refactor: move measure_df and compare_df to utils

overdodactyl · Jan 5, 2024 · 7163d5c · 7163d5c
1 parent 6af1527
commit 7163d5c
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diff --git a/R/dx_metrics.R b/R/dx_metrics.R
@@ -590,68 +590,6 @@ calculate_mcc <- function(cm) {
 }
 
 
-#' Create a Data Frame for Metric Measures
-#'
-#' This internal function creates a data frame for storing metric measures, including
-#' the measure name, its estimate, confidence interval type, and any additional notes.
-#'
-#' @param measure The name of the measure.
-#' @param estimate The formatted estimate of the measure.
-#' @param fraction The fraction representing the measure (if applicable).
-#' @param ci_type The type of confidence interval used.
-#' @param notes Additional notes or interpretation about the measure.
-#' @param estimate_raw The raw estimate value.
-#' @param lci_raw The lower limit of the confidence interval (raw).
-#' @param uci_raw The upper limit of the confidence interval (raw).
-#' @return A data frame with the specified measure details.
-#' @noRd
-measure_df <- function(measure = "", estimate = "", fraction = "",
-                       ci_type = "", notes = "", estimate_raw = NA,
-                       lci_raw = NA, uci_raw = NA) {
-
-  metric <- data.frame(
-    measure = measure,
-    summary = estimate,
-    estimate = estimate_raw,
-    conf_low = lci_raw,
-    conf_high = uci_raw,
-    fraction = fraction,
-    conf_type = ci_type,
-    notes = notes,
-    stringsAsFactors = FALSE
-  )
-
-  return_df(metric)
-
-}
-
-compare_df <- function(models = "",
-                       test = "",
-                       summary = "",
-                       p_value = "",
-                       estimate = "",
-                       conf_low = NA,
-                       conf_high = NA,
-                       statistic = "",
-                       notes = "") {
-
-  metric <- data.frame(
-    models = models,
-    test = test,
-    summary = summary,
-    p_value = p_value,
-    estimate = estimate,
-    conf_low = conf_low,
-    conf_high = conf_high,
-    statistic = statistic,
-    notes = notes,
-    stringsAsFactors = FALSE
-  )
-
-  return_df(metric)
-
-}
-
 #' Calculate a Binomial Metric
 #'
 #' This internal function calculates a binomial metric and its confidence interval

diff --git a/R/dx_utils.R b/R/dx_utils.R
@@ -305,4 +305,66 @@ two_model_name <- function(x, y) {
 }
 
 
+#' Create a Data Frame for Metric Measures
+#'
+#' This internal function creates a data frame for storing metric measures, including
+#' the measure name, its estimate, confidence interval type, and any additional notes.
+#'
+#' @param measure The name of the measure.
+#' @param estimate The formatted estimate of the measure.
+#' @param fraction The fraction representing the measure (if applicable).
+#' @param ci_type The type of confidence interval used.
+#' @param notes Additional notes or interpretation about the measure.
+#' @param estimate_raw The raw estimate value.
+#' @param lci_raw The lower limit of the confidence interval (raw).
+#' @param uci_raw The upper limit of the confidence interval (raw).
+#' @return A data frame with the specified measure details.
+#' @noRd
+measure_df <- function(measure = "", estimate = "", fraction = "",
+                       ci_type = "", notes = "", estimate_raw = NA,
+                       lci_raw = NA, uci_raw = NA) {
+
+  metric <- data.frame(
+    measure = measure,
+    summary = estimate,
+    estimate = estimate_raw,
+    conf_low = lci_raw,
+    conf_high = uci_raw,
+    fraction = fraction,
+    conf_type = ci_type,
+    notes = notes,
+    stringsAsFactors = FALSE
+  )
+
+  return_df(metric)
+
+}
+
+compare_df <- function(models = "",
+                       test = "",
+                       summary = "",
+                       p_value = "",
+                       estimate = "",
+                       conf_low = NA,
+                       conf_high = NA,
+                       statistic = "",
+                       notes = "") {
+
+  metric <- data.frame(
+    models = models,
+    test = test,
+    summary = summary,
+    p_value = p_value,
+    estimate = estimate,
+    conf_low = conf_low,
+    conf_high = conf_high,
+    statistic = statistic,
+    notes = notes,
+    stringsAsFactors = FALSE
+  )
+
+  return_df(metric)
+
+}
+