tidy style: remove unneeded spaces

tidymodels · Apr 22, 2024 · 2689bdb · 2689bdb
1 parent 4164156
commit 2689bdb
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Showing 4 changed files with 9 additions and 9 deletions.
diff --git a/R/container.R b/R/container.R
@@ -116,7 +116,7 @@ fit.container <- function(object, .data, outcome, estimate, probabilities = c(),
 
 
 
-  object <- set_container_type(object, .data[[ dat$outcome ]])
+  object <- set_container_type(object, .data[[dat$outcome]])
 
   object <- new_container(object$mode, object$type,
                           operations = object$operations,

diff --git a/R/equivocal_zone.R b/R/equivocal_zone.R
@@ -80,12 +80,12 @@ fit.equivocal_zone <- function(object, data, parent = NULL, ...) {
 predict.equivocal_zone <- function(object, new_data, parent, ...) {
   est_nm <- parent$columns$estimate
   prob_nm <- parent$columns$probabilities[1]
-  lvls <- levels(new_data[[ est_nm ]])
+  lvls <- levels(new_data[[est_nm]])
   col_syms <- syms(prob_nm[1])
   cls_pred <- probably::make_two_class_pred(new_data[[prob_nm]], levels = lvls,
                                             buffer = object$arguments$value,
                                             threshold = object$arguments$threshold)
-  new_data[[ est_nm ]] <- cls_pred # todo convert to factor?
+  new_data[[est_nm]] <- cls_pred # todo convert to factor?
   new_data
 }
 

diff --git a/R/numeric_range.R b/R/numeric_range.R
@@ -75,8 +75,8 @@ predict.numeric_range <- function(object, new_data, parent, ...) {
   hi <- object$arguments$upper_limit
 
   # todo depends on tm predict col names
-  new_data[[ est_nm ]] <-
-    probably::bound_prediction(new_data, lower_limit = lo, upper_limit = hi)[[ est_nm ]]
+  new_data[[est_nm]] <-
+    probably::bound_prediction(new_data, lower_limit = lo, upper_limit = hi)[[est_nm]]
   new_data
 }
 

diff --git a/R/prob_threshold.R b/R/prob_threshold.R
@@ -76,11 +76,11 @@ fit.probability_threshold <- function(object, data, parent = NULL, ...) {
 predict.probability_threshold <- function(object, new_data, parent, ...) {
   est_nm <- parent$columns$estimate
   prob_nm <- parent$columns$probabilities[1]
-  lvls <- levels(new_data[[ est_nm ]])
+  lvls <- levels(new_data[[est_nm]])
 
-  new_data[[ est_nm ]] <-
-    ifelse(new_data[[ prob_nm ]] >= object$arguments$threshold, lvls[1], lvls[2])
-  new_data[[ est_nm ]] <- factor(new_data[[ est_nm ]], levels = lvls)
+  new_data[[est_nm]] <-
+    ifelse(new_data[[prob_nm]] >= object$arguments$threshold, lvls[1], lvls[2])
+  new_data[[est_nm]] <- factor(new_data[[est_nm]], levels = lvls)
   new_data
 }