rename adjust_*_calibration(type) to adjust_*_calibration(method)

R/adjust-numeric-calibration.R

@@ -1,7 +1,7 @@
 #' Re-calibrate numeric predictions
 #'
 #' @param x A [container()].
-#' @param type Character. One of `"linear"`, `"isotonic"`, or
+#' @param method Character. One of `"linear"`, `"isotonic"`, or
 #' `"isotonic_boot"`, corresponding to the function from the \pkg{probably}
 #' package [probably::cal_estimate_linear()],
 #' [probably::cal_estimate_isotonic()], or
@@ -20,20 +20,20 @@
 #' # specify calibration
 #' reg_ctr <-
 #'   container() %>%
-#'   adjust_numeric_calibration(type = "linear")
+#'   adjust_numeric_calibration(method = "linear")
 #'
 #' # train container
 #' reg_ctr_trained <- fit(reg_ctr, dat, outcome = y, estimate = y_pred)
 #'
 #' predict(reg_ctr_trained, dat)
 #' @export
-adjust_numeric_calibration <- function(x, type = NULL) {
+adjust_numeric_calibration <- function(x, method = NULL) {
   # to-do: add argument specifying `prop` in initial_split
   check_container(x, calibration_type = "numeric")
-  # wait to `check_type()` until `fit()` time
-  if (!is.null(type)) {
+  # wait to `check_method()` until `fit()` time
+  if (!is.null(method)) {
     arg_match0(
-      type,
+      method,
       c("linear", "isotonic", "isotonic_boot")
     )
   }
@@ -43,7 +43,7 @@ adjust_numeric_calibration <- function(x, type = NULL) {
       "numeric_calibration",
       inputs = "numeric",
       outputs = "numeric",
-      arguments = list(type = type),
+      arguments = list(method = method),
       results = list(),
       trained = FALSE
     )
@@ -66,13 +66,13 @@ print.numeric_calibration <- function(x, ...) {
 
 #' @export
 fit.numeric_calibration <- function(object, data, container = NULL, ...) {
-  type <- check_type(object$type, container$type)
+  method <- check_method(object$method, container$type)
   # todo: adjust_numeric_calibration() should take arguments to pass to
   # cal_estimate_* via dots
   fit <-
     eval_bare(
       call2(
-        paste0("cal_estimate_", type),
+        paste0("cal_estimate_", method),
         .data = data,
         truth = container$columns$outcome,
         estimate = container$columns$estimate,

R/adjust-probability-calibration.R

@@ -1,18 +1,18 @@
 #' Re-calibrate classification probability predictions
 #'
 #' @param x A [container()].
-#' @param type Character. One of `"logistic"`, `"multinomial"`,
+#' @param method Character. One of `"logistic"`, `"multinomial"`,
 #' `"beta"`, `"isotonic"`, or `"isotonic_boot"`, corresponding to the
 #' function from the \pkg{probably} package [probably::cal_estimate_logistic()],
 #' [probably::cal_estimate_multinomial()], etc., respectively.
 #' @export
-adjust_probability_calibration <- function(x, type = NULL) {
+adjust_probability_calibration <- function(x, method = NULL) {
   # to-do: add argument specifying `prop` in initial_split
   check_container(x, calibration_type = "probability")
-  # wait to `check_type()` until `fit()` time
-  if (!is.null(type)) {
+  # wait to `check_method()` until `fit()` time
+  if (!is.null(method)) {
     arg_match(
-      type,
+      method,
       c("logistic", "multinomial", "beta", "isotonic", "isotonic_boot")
     )
   }
@@ -22,7 +22,7 @@ adjust_probability_calibration <- function(x, type = NULL) {
       "probability_calibration",
       inputs = "probability",
       outputs = "probability_class",
-      arguments = list(type = type),
+      arguments = list(method = method),
       results = list(),
       trained = FALSE
     )
@@ -45,14 +45,14 @@ print.probability_calibration <- function(x, ...) {
 
 #' @export
 fit.probability_calibration <- function(object, data, container = NULL, ...) {
-  type <- check_type(object$type, container$type)
+  method <- check_method(object$method, container$type)
   # todo: adjust_probability_calibration() should take arguments to pass to
   # cal_estimate_* via dots
   # to-do: add argument specifying `prop` in initial_split
   fit <-
     eval_bare(
       call2(
-        paste0("cal_estimate_", type),
+        paste0("cal_estimate_", method),
         .data = data,
         # todo: make getters for the entries in `columns`
         truth = container$columns$outcome,

R/utils.R

@@ -61,13 +61,13 @@ check_container <- function(x, calibration_type = NULL, call = caller_env(), arg
   # check that the type of calibration ("numeric" or "probability") is
   # compatible with the container type
   if (!is.null(calibration_type)) {
-    container_type <- x$type
+    type <- x$type
     switch(
-      container_type,
+      type,
       regression =
-        check_calibration_type(calibration_type, "numeric", container_type, call = call),
-      binary = , multinomial =
-        check_calibration_type(calibration_type, "probability", container_type, call = call)
+        check_calibration_type(calibration_type, "numeric", type, call = call),
+      binary = , multiclass =
+        check_calibration_type(calibration_type, "probability", type, call = call)
     )
   }
 
@@ -90,54 +90,53 @@ types_binary <- c("logistic", "beta", "isotonic", "isotonic_boot")
 types_multiclass <- c("multinomial", "beta", "isotonic", "isotonic_boot")
 # a check function to be called when a container is being `fit()`ted.
 # by the time a container is fitted, we have:
-# * `adjust_type`, the `type` argument passed to an `adjust_*` function
+# * `method`, the `method` argument passed to an `adjust_*` function
 #     * this argument has already been checked to agree with the kind of
 #       `adjust_*()` function via `arg_match0()`.
 # * `container_type`, the `type` argument either specified in `container()`
 #   or inferred in `fit.container()`.
-check_type <- function(adjust_type,
-                       container_type,
-                       arg = caller_arg(adjust_type),
+check_method <- function(method,
+                       type,
+                       arg = caller_arg(method),
                        call = caller_env()) {
-  # if no `adjust_type` was supplied, infer a reasonable one based on the
-  # `container_type`
-  if (is.null(adjust_type)) {
+  # if no `method` was supplied, infer a reasonable one based on the `type`
+  if (is.null(method)) {
     switch(
-      container_type,
+      type,
       regression = return("linear"),
       binary = return("logistic"),
       multiclass = return("multinomial")
     )
   }
 
   switch(
-    container_type,
+    type,
     regression = arg_match0(
-      adjust_type,
+      method,
       types_regression,
       arg_nm = arg,
       error_call = call
     ),
     binary = arg_match0(
-      adjust_type,
+      method,
       types_binary,
       arg_nm = arg,
       error_call = call
     ),
     multiclass = arg_match0(
-      adjust_type,
+      method,
       types_multiclass,
       arg_nm = arg,
       error_call = call
     ),
     arg_match0(
-      adjust_type,
+      method,
       unique(c(types_regression, types_binary, types_multiclass)),
       arg_nm = arg,
       error_call = call
     )
   )
 
-  adjust_type
+  method
 }
 

tests/testthat/_snaps/adjust-numeric-calibration.md

@@ -15,7 +15,7 @@
       adjust_numeric_calibration(container(), "boop")
     Condition
       Error in `adjust_numeric_calibration()`:
-      ! `type` must be one of "linear", "isotonic", or "isotonic_boot", not "boop".
+      ! `method` must be one of "linear", "isotonic", or "isotonic_boot", not "boop".
 
 ---
 
@@ -31,6 +31,6 @@
       container("regression") %>% adjust_numeric_calibration("binary")
     Condition
       Error in `adjust_numeric_calibration()`:
-      ! `type` must be one of "linear", "isotonic", or "isotonic_boot", not "binary".
+      ! `method` must be one of "linear", "isotonic", or "isotonic_boot", not "binary".
       i Did you mean "linear"?
 

tests/testthat/_snaps/adjust-probability-calibration.md

@@ -15,7 +15,7 @@
       adjust_probability_calibration(container(), "boop")
     Condition
       Error in `adjust_probability_calibration()`:
-      ! `type` must be one of "logistic", "multinomial", "beta", "isotonic", or "isotonic_boot", not "boop".
+      ! `method` must be one of "logistic", "multinomial", "beta", "isotonic", or "isotonic_boot", not "boop".
 
 ---
 
@@ -31,5 +31,5 @@
       container("binary") %>% adjust_probability_calibration("linear")
     Condition
       Error in `adjust_probability_calibration()`:
-      ! `type` must be one of "logistic", "multinomial", "beta", "isotonic", or "isotonic_boot", not "linear".
+      ! `method` must be one of "logistic", "multinomial", "beta", "isotonic", or "isotonic_boot", not "linear".