sv_importance and sv_interaction receive a sort_features option.

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: shapviz
 Title: SHAP Visualizations
-Version: 0.9.3
+Version: 0.9.4
 Authors@R: c(
     person("Michael", "Mayer", , "[email protected]", role = c("aut", "cre")),
     person("Adrian", "Stando", , "[email protected]", role = "ctb")
@@ -21,7 +21,7 @@ Depends:
     R (>= 3.6.0)
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 Imports: 
     ggfittext (>= 0.8.0),
     gggenes,

NEWS.md

@@ -1,3 +1,9 @@
+# shapviz 0.9.4
+
+## Improvements
+
+- New argument `sort_features = TRUE` in `sv_importance()` and `sv_interaction()`. Set to `FALSE` to show the features as they appear in your SHAP matrix. In that case, the plots will show the *first* `max_display` features, not the *most important* features. Implements #136.
+
 # shapviz 0.9.3
 
 ## `sv_dependence()`: Control over automatic color feature selection

R/sv_importance.R

@@ -14,7 +14,7 @@
 #' @param kind Should a "bar" plot (the default), a "beeswarm" plot, or "both" be shown?
 #'   Set to "no" in order to suppress plotting. In that case, the sorted
 #'   SHAP feature importances of all variables are returned.
-#' @param max_display Maximum number of features (with highest importance) to plot.
+#' @param max_display How many features should be plotted?
 #'   Set to `Inf` to show all features. Has no effect if `kind = "no"`.
 #' @param fill Color used to fill the bars (only used if bars are shown).
 #' @param bar_width Relative width of the bars (only used if bars are shown).
@@ -38,6 +38,7 @@
 #'   (only if `show_numbers = TRUE`). To change to scientific notation, use
 #'   `function(x) = prettyNum(x, scientific = TRUE)`.
 #' @param number_size Text size of the numbers (if `show_numbers = TRUE`).
+#' @param sort_features Should features be sorted or not? The default is `TRUE`.
 #' @param ... Arguments passed to [ggplot2::geom_bar()] (if `kind = "bar"`) or to
 #'   [ggplot2::geom_point()] otherwise. For instance, passing `alpha = 0.2` will produce
 #'   semi-transparent beeswarms, and setting `size = 3` will produce larger dots.
@@ -75,10 +76,10 @@ sv_importance.shapviz <- function(object, kind = c("bar", "beeswarm", "both", "n
                                   viridis_args = getOption("shapviz.viridis_args"),
                                   color_bar_title = "Feature value",
                                   show_numbers = FALSE, format_fun = format_max,
-                                  number_size = 3.2, ...) {
+                                  number_size = 3.2, sort_features = TRUE, ...) {
   stopifnot("format_fun must be a function" = is.function(format_fun))
   kind <- match.arg(kind)
-  imp <- .get_imp(get_shap_values(object))
+  imp <- .get_imp(get_shap_values(object), sort_features = sort_features)
 
   if (kind == "no") {
     return(imp)
@@ -162,13 +163,13 @@ sv_importance.mshapviz <- function(object, kind = c("bar", "beeswarm", "both", "
                                    viridis_args = getOption("shapviz.viridis_args"),
                                    color_bar_title = "Feature value",
                                    show_numbers = FALSE, format_fun = format_max,
-                                   number_size = 3.2, ...) {
+                                   number_size = 3.2, sort_features = TRUE, ...) {
   kind <- match.arg(kind)
   bar_type <- match.arg(bar_type)
 
   # All other cases are done via {patchwork}
   if (kind %in% c("bar", "no") && bar_type != "separate") {
-    imp <- .get_imp(get_shap_values(object))
+    imp <- .get_imp(get_shap_values(object), sort_features = sort_features)
     if (kind == "no") {
       return(imp)
     }
@@ -223,6 +224,7 @@ sv_importance.mshapviz <- function(object, kind = c("bar", "beeswarm", "both", "
     show_numbers = show_numbers,
     format_fun = format_fun,
     number_size = number_size,
+    sort_features = sort_features,
     ...
   )
   if (kind == "no") {
@@ -243,13 +245,20 @@ sv_importance.mshapviz <- function(object, kind = c("bar", "beeswarm", "both", "
   (z - r[1L]) /(r[2L] - r[1L])
 }
 
-.get_imp <- function(z) {
+.get_imp <- function(z, sort_features = TRUE) {
   if (is.matrix(z)) {
-    return(sort(colMeans(abs(z)), decreasing = TRUE))
+    imp <- colMeans(abs(z))
+    if (sort_features) {
+      imp <- sort(imp, decreasing = TRUE)
+    }
+    return(imp)
   }
   # list/mshapviz
   imp <- sapply(z, function(x) colMeans(abs(x)))
-  imp[order(-rowSums(imp)), ]
+  if (sort_features) {
+    imp <- imp[order(-rowSums(imp)), ]
+  }
+  return(imp)
 }
 
 .scale_X <- function(X) {

R/sv_interaction.R

@@ -45,12 +45,13 @@ sv_interaction.shapviz <- function(object, kind = c("beeswarm", "no"),
                                    max_display = 7L, alpha = 0.3,
                                    bee_width = 0.3, bee_adjust = 0.5,
                                    viridis_args = getOption("shapviz.viridis_args"),
-                                   color_bar_title = "Row feature value", ...) {
+                                   color_bar_title = "Row feature value",
+                                   sort_features = TRUE, ...) {
   kind <- match.arg(kind)
   if (is.null(get_shap_interactions(object))) {
     stop("No SHAP interaction values available.")
   }
-  ord <- names(.get_imp(get_shap_values(object)))
+  ord <- names(.get_imp(get_shap_values(object), sort_features = sort_features))
   object <- object[, ord]
 
   if (kind == "no") {
@@ -112,7 +113,8 @@ sv_interaction.mshapviz <- function(object, kind = c("beeswarm", "no"),
                                     max_display = 7L, alpha = 0.3,
                                     bee_width = 0.3, bee_adjust = 0.5,
                                     viridis_args = getOption("shapviz.viridis_args"),
-                                    color_bar_title = "Row feature value", ...) {
+                                    color_bar_title = "Row feature value",
+                                    sort_features = TRUE, ...) {
   kind <- match.arg(kind)
 
   plot_list <- lapply(
@@ -126,6 +128,7 @@ sv_interaction.mshapviz <- function(object, kind = c("beeswarm", "no"),
     bee_adjust = bee_adjust,
     viridis_args = viridis_args,
     color_bar_title = color_bar_title,
+    sort_features = sort_features,
     ...
   )
   if (kind == "no") {

packaging.R

@@ -15,7 +15,7 @@ library(usethis)
 use_description(
   fields = list(
     Title = "SHAP Visualizations",
-    Version = "0.9.3",
+    Version = "0.9.4",
     Description = "Visualizations for SHAP (SHapley Additive exPlanations),
     such as waterfall plots, force plots, various types of importance plots,
     dependence plots, and interaction plots.

tests/testthat/test-plots-mshapviz.R

@@ -108,20 +108,31 @@ test_that("plots work for non-syntactic column names", {
   )
 })
 
-test_that("sv_importance() and sv_interaction() and kind = 'no' gives matrix", {
-  X_pred <- data.matrix(iris[, -1L])
-  dtrain <- xgboost::xgb.DMatrix(X_pred, label = iris[, 1L], nthread = 1)
-  fit <- xgboost::xgb.train(params = list(nthread = 1L), data = dtrain, nrounds = 1L)
-  x <- shapviz(fit, X_pred = X_pred, interactions = TRUE)
-  x <- c(m1 = x, m2 = x)
+X_pred <- data.matrix(iris[, -1L])
+dtrain <- xgboost::xgb.DMatrix(X_pred, label = iris[, 1L], nthread = 1)
+fit <- xgboost::xgb.train(params = list(nthread = 1L), data = dtrain, nrounds = 1L)
+x <- shapviz(fit, X_pred = X_pred, interactions = TRUE)
+x <- c(m1 = x, m2 = x)
 
+test_that("sv_importance() and sv_interaction() and kind = 'no' gives matrix", {
   imp <- sv_importance(x, kind = "no")
   expect_true(is.matrix(imp) && all(dim(imp) == c(4L, length(x))))
 
   inter <- sv_interaction(x, kind = "no")
   expect_true(is.list(inter) && all(dim(inter[[1L]]) == rep(ncol(X_pred), 2L)))
 })
 
+
+test_that("sv_importance() and sv_interaction() respect sort_features = FALSE", {
+  imp <- sv_importance(x, kind = "no", sort_features = FALSE)
+  expect_true(all(rownames(imp) == colnames(x$m1)))
+
+  inter <- sv_interaction(x, kind = "no", sort_features = FALSE)
+  expect_true(all(rownames(inter$m1) == colnames(x$m1)))
+})
+
+
+
 test_that("sv_dependence() does not work with multiple v", {
   X_pred <- data.matrix(iris[, -1L])
   dtrain <- xgboost::xgb.DMatrix(X_pred, label = iris[, 1L], nthread = 1)

tests/testthat/test-plots-shapviz.R

@@ -173,3 +173,16 @@ test_that("sv_importance() and sv_interaction() and kind = 'no' gives numeric ou
   expect_true(is.numeric(inter) && all(dim(inter) == rep(ncol(X_pred), 2L)))
 })
 
+test_that("sv_importance() and sv_interaction() respect sort_features = FALSE", {
+  X_pred <- data.matrix(iris[, -1L])
+  dtrain <- xgboost::xgb.DMatrix(X_pred, label = iris[, 1L], nthread = 1)
+  fit <- xgboost::xgb.train(params = list(nthread = 1L), data = dtrain, nrounds = 1L)
+  x <- shapviz(fit, X_pred = X_pred, interactions = TRUE)
+
+  imp <- sv_importance(x, kind = "no", sort_features = FALSE)
+  expect_true(all(names(imp) == colnames(x)))
+
+  inter <- sv_interaction(x, kind = "no", sort_features = FALSE)
+  expect_true(all(names(inter) == colnames(x)))
+})
+