joint.bw = "mean" instead of "owm"

R/type_density.R

@@ -15,8 +15,8 @@
 #' @param joint.bw character string indicating whether (and how) the smoothing
 #'   bandwidth should be computed from the joint data distribution, in case
 #'   there are multiple subgroups (from `by` or `facet`). The default of
-#'   `"owm"` will compute the joint bandwidth as the observation-weighted mean
-#'   of the individual subgroup bandwidths. Choosing `"full"` will result in a
+#'   `"mean"` will compute the joint bandwidth as the mean of the individual
+#'   subgroup bandwidths (weighted by their number of observations). Choosing `"full"` will result in a
 #'   joint bandwidth computed from the full distribution (merging all subgroups).
 #'   For `"none"` the individual bandwidth will be computed independently for
 #'   each subgroup. When no grouped or faceted densities are visualized, the
@@ -38,7 +38,7 @@
 #'   bandwidth across all subgroups. The following strategies are available via the
 #'   `joint.bw` argument.
 #' 
-#'   The default `joint.bw = "owm"` first computes the individual bandwidths for
+#'   The default `joint.bw = "mean"` first computes the individual bandwidths for
 #'   each group but then computes their mean, weighted by the number of observations
 #'   in each group. This will work well when all groups have similar amounts of
 #'   scatter (similar variances), even when they have potentially rather different
@@ -77,7 +77,7 @@
 #' # individual subgroup bandwidths (weighted by group size) as the
 #' # joint bandwidth. Alternatively, the bandwidth from the "full"
 #' # data or separate individual bandwidths ("none") can be used.
-#' tinyplot(~Sepal.Length | Species, data = iris, type = "density") # owm (default)
+#' tinyplot(~Sepal.Length | Species, data = iris, type = "density") # mean (default)
 #' tinyplot_add(joint.bw = "full", lty = 2)                         # full data
 #' tinyplot_add(joint.bw = "none", lty = 3)                         # none (individual)
 #' legend("topright", c("Mean", "Full", "None"), lty = 1:3, bty = "n", title = "Joint BW")
@@ -91,11 +91,11 @@ type_density = function(
         kernel = c("gaussian", "epanechnikov", "rectangular", "triangular", "biweight", "cosine", "optcosine"),
         n = 512,
         # more args from density here?
-        joint.bw =  c("owm", "full", "none"),
+        joint.bw =  c("mean", "full", "none"),
         alpha = NULL
     ) {
     kernel = match.arg(kernel, c("gaussian", "epanechnikov", "rectangular", "triangular", "biweight", "cosine", "optcosine"))
-    joint.bw = match.arg(joint.bw, c("owm", "full", "none"))
+    joint.bw = match.arg(joint.bw, c("mean", "full", "none"))
     out = list(
         data = data_density(bw = bw, adjust = adjust, kernel = kernel, n = n,
                             joint.bw = joint.bw, alpha = alpha),
@@ -136,7 +136,7 @@ data_density = function(bw = "nrd0", adjust = 1, kernel = "gaussian", n = 512,
             }
             if (joint.bw == "full") {
                 dens_bw = bw_fun(kernel = bw, unlist(sapply(datapoints, `[[`, "x")))
-            } else if (joint.bw == "owm") {
+            } else if (joint.bw == "mean") {
                 bws = sapply(datapoints, function(dat) bw_fun(kernel = bw, dat$x))
                 ws = sapply(datapoints, nrow)
                 dens_bw = weighted.mean(bws, ws)

R/type_ridge.R

@@ -36,8 +36,8 @@
 #'   the version used by S.
 #' @param joint.bw character string indicating whether (and how) the smoothing
 #'   bandwidth should be computed from the joint data distribution. The default of
-#'   `"owm"` will compute the joint bandwidth as the observation-weighted mean
-#'   of the individual subgroup bandwidths. Choosing `"full"` will result in a
+#'   `"mean"` will compute the joint bandwidth as the mean of the individual
+#'   subgroup bandwidths (weighted by their number of observations). Choosing `"full"` will result in a
 #'   joint bandwidth computed from the full distribution (merging all subgroups).
 #'   For `"none"` the individual bandwidth will be computed independently for
 #'   each subgroup. See \code{\link{type_density}} for some discussion of
@@ -168,7 +168,7 @@ type_ridge = function(
     probs = NULL,
     ylevels = NULL,
     bw = "nrd0",
-    joint.bw =  c("owm", "full", "none"),
+    joint.bw =  c("mean", "full", "none"),
     adjust = 1,
     kernel = c("gaussian", "epanechnikov", "rectangular", "triangular", "biweight", "cosine", "optcosine"),
     n = 512,
@@ -180,7 +180,7 @@ type_ridge = function(
     ) {
 
   kernel = match.arg(kernel, c("gaussian", "epanechnikov", "rectangular", "triangular", "biweight", "cosine", "optcosine"))
-  joint.bw = match.arg(joint.bw, c("owm", "full", "none"))
+  joint.bw = match.arg(joint.bw, c("mean", "full", "none"))
 
   out = list(
     draw = draw_ridge(),
@@ -206,7 +206,7 @@ type_ridge = function(
 #
 ## Underlying data_ridge function
 data_ridge = function(bw = "nrd0", adjust = 1, kernel = "gaussian", n = 512,
-                      joint.bw = "owm",
+                      joint.bw = "mean",
                       scale = 1.5,
                       global.max = TRUE,
                       gradient = FALSE,
@@ -264,7 +264,7 @@ data_ridge = function(bw = "nrd0", adjust = 1, kernel = "gaussian", n = 512,
         }
         if (joint.bw == "full") {
             dens_bw = bw_fun(kernel = bw, unlist(sapply(datapoints, `[[`, "x")))
-        } else if (joint.bw == "owm") {
+        } else if (joint.bw == "mean") {
             bws = sapply(datapoints, function(dat) bw_fun(kernel = bw, dat$x))
             ws = sapply(datapoints, nrow)
             dens_bw = weighted.mean(bws, ws)

inst/tinytest/test-density.R

@@ -64,7 +64,7 @@ expect_snapshot_plot(f1, label = "density_type_bw_sj")
 f1 = function() {
   tinyplot(~ Sepal.Width | Species, iris, type = type_density(joint.bw = "none"))
   tinyplot_add(type = type_density(joint.bw = "full"), lty = 2)
-  tinyplot_add(type = type_density(joint.bw = "owm"), lty = 3)
+  tinyplot_add(type = type_density(joint.bw = "mean"), lty = 3)
   legend("topright", c("None", "Full", "OWM"), lty = 1:3, title = "Joint BW")
 }
 expect_snapshot_plot(f1, label = "density_type_joint_bw")

inst/tinytest/test-ridge.R

@@ -18,7 +18,7 @@ f = function() {
   tinyplot(
     Species ~ Sepal.Width, data = iris,
     main = 'joint.bw = "owm"',
-    type = type_ridge(joint.bw = "owm")
+    type = type_ridge(joint.bw = "mean")
   )
 }
 expect_snapshot_plot(f, label = "ridge_joint_owm")