, 280
R/g_forest.R                                 438      21  95.21%   199, 319, 336-337, 342-343, 356, 372, 419, 450, 526, 535, 616-620, 630, 705, 708, 832
R/g_lineplot.R                               206      34  83.50%   168, 181, 210, 236-239, 315-322, 340-341, 347-357, 449, 455, 457, 499-500, 504-505
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_logistic_regression.R                    468       3  99.36%   206-207, 276
R/h_map_for_count_abnormal.R                  57       2  96.49%   77-78
R/h_pkparam_sort.R                            15       0  100.00%
R/h_response_biomarkers_subgroups.R           76       0  100.00%
R/h_response_subgroups.R                     171      12  92.98%   257-270
R/h_stack_by_baskets.R                        67       3  95.52%   68-69, 95
R/h_step.R                                   180       0  100.00%
R/h_survival_biomarkers_subgroups.R           81       0  100.00%
R/h_survival_duration_subgroups.R            200      12  94.00%   259-271
R/imputation_rule.R                           17       2  88.24%   54-55
R/incidence_rate.R                            96       7  92.71%   44-51
R/individual_patient_plot.R                  133       0  100.00%
R/kaplan_meier_plot.R                        688      65  90.55%   236-239, 279-314, 323-327, 538, 725-727, 735-737, 769-770, 943-946, 1169, 1495-1506
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             61       0  100.00%
R/response_subgroups.R                       185       4  97.84%   267, 315-317
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                         101       1  99.01%   172
R/summarize_change.R                          30       0  100.00%
R/summarize_colvars.R                         13       2  84.62%   72-73
R/summarize_coxreg.R                         178       6  96.63%   201-202, 209, 346-347, 442
R/summarize_glm_count.R                      170      29  82.94%   160, 164-214, 259-260
R/summarize_num_patients.R                    99       9  90.91%   108-110, 160-161, 252-257
R/summarize_patients_exposure_in_cols.R       96       1  98.96%   42
R/survival_biomarkers_subgroups.R             63       0  100.00%
R/survival_coxph_pairwise.R                   76       9  88.16%   51-59
R/survival_duration_subgroups.R              184       0  100.00%
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       136       4  97.06%   72, 577-580
R/utils_factor.R                             109       2  98.17%   84, 302
R/utils_ggplot.R                              68      68  0.00%    39-125
R/utils_grid.R                               111       5  95.50%   149, 258-264
R/utils_rtables.R                            100       9  91.00%   39, 46, 51, 58-62, 403-404
R/utils_split_funs.R                          52       2  96.15%   81, 93
R/utils.R                                    137      10  92.70%   92, 94, 98, 118, 121, 124, 128, 137-138, 311
TOTAL                                       9969     593  94.05%

Diff against main

Filename      Stmts    Miss  Cover
----------  -------  ------  --------
TOTAL             0       0  +100.00%

Results for commit: 98be89b

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

[github-actions]

Unit Tests Summary

       1 files       82 suites   1m 6s ⏱️
   807 tests    782 ✔️   25 💤 0 ❌
1 709 runs  1 059 ✔️ 650 💤 0 ❌

Results for commit 98be89b.

[shajoezhu]

I thought we fixed this in 4c11291?

[pawelru]

I thought we fixed this in 4c11291?

There was a 20a84ff shortly after due to warnings in tests of that function in chevron.

Interestingly, each of those commits and also this one are green on CI of this repo. Errors where caught inside integration tests but those does not stem from integration but rather tests within a given repo. This should fail in CI 🤔

[edelarua]

Lgtm! Thanks @pawelru. I ran the tests locally and can confirm that only the g_lineplot snaps are changing for me (so your other snapshot changes are probably caused by a version discrepancy).