container -> tailor

.Rbuildignore

@@ -1,4 +1,4 @@
-^container\.Rproj$
+^tailor\.Rproj$
 ^\.Rproj\.user$
 ^LICENSE\.md$
 ^README\.Rmd$

.github/CONTRIBUTING.md

@@ -1,6 +1,6 @@
-# Contributing to container
+# Contributing to tailor
 
-This outlines how to propose a change to container.
+This outlines how to propose a change to tailor.
 For a detailed discussion on contributing to this and other tidyverse packages, please see the [development contributing guide](https://rstd.io/tidy-contrib) and our [code review principles](https://code-review.tidyverse.org/).
 
 ## Fixing typos
@@ -18,7 +18,7 @@ See our guide on [how to create a great issue](https://code-review.tidyverse.org
 
 ### Pull request process
 
-*   Fork the package and clone onto your computer. If you haven't done this before, we recommend using `usethis::create_from_github("tidymodels/container", fork = TRUE)`.
+*   Fork the package and clone onto your computer. If you haven't done this before, we recommend using `usethis::create_from_github("tidymodels/tailor", fork = TRUE)`.
 
 *   Install all development dependencies with `devtools::install_dev_deps()`, and then make sure the package passes R CMD check by running `devtools::check()`. 
     If R CMD check doesn't pass cleanly, it's a good idea to ask for help before continuing. 
@@ -42,6 +42,6 @@ See our guide on [how to create a great issue](https://code-review.tidyverse.org
 
 ## Code of Conduct
 
-Please note that the container project is released with a
+Please note that the tailor project is released with a
 [Contributor Code of Conduct](CODE_OF_CONDUCT.md). By contributing to this
 project you agree to abide by its terms.

.github/SUPPORT.md

@@ -1,6 +1,6 @@
-# Getting help with container
+# Getting help with tailor
 
-Thanks for using container!
+Thanks for using tailor!
 Before filing an issue, there are a few places to explore and pieces to put together to make the process as smooth as possible.
 
 ## Make a reprex
@@ -16,12 +16,12 @@ Armed with your reprex, the next step is to figure out [where to ask](https://ww
 
 *   If it's a question: start with [community.rstudio.com](https://community.rstudio.com/), and/or StackOverflow. There are more people there to answer questions.  
 
-*   If it's a bug: you're in the right place, [file an issue](https://github.com/tidymodels/container/issues/new).  
+*   If it's a bug: you're in the right place, [file an issue](https://github.com/tidymodels/tailor/issues/new).  
 
 *   If you're not sure: let the community help you figure it out! 
     If your problem _is_ a bug or a feature request, you can easily return here and report it. 
 
-Before opening a new issue, be sure to [search issues and pull requests](https://github.com/tidymodels/container/issues) to make sure the bug hasn't been reported and/or already fixed in the development version. 
+Before opening a new issue, be sure to [search issues and pull requests](https://github.com/tidymodels/tailor/issues) to make sure the bug hasn't been reported and/or already fixed in the development version. 
 By default, the search will be pre-populated with `is:issue is:open`. 
 You can [edit the qualifiers](https://help.github.com/articles/searching-issues-and-pull-requests/)  (e.g. `is:pr`, `is:closed`) as needed. 
 For example, you'd simply remove `is:open` to search _all_ issues in the repo, open or closed.

DESCRIPTION

@@ -1,4 +1,4 @@
-Package: container
+Package: tailor
 Title: Sandbox for a postprocessor object
 Version: 0.0.0.9001
 Authors@R: c(
@@ -10,8 +10,8 @@ Authors@R: c(
   )
 Description: Sandbox for a postprocessor object.
 License: MIT + file LICENSE
-URL: https://github.com/tidymodels/container
-BugReports: https://github.com/tidymodels/container/issues
+URL: https://github.com/tidymodels/tailor
+BugReports: https://github.com/tidymodels/tailor/issues
 Imports: 
     cli,
     dplyr,

LICENSE

@@ -1,2 +1,2 @@
 YEAR: 2024
-COPYRIGHT HOLDER: container authors
+COPYRIGHT HOLDER: tailor authors

LICENSE.md

@@ -1,6 +1,6 @@
 # MIT License
 
-Copyright (c) 2024 container authors
+Copyright (c) 2024 tailor authors
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

NAMESPACE

@@ -1,26 +1,26 @@
 # Generated by roxygen2: do not edit by hand
 
-S3method(fit,container)
 S3method(fit,equivocal_zone)
 S3method(fit,numeric_calibration)
 S3method(fit,numeric_range)
 S3method(fit,predictions_custom)
 S3method(fit,probability_calibration)
 S3method(fit,probability_threshold)
-S3method(predict,container)
+S3method(fit,tailor)
 S3method(predict,equivocal_zone)
 S3method(predict,numeric_calibration)
 S3method(predict,numeric_range)
 S3method(predict,predictions_custom)
 S3method(predict,probability_calibration)
 S3method(predict,probability_threshold)
-S3method(print,container)
+S3method(predict,tailor)
 S3method(print,equivocal_zone)
 S3method(print,numeric_calibration)
 S3method(print,numeric_range)
 S3method(print,predictions_custom)
 S3method(print,probability_calibration)
 S3method(print,probability_threshold)
+S3method(print,tailor)
 S3method(required_pkgs,equivocal_zone)
 S3method(required_pkgs,numeric_calibration)
 S3method(required_pkgs,numeric_range)
@@ -40,11 +40,11 @@ export(adjust_numeric_range)
 export(adjust_predictions_custom)
 export(adjust_probability_calibration)
 export(adjust_probability_threshold)
-export(container)
 export(extract_parameter_dials)
 export(extract_parameter_set_dials)
 export(fit)
 export(required_pkgs)
+export(tailor)
 export(tidy)
 export(tunable)
 export(tune_args)

R/adjust-equivocal-zone.R

@@ -1,6 +1,6 @@
 #' Apply an equivocal zone to a binary classification model.
 #'
-#' @param x A [container()].
+#' @param x A [tailor()].
 #' @param value A numeric value (between zero and 1/2) or [hardhat::tune()]. The
 #' value is the size of the buffer around the threshold.
 #' @param threshold A numeric value (between zero and one) or [hardhat::tune()].
@@ -9,7 +9,7 @@
 #' library(modeldata)
 #'
 #' post_obj <-
-#'   container() %>%
+#'   tailor() %>%
 #'   adjust_equivocal_zone(value = 1 / 4)
 #'
 #'
@@ -24,7 +24,7 @@
 #' predict(post_res, two_class_example)
 #' @export
 adjust_equivocal_zone <- function(x, value = 0.1, threshold = 1 / 2) {
-  check_container(x)
+  check_tailor(x)
   if (!is_tune(value)) {
     check_number_decimal(value, min = 0, max = 1 / 2)
   }
@@ -42,7 +42,7 @@ adjust_equivocal_zone <- function(x, value = 0.1, threshold = 1 / 2) {
       trained = FALSE
     )
 
-  new_container(
+  new_tailor(
     type = x$type,
     operations = c(x$operations, list(op)),
     columns = x$dat,
@@ -68,7 +68,7 @@ print.equivocal_zone <- function(x, ...) {
 }
 
 #' @export
-fit.equivocal_zone <- function(object, data, container = NULL, ...) {
+fit.equivocal_zone <- function(object, data, tailor = NULL, ...) {
   new_operation(
     class(object),
     inputs = object$inputs,
@@ -80,9 +80,9 @@ fit.equivocal_zone <- function(object, data, container = NULL, ...) {
 }
 
 #' @export
-predict.equivocal_zone <- function(object, new_data, container, ...) {
-  est_nm <- container$columns$estimate
-  prob_nm <- container$columns$probabilities[1]
+predict.equivocal_zone <- function(object, new_data, tailor, ...) {
+  est_nm <- tailor$columns$estimate
+  prob_nm <- tailor$columns$probabilities[1]
   lvls <- levels(new_data[[est_nm]])
   col_syms <- syms(prob_nm[1])
   cls_pred <- probably::make_two_class_pred(
@@ -97,15 +97,15 @@ predict.equivocal_zone <- function(object, new_data, container, ...) {
 
 #' @export
 required_pkgs.equivocal_zone <- function(x, ...) {
-  c("container", "probably")
+  c("tailor", "probably")
 }
 
 #' @export
 tunable.equivocal_zone <- function(x, ...) {
   tibble::new_tibble(list(
     name = "buffer",
     call_info = list(list(pkg = "dials", fun = "buffer")),
-    source = "container",
+    source = "tailor",
     component = "equivocal_zone",
     component_id = "equivocal_zone"
   ))

R/adjust-numeric-calibration.R

@@ -1,6 +1,6 @@
 #' Re-calibrate numeric predictions
 #'
-#' @param x A [container()].
+#' @param x A [tailor()].
 #' @param method Character. One of `"linear"`, `"isotonic"`, or
 #' `"isotonic_boot"`, corresponding to the function from the \pkg{probably}
 #' package [probably::cal_estimate_linear()],
@@ -18,18 +18,18 @@
 #' dat
 #'
 #' # specify calibration
-#' reg_ctr <-
-#'   container() %>%
+#' reg_tailor <-
+#'   tailor() %>%
 #'   adjust_numeric_calibration(method = "linear")
 #'
-#' # train container
-#' reg_ctr_trained <- fit(reg_ctr, dat, outcome = y, estimate = y_pred)
+#' # train tailor
+#' reg_tailor_trained <- fit(reg_tailor, dat, outcome = y, estimate = y_pred)
 #'
-#' predict(reg_ctr_trained, dat)
+#' predict(reg_tailor_trained, dat)
 #' @export
 adjust_numeric_calibration <- function(x, method = NULL) {
   # to-do: add argument specifying `prop` in initial_split
-  check_container(x, calibration_type = "numeric")
+  check_tailor(x, calibration_type = "numeric")
   # wait to `check_method()` until `fit()` time
   if (!is.null(method)) {
     arg_match0(
@@ -48,7 +48,7 @@ adjust_numeric_calibration <- function(x, method = NULL) {
       trained = FALSE
     )
 
-  new_container(
+  new_tailor(
     type = x$type,
     operations = c(x$operations, list(op)),
     columns = x$dat,
@@ -65,17 +65,17 @@ print.numeric_calibration <- function(x, ...) {
 }
 
 #' @export
-fit.numeric_calibration <- function(object, data, container = NULL, ...) {
-  method <- check_method(object$method, container$type)
+fit.numeric_calibration <- function(object, data, tailor = NULL, ...) {
+  method <- check_method(object$method, tailor$type)
   # todo: adjust_numeric_calibration() should take arguments to pass to
   # cal_estimate_* via dots
   fit <-
     eval_bare(
       call2(
         paste0("cal_estimate_", method),
         .data = data,
-        truth = container$columns$outcome,
-        estimate = container$columns$estimate,
+        truth = tailor$columns$outcome,
+        estimate = tailor$columns$estimate,
         .ns = "probably"
       )
     )
@@ -91,14 +91,14 @@ fit.numeric_calibration <- function(object, data, container = NULL, ...) {
 }
 
 #' @export
-predict.numeric_calibration <- function(object, new_data, container, ...) {
+predict.numeric_calibration <- function(object, new_data, tailor, ...) {
   probably::cal_apply(new_data, object$results$fit)
 }
 
 # todo probably needs required_pkgs methods for cal objects
 #' @export
 required_pkgs.numeric_calibration <- function(x, ...) {
-  c("container", "probably")
+  c("tailor", "probably")
 }
 
 #' @export

R/adjust-numeric-range.R

@@ -1,12 +1,12 @@
 #' Truncate the range of numeric predictions
 #'
-#' @param x A [container()].
+#' @param x A [tailor()].
 #' @param upper_limit,lower_limit A numeric value, NA (for no truncation) or
 #' [hardhat::tune()].
 #' @export
 adjust_numeric_range <- function(x, lower_limit = -Inf, upper_limit = Inf) {
   # remaining input checks are done via probably::bound_prediction
-  check_container(x)
+  check_tailor(x)
 
   op <-
     new_operation(
@@ -18,7 +18,7 @@ adjust_numeric_range <- function(x, lower_limit = -Inf, upper_limit = Inf) {
       trained = FALSE
     )
 
-  new_container(
+  new_tailor(
     type = x$type,
     operations = c(x$operations, list(op)),
     columns = x$dat,
@@ -57,7 +57,7 @@ print.numeric_range <- function(x, ...) {
 }
 
 #' @export
-fit.numeric_range <- function(object, data, container = NULL, ...) {
+fit.numeric_range <- function(object, data, tailor = NULL, ...) {
   new_operation(
     class(object),
     inputs = object$inputs,
@@ -69,8 +69,8 @@ fit.numeric_range <- function(object, data, container = NULL, ...) {
 }
 
 #' @export
-predict.numeric_range <- function(object, new_data, container, ...) {
-  est_nm <- container$columns$estimate
+predict.numeric_range <- function(object, new_data, tailor, ...) {
+  est_nm <- tailor$columns$estimate
   lo <- object$arguments$lower_limit
   hi <- object$arguments$upper_limit
 
@@ -82,7 +82,7 @@ predict.numeric_range <- function(object, new_data, container, ...) {
 
 #' @export
 required_pkgs.numeric_range <- function(x, ...) {
-  c("container", "probably")
+  c("tailor", "probably")
 }
 
 #' @export
@@ -93,7 +93,7 @@ tunable.numeric_range <- function(x, ...) {
       list(pkg = "dials", fun = "lower_limit"), # todo make these dials functions
       list(pkg = "dials", fun = "upper_limit")
     ),
-    source = "container",
+    source = "tailor",
     component = "numeric_range",
     component_id = "numeric_range"
   ))