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plotly_build.R
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#' 'Build' (i.e., evaluate) a plotly object
#'
#' This generic function creates the list object sent to plotly.js
#' for rendering. Using this function can be useful for overriding defaults
#' provided by `ggplotly`/`plot_ly` or for debugging rendering
#' errors.
#'
#' @param p a ggplot object, or a plotly object, or a list.
#' @param registerFrames should a frame trace attribute be interpreted as frames in an animation?
#' @export
#' @examples
#'
#' p <- plot_ly(economics, x = ~date, y = ~pce)
#' # the unevaluated plotly object
#' str(p)
#' # the evaluated data
#' str(plotly_build(p)$x$data)
#'
plotly_build <- function(p, registerFrames = TRUE) {
UseMethod("plotly_build")
}
#' @export
plotly_build.NULL <- function(...) {
htmltools::browsable(htmltools::div(...))
}
#' @export
plotly_build.list <- function(p, registerFrames = TRUE) {
plotly_build(as_widget(p))
}
#' @export
plotly_build.gg <- function(p, registerFrames = TRUE) {
# note: since preRenderHook = plotly_build in as_widget(),
# plotly_build.plotly() will be called on gg objects as well
plotly_build(ggplotly(p))
}
#' @export
plotly_build.plotly <- function(p, registerFrames = TRUE) {
# make this plot retrievable
set_last_plot(p)
layouts <- Map(function(x, y) {
d <- plotly_data(p, y)
x <- rapply(x, eval_attr, data = d, how = "list")
# if an annotation attribute is an array, expand into multiple annotations
nAnnotations <- max(lengths(x$annotations) %||% 0)
if (!is.null(names(x$annotations))) {
# font is the only list object, so store it, and attach after transposing
font <- x$annotations[["font"]]
x$annotations <- purrr::transpose(lapply(x$annotations, function(x) {
as.list(rep(x, length.out = nAnnotations))
}))
for (i in seq_len(nAnnotations)) {
x$annotations[[i]][["font"]] <- font
}
}
x[lengths(x) > 0]
}, p$x$layoutAttrs, names2(p$x$layoutAttrs))
# get rid of the data -> layout mapping
p$x$layoutAttrs <- NULL
# accumulate, rather than override, annotations.
annotations <- Reduce(c, c(
list(p$x$layout$annotations),
setNames(compact(lapply(layouts, "[[", "annotations")), NULL)
))
# merge layouts into a single layout (more recent layouts will override older ones)
p$x$layout <- modify_list(p$x$layout, Reduce(modify_list, layouts))
p$x$layout$annotations <- annotations
# keep frame mapping for populating layout.slider.currentvalue in animations
frameMapping <- unique(unlist(
lapply(p$x$attrs, function(x) deparse2(x[["frame"]])),
use.names = FALSE
))
if (length(frameMapping) > 1) {
warning("Only one `frame` variable is allowed", call. = FALSE)
}
# Attributes should be NULL if none exist (rather than an empty list)
if (length(p$x$attrs) == 0) p$x$attrs <- NULL
# If there is just one (unevaluated) trace, and the data is sf, add an sf layer
if (length(p$x$attrs) == 1 && !inherits(p$x$attrs[[1]], "plotly_eval") && is_sf(plotly_data(p))) {
p <- add_sf(p)
}
# If type was not specified in plot_ly(), it doesn't create a trace unless
# there are no other traces
if (is.null(p$x$attrs[[1]][["type"]]) && length(p$x$attrs) > 1) {
p$x$attrs[[1]] <- NULL
}
# have the attributes already been evaluated?
is.evaled <- function(x) inherits(x, "plotly_eval")
attrsToEval <- p$x$attrs[!vapply(p$x$attrs, is.evaled, logical(1))]
# trace type checking and renaming for plot objects
if (is_mapbox(p) || is_geo(p)) {
p <- geo2cartesian(p)
attrsToEval <- lapply(attrsToEval, function(tr) {
if (!grepl("scatter|choropleth", tr[["type"]] %||% "scatter")) {
stop("Cant add a '", tr[["type"]], "' trace to a map object", call. = FALSE)
}
if (is_mapbox(p)) tr[["type"]] <- "scattermapbox"
if (is_geo(p)) {
tr[["type"]] <- if (!is.null(tr[["z"]])) "choropleth" else "scattergeo"
}
tr
})
}
dats <- Map(function(x, y) {
# grab the data for this trace
dat <- plotly_data(p, y)
# formula/symbol/attribute evaluation
trace <- structure(
rapply(x, eval_attr, data = dat, how = "list"),
class = oldClass(x)
)
# determine trace type (if not specified, can depend on the # of data points)
# note that this should also determine a sensible mode, if appropriate
trace <- verify_type(trace)
# verify orientation of boxes/bars
trace <- verify_orientation(trace)
# supply sensible defaults based on trace type
trace <- coerce_attr_defaults(trace, p$x$layout)
# attach crosstalk info, if necessary
if (crosstalk_key() %in% names(dat) && isTRUE(trace[["inherit"]] %||% TRUE)) {
trace[["key"]] <- trace[["key"]] %||% dat[[crosstalk_key()]]
trace[["set"]] <- trace[["set"]] %||% attr(dat, "set")
}
# if appropriate, tack on a group index
grps <- if (has_group(trace)) tryNULL(dplyr::group_vars(dat))
if (length(grps) && any(lengths(trace) == NROW(dat))) {
trace[[".plotlyGroupIndex"]] <- interaction(dat[, grps, drop = F])
}
# add sensible axis names to layout
for (i in c("x", "y", "z")) {
nm <- paste0(i, "axis")
idx <- which(names(trace) %in% i)
if (length(idx) == 1) {
title <- default(deparse2(x[[idx]]))
if (is3d(trace$type) || i == "z") {
p$x$layout$scene[[nm]]$title <<- p$x$layout$scene[[nm]]$title %||% title
} else {
p$x$layout[[nm]]$title <<- p$x$layout[[nm]]$title %||% title
}
}
}
if (inherits(trace, c("plotly_surface", "plotly_contour"))) {
# TODO: generate matrix for users?
# (1) if z is vector, and x/y are null throw error
# (2) if x/y/z are vectors and length(x) * length(y) == length(z), convert z to matrix
if (!is.matrix(trace[["z"]]) || !is.numeric(trace[["z"]])) {
stop("`z` must be a numeric matrix", call. = FALSE)
}
}
# collect non-positional scales, plotly.js data_arrays, and "special"
# array attributes for "data training"
Attrs <- Schema$traces[[trace[["type"]]]]$attributes
isArray <- vapply(Attrs, function(x) {
tryFALSE(identical(x[["valType"]], "data_array"))
}, logical(1))
arrayOk <- vapply(Attrs, function(x) tryNULL(x[["arrayOk"]]) %||% FALSE, logical(1))
# "non-tidy" traces allow x/y of different lengths, so ignore those
dataArrayAttrs <- if (is_tidy(trace)) names(Attrs)[isArray | arrayOk]
allAttrs <- c(
dataArrayAttrs, special_attrs(trace), npscales(), "frame",
# for some reason, text isn't listed as a data array in some traces
# I'm looking at you scattergeo...
".plotlyGroupIndex", "text", "key", "fillcolor", "name", "legendgroup"
)
tr <- trace[names(trace) %in% allAttrs]
# TODO: does it make sense to "train" matrices/2D-tables (e.g. z)?
tr <- tr[vapply(tr, function(x) is.null(dim(x)) && is.atomic(x), logical(1))]
# white-list customdata as this can be a non-atomic vector
tr$customdata <- trace$customdata
builtData <- tibble::as_tibble(tr)
# avoid clobbering I() (i.e., variables that shouldn't be scaled)
for (i in seq_along(tr)) {
if (inherits(tr[[i]], "AsIs")) builtData[[i]] <- I(builtData[[i]])
}
if (NROW(builtData) > 0) {
# Build the index used to split one "trace" into multiple traces
isAsIs <- vapply(builtData, function(x) inherits(x, "AsIs"), logical(1))
isDiscrete <- vapply(builtData, is.discrete, logical(1))
# note: can only have one linetype per trace
isSplit <- names(builtData) %in% c("split", "linetype", "frame", "fillcolor", "name") |
!isAsIs & isDiscrete & names(builtData) %in% c("symbol", "color")
if (any(isSplit)) {
paste2 <- function(x, y) if (identical(x, y)) x else paste(x, y, sep = br())
splitVars <- builtData[isSplit]
builtData[[".plotlyTraceIndex"]] <- Reduce(paste2, splitVars)
# in registerFrames() we need to strip the frame from .plotlyTraceIndex
# so keep track of which variable it is...
trace$frameOrder <- which(names(splitVars) %in% "frame")
}
# Build the index used to determine grouping (later on, NAs are inserted
# via group2NA() to create the groups). This is done in 3 parts:
# 1. Sort data by the trace index since groups are nested within traces.
# 2. Translate missing values on positional scales to a grouping variable.
# If grouping isn't relevant for this trace, a warning is thrown since
# NAs are removed.
# 3. The grouping from (2) and any groups detected via dplyr::groups()
# are combined into a single grouping variable, .plotlyGroupIndex
builtData <- arrange_safe(builtData, ".plotlyTraceIndex")
# Missing values have special meaning for waterfall
vars <- if (trace$type != "waterfall") c("x", "y", "z")
isComplete <- complete.cases(builtData[names(builtData) %in% vars])
# warn about missing values if groups aren't relevant for this trace type
if (any(!isComplete) && !has_group(trace)) {
warning("Ignoring ", sum(!isComplete), " observations", call. = FALSE)
}
builtData[[".plotlyMissingIndex"]] <- cumsum(!isComplete)
builtData <- builtData[isComplete, ]
if (length(grps) && has_group(trace) && isTRUE(trace[["connectgaps"]])) {
stop(
"Can't use connectgaps=TRUE when data has group(s).", call. = FALSE
)
}
builtData[[".plotlyGroupIndex"]] <- interaction(
builtData[[".plotlyGroupIndex"]] %||% "",
builtData[[".plotlyMissingIndex"]]
)
builtData <- arrange_safe(builtData,
c(".plotlyTraceIndex", ".plotlyGroupIndex",
if (inherits(trace, "plotly_line")) "x")
)
builtData <- train_data(builtData, trace)
trace[[".plotlyVariableMapping"]] <- names(builtData)
# copy over to the trace data
for (i in names(builtData)) {
trace[[i]] <- builtData[[i]]
}
}
# TODO: provide a better way to clean up "high-level" attrs
trace[c("ymin", "ymax", "yend", "xend")] <- NULL
trace[lengths(trace) > 0]
}, attrsToEval, names2(attrsToEval))
p$x$attrs <- lapply(p$x$attrs, function(x) structure(x, class = "plotly_eval"))
# traceify by the interaction of discrete variables
traces <- list()
for (i in seq_along(dats)) {
d <- dats[[i]]
scaleAttrs <- names(d) %in% paste0(npscales(), "s")
traces <- c(traces, traceify(d[!scaleAttrs], d$.plotlyTraceIndex))
if (i == 1) traces[[1]] <- c(traces[[1]], d[scaleAttrs])
}
# insert NAs to differentiate groups
traces <- lapply(traces, function(x) {
d <- tibble::as_tibble(x[names(x) %in% x$.plotlyVariableMapping])
d <- group2NA(
d, if (has_group(x)) ".plotlyGroupIndex",
ordered = if (inherits(x, "plotly_line")) "x",
retrace.first = inherits(x, "plotly_polygon")
)
for (i in x$.plotlyVariableMapping) {
# try to reduce the amount of data we have to send for non-positional scales
x[[i]] <- structure(
if (i %in% npscales()) uniq(d[[i]]) else d[[i]],
class = oldClass(x[[i]])
)
}
x
})
# Map special plot_ly() arguments to plotly.js trace attributes.
# Note that symbol/linetype can modify the mode, so those are applied first
# TODO: use 'legends 2.0' to create legends for these discrete mappings
# https://github.com/plotly/plotly.js/issues/1668
if (length(traces)) {
traces <- map_symbol(traces)
traces <- map_linetype(traces)
traces <- map_size(traces)
traces <- map_size(traces, stroke = TRUE) #i.e., span
colorTitle <- unlist(lapply(p$x$attrs, function(x) { deparse2(x[["color"]] %||% x[["z"]]) }))
strokeTitle <- unlist(lapply(p$x$attrs, function(x) deparse2(x[["stroke"]])))
traces <- map_color(traces, title = paste(colorTitle, collapse = br()), colorway = colorway(p))
traces <- map_color(traces, stroke = TRUE, title = paste(strokeTitle, collapse = br()), colorway = colorway(p))
}
for (i in seq_along(traces)) {
# remove special mapping attributes
mappingAttrs <- c(
"alpha", "alpha_stroke", npscales(), paste0(npscales(), "s"),
".plotlyGroupIndex", ".plotlyMissingIndex",
".plotlyTraceIndex", ".plotlyVariableMapping", "inherit"
)
for (j in mappingAttrs) {
traces[[i]][[j]] <- NULL
}
}
# .crossTalkKey -> key
traces <- lapply(traces, function(x) {
setNames(x, sub(crosstalk_key(), "key", names(x), fixed = TRUE))
})
# it's possible that the plot object already has some traces
# (like figures pulled from a plotly server)
p$x$data <- setNames(c(p$x$data, traces), NULL)
# supply linked highlighting options/features
p <- supply_highlight_attrs(p)
# supply trace anchor and domain information
p <- supply_defaults(p)
# attribute naming corrections for "geo-like" traces
p <- cartesian2geo(p)
# Compute sensible bounding boxes for each mapbox/geo subplot
p <- fit_bounds(p)
# polar charts don't like null width/height keys
if (is.null(p$x$layout[["height"]])) p$x$layout[["height"]] <- NULL
if (is.null(p$x$layout[["width"]])) p$x$layout[["width"]] <- NULL
# ensure we get the order of categories correct
# (plotly.js uses the order in which categories appear by default)
p <- populate_categorical_axes(p)
# translate '\n' to '<br />' in text strings
p <- translate_linebreaks(p)
# if it makes sense, add markers/lines/text to mode
p <- verify_mode(p)
# annotations & shapes must be an array of objects
# TODO: should we add anything else to this?
p <- verify_arrays(p)
# set a sensible hovermode if it hasn't been specified already
p <- verify_hovermode(p)
# try to convert to webgl if toWebGl was used
p <- verify_webgl(p)
# throw warning if webgl is being used in shinytest
# currently, shinytest won't rely this warning, but it should
# https://github.com/rstudio/shinytest/issues/146
if (isTRUE(getOption("shiny.testmode"))) {
if (is.webgl(p)) warning("shinytest can't currently render WebGL-based graphics.")
}
# crosstalk dynamically adds traces, meaning that a legend could be dynamically
# added, which is confusing. So here we populate a sensible default.
p <- verify_showlegend(p)
# NOTE: this needs to occur *before* registering frames so simple/nested key
# flags get passed onto frame data.
p <- verify_key_type(p)
if (registerFrames) {
p <- registerFrames(p, frameMapping = frameMapping)
}
# set the default plotly.js events to register in shiny
p <- shiny_defaults_set(p)
p <- verify_guides(p)
# verify colorscale attributes are in a sensible data structure
p <- verify_colorscale(p)
# verify plot attributes are legal according to the plotly.js spec
p <- verify_attr_names(p)
# box up 'data_array' attributes where appropriate
p <- verify_attr_spec(p)
# make sure we're including mathjax (if TeX() is used)
p <- verify_mathjax(p)
# if a partial bundle was specified, make sure it supports the visualization
p <- verify_partial_bundle(p)
# scattergl currently doesn't render in RStudio on Windows
# https://github.com/ropensci/plotly/issues/1214
p <- verify_scattergl_platform(p)
# make sure plots don't get sent out of the network (for enterprise)
p$x$base_url <- get_domain()
p
}
# ----------------------------------------------------------------
# Functions used solely within plotly_build
# ----------------------------------------------------------------
registerFrames <- function(p, frameMapping = NULL) {
# ensure one frame value per trace, and if its missing, insert NA
p$x$data <- lapply(p$x$data, function(tr) {
tr[["frame"]] <- tr[["frame"]][[1]] %||% NA
tr
})
# the ordering of this object determines the ordering of the frames
frameAttrs <- unlist(lapply(p$x$data, "[[", "frame"))
# NOTE: getLevels() should drop NAs
frameNames <- getLevels(frameAttrs)
p$x$data <- lapply(p$x$data, function(tr) { tr$frame <- as.character(tr$frame); tr })
# remove frames from the trace names
for (i in seq_along(p$x$data)) {
tr <- p$x$data[[i]]
if (length(tr[["name"]]) != 1) next
nms <- strsplit(as.character(tr[["name"]]), br())[[1]]
idx <- setdiff(seq_along(nms), tr$frameOrder %||% 0)
p$x$data[[i]]$name <- if (length(idx)) paste(nms[idx], collapse = br()) else NULL
p$x$data[[i]]$frameOrder <- NULL
}
# exit in trivial cases
nFrames <- length(frameNames)
if (nFrames < 2) return(p)
# --------------------------------------------------------------------------
# set a "global" range of x/y (TODO: handle multiple axes?)
# --------------------------------------------------------------------------
x <- unlist(lapply(p$x$data, function(x) x[["x"]]))
if (is.numeric(x)) {
rng <- range(x, na.rm = TRUE)
if (identical(p$x$layout$xaxis$type, "log")) {
rng <- log10(rng)
rng[is.nan(rng)] <- 0
}
p$x$layout$xaxis$range <- p$x$layout$xaxis$range %||% extendrange(rng)
}
y <- unlist(lapply(p$x$data, function(x) x[["y"]]))
if (is.numeric(y)) {
rng <- range(y, na.rm = TRUE)
if (identical(p$x$layout$yaxis$type, "log")) {
rng <- log10(rng)
rng[is.nan(rng)] <- 0
}
p$x$layout$yaxis$range <- p$x$layout$yaxis$range %||% extendrange(rng)
}
# --------------------------------------------------------------------------
# Similar to setting a global x/y range, we need a "global trace range"
#
# implementation details via @rreusser: frames specify *state changes*,
# so if frame 1 has 3 traces, and frame 2 has 2 traces,
# we need to explicity supply 3 traces
# in both frames, but make 1 invisible in frame 2. For example,
# http://codepen.io/cpsievert/pen/gmXVWe
# For that reason, every frame (including the "initial" frame) has the
# max # of traces and "missing traces" are not visible (i.e., `visible=false`)
# --------------------------------------------------------------------------
# remember, at this point, frame has been removed from the trace name
frameTraceNames <- unique(unlist(lapply(p$x$data[!is.na(frameAttrs)], "[[", "name")))
for (i in seq_along(frameNames)) {
nm <- frameNames[[i]]
d <- p$x$data[sapply(p$x$data, "[[", "frame") %in% nm]
# ensure, the frames API knows what is visible/invisible
d <- lapply(d, function(tr) { tr$visible <- tr$visible %||% TRUE; tr })
# if this frame is missing a trace name, supply an invisible one
traceNamesMissing <- setdiff(frameTraceNames, sapply(d, "[[", "name"))
for (j in traceNamesMissing) {
idx <- vapply(p$x$data, function(tr) isTRUE(tr[["name"]] == j), logical(1))
idx <- which(idx)[[1]]
invisible <- modify_list(p$x$data[[idx]], list(visible = FALSE))
d <- c(d, list(invisible))
}
p$x$frames[[i]] <- list(
name = as.character(format(nm)),
data = lapply(d, function(tr) {
spec <- Schema$traces[[tr$type %||% "scatter"]]$attributes
verify_attr(tr, spec)
})
)
}
# ensure the plot knows about the "global trace range"
firstFrame <- vapply(p$x$data, function(tr) isTRUE(tr[["frame"]] %in% frameNames[[1]]), logical(1))
p$x$data[firstFrame] <- p$x$frames[[1]]$data
# remove frame traces
idx <- vapply(p$x$data, function(tr) isTRUE(tr[["frame"]] %in% frameNames[-1]), logical(1))
p$x$data[idx] <- NULL
# this works since we now have a global trace range
p$x$frames <- lapply(p$x$frames, function(f) {
f$traces <- i(which(!is.na(sapply(p$x$data, "[[", "frame"))) - 1)
f
})
# retrain color defaults
p$x$data <- colorway_retrain(p$x$data, colorway(p))
p$x$frames <- lapply(p$x$frames, function(f) {
f$data <- colorway_retrain(f$data, colorway(p)[f$traces + 1])
f
})
# populate layout.sliders.currentvalue with a sensible default
defaultvalue <- if (length(frameMapping) == 1) {
list(
prefix = paste0(frameMapping, ": "),
xanchor = 'right',
font = list(
size = 16,
color = toRGB("gray80")
)
)
} else NULL
# supply animation option defaults (a la, highlight_defaults())
p$animation <- p$animation %||% animation_opts_defaults()
# if all the frame trace data are scatter traces, set a default of redraw=F
types <- unique(unlist(lapply(p$x$frames, function(f) {
vapply(f$data, function(tr) tr$type %||% "scatter", character(1))
})))
if (identical(types, "scatter") && is.default(p$animation$frame$redraw)) {
p$animation$frame$redraw <- default(FALSE)
}
# _always_ display an animation button and slider by default
animation_button_supply(
animation_slider_supply(p, currentvalue = defaultvalue)
)
}
train_data <- function(data, trace) {
if (inherits(trace, "plotly_ribbon")) {
data <- ribbon_dat(data)
}
if (inherits(trace, "plotly_segment")) {
# TODO: this could be faster, more efficient
data$.plotlyGroupIndex <- seq_len(NROW(data))
idx <- rep(seq_len(NROW(data)), each = 2)
dat <- as.data.frame(data[!grepl("^xend$|^yend", names(data))])
dat <- dat[idx, ]
idx2 <- seq.int(2, NROW(dat), by = 2)
dat[idx2, "x"] <- data[["xend"]]
dat[idx2, "y"] <- data[["yend"]]
data <- dplyr::group_by_(dat, ".plotlyGroupIndex", add = TRUE)
}
# TODO: a lot more geoms!!!
data
}
map_size <- function(traces, stroke = FALSE) {
sizeList <- lapply(traces, "[[", if (stroke) "span" else "size")
nSizes <- lengths(sizeList)
# if no "top-level" size is present, return traces untouched
if (all(nSizes == 0)) return(traces)
allSize <- unlist(compact(sizeList))
if (!is.null(allSize) && is.discrete(allSize)) {
stop("`size`/`width` values must be numeric .", call. = FALSE)
}
sizeRange <- range(allSize, na.rm = TRUE)
mapSize <- switch(
if (stroke) "span" else "size",
span = function(trace, sizes) {
type <- trace$type %||% "scatter"
size_ <- uniq(sizes)
isSingular <- length(size_) == 1
attrs <- Schema$traces[[type]]$attributes
# `span` controls marker.line.width
if (has_attr(type, "marker")) {
s <- if (isSingular) size_ else if (array_ok(attrs$marker$line$width)) sizes
trace$marker$line <- modify_list(list(width = default(s)), trace$marker$line)
}
# `span` controls error_[x/y].thickness
for (attr in c("error_y", "error_x")) {
if (!has_attr(type, attr)) next
s <- if (isSingular) size_ else if (array_ok(attrs[[attr]]$thickness)) sizes
trace[[attr]] <- modify_list(list(thickness = default(s)), trace[[attr]])
}
# When fill exists, `span` controls line.width
if (has_fill(trace) && has_attr(type, "line")) {
s <- if (isSingular) size_ else if (array_ok(attrs$line$width)) sizes else NA
if (is.na(s)) {
warning("`line.width` does not currently support multiple values.", call. = FALSE)
} else {
trace[["line"]] <- modify_list(list(width = default(s)), trace[["line"]])
}
}
trace
},
size = function(trace, sizes) {
type <- trace$type %||% "scatter"
size_ <- uniq(sizes)
isSingular <- length(size_) == 1
attrs <- Schema$traces[[type]]$attributes
# `size` controls marker.size (note 'bar' traces have marker but not marker.size)
# TODO: always ensure an array? https://github.com/ropensci/plotly/pull/1176
if (has_attr(type, "marker") && "size" %in% names(attrs$marker)) {
s <- if (isSingular) size_ else if (array_ok(attrs$marker$size)) sizes
trace$marker <- modify_list(list(size = default(s), sizemode = default("area")), trace$marker)
}
# `size` controls textfont.size
if (has_attr(type, "textfont")) {
s <- if (isSingular) size_ else if (array_ok(attrs$textfont$size)) sizes
trace$textfont <- modify_list(list(size = default(s)), trace$textfont)
}
# `size` controls error_[x/y].width
for (attr in c("error_y", "error_x")) {
if (!has_attr(type, attr)) next
s <- if (isSingular) size_ else if (array_ok(attrs[[attr]]$width)) sizes
trace[[attr]] <- modify_list(list(width = default(s)), trace[[attr]])
}
# if fill does not exist, `size` controls line.width
if (!has_fill(trace) && has_attr(type, "line")) {
s <- if (isSingular) size_ else if (array_ok(attrs$line$width)) sizes else NA
if (is.na(s)) {
warning("`line.width` does not currently support multiple values.", call. = FALSE)
} else {
trace[["line"]] <- modify_list(list(width = default(s)), trace[["line"]])
}
}
trace
}
)
for (i in which(nSizes > 0)) {
s <- sizeList[[i]]
isConstant <- inherits(s, "AsIs")
sizeI <- if (isConstant) {
structure(s, class = setdiff(class(s), "AsIs"))
} else {
to <- if (stroke) traces[[1]][["spans"]] else traces[[1]][["sizes"]]
scales::rescale(s, from = sizeRange, to = to)
}
traces[[i]] <- mapSize(traces[[i]], sizeI)
}
traces
}
# appends a new (empty) trace to generate (plot-wide) colorbar/colorscale
map_color <- function(traces, stroke = FALSE, title = "", colorway, na.color = "transparent") {
color <- if (stroke) {
lapply(traces, function(x) { x[["stroke"]] %||% x[["color"]] })
} else {
lapply(traces, function(x) { x[["color"]] %||% if (grepl("histogram2d", x[["type"]])) c(0, 1) else if (has_attr(x[["type"]], "colorscale")) x[["surfacecolor"]] %||% x[["z"]] })
}
alphas <- if (stroke) {
vapply(traces, function(x) x$alpha_stroke %||% 1, numeric(1))
} else {
vapply(traces, function(x) x[["alpha"]] %||% 1, numeric(1))
}
isConstant <- vapply(color, function(x) inherits(x, "AsIs") || is.null(x), logical(1))
isNumeric <- vapply(color, is.numeric, logical(1)) & !isConstant
isDiscrete <- vapply(color, is.discrete, logical(1)) & !isConstant
if (any(isNumeric & isDiscrete)) stop("Can't have both discrete and numeric color mappings", call. = FALSE)
uniqColor <- lapply(color, uniq)
isSingular <- lengths(uniqColor) == 1
# color/colorscale/colorbar attribute placement depends on trace type and marker mode
# TODO: remove these and make numeric colorscale mapping more like the rest
types <- vapply(traces, function(tr) tr$type %||% "scatter", character(1))
modes <- vapply(traces, function(tr) tr$mode %||% "lines", character(1))
hasLine <- has_line(types, modes)
hasLineColor <- has_color_array(types, "line")
hasText <- has_text(types, modes)
hasTextColor <- has_color_array(types, "text")
hasZ <- has_attr(types, "colorscale") & !stroke &
any(vapply(traces, function(tr) {
!is.null(tr[["z"]]) || grepl("histogram2d", tr[["type"]])
}, logical(1)))
# IDEA - attach color codes whether they make sense, unless there is a
# vector of color codes and the target is a constant
mapColor <- switch(
if (stroke) "stroke" else "fill",
stroke = function(trace, rgba, is_colorway = FALSE) {
type <- trace$type %||% "scatter"
rgba_ <- uniq(rgba)
isSingular <- length(rgba_) == 1
attrs <- Schema$traces[[type]]$attributes
default_ <- if (is_colorway) function(x) prefix_class(default(x), "colorway") else default
if (has_attr(type, "marker")) {
col <- if (isSingular) rgba_ else if (array_ok(attrs$marker$line$color)) rgba
trace$marker$line <- modify_list(list(color = default_(col)), trace$marker$line)
}
if (has_fill(trace)) {
col <- if (isSingular) rgba_ else if (array_ok(attrs$line$color)) rgba
if (is.null(col)) {
warning("`line.color` does not currently support multiple values.", call. = FALSE)
} else {
trace$line <- modify_list(list(color = default_(col)), trace$line)
}
}
trace
},
fill = function(trace, rgba, is_colorway = FALSE) {
type <- trace$type %||% "scatter"
rgba_ <- uniq(rgba)
isSingular <- length(rgba_) == 1
attrs <- Schema$traces[[type]]$attributes
default_ <- if (is_colorway) function(x) prefix_class(default(x), "colorway") else default
# `color` controls marker.color, textfont.color, error_[x/y].color
# TODO: any more attributes that make sense to include here?
for (attr in c("marker", "textfont", "error_y", "error_x")) {
if (!has_attr(type, attr)) next
if (is_colorway && "textfont" == attr) next
col <- if (isSingular) rgba_ else if (array_ok(attrs[[attr]]$color)) rgba else NA
if (is.na(col)) {
warning("`", attr, ".color` does not currently support multiple values.", call. = FALSE)
} else {
trace[[attr]] <- modify_list(list(color = default_(col)), trace[[attr]])
}
}
# If trace has fill, `color` controls fillcolor; otherwise line.color
if (has_fill(trace)) {
if (!isSingular) warning("Only one fillcolor per trace allowed", call. = FALSE)
# alpha defaults to 0.5 when applied to fillcolor
if (is.null(trace[["alpha"]])) rgba_ <- toRGB(rgba_, 0.5)
if (isSingular) trace <- modify_list(list(fillcolor = default_(rgba_)), trace)
} else if (has_attr(type, "line")) {
# if fill does not exist, 'color' controls line.color
col <- if (isSingular) rgba_ else if (array_ok(attrs$line$color)) rgba else NA
if (is.na(col)) {
warning("`line.color` does not currently support multiple values.", call. = FALSE)
} else {
trace[["line"]] <- modify_list(list(color = default_(col)), trace[["line"]])
}
}
trace
}
)
# i.e., interpret values as color codes
if (any(isConstant)) {
colorCodes <- Map(`%||%`, color, rep(colorway, length.out = length(traces)))
colorCodes <- Map(toRGB, colorCodes[isConstant], alphas[isConstant])
isColorway <- lengths(color[isConstant]) == 0
traces[isConstant] <- Map(mapColor, traces[isConstant], colorCodes, isColorway)
}
# since stroke inherits from color, it should inherit the palette too
palette <- if (stroke) traces[[1]][["strokes"]] %||% traces[[1]][["colors"]] else traces[[1]][["colors"]]
if (any(isDiscrete)) {
# unlist() does _not_ preserve order factors
isOrdered <- all(vapply(color[isDiscrete], is.ordered, logical(1)))
lvls <- getLevels(unlist(color[isDiscrete]))
N <- length(lvls)
pal <- palette %||% if (isOrdered) viridisLite::viridis(N) else RColorBrewer::brewer.pal(N, "Set2")
colScale <- scales::col_factor(pal, levels = names(pal) %||% lvls, na.color = na.color)
color_codes <- Map(function(x, y) toRGB(colScale(as.character(x)), y), color[isDiscrete], alphas[isDiscrete])
traces[isDiscrete] <- Map(mapColor, traces[isDiscrete], color_codes)
}
if (any(isNumeric)) {
pal <- palette %||% viridisLite::viridis(10)
# TODO: use ggstat::frange() when it's on CRAN?
allColor <- unlist(color[isNumeric])
rng <- range(allColor, na.rm = TRUE)
colScale <- scales::col_numeric(pal, rng, na.color = na.color)
# generate the colorscale to be shared across traces
vals <- if (diff(rng) > 0) {
seq(rng[1], rng[2], length.out = 25)
} else {
c(0, 1)
}
colorScale <- matrix(
c(scales::rescale(vals), toRGB(colScale(vals), alphas[[1]])),
ncol = 2
)
colorObj <- list(
colorbar = lapply(list(title = as.character(title), ticklen = 2), default),
cmin = default(rng[1]),
cmax = default(rng[2]),
colorscale = default(colorScale),
showscale = default(FALSE)
)
for (i in which(isNumeric)) {
# when colorscale is being attached to `z`, we don't need color values in
# colorObj, so create colorbar trace now and exit early
if (hasZ[[i]]) {
colorObj[c("cmin", "cmax")] <- NULL
colorObj[["showscale"]] <- default(TRUE)
traces[[i]] <- modify_list(colorObj, traces[[i]])
traces[[i]] <- structure(traces[[i]], class = c("plotly_colorbar", "zcolor"))
next
}
# if trace is singular (i.e., one unique color in this trace), then there
# is no need for a colorscale, and both stroke/color have relevancy
if (isSingular[[i]]) {
col <- colScale(uniq(color[[i]]))
traces[[i]] <- mapColor(traces[[i]], toRGB(col, alphas[[i]]))
} else {
colorObj$color <- default(color[[i]])
if (stroke) {
traces[[i]]$marker$line <- modify_list(colorObj, traces[[i]]$marker$line)
} else {
traces[[i]]$marker <- modify_list(colorObj, traces[[i]]$marker)
}
if (hasLine[[i]]) {
if (hasLineColor[[i]]) {
traces[[i]]$line <- modify_list(colorObj, traces[[i]]$line)
} else {
warning("line.color doesn't (yet) support data arrays", call. = FALSE)
}
}
if (hasText[[i]]) {
if (hasTextColor[[i]]) {
traces[[i]]$textfont <- modify_list(colorObj, traces[[i]]$textfont)
} else {
warning("textfont.color doesn't (yet) support data arrays", call. = FALSE)
}
}
# TODO: how to make the summary stat (mean) customizable?
if (has_fill(traces[[i]])) {
warning("Only one fillcolor per trace allowed", call. = FALSE)
col <- toRGB(colScale(mean(colorObj$color, na.rm = TRUE)), alphas[[i]])
if (is.null(traces[[i]][["alpha"]])) col <- toRGB(col, 0.5)
traces[[i]] <- modify_list(list(fillcolor = col), traces[[i]])
}
}
}
# exit early if no additional colorbar trace is needed
if (any(hasZ)) return(traces)
if (stroke && sum(lengths(lapply(traces, "[[", "stroke"))) == 0) return(traces)
# add an "empty" trace with the colorbar
colorObj$color <- rng
colorObj$showscale <- default(TRUE)
colorBarTrace <- list(
x = range(unlist(lapply(traces, "[[", "x")), na.rm = TRUE),
y = range(unlist(lapply(traces, "[[", "y")), na.rm = TRUE),
type = if (any(types %in% glTypes())) "scattergl" else "scatter",
mode = "markers",
opacity = 0,
hoverinfo = "none",
showlegend = FALSE,
marker = colorObj
)
# 3D needs a z property
if ("scatter3d" %in% types) {
colorBarTrace$type <- "scatter3d"
colorBarTrace$z <- range(unlist(lapply(traces, "[[", "z")), na.rm = TRUE)
}
if (length(type <- intersect(c("scattergeo", "scattermapbox"), types))) {
colorBarTrace$type <- type
colorBarTrace$lat <- colorBarTrace$y
colorBarTrace$lon <- colorBarTrace$x
colorBarTrace[["x"]] <- NULL
colorBarTrace[["y"]] <- NULL
}
traces[[length(traces) + 1]] <- structure(colorBarTrace, class = "plotly_colorbar")
}
traces
}
map_symbol <- function(traces) {
symbolList <- lapply(traces, "[[", "symbol")
nSymbols <- lengths(symbolList)
# if no "top-level" symbol is present, return traces untouched
if (all(nSymbols == 0)) {
return(traces)
}
symbol <- unlist(compact(symbolList))
lvls <- getLevels(symbol)
# get a sensible default palette (also throws warnings)
pal <- setNames(scales::shape_pal()(length(lvls)), lvls)
pal <- supplyUserPalette(pal, traces[[1]][["symbols"]])
validSymbols <- as.character(Schema$traces$scatter$attributes$marker$symbol$values)
for (i in which(nSymbols > 0)) {
s <- symbolList[[i]]
symbols <- pch2symbol(if (inherits(s, "AsIs")) s else as.character(pal[as.character(s)]))
illegalSymbols <- setdiff(symbols, validSymbols)
if (length(illegalSymbols)) {
warning(
"The following are not valid symbol codes:\n'",
paste(illegalSymbols, collapse = "', '"), "'\n",
"Valid symbols include:\n'",
paste(validSymbols, collapse = "', '"), call. = FALSE
)
}
traces[[i]][["marker"]] <- modify_list(
list(symbol = default(symbols)), traces[[i]][["marker"]]
)
# ensure the mode is set so that the symbol is relevant
if (!grepl("markers", traces[[i]]$mode %||% "")) {
message("Adding markers to mode; otherwise symbol would have no effect.")
traces[[i]]$mode <- paste0(traces[[i]]$mode, "+markers")
}
}
traces
}
map_linetype <- function(traces) {
linetypeList <- lapply(traces, "[[", "linetype")
nLinetypes <- lengths(linetypeList)
# if no "top-level" linetype is present, return traces untouched
if (all(nLinetypes == 0)) return(traces)
linetype <- unlist(compact(linetypeList))
lvls <- getLevels(linetype)
# get a sensible default palette
pal <- setNames(scales::linetype_pal()(length(lvls)), lvls)
pal <- supplyUserPalette(pal, traces[[1]][["linetypes"]])
validLinetypes <- as.character(Schema$traces$scatter$attributes$line$dash$values)
if (length(pal) > length(validLinetypes)) {
warning("plotly.js only supports 6 different linetypes", call. = FALSE)
}
for (i in which(nLinetypes > 0)) {
l <- linetypeList[[i]]
dashes <- lty2dash(if (inherits(l, "AsIs")) l else as.character(pal[as.character(l)]))
illegalLinetypes <- setdiff(dashes, validLinetypes)
if (length(illegalLinetypes)) {
warning(
"The following are not valid linetype codes:\n'",
paste(illegalLinetypes, collapse = "', '"), "'\n",
"Valid linetypes include:\n'",
paste(validLinetypes, collapse = "', '"), "'", call. = FALSE
)
}
traces[[i]][["line"]] <- modify_list(
list(dash = default(dashes)), traces[[i]][["line"]]
)
# ensure the mode is set so that the linetype is relevant
if (!grepl("lines", traces[[i]]$mode %||% "")) {
message("Adding lines to mode; otherwise linetype would have no effect.")
traces[[i]][["mode"]] <- paste0(traces[[i]][["mode"]], "+lines")
}
}
traces
}
# break up a single trace into multiple traces according to values stored
# a particular key name
traceify <- function(dat, x = NULL) {
if (length(x) == 0) return(list(dat))
lvls <- if (is.factor(x)) levels(x) else unique(x)
lvls <- lvls[lvls %in% x]
# the order of lvls determines the order in which traces are drawn
# for ordered factors at least, it makes sense to draw the highest level first
# since that _should_ be the darkest color in a sequential pallette
if (is.ordered(x)) lvls <- rev(lvls)
n <- length(x)
# recursively search for a non-list of appropriate length (if it is, subset it)
recurse <- function(z, n, idx) {
if (is.list(z)) lapply(z, recurse, n, idx) else if (length(z) == n) z[idx] else z
}
new_dat <- list()
for (j in seq_along(lvls)) {
new_dat[[j]] <- lapply(dat, function(y) recurse(y, n, x %in% lvls[j]))
new_dat[[j]]$name <- new_dat[[j]]$name %||% lvls[j]
}
return(new_dat)
}