Merge pull request #227 from ropensci/baobao-trace_order

Correcting the order of traces

Author: cpsievert

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: plotly
 Title: Create Interactive Web Graphics via Plotly's JavaScript Graphing Library
-Version: 2.0.9
+Version: 2.0.10
 Authors@R: c(person("Carson", "Sievert", role = c("aut", "cre"),
     email = "[email protected]"),
     person("Chris", "Parmer", role = c("aut", "cph"),

NEWS

@@ -1,3 +1,7 @@
+2.0.10 -- 10 Dec 2015
+
+Fix #225
+
 2.0.9 -- 10 Dec 2015
 
 Fix #333

R/trace_generation.R

@@ -278,6 +278,16 @@ layer2traces <- function(l, d, misc) {
     }
   })
 
+  # reverse the traces in the following cases:
+  # geom_area
+  # geom_density with position = stack
+  if (g$geom == "area" | 
+        g$geom == "density" & l$position$.super$objname == "stack"){
+    traces <- rev(traces)
+  } else{
+    traces
+  }
+  
   ord <- order(sort.val)
   no.sort <- traces[ord]
   for(tr.i in seq_along(no.sort)){

tests/testthat/test-ggplot-area.R

@@ -22,3 +22,44 @@ test_that("transparency alpha in geom_area is converted", {
   expect_identical(L$data[[1]]$line$color, "transparent")
   expect_identical(L$data[[1]]$fillcolor, "rgba(51,51,51,0.4)")
 })
+
+save_outputs(gg, "area-fillcolor")
+
+# Test that the order of traces is correct
+# Expect traces function
+expect_traces <- function(gg, n_traces, name) {
+  stopifnot(is.ggplot(gg))
+  stopifnot(is.numeric(n_traces))
+  save_outputs(gg, paste0("area-", name))
+  L <- gg2list(gg)
+  all_traces <- L$data
+  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, layout = L$layout)
+}
+# Generate data
+df <- aggregate(price ~ cut + carat, data = diamonds, FUN = length)
+names(df)[3] <- "n"
+temp <- aggregate(n ~ carat, data = df, FUN = sum)
+names(temp)[2] <- "sum.n"
+df <- merge(x = df, y = temp, all.x = TRUE)
+df$freq <- df$n / df$sum.n
+# Generate ggplot object
+p <- ggplot(data = df, aes(x = carat, y = freq, fill = cut)) + 
+  geom_area() 
+# Test 
+test_that("traces are ordered correctly in geom_area", {
+  info <- expect_traces(p, 5, "traces_order")
+  tr <- info$traces[[1]]
+  la <- info$layout
+  expect_identical(tr$type, "scatter")
+  # check trace order
+  trace.names <- rev(levels(df$cut))
+  for (i in 1:5){
+    expect_identical(info$traces[[i]]$name, trace.names[i])
+  }
+})
+

tests/testthat/test-ggplot-density.R

@@ -10,15 +10,15 @@ expect_traces <- function(gg, n.traces, name) {
   })
   has.data <- all.traces[!no.data]
   expect_equal(length(has.data), n.traces)
-  list(traces=has.data, layout=L$layout)
+  list(data=has.data, layout=L$layout)
 }
 
 # Draw a probability density estimation using geom_density
 base <- ggplot(mtcars, aes(wt))
 
 test_that("geom_density() is translated to area chart", {
   info <- expect_traces(base + geom_density(), 1, "simple")
-  tr <- info$traces[[1]]
+  tr <- info$data[[1]]
   expect_identical(tr$type, "scatter")
   expect_identical(tr$fill, "tozeroy")
   expect_identical(tr$fillcolor, "rgba(51,51,51,0)")
@@ -27,7 +27,7 @@ test_that("geom_density() is translated to area chart", {
 test_that("geom_density() respects fill aesthetic", {
   gg <- base + geom_density(aes(fill=factor(vs)), alpha = 0.3)
   info <- expect_traces(gg, 2, "fill")
-  trs <- info$traces
+  trs <- info$data
   type <- unique(sapply(trs, "[[", "type"))
   fill <- unique(sapply(trs, "[[", "fill"))
   expect_identical(type, "scatter")
@@ -36,7 +36,7 @@ test_that("geom_density() respects fill aesthetic", {
 
 test_that("geom_density() respects colour aesthetic", {
   info <- expect_traces(base + geom_density(aes(colour=factor(vs))), 2, "color")
-  trs <- info$traces
+  trs <- info$data
   type <- unique(sapply(trs, "[[", "type"))
   fill <- unique(sapply(trs, "[[", "fill"))
   expect_identical(type, "scatter")
@@ -49,7 +49,19 @@ g <- base +
 
 test_that("geom_histogram(aes(y = ..density..)) + geom_density() works", {
   info <- expect_traces(g, 2, "histogram")
-  trs <- info$traces
+  trs <- info$data
   type <- unique(sapply(trs, "[[", "type"))
   expect_identical(sort(type), c("bar", "scatter"))
 })
+
+# Check if the traces are in the correct order when position = stack
+# Generate ggplot object
+p <- ggplot(data = mtcars, aes(x = mpg, fill = factor(cyl))) + 
+  geom_density(position = "stack")
+
+test_that("traces are ordered correctly in geom_density", {
+  info <- expect_traces(p, 3, "traces_order")
+  nms <- sapply(info$data, "[[", "name")
+  expect_identical(nms, c("8", "6", "4"))
+})
+