Decorators: Accepts new snapshot from testthat::test() (#1304)

# Pull Request

<!--- Replace `#nnn` with your issue link for reference. -->

Part of
insightsengineering/teal#1371 (comment)

### Changes description

- Tracks changes in the template code of the decorators feature branch
- Renames variables to be `plot`, `table` or (in case of multiple
decoratable elements) `<name>_plot` and `<name>_table`

### Workflow

Manually triggered:
https://github.com/insightsengineering/teal.modules.clinical/actions/runs/12359120026

[![Check
🛠](https://github.com/insightsengineering/teal.modules.clinical/actions/workflows/check.yaml/badge.svg?branch=snapshots%401187_decorate_output%40main)](https://github.com/insightsengineering/teal.modules.clinical/actions/workflows/check.yaml)

tests/testthat/_snaps/tm_a_gee.md

@@ -13,9 +13,9 @@
       
       $table
       {
-          result_table <- tern.gee::as.rtable(model_fit, type = "cov")
-          subtitles(result_table) <- NULL
-          main_footer(result_table) <- NULL
+          table <- tern.gee::as.rtable(model_fit, type = "cov")
+          subtitles(table) <- NULL
+          main_footer(table) <- NULL
       }
       
 
@@ -34,9 +34,9 @@
       
       $table
       {
-          result_table <- tern.gee::as.rtable(data.frame(Coefficient = model_fit$coefficients))
-          subtitles(result_table) <- NULL
-          main_footer(result_table) <- NULL
+          table <- tern.gee::as.rtable(data.frame(Coefficient = model_fit$coefficients))
+          subtitles(table) <- NULL
+          main_footer(table) <- NULL
       }
       
 
@@ -56,13 +56,12 @@
       $table
       {
           lsmeans_fit_model <- tern.gee::lsmeans(model_fit, 0.95)
-          result_table <- rtables::basic_table(show_colcounts = TRUE) %>% 
+          table <- rtables::basic_table(show_colcounts = TRUE) %>% 
               rtables::split_cols_by(var = "ARM", ref_group = model_fit$ref_level) %>% 
               tern.gee::summarize_gee_logistic() %>% rtables::build_table(df = lsmeans_fit_model, 
               alt_counts_df = ANL_ADSL)
-          subtitles(result_table) <- NULL
-          main_footer(result_table) <- NULL
-          result_table
+          subtitles(table) <- NULL
+          main_footer(table) <- NULL
       }
       
 
@@ -82,13 +81,12 @@
       $table
       {
           lsmeans_fit_model <- tern.gee::lsmeans(model_fit, 0.95)
-          result_table <- rtables::basic_table(show_colcounts = TRUE) %>% 
+          table <- rtables::basic_table(show_colcounts = TRUE) %>% 
               rtables::split_cols_by(var = "ARM", ref_group = model_fit$ref_level) %>% 
               tern.gee::summarize_gee_logistic() %>% rtables::build_table(df = lsmeans_fit_model, 
               alt_counts_df = ANL_ADSL)
-          subtitles(result_table) <- NULL
-          main_footer(result_table) <- NULL
-          result_table
+          subtitles(table) <- NULL
+          main_footer(table) <- NULL
       }
       
 

tests/testthat/_snaps/tm_a_mmrm.md

@@ -62,9 +62,8 @@
       
       $cov_matrix
       {
-          cov_matrix <- tern.mmrm::as.rtable(fit_mmrm, type = "cov")
-          subtitles(cov_matrix) <- NULL
-          cov_matrix
+          covariance_table <- tern.mmrm::as.rtable(fit_mmrm, type = "cov")
+          subtitles(covariance_table) <- NULL
       }
       
 
@@ -80,9 +79,8 @@
       
       $cov_matrix
       {
-          cov_matrix <- tern.mmrm::as.rtable(fit_mmrm, type = "cov")
-          subtitles(cov_matrix) <- NULL
-          cov_matrix
+          covariance_table <- tern.mmrm::as.rtable(fit_mmrm, type = "cov")
+          subtitles(covariance_table) <- NULL
       }
       
 

tests/testthat/_snaps/tm_g_ci.md

@@ -4,15 +4,14 @@
       res
     Output
       {
-          gg <- ggplot2::ggplot(data = ANL, mapping = ggplot2::aes(x = ARMCD, 
+          plot <- ggplot2::ggplot(data = ANL, mapping = ggplot2::aes(x = ARMCD, 
               y = AVAL, color = SEX, lty = SEX, shape = SEX)) + ggplot2::stat_summary(fun.data = stat_mean_ci, 
               geom = "errorbar", width = 0.1, position = ggplot2::position_dodge(width = 0.5)) + 
               ggplot2::stat_summary(fun = mean, geom = "point", position = ggplot2::position_dodge(width = 0.5)) + 
               ggplot2::labs(title = "Confidence Interval Plot by Treatment Group", 
                   caption = "Mean and 95% CIs for mean are displayed.", 
                   x = "Treatment Group", y = "Value", color = "", lty = "", 
                   shape = "")
-          print(gg)
       }
 
 # 3. Confidence Interval Plot (using different stratification variable)
@@ -21,7 +20,7 @@
       res
     Output
       {
-          gg <- ggplot2::ggplot(data = ANL, mapping = ggplot2::aes(x = ARMCD, 
+          plot <- ggplot2::ggplot(data = ANL, mapping = ggplot2::aes(x = ARMCD, 
               y = AVAL, color = STRATA2, lty = STRATA2, shape = STRATA2)) + 
               ggplot2::stat_summary(fun.data = stat_mean_ci, geom = "errorbar", 
                   width = 0.1, position = ggplot2::position_dodge(width = 0.5)) + 
@@ -30,7 +29,6 @@
                   caption = "Mean and 95% CIs for mean are displayed.", 
                   x = "Treatment Group", y = "Value", color = "", lty = "", 
                   shape = "")
-          print(gg)
       }
 
 # 4. Median and 95% CIs for median
@@ -39,7 +37,7 @@
       res
     Output
       {
-          gg <- ggplot2::ggplot(data = ANL, mapping = ggplot2::aes(x = ARMCD, 
+          plot <- ggplot2::ggplot(data = ANL, mapping = ggplot2::aes(x = ARMCD, 
               y = AVAL, color = STRATA1, lty = STRATA1, shape = STRATA1)) + 
               ggplot2::stat_summary(fun.data = stat_median_ci, geom = "errorbar", 
                   width = 0.1, position = ggplot2::position_dodge(width = 0.5)) + 
@@ -48,7 +46,6 @@
                   caption = "Median and 95% CIs for median are displayed.", 
                   x = "Treatment Group", y = "Value", color = "", lty = "", 
                   shape = "")
-          print(gg)
       }
 
 # 5. Using different alpha level
@@ -57,14 +54,13 @@
       res
     Output
       {
-          gg <- ggplot2::ggplot(data = ANL, mapping = ggplot2::aes(x = ARMCD, 
+          plot <- ggplot2::ggplot(data = ANL, mapping = ggplot2::aes(x = ARMCD, 
               y = AVAL, color = SEX, lty = SEX, shape = SEX)) + ggplot2::stat_summary(fun.data = function(x) stat_mean_ci(x, 
               conf_level = 0.9), geom = "errorbar", width = 0.1, position = ggplot2::position_dodge(width = 0.5)) + 
               ggplot2::stat_summary(fun = mean, geom = "point", position = ggplot2::position_dodge(width = 0.5)) + 
               ggplot2::labs(title = "Confidence Interval Plot by Treatment Group", 
                   caption = "Mean and 90% CIs for mean are displayed.", 
                   x = "Treatment Group", y = "Value", color = "", lty = "", 
                   shape = "")
-          print(gg)
       }
 

tests/testthat/_snaps/tm_g_forest_rsp.md

@@ -35,7 +35,7 @@
           as_list = TRUE)
       
       $plot[[2]]
-      p <- cowplot::plot_grid(f[["table"]] + ggplot2::labs(title = "Forest Plot of Best Overall Response for "), 
+      plot <- cowplot::plot_grid(f[["table"]] + ggplot2::labs(title = "Forest Plot of Best Overall Response for "), 
           f[["plot"]] + ggplot2::labs(caption = ""), align = "h", axis = "tblr", 
           rel_widths = c(1 - 0.25, 0.25))
       
@@ -80,7 +80,7 @@
           as_list = TRUE)
       
       $plot[[2]]
-      p <- cowplot::plot_grid(f[["table"]] + ggplot2::labs(title = "Forest Plot of Best Overall Response for "), 
+      plot <- cowplot::plot_grid(f[["table"]] + ggplot2::labs(title = "Forest Plot of Best Overall Response for "), 
           f[["plot"]] + ggplot2::labs(caption = ""), align = "h", axis = "tblr", 
           rel_widths = c(1 - 0.25, 0.25))
       

tests/testthat/_snaps/tm_g_forest_tte.md

@@ -38,7 +38,7 @@
           as_list = TRUE)
       
       $plot[[2]]
-      p <- cowplot::plot_grid(f[["table"]] + ggplot2::labs(title = "Forest Plot of Survival Duration for \nStratified by STRATA2", 
+      plot <- cowplot::plot_grid(f[["table"]] + ggplot2::labs(title = "Forest Plot of Survival Duration for \nStratified by STRATA2", 
           subtitle = NULL), f[["plot"]] + ggplot2::labs(caption = ""), 
           align = "h", axis = "tblr", rel_widths = c(1 - 0.25, 0.25))
       
@@ -85,7 +85,7 @@
           as_list = TRUE)
       
       $plot[[2]]
-      p <- cowplot::plot_grid(f[["table"]] + ggplot2::labs(title = "Forest Plot of Survival Duration for \nStratified by STRATA2", 
+      plot <- cowplot::plot_grid(f[["table"]] + ggplot2::labs(title = "Forest Plot of Survival Duration for \nStratified by STRATA2", 
           subtitle = NULL), f[["plot"]] + ggplot2::labs(caption = ""), 
           align = "h", axis = "tblr", rel_widths = c(1 - 0.25, 0.25))
       

tests/testthat/_snaps/tm_g_km.md

@@ -52,7 +52,6 @@
           g_km_counter <- g_km_counter_generator()
           plot_list <- lapply(anl, g_km_counter)
           plot <- cowplot::plot_grid(plotlist = plot_list, ncol = 1)
-          plot
       }
       
 
@@ -114,7 +113,6 @@
           g_km_counter <- g_km_counter_generator()
           plot_list <- lapply(anl, g_km_counter)
           plot <- cowplot::plot_grid(plotlist = plot_list, ncol = 1)
-          plot
       }
       
 
@@ -177,7 +175,6 @@
           g_km_counter <- g_km_counter_generator()
           plot_list <- lapply(anl, g_km_counter)
           plot <- cowplot::plot_grid(plotlist = plot_list, ncol = 1)
-          plot
       }
       
 

tests/testthat/_snaps/tm_g_lineplot.md

@@ -24,7 +24,6 @@
               legend_title = NULL, ggtheme = ggplot2::theme_minimal(), 
               control = control_analyze_vars(conf_level = 0.95), subtitle_add_paramcd = FALSE, 
               subtitle_add_unit = FALSE)
-          plot
       }
       
 
@@ -54,7 +53,6 @@
               legend_title = NULL, ggtheme = ggplot2::theme_minimal(), 
               control = control_analyze_vars(conf_level = 0.9), subtitle_add_paramcd = FALSE, 
               subtitle_add_unit = FALSE)
-          plot
       }
       
 

tests/testthat/_snaps/tm_t_abnormality.md

@@ -38,9 +38,8 @@
       
       $table
       {
-          result <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = adsl) %>% 
+          table <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = adsl) %>% 
               rtables::prune_table()
-          result
       }
       
 
@@ -83,9 +82,8 @@
       
       $table
       {
-          result <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = adsl) %>% 
+          table <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = adsl) %>% 
               rtables::prune_table()
-          result
       }
       
 
@@ -129,9 +127,8 @@
       
       $table
       {
-          result <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = adsl) %>% 
+          table <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = adsl) %>% 
               rtables::prune_table()
-          result
       }
       
 

tests/testthat/_snaps/tm_t_abnormality_by_worst_grade.md

@@ -40,8 +40,7 @@
       
       $table
       {
-          result <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = adsl)
-          result
+          table <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = adsl)
       }
       
 
@@ -87,8 +86,7 @@
       
       $table
       {
-          result <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = myadsl)
-          result
+          table <- rtables::build_table(lyt = lyt, df = anl, alt_counts_df = myadsl)
       }
       
 

tests/testthat/_snaps/tm_t_ancova.md

@@ -30,8 +30,7 @@
       
       $table
       {
-          result <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
-          result
+          table <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
       }
       
 
@@ -68,8 +67,7 @@
       
       $table
       {
-          result <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
-          result
+          table <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
       }
       
 
@@ -107,8 +105,7 @@
       
       $table
       {
-          result <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
-          result
+          table <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
       }
       
 
@@ -148,8 +145,7 @@
       
       $table
       {
-          result <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
-          result
+          table <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
       }
       
 
@@ -187,8 +183,7 @@
       
       $table
       {
-          result <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
-          result
+          table <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
       }
       
 
@@ -225,8 +220,7 @@
       
       $table
       {
-          result <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
-          result
+          table <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
       }
       
 
@@ -263,8 +257,7 @@
       
       $table
       {
-          result <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
-          result
+          table <- rtables::build_table(lyt = lyt, df = adqs, alt_counts_df = adsl)
       }