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#' Hyperbolic Transformations
#'
#' `step_hyperbolic` creates a *specification* of a
#' recipe step that will transform data using a hyperbolic
#' function.
#'
#' @inheritParams step_center
#' @param ... One or more selector functions to choose which
#' variables are affected by the step. See [selections()]
#' for more details. For the `tidy` method, these are not
#' currently used.
#' @param role Not used by this step since no new variables are
#' created.
#' @param func A character value for the function. Valid values
#' are "sin", "cos", or "tan".
#' @param inverse A logical: should the inverse function be used?
#' @param columns A character string of variable names that will
#' be populated (eventually) by the `terms` argument.
#' @return An updated version of `recipe` with the new step
#' added to the sequence of existing steps (if any). For the
#' `tidy` method, a tibble with columns `terms` (the
#' columns that will be affected), `inverse`, and `func`.
#' @keywords datagen
#' @concept preprocessing
#' @concept transformation_methods
#' @export
#' @examples
#' set.seed(313)
#' examples <- matrix(rnorm(40), ncol = 2)
#' examples <- as.data.frame(examples)
#'
#' rec <- recipe(~ V1 + V2, data = examples)
#'
#' cos_trans <- rec %>%
#' step_hyperbolic(all_predictors(),
#' func = "cos", inverse = FALSE)
#'
#' cos_obj <- prep(cos_trans, training = examples)
#'
#' transformed_te <- bake(cos_obj, examples)
#' plot(examples$V1, transformed_te$V1)
#'
#' tidy(cos_trans, number = 1)
#' tidy(cos_obj, number = 1)
#' @seealso [step_logit()] [step_invlogit()]
#' [step_log()] [step_sqrt()] [recipe()]
#' [prep.recipe()] [bake.recipe()]
step_hyperbolic <-
function(recipe,
...,
role = NA,
trained = FALSE,
func = "sin",
inverse = TRUE,
columns = NULL,
skip = FALSE,
id = rand_id("hyperbolic")) {
funcs <- c("sin", "cos", "tan")
if (!(func %in% funcs))
rlang::abort("`func` should be either `sin``, `cos`, or `tan`")
add_step(
recipe,
step_hyperbolic_new(
terms = ellipse_check(...),
role = role,
trained = trained,
func = func,
inverse = inverse,
columns = columns,
skip = skip,
id = id
)
)
}
step_hyperbolic_new <-
function(terms, role, trained, func, inverse, columns, skip, id) {
step(
subclass = "hyperbolic",
terms = terms,
role = role,
trained = trained,
func = func,
inverse = inverse,
columns = columns,
skip = skip,
id = id
)
}
#' @export
prep.step_hyperbolic <- function(x, training, info = NULL, ...) {
col_names <- eval_select_recipes(x$terms, training, info)
check_type(training[, col_names])
step_hyperbolic_new(
terms = x$terms,
role = x$role,
trained = TRUE,
func = x$func,
inverse = x$inverse,
columns = col_names,
skip = x$skip,
id = x$id
)
}
#' @export
bake.step_hyperbolic <- function(object, new_data, ...) {
func <- if (object$inverse)
get(paste0("a", object$func))
else
get(object$func)
col_names <- object$columns
for (i in seq_along(col_names))
new_data[, col_names[i]] <-
func(getElement(new_data, col_names[i]))
as_tibble(new_data)
}
print.step_hyperbolic <-
function(x, width = max(20, options()$width - 32), ...) {
ttl <- paste("Hyperbolic", x$func)
if (x$inverse)
ttl <- paste(ttl, "(inv)")
cat(ttl, "transformation on ")
printer(x$columns, x$terms, x$trained, width = width)
invisible(x)
}
#' @rdname step_hyperbolic
#' @param x A `step_hyperbolic` object.
#' @export
tidy.step_hyperbolic <- function(x, ...) {
out <- simple_terms(x, ...)
out$inverse <- x$inverse
out$func <- x$func
out$id <- x$id
out
}
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