replacing plyr occurences

tests/testthat/helper-plot-data.r

@@ -1,14 +1,21 @@
 # Transform the data as the coordinate system does
+library(data.table)
+# Transform the data as the coordinate system does
 cdata <- function(plot) {
   pieces <- ggplot_build(plot)
+  # Process each piece of data while maintaining panel structure
+  result <- lapply(pieces$data, function(d) {
+    dt <- as.data.table(d)
 
-  lapply(pieces$data, function(d) {
-    plyr::ddply(d, "PANEL", function(panel_data) {
-      scales <- panel_scales(pieces$panel, panel_data$PANEL[1])
+    # Explicitly group by PANEL and process each panel's data
+    dt[, {
+      scales <- panel_scales(pieces$panel, PANEL)
       details <- plot$coordinates$train(scales)
-      plot$coordinates$transform(panel_data, details)
-    })
+      as.data.table(plot$coordinates$transform(as.data.frame(.SD), details))
+    }, by = PANEL]
   })
+
+  return(result)
 }
 
 pranges <- function(plot) {

tests/testthat/test-compiler-animation.R

@@ -1,38 +1,42 @@
 acontext("animation")
 
-if(require(maps) && require(plyr)){
-  data(UStornadoes, package = "animint2")
-  stateOrder <- data.frame(state = unique(UStornadoes$state)[order(unique(UStornadoes$TornadoesSqMile), decreasing=T)], rank = 1:49) # order states by tornadoes per square mile
-  UStornadoes$state <- factor(UStornadoes$state, levels=stateOrder$state, ordered=TRUE)
-  UStornadoes$weight <- 1/UStornadoes$LandArea
-  # useful for stat_bin, etc.
-  USpolygons <- map_data("state")
-  USpolygons$state = state.abb[match(USpolygons$region, tolower(state.name))]
-  UStornadoCounts <-
-    ddply(UStornadoes, .(state, year), summarize, count=length(state))
-  tornado.anim <- list(
-    map=ggplot()+
-      geom_polygon(aes(
-        x=long, y=lat, group=group),
-        data=USpolygons,
-        clickSelects="state",
-        fill="black", colour="grey") +
-      geom_segment(aes(
-        x=startLong, y=startLat, xend=endLong, yend=endLat),
-        showSelected="year",
-        colour="#55B1F7", data=UStornadoes),
-    ts=ggplot()+
-      make_tallrect(UStornadoCounts, "year")+
-      geom_line(aes(
-        year, count, group=state),
-        clickSelects="state",
-        data=UStornadoCounts, alpha=3/5, size=4),
-    time=list(variable="year",ms=2000))
-  test_that("tornado animation frames correct", {
-    info <- animint2dir(tornado.anim, open.browser=FALSE)
-    expect_identical(info$time$sequence, as.character(1950:2012))
-  })
-}
+library(data.table)
+library(animint2)
+library(maps)
+
+data(UStornadoes, package = "animint2")
+stateOrder <- data.frame(state = unique(UStornadoes$state)[order(unique(UStornadoes$TornadoesSqMile), decreasing=T)], rank = 1:49) # order states by tornadoes per square mile
+UStornadoes$state <- factor(UStornadoes$state, levels=stateOrder$state, ordered=TRUE)
+UStornadoes$weight <- 1/UStornadoes$LandArea
+# useful for stat_bin, etc.
+USpolygons <- map_data("state")
+USpolygons$state <- state.abb[match(USpolygons$region, tolower(state.name))]
+
+UStornadoes_dt <- data.table(UStornadoes)
+UStornadoCounts <- UStornadoes_dt[, .(count = .N), by = .(state, year)]
+
+tornado.anim <- list(
+  map=ggplot()+
+    geom_polygon(aes(
+      x=long, y=lat, group=group),
+      data=USpolygons,
+      clickSelects="state",
+      fill="black", colour="grey") +
+    geom_segment(aes(
+      x=startLong, y=startLat, xend=endLong, yend=endLat),
+      showSelected="year",
+      colour="#55B1F7", data=UStornadoes_dt),
+  ts=ggplot()+
+    make_tallrect(UStornadoCounts, "year")+
+    geom_line(aes(
+      year, count, group=state),
+      clickSelects="state",
+      data=UStornadoCounts, alpha=3/5, size=4),
+  time=list(variable="year",ms=2000))
+test_that("tornado animation frames correct", {
+  info <- animint2dir(tornado.anim, open.browser=FALSE)
+  expect_identical(info$time$sequence, as.character(1950:2012))
+})
 
 ## WorldBank/gapminder example.
 data(WorldBank, package = "animint2")

tests/testthat/test-compiler-fortify.r

@@ -1,5 +1,6 @@
 context("Fortify")
 library(sp)
+library(animint2)
 
 test_that("Spatial polygons have correct ordering", {
   make_square <- function(x = 0, y = 0, height = 1, width = 1){
@@ -32,6 +33,9 @@ test_that("Spatial polygons have correct ordering", {
   polys2_sp <- SpatialPolygons(polys2)
   fake_sp2 <- SpatialPolygonsDataFrame(polys2_sp, fake_data)
 
-  expect_equivalent(fortify(fake_sp), plyr::arrange(fortify(fake_sp2), id, order))
-
+  # arranged with data.table[order(id, order)]
+  fortified_sp2 <- fortify(fake_sp2)
+  fortified_sp2 <- as.data.table(fortified_sp2)
+  fortified_sp2 <- fortified_sp2[order(id, order)]
+  expect_equivalent(fortify(fake_sp), fortified_sp2)
 })

tests/testthat/test-compiler-save-separate-chunks.R

@@ -1,5 +1,5 @@
 acontext("save separate chunks")
-library(plyr)
+library(data.table)
 
 data(FluView, package = "animint2")
 # use one season to test
@@ -85,15 +85,13 @@ test_that("save separate chunks for geom_polygon", {
 })
 
 ### test case 2
-USdots <-
-  ddply(FluView$USpolygons, .(region), summarise,
-        mean.lat = mean(lat), 
-        mean.long = mean(long))
-# add state flu to points.
-flu.points <- ldply(unique(state_flu$WEEKEND), function(we) {
+USpolygons_dt <- as.data.table(FluView$USpolygons)
+USdots <- USpolygons_dt[, .(mean.lat = mean(lat), mean.long = mean(long)), by = region]
+
+flu.points <- rbindlist(lapply(unique(state_flu$WEEKEND), function(we) {
   df <- subset(state_flu, WEEKEND == we)
   merge(USdots, df, by.x = "region", by.y = "state")
-})
+}))
 
 test_that("save separate chunks for geom_point without specifying group", {
   # the compiler will not break a geom into chunks if any of the resulting 

tests/testthat/test-renderer1-hjust-text-anchor.R

@@ -39,12 +39,13 @@ grad.desc <- function(
 
 dat <- grad.desc()
 contour <- dat$contour
-objective <- dat$objective
-objective <- plyr::ldply(objective$iteration, function(i) {
-  df <- subset(objective, iteration <= i)
-  cbind(df, iteration2 = i)
-})
-objective2 <- subset(objective, iteration == iteration2)
+objective <- as.data.table(dat$objective)
+
+objective <- objective[, {
+  .SD[, .(iteration, x, y, z, iteration2 = i)]
+}, by = .(i = iteration)][, i := NULL][]
+
+objective2 <- objective[iteration == iteration2]
 
 grad.desc.viz <- function(hjust) {
   objective2$hjust <- hjust

tests/testthat/test-renderer1-interactivity.R

@@ -178,9 +178,10 @@ UStornadoes$state <- factor(UStornadoes$state, levels=stateOrder$state, ordered=
 UStornadoes$weight <- 1/UStornadoes$LandArea
 USpolygons <- map_data("state")
 USpolygons$state = state.abb[match(USpolygons$region, tolower(state.name))]
-library(plyr)
-UStornadoCounts <-
-  ddply(UStornadoes, .(state, year), summarize, count=length(state))
+
+library(data.table) 
+UStornadoes_dt <- as.data.table(UStornadoes)
+UStornadoCounts <- UStornadoes_dt[, .(count = .N), by = .(state, year)]
 seg.color <- "#55B1F7"
 tornado.lines <- list(
   map=ggplot()+