replace custom stop and warn messages with cli versions

R/helper_functions.R

@@ -63,14 +63,13 @@ apply_sector_split_to_loans <- function(data,
     )
 
   if (nrow(unique_companies_pre_split) != nrow(unique_companies_post_split)) {
-    warning(
-      glue::glue(
-        "Applying the sector split has lead to changes in the number of unique
-        companies covered in the analysis. Prior to the split, there were
-        {nrow(unique_companies_pre_split)} unique companies. After the split,
-        there are {nrow(unique_companies_post_split)} unique companies."
-      )
-    )
+    n_pre <- nrow(unique_companies_pre_split)
+    n_post <- nrow(unique_companies_post_split)
+    cli::cli_warn(c(
+      "!" = "Applying the sector split has lead to changes in the number of unique companies covered in the analysis.",
+      "i" = "Prior to the split, there {?was/were} {.strong {n_pre}} unique compan{?y/ies}.",
+      "i" = "After the split, there {?is/are} {.strong {n_post}} unique compan{?y/ies}."
+    ))
   }
 
   data

R/prepare_sector_split.R

@@ -228,15 +228,7 @@ prepare_sector_split <- function() {
     )
 
   ### check that the sum of the sector split of each company is 1----
-  check_sector_split_all_companies <- sector_split_all_companies %>%
-    dplyr::summarise(
-      sum_share = sum(.data[["sector_split"]], na.rm = TRUE),
-      .by = "company_id"
-    )
-
-  if (any(round(check_sector_split_all_companies$sum_share, 3) != 1)) {
-    stop("sector_split_all_companies contains companies for which the sum of the sector split deviates from 1")
-  }
+  stop_if_sector_split_not_one(sector_split_all_companies)
 
   ## calculate primary energy-based sector split for energy sectors----
   # keep only companies that are active in multiple energy sectors
@@ -309,15 +301,7 @@ prepare_sector_split <- function() {
     dplyr::filter(.data$company_id %in% company_ids_primary_energy_split)
 
   ### check that the sum of the primary energy based sector split of each company is 1----
-  check_sector_split_multi_energy_companies <- sector_split_multi_energy_companies %>%
-    dplyr::summarise(
-      sum_share = sum(.data[["sector_split"]], na.rm = TRUE),
-      .by = "company_id"
-    )
-
-  if (any(round(check_sector_split_multi_energy_companies$sum_share, 3) != 1)) {
-    stop("sector_split_multi_energy_companies contains companies for which the sum of the sector split deviates from 1")
-  }
+  stop_if_sector_split_not_one(sector_split_multi_energy_companies)
 
   ## combine the sector splits----
   # we want to use the plain equal weights split for companies that do not operate in more than one energy sector
@@ -344,16 +328,7 @@ prepare_sector_split <- function() {
     )
 
   ### check that the sum of the combined sector split of each company is 1----
-  check_sector_split_all_companies_final <- sector_split_all_companies_final %>%
-    dplyr::summarise(
-      sum_share = sum(.data$sector_split, na.rm = TRUE),
-      .by = "company_id"
-    )
-
-  if (any(round(check_sector_split_all_companies_final$sum_share, 3) != 1)) {
-    stop("sector_split_all_companies_final contains companies for which the sum of the sector split deviates from 1")
-  }
-
+  stop_if_sector_split_not_one(sector_split_all_companies_final)
 
   ## write output----
   sector_split_multi_energy_companies %>%

R/run_calculate_loanbook_coverage.R

@@ -36,10 +36,8 @@ run_calculate_loanbook_coverage <- function() {
 
   ## read matched prioritized loan books----
   list_matched_prioritized <- list.files(path = dir_matched, pattern = "^matched_prio_.*csv$")
+  stop_if_no_files_found(list_matched_prioritized, dir_matched, "dir_matched", "matched prioritized loan book CSVs")
 
-  if (length(list_matched_prioritized) == 0) {
-    stop(glue::glue("No matched prioritized loan book csvs found in {dir_matched}. Please check your project setup!"))
-  }
 
   matched_prioritized <- readr::read_csv(
     file = file.path(dir_matched, list_matched_prioritized),

R/run_calculate_match_success_rate.R

@@ -56,10 +56,7 @@ run_calculate_match_success_rate <- function() {
 
   ## load raw loan books----
   list_raw <- list.files(dir_raw)[grepl("csv$", list.files(dir_raw))]
-
-  if (length(list_raw) == 0) {
-    stop(glue::glue("No raw loan book csvs found in {dir_raw}. Please check your project setup!"))
-  }
+  stop_if_no_files_found(list_raw, dir_raw, "dir_raw", "raw loan book CSVs")
 
   raw_lbk <- readr::read_csv(
     file = file.path(dir_raw, list_raw),
@@ -73,10 +70,7 @@ run_calculate_match_success_rate <- function() {
 
   ## load matched prioritized loan books----
   list_matched_prioritized <- list.files(dir_matched)[grepl("^matched_prio_.*csv$", list.files(dir_matched))]
-
-  if (length(list_matched_prioritized) == 0) {
-    stop(glue::glue("No matched prioritized loan book csvs found in {dir_matched}. Please check your project setup!"))
-  }
+  stop_if_no_files_found(list_matched_prioritized, dir_matched, "dir_matched", "matched prioritized loan book CSVs")
 
   matched_prioritized <- readr::read_csv(
     file = file.path(dir_matched, list_matched_prioritized),
@@ -95,11 +89,11 @@ run_calculate_match_success_rate <- function() {
     sector_classifications_used <- unique(raw_lbk$sector_classification_system)
 
     if (length(sector_classifications_used) != 1) {
-      stop(
-        glue::glue(
-          "Number of sector classification systems across all loan books must be 1.
-          Your raw loan books use {length(sector_classifications_used)} different
-          types of sector classifications. Please choose one!"
+      cli::cli_abort(
+        message = c(
+          "x" = "Number of sector classification systems across all loan books is > 1.",
+          "i" = "You can only use one sector classification at the same time.",
+          "i" = "Your raw loan books use {length(sector_classifications_used)} different types of sector classifications."
         )
       )
     }

R/run_match_prioritize.R

@@ -25,13 +25,18 @@ run_match_prioritize <- function() {
       !inherits(match_prio_priority, "formula") &
       !inherits(match_prio_priority, "function")
     ) {
-      stop(
-        glue::glue(
-          "Argument match_prio_priority must be of one of: a character vector, a
-          function, or a quosure-style lambda function. Your input is of class
-          {class(match_prio_priority)}. Please check your input."
-        )
+      valid_types <- c(
+        "a character vector",
+        "a function",
+        "a quosure-style lambda function"
       )
+      cli::cli_abort(c(
+        "x" = paste0(
+          "Argument {.arg match_prio_priority} must be of one of: {.or {valid_types}}, ",
+          "not {.cls {class(match_prio_priority)}}."
+        ),
+        "i" = "Check the {.val match_prioritize:priority} parameter set in your {.file config.yml}."
+      ))
     }
   }
 
@@ -40,7 +45,11 @@ run_match_prioritize <- function() {
   list_matched_manual <- list.files(path = dir_matched, pattern = "^matched_lbk_.*_manual[.]csv$")
 
   if (length(list_matched_manual) == 0) {
-    stop(glue::glue("No manually matched loan book csvs found in {dir_matched}. Please check your project setup!"))
+    cli::cli_abort(c(
+      "x" = "No manually matched loan book csvs were found.",
+      "i" = "No files matching the pattern {.code ^matched_lbk_.*_manual[.]csv$} were found in {.path {dir_matched}}. Have you done the manual matching process and named the edited CSVs properly?",
+      "i" = "If {.path {dir_matched}} is not the correct directory, check the {.val dir_matched} parameter set in your {.file config.yml}."
+    ))
   }
 
   matched_lbk_manual <- readr::read_csv(

R/run_matching.R

@@ -105,10 +105,7 @@ run_matching <- function() {
 
   ## load raw loan books----
   list_raw <- list.files(path = dir_raw, pattern = "[.]csv$")
-
-  if (length(list_raw) == 0) {
-    stop(glue::glue("No raw loan book csvs found in {dir_raw}. Please check your project setup!"))
-  }
+  stop_if_no_files_found(list_raw, dir_raw, "dir_raw", "raw loan book CSVs")
 
   raw_lbk <- readr::read_csv(
     file = file.path(dir_raw, list_raw),

R/stop_if_.R

@@ -139,3 +139,59 @@ stop_if_not_expected_columns <- function(data, cols, desc = NULL) {
     )
   }
 }
+
+
+#' stop_if_no_files_found
+#'
+#' @param files a vector of files found
+#' @param dir a dir where files were not found
+#' @param dir_param a string identifying the paramter name in the config that
+#'   defines the directory
+#' @param desc a string describing the type of files expected to be found
+#'
+#' @return `NULL` invisibly or an error
+#'
+#' @noRd
+
+stop_if_no_files_found <- function(files, dir, dir_param, desc) {
+  if (length(files) == 0) {
+    cli::cli_abort(
+      message = c(
+        "x" = "No {desc} found.",
+        "i" = "Directory searched: {.path {dir}}",
+        "i" = "Check the {.arg {dir_param}} parameter in your {.file config.yml}."
+      ),
+      call = rlang::caller_env()
+    )
+  }
+}
+
+
+#' stop_if_sector_split_not_one
+#'
+#' @param data a data frame to be checked
+#'
+#' @return `NULL` invisibly or an error
+#'
+#' @noRd
+
+stop_if_sector_split_not_one <- function(data) {
+  check_sector_split <-
+    dplyr::summarise(
+      data,
+      sum_share = sum(.data[["sector_split"]], na.rm = TRUE),
+      .by = "company_id"
+    )
+
+  if (any(round(check_sector_split$sum_share, 3) != 1)) {
+    obj_name <- deparse(substitute(data))
+    msg <- "{.arg {obj_name}} contains companies for which the sum of the sector split deviates from 1"
+    cli::cli_abort(
+      message = c(
+        "x" = msg,
+        "i" = "Check the sector split set in your {.file config.yml}."
+      ),
+      call = rlang::caller_env()
+    )
+  }
+}