Merge pull request #202 from ropensci/carson-density

geom_density() as filled area chart

Author: cpsievert

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: plotly
 Type: Package
 Title: Interactive, publication-quality graphs online.
-Version: 0.5.28
+Version: 0.5.29
 Authors@R: c(person("Chris", "Parmer", role = c("aut", "cre"),
     email = "[email protected]"),
     person("Scott", "Chamberlain", role = "aut",

NEWS

@@ -1,4 +1,8 @@
-0.5.27 -- 15 April 2015
+0.5.29 -- 16 April 2015
+
+geom_density() as filled area chart #202 
+
+0.5.28 -- 15 April 2015
 
 Let ggplot handle histogram binning. Fix #198
 

R/trace_generation.R

@@ -251,10 +251,6 @@ layer2traces <- function(l, d, misc) {
         "stack"
       } else "group"
     }
-    # TODO: remove this once we reimplement density as area
-    if (g$geom == "density") {
-      tr$bargap <- 0
-    }
 
     traces <- c(traces, list(tr))
   }
@@ -354,10 +350,9 @@ toBasic <- list(
     g
   },
   density=function(g) {
-    g$params$xstart <- min(g$data$x)
-    g$params$xend <- max(g$data$x)
-    g$params$binwidth <- (max(g$data$x) - min(g$data$x))/30
-    g$data <- g$prestats.data
+    g$geom <- "area"
+    if (is.null(g$data$fill) && is.null(g$params$alpha)) g$params$alpha <- 0
+    if (is.null(g$data$colour)) g$params$colour <- "black"
     g
   },
   density2d=function(g) {
@@ -628,15 +623,6 @@ geom2trace <- list(
     L$contours=list(coloring="lines")
     L
   },
-  density=function(data, params) {
-    L <- list(x=data$x,
-              name=params$name,
-              text=data$text,
-              marker=list(color=toRGB(params$fill)),
-              type="histogram",
-              autobinx=TRUE,
-              histnorm="probability density")
-  },
   density2d=function(data, params) {
     L <- list(x=data$x,
               y=data$y,

tests/testthat/test-ggplot-density.R

@@ -1,15 +1,45 @@
 context("Probability density")
 
+expect_traces <- function(gg, n.traces, name) {
+  stopifnot(is.ggplot(gg))
+  stopifnot(is.numeric(n.traces))
+  save_outputs(gg, paste0("density-", name))
+  L <- gg2list(gg)
+  is.trace <- names(L) == ""
+  all.traces <- L[is.trace]
+  no.data <- sapply(all.traces, function(tr) {
+    is.null(tr[["x"]]) && is.null(tr[["y"]])
+  })
+  has.data <- all.traces[!no.data]
+  expect_equal(length(has.data), n.traces)
+  list(traces=has.data, kwargs=L$kwargs)
+}
+
 # Draw a probability density estimation using geom_density
-m <- ggplot(movies) + geom_density(aes(rating))
-L <- gg2list(m)
-
-test_that("geom_density is translated to a normalized histogram", {
-  expect_equal(length(L), 2)
-  expect_identical(L[[1]]$type, "histogram")
-  expect_true(L[[1]]$autobinx)
-  expect_identical(L[[1]]$histnorm, "probability density")
-  expect_equal(L[[2]]$layout$bargap, 0)
+base <- ggplot(mtcars, aes(wt))
+
+test_that("geom_density() is translated to area chart", {
+  info <- expect_traces(base + geom_density(), 1, "simple")
+  tr <- info$traces[[1]]
+  expect_identical(tr$type, "scatter")
+  expect_identical(tr$fill, "tozeroy")
+  expect_identical(tr$fillcolor, "rgba(51,51,51,0)")
 })
 
-save_outputs(m, "density")
+test_that("geom_density() respects fill aesthetic", {
+  info <- expect_traces(base + geom_density(aes(fill=factor(vs))), 2, "fill")
+  trs <- info$traces
+  type <- unique(sapply(trs, "[[", "type"))
+  fill <- unique(sapply(trs, "[[", "fill"))
+  expect_identical(type, "scatter")
+  expect_identical(fill, "tozeroy")
+})
+
+test_that("geom_density() respects colour aesthetic", {
+  info <- expect_traces(base + geom_density(aes(colour=factor(vs))), 2, "color")
+  trs <- info$traces
+  type <- unique(sapply(trs, "[[", "type"))
+  fill <- unique(sapply(trs, "[[", "fill"))
+  expect_identical(type, "scatter")
+  expect_identical(fill, "tozeroy")
+})