Unit test for life_exp() plot and gen_data_le() function

.Rbuildignore

@@ -3,7 +3,6 @@
 ^README\.Rmd$
 ^\.Rproj\.user$
 ^\.github$
-^\.pre-commit-config\.yaml$
 ^_pkgdown\.yml$
 ^docs$
 ^pkgdown$

.github/PULL_REQUEST_TEMPLATE.md

@@ -29,5 +29,3 @@ Fixes #<NUM>
 
 - [ ] *Lorem ipsum dolor sit amet, consectetur adipiscing.*
 - [ ] Everything looks ok?
-
-Thank you!

.github/workflows/lint.yaml

@@ -0,0 +1,33 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+on:
+  push:
+    branches: [main, master]
+  pull_request:
+
+name: lint.yaml
+
+permissions: read-all
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::lintr, local::.
+          needs: lint
+
+      - name: Lint
+        run: lintr::lint_package()
+        shell: Rscript {0}
+        env:
+          LINTR_ERROR_ON_LINT: true

.github/workflows/pr-commands.yaml

@@ -0,0 +1,85 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+on:
+  issue_comment:
+    types: [created]
+
+name: pr-commands.yaml
+
+permissions: read-all
+
+jobs:
+  document:
+    if: ${{ github.event.issue.pull_request && (github.event.comment.author_association == 'MEMBER' || github.event.comment.author_association == 'OWNER') && startsWith(github.event.comment.body, '/document') }}
+    name: document
+    runs-on: ubuntu-latest
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+    permissions:
+      contents: write
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/pr-fetch@v2
+        with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::roxygen2
+          needs: pr-document
+
+      - name: Document
+        run: roxygen2::roxygenise()
+        shell: Rscript {0}
+
+      - name: commit
+        run: |
+          git config --local user.name "$GITHUB_ACTOR"
+          git config --local user.email "[email protected]"
+          git add man/\* NAMESPACE
+          git commit -m 'Document'
+
+      - uses: r-lib/actions/pr-push@v2
+        with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+
+  style:
+    if: ${{ github.event.issue.pull_request && (github.event.comment.author_association == 'MEMBER' || github.event.comment.author_association == 'OWNER') && startsWith(github.event.comment.body, '/style') }}
+    name: style
+    runs-on: ubuntu-latest
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+    permissions:
+      contents: write
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/pr-fetch@v2
+        with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+
+      - uses: r-lib/actions/setup-r@v2
+
+      - name: Install dependencies
+        run: install.packages("styler")
+        shell: Rscript {0}
+
+      - name: Style
+        run: styler::style_pkg()
+        shell: Rscript {0}
+
+      - name: commit
+        run: |
+          git config --local user.name "$GITHUB_ACTOR"
+          git config --local user.email "[email protected]"
+          git add \*.R
+          git commit -m 'Style'
+
+      - uses: r-lib/actions/pr-push@v2
+        with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}

R/data-process.R

@@ -1,23 +1,23 @@
 #' Data Processing
 #'
 #' This file contains a set of functions designed to work together for processing the data.
 #' Below is a description of how to use these functions in sequence.
 #'
 #' ## Step-by-Step Usage:
 #'
 #' 1. **Read the data**: This function reads the data from the location specified `data <-  readRDS("data.rds")`.
 #'
 #' 1. **`gen_data_weighted`**: Calculates weighted mean values for various metrics over years `data_weighted <- gen_data_weighted(data)`.
 #'
 #' 1. **`gen_data_weighted_rf`**: Calculates the differences between intervention and baseline values for risk factors `data_weighted_rf_wide_collapse <- gen_data_weighted_rf(data_weighted)`.
 #'
 #' 1. **`gen_data_weighted_ds`**: Calculates the differences between intervention and baseline values for incidences `data_weighted_ds_wide_collapse <- gen_data_weighted_ds(data_weighted)`.
 #'
 #' 1. **`gen_data_weighted_burden`**: Calculates the differences between intervention and baseline values for burden of disease `data_weighted_burden_wide_collapse <- gen_data_weighted_burden(data_weighted)`.
 #'
 #' 1. **`gen_data_weighted_burden_spline`**: Performs data smoothing for burden of disease, when necessary. For instance, with only a few simulations, there can be positive values in difference in burden of disease `data_weighted_burden_spline <- gen_data_weighted_burden_spline(data_weighted_burden_wide_collapse)`.
 #'
 #' 1. **`gen_data_le`**: Calculates life expectancy for various age and groups `data_ple_wide <- gen_data_le(data_weighted)`.
 #'
 #' ## Examples
 #' ```r
@@ -27,7 +27,7 @@
 #' data_weighted_rf_wide_collapse <- gen_data_weighted_rf(data_weighted)
 #' data_weighted_ds_wide_collapse <- gen_data_weighted_ds(data_weighted)
 #' data_weighted_burden_wide_collapse <- gen_data_weighted_burden(data_weighted)
 #' data_weighted_burden_spline <- gen_data_weighted_burden_spline(data_weighted_burden_wide_collapse)
 #' data_ple_wide <- gen_data_le(data_weighted)
 #' ```
 #'
@@ -45,7 +45,7 @@
   print("Loading the config file...")
   config <- load_config("default")
   print("Processing the data...")
   colnames(data) <- gsub("^mean_", "", colnames(data)) # Clean the column names by removing 'mean_'
   weight_column <- rlang::sym(config$weight)
   data_weighted <- data |>
     dplyr::group_by(dplyr::across(dplyr::all_of(config$grouping_vars))) |>
@@ -179,9 +179,9 @@
   )
 
   data_weighted_ds_wide <- tidyr::pivot_wider(data_weighted_ds,
-                                              names_from = config$names_from,
-                                              id_cols = config$id_cols,
-                                              values_from = config$weighted_ds
+    names_from = config$names_from,
+    id_cols = config$id_cols,
+    values_from = config$weighted_ds
   )
 
   data_weighted_ds_wide_diff <- data_weighted_ds_wide |>
@@ -359,9 +359,11 @@
   config <- load_config("default")
   print("Processing the data...")
   config_file_path <- system.file("config", "config.yml", package = "healthgpsrvis")
-  burden_spline <- config::get(value = "burden_spline",
-                               file = config_file_path,
-                               use_parent = FALSE)
+  burden_spline <- config::get(
+    value = "burden_spline",
+    file = config_file_path,
+    use_parent = FALSE
+  )
 
   ## This function is data smoothing
   ## It is applied manually now in India project due to abnormal positive values in diff_daly or cumdiff_daly
@@ -391,25 +393,31 @@
   ## Fit spline and predict
   spline_fit_mean <- splines::interpSpline(
     as.numeric(unlist(data_weighted_burden_mean[config$group])),
-    as.numeric(unlist(data_weighted_burden_mean[burden_spline[[1]]$burden_mean])))
+    as.numeric(unlist(data_weighted_burden_mean[burden_spline[[1]]$burden_mean]))
+  )
   data_weighted_burden_spline[burden_spline[[1]]$burden_mean] <- stats::predict(
     spline_fit_mean,
-    as.numeric(unlist(data_weighted_burden_spline[config$group])))$y
+    as.numeric(unlist(data_weighted_burden_spline[config$group]))
+  )$y
 
   spline_fit_min <- splines::interpSpline(
     as.numeric(unlist(data_weighted_burden_min[config$group])),
-    as.numeric(unlist(data_weighted_burden_min[burden_spline[[2]]$burden_min])))
+    as.numeric(unlist(data_weighted_burden_min[burden_spline[[2]]$burden_min]))
+  )
   data_weighted_burden_spline[burden_spline[[2]]$burden_min] <- stats::predict(
     spline_fit_min,
-    as.numeric(unlist(data_weighted_burden_spline[config$group])))$y
+    as.numeric(unlist(data_weighted_burden_spline[config$group]))
+  )$y
 
   ## Use smooth.spline for ps4-low
   spline_fit_max <- splines::interpSpline(
     as.numeric(unlist(data_weighted_burden_max[config$group])),
-    as.numeric(unlist(data_weighted_burden_max[burden_spline[[3]]$burden_max])))
+    as.numeric(unlist(data_weighted_burden_max[burden_spline[[3]]$burden_max]))
+  )
   data_weighted_burden_spline[burden_spline[[3]]$burden_max] <- stats::predict(
     spline_fit_max,
-    as.numeric(unlist(data_weighted_burden_spline[config$group])))$y
+    as.numeric(unlist(data_weighted_burden_spline[config$group]))
+  )$y
 
   ## Keep 0 values in the first two years, before policy implementation
   group <- config$group
@@ -419,7 +427,8 @@
     data_weighted_burden_spline[[burden_sp]] <- ifelse(
       data_weighted_burden_spline[[group]] < 2024,
       0,
-      data_weighted_burden_spline[[burden_sp]])
+      data_weighted_burden_spline[[burden_sp]]
+    )
   }
   print("Data processing complete.")
   return(data_weighted_burden_spline)
@@ -433,6 +442,7 @@
 #' @return A data frame with life expectancy.
 #' @export
 gen_data_le <- function(data_mean) {
+  print("Processing the data...")
   data_le <- data_mean[, c(
     data_mean$source,
     data_mean$time,
@@ -476,7 +486,7 @@
     values_from = c(data_ple$ple)
   )
   data_ple_wide$diff <- data_ple_wide$intervention - data_ple_wide$baseline
-
+  print("Data processing complete.")
   return(data_ple_wide)
 }
 
@@ -485,4 +495,5 @@
   "incidence_intracerebralhemorrhage", "incidence_ischemicstroke",
   "incidence_subarachnoidhemorrhage", "prevalence_intracerebralhemorrhage",
   "prevalence_ischemicstroke", "prevalence_subarachnoidhemorrhage",
-  "diff_energyintake", "diff_inc_diabetes"))
+  "diff_energyintake", "diff_inc_diabetes"
+))

tests/testthat/test-data-process.R

@@ -193,7 +193,8 @@ test_that("Columns in the generated dataframe", {
 
   # Generate a data frame with spline smoothing applied for burden of disease
   data_weighted_burden_spline <- gen_data_weighted_burden_spline(
-    data_weighted_bd_wide_collapse)
+    data_weighted_bd_wide_collapse
+  )
 
   # Check if the data has the expected number of columns
   expect_equal(ncol(data_weighted_burden_spline), 4)
@@ -204,3 +205,5 @@ test_that("Columns in the generated dataframe", {
     c("time", "cumdiff_daly_mean", "cumdiff_daly_min", "cumdiff_daly_max")
   )
 })
+
+# Testing gen_data_le() function

tests/testthat/test-health-plots.R

@@ -265,6 +265,20 @@ test_that("life_exp function works correctly", {
   expect_equal(plot_le$labels$title, "Increase in life expectancy under intervention")
 })
 
+# Testing life_exp() function
+test_that("life_exp function works correctly", {
+  # Create sample data
+  data_ple_wide <- data.frame(
+    timediff = seq(-9, 21, by = 1),
+    diff = runif(31, -3, 0)
+  )
+
+  # Test for valid input
+  plot_le <- life_exp(data_ple_wide$diff, data_ple_wide)
+  expect_s3_class(plot_le, "ggplot")
+  expect_equal(plot_le$labels$title, "Increase in life expectancy under intervention")
+})
+
 # Testing combine_plots() function
 test_that("combine_plots function works correctly", {
   # Create sample metrics