add more useful indexes

DESCRIPTION

@@ -41,11 +41,13 @@ Suggests:
  rmarkdown,
  tidyr,
  covr,
- plotly
+ plotly,
+ cassowaryr,
+ minerva
 License: MIT + file LICENSE
 LazyData: true
 URL: https://github.com/ggobi/tourr
 BugReports: https://github.com/ggobi/tourr/issues
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 Encoding: UTF-8
 VignetteBuilder: knitr

NAMESPACE

@@ -12,6 +12,8 @@ S3method(plot,path_index)
 S3method(print,history_array)
 S3method(print,tour_path)
 S3method(str,history_array)
+export(MIC)
+export(TIC)
 export(anchored_orthogonal_distance)
 export(andrews)
 export(angular_breaks)
@@ -40,6 +42,7 @@ export(center)
 export(cmass)
 export(cumulative_radial)
 export(dcor2d)
+export(dcor2d_2)
 export(dependence_tour)
 export(display_andrews)
 export(display_density2d)
@@ -75,6 +78,7 @@ export(lda_pp)
 export(linear_breaks)
 export(little_tour)
 export(local_tour)
+export(loess2d)
 export(manual_slice)
 export(mapColors)
 export(mapShapes)
@@ -109,6 +113,7 @@ export(search_posse)
 export(slice_index)
 export(sphere_data)
 export(splines2d)
+export(stringy)
 export(thaw)
 importFrom(grDevices,dev.cur)
 importFrom(grDevices,dev.flush)

R/interesting-indices.r

@@ -1,11 +1,45 @@
+#' Scagnostic indexes.
+#'
+#' Compute the scagnostic measures from the cassowaryr package
+#' @export
+stringy <- function(){
+ function(mat){
+ cassowaryr::sc_stringy(mat[,1], mat[,2])
+ }
+}
+
+
+#' Maximum and total information coefficient index.
+#'
+#' Compute the maximum and total information coefficient indexes,
+#' see \code{minerva::mine}.
+#'
+#' @rdname indexes
+#' @export
+MIC <- function(){
+ function(mat){
+ minerva::mine(mat[,1], mat[,2], alpha = 0.3, est = "mic_e")$MIC
+ }
+}
+
+#' @rdname indexes
+#' @export
+TIC <- function(){
+ function(mat){
+ minerva::mine(mat[,1], mat[,2], est = "mic_e", alpha = 0.3)$TIC
+ }
+}
+
 #' Distance correlation index.
 #'
-#' Computes the distance correlation based index on
-#' 2D projections of the data.
+#' Computes the distance correlation based index on 2D projections of the data.
+#' \code{dcor2d_2} uses the faster implementation of the distance correlation
+#' for bivariate data, see \code{energy::dcor2d}.
 #'
 #' @keywords hplot
 #' @importFrom stats na.omit
 #' @export
+#' @rdname dcor
 dcor2d <- function() {
  function(mat) {
  xy <- na.omit(data.frame(x = mat[, 1], y = mat[, 2]))
@@ -14,15 +48,26 @@ dcor2d <- function() {
  }
 }
 
-#' Spline based index.
+#' @rdname dcor
+#' @export
+dcor2d_2 <- function() {
+ function(mat) {
+ xy <- na.omit(data.frame(x = mat[, 1], y = mat[, 2]))
+ measure <- with(xy, energy::dcor2d(x, y, type = "U"))
+ return(measure)
+ }
+}
+
+#' Spline/loess based index.
 #'
 #' Compares the variance in residuals of a fitted
-#' spline model to the overall variance to find
+#' spline/loess model to the overall variance to find
 #' functional dependence in 2D projections
 #' of the data.
 #'
 #' @keywords hplot
 #' @importFrom stats residuals var
+#' @rdname spline-loess
 #' @export
 splines2d <- function() {
  function(mat) {
@@ -38,6 +83,20 @@ splines2d <- function() {
  }
 }
 
+#' @rdname spline-loess
+#' @export
+loess2d <- function() {
+ function(mat) {
+ mat <- as.data.frame(mat)
+ colnames(mat) <- c("x", "y")
+ loess_fit <- loess(y ~ x, data = mat, span = 0.05)
+ loess_fit2 <- loess(x ~ y, data = mat, span = 0.05)
+ measure <- max(1 - var(residuals(loess_fit), na.rm = T) / var(mat$y, na.rm = T),
+ 1 - var(residuals(loess_fit2), na.rm = T) / var(mat$y, na.rm = T)
+ )
+ return(measure)
+ }
+}
 
 
 #' Normality index.

_pkgdown.yml

@@ -52,6 +52,8 @@ reference:
  - slice_index
  - norm_bin
  - norm_kol
+ - stringy
+ - MIC
 - title: Search functions
  desc: >
  Functions for index optimisation in guided tour