Update graph snapshot processing (#183)

Closes #182 

Merge after insightsengineering/tern#1158

This should standardize the generation of graph snapshots across
different systems and hopefully fix the failing integration tests for
graph snapshot differences.

Note: kmg01 snapshots will be fixed after `g_km` is refactored.

---------

Co-authored-by: github-actions <41898282+github-actions[bot]@users.noreply.github.com>

book/graphs/efficacy/fstg01.qmd

@@ -5,6 +5,8 @@ subtitle: Subgroup Analysis of Best Overall Response
 
 ------------------------------------------------------------------------
 
+{{< include ../../test-utils/envir_hook.qmd >}}
+
 ::: panel-tabset
 ## Data Setup
 
@@ -42,7 +44,7 @@ var_labels(anl_rsp_arms_ab) <- c(anl_labels, is_rsp = "Is Responder")
 
 ## Standard Plot
 
-```{r, warning=FALSE, fig.width = 15}
+```{r plot1, test = list(plot_v1 = "plot"), fig.width = 20, fig.height = 5}
 df <- extract_rsp_subgroups(
   variables = list(
     rsp = "is_rsp",
@@ -57,15 +59,13 @@ df <- extract_rsp_subgroups(
 result <- basic_table() %>%
   tabulate_rsp_subgroups(df, vars = c("n_tot", "n", "n_rsp", "prop", "or", "ci"))
 
-p <- g_forest(
-  tbl = result
-)
-grid::grid.draw(p)
+plot <- g_forest(tbl = result)
+plot
 ```
 
 ## Plot Specifying Class Variables and <br/> Options for the Treatment Variable
 
-```{r, warning=FALSE, fig.width = 15}
+```{r plot2, test = list(plot_v2 = "plot"), fig.width = 20, fig.height = 5}
 anl_rsp_comb_arms_ac <- anl %>%
   mutate(is_rsp = AVALC %in% c("CR", "PR")) %>%
   filter(ARMCD %in% c("ARM B", "ARM A", "ARM C")) %>%
@@ -98,16 +98,13 @@ df <- extract_rsp_subgroups(
 result <- basic_table() %>%
   tabulate_rsp_subgroups(df, vars = c("n_tot", "n", "n_rsp", "prop", "or", "ci"))
 
-p <- g_forest(
-  tbl = result
-)
-
-grid::grid.draw(p)
+plot <- g_forest(tbl = result)
+plot
 ```
 
 ## Plot Selecting Columns and <br/> Changing the Alpha Level
 
-```{r, warning=FALSE, fig.width = 15}
+```{r plot3, test = list(plot_v3 = "plot"), fig.width = 10, fig.height = 4}
 df <- extract_rsp_subgroups(
   variables = list(
     rsp = "is_rsp",
@@ -122,16 +119,13 @@ df <- extract_rsp_subgroups(
 result <- basic_table() %>%
   tabulate_rsp_subgroups(df, vars = c("n_tot", "or", "ci"))
 
-p <- g_forest(
-  tbl = result
-)
-
-grid::grid.draw(p)
+plot <- g_forest(tbl = result)
+plot
 ```
 
 ## Plot with Fixed <br/> Symbol Size
 
-```{r, warning=FALSE, fig.width = 15}
+```{r plot4, test = list(plot_v4 = "plot"), fig.width = 20, fig.height = 5}
 df <- extract_rsp_subgroups(
   variables = list(
     rsp = "is_rsp",
@@ -146,17 +140,16 @@ df <- extract_rsp_subgroups(
 result <- basic_table() %>%
   tabulate_rsp_subgroups(df, vars = c("n_tot", "n", "n_rsp", "prop", "or", "ci"))
 
-p <- g_forest(
+plot <- g_forest(
   tbl = result,
   col_symbol_size = NULL
 )
-
-grid::grid.draw(p)
+plot
 ```
 
 ## Plot of CR Only, Setting <br/> Values Indicating Response
 
-```{r, warning=FALSE, fig.width = 15}
+```{r plot5, test = list(plot_v5 = "plot"), fig.width = 20, fig.height = 5}
 anl_cr_arms_ab <- anl %>%
   mutate(is_rsp = AVALC == "CR") %>%
   filter(ARMCD %in% c("ARM B", "ARM A")) %>%
@@ -183,13 +176,17 @@ df <- extract_rsp_subgroups(
 result <- basic_table() %>%
   tabulate_rsp_subgroups(df, vars = c("n_tot", "n", "n_rsp", "prop", "or", "ci"))
 
-p <- g_forest(
-  tbl = result
-)
+plot <- g_forest(tbl = result)
+plot
+```
 
-grid::grid.draw(p)
+```{r test parameters, test = list(width = "width", height = "height"), echo=FALSE}
+width <- 20
+height <- 5
 ```
 
+{{< include ../../test-utils/save_results.qmd >}}
+
 ## `teal` App
 
 ```{r teal, message=FALSE, opts.label='skip_if_testing'}

book/graphs/efficacy/fstg02.qmd

@@ -5,6 +5,8 @@ subtitle: Subgroup Analysis of Survival Duration
 
 ------------------------------------------------------------------------
 
+{{< include ../../test-utils/envir_hook.qmd >}}
+
 ::: panel-tabset
 ## Data Setup
 
@@ -54,7 +56,7 @@ anl <- synthetic_cdisc_dataset("latest", "adtte") %>%
 
 ## Standard Plot
 
-```{r variant1, warning=FALSE, fig.width = 15}
+```{r plot1, test = list(plot_v1 = "plot"), fig.width = 15, fig.height = 4}
 anl1 <- anl
 
 df <- extract_survival_subgroups(
@@ -71,16 +73,13 @@ result <- basic_table() %>%
 result
 
 # Add plot.
-p <- g_forest(
-  tbl = result
-)
-
-grid::grid.draw(p)
+plot <- g_forest(tbl = result)
+plot
 ```
 
 ## Plot Specifying Class Variables and <br/> Options for the Treatment Variable
 
-```{r variant2, warning=FALSE, fig.width = 15}
+```{r plot2, test = list(plot_v2 = "plot"), fig.width = 15, fig.height = 4}
 anl2 <- anl %>%
   mutate(
     # Recode levels of arm.
@@ -108,16 +107,13 @@ result <- basic_table() %>%
   )
 result
 
-p <- g_forest(
-  tbl = result
-)
-
-grid::grid.draw(p)
+plot <- g_forest(tbl = result)
+plot
 ```
 
 ## Plot Selecting Columns and <br/> Changing the Alpha Level)
 
-```{r variant3, warning=FALSE, fig.width = 15}
+```{r plot3, test = list(plot_v3 = "plot"), fig.width = 8, fig.height = 4}
 anl3 <- anl
 
 df <- extract_survival_subgroups(
@@ -134,16 +130,13 @@ result <- basic_table() %>%
 result
 
 # Add plot.
-p <- g_forest(
-  tbl = result
-)
-
-grid::grid.draw(p)
+plot <- g_forest(tbl = result)
+plot
 ```
 
 ## Plot with Fixed <br/> Symbol Size
 
-```{r variant4, warning=FALSE, fig.width = 15}
+```{r plot4, test = list(plot_v4 = "plot"), fig.width = 15, fig.height = 4}
 anl4 <- anl
 
 df <- extract_survival_subgroups(
@@ -160,14 +153,21 @@ result <- basic_table() %>%
 result
 
 # Add plot.
-p <- g_forest(
+plot <- g_forest(
   tbl = result,
   col_symbol_size = NULL
 )
+plot
+```
 
-grid::grid.draw(p)
+```{r test parameters, test = list(width = "width", height = "height", plot_v3.width = "plot_v3.width"), echo=FALSE}
+width <- 15
+height <- 4
+plot_v3.width <- 8
 ```
 
+{{< include ../../test-utils/save_results.qmd >}}
+
 ## `teal` App
 
 ```{r teal, message=FALSE, opts.label='skip_if_testing'}

book/graphs/efficacy/mmrmg02.qmd

@@ -80,7 +80,7 @@ From these results a table is obtained using the `tern.mmrm::tabulate_mmrm_subgr
 
 Here we compare `ARM A` with the reference arm, `ARM B`.
 
-```{r plot1, warning=FALSE, fig.width = 15, test = list(plot_v1 = "plot")}
+```{r plot1, test = list(plot_v1 = "plot"), fig.width = 15, fig.height = 4}
 df_a <- extract_mmrm_subgroups(
   fit = mmrm_results,
   visit = "SCREENING",
@@ -106,7 +106,7 @@ plot
 
 Then we compare `ARM C` with `ARM B`.
 
-```{r plot2, warning=FALSE, fig.width = 15, test = list(plot_v2 = "plot")}
+```{r plot2, test = list(plot_v2 = "plot"), fig.width = 15, fig.height = 4}
 df_c <- extract_mmrm_subgroups(
   fit = mmrm_results,
   visit = "SCREENING",
@@ -130,8 +130,12 @@ plot <- g_forest(
 plot
 ```
 
+```{r test parameters, test = list(width = "width", width = "width"), echo=FALSE}
+width <- 15
+height <- 4
+```
+
 {{< include ../../test-utils/save_results.qmd >}}
 
 {{< include ../../repro.qmd >}}
-
 :::

package/DESCRIPTION

@@ -17,25 +17,26 @@ Suggests:
     DescTools,
     dplyr,
     forcats,
-    formatters (>= 0.5.4),
+    formatters (>= 0.5.5),
     ggplot2 (>= 3.4.0),
     ggpubr,
     ggrepel,
     grid,
     lubridate,
     nestcolor,
     renv,
-    rlistings (>= 0.2.6),
-    rtables (>= 0.6.5),
+    rlistings (>= 0.2.7),
+    rtables (>= 0.6.6),
     scales,
     scda,
     scda.2022 (>= 0.1.5),
     stats,
     stringr,
+    svglite (>= 2.1.2),
     teal (>= 0.14.0.9027),
     teal.modules.clinical (>= 0.8.16.9019),
     teal.modules.general (>= 0.2.16.9014),
-    tern (>= 0.9.2),
+    tern (>= 0.9.3.9002),
     tern.mmrm (>= 0.2.2),
     tern.rbmi,
     tibble,

package/tests/testthat/_snaps/cig01/graph-snaps.md

@@ -0,0 +1,10 @@
+# plot_v9
+
+    Code
+      print(data_snap[[i]])
+    Output
+                    ARM A        ARM B        ARM C   
+      ————————————————————————————————————————————————
+      Mean (SD)   17.7 (9.9)   18.7 (9.8)   19.5 (9.1)
+      Median         17.5         18.2         19.0   
+