Max Kuhn topepo

Transitioning Traditional Quarto chunks to light/dark mode

You are a terse assistant designed to help R package developers migrate Quarto content for R code chunks for figures and tables to fenced code blocks. No further commentary.

After the transition, the traditional code chunk’s label is used in the outer layer of fencing. The chunk’s label is altered to remove the prefix fig- or tbl-.

The caption from the input is removed from the R code chunk and is added to the last div layer. All other R code chunk options should remain the same.

In the new output, add a new yaml option: #| renderings: [light, dark]

Transitioning Traditional Quarto chunks to fenced divs

You are a terse assistant designed to help R package developers migrate Quarto content for R code chunks for figures and tables to fenced code blocks. No further commentary.

After the transition, the original label yaml option is used in a fenced div and the label is removed from the traditional code chunk’s options.

After the transition, the original caption yaml option is added to the last div layer and the caption is removed from the traditional code chunk’s options.

The label and caption options should be the only yaml options removed form the code chunk.

	library(tidymodels)
	library(probably)

	set.seed(12)
	example <-
	two_class_example %>%
	mutate(
	model = sample(c("logistic", "xgboost"), size = nrow(two_class_example), replace = TRUE)
	) %>%
	rename(`$@#!` = Class1, cls_2.5 = Class2)

	smooth_ph_linear_pred <- function(formula, data, deg_free = 5, grid_size = 500) {
	require(rlang)
	rlang::is_installed("survival")
	rlang::is_installed("ggplot2")
	rlang::is_installed("splines2")
	rlang::is_installed("cli")
	require(ggplot2)

	# check 1 pred and continuous
	pred_sym <- rlang::f_rhs(formula)

	# pak::pak(c("tidymodels/finetune@nested"), ask = FALSE)
	library(tidymodels)
	library(finetune)
	library(rlang)
	library(sfd)
	library(doMC)

	# ------------------------------------------------------------------------------

	tidymodels_prefer()

	library(tidymodels)
	library(doMC)

	# ------------------------------------------------------------------------------

	tidymodels_prefer()
	theme_set(theme_bw())
	options(pillar.advice = FALSE, pillar.min_title_chars = Inf)
	registerDoMC(cores = parallel::detectCores())

	# Allow fuser functions to work in tidymodels
	# See https://stackoverflow.com/questions/75871678/how-can-i-pass-an-extra-variable-to-a-tidymodels-fit-function

	# Create a function that can parse a formula that uses a special (non-existant)
	# `groups()` function. This returns a list of character vectors that has the
	# columns and their roles based on the formula. It works with '.'.

	fuser_variables <- function(f, data) {
	cl <- match.call()
	trms <- terms(f, data = data, specials = "groups")

	extract_code <- function(file) {
	# TODO we could put in an argument for the pattern
	# or something more sophisticated...
	target <- tempfile()
	knitr::purl(file, output = target, quiet = TRUE)
	code <- readLines(target)
	code <- gsub("^##.*", "", code)
	r_file <- gsub("[Rq]md$", "R", file)
	writeLines(code, r_file)
	invisible(TRUE)

	#' Check to see if a repo has remote dependencies.
	#' @param repos A character vector of repos to query (e.g. `tidyverse/dplyr`).
	#' @param hard_depend Should only depends and imports be included in the query.
	#' Using `FALSE` will include suggests and others.
	#' @details Packages listed in `Config/Needs/*` will not be returned.
	#' Requires dplyr, pak, and purrr.
	#' @return A tibble with columns for the repo and any github repos that are
	#' listed as dependencies.
	#' @examples
	#' tests <- paste0("tidymodels/", c("broom", "parsnip", "recipes"))