ifelse -> if_else

R/annotate_masses.R

@@ -257,23 +257,25 @@ annotate_masses <-
       tidytable::left_join(clusters_table |>
         tidytable::mutate(join = "x")) |>
       tidytable::bind_rows(adducts_table) |>
-      tidytable::mutate(adduct = ifelse(
-        test = !is.na(cluster),
-        yes = paste0(
-          adduct |> gsub(
-            pattern = "M(?![a-z]).*",
-            replacement = "M",
-            perl = TRUE
-          ),
+      tidytable::mutate(adduct = tidytable::if_else(
+        condition = !is.na(cluster),
+        true = paste0(
+          adduct |>
+            gsub(
+              pattern = "M(?![a-z]).*",
+              replacement = "M",
+              perl = TRUE
+            ),
           "+",
           cluster,
-          adduct |> gsub(
-            pattern = ".*M(?![a-z])",
-            replacement = "",
-            perl = TRUE
-          )
+          adduct |>
+            gsub(
+              pattern = ".*M(?![a-z])",
+              replacement = "",
+              perl = TRUE
+            )
         ),
-        no = adduct
+        false = adduct
       )) |>
       # Single charge monomers only
       tidytable::filter(grepl(
@@ -332,15 +334,15 @@ annotate_masses <-
       tidytable::filter(!is.na(Group1)) |>
       tidytable::mutate(tidytable::across(.cols = c("rt"), .fns = as.character)) |>
       tidytable::mutate(
-        adduct = ifelse(
-          test = is.na(adduct),
-          yes = as.character(Group1),
-          no = adduct
+        adduct = tidytable::if_else(
+          condition = is.na(adduct),
+          true = as.character(Group1),
+          false = adduct
         ),
-        adduct_dest = ifelse(
-          test = is.na(adduct_dest),
-          yes = as.character(Group2),
-          no = adduct_dest
+        adduct_dest = tidytable::if_else(
+          condition = is.na(adduct_dest),
+          true = as.character(Group2),
+          false = adduct_dest
         )
       ) |>
       tidytable::distinct(feature_id, adduct, adduct_dest, !!as.name(paste("feature_id", "dest", sep = "_")))
@@ -380,23 +382,25 @@ annotate_masses <-
       tidytable::left_join(df_nl_min) |>
       tidytable::bind_rows(df_adducted) |>
       tidytable::distinct() |>
-      tidytable::mutate(adduct = ifelse(
-        test = !is.na(loss),
-        yes = paste0(
-          adduct |> gsub(
-            pattern = "M(?![a-z]).*",
-            replacement = "M",
-            perl = TRUE
-          ),
+      tidytable::mutate(adduct = tidytable::if_else(
+        condition = !is.na(loss),
+        true = paste0(
+          adduct |>
+            gsub(
+              pattern = "M(?![a-z]).*",
+              replacement = "M",
+              perl = TRUE
+            ),
           "-",
           loss,
-          adduct |> gsub(
-            pattern = ".*M(?![a-z])",
-            replacement = "",
-            perl = TRUE
-          )
+          adduct |>
+            gsub(
+              pattern = ".*M(?![a-z])",
+              replacement = "",
+              perl = TRUE
+            )
         ),
-        no = adduct
+        false = adduct
       ))
     rm(df_adducted, df_nl_min)
 

R/annotate_spectra.R

@@ -248,15 +248,15 @@ annotate_spectra <- function(input = get_params(step = "annotate_spectra")$files
       df_final <- df_final |>
         tidytable::mutate(
           candidate_structure_error_mz = target_precursorMz - precursorMz,
-          candidate_structure_inchikey_no_stereo = ifelse(
-            test = is.na(target_inchikey_no_stereo),
-            yes = target_inchikey |>
+          candidate_structure_inchikey_no_stereo = tidytable::if_else(
+            condition = is.na(target_inchikey_no_stereo),
+            true = target_inchikey |>
               gsub(
                 pattern = "-.*",
                 replacement = "",
                 perl = TRUE
               ),
-            no = target_inchikey_no_stereo
+            false = target_inchikey_no_stereo
           ),
           candidate_structure_smiles_no_stereo = tidytable::coalesce(target_smiles_no_stereo, target_smiles)
         ) |>

R/clean_bio.R

@@ -94,10 +94,10 @@ clean_bio <-
             feature_source, !!as.name(feature_val_name) := !!as.name(candidates), !!as.name(consistency_name), !!as.name(feature_score_name)
           ) |>
           tidytable::mutate(
-            !!as.name(feature_val_name) := ifelse(
-              test = !!as.name(feature_score_name) >= minimal_consistency,
-              yes = !!as.name(feature_val_name),
-              no = "notConsistent"
+            !!as.name(feature_val_name) := tidytable::if_else(
+              condition = !!as.name(feature_score_name) >= minimal_consistency,
+              true = !!as.name(feature_val_name),
+              false = "notConsistent"
             )
           )
       }

R/clean_collapse.R

@@ -11,10 +11,10 @@
 clean_collapse <- function(grouped_df, cols = NA) {
   clean_collapse_df <- grouped_df |>
     tidytable::reframe(tidytable::across(
-      .cols = ifelse(
-        test = is.na(cols),
-        yes = tidyselect::everything(),
-        no = cols
+      .cols = tidytable::if_else(
+        condition = is.na(cols),
+        true = tidyselect::everything(),
+        false = cols
       ),
       .fns = function(x) {
         x <- list(paste(unique(x[!is.na(x)]), collapse = " $ "))

R/harmonize_spectra.R

@@ -151,15 +151,15 @@ harmonize_spectra <- function(spectra,
     tidytable::mutate(
       library = metad,
       exactmass = as.numeric(exactmass),
-      spectrum_id = ifelse(
-        test = is.na(spectrum_id),
-        yes = tidytable::row_number(),
-        no = as.numeric(spectrum_id)
+      spectrum_id = tidytable::if_else(
+        condition = is.na(spectrum_id),
+        true = tidytable::row_number(),
+        false = as.numeric(spectrum_id)
       ),
-      compound_id = ifelse(
-        test = is.na(compound_id),
-        yes = name,
-        no = compound_id
+      compound_id = tidytable::if_else(
+        condition = is.na(compound_id),
+        true = name,
+        false = compound_id
       )
     ) |>
     data.frame()

R/prepare_libraries_rt.R

@@ -152,7 +152,7 @@ prepare_libraries_rt <-
           data.frame() |>
           tidytable::mutate(type = type) |>
           tidytable::rowwise() |>
-          tidytable::mutate(rt = ifelse(unit == "seconds", yes = as.numeric(rt) / 60, no = rt)) |>
+          tidytable::mutate(rt = tidytable::if_else(condition = unit == "seconds", true = as.numeric(rt) / 60, false = rt)) |>
           tidytable::bind_rows(data.frame(inchikey = NA_character_, smiles = NA_character_)) |>
           tidytable::filter(!is.na(rt)) |>
           tidytable::filter(!is.na(smiles)) |>

R/weight_bio.R

@@ -177,10 +177,10 @@ weight_bio <-
               !!as.name(samples) == "notClassified"
           ) |>
           tidytable::mutate(
-            !!as.name(score_name) := ifelse(
-              test = !!as.name(samples) != "notClassified",
-              yes = !!as.name(score) * 1,
-              no = 0
+            !!as.name(score_name) := tidytable::if_else(
+              condition = !!as.name(samples) != "notClassified",
+              true = !!as.name(score) * 1,
+              false = 0
             )
           )
       }

inst/_targets.R

@@ -2010,10 +2010,10 @@ list(
               rtime = tidytable::cur_group_id(),
               .by = "short_ik"
             ) |>
-            tidytable::mutate(precursorCharge = ifelse(
-              test = mode == "pos",
-              yes = as.integer(1),
-              no = as.integer(-1)
+            tidytable::mutate(precursorCharge = tidytable::if_else(
+              condition = mode == "pos",
+              true = as.integer(1),
+              false = as.integer(-1)
             )) |>
             tidytable::select(
               acquisitionNum,