insightsengineering / tern

Table, Listings, and Graphs (TLG) library for common outputs used in clinical trials
https://insightsengineering.github.io/tern/
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add snaps for bland-altman function #1201

Closed ayogasekaram closed 8 months ago

ayogasekaram commented 8 months ago

closes #1175

github-actions[bot] commented 8 months ago

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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       9  95.26%   488-489, 505, 529, 685-686, 692, 710-711
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/bland_altman.R                              92       1  98.91%   37
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               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, 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       2  98.90%   145, 280
R/g_forest.R                                 569     412  27.59%   183-186, 189-192, 195-201, 204-207, 210-213, 240, 252-255, 260-261, 277, 287-290, 335-338, 345, 414, 491-1011
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           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                        67       3  95.52%   68-69, 95
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/individual_patient_plot.R                  133       0  100.00%
R/kaplan_meier_plot.R                        695      76  89.06%   254-257, 297-332, 341-345, 556, 700-701, 733, 743-745, 753-755, 780, 787-788, 961-964, 1187, 1381-1386, 1422, 1522-1533
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                         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                      195      27  86.15%   206, 224-256, 301-302
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             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       136       4  97.06%   72, 577-580
R/utils_factor.R                             109       2  98.17%   84, 302
R/utils_ggplot.R                              72       0  100.00%
R/utils_grid.R                               111       5  95.50%   149, 258-265
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                                    141      10  92.91%   92, 94, 98, 118, 121, 124, 128, 137-138, 332
TOTAL                                      10307     982  90.47%

Diff against main

Filename            Stmts    Miss  Cover
----------------  -------  ------  -------
R/bland_altman.R        0     -54  +58.70%
TOTAL                   0     -54  +0.52%

Results for commit: 57bdafca688af2e8a1913b2f68fc667c6eb2b6fa

Minimum allowed coverage is 80%

:recycle: This comment has been updated with latest results

github-actions[bot] commented 8 months ago

Unit Test Performance Difference

Additional test case details | Test Suite | $Status$ | Time on `main` | $±Time$ | Test Case | |:-----|:----:|:----:|:----:|:-----| | bland-altman | 👶 | | $+0.04$ | g_bland_altman_works_with_default_settings | | bland-altman | 👶 | | $+0.01$ | s_bland_altman_works_with_default_settings |

Results for commit 71bfa4b69537e93c5ba7914d3e72c1697801357c

♻️ This comment has been updated with latest results.

github-actions[bot] commented 8 months ago

Unit Tests Summary

    1 files     83 suites   1m 1s :stopwatch:   823 tests   795 :white_check_mark:  28 :zzz: 0 :x: 1 733 runs  1 071 :white_check_mark: 662 :zzz: 0 :x:

Results for commit 57bdafca.

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

ayogasekaram commented 8 months ago

@Melkiades great point. the g_bland_altman function only calls base colours - not the nestcolors package. The with_options is setup for this test like the other graphs so I think it should be okay but I can remove it if it fails the integration tests :)