Toby cookbook lines

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: plotly
 Type: Package
 Title: Interactive, publication-quality graphs online.
-Version: 0.5.29
+Version: 0.5.30
 Authors@R: c(person("Chris", "Parmer", role = c("aut", "cre"),
     email = "[email protected]"),
     person("Scott", "Chamberlain", role = "aut",

NEWS

@@ -1,3 +1,7 @@
+0.5.30 -- 5 May 2015
+
+Add test-cookbook-lines.R and fix bugs that showed up in those tests.
+
 0.5.29 -- 16 April 2015
 
 geom_density() as filled area chart #202 

R/ggplotly.R

@@ -62,11 +62,12 @@ markLegends <-
        errorbarh=c("colour", "linetype"),
        area=c("colour", "fill"),
        step=c("linetype", "size", "colour"),
-       boxplot=c("x"),
        text=c("colour"))
 
 markUnique <- as.character(unique(unlist(markLegends)))
 
+markSplit <- c(markLegends,list(boxplot=c("x")))
+
 #' Convert a ggplot to a list.
 #' @import ggplot2
 #' @param p ggplot2 plot.
@@ -97,29 +98,91 @@ gg2list <- function(p){
   # worry about combining global and layer-specific aes/data later.
   for(layer.i in seq_along(p$layers)) {
     layer.aes <- p$layers[[layer.i]]$mapping
-    to.copy <- names(p$mapping)[!names(p$mapping) %in% names(layer.aes)]
-    layer.aes[to.copy] <- p$mapping[to.copy]
-    mark.names <- markUnique[markUnique %in% names(layer.aes)]
+    if(p$layers[[layer.i]]$inherit.aes){
+      to.copy <- names(p$mapping)[!names(p$mapping) %in% names(layer.aes)]
+      layer.aes[to.copy] <- p$mapping[to.copy]
+    }
+    mark.names <- names(layer.aes) # make aes.name for all aes.
     name.names <- sprintf("%s.name", mark.names)
     layer.aes[name.names] <- layer.aes[mark.names]
     p$layers[[layer.i]]$mapping <- layer.aes
     if(!is.data.frame(p$layers[[layer.i]]$data)){
       p$layers[[layer.i]]$data <- p$data
     }
   }
+
+  # Test fill and color to see if they encode a quantitative
+  # variable. This may be useful for several reasons: (1) it is
+  # sometimes possible to plot several different colors in the same
+  # trace (e.g. points), and that is faster for large numbers of
+  # data points and colors; (2) factors on x or y axes should be
+  # sent to plotly as characters, not as numeric data (which is
+  # what ggplot_build gives us).
+  misc <- list()
+  for(a in c("fill", "colour", "x", "y", "size")){
+    for(data.type in c("continuous", "date", "datetime", "discrete")){
+      fun.name <- sprintf("scale_%s_%s", a, data.type)
+      misc.name <- paste0("is.", data.type)
+      misc[[misc.name]][[a]] <- tryCatch({
+        fun <- get(fun.name)
+        suppressMessages({
+          with.scale <- original.p + fun()
+        })
+        ggplot_build(with.scale)
+        TRUE
+      }, error=function(e){
+        FALSE
+      })
+    }
+  }
+
+  ## scales are needed for legend ordering.
+  misc$breaks <- list()
+  for(sc in p$scales$scales){
+    a.vec <- sc$aesthetics
+    default.breaks <- inherits(sc$breaks, "waiver")
+    if (length(a.vec) == 1 && (!default.breaks) ) {
+      ## TODO: generalize for x/y scales too.
+      br <- sc$breaks
+      ranks <- seq_along(br)
+      names(ranks) <- br
+      misc$breaks[[a.vec]] <- ranks
+    }
+    ## store if this is a reverse scale so we can undo that later.
+    if(is.character(sc$trans$name)){
+      misc$trans[sc$aesthetics] <- sc$trans$name
+    }
+  }
+  reverse.aes <- names(misc$trans)[misc$trans=="reverse"]
 
   # Extract data from built ggplots
   built <- ggplot_build2(p)
-  # Get global x-range now because we need some of its info in layer2traces
-  ggranges <- built$panel$ranges
-  # Extract x.range
-  xrange <- sapply(ggranges, `[[`, "x.range", simplify=FALSE, USE.NAMES=FALSE)
-  ggxmin <- min(sapply(xrange, min))
-  ggxmax <- max(sapply(xrange, max))
-  # Extract y.range
-  yrange <- sapply(ggranges, `[[`, "y.range", simplify=FALSE, USE.NAMES=FALSE)
-  ggymin <- min(sapply(yrange, min))
-  ggymax <- max(sapply(yrange, max))
+  # Get global ranges now because we need some of its info in layer2traces
+  ranges.list <- list()
+  for(xy in c("x", "y")){
+    use.ranges <-
+      misc$is.continuous[[xy]] ||
+      misc$is.date[[xy]] ||
+      misc$is.datetime[[xy]] 
+    range.values <- if(use.ranges){
+      range.name <- paste0(xy, ".range")
+      sapply(built$panel$ranges, "[[", range.name)
+    }else{
+      ## for categorical variables on the axes, panel$ranges info is
+      ## meaningless.
+      name.name <- paste0(xy, ".name")
+      sapply(built$data, function(df){
+        if(name.name %in% names(df)){
+          ## usually for discrete data there is a .name column.
+          paste(df[[name.name]])
+        }else{
+          ## for heatmaps there may not be.
+          df[[xy]]
+        }
+      })
+    }
+    ranges.list[[xy]] <- range(range.values)
+  }
 
   # Get global size range because we need some of its info in layer2traces
   if ("size.name" %in% name.names) {
@@ -135,51 +198,7 @@ gg2list <- function(p){
 
     # for each layer, there is a correpsonding data.frame which
     # evaluates the aesthetic mapping.
-    df <- built$data[[i]]
-
-    # Test fill and color to see if they encode a quantitative
-    # variable. This may be useful for several reasons: (1) it is
-    # sometimes possible to plot several different colors in the same
-    # trace (e.g. points), and that is faster for large numbers of
-    # data points and colors; (2) factors on x or y axes should be
-    # sent to plotly as characters, not as numeric data (which is
-    # what ggplot_build gives us).
-    misc <- list()
-    for(a in c("fill", "colour", "x", "y", "size")){
-      for(data.type in c("continuous", "date", "datetime", "discrete")){
-        fun.name <- sprintf("scale_%s_%s", a, data.type)
-        misc.name <- paste0("is.", data.type)
-        misc[[misc.name]][[a]] <- tryCatch({
-          fun <- get(fun.name)
-          suppressMessages({
-            with.scale <- original.p + fun()
-          })
-          ggplot_build(with.scale)
-          TRUE
-        }, error=function(e){
-          FALSE
-        })
-      }
-    }
-
-    # scales are needed for legend ordering.
-    misc$breaks <- list()
-    for(sc in p$scales$scales){
-      a.vec <- sc$aesthetics
-      default.breaks <- inherits(sc$breaks, "waiver")
-      if (length(a.vec) == 1 && (!default.breaks) ) {
-        # TODO: generalize for x/y scales too.
-        br <- sc$breaks
-        ranks <- seq_along(br)
-        names(ranks) <- br
-        misc$breaks[[a.vec]] <- ranks
-      }
-      ## store if this is a reverse scale so we can undo that later.
-      if(is.character(sc$trans$name)){
-        misc$trans[sc$aesthetics] <- sc$trans$name
-      }
-    }
-    reverse.aes <- names(misc$trans)[misc$trans=="reverse"]
+    df <- built$data[[i]]    
 
     # get gglayout now because we need some of its info in layer2traces
     gglayout <- built$panel$layout
@@ -203,21 +222,24 @@ gg2list <- function(p){
     for (a in replace.aes) {
       prestats[[a]] <- -1 * prestats[[a]]
     }
-    misc$prestats.data <-
+    L$prestats.data <-
       merge(prestats,
             gglayout[, c("PANEL", "plotly.row", "COL")])
-
-    # Add global x-range info
-    misc$prestats.data$globxmin <- ggxmin
-    misc$prestats.data$globxmax <- ggxmax
-    # Add global y-range info
-    misc$prestats.data$globymin <- ggymin
-    misc$prestats.data$globymax <- ggymax
+
+    # Add global range info.
+    for(xy in names(ranges.list)){
+      range.vec <- ranges.list[[xy]]
+      names(range.vec) <- c("min", "max")
+      for(range.name in names(range.vec)){
+        glob.name <- paste0("glob", xy, range.name)
+        L$prestats.data[[glob.name]] <- range.vec[[range.name]]
+      }
+    }
 
     # Add global size info if relevant
     if ("size.name" %in% name.names) {
-      misc$prestats.data$globsizemin <- ggsizemin
-      misc$prestats.data$globsizemax <- ggsizemax
+      L$prestats.data$globsizemin <- ggsizemin
+      L$prestats.data$globsizemax <- ggsizemax
     }
 
     # This extracts essential info for this geom/layer.
@@ -415,7 +437,7 @@ gg2list <- function(p){
         sc$limits
       }else{
         if(misc$is.continuous[[xy]]){
-          ggranges[[1]][[s("%s.range")]] #TODO: facets!
+          built$panel$ranges[[1]][[s("%s.range")]] #TODO: facets!
         }else{ # for a discrete scale, range should be NULL.
           NULL
         }
@@ -594,9 +616,6 @@ gg2list <- function(p){
     layout$annotations <- annotations
   }
 
-  # Remove legend if theme has no legend position
-  layout$showlegend <- !(theme.pars$legend.position=="none")
-
   # Main plot title.
   layout$title <- built$plot$labels$title
 
@@ -612,10 +631,6 @@ gg2list <- function(p){
   layout$legend <- list(bordercolor="transparent", 
                         x=1.05, y=1/2,
                         xanchor="center", yanchor="top")
-  # Workaround for removing unnecessary legends.
-  # [markUnique != "x"] is for boxplot's particular case.
-  if (any(names(layer.aes) %in% markUnique[markUnique != "x"]) == FALSE)
-    layout$showlegend <- FALSE
 
   ## Legend hiding when guides(fill="none").
   legends.present <- unique(unlist(layer.legends))
@@ -628,12 +643,17 @@ gg2list <- function(p){
   is.hidden <- function(x){
     is.false(x) || is.none(x)
   }
+  layout$showlegend <- if(length(legends.present) == 0) FALSE else TRUE
   for(a in legends.present){
     if(is.hidden(p$guides[[a]])){
       layout$showlegend <- FALSE
     }
   }
-
+  # Legend hiding from theme.
+  if(theme.pars$legend.position=="none"){
+    layout$showlegend <- FALSE
+  }
+
   # Only show a legend title if there is at least 1 trace with
   # showlegend=TRUE.
   trace.showlegend <- sapply(trace.list, "[[", "showlegend")

R/trace_generation.R

@@ -1,7 +1,7 @@
 #' Convert a layer to a list of traces. Called from gg2list()
 #' @param l one layer of the ggplot object
 #' @param d one layer of calculated data from ggplot2::ggplot_build(p)
-#' @param misc named list.
+#' @param misc named list of plot info, independent of layer.
 #' @return list representing a layer, with corresponding aesthetics, ranges, and groups.
 #' @export
 layer2traces <- function(l, d, misc) {
@@ -12,7 +12,7 @@ layer2traces <- function(l, d, misc) {
   }
   g <- list(geom=l$geom$objname,
             data=not.na(d),
-            prestats.data=not.na(misc$prestats.data))
+            prestats.data=not.na(l$prestats.data))
 
   # needed for when group, etc. is an expression.
   g$aes <- sapply(l$mapping, function(k) as.character(as.expression(k)))
@@ -46,21 +46,22 @@ layer2traces <- function(l, d, misc) {
     g$geom <- "bar"
     bargap <- 0
   }
-  
+
   # For non-numeric data on the axes, we should take the values from
   # the original data.
   for (axis.name in c("x", "y")) {    
     if (!misc$is.continuous[[axis.name]]) {
       aes.names <- paste0(axis.name, c("", "end", "min", "max"))
       aes.used <- aes.names[aes.names %in% names(g$aes)]
       for(a in aes.used) {
+        a.name <- paste0(a, ".name")
         col.name <- g$aes[aes.used]
         dtemp <- l$data[[col.name]]
         if (is.null(dtemp)) {
-          if (!inherits(g$data[[paste0(a, ".name")]], "NULL")) {
+          if (!is.null(g$data[[a.name]])) {
             # Handle the case where as.Date() is passed in aes argument.
-            if (class(g$data[[a]]) != class(g$data[[paste0(a, ".name")]])) {
-              g$data[[a]] <- g$data[[paste0(a, ".name")]]
+            if (class(g$data[[a]]) != class(g$data[[a.name]])) {
+              g$data[[a]] <- g$data[[a.name]]
               data.vec <- g$data[[a]]
             }
           }
@@ -86,14 +87,18 @@ layer2traces <- function(l, d, misc) {
         } else if (inherits(data.vec, "factor")) {
           # Re-order data so that Plotly gets it right from ggplot2.
           g$data <- g$data[order(g$data[[a]]), ]
-          data.vec <- data.vec[match(g$data[[a]], as.numeric(data.vec))]
+          vec.i <- match(g$data[[a]], as.numeric(data.vec))
+          if(anyNA(vec.i)){
+            vec.i <- match(g$data[[a.name]], data.vec)
+          }
+          data.vec <- data.vec[vec.i]
           g$prestats.data <- g$prestats.data[order(g$prestats.data[[a]]), ]
-          pdata.vec <- pdata.vec[match(g$prestats.data[[a]],
-                                       as.numeric(pdata.vec))]
+          pvec.i <- match(g$prestats.data[[a]], as.numeric(pdata.vec))
+          pdata.vec <- pdata.vec[pvec.i]
           if (length(pdata.vec) == length(data.vec))
             pdata.vec <- data.vec
           if (!is.factor(pdata.vec))
-            pdata.vec <- g$prestats.data[[paste0(a, ".name")]]
+            pdata.vec <- g$prestats.data[[a.name]]
         }
         g$data[[a]] <- data.vec
         g$prestats.data[[a]] <- pdata.vec
@@ -131,7 +136,7 @@ layer2traces <- function(l, d, misc) {
 
   # symbol=circle,square,diamond,cross,x,
   # triangle-up,triangle-down,triangle-left,triangle-right
-  
+
   # First convert to a "basic" geom, e.g. segments become lines.
   convert <- toBasic[[g$geom]]
   basic <- if(is.null(convert)){
@@ -141,8 +146,8 @@ layer2traces <- function(l, d, misc) {
   }
   # Then split on visual characteristics that will get different
   # legend entries.
-  data.list <- if (basic$geom %in% names(markLegends)) {
-    mark.names <- markLegends[[basic$geom]]
+  data.list <- if (basic$geom %in% names(markSplit)) {
+    mark.names <- markSplit[[basic$geom]]
     # However, continuously colored points are an exception: they do
     # not need a legend entry, and they can be efficiently rendered
     # using just 1 trace.
@@ -173,7 +178,7 @@ layer2traces <- function(l, d, misc) {
   }
   # Split hline and vline when multiple panels or intercepts:
   # Need multiple traces accordingly.
-  if (g$geom == "hline" || g$geom == "vline") {
+  if (g$geom %in% c("hline", "vline")) {
     intercept <- paste0(ifelse(g$geom == "hline", "y", "x"), "intercept")
     vec.list <- basic$data[c("PANEL", intercept)]
     df.list <- split(basic$data, vec.list, drop=TRUE)