docs(sessions): 📝 split exercises up into smaller sets

Closes #139

appendix/model-variability.qmd

@@ -288,7 +288,7 @@ run.
 metabolites_with_bootstrap_results <- lipidomics |>
   split_by_metabolite() |>
   map(generate_model_variation) |>
-  map(tidy_bootstrap_output) |> 
+  map(tidy_bootstrap_output) |>
   list_rbind()
 metabolites_with_bootstrap_results
 ```
@@ -298,21 +298,12 @@ metabolites_with_bootstrap_results
 metabolites_with_bootstrap_results
 ```
 
-## :technologist: Exercise: Convert to function and add as a target in the pipeline
+## :technologist: Exercise: Convert variation calculation into a function
 
-> Time: \~15 minutes.
-
-Continue the workflow we've applied throughout the course:
-
-1.  Move the code into a function structure (use the scaffold below as a
-    guide).
-2.  Include one argument in the `function()` called `data`.
-3.  Replace `lipidomics` in the code with `data`.
-4.  Add the Roxygen documentation with {{< var keybind.roxgyen >}}.
-5.  Cut and paste the function over into the `R/functions.R` file.
-6.  Style using {{< var keybind.styler >}}.
-7.  Commit the changes to the Git history with {{< var keybind.git >}}.
+> Time: \~8 minutes.
 
+Continue the workflow we've applied throughout the course, convert the 
+code to calculate the variation of the model estimates into a function.
 Use this code as a guide for the function.
 
 ``` r
@@ -323,6 +314,15 @@ calculate_variation <- function(___) {
 }
 ```
 
+1.  Move the code we made right before this exercise into a function structure
+    (use the scaffold below as a guide).
+2.  Include one argument in the `function()` called `data`.
+3.  Replace `lipidomics` in the code with `data`.
+4.  Add the Roxygen documentation with {{< var keybind.roxgyen >}}.
+5.  Cut and paste the function over into the `R/functions.R` file.
+6.  Style using {{< var keybind.styler >}}.
+7.  Commit the changes to the Git history with {{< var keybind.git >}}.
+
 ```{r solution-new-function-calculate-variation}
 #| eval: false
 #| code-fold: true
@@ -337,12 +337,27 @@ calculate_variation <- function(data) {
   data |>
     split_by_metabolite() |>
     purrr::map(generate_model_variation) |>
-    purrr::map(tidy_bootstrap_output) |> 
+    purrr::map(tidy_bootstrap_output) |>
     purrr::list_rbind()
 }
 ```
 
-Next, add the function to `_targets.R`.
+## :technologist: Exercise: Add the new function as a target in the pipeline
+
+> Time: \~8 minutes.
+
+Continuing from the previous exercise, add the `calculate_variation()` function
+to `_targets.R`. Use this code as a scaffold:
+
+``` r
+list(
+  ...,
+  tar_target(
+    name = ___,
+    command = ___
+  )
+)
+```
 
 1.  Create another `tar_target()` item in the `list()` at the bottom of
     the file.
@@ -354,14 +369,15 @@ Next, add the function to `_targets.R`.
     {{< var keybind.targets-make >}}.
 4.  Commit the changes to the Git history with {{< var keybind.git >}}.
 
-Use this code as a scaffold:
-
-``` r
+```{r solution-calculate-variation-to-pipeline}
+#| eval: false
+#| code-fold: true
+#| code-summary: "**Click for the solution**. Only click if you are struggling or are out of time."
 list(
-  ...,
+  # ...,
   tar_target(
-    name = ___,
-    command = ___
+    name = df_model_variation,
+    command = calculate_variation(lipidomics)
   )
 )
 ```
@@ -370,14 +386,14 @@ list(
 #| eval: false
 #| echo: false
 #| purl: true
-variation_targets_code <- '
+variation_targets_code <- "
   ),
   tar_target(
     name = df_model_variation,
     command = calculate_variation(lipidomics)
   )
 )
-'
+"
 # print_lines("_targets.R")
 revise_by_line_num(
   path = "_targets.R",
@@ -391,19 +407,6 @@ targets::tar_make()
 git_ci("_targets.R", "Update targets with model variation")
 ```
 
-```{r solution-calculate-variation-to-pipeline}
-#| eval: false
-#| code-fold: true
-#| code-summary: "**Click for the solution**. Only click if you are struggling or are out of time."
-list(
-  # ...,
-  tar_target(
-    name = df_model_variation,
-    command = calculate_variation(lipidomics)
-  )
-)
-```
-
 ## Visualizing the variability of results
 
 ::: {.callout-note collapse="true"}