From 2689bdb8e57362ab0b67b65c44a252c9baf20995 Mon Sep 17 00:00:00 2001
From: simonpcouch <simonpatrickcouch@gmail.com>
Date: Mon, 22 Apr 2024 13:38:58 -0500
Subject: [PATCH] tidy style: remove unneeded spaces

---
 R/container.R      | 2 +-
 R/equivocal_zone.R | 4 ++--
 R/numeric_range.R  | 4 ++--
 R/prob_threshold.R | 8 ++++----
 4 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/R/container.R b/R/container.R
index c8c720d..56f6938 100644
--- 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$operations,
diff --git a/R/equivocal_zone.R b/R/equivocal_zone.R
index 1f7a44d..9575656 100644
--- a/R/equivocal_zone.R
+++ b/R/equivocal_zone.R
@@ -80,12 +80,12 @@ fit.equivocal_zone <- function(object, data, parent = NULL, ...) {
 predict.equivocal_zone <- function(object, new_data, parent, ...) {
   est_nm <- parent$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
index 1b37f8c..96441d5 100644
--- 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
index 6109781..3ee6cd7 100644
--- 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
 }