new parameters for tidymodels/embed#213

NAMESPACE

@@ -86,6 +86,7 @@ export(grid_regular)
 export(harmonic_frequency)
 export(has_unknowns)
 export(hidden_units)
+export(initial_umap)
 export(is_unknown)
 export(kernel_offset)
 export(learn_rate)
@@ -172,6 +173,7 @@ export(summary_stat)
 export(surv_dist)
 export(survival_link)
 export(svm_margin)
+export(target_weight)
 export(threshold)
 export(token)
 export(tree_depth)
@@ -189,6 +191,7 @@ export(value_set)
 export(value_transform)
 export(value_validate)
 export(values_activation)
+export(values_initial_umap)
 export(values_prune_method)
 export(values_regularization_method)
 export(values_scheduler)

R/param_initial_umap.R

@@ -0,0 +1,29 @@
+#' Initialization method for UMAP
+#'
+#' This parameter is the type of initialization for the UMAP coordinates. Can be
+#' one of `"spectral"`, `"normlaplacian"`, `"random"`, `"lvrandom"`,
+#' `"laplacian"`, `"pca"`, `"spca"`, or `"agspectral"`.See [uwot::umap()] for
+#' more details.
+#'
+#' @param values A character string of possible values. See `values_initial_umap`
+#'  in examples below.
+#'
+#' @details
+#' This parameter is used in `recipes` via [embed::step_umap()].
+#' @examples
+#' values_initial_umap
+#' initial_umap()
+#' @export
+initial_umap <- function(values = values_initial_umap) {
+  new_qual_param(
+    type = "character",
+    values = values,
+    label = c(initial_umap = "UMAP Initialization"),
+    finalize = NULL
+  )
+}
+
+#' @rdname initial_umap
+#' @export
+values_initial_umap <- c("spectral", "normlaplacian", "random", "lvrandom",
+                       "laplacian", "pca", "spca", "agspectral")

R/param_target_weight.R

@@ -0,0 +1,21 @@
+#' Amount of supervision parameter
+#'
+#' For [uwot::umap()] and [embed::step_umap()], this is a weighting factor
+#' between data topology and target topology. A value of 0.0 weights entirely
+#' on data, a value of 1.0 weights entirely on target. The default of 0.5
+#' balances the weighting equally between data and target.
+#'
+#' @inheritParams Laplace
+#' @examples
+#' target_weight()
+#' @export
+target_weight <- function(range = c(0, 1), trans = NULL) {
+  new_quant_param(
+    type = "double",
+    range = range,
+    inclusive = c(TRUE, FALSE),
+    trans = trans,
+    label = c(target_weight = "Proportion Supervised"),
+    finalize = NULL
+  )
+}

_pkgdown.yml

@@ -53,6 +53,7 @@ reference:
     - extrapolation
     - freq_cut
     - harmonic_frequency
+    - initial_umap
     - Laplace
     - learn_rate
     - max_nodes
@@ -93,6 +94,7 @@ reference:
     - summary_stat
     - surv_dist
     - survival_link
+    - target_weight
     - threshold
     - token
     - trees

tests/testthat/test-params.R

@@ -82,6 +82,7 @@ test_that("param ranges", {
   expect_equal(num_runs(c(2, 100))$range, list(lower = 2, upper = 100))
   expect_equal(harmonic_frequency(c(2, 100))$range, list(lower = 2, upper = 100))
   expect_equal(validation_set_prop(c(0.1, 0.4))$range, list(lower = 0.1, upper = 0.4))
+  expect_equal(target_weight(c(0.1, 0.4))$range, list(lower = 0.1, upper = 0.4))
 })
 
 
@@ -107,4 +108,5 @@ test_that("param values", {
   expect_equal(survival_link()$values, values_survival_link)
   expect_equal(activation()$values, values_activation)
   expect_equal(rate_schedule()$values, values_scheduler)
+  expect_equal(initial_umap()$values, values_initial_umap)
 })