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4 Commits

Author SHA1 Message Date
Daniel Schwabeneder
9df1ef0d4d update and enable precompiles 2020-04-04 17:38:38 +02:00
Daniel Schwabeneder
e851dcded2 move remaining user recipes in series.jl to recipes.jl 2020-04-04 17:32:45 +02:00
Daniel Schwabeneder
79f8402483 extract the recipe pipeline into separate submodule 2020-04-04 17:30:04 +02:00
Daniel Schwabeneder
f86b324200 rename some functions 2020-04-02 20:12:03 +02:00
23 changed files with 2136 additions and 1648 deletions

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@ -44,7 +44,7 @@ PlotThemes = "1"
PlotUtils = "0.6.5"
RecipesBase = "0.8"
Reexport = "0.2"
Requires = "0.5, 1.0"
Requires = "0.5, 1"
Showoff = "0.3.1"
StatsBase = "0.32"
julia = "1"
@ -53,12 +53,12 @@ julia = "1"
FileIO = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
GeometryTypes = "4d00f742-c7ba-57c2-abde-4428a4b178cb"
Gtk = "4c0ca9eb-093a-5379-98c5-f87ac0bbbf44"
HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f"
ImageMagick = "6218d12a-5da1-5696-b52f-db25d2ecc6d1"
Images = "916415d5-f1e6-5110-898d-aaa5f9f070e0"
LibGit2 = "76f85450-5226-5b5a-8eaa-529ad045b433"
OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
PGFPlotsX = "8314cec4-20b6-5062-9cdb-752b83310925"
HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f"
RDatasets = "ce6b1742-4840-55fa-b093-852dadbb1d8b"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"

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@ -163,6 +163,24 @@ using .PlotMeasures
import .PlotMeasures: Length, AbsoluteLength, Measure, width, height
# ---------------------------------------------------------
include("RecipePipeline/RecipePipeline.jl")
import .RecipePipeline
import .RecipePipeline: SliceIt,
DefaultsDict,
Formatted,
AbstractSurface,
Surface,
Volume,
is3d,
is_surface,
needs_3d_axes,
group_as_matrix,
reset_kw!,
pop_kw!,
scale_func,
inverse_scale_func,
unzip
include("types.jl")
include("utils.jl")
include("components.jl")
@ -171,7 +189,6 @@ include("args.jl")
include("themes.jl")
include("plot.jl")
include("pipeline.jl")
include("series.jl")
include("layouts.jl")
include("subplots.jl")
include("recipes.jl")

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@ -0,0 +1,97 @@
module RecipePipeline
import RecipesBase
import RecipesBase: @recipe, @series, RecipeData, is_explicit
import PlotUtils # tryrange and adapted_grid
export recipe_pipeline!
# Plots relies on these:
export SliceIt,
DefaultsDict,
Formatted,
AbstractSurface,
Surface,
Volume,
is3d,
is_surface,
needs_3d_axes,
group_as_matrix,
reset_kw!,
pop_kw!,
scale_func,
inverse_scale_func,
unzip
# API
export warn_on_recipe_aliases,
splittable_attribute,
split_attribute,
process_userrecipe!,
get_axis_limits,
is_axis_attribute,
type_alias,
plot_setup!,
slice_series_attributes!
include("api.jl")
include("utils.jl")
include("series.jl")
include("group.jl")
include("user_recipe.jl")
include("type_recipe.jl")
include("plot_recipe.jl")
include("series_recipe.jl")
"""
recipe_pipeline!(plt, plotattributes, args)
Recursively apply user recipes, type recipes, plot recipes and series recipes to build a
list of `Dict`s, each corresponding to a series. At the beginning `plotattributes`
contains only the keyword arguments passed in by the user. Add all series to the plot
bject `plt` and return it.
"""
function recipe_pipeline!(plt, plotattributes, args)
plotattributes[:plot_object] = plt
# --------------------------------
# "USER RECIPES"
# --------------------------------
# process user and type recipes
kw_list = _process_userrecipes!(plt, plotattributes, args)
# --------------------------------
# "PLOT RECIPES"
# --------------------------------
# The "Plot recipe" acts like a series type, and is processed before the plot layout
# is created, which allows for setting layouts and other plot-wide attributes.
# We get inputs which have been fully processed by "user recipes" and "type recipes",
# so we can expect standard vectors, surfaces, etc. No defaults have been set yet.
kw_list = _process_plotrecipes!(plt, kw_list)
# --------------------------------
# Plot/Subplot/Layout setup
# --------------------------------
plot_setup!(plt, plotattributes, kw_list)
# At this point, `kw_list` is fully decomposed into individual series... one KW per
# series. The next step is to recursively apply series recipes until the backend
# supports that series type.
# --------------------------------
# "SERIES RECIPES"
# --------------------------------
_process_seriesrecipes!(plt, kw_list)
# --------------------------------
# Return processed plot object
# --------------------------------
return plt
end
end

142
src/RecipePipeline/api.jl Normal file
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@ -0,0 +1,142 @@
## Warnings
"""
warn_on_recipe_aliases!(plt, plotattributes, recipe_type, args...)
Warn if an alias is dedected in `plotattributes` after a recipe of type `recipe_type` is
applied to 'args'. `recipe_type` is either `:user`, `:type`, `:plot` or `:series`.
"""
function warn_on_recipe_aliases!(plt, plotattributes, recipe_type, args...) end
## Grouping
"""
splittable_attribute(plt, key, val, len)
Returns `true` if the attribute `key` with the value `val` can be split into groups with
group provided as a vector of length `len`, `false` otherwise.
"""
splittable_attribute(plt, key, val, len) = false
splittable_attribute(plt, key, val::AbstractArray, len) =
!(key in (:group, :color_palette)) && length(axes(val, 1)) == len
splittable_attribute(plt, key, val::Tuple, n) = all(splittable_attribute.(key, val, len))
"""
split_attribute(plt, key, val, indices)
Select the proper indices from `val` for attribute `key`.
"""
split_attribute(plt, key, val::AbstractArray, indices) =
val[indices, fill(Colon(), ndims(val) - 1)...]
split_attribute(plt, key, val::Tuple, indices) =
Tuple(split_attribute(key, v, indices) for v in val)
## Preprocessing attributes
"""
preprocess_attributes!(plt, plotattributes)
Any plotting package specific preprocessing of user or recipe input happens here.
For example, Plots replaces aliases and expands magic arguments.
"""
function preprocess_attributes!(plt, plotattributes) end
# TODO: should the Plots version be defined as fallback in RecipePipeline?
"""
is_subplot_attribute(plt, attr)
Returns `true` if `attr` is a subplot attribute, otherwise `false`.
"""
is_subplot_attribute(plt, attr) = false
# TODO: should the Plots version be defined as fallback in RecipePipeline?
"""
is_axis_attribute(plt, attr)
Returns `true` if `attr` is an axis attribute, i.e. it applies to `xattr`, `yattr` and
`zattr`, otherwise `false`.
"""
is_axis_attribute(plt, attr) = false
## User recipes
"""
process_userrecipe!(plt, attributes_list, attributes)
Do plotting package specific post-processing and add series attributes to attributes_list.
For example, Plots increases the number of series in `plt`, sets `:series_plotindex` in
attributes and possible adds new series attributes for errorbars or smooth.
"""
function process_userrecipe!(plt, attributes_list, attributes)
push!(attributes_list, attributes)
end
"""
get_axis_limits(plt, letter)
Get the limits for the axis specified by `letter` (`:x`, `:y` or `:z`) in `plt`. If it
errors, `tryrange` from PlotUtils is used.
"""
get_axis_limits(plt, letter) = ErrorException("Axis limits not defined.")
## Plot recipes
"""
type_alias(plt, st)
Return the seriestype alias for `st`.
"""
type_alias(plt, st) = st
## Plot setup
"""
plot_setup!(plt, plotattributes, kw_list)
Setup plot, subplots and layouts.
For example, Plots creates the backend figure, initializes subplots, expands extrema and
links subplot axes.
"""
function plot_setup!(plt, plotattributes, kw_list) end
## Series recipes
"""
slice_series_attributes!(plt, kw_list, kw)
For attributes given as vector with one element per series, only select the value for
current series.
"""
function slice_series_attributes!(plt, kw_list, kw) end
"""
series_defaults(plt)
Returns a `Dict` storing the defaults for series attributes.
"""
series_defaults(plt) = Dict{Symbol, Any}()
# TODO: Add a more sensible fallback including e.g. path, scatter, ...
"""
is_seriestype_supported(plt, st)
Check if the plotting package natively supports the seriestype `st`.
"""
is_seriestype_supported(plt, st) = false
"""
add_series!(plt, kw)
Adds the series defined by `kw` to the plot object.
For example Plots updates the current subplot arguments, expands extrema and pushes the
the series to the series_list of `plt`.
"""
function add_series!(plt, kw) end

122
src/RecipePipeline/group.jl Normal file
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@ -0,0 +1,122 @@
"A special type that will break up incoming data into groups, and allow for easier creation of grouped plots"
mutable struct GroupBy
group_labels::Vector # length == numGroups
group_indices::Vector{Vector{Int}} # list of indices for each group
end
# this is when given a vector-type of values to group by
function _extract_group_attributes(v::AVec, args...; legend_entry = string)
group_labels = sort(collect(unique(v)))
n = length(group_labels)
if n > 100
@warn("You created n=$n groups... Is that intended?")
end
group_indices = Vector{Int}[filter(i -> v[i] == glab, eachindex(v)) for glab in group_labels]
GroupBy(map(legend_entry, group_labels), group_indices)
end
legend_entry_from_tuple(ns::Tuple) = join(ns, ' ')
# this is when given a tuple of vectors of values to group by
function _extract_group_attributes(vs::Tuple, args...)
isempty(vs) && return GroupBy([""], [axes(args[1],1)])
v = map(tuple, vs...)
_extract_group_attributes(v, args...; legend_entry = legend_entry_from_tuple)
end
# allow passing NamedTuples for a named legend entry
legend_entry_from_tuple(ns::NamedTuple) =
join(["$k = $v" for (k, v) in pairs(ns)], ", ")
function _extract_group_attributes(vs::NamedTuple, args...)
isempty(vs) && return GroupBy([""], [axes(args[1],1)])
v = map(NamedTuple{keys(vs)}tuple, values(vs)...)
_extract_group_attributes(v, args...; legend_entry = legend_entry_from_tuple)
end
# expecting a mapping of "group label" to "group indices"
function _extract_group_attributes(idxmap::Dict{T,V}, args...) where {T, V<:AVec{Int}}
group_labels = sortedkeys(idxmap)
group_indices = Vector{Int}[collect(idxmap[k]) for k in group_labels]
GroupBy(group_labels, group_indices)
end
filter_data(v::AVec, idxfilter::AVec{Int}) = v[idxfilter]
filter_data(v, idxfilter) = v
function filter_data!(plotattributes::AKW, idxfilter)
for s in (:x, :y, :z)
plotattributes[s] = filter_data(get(plotattributes, s, nothing), idxfilter)
end
end
function _filter_input_data!(plotattributes::AKW)
idxfilter = pop!(plotattributes, :idxfilter, nothing)
if idxfilter !== nothing
filter_data!(plotattributes, idxfilter)
end
end
function groupedvec2mat(x_ind, x, y::AbstractArray, groupby, def_val = y[1])
y_mat = Array{promote_type(eltype(y), typeof(def_val))}(
undef,
length(keys(x_ind)),
length(groupby.group_labels),
)
fill!(y_mat, def_val)
for i in eachindex(groupby.group_labels)
xi = x[groupby.group_indices[i]]
yi = y[groupby.group_indices[i]]
y_mat[getindex.(Ref(x_ind), xi), i] = yi
end
return y_mat
end
groupedvec2mat(x_ind, x, y::Tuple, groupby) =
Tuple(groupedvec2mat(x_ind, x, v, groupby) for v in y)
group_as_matrix(t) = false
# split the group into 1 series per group, and set the label and idxfilter for each
@recipe function f(groupby::GroupBy, args...)
plt = plotattributes[:plot_object]
group_length = maximum(union(groupby.group_indices...))
if !(group_as_matrix(args[1]))
for (i, glab) in enumerate(groupby.group_labels)
@series begin
label --> string(glab)
idxfilter --> groupby.group_indices[i]
for (key, val) in plotattributes
if splittable_attribute(plt, key, val, group_length)
:($key) := split_attribute(plt, key, val, groupby.group_indices[i])
end
end
args
end
end
else
g = args[1]
if length(g.args) == 1
x = zeros(Int, group_length)
for indexes in groupby.group_indices
x[indexes] = eachindex(indexes)
end
last_args = g.args
else
x = g.args[1]
last_args = g.args[2:end]
end
x_u = unique(sort(x))
x_ind = Dict(zip(x_u, eachindex(x_u)))
for (key, val) in plotattributes
if splittable_kw(key, val, group_length)
:($key) := groupedvec2mat(x_ind, x, val, groupby)
end
end
label --> reshape(groupby.group_labels, 1, :)
typeof(g)((
x_u,
(groupedvec2mat(x_ind, x, arg, groupby, NaN) for arg in last_args)...,
))
end
end

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@ -0,0 +1,46 @@
"""
_process_plotrecipes!(plt, kw_list)
Grab the first in line to be processed and pass it through `apply_recipe` to generate a
list of `RecipeData` objects.
If we applied a "plot recipe" without error, then add the returned datalist's KWs,
otherwise we just add the original KW.
"""
function _process_plotrecipes!(plt, kw_list)
still_to_process = kw_list
kw_list = KW[]
while !isempty(still_to_process)
next_kw = popfirst!(still_to_process)
_process_plotrecipe(plt, next_kw, kw_list, still_to_process)
end
return kw_list
end
function _process_plotrecipe(plt, kw, kw_list, still_to_process)
if !isa(get(kw, :seriestype, nothing), Symbol)
# seriestype was never set, or it's not a Symbol, so it can't be a plot recipe
push!(kw_list, kw)
return
end
try
st = kw[:seriestype]
st = kw[:seriestype] = type_alias(plt, st)
datalist = RecipesBase.apply_recipe(kw, Val{st}, plt)
warn_on_recipe_aliases!(plt, datalist, :plot, st)
for data in datalist
preprocess_attributes!(plt, data.plotattributes)
if data.plotattributes[:seriestype] == st
error("Plot recipe $st returned the same seriestype: $(data.plotattributes)")
end
push!(still_to_process, data.plotattributes)
end
catch err
if isa(err, MethodError)
push!(kw_list, kw)
else
rethrow()
end
end
return
end

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@ -0,0 +1,170 @@
const FuncOrFuncs{F} = Union{F, Vector{F}, Matrix{F}}
const MaybeNumber = Union{Number, Missing}
const MaybeString = Union{AbstractString, Missing}
const DataPoint = Union{MaybeNumber, MaybeString}
_prepare_series_data(x) = error("Cannot convert $(typeof(x)) to series data for plotting")
_prepare_series_data(::Nothing) = nothing
_prepare_series_data(t::Tuple{T, T}) where {T <: Number} = t
_prepare_series_data(f::Function) = f
_prepare_series_data(ar::AbstractRange{<:Number}) = ar
function _prepare_series_data(a::AbstractArray{<:MaybeNumber})
f = isimmutable(a) ? replace : replace!
a = f(x -> ismissing(x) || isinf(x) ? NaN : x, map(float, a))
end
_prepare_series_data(a::AbstractArray{<:Missing}) = fill(NaN, axes(a))
_prepare_series_data(a::AbstractArray{<:MaybeString}) =
replace(x -> ismissing(x) ? "" : x, a)
_prepare_series_data(s::Surface{<:AMat{<:MaybeNumber}}) =
Surface(_prepare_series_data(s.surf))
_prepare_series_data(s::Surface) = s # non-numeric Surface, such as an image
_prepare_series_data(v::Volume) =
Volume(_prepare_series_data(v.v), v.x_extents, v.y_extents, v.z_extents)
# default: assume x represents a single series
_series_data_vector(x, plotattributes) = [_prepare_series_data(x)]
# fixed number of blank series
_series_data_vector(n::Integer, plotattributes) = [zeros(0) for i in 1:n]
# vector of data points is a single series
_series_data_vector(v::AVec{<:DataPoint}, plotattributes) = [_prepare_series_data(v)]
# list of things (maybe other vectors, functions, or something else)
function _series_data_vector(v::AVec, plotattributes)
if all(x -> x isa MaybeNumber, v)
_series_data_vector(Vector{MaybeNumber}(v), plotattributes)
elseif all(x -> x isa MaybeString, v)
_series_data_vector(Vector{MaybeString}(v), plotattributes)
else
vcat((_series_data_vector(vi, plotattributes) for vi in v)...)
end
end
# Matrix is split into columns
function _series_data_vector(v::AMat{<:DataPoint}, plotattributes)
if is3d(plotattributes)
[_prepare_series_data(Surface(v))]
else
[_prepare_series_data(v[:, i]) for i in axes(v, 2)]
end
end
# --------------------------------------------------------------------
# Fillranges & ribbons
_process_fillrange(range::Number, plotattributes) = [range]
_process_fillrange(range, plotattributes) = _series_data_vector(range, plotattributes)
_process_ribbon(ribbon::Number, plotattributes) = [ribbon]
_process_ribbon(ribbon, plotattributes) = _series_data_vector(ribbon, plotattributes)
# ribbon as a tuple: (lower_ribbons, upper_ribbons)
_process_ribbon(ribbon::Tuple{S, T}, plotattributes) where {S, T} = collect(zip(
_series_data_vector(ribbon[1], plotattributes),
_series_data_vector(ribbon[2], plotattributes),
))
# --------------------------------------------------------------------
_compute_x(x::Nothing, y::Nothing, z) = axes(z, 1)
_compute_x(x::Nothing, y, z) = axes(y, 1)
_compute_x(x::Function, y, z) = map(x, y)
_compute_x(x, y, z) = x
_compute_y(x::Nothing, y::Nothing, z) = axes(z, 2)
_compute_y(x, y::Function, z) = map(y, x)
_compute_y(x, y, z) = y
_compute_z(x, y, z::Function) = map(z, x, y)
_compute_z(x, y, z::AbstractMatrix) = Surface(z)
_compute_z(x, y, z::Nothing) = nothing
_compute_z(x, y, z) = z
_nobigs(v::AVec{BigFloat}) = map(Float64, v)
_nobigs(v::AVec{BigInt}) = map(Int64, v)
_nobigs(v) = v
@noinline function _compute_xyz(x, y, z)
x = _compute_x(x, y, z)
y = _compute_y(x, y, z)
z = _compute_z(x, y, z)
_nobigs(x), _nobigs(y), _nobigs(z)
end
# not allowed
_compute_xyz(x::Nothing, y::FuncOrFuncs{F}, z) where {F <: Function} =
error("If you want to plot the function `$y`, you need to define the x values!")
_compute_xyz(x::Nothing, y::Nothing, z::FuncOrFuncs{F}) where {F <: Function} =
error("If you want to plot the function `$z`, you need to define x and y values!")
_compute_xyz(x::Nothing, y::Nothing, z::Nothing) = error("x/y/z are all nothing!")
# --------------------------------------------------------------------
# we are going to build recipes to do the processing and splitting of the args
# --------------------------------------------------------------------
# The catch-all SliceIt recipe
# --------------------------------------------------------------------
# ensure we dispatch to the slicer
struct SliceIt end
# TODO: Should ribbon and fillrange be handled by the plotting package?
# The `SliceIt` recipe finishes user and type recipe processing.
# It splits processed data into individual series data, stores in copied `plotattributes`
# for each series and returns no arguments.
@recipe function f(::Type{SliceIt}, x, y, z)
# handle data with formatting attached
if typeof(x) <: Formatted
xformatter := x.formatter
x = x.data
end
if typeof(y) <: Formatted
yformatter := y.formatter
y = y.data
end
if typeof(z) <: Formatted
zformatter := z.formatter
z = z.data
end
xs = _series_data_vector(x, plotattributes)
ys = _series_data_vector(y, plotattributes)
zs = _series_data_vector(z, plotattributes)
fr = pop!(plotattributes, :fillrange, nothing)
fillranges = _process_fillrange(fr, plotattributes)
mf = length(fillranges)
rib = pop!(plotattributes, :ribbon, nothing)
ribbons = _process_ribbon(rib, plotattributes)
mr = length(ribbons)
mx = length(xs)
my = length(ys)
mz = length(zs)
if mx > 0 && my > 0 && mz > 0
for i in 1:max(mx, my, mz)
# add a new series
di = copy(plotattributes)
xi, yi, zi = xs[mod1(i, mx)], ys[mod1(i, my)], zs[mod1(i, mz)]
di[:x], di[:y], di[:z] = _compute_xyz(xi, yi, zi)
# handle fillrange
fr = fillranges[mod1(i, mf)]
di[:fillrange] = isa(fr, Function) ? map(fr, di[:x]) : fr
# handle ribbons
rib = ribbons[mod1(i, mr)]
di[:ribbon] = isa(rib, Function) ? map(rib, di[:x]) : rib
push!(series_list, RecipeData(di, ()))
end
end
nothing # don't add a series for the main block
end

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@ -0,0 +1,62 @@
"""
_process_seriesrecipes!(plt, kw_list)
Recursively apply series recipes until the backend supports the seriestype
"""
function _process_seriesrecipes!(plt, kw_list)
for kw in kw_list
# in series attributes given as vector with one element per series,
# select the value for current series
slice_series_attributes!(plt, kw_list, kw)
series_attr = DefaultsDict(kw, series_defaults(plt))
# now we have a fully specified series, with colors chosen. we must recursively
# handle series recipes, which dispatch on seriestype. If a backend does not
# natively support a seriestype, we check for a recipe that will convert that
# series type into one made up of lower-level components.
# For example, a histogram is just a bar plot with binned data, a bar plot is
# really a filled step plot, and a step plot is really just a path. So any backend
# that supports drawing a path will implicitly be able to support step, bar, and
# histogram plots (and any recipes that use those components).
_process_seriesrecipe(plt, series_attr)
end
end
# this method recursively applies series recipes when the seriestype is not supported
# natively by the backend
function _process_seriesrecipe(plt, plotattributes)
# replace seriestype aliases
st = Symbol(plotattributes[:seriestype])
st = plotattributes[:seriestype] = type_alias(plt, st)
# shapes shouldn't have fillrange set
if plotattributes[:seriestype] == :shape
plotattributes[:fillrange] = nothing
end
# if it's natively supported, finalize processing and pass along to the backend,
# otherwise recurse
if is_seriestype_supported(plt, st)
add_series!(plt, plotattributes)
else
# get a sub list of series for this seriestype
x, y, z = plotattributes[:x], plotattributes[:y], plotattributes[:z]
datalist = RecipesBase.apply_recipe(plotattributes, Val{st}, x, y, z)
warn_on_recipe_aliases!(plt, datalist, :series, st)
# assuming there was no error, recursively apply the series recipes
for data in datalist
if isa(data, RecipeData)
preprocess_attributes!(plt, data.plotattributes)
if data.plotattributes[:seriestype] == st
error("The seriestype didn't change in series recipe $st. This will cause a StackOverflow.")
end
_process_seriesrecipe(plt, data.plotattributes)
else
@warn("Unhandled recipe: $(data)")
break
end
end
end
nothing
end

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@ -0,0 +1,94 @@
# this is the default "type recipe"... just pass the object through
@recipe f(::Type{T}, v::T) where {T} = v
# this should catch unhandled "series recipes" and error with a nice message
@recipe f(::Type{V}, x, y, z) where {V <: Val} =
error("The backend must not support the series type $V, and there isn't a series recipe defined.")
"""
_apply_type_recipe(plotattributes, v::T, letter)
Apply the type recipe with signature `(::Type{T}, ::T)`.
"""
function _apply_type_recipe(plotattributes, v, letter)
_preprocess_axis_args!(plotattributes, letter)
rdvec = RecipesBase.apply_recipe(plotattributes, typeof(v), v)
warn_on_recipe_aliases!(plotattributes[:plot_object], plotattributes, :type, typeof(v))
_postprocess_axis_args!(plotattributes, letter)
return rdvec[1].args[1]
end
# Handle type recipes when the recipe is defined on the elements.
# This sort of recipe should return a pair of functions... one to convert to number,
# and one to format tick values.
function _apply_type_recipe(plotattributes, v::AbstractArray, letter)
plt = plotattributes[:plot_object]
_preprocess_axis_args!(plotattributes, letter)
# First we try to apply an array type recipe.
w = RecipesBase.apply_recipe(plotattributes, typeof(v), v)[1].args[1]
warn_on_recipe_aliases!(plt, plotattributes, :type, typeof(v))
# If the type did not change try it element-wise
if typeof(v) == typeof(w)
isempty(skipmissing(v)) && return Float64[]
x = first(skipmissing(v))
args = RecipesBase.apply_recipe(plotattributes, typeof(x), x)[1].args
warn_on_recipe_aliases!(plt, plotattributes, :type, typeof(x))
_postprocess_axis_args!(plotattributes, letter)
if length(args) == 2 && all(arg -> arg isa Function, args)
numfunc, formatter = args
return Formatted(map(numfunc, v), formatter)
else
return v
end
end
_postprocess_axis_args!(plotattributes, letter)
return w
end
# special handling for Surface... need to properly unwrap and re-wrap
_apply_type_recipe(plotattributes, v::Surface{<:AMat{<:DataPoint}}) = v
function _apply_type_recipe(plotattributes, v::Surface)
ret = _apply_type_recipe(plotattributes, v.surf)
if typeof(ret) <: Formatted
Formatted(Surface(ret.data), ret.formatter)
else
Surface(ret.data)
end
end
# don't do anything for datapoints or nothing
_apply_type_recipe(plotattributes, v::AbstractArray{<:DataPoint}, letter) = v
_apply_type_recipe(plotattributes, v::Nothing, letter) = v
# axis args before type recipes should still be mapped to all axes
function _preprocess_axis_args!(plotattributes)
plt = plotattributes[:plot_object]
for (k, v) in plotattributes
if is_axis_attribute(plt, k)
pop!(plotattributes, k)
for l in (:x, :y, :z)
lk = Symbol(l, k)
haskey(plotattributes, lk) || (plotattributes[lk] = v)
end
end
end
end
function _preprocess_axis_args!(plotattributes, letter)
plotattributes[:letter] = letter
_preprocess_axis_args!(plotattributes)
end
# axis args in type recipes should only be applied to the current axis
function _postprocess_axis_args!(plotattributes, letter)
plt = plotattributes[:plot_object]
pop!(plotattributes, :letter)
if letter in (:x, :y, :z)
for (k, v) in plotattributes
if is_axis_attribute(plt, k)
pop!(plotattributes, k)
lk = Symbol(letter, k)
haskey(plotattributes, lk) || (plotattributes[lk] = v)
end
end
end
end

View File

@ -0,0 +1,330 @@
"""
_process_userrecipes(plt, plotattributes, args)
Wrap input arguments in a `RecipeData' vector and recursively apply user recipes and type
recipes on the first element. Prepend the returned `RecipeData` vector. If an element with
empy `args` is returned pop it from the vector, finish up, and it to vector of `Dict`s with
processed series. When all arguments are processed return the series `Dict`.
"""
function _process_userrecipes!(plt, plotattributes, args)
still_to_process = _recipedata_vector(plt, plotattributes, args)
# for plotting recipes, swap out the args and update the parameter dictionary
# we are keeping a stack of series that still need to be processed.
# each pass through the loop, we pop one off and apply the recipe.
# the recipe will return a list a Series objects... the ones that are
# finished (no more args) get added to the kw_list, the ones that are not
# are placed on top of the stack and are then processed further.
kw_list = KW[]
while !isempty(still_to_process)
# grab the first in line to be processed and either add it to the kw_list or
# pass it through apply_recipe to generate a list of RecipeData objects
# (data + attributes) for further processing.
next_series = popfirst!(still_to_process)
# recipedata should be of type RecipeData.
# if it's not then the inputs must not have been fully processed by recipes
if !(typeof(next_series) <: RecipeData)
error("Inputs couldn't be processed... expected RecipeData but got: $next_series")
end
if isempty(next_series.args)
_finish_userrecipe!(plt, kw_list, next_series)
else
rd_list =
RecipesBase.apply_recipe(next_series.plotattributes, next_series.args...)
warn_on_recipe_aliases!(plt, rd_list, :user, next_series.args...)
prepend!(still_to_process, rd_list)
end
end
# don't allow something else to handle it
plotattributes[:smooth] = false
kw_list
end
# TODO Move this to api.jl?
function _recipedata_vector(plt, plotattributes, args)
still_to_process = RecipeData[]
# the grouping mechanism is a recipe on a GroupBy object
# we simply add the GroupBy object to the front of the args list to allow
# the recipe to be applied
if haskey(plotattributes, :group)
args = (_extract_group_attributes(plotattributes[:group], args...), args...)
end
# if we were passed a vector/matrix of seriestypes and there's more than one row,
# we want to duplicate the inputs, once for each seriestype row.
if !isempty(args)
append!(still_to_process, _expand_seriestype_array(plotattributes, args))
end
# remove subplot and axis args from plotattributes...
# they will be passed through in the kw_list
if !isempty(args)
for (k, v) in plotattributes
if is_subplot_attribute(plt, k) || is_axis_attribute(plt, k)
reset_kw!(plotattributes, k)
end
end
end
still_to_process
end
function _expand_seriestype_array(plotattributes, args)
sts = get(plotattributes, :seriestype, :path)
if typeof(sts) <: AbstractArray
reset_kw!(plotattributes, :seriestype)
rd = Vector{RecipeData}(undef, size(sts, 1))
for r in axes(sts, 1)
dc = copy(plotattributes)
dc[:seriestype] = sts[r:r, :]
rd[r] = RecipeData(dc, args)
end
rd
else
RecipeData[RecipeData(copy(plotattributes), args)]
end
end
function _finish_userrecipe!(plt, kw_list, recipedata)
# when the arg tuple is empty, that means there's nothing left to recursively
# process... finish up and add to the kw_list
kw = recipedata.plotattributes
preprocess_attributes!(plt, kw)
# if there was a grouping, filter the data here
_filter_input_data!(kw)
process_userrecipe!(plt, kw_list, kw)
end
# --------------------------------
# Fallback user recipes
# --------------------------------
# These call `_apply_type_recipe` in type_recipe.jl and finally the `SliceIt` recipe in
# series.jl.
# handle "type recipes" by converting inputs, and then either re-calling or slicing
@recipe function f(x, y, z)
wrap_surfaces!(plotattributes, x, y, z)
did_replace = false
newx = _apply_type_recipe(plotattributes, x, :x)
x === newx || (did_replace = true)
newy = _apply_type_recipe(plotattributes, y, :y)
y === newy || (did_replace = true)
newz = _apply_type_recipe(plotattributes, z, :z)
z === newz || (did_replace = true)
if did_replace
newx, newy, newz
else
SliceIt, x, y, z
end
end
@recipe function f(x, y)
wrap_surfaces!(plotattributes, x, y)
did_replace = false
newx = _apply_type_recipe(plotattributes, x, :x)
x === newx || (did_replace = true)
newy = _apply_type_recipe(plotattributes, y, :y)
y === newy || (did_replace = true)
if did_replace
newx, newy
else
SliceIt, x, y, nothing
end
end
@recipe function f(y)
wrap_surfaces!(plotattributes, y)
newy = _apply_type_recipe(plotattributes, y, :y)
if y !== newy
newy
else
SliceIt, nothing, y, nothing
end
end
# if there's more than 3 inputs, it can't be passed directly to SliceIt
# so we'll apply_type_recipe to all of them
@recipe function f(v1, v2, v3, v4, vrest...)
did_replace = false
newargs = map(
v -> begin
newv = _apply_type_recipe(plotattributes, v, :unknown)
if newv !== v
did_replace = true
end
newv
end,
(v1, v2, v3, v4, vrest...),
)
if !did_replace
error("Couldn't process recipe args: $(map(typeof, (v1, v2, v3, v4, vrest...)))")
end
newargs
end
# helper function to ensure relevant attributes are wrapped by Surface
function wrap_surfaces!(plotattributes, args...) end
wrap_surfaces!(plotattributes, x::AMat, y::AMat, z::AMat) = wrap_surfaces!(plotattributes)
wrap_surfaces!(plotattributes, x::AVec, y::AVec, z::AMat) = wrap_surfaces!(plotattributes)
function wrap_surfaces!(plotattributes, x::AVec, y::AVec, z::Surface)
wrap_surfaces!(plotattributes)
end
function wrap_surfaces!(plotattributes)
if haskey(plotattributes, :fill_z)
v = plotattributes[:fill_z]
if !isa(v, Surface)
plotattributes[:fill_z] = Surface(v)
end
end
end
# --------------------------------
# Special Cases
# --------------------------------
# --------------------------------
# 1 argument
@recipe function f(n::Integer)
if is3d(plotattributes)
SliceIt, n, n, n
else
SliceIt, n, n, nothing
end
end
# return a surface if this is a 3d plot, otherwise let it be sliced up
@recipe function f(mat::AMat)
if is3d(plotattributes)
n, m = axes(mat)
m, n, Surface(mat)
else
nothing, mat, nothing
end
end
# if a matrix is wrapped by Formatted, do similar logic, but wrap data with Surface
@recipe function f(fmt::Formatted{<:AMat})
if is3d(plotattributes)
mat = fmt.data
n, m = axes(mat)
m, n, Formatted(Surface(mat), fmt.formatter)
else
nothing, fmt, nothing
end
end
# assume this is a Volume, so construct one
@recipe function f(vol::AbstractArray{<:MaybeNumber, 3}, args...)
seriestype := :volume
SliceIt, nothing, Volume(vol, args...), nothing
end
# Dicts: each entry is a data point (x,y)=(key,value)
@recipe f(d::AbstractDict) = collect(keys(d)), collect(values(d))
# function without range... use the current range of the x-axis
@recipe function f(f::FuncOrFuncs{F}) where {F <: Function}
plt = plotattributes[:plot_object]
xmin, xmax = if haskey(plotattributes, :xlims)
plotattributes[:xlims]
else
try
get_axis_limits(plt, :x)
catch
xinv = inverse_scale_func(get(plotattributes, :xscale, :identity))
xm = PlotUtils.tryrange(f, xinv.([-5, -1, 0, 0.01]))
xm, PlotUtils.tryrange(f, filter(x -> x > xm, xinv.([5, 1, 0.99, 0, -0.01])))
end
end
f, xmin, xmax
end
# --------------------------------
# 2 arguments
# if functions come first, just swap the order (not to be confused with parametric
# functions... as there would be more than one function passed in)
@recipe function f(f::FuncOrFuncs{F}, x) where {F <: Function}
F2 = typeof(x)
@assert !(F2 <: Function || (F2 <: AbstractArray && F2.parameters[1] <: Function))
# otherwise we'd hit infinite recursion here
x, f
end
# --------------------------------
# 3 arguments
# surface-like... function
@recipe function f(x::AVec, y::AVec, zf::Function)
x, y, Surface(zf, x, y) # TODO: replace with SurfaceFunction when supported
end
# surface-like... matrix grid
@recipe function f(x::AVec, y::AVec, z::AMat)
if !is_surface(plotattributes)
plotattributes[:seriestype] = :contour
end
x, y, Surface(z)
end
# parametric functions
# special handling... xmin/xmax with parametric function(s)
@recipe function f(f::Function, xmin::Number, xmax::Number)
xscale, yscale = [get(plotattributes, sym, :identity) for sym in (:xscale, :yscale)]
_scaled_adapted_grid(f, xscale, yscale, xmin, xmax)
end
@recipe function f(fs::AbstractArray{F}, xmin::Number, xmax::Number) where {F <: Function}
xscale, yscale = [get(plotattributes, sym, :identity) for sym in (:xscale, :yscale)]
unzip(_scaled_adapted_grid.(fs, xscale, yscale, xmin, xmax))
end
@recipe f(
fx::FuncOrFuncs{F},
fy::FuncOrFuncs{G},
u::AVec,
) where {F <: Function, G <: Function} = _map_funcs(fx, u), _map_funcs(fy, u)
@recipe f(
fx::FuncOrFuncs{F},
fy::FuncOrFuncs{G},
umin::Number,
umax::Number,
n = 200,
) where {F <: Function, G <: Function} = fx, fy, range(umin, stop = umax, length = n)
function _scaled_adapted_grid(f, xscale, yscale, xmin, xmax)
(xf, xinv), (yf, yinv) = ((scale_func(s), inverse_scale_func(s)) for s in (xscale, yscale))
xs, ys = PlotUtils.adapted_grid(yf f xinv, xf.((xmin, xmax)))
xinv.(xs), yinv.(ys)
end
# special handling... 3D parametric function(s)
@recipe function f(
fx::FuncOrFuncs{F},
fy::FuncOrFuncs{G},
fz::FuncOrFuncs{H},
u::AVec,
) where {F <: Function, G <: Function, H <: Function}
_map_funcs(fx, u), _map_funcs(fy, u), _map_funcs(fz, u)
end
@recipe function f(
fx::FuncOrFuncs{F},
fy::FuncOrFuncs{G},
fz::FuncOrFuncs{H},
umin::Number,
umax::Number,
numPoints = 200,
) where {F <: Function, G <: Function, H <: Function}
fx, fy, fz, range(umin, stop = umax, length = numPoints)
end
# list of tuples
@recipe f(v::AVec{<:Tuple}) = unzip(v)
@recipe f(tup::Tuple) = [tup]

220
src/RecipePipeline/utils.jl Normal file
View File

@ -0,0 +1,220 @@
const AVec = AbstractVector
const AMat = AbstractMatrix
const KW = Dict{Symbol, Any}
const AKW = AbstractDict{Symbol, Any}
# --------------------------------
# DefaultsDict
# --------------------------------
struct DefaultsDict <: AbstractDict{Symbol, Any}
explicit::KW
defaults::KW
end
function Base.getindex(dd::DefaultsDict, k)
return haskey(dd.explicit, k) ? dd.explicit[k] : dd.defaults[k]
end
Base.haskey(dd::DefaultsDict, k) = haskey(dd.explicit, k) || haskey(dd.defaults, k)
Base.get(dd::DefaultsDict, k, default) = haskey(dd, k) ? dd[k] : default
function Base.get!(dd::DefaultsDict, k, default)
v = if haskey(dd, k)
dd[k]
else
dd.defaults[k] = default
end
return v
end
function Base.delete!(dd::DefaultsDict, k)
haskey(dd.explicit, k) && delete!(dd.explicit, k)
haskey(dd.defaults, k) && delete!(dd.defaults, k)
end
Base.length(dd::DefaultsDict) = length(union(keys(dd.explicit), keys(dd.defaults)))
function Base.iterate(dd::DefaultsDict)
exp_keys = keys(dd.explicit)
def_keys = setdiff(keys(dd.defaults), exp_keys)
key_list = collect(Iterators.flatten((exp_keys, def_keys)))
iterate(dd, (key_list, 1))
end
function Base.iterate(dd::DefaultsDict, (key_list, i))
i > length(key_list) && return nothing
k = key_list[i]
(k => dd[k], (key_list, i + 1))
end
Base.copy(dd::DefaultsDict) = DefaultsDict(copy(dd.explicit), dd.defaults)
RecipesBase.is_explicit(dd::DefaultsDict, k) = haskey(dd.explicit, k)
isdefault(dd::DefaultsDict, k) = !is_explicit(dd, k) && haskey(dd.defaults, k)
Base.setindex!(dd::DefaultsDict, v, k) = dd.explicit[k] = v
# Reset to default value and return dict
reset_kw!(dd::DefaultsDict, k) = is_explicit(dd, k) ? delete!(dd.explicit, k) : dd
# Reset to default value and return old value
pop_kw!(dd::DefaultsDict, k) = is_explicit(dd, k) ? pop!(dd.explicit, k) : dd.defaults[k]
pop_kw!(dd::DefaultsDict, k, default) =
is_explicit(dd, k) ? pop!(dd.explicit, k) : get(dd.defaults, k, default)
# Fallbacks for dicts without defaults
reset_kw!(d::AKW, k) = delete!(d, k)
pop_kw!(d::AKW, k) = pop!(d, k)
pop_kw!(d::AKW, k, default) = pop!(d, k, default)
# --------------------------------
# 3D types
# --------------------------------
abstract type AbstractSurface end
"represents a contour or surface mesh"
struct Surface{M <: AMat} <: AbstractSurface
surf::M
end
Surface(f::Function, x, y) = Surface(Float64[f(xi, yi) for yi in y, xi in x])
Base.Array(surf::Surface) = surf.surf
for f in (:length, :size, :axes)
@eval Base.$f(surf::Surface, args...) = $f(surf.surf, args...)
end
Base.copy(surf::Surface) = Surface(copy(surf.surf))
Base.eltype(surf::Surface{T}) where {T} = eltype(T)
struct Volume{T}
v::Array{T, 3}
x_extents::Tuple{T, T}
y_extents::Tuple{T, T}
z_extents::Tuple{T, T}
end
default_extents(::Type{T}) where {T} = (zero(T), one(T))
function Volume(
v::Array{T, 3},
x_extents = default_extents(T),
y_extents = default_extents(T),
z_extents = default_extents(T),
) where {T}
Volume(v, x_extents, y_extents, z_extents)
end
Base.Array(vol::Volume) = vol.v
for f in (:length, :size)
@eval Base.$f(vol::Volume, args...) = $f(vol.v, args...)
end
Base.copy(vol::Volume{T}) where {T} =
Volume{T}(copy(vol.v), vol.x_extents, vol.y_extents, vol.z_extents)
Base.eltype(vol::Volume{T}) where {T} = T
# --------------------------------
# Formatting
# --------------------------------
"Represents data values with formatting that should apply to the tick labels."
struct Formatted{T}
data::T
formatter::Function
end
# -------------------------------
# 3D seriestypes
# -------------------------------
# TODO: Move to RecipesBase?
"""
is3d(::Type{Val{:myseriestype}})
Returns `true` if `myseriestype` represents a 3D series, `false` otherwise.
"""
is3d(st) = false
for st in (
:contour,
:contourf,
:contour3d,
:heatmap,
:image,
:path3d,
:scatter3d,
:surface,
:volume,
:wireframe,
)
@eval is3d(::Type{Val{Symbol($(string(st)))}}) = true
end
is3d(st::Symbol) = is3d(Val{st})
is3d(plt, stv::AbstractArray) = all(st -> is3d(plt, st), stv)
is3d(plotattributes::AbstractDict) = is3d(get(plotattributes, :seriestype, :path))
"""
is_surface(::Type{Val{:myseriestype}})
Returns `true` if `myseriestype` represents a surface series, `false` otherwise.
"""
is_surface(st) = false
for st in (:contour, :contourf, :contour3d, :image, :heatmap, :surface, :wireframe)
@eval is_surface(::Type{Val{Symbol($(string(st)))}}) = true
end
is_surface(st::Symbol) = is_surface(Val{st})
is_surface(plt, stv::AbstractArray) = all(st -> is_surface(plt, st), stv)
is_surface(plotattributes::AbstractDict) =
is_surface(get(plotattributes, :seriestype, :path))
"""
needs_3d_axes(::Type{Val{:myseriestype}})
Returns `true` if `myseriestype` needs 3d axes, `false` otherwise.
"""
needs_3d_axes(st) = false
for st in (
:contour3d,
:path3d,
:scatter3d,
:surface,
:volume,
:wireframe,
)
@eval needs_3d_axes(::Type{Val{Symbol($(string(st)))}}) = true
end
needs_3d_axes(st::Symbol) = needs_3d_axes(Val{st})
needs_3d_axes(plt, stv::AbstractArray) = all(st -> needs_3d_axes(plt, st), stv)
needs_3d_axes(plotattributes::AbstractDict) =
needs_3d_axes(get(plotattributes, :seriestype, :path))
# --------------------------------
# Scales
# --------------------------------
const SCALE_FUNCTIONS = Dict{Symbol, Function}(:log10 => log10, :log2 => log2, :ln => log)
const INVERSE_SCALE_FUNCTIONS =
Dict{Symbol, Function}(:log10 => exp10, :log2 => exp2, :ln => exp)
scale_func(scale::Symbol) = x -> get(SCALE_FUNCTIONS, scale, identity)(Float64(x))
inverse_scale_func(scale::Symbol) =
x -> get(INVERSE_SCALE_FUNCTIONS, scale, identity)(Float64(x))
# --------------------------------
# Unzip
# --------------------------------
for i in 2:4
@eval begin
unzip(v::AVec{<:Tuple{Vararg{T, $i} where T}}) =
$(Expr(:tuple, (:([t[$j] for t in v]) for j in 1:i)...))
end
end
# --------------------------------
# Map functions on vectors
# --------------------------------
_map_funcs(f::Function, u::AVec) = map(f, u)
_map_funcs(fs::AVec{F}, u::AVec) where {F <: Function} = [map(f, u) for f in fs]

View File

@ -86,12 +86,9 @@ const _surface_like = [:contour, :contourf, :contour3d, :heatmap, :surface, :wir
like_histogram(seriestype::Symbol) = seriestype in _histogram_like
like_line(seriestype::Symbol) = seriestype in _line_like
like_surface(seriestype::Symbol) = seriestype in _surface_like
like_surface(seriestype::Symbol) = is_surface(seriestype)
is3d(seriestype::Symbol) = seriestype in _3dTypes
is3d(series::Series) = is3d(series.plotattributes)
is3d(plotattributes::AKW) = trueOrAllTrue(is3d, Symbol(plotattributes[:seriestype]))
is3d(sp::Subplot) = string(sp.attr[:projection]) == "3d"
ispolar(sp::Subplot) = string(sp.attr[:projection]) == "polar"
ispolar(series::Series) = ispolar(series.plotattributes[:subplot])
@ -682,7 +679,7 @@ end
function default(; kw...)
kw = KW(kw)
preprocessArgs!(kw)
preprocess_attributes!(kw)
for (k,v) in kw
default(k, v)
end
@ -935,7 +932,7 @@ function _add_markershape(plotattributes::AKW)
end
"Handle all preprocessing of args... break out colors/sizes/etc and replace aliases."
function preprocessArgs!(plotattributes::AKW)
function preprocess_attributes!(plotattributes::AKW)
replaceAliases!(plotattributes, _keyAliases)
# handle axis args common to all axis
@ -1112,75 +1109,13 @@ function preprocessArgs!(plotattributes::AKW)
return
end
# -----------------------------------------------------------------------------
"A special type that will break up incoming data into groups, and allow for easier creation of grouped plots"
mutable struct GroupBy
groupLabels::Vector # length == numGroups
groupIds::Vector{Vector{Int}} # list of indices for each group
end
# this is when given a vector-type of values to group by
function extractGroupArgs(v::AVec, args...; legendEntry = string)
groupLabels = sort(collect(unique(v)))
n = length(groupLabels)
if n > 100
@warn("You created n=$n groups... Is that intended?")
end
groupIds = Vector{Int}[filter(i -> v[i] == glab, eachindex(v)) for glab in groupLabels]
GroupBy(map(legendEntry, groupLabels), groupIds)
end
legendEntryFromTuple(ns::Tuple) = join(ns, ' ')
# this is when given a tuple of vectors of values to group by
function extractGroupArgs(vs::Tuple, args...)
isempty(vs) && return GroupBy([""], [axes(args[1],1)])
v = map(tuple, vs...)
extractGroupArgs(v, args...; legendEntry = legendEntryFromTuple)
end
# allow passing NamedTuples for a named legend entry
legendEntryFromTuple(ns::NamedTuple) =
join(["$k = $v" for (k, v) in pairs(ns)], ", ")
function extractGroupArgs(vs::NamedTuple, args...)
isempty(vs) && return GroupBy([""], [axes(args[1],1)])
v = map(NamedTuple{keys(vs)}tuple, values(vs)...)
extractGroupArgs(v, args...; legendEntry = legendEntryFromTuple)
end
# expecting a mapping of "group label" to "group indices"
function extractGroupArgs(idxmap::Dict{T,V}, args...) where {T, V<:AVec{Int}}
groupLabels = sortedkeys(idxmap)
groupIds = Vector{Int}[collect(idxmap[k]) for k in groupLabels]
GroupBy(groupLabels, groupIds)
end
filter_data(v::AVec, idxfilter::AVec{Int}) = v[idxfilter]
filter_data(v, idxfilter) = v
function filter_data!(plotattributes::AKW, idxfilter)
for s in (:x, :y, :z)
plotattributes[s] = filter_data(get(plotattributes, s, nothing), idxfilter)
end
end
function _filter_input_data!(plotattributes::AKW)
idxfilter = pop!(plotattributes, :idxfilter, nothing)
if idxfilter !== nothing
filter_data!(plotattributes, idxfilter)
end
end
# -----------------------------------------------------------------------------
const _already_warned = Dict{Symbol,Set{Symbol}}()
const _to_warn = Set{Symbol}()
function warnOnUnsupported_args(pkg::AbstractBackend, plotattributes)
function warn_on_unsupported_args(pkg::AbstractBackend, plotattributes)
empty!(_to_warn)
bend = backend_name(pkg)
already_warned = get!(_already_warned, bend, Set{Symbol}())
@ -1204,7 +1139,7 @@ end
# _markershape_supported(pkg::AbstractBackend, shape::Shape) = Shape in supported_markers(pkg)
# _markershape_supported(pkg::AbstractBackend, shapes::AVec) = all([_markershape_supported(pkg, shape) for shape in shapes])
function warnOnUnsupported(pkg::AbstractBackend, plotattributes)
function warn_on_unsupported(pkg::AbstractBackend, plotattributes)
if !is_seriestype_supported(pkg, plotattributes[:seriestype])
@warn("seriestype $(plotattributes[:seriestype]) is unsupported with $pkg. Choose from: $(supported_seriestypes(pkg))")
end
@ -1216,7 +1151,7 @@ function warnOnUnsupported(pkg::AbstractBackend, plotattributes)
end
end
function warnOnUnsupported_scales(pkg::AbstractBackend, plotattributes::AKW)
function warn_on_unsupported_scales(pkg::AbstractBackend, plotattributes::AKW)
for k in (:xscale, :yscale, :zscale, :scale)
if haskey(plotattributes, k)
v = plotattributes[k]

View File

@ -17,7 +17,7 @@ function Axis(sp::Subplot, letter::Symbol, args...; kw...)
:show => true, # show or hide the axis? (useful for linked subplots)
)
attr = Attr(explicit, _axis_defaults_byletter[letter])
attr = DefaultsDict(explicit, _axis_defaults_byletter[letter])
# update the defaults
attr!(Axis([sp], attr), args...; kw...)
@ -85,7 +85,7 @@ function attr!(axis::Axis, args...; kw...)
end
# then preprocess keyword arguments
preprocessArgs!(KW(kw))
preprocess_attributes!(KW(kw))
# then override for any keywords... only those keywords that already exists in plotattributes
for (k,v) in kw
@ -117,33 +117,11 @@ Base.setindex!(axis::Axis, v, ks::Symbol...) = setindex!(axis.plotattributes, v,
Base.haskey(axis::Axis, k::Symbol) = haskey(axis.plotattributes, k)
ignorenan_extrema(axis::Axis) = (ex = axis[:extrema]; (ex.emin, ex.emax))
const _scale_funcs = Dict{Symbol,Function}(
:log10 => log10,
:log2 => log2,
:ln => log,
)
const _inv_scale_funcs = Dict{Symbol,Function}(
:log10 => exp10,
:log2 => exp2,
:ln => exp,
)
# const _label_func = Dict{Symbol,Function}(
# :log10 => x -> "10^$x",
# :log2 => x -> "2^$x",
# :ln => x -> "e^$x",
# )
const _label_func = Dict{Symbol,Function}(
:log10 => x -> "10^$x",
:log2 => x -> "2^$x",
:ln => x -> "e^$x",
)
scalefunc(scale::Symbol) = x -> get(_scale_funcs, scale, identity)(Float64(x))
invscalefunc(scale::Symbol) = x -> get(_inv_scale_funcs, scale, identity)(Float64(x))
labelfunc(scale::Symbol, backend::AbstractBackend) = get(_label_func, scale, string)
function optimal_ticks_and_labels(sp::Subplot, axis::Axis, ticks = nothing)
@ -151,7 +129,7 @@ function optimal_ticks_and_labels(sp::Subplot, axis::Axis, ticks = nothing)
# scale the limits
scale = axis[:scale]
sf = scalefunc(scale)
sf = scale_func(scale)
# If the axis input was a Date or DateTime use a special logic to find
# "round" Date(Time)s as ticks
@ -196,11 +174,11 @@ function optimal_ticks_and_labels(sp::Subplot, axis::Axis, ticks = nothing)
# chosen ticks is not too much bigger than amin - amax:
strict_span = false,
)
axis[:lims] = map(invscalefunc(scale), (viewmin, viewmax))
axis[:lims] = map(inverse_scale_func(scale), (viewmin, viewmax))
else
scaled_ticks = map(sf, (filter(t -> amin <= t <= amax, ticks)))
end
unscaled_ticks = map(invscalefunc(scale), scaled_ticks)
unscaled_ticks = map(inverse_scale_func(scale), scaled_ticks)
labels = if any(isfinite, unscaled_ticks)
formatter = axis[:formatter]
@ -400,7 +378,7 @@ function expand_extrema!(sp::Subplot, plotattributes::AKW)
if fr === nothing && plotattributes[:seriestype] == :bar
fr = 0.0
end
if fr !== nothing && !all3D(plotattributes)
if fr !== nothing && !is3d(plotattributes)
axis = sp.attr[vert ? :yaxis : :xaxis]
if typeof(fr) <: Tuple
for fri in fr
@ -445,7 +423,7 @@ end
# push the limits out slightly
function widen(lmin, lmax, scale = :identity)
f, invf = scalefunc(scale), invscalefunc(scale)
f, invf = scale_func(scale), inverse_scale_func(scale)
span = f(lmax) - f(lmin)
# eps = NaNMath.max(1e-16, min(1e-2span, 1e-10))
eps = NaNMath.max(1e-16, 0.03span)
@ -648,8 +626,8 @@ function axis_drawing_info(sp::Subplot)
sp[:framestyle] in (:semi, :box) && push!(xborder_segs, (xmin, y2), (xmax, y2)) # top spine
end
if !(xaxis[:ticks] in (:none, nothing, false))
f = scalefunc(yaxis[:scale])
invf = invscalefunc(yaxis[:scale])
f = scale_func(yaxis[:scale])
invf = inverse_scale_func(yaxis[:scale])
tick_start, tick_stop = if sp[:framestyle] == :origin
t = invf(f(0) + 0.012 * (f(ymax) - f(ymin)))
(-t, t)
@ -702,8 +680,8 @@ function axis_drawing_info(sp::Subplot)
sp[:framestyle] in (:semi, :box) && push!(yborder_segs, (x2, ymin), (x2, ymax)) # right spine
end
if !(yaxis[:ticks] in (:none, nothing, false))
f = scalefunc(xaxis[:scale])
invf = invscalefunc(xaxis[:scale])
f = scale_func(xaxis[:scale])
invf = inverse_scale_func(xaxis[:scale])
tick_start, tick_stop = if sp[:framestyle] == :origin
t = invf(f(0) + 0.012 * (f(xmax) - f(xmin)))
(-t, t)
@ -794,8 +772,8 @@ function axis_drawing_info_3d(sp::Subplot)
sp[:framestyle] in (:semi, :box) && push!(xborder_segs, (xmin, y2, z2), (xmax, y2, z2)) # top spine
end
if !(xaxis[:ticks] in (:none, nothing, false))
f = scalefunc(yaxis[:scale])
invf = invscalefunc(yaxis[:scale])
f = scale_func(yaxis[:scale])
invf = inverse_scale_func(yaxis[:scale])
tick_start, tick_stop = if sp[:framestyle] == :origin
t = invf(f(0) + 0.012 * (f(ymax) - f(ymin)))
(-t, t)
@ -869,8 +847,8 @@ function axis_drawing_info_3d(sp::Subplot)
sp[:framestyle] in (:semi, :box) && push!(yborder_segs, (x2, ymin, z2), (x2, ymax, z2)) # right spine
end
if !(yaxis[:ticks] in (:none, nothing, false))
f = scalefunc(xaxis[:scale])
invf = invscalefunc(xaxis[:scale])
f = scale_func(xaxis[:scale])
invf = inverse_scale_func(xaxis[:scale])
tick_start, tick_stop = if sp[:framestyle] == :origin
t = invf(f(0) + 0.012 * (f(xmax) - f(xmin)))
(-t, t)
@ -944,8 +922,8 @@ function axis_drawing_info_3d(sp::Subplot)
sp[:framestyle] in (:semi, :box) && push!(zborder_segs, (x2, y2, zmin), (x2, y2, zmax))
end
if !(zaxis[:ticks] in (:none, nothing, false))
f = scalefunc(xaxis[:scale])
invf = invscalefunc(xaxis[:scale])
f = scale_func(xaxis[:scale])
invf = inverse_scale_func(xaxis[:scale])
tick_start, tick_stop = if sp[:framestyle] == :origin
t = invf(f(0) + 0.012 * (f(ymax) - f(ymin)))
(-t, t)

View File

@ -83,7 +83,7 @@ if length(HDF5PLOT_MAP_TELEM2STR) < 1
"ARRAY" => Array, #Dict won't allow Array to be key in HDF5PLOT_MAP_TELEM2STR
#Sub-structure types:
"ATTR" => Attr,
"DEFAULTSDICT" => DefaultsDict,
"FONT" => Font,
"BOUNDINGBOX" => BoundingBox,
"GRIDLAYOUT" => GridLayout,
@ -395,12 +395,12 @@ function _hdf5plot_write(grp, plotattributes::KW)
end
return
end
function _hdf5plot_write(grp, plotattributes::Attr)
function _hdf5plot_write(grp, plotattributes::DefaultsDict)
for (k, v) in plotattributes
kstr = string(k)
_hdf5plot_gwrite(grp, kstr, v)
end
_hdf5plot_writetype(grp, Attr)
_hdf5plot_writetype(grp, DefaultsDict)
end
@ -558,14 +558,14 @@ parent = RootLayout()
return GridLayout(parent, minpad, bbox, grid, widths, heights, attr)
end
function _hdf5plot_read(grp, T::Type{Attr})
attr = Attr(KW(), _plot_defaults)
function _hdf5plot_read(grp, T::Type{DefaultsDict})
attr = DefaultsDict(KW(), _plot_defaults)
v = _hdf5plot_read(grp, attr)
return attr
end
function _hdf5plot_read(grp, k::String, T::Type{Axis})
grp = HDF5.g_open(grp, k)
plotattributes = Attr(KW(), _plot_defaults)
plotattributes = DefaultsDict(KW(), _plot_defaults)
_hdf5plot_read(grp, plotattributes)
return Axis([], plotattributes)
end
@ -610,7 +610,7 @@ function _hdf5plot_readattr(grp, plotattributes::AbstractDict)
return
end
_hdf5plot_read(grp, plotattributes::KW) = _hdf5plot_readattr(grp, plotattributes)
_hdf5plot_read(grp, plotattributes::Attr) = _hdf5plot_readattr(grp, plotattributes)
_hdf5plot_read(grp, plotattributes::DefaultsDict) = _hdf5plot_readattr(grp, plotattributes)
# Read main plot structures:
# ----------------------------------------------------------------
@ -623,7 +623,7 @@ function _hdf5plot_read(sp::Subplot, subpath::String, f)
for i in 1:nseries
grp = HDF5.g_open(f, _hdf5_plotelempath("$subpath/series_list/series$i"))
seriesinfo = Attr(KW(), _plot_defaults)
seriesinfo = DefaultsDict(KW(), _plot_defaults)
_hdf5plot_read(grp, seriesinfo)
plot!(sp, seriesinfo[:x], seriesinfo[:y]) #Add data & create data structures
_hdf5_merge!(sp.series_list[end].plotattributes, seriesinfo)
@ -631,7 +631,7 @@ function _hdf5plot_read(sp::Subplot, subpath::String, f)
#Perform after adding series... otherwise values get overwritten:
grp = HDF5.g_open(f, _hdf5_plotelempath("$subpath/attr"))
attr = Attr(KW(), _plot_defaults)
attr = DefaultsDict(KW(), _plot_defaults)
_hdf5plot_read(grp, attr)
_hdf5_merge!(sp.attr, attr)

View File

@ -652,23 +652,6 @@ end
# -----------------------------------------------------------------------
abstract type AbstractSurface end
"represents a contour or surface mesh"
struct Surface{M<:AMat} <: AbstractSurface
surf::M
end
Surface(f::Function, x, y) = Surface(Float64[f(xi,yi) for yi in y, xi in x])
Base.Array(surf::Surface) = surf.surf
for f in (:length, :size, :axes)
@eval Base.$f(surf::Surface, args...) = $f(surf.surf, args...)
end
Base.copy(surf::Surface) = Surface(copy(surf.surf))
Base.eltype(surf::Surface{T}) where {T} = eltype(T)
function expand_extrema!(a::Axis, surf::Surface)
ex = a[:extrema]
for vi in surf.surf
@ -688,28 +671,7 @@ end
# # I don't want to clash with ValidatedNumerics, but this would be nice:
# ..(a::T, b::T) = (a,b)
struct Volume{T}
v::Array{T,3}
x_extents::Tuple{T,T}
y_extents::Tuple{T,T}
z_extents::Tuple{T,T}
end
default_extents(::Type{T}) where {T} = (zero(T), one(T))
function Volume(v::Array{T,3},
x_extents = default_extents(T),
y_extents = default_extents(T),
z_extents = default_extents(T)) where T
Volume(v, x_extents, y_extents, z_extents)
end
Base.Array(vol::Volume) = vol.v
for f in (:length, :size)
@eval Base.$f(vol::Volume, args...) = $f(vol.v, args...)
end
Base.copy(vol::Volume{T}) where {T} = Volume{T}(copy(vol.v), vol.x_extents, vol.y_extents, vol.z_extents)
Base.eltype(vol::Volume{T}) where {T} = T
# -----------------------------------------------------------------------
@ -773,14 +735,6 @@ function add_arrows(func::Function, x::AVec, y::AVec)
end
end
# -----------------------------------------------------------------------
"Represents data values with formatting that should apply to the tick labels."
struct Formatted{T}
data::T
formatter::Function
end
# -----------------------------------------------------------------------
"create a BezierCurve for plotting"
mutable struct BezierCurve{T <: GeometryTypes.Point}

View File

@ -1,127 +1,74 @@
# Error for aliases used in recipes
function warn_on_recipe_aliases!(plotattributes, recipe_type, args...)
# RecipePipeline API
## Warnings
function RecipePipeline.warn_on_recipe_aliases!(
plt::Plot,
plotattributes,
recipe_type,
args...,
)
for k in keys(plotattributes)
if !is_default_attribute(k)
dk = get(_keyAliases, k, k)
if k !== dk
@warn "Attribute alias `$k` detected in the $recipe_type recipe defined for the signature $(signature_string(Val{recipe_type}, args...)). To ensure expected behavior it is recommended to use the default attribute `$dk`."
@warn "Attribute alias `$k` detected in the $recipe_type recipe defined for the signature $(_signature_string(Val{recipe_type}, args...)). To ensure expected behavior it is recommended to use the default attribute `$dk`."
end
plotattributes[dk] = pop_kw!(plotattributes, k)
end
end
end
function warn_on_recipe_aliases!(v::AbstractVector, recipe_type, args...)
foreach(x -> warn_on_recipe_aliases!(x, recipe_type, args...), v)
function RecipePipeline.warn_on_recipe_aliases!(
plt::Plot,
v::AbstractVector,
recipe_type,
args...,
)
foreach(x -> RecipePipeline.warn_on_recipe_aliases!(plt, x, recipe_type, args...), v)
end
function warn_on_recipe_aliases!(rd::RecipeData, recipe_type, args...)
warn_on_recipe_aliases!(rd.plotattributes, recipe_type, args...)
function RecipePipeline.warn_on_recipe_aliases!(
plt::Plot,
rd::RecipeData,
recipe_type,
args...,
)
RecipePipeline.warn_on_recipe_aliases!(plt, rd.plotattributes, recipe_type, args...)
end
function signature_string(::Type{Val{:user}}, args...)
function _signature_string(::Type{Val{:user}}, args...)
return string("(::", join(string.(typeof.(args)), ", ::"), ")")
end
signature_string(::Type{Val{:type}}, T) = "(::Type{$T}, ::$T)"
signature_string(::Type{Val{:plot}}, st) = "(::Type{Val{:$st}}, ::AbstractPlot)"
signature_string(::Type{Val{:series}}, st) = "(::Type{Val{:$st}}, x, y, z)"
_signature_string(::Type{Val{:type}}, T) = "(::Type{$T}, ::$T)"
_signature_string(::Type{Val{:plot}}, st) = "(::Type{Val{:$st}}, ::AbstractPlot)"
_signature_string(::Type{Val{:series}}, st) = "(::Type{Val{:$st}}, x, y, z)"
# ------------------------------------------------------------------
# preprocessing
function series_idx(kw_list::AVec{KW}, kw::AKW)
Int(kw[:series_plotindex]) - Int(kw_list[1][:series_plotindex]) + 1
## Grouping
RecipePipeline.splittable_attribute(plt::Plot, key, val::SeriesAnnotations, len) =
RecipePipeline.splittable_attribute(plt, key, val.strs, len)
function RecipePipeline.split_attribute(plt::Plot, key, val::SeriesAnnotations, indices)
split_strs = _RecipePipeline.split_attribute(key, val.strs, indices)
return SeriesAnnotations(split_strs, val.font, val.baseshape, val.scalefactor)
end
function _expand_seriestype_array(plotattributes::AKW, args)
sts = get(plotattributes, :seriestype, :path)
if typeof(sts) <: AbstractArray
reset_kw!(plotattributes, :seriestype)
rd = Vector{RecipeData}(undef, size(sts, 1))
for r in axes(sts, 1)
dc = copy(plotattributes)
dc[:seriestype] = sts[r:r,:]
rd[r] = RecipeData(dc, args)
end
rd
else
RecipeData[RecipeData(copy(plotattributes), args)]
end
end
function _preprocess_args(plotattributes::AKW, args, still_to_process::Vector{RecipeData})
# the grouping mechanism is a recipe on a GroupBy object
# we simply add the GroupBy object to the front of the args list to allow
# the recipe to be applied
if haskey(plotattributes, :group)
args = (extractGroupArgs(plotattributes[:group], args...), args...)
end
## Preprocessing attributes
# if we were passed a vector/matrix of seriestypes and there's more than one row,
# we want to duplicate the inputs, once for each seriestype row.
if !isempty(args)
append!(still_to_process, _expand_seriestype_array(plotattributes, args))
end
RecipePipeline.preprocess_attributes!(plt::Plot, plotattributes) =
preprocess_attributes!(plotattributes) # in src/args.jl
# remove subplot and axis args from plotattributes... they will be passed through in the kw_list
if !isempty(args)
for (k,v) in plotattributes
if k in _all_subplot_args || k in _all_axis_args
reset_kw!(plotattributes, k)
end
end
end
RecipePipeline.is_axis_attribute(plt::Plot, attr) = is_axis_attr_noletter(attr) # in src/args.jl
args
end
# ------------------------------------------------------------------
# user recipes
RecipePipeline.is_subplot_attribute(plt::Plot, attr) = is_subplot_attr(attr) # in src/args.jl
function _process_userrecipes(plt::Plot, plotattributes::AKW, args)
still_to_process = RecipeData[]
args = _preprocess_args(plotattributes, args, still_to_process)
## User recipes
# for plotting recipes, swap out the args and update the parameter dictionary
# we are keeping a stack of series that still need to be processed.
# each pass through the loop, we pop one off and apply the recipe.
# the recipe will return a list a Series objects... the ones that are
# finished (no more args) get added to the kw_list, the ones that are not
# are placed on top of the stack and are then processed further.
kw_list = KW[]
while !isempty(still_to_process)
# grab the first in line to be processed and either add it to the kw_list or
# pass it through apply_recipe to generate a list of RecipeData objects (data + attributes)
# for further processing.
next_series = popfirst!(still_to_process)
# recipedata should be of type RecipeData. if it's not then the inputs must not have been fully processed by recipes
if !(typeof(next_series) <: RecipeData)
error("Inputs couldn't be processed... expected RecipeData but got: $next_series")
end
if isempty(next_series.args)
_process_userrecipe(plt, kw_list, next_series)
else
rd_list = RecipesBase.apply_recipe(
next_series.plotattributes,
next_series.args...
)
warn_on_recipe_aliases!(rd_list, :user, next_series.args...)
prepend!(still_to_process,rd_list)
end
end
# don't allow something else to handle it
plotattributes[:smooth] = false
kw_list
end
function _process_userrecipe(plt::Plot, kw_list::Vector{KW}, recipedata::RecipeData)
# when the arg tuple is empty, that means there's nothing left to recursively
# process... finish up and add to the kw_list
kw = recipedata.plotattributes
preprocessArgs!(kw)
function RecipePipeline.process_userrecipe!(plt::Plot, kw_list, kw)
_preprocess_userrecipe(kw)
warnOnUnsupported_scales(plt.backend, kw)
warn_on_unsupported_scales(plt.backend, kw)
# add the plot index
plt.n += 1
kw[:series_plotindex] = plt.n
@ -135,18 +82,17 @@ end
function _preprocess_userrecipe(kw::AKW)
_add_markershape(kw)
# if there was a grouping, filter the data here
_filter_input_data!(kw)
# map marker_z if it's a Function
if isa(get(kw, :marker_z, nothing), Function)
# TODO: should this take y and/or z as arguments?
kw[:marker_z] = isa(kw[:z], Nothing) ? map(kw[:marker_z], kw[:x], kw[:y]) : map(kw[:marker_z], kw[:x], kw[:y], kw[:z])
kw[:marker_z] = isa(kw[:z], Nothing) ? map(kw[:marker_z], kw[:x], kw[:y]) :
map(kw[:marker_z], kw[:x], kw[:y], kw[:z])
end
# map line_z if it's a Function
if isa(get(kw, :line_z, nothing), Function)
kw[:line_z] = isa(kw[:z], Nothing) ? map(kw[:line_z], kw[:x], kw[:y]) : map(kw[:line_z], kw[:x], kw[:y], kw[:z])
kw[:line_z] = isa(kw[:z], Nothing) ? map(kw[:line_z], kw[:x], kw[:y]) :
map(kw[:line_z], kw[:x], kw[:y], kw[:z])
end
# convert a ribbon into a fillrange
@ -178,59 +124,43 @@ function _add_smooth_kw(kw_list::Vector{KW}, kw::AKW)
β, α = convert(Matrix{Float64}, [x ones(length(x))]) \ convert(Vector{Float64}, y)
sx = [ignorenan_minimum(x), ignorenan_maximum(x)]
sy = β .* sx .+ α
push!(kw_list, merge(copy(kw), KW(
:seriestype => :path,
:x => sx,
:y => sy,
:fillrange => nothing,
:label => "",
:primary => false,
)))
push!(
kw_list,
merge(
copy(kw),
KW(
:seriestype => :path,
:x => sx,
:y => sy,
:fillrange => nothing,
:label => "",
:primary => false,
),
),
)
end
end
# ------------------------------------------------------------------
# plot recipes
# Grab the first in line to be processed and pass it through apply_recipe
# to generate a list of RecipeData objects (data + attributes).
# If we applied a "plot recipe" without error, then add the returned datalist's KWs,
# otherwise we just add the original KW.
function _process_plotrecipe(plt::Plot, kw::AKW, kw_list::Vector{KW}, still_to_process::Vector{KW})
if !isa(get(kw, :seriestype, nothing), Symbol)
# seriestype was never set, or it's not a Symbol, so it can't be a plot recipe
push!(kw_list, kw)
return
end
try
st = kw[:seriestype]
st = kw[:seriestype] = get(_typeAliases, st, st)
datalist = RecipesBase.apply_recipe(kw, Val{st}, plt)
warn_on_recipe_aliases!(datalist, :plot, st)
for data in datalist
preprocessArgs!(data.plotattributes)
if data.plotattributes[:seriestype] == st
error("Plot recipe $st returned the same seriestype: $(data.plotattributes)")
end
push!(still_to_process, data.plotattributes)
end
catch err
if isa(err, MethodError)
push!(kw_list, kw)
else
rethrow()
end
end
return
RecipePipeline.get_axis_limits(plt::Plot, f, letter) = axis_limits(plt[1], :x)
## Plot recipes
RecipePipeline.type_alias(plt::Plot) = get(_typeAliases, st, st)
## Plot setup
function RecipePipeline.plot_setup!(plt::Plot, plotattributes, kw_list)
_plot_setup(plt, plotattributes, kw_list)
_subplot_setup(plt, plotattributes, kw_list)
end
# ------------------------------------------------------------------
# setup plot and subplot
# TODO: Should some of this logic be moved to RecipePipeline?
function _plot_setup(plt::Plot, plotattributes::AKW, kw_list::Vector{KW})
# merge in anything meant for the Plot
for kw in kw_list, (k,v) in kw
for kw in kw_list, (k, v) in kw
haskey(_plot_defaults, k) && (plotattributes[k] = pop!(kw, k))
end
@ -241,7 +171,7 @@ function _plot_setup(plt::Plot, plotattributes::AKW, kw_list::Vector{KW})
# create the layout and subplots from the inputs
plt.layout, plt.subplots, plt.spmap = build_layout(plt.attr)
for (idx,sp) in enumerate(plt.subplots)
for (idx, sp) in enumerate(plt.subplots)
sp.plt = plt
sp.attr[:subplot_index] = idx
end
@ -266,7 +196,7 @@ function _plot_setup(plt::Plot, plotattributes::AKW, kw_list::Vector{KW})
else
parent = plt.layout
end
sp = Subplot(backend(), parent=parent)
sp = Subplot(backend(), parent = parent)
sp.plt = plt
push!(plt.subplots, sp)
push!(plt.inset_subplots, sp)
@ -282,28 +212,34 @@ function _subplot_setup(plt::Plot, plotattributes::AKW, kw_list::Vector{KW})
# Subplot/Axis attributes set by a user/series recipe apply only to the
# Subplot object which they belong to.
# TODO: allow matrices to still apply to all subplots
sp_attrs = Dict{Subplot,Any}()
sp_attrs = Dict{Subplot, Any}()
for kw in kw_list
# get the Subplot object to which the series belongs.
sps = get(kw, :subplot, :auto)
sp = get_subplot(plt, _cycle(sps == :auto ? plt.subplots : plt.subplots[sps], series_idx(kw_list,kw)))
sp = get_subplot(
plt,
_cycle(
sps == :auto ? plt.subplots : plt.subplots[sps],
series_idx(kw_list, kw),
),
)
kw[:subplot] = sp
# extract subplot/axis attributes from kw and add to sp_attr
attr = KW()
for (k,v) in collect(kw)
for (k, v) in collect(kw)
if is_subplot_attr(k) || is_axis_attr(k)
attr[k] = pop!(kw, k)
end
if is_axis_attr_noletter(k)
v = pop!(kw, k)
for letter in (:x,:y,:z)
attr[Symbol(letter,k)] = v
for letter in (:x, :y, :z)
attr[Symbol(letter, k)] = v
end
end
for k in (:scale,), letter in (:x,:y,:z)
for k in (:scale,), letter in (:x, :y, :z)
# Series recipes may need access to this information
lk = Symbol(letter,k)
lk = Symbol(letter, k)
if haskey(attr, lk)
kw[lk] = attr[lk]
end
@ -313,7 +249,7 @@ function _subplot_setup(plt::Plot, plotattributes::AKW, kw_list::Vector{KW})
end
# override subplot/axis args. `sp_attrs` take precendence
for (idx,sp) in enumerate(plt.subplots)
for (idx, sp) in enumerate(plt.subplots)
attr = if !haskey(plotattributes, :subplot) || plotattributes[:subplot] == idx
merge(plotattributes, get(sp_attrs, sp, KW()))
else
@ -326,9 +262,34 @@ function _subplot_setup(plt::Plot, plotattributes::AKW, kw_list::Vector{KW})
link_axes!(plt.layout, plt[:link])
end
function series_idx(kw_list::AVec{KW}, kw::AKW)
Int(kw[:series_plotindex]) - Int(kw_list[1][:series_plotindex]) + 1
end
## Series recipes
function RecipePipeline.slice_series_attributes!(plt::Plot, kw_list, kw)
sp::Subplot = kw[:subplot]
# in series attributes given as vector with one element per series,
# select the value for current series
_slice_series_args!(kw, plt, sp, series_idx(kw_list, kw))
end
RecipePipeline.series_defaults(plt::Plot) = _series_defaults # in args.jl
RecipePipeline.is_seriestype_supported(plt::Plot, st) = is_seriestype_supported(st)
function RecipePipeline.add_series!(plt::Plot, plotattributes)
sp = _prepare_subplot(plt, plotattributes)
_expand_subplot_extrema(sp, plotattributes, plotattributes[:seriestype])
_update_series_attributes!(plotattributes, plt, sp)
_add_the_series(plt, sp, plotattributes)
end
# getting ready to add the series... last update to subplot from anything
# that might have been added during series recipes
function _prepare_subplot(plt::Plot{T}, plotattributes::AKW) where T
function _prepare_subplot(plt::Plot{T}, plotattributes::AKW) where {T}
st::Symbol = plotattributes[:seriestype]
sp::Subplot{T} = plotattributes[:subplot]
sp_idx = get_subplot_index(plt, sp)
@ -337,7 +298,7 @@ function _prepare_subplot(plt::Plot{T}, plotattributes::AKW) where T
st = _override_seriestype_check(plotattributes, st)
# change to a 3d projection for this subplot?
if is3d(st)
if needs_3d_axes(st)
sp.attr[:projection] = "3d"
end
@ -349,14 +310,12 @@ function _prepare_subplot(plt::Plot{T}, plotattributes::AKW) where T
sp
end
# ------------------------------------------------------------------
# series types
function _override_seriestype_check(plotattributes::AKW, st::Symbol)
# do we want to override the series type?
if !is3d(st) && !(st in (:contour,:contour3d))
if !is3d(st) && !(st in (:contour, :contour3d))
z = plotattributes[:z]
if !isa(z, Nothing) && (size(plotattributes[:x]) == size(plotattributes[:y]) == size(z))
if !isa(z, Nothing) &&
(size(plotattributes[:x]) == size(plotattributes[:y]) == size(z))
st = (st == :scatter ? :scatter3d : :path3d)
plotattributes[:seriestype] = st
end
@ -364,27 +323,11 @@ function _override_seriestype_check(plotattributes::AKW, st::Symbol)
st
end
function _prepare_annotations(sp::Subplot, plotattributes::AKW)
# strip out series annotations (those which are based on series x/y coords)
# and add them to the subplot attr
sp_anns = annotations(sp[:annotations])
# series_anns = annotations(pop!(plotattributes, :series_annotations, []))
# if isa(series_anns, SeriesAnnotations)
# series_anns.x = plotattributes[:x]
# series_anns.y = plotattributes[:y]
# elseif length(series_anns) > 0
# x, y = plotattributes[:x], plotattributes[:y]
# nx, ny, na = map(length, (x,y,series_anns))
# n = max(nx, ny, na)
# series_anns = [(x[mod1(i,nx)], y[mod1(i,ny)], text(series_anns[mod1(i,na)])) for i=1:n]
# end
# sp.attr[:annotations] = vcat(sp_anns, series_anns)
end
function _expand_subplot_extrema(sp::Subplot, plotattributes::AKW, st::Symbol)
# adjust extrema and discrete info
if st == :image
xmin, xmax = ignorenan_extrema(plotattributes[:x]); ymin, ymax = ignorenan_extrema(plotattributes[:y])
xmin, xmax = ignorenan_extrema(plotattributes[:x])
ymin, ymax = ignorenan_extrema(plotattributes[:y])
expand_extrema!(sp[:xaxis], (xmin, xmax))
expand_extrema!(sp[:yaxis], (ymin, ymax))
elseif !(st in (:pie, :histogram, :bins2d, :histogram2d))
@ -398,56 +341,10 @@ function _expand_subplot_extrema(sp::Subplot, plotattributes::AKW, st::Symbol)
end
function _add_the_series(plt, sp, plotattributes)
warnOnUnsupported_args(plt.backend, plotattributes)
warnOnUnsupported(plt.backend, plotattributes)
warn_on_unsupported_args(plt.backend, plotattributes)
warn_on_unsupported(plt.backend, plotattributes)
series = Series(plotattributes)
push!(plt.series_list, series)
push!(sp.series_list, series)
_series_added(plt, series)
end
# -------------------------------------------------------------------------------
# this method recursively applies series recipes when the seriestype is not supported
# natively by the backend
function _process_seriesrecipe(plt::Plot, plotattributes::AKW)
#println("process $(typeof(plotattributes))")
# replace seriestype aliases
st = Symbol(plotattributes[:seriestype])
st = plotattributes[:seriestype] = get(_typeAliases, st, st)
# shapes shouldn't have fillrange set
if plotattributes[:seriestype] == :shape
plotattributes[:fillrange] = nothing
end
# if it's natively supported, finalize processing and pass along to the backend, otherwise recurse
if is_seriestype_supported(st)
sp = _prepare_subplot(plt, plotattributes)
_prepare_annotations(sp, plotattributes)
_expand_subplot_extrema(sp, plotattributes, st)
_update_series_attributes!(plotattributes, plt, sp)
_add_the_series(plt, sp, plotattributes)
else
# get a sub list of series for this seriestype
x, y, z = plotattributes[:x], plotattributes[:y], plotattributes[:z]
datalist = RecipesBase.apply_recipe(plotattributes, Val{st}, x, y, z)
warn_on_recipe_aliases!(datalist, :series, st)
# assuming there was no error, recursively apply the series recipes
for data in datalist
if isa(data, RecipeData)
preprocessArgs!(data.plotattributes)
if data.plotattributes[:seriestype] == st
error("The seriestype didn't change in series recipe $st. This will cause a StackOverflow.")
end
_process_seriesrecipe(plt, data.plotattributes)
else
@warn("Unhandled recipe: $(data)")
break
end
end
end
nothing
end

View File

@ -49,7 +49,7 @@ as a String to look up its docstring; e.g. `plotattr("seriestype")`.
function plot(args...; kw...)
# this creates a new plot with args/kw and sets it to be the current plot
plotattributes = KW(kw)
preprocessArgs!(plotattributes)
preprocess_attributes!(plotattributes)
# create an empty Plot then process
plt = Plot()
@ -61,7 +61,7 @@ end
# note: we split into plt1 and plts_tail so we can dispatch correctly
function plot(plt1::Plot, plts_tail::Plot...; kw...)
plotattributes = KW(kw)
preprocessArgs!(plotattributes)
preprocess_attributes!(plotattributes)
# build our plot vector from the args
n = length(plts_tail) + 1
@ -153,7 +153,7 @@ end
# this adds to a specific plot... most plot commands will flow through here
function plot!(plt::Plot, args...; kw...)
plotattributes = KW(kw)
preprocessArgs!(plotattributes)
preprocess_attributes!(plotattributes)
# merge!(plt.user_attr, plotattributes)
_plot!(plt, plotattributes, args)
end
@ -163,87 +163,11 @@ end
# this is the core plotting function. recursively apply recipes to build
# a list of series KW dicts.
# note: at entry, we only have those preprocessed args which were passed in... no default values yet
function _plot!(plt::Plot, plotattributes::AKW, args::Tuple)
plotattributes[:plot_object] = plt
if !isempty(args) && !isdefined(Main, :StatsPlots) &&
first(split(string(typeof(args[1])), ".")) == "DataFrames"
@warn("You're trying to plot a DataFrame, but this functionality is provided by StatsPlots")
end
# --------------------------------
# "USER RECIPES"
# --------------------------------
kw_list = _process_userrecipes(plt, plotattributes, args)
# @info(1)
# map(DD, kw_list)
# --------------------------------
# "PLOT RECIPES"
# --------------------------------
# "plot recipe", which acts like a series type, and is processed before
# the plot layout is created, which allows for setting layouts and other plot-wide attributes.
# we get inputs which have been fully processed by "user recipes" and "type recipes",
# so we can expect standard vectors, surfaces, etc. No defaults have been set yet.
still_to_process = kw_list
kw_list = KW[]
while !isempty(still_to_process)
next_kw = popfirst!(still_to_process)
_process_plotrecipe(plt, next_kw, kw_list, still_to_process)
end
# @info(2)
# map(DD, kw_list)
# --------------------------------
# Plot/Subplot/Layout setup
# --------------------------------
_plot_setup(plt, plotattributes, kw_list)
_subplot_setup(plt, plotattributes, kw_list)
# !!! note: At this point, kw_list is fully decomposed into individual series... one KW per series. !!!
# !!! The next step is to recursively apply series recipes until the backend supports that series type !!!
# --------------------------------
# "SERIES RECIPES"
# --------------------------------
# @info(3)
# map(DD, kw_list)
for kw in kw_list
sp::Subplot = kw[:subplot]
# in series attributes given as vector with one element per series,
# select the value for current series
_slice_series_args!(kw, plt, sp, series_idx(kw_list,kw))
series_attr = Attr(kw, _series_defaults)
# now we have a fully specified series, with colors chosen. we must recursively handle
# series recipes, which dispatch on seriestype. If a backend does not natively support a seriestype,
# we check for a recipe that will convert that series type into one made up of lower-level components.
# For example, a histogram is just a bar plot with binned data, a bar plot is really a filled step plot,
# and a step plot is really just a path. So any backend that supports drawing a path will implicitly
# be able to support step, bar, and histogram plots (and any recipes that use those components).
_process_seriesrecipe(plt, series_attr)
end
# --------------------------------
function _plot!(plt::Plot, plotattributes, args)
RecipePipeline.recipe_pipeline!(plt, plotattributes, args)
current(plt)
# do we want to force display?
# if plt[:show]
# gui(plt)
# end
_do_plot_show(plt, plt[:show])
plt
return plt
end

File diff suppressed because it is too large Load Diff

View File

@ -457,6 +457,8 @@ end
()
end
@deps plots_heatmap shape
is_3d(::Type{Val{:plots_heatmap}}) = true
is_surface(::Type{Val{:plots_heatmap}}) = true
# ---------------------------------------------------------------------------
# Histograms
@ -1165,6 +1167,118 @@ end
@deps quiver shape path
# --------------------------------------------------------------------
# 1 argument
# --------------------------------------------------------------------
# images - grays
function clamp_greys!(mat::AMat{<:Gray})
for i in eachindex(mat)
mat[i].val < 0 && (mat[i] = Gray(0))
mat[i].val > 1 && (mat[i] = Gray(1))
end
mat
end
@recipe function f(mat::AMat{<:Gray})
n, m = axes(mat)
if is_seriestype_supported(:image)
seriestype := :image
yflip --> true
SliceIt, m, n, Surface(clamp_greys!(mat))
else
seriestype := :heatmap
yflip --> true
cbar --> false
fillcolor --> ColorGradient([:black, :white])
SliceIt, m, n, Surface(clamp!(convert(Matrix{Float64}, mat), 0.0, 1.0))
end
end
# images - colors
@recipe function f(mat::AMat{T}) where {T <: Colorant}
n, m = axes(mat)
if is_seriestype_supported(:image)
seriestype := :image
yflip --> true
SliceIt, m, n, Surface(mat)
else
seriestype := :heatmap
yflip --> true
cbar --> false
aspect_ratio --> :equal
z, plotattributes[:fillcolor] = replace_image_with_heatmap(mat)
SliceIt, m, n, Surface(z)
end
end
# plotting arbitrary shapes/polygons
@recipe function f(shape::Shape)
seriestype --> :shape
coords(shape)
end
@recipe function f(shapes::AVec{Shape})
seriestype --> :shape
coords(shapes)
end
@recipe function f(shapes::AMat{Shape})
seriestype --> :shape
for j in axes(shapes, 2)
@series coords(vec(shapes[:, j]))
end
end
# --------------------------------------------------------------------
# 3 arguments
# --------------------------------------------------------------------
# images - grays
@recipe function f(x::AVec, y::AVec, mat::AMat{T}) where {T <: Gray}
if is_seriestype_supported(:image)
seriestype := :image
yflip --> true
SliceIt, x, y, Surface(mat)
else
seriestype := :heatmap
yflip --> true
cbar --> false
fillcolor --> ColorGradient([:black, :white])
SliceIt, x, y, Surface(convert(Matrix{Float64}, mat))
end
end
# images - colors
@recipe function f(x::AVec, y::AVec, mat::AMat{T}) where {T <: Colorant}
if is_seriestype_supported(:image)
seriestype := :image
yflip --> true
SliceIt, x, y, Surface(mat)
else
seriestype := :heatmap
yflip --> true
cbar --> false
z, plotattributes[:fillcolor] = replace_image_with_heatmap(mat)
SliceIt, x, y, Surface(z)
end
end
# --------------------------------------------------------------------
# Lists of tuples and GeometryTypes.Points
# --------------------------------------------------------------------
@recipe f(v::AVec{<:GeometryTypes.Point}) = unzip(v)
@recipe f(p::GeometryTypes.Point) = [p]
# Special case for 4-tuples in :ohlc series
@recipe f(xyuv::AVec{<:Tuple{R1, R2, R3, R4}}) where {R1, R2, R3, R4} =
get(plotattributes, :seriestype, :path) == :ohlc ? OHLC[OHLC(t...) for t in xyuv] :
unzip(xyuv)
# -------------------------------------------------
# TODO: move OHLC to PlotRecipes finance.jl

View File

@ -1,651 +0,0 @@
# create a new "build_series_args" which converts all inputs into xs = Any[xitems], ys = Any[yitems].
# Special handling for: no args, xmin/xmax, parametric, dataframes
# Then once inputs have been converted, build the series args, map functions, etc.
# This should cut down on boilerplate code and allow more focused dispatch on type
# note: returns meta information... mainly for use with automatic labeling from DataFrames for now
const FuncOrFuncs{F} = Union{F, Vector{F}, Matrix{F}}
const MaybeNumber = Union{Number, Missing}
const MaybeString = Union{AbstractString, Missing}
const DataPoint = Union{MaybeNumber, MaybeString}
prepareSeriesData(x) = error("Cannot convert $(typeof(x)) to series data for plotting")
prepareSeriesData(::Nothing) = nothing
prepareSeriesData(t::Tuple{T, T}) where {T<:Number} = t
prepareSeriesData(f::Function) = f
prepareSeriesData(ar::AbstractRange{<:Number}) = ar
function prepareSeriesData(a::AbstractArray{<:MaybeNumber})
f = isimmutable(a) ? replace : replace!
a = f(x -> ismissing(x) || isinf(x) ? NaN : x, map(float, a))
end
prepareSeriesData(a::AbstractArray{<:Missing}) = fill(NaN, axes(a))
prepareSeriesData(a::AbstractArray{<:MaybeString}) = replace(x -> ismissing(x) ? "" : x, a)
prepareSeriesData(s::Surface{<:AMat{<:MaybeNumber}}) = Surface(prepareSeriesData(s.surf))
prepareSeriesData(s::Surface) = s # non-numeric Surface, such as an image
prepareSeriesData(v::Volume) = Volume(prepareSeriesData(v.v), v.x_extents, v.y_extents, v.z_extents)
# default: assume x represents a single series
series_vector(x, plotattributes) = [prepareSeriesData(x)]
# fixed number of blank series
series_vector(n::Integer, plotattributes) = [zeros(0) for i in 1:n]
# vector of data points is a single series
series_vector(v::AVec{<:DataPoint}, plotattributes) = [prepareSeriesData(v)]
# list of things (maybe other vectors, functions, or something else)
function series_vector(v::AVec, plotattributes)
if all(x -> x isa MaybeNumber, v)
series_vector(Vector{MaybeNumber}(v), plotattributes)
elseif all(x -> x isa MaybeString, v)
series_vector(Vector{MaybeString}(v), plotattributes)
else
vcat((series_vector(vi, plotattributes) for vi in v)...)
end
end
# Matrix is split into columns
function series_vector(v::AMat{<:DataPoint}, plotattributes)
if all3D(plotattributes)
[prepareSeriesData(Surface(v))]
else
[prepareSeriesData(v[:, i]) for i in axes(v, 2)]
end
end
# --------------------------------------------------------------------
# Fillranges & ribbons
process_fillrange(range::Number, plotattributes) = [range]
process_fillrange(range, plotattributes) = series_vector(range, plotattributes)
process_ribbon(ribbon::Number, plotattributes) = [ribbon]
process_ribbon(ribbon, plotattributes) = series_vector(ribbon, plotattributes)
# ribbon as a tuple: (lower_ribbons, upper_ribbons)
process_ribbon(ribbon::Tuple{S, T}, plotattributes) where {S, T} = collect(zip(
series_vector(ribbon[1], plotattributes),
series_vector(ribbon[2], plotattributes),
))
# --------------------------------------------------------------------
compute_x(x::Nothing, y::Nothing, z) = axes(z,1)
compute_x(x::Nothing, y, z) = axes(y,1)
compute_x(x::Function, y, z) = map(x, y)
compute_x(x, y, z) = x
compute_y(x::Nothing, y::Nothing, z) = axes(z,2)
compute_y(x, y::Function, z) = map(y, x)
compute_y(x, y, z) = y
compute_z(x, y, z::Function) = map(z, x, y)
compute_z(x, y, z::AbstractMatrix) = Surface(z)
compute_z(x, y, z::Nothing) = nothing
compute_z(x, y, z) = z
nobigs(v::AVec{BigFloat}) = map(Float64, v)
nobigs(v::AVec{BigInt}) = map(Int64, v)
nobigs(v) = v
@noinline function compute_xyz(x, y, z)
x = compute_x(x,y,z)
y = compute_y(x,y,z)
z = compute_z(x,y,z)
nobigs(x), nobigs(y), nobigs(z)
end
# not allowed
compute_xyz(x::Nothing, y::FuncOrFuncs{F}, z) where {F<:Function} = error("If you want to plot the function `$y`, you need to define the x values!")
compute_xyz(x::Nothing, y::Nothing, z::FuncOrFuncs{F}) where {F<:Function} = error("If you want to plot the function `$z`, you need to define x and y values!")
compute_xyz(x::Nothing, y::Nothing, z::Nothing) = error("x/y/z are all nothing!")
# --------------------------------------------------------------------
# we are going to build recipes to do the processing and splitting of the args
# --------------------------------------------------------------------
# The catch-all SliceIt recipe
# --------------------------------------------------------------------
# ensure we dispatch to the slicer
struct SliceIt end
# The `SliceIt` recipe finishes user and type recipe processing.
# It splits processed data into individual series data, stores in copied `plotattributes`
# for each series and returns no arguments.
@recipe function f(::Type{SliceIt}, x, y, z)
# handle data with formatting attached
if typeof(x) <: Formatted
xformatter := x.formatter
x = x.data
end
if typeof(y) <: Formatted
yformatter := y.formatter
y = y.data
end
if typeof(z) <: Formatted
zformatter := z.formatter
z = z.data
end
xs = series_vector(x, plotattributes)
ys = series_vector(y, plotattributes)
zs = series_vector(z, plotattributes)
fr = pop!(plotattributes, :fillrange, nothing)
fillranges = process_fillrange(fr, plotattributes)
mf = length(fillranges)
rib = pop!(plotattributes, :ribbon, nothing)
ribbons = process_ribbon(rib, plotattributes)
mr = length(ribbons)
mx = length(xs)
my = length(ys)
mz = length(zs)
if mx > 0 && my > 0 && mz > 0
for i in 1:max(mx, my, mz)
# add a new series
di = copy(plotattributes)
xi, yi, zi = xs[mod1(i,mx)], ys[mod1(i,my)], zs[mod1(i,mz)]
di[:x], di[:y], di[:z] = compute_xyz(xi, yi, zi)
# handle fillrange
fr = fillranges[mod1(i,mf)]
di[:fillrange] = isa(fr, Function) ? map(fr, di[:x]) : fr
# handle ribbons
rib = ribbons[mod1(i,mr)]
di[:ribbon] = isa(rib, Function) ? map(rib, di[:x]) : rib
push!(series_list, RecipeData(di, ()))
end
end
nothing # don't add a series for the main block
end
# --------------------------------------------------------------------
# Apply type recipes
# --------------------------------------------------------------------
# this is the default "type recipe"... just pass the object through
@recipe f(::Type{T}, v::T) where T = v
# this should catch unhandled "series recipes" and error with a nice message
@recipe f(::Type{V}, x, y, z) where {V<:Val} = error("The backend must not support the series type $V, and there isn't a series recipe defined.")
function _apply_type_recipe(plotattributes, v, letter)
_preprocess_axis_args!(plotattributes, letter)
rdvec = RecipesBase.apply_recipe(plotattributes, typeof(v), v)
warn_on_recipe_aliases!(plotattributes, :type, typeof(v))
_postprocess_axis_args!(plotattributes, letter)
return rdvec[1].args[1]
end
# Handle type recipes when the recipe is defined on the elements.
# This sort of recipe should return a pair of functions... one to convert to number,
# and one to format tick values.
function _apply_type_recipe(plotattributes, v::AbstractArray, letter)
_preprocess_axis_args!(plotattributes, letter)
# First we try to apply an array type recipe.
w = RecipesBase.apply_recipe(plotattributes, typeof(v), v)[1].args[1]
warn_on_recipe_aliases!(plotattributes, :type, typeof(v))
# If the type did not change try it element-wise
if typeof(v) == typeof(w)
isempty(skipmissing(v)) && return Float64[]
x = first(skipmissing(v))
args = RecipesBase.apply_recipe(plotattributes, typeof(x), x)[1].args
warn_on_recipe_aliases!(plotattributes, :type, typeof(x))
_postprocess_axis_args!(plotattributes, letter)
if length(args) == 2 && all(arg -> arg isa Function, args)
numfunc, formatter = args
return Formatted(map(numfunc, v), formatter)
else
return v
end
end
_postprocess_axis_args!(plotattributes, letter)
return w
end
# special handling for Surface... need to properly unwrap and re-wrap
_apply_type_recipe(plotattributes, v::Surface{<:AMat{<:DataPoint}}) = v
function _apply_type_recipe(plotattributes, v::Surface)
ret = _apply_type_recipe(plotattributes, v.surf)
if typeof(ret) <: Formatted
Formatted(Surface(ret.data), ret.formatter)
else
Surface(ret.data)
end
end
# don't do anything for datapoints or nothing
_apply_type_recipe(plotattributes, v::AbstractArray{<:DataPoint}, letter) = v
_apply_type_recipe(plotattributes, v::Nothing, letter) = v
# axis args before type recipes should still be mapped to all axes
function _preprocess_axis_args!(plotattributes)
for (k, v) in plotattributes
if is_axis_attr_noletter(k)
pop!(plotattributes, k)
for l in (:x, :y, :z)
lk = Symbol(l, k)
haskey(plotattributes, lk) || (plotattributes[lk] = v)
end
end
end
end
function _preprocess_axis_args!(plotattributes, letter)
plotattributes[:letter] = letter
_preprocess_axis_args!(plotattributes)
end
# axis args in type recipes should only be applied to the current axis
function _postprocess_axis_args!(plotattributes, letter)
pop!(plotattributes, :letter)
if letter in (:x, :y, :z)
for (k, v) in plotattributes
if is_axis_attr_noletter(k)
pop!(plotattributes, k)
lk = Symbol(letter, k)
haskey(plotattributes, lk) || (plotattributes[lk] = v)
end
end
end
end
# --------------------------------------------------------------------
# Fallback user recipes calling type recipes
# --------------------------------------------------------------------
# handle "type recipes" by converting inputs, and then either re-calling or slicing
@recipe function f(x, y, z)
wrap_surfaces!(plotattributes, x, y, z)
did_replace = false
newx = _apply_type_recipe(plotattributes, x, :x)
x === newx || (did_replace = true)
newy = _apply_type_recipe(plotattributes, y, :y)
y === newy || (did_replace = true)
newz = _apply_type_recipe(plotattributes, z, :z)
z === newz || (did_replace = true)
if did_replace
newx, newy, newz
else
SliceIt, x, y, z
end
end
@recipe function f(x, y)
wrap_surfaces!(plotattributes, x, y)
did_replace = false
newx = _apply_type_recipe(plotattributes, x, :x)
x === newx || (did_replace = true)
newy = _apply_type_recipe(plotattributes, y, :y)
y === newy || (did_replace = true)
if did_replace
newx, newy
else
SliceIt, x, y, nothing
end
end
@recipe function f(y)
wrap_surfaces!(plotattributes, y)
newy = _apply_type_recipe(plotattributes, y, :y)
if y !== newy
newy
else
SliceIt, nothing, y, nothing
end
end
# if there's more than 3 inputs, it can't be passed directly to SliceIt
# so we'll apply_type_recipe to all of them
@recipe function f(v1, v2, v3, v4, vrest...)
did_replace = false
newargs = map(v -> begin
newv = _apply_type_recipe(plotattributes, v, :unknown)
if newv !== v
did_replace = true
end
newv
end, (v1, v2, v3, v4, vrest...))
if !did_replace
error("Couldn't process recipe args: $(map(typeof, (v1, v2, v3, v4, vrest...)))")
end
newargs
end
# helper function to ensure relevant attributes are wrapped by Surface
function wrap_surfaces!(plotattributes, args...) end
wrap_surfaces!(plotattributes, x::AMat, y::AMat, z::AMat) = wrap_surfaces!(plotattributes)
wrap_surfaces!(plotattributes, x::AVec, y::AVec, z::AMat) = wrap_surfaces!(plotattributes)
function wrap_surfaces!(plotattributes, x::AVec, y::AVec, z::Surface)
wrap_surfaces!(plotattributes)
end
function wrap_surfaces!(plotattributes)
if haskey(plotattributes, :fill_z)
v = plotattributes[:fill_z]
if !isa(v, Surface)
plotattributes[:fill_z] = Surface(v)
end
end
end
# --------------------------------------------------------------------
# 1 argument
# --------------------------------------------------------------------
@recipe f(n::Integer) = is3d(get(plotattributes,:seriestype,:path)) ? (SliceIt, n, n, n) : (SliceIt, n, n, nothing)
all3D(plotattributes) = trueOrAllTrue(
st -> st in (
:contour,
:contourf,
:heatmap,
:surface,
:wireframe,
:contour3d,
:image,
:plots_heatmap,
),
get(plotattributes, :seriestype, :none),
)
# return a surface if this is a 3d plot, otherwise let it be sliced up
@recipe function f(mat::AMat)
if all3D(plotattributes)
n, m = axes(mat)
m, n, Surface(mat)
else
nothing, mat, nothing
end
end
# if a matrix is wrapped by Formatted, do similar logic, but wrap data with Surface
@recipe function f(fmt::Formatted{<:AMat})
if all3D(plotattributes)
mat = fmt.data
n, m = axes(mat)
m, n, Formatted(Surface(mat), fmt.formatter)
else
nothing, fmt, nothing
end
end
# assume this is a Volume, so construct one
@recipe function f(vol::AbstractArray{<:MaybeNumber, 3}, args...)
seriestype := :volume
SliceIt, nothing, Volume(vol, args...), nothing
end
# images - grays
function clamp_greys!(mat::AMat{<:Gray})
for i in eachindex(mat)
mat[i].val < 0 && (mat[i] = Gray(0))
mat[i].val > 1 && (mat[i] = Gray(1))
end
mat
end
@recipe function f(mat::AMat{<:Gray})
n, m = axes(mat)
if is_seriestype_supported(:image)
seriestype := :image
yflip --> true
SliceIt, m, n, Surface(clamp_greys!(mat))
else
seriestype := :heatmap
yflip --> true
cbar --> false
fillcolor --> ColorGradient([:black, :white])
SliceIt, m, n, Surface(clamp!(convert(Matrix{Float64}, mat), 0., 1.))
end
end
# images - colors
@recipe function f(mat::AMat{T}) where T<:Colorant
n, m = axes(mat)
if is_seriestype_supported(:image)
seriestype := :image
yflip --> true
SliceIt, m, n, Surface(mat)
else
seriestype := :heatmap
yflip --> true
cbar --> false
aspect_ratio --> :equal
z, plotattributes[:fillcolor] = replace_image_with_heatmap(mat)
SliceIt, m, n, Surface(z)
end
end
# plotting arbitrary shapes/polygons
@recipe function f(shape::Shape)
seriestype --> :shape
coords(shape)
end
@recipe function f(shapes::AVec{Shape})
seriestype --> :shape
coords(shapes)
end
@recipe function f(shapes::AMat{Shape})
seriestype --> :shape
for j in axes(shapes,2)
@series coords(vec(shapes[:,j]))
end
end
# Dicts: each entry is a data point (x,y)=(key,value)
@recipe f(d::AbstractDict) = collect(keys(d)), collect(values(d))
# function without range... use the current range of the x-axis
@recipe function f(f::FuncOrFuncs{F}) where F<:Function
plt = plotattributes[:plot_object]
xmin, xmax = if haskey(plotattributes, :xlims)
plotattributes[:xlims]
else
try
axis_limits(plt[1], :x)
catch
xinv = invscalefunc(get(plotattributes, :xscale, :identity))
xm = PlotUtils.tryrange(f, xinv.([-5,-1,0,0.01]))
xm, PlotUtils.tryrange(f, filter(x->x>xm, xinv.([5,1,0.99, 0, -0.01])))
end
end
f, xmin, xmax
end
# --------------------------------------------------------------------
# 2 arguments
# --------------------------------------------------------------------
# if functions come first, just swap the order (not to be confused with parametric
# functions... as there would be more than one function passed in)
@recipe function f(f::FuncOrFuncs{F}, x) where F<:Function
F2 = typeof(x)
@assert !(F2 <: Function || (F2 <: AbstractArray && F2.parameters[1] <: Function)) # otherwise we'd hit infinite recursion here
x, f
end
# --------------------------------------------------------------------
# 3 arguments
# --------------------------------------------------------------------
# surface-like... function
@recipe function f(x::AVec, y::AVec, zf::Function)
x, y, Surface(zf, x, y) # TODO: replace with SurfaceFunction when supported
end
# surface-like... matrix grid
@recipe function f(x::AVec, y::AVec, z::AMat)
if !like_surface(get(plotattributes, :seriestype, :none))
plotattributes[:seriestype] = :contour
end
x, y, Surface(z)
end
# images - grays
@recipe function f(x::AVec, y::AVec, mat::AMat{T}) where T<:Gray
if is_seriestype_supported(:image)
seriestype := :image
yflip --> true
SliceIt, x, y, Surface(mat)
else
seriestype := :heatmap
yflip --> true
cbar --> false
fillcolor --> ColorGradient([:black, :white])
SliceIt, x, y, Surface(convert(Matrix{Float64}, mat))
end
end
# images - colors
@recipe function f(x::AVec, y::AVec, mat::AMat{T}) where T<:Colorant
if is_seriestype_supported(:image)
seriestype := :image
yflip --> true
SliceIt, x, y, Surface(mat)
else
seriestype := :heatmap
yflip --> true
cbar --> false
z, plotattributes[:fillcolor] = replace_image_with_heatmap(mat)
SliceIt, x, y, Surface(z)
end
end
# --------------------------------------------------------------------
# Parametric functions
# --------------------------------------------------------------------
# special handling... xmin/xmax with parametric function(s)
@recipe function f(f::Function, xmin::Number, xmax::Number)
xscale, yscale = [get(plotattributes, sym, :identity) for sym=(:xscale,:yscale)]
_scaled_adapted_grid(f, xscale, yscale, xmin, xmax)
end
@recipe function f(fs::AbstractArray{F}, xmin::Number, xmax::Number) where F<:Function
xscale, yscale = [get(plotattributes, sym, :identity) for sym=(:xscale,:yscale)]
unzip(_scaled_adapted_grid.(fs, xscale, yscale, xmin, xmax))
end
@recipe f(fx::FuncOrFuncs{F}, fy::FuncOrFuncs{G}, u::AVec) where {F<:Function,G<:Function} = mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u)
@recipe f(fx::FuncOrFuncs{F}, fy::FuncOrFuncs{G}, umin::Number, umax::Number, n = 200) where {F<:Function,G<:Function} = fx, fy, range(umin, stop = umax, length = n)
function _scaled_adapted_grid(f, xscale, yscale, xmin, xmax)
(xf, xinv), (yf, yinv) = ((scalefunc(s),invscalefunc(s)) for s in (xscale,yscale))
xs, ys = adapted_grid(yf∘f∘xinv, xf.((xmin, xmax)))
xinv.(xs), yinv.(ys)
end
# special handling... 3D parametric function(s)
@recipe function f(fx::FuncOrFuncs{F}, fy::FuncOrFuncs{G}, fz::FuncOrFuncs{H}, u::AVec) where {F<:Function,G<:Function,H<:Function}
mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u), mapFuncOrFuncs(fz, u)
end
@recipe function f(fx::FuncOrFuncs{F}, fy::FuncOrFuncs{G}, fz::FuncOrFuncs{H}, umin::Number, umax::Number, numPoints = 200) where {F<:Function,G<:Function,H<:Function}
fx, fy, fz, range(umin, stop = umax, length = numPoints)
end
# --------------------------------------------------------------------
# Lists of tuples and GeometryTypes.Points
# --------------------------------------------------------------------
@recipe f(v::AVec{<:Tuple}) = unzip(v)
@recipe f(v::AVec{<:GeometryTypes.Point}) = unzip(v)
@recipe f(tup::Tuple) = [tup]
@recipe f(p::GeometryTypes.Point) = [p]
# Special case for 4-tuples in :ohlc series
@recipe f(xyuv::AVec{<:Tuple{R1,R2,R3,R4}}) where {R1,R2,R3,R4} = get(plotattributes,:seriestype,:path)==:ohlc ? OHLC[OHLC(t...) for t in xyuv] : unzip(xyuv)
# --------------------------------------------------------------------
# handle grouping
# --------------------------------------------------------------------
splittable_kw(key, val, lengthGroup) = false
splittable_kw(key, val::AbstractArray, lengthGroup) = !(key in (:group, :color_palette)) && length(axes(val,1)) == lengthGroup
splittable_kw(key, val::Tuple, lengthGroup) = all(splittable_kw.(key, val, lengthGroup))
splittable_kw(key, val::SeriesAnnotations, lengthGroup) = splittable_kw(key, val.strs, lengthGroup)
split_kw(key, val::AbstractArray, indices) = val[indices, fill(Colon(), ndims(val)-1)...]
split_kw(key, val::Tuple, indices) = Tuple(split_kw(key, v, indices) for v in val)
function split_kw(key, val::SeriesAnnotations, indices)
split_strs = split_kw(key, val.strs, indices)
return SeriesAnnotations(split_strs, val.font, val.baseshape, val.scalefactor)
end
function groupedvec2mat(x_ind, x, y::AbstractArray, groupby, def_val = y[1])
y_mat = Array{promote_type(eltype(y), typeof(def_val))}(undef, length(keys(x_ind)), length(groupby.groupLabels))
fill!(y_mat, def_val)
for i in eachindex(groupby.groupLabels)
xi = x[groupby.groupIds[i]]
yi = y[groupby.groupIds[i]]
y_mat[getindex.(Ref(x_ind), xi), i] = yi
end
return y_mat
end
groupedvec2mat(x_ind, x, y::Tuple, groupby) = Tuple(groupedvec2mat(x_ind, x, v, groupby) for v in y)
group_as_matrix(t) = false
# split the group into 1 series per group, and set the label and idxfilter for each
@recipe function f(groupby::GroupBy, args...)
lengthGroup = maximum(union(groupby.groupIds...))
if !(group_as_matrix(args[1]))
for (i,glab) in enumerate(groupby.groupLabels)
@series begin
label --> string(glab)
idxfilter --> groupby.groupIds[i]
for (key,val) in plotattributes
if splittable_kw(key, val, lengthGroup)
:($key) := split_kw(key, val, groupby.groupIds[i])
end
end
args
end
end
else
g = args[1]
if length(g.args) == 1
x = zeros(Int, lengthGroup)
for indexes in groupby.groupIds
x[indexes] = eachindex(indexes)
end
last_args = g.args
else
x = g.args[1]
last_args = g.args[2:end]
end
x_u = unique(sort(x))
x_ind = Dict(zip(x_u, eachindex(x_u)))
for (key,val) in plotattributes
if splittable_kw(key, val, lengthGroup)
:($key) := groupedvec2mat(x_ind, x, val, groupby)
end
end
label --> reshape(groupby.groupLabels, 1, :)
typeof(g)((x_u, (groupedvec2mat(x_ind, x, arg, groupby, NaN) for arg in last_args)...))
end
end

View File

@ -7,7 +7,7 @@ function Subplot(::T; parent = RootLayout()) where T<:AbstractBackend
(20mm, 5mm, 2mm, 10mm),
defaultbox,
defaultbox,
Attr(KW(), _subplot_defaults),
DefaultsDict(KW(), _subplot_defaults),
nothing,
nothing
)

View File

@ -18,65 +18,10 @@ end
wrap(obj::T) where {T} = InputWrapper{T}(obj)
Base.isempty(wrapper::InputWrapper) = false
# -----------------------------------------------------------
struct Attr <: AbstractDict{Symbol,Any}
explicit::KW
defaults::KW
end
function Base.getindex(attr::Attr, k)
return haskey(attr.explicit, k) ? attr.explicit[k] : attr.defaults[k]
end
Base.haskey(attr::Attr, k) = haskey(attr.explicit,k) || haskey(attr.defaults,k)
Base.get(attr::Attr, k, default) = haskey(attr, k) ? attr[k] : default
function Base.get!(attr::Attr, k, default)
v = if haskey(attr, k)
attr[k]
else
attr.defaults[k] = default
end
return v
end
function Base.delete!(attr::Attr, k)
haskey(attr.explicit, k) && delete!(attr.explicit, k)
haskey(attr.defaults, k) && delete!(attr.defaults, k)
end
Base.length(attr::Attr) = length(union(keys(attr.explicit), keys(attr.defaults)))
function Base.iterate(attr::Attr)
exp_keys = keys(attr.explicit)
def_keys = setdiff(keys(attr.defaults), exp_keys)
key_list = collect(Iterators.flatten((exp_keys, def_keys)))
iterate(attr, (key_list, 1))
end
function Base.iterate(attr::Attr, (key_list, i))
i > length(key_list) && return nothing
k = key_list[i]
(k=>attr[k], (key_list, i+1))
end
Base.copy(attr::Attr) = Attr(copy(attr.explicit), attr.defaults)
RecipesBase.is_explicit(attr::Attr, k) = haskey(attr.explicit,k)
isdefault(attr::Attr, k) = !is_explicit(attr,k) && haskey(attr.defaults,k)
Base.setindex!(attr::Attr, v, k) = attr.explicit[k] = v
# Reset to default value and return dict
reset_kw!(attr::Attr, k) = is_explicit(attr, k) ? delete!(attr.explicit, k) : attr
# Reset to default value and return old value
pop_kw!(attr::Attr, k) = is_explicit(attr, k) ? pop!(attr.explicit, k) : attr.defaults[k]
pop_kw!(attr::Attr, k, default) = is_explicit(attr, k) ? pop!(attr.explicit, k) : get(attr.defaults, k, default)
# Fallbacks for dicts without defaults
reset_kw!(d::AKW, k) = delete!(d, k)
pop_kw!(d::AKW, k) = pop!(d, k)
pop_kw!(d::AKW, k, default) = pop!(d, k, default)
# -----------------------------------------------------------
mutable struct Series
plotattributes::Attr
plotattributes::DefaultsDict
end
attr(series::Series, k::Symbol) = series.plotattributes[k]
@ -91,7 +36,7 @@ mutable struct Subplot{T<:AbstractBackend} <: AbstractLayout
minpad::Tuple # leftpad, toppad, rightpad, bottompad
bbox::BoundingBox # the canvas area which is available to this subplot
plotarea::BoundingBox # the part where the data goes
attr::Attr # args specific to this subplot
attr::DefaultsDict # args specific to this subplot
o # can store backend-specific data... like a pyplot ax
plt # the enclosing Plot object (can't give it a type because of no forward declarations)
end
@ -103,7 +48,7 @@ Base.show(io::IO, sp::Subplot) = print(io, "Subplot{$(sp[:subplot_index])}")
# simple wrapper around a KW so we can hold all attributes pertaining to the axis in one place
mutable struct Axis
sps::Vector{Subplot}
plotattributes::Attr
plotattributes::DefaultsDict
end
mutable struct Extrema
@ -122,7 +67,7 @@ const SubplotMap = Dict{Any, Subplot}
mutable struct Plot{T<:AbstractBackend} <: AbstractPlot{T}
backend::T # the backend type
n::Int # number of series
attr::Attr # arguments for the whole plot
attr::DefaultsDict # arguments for the whole plot
series_list::Vector{Series} # arguments for each series
o # the backend's plot object
subplots::Vector{Subplot}
@ -133,7 +78,7 @@ mutable struct Plot{T<:AbstractBackend} <: AbstractPlot{T}
end
function Plot()
Plot(backend(), 0, Attr(KW(), _plot_defaults), Series[], nothing,
Plot(backend(), 0, DefaultsDict(KW(), _plot_defaults), Series[], nothing,
Subplot[], SubplotMap(), EmptyLayout(),
Subplot[], false)
end

View File

@ -143,9 +143,6 @@ makevec(v::T) where {T} = T[v]
maketuple(x::Real) = (x,x)
maketuple(x::Tuple{T,S}) where {T,S} = x
mapFuncOrFuncs(f::Function, u::AVec) = map(f, u)
mapFuncOrFuncs(fs::AVec{F}, u::AVec) where {F<:Function} = [map(f, u) for f in fs]
for i in 2:4
@eval begin
unzip(v::Union{AVec{<:Tuple{Vararg{T,$i} where T}},
@ -229,7 +226,7 @@ end
"create an (n+1) list of the outsides of heatmap rectangles"
function heatmap_edges(v::AVec, scale::Symbol = :identity, isedges::Bool = false)
f, invf = scalefunc(scale), invscalefunc(scale)
f, invf = scale_func(scale), inverse_scale_func(scale)
map(invf, _heatmap_edges(map(f,v), isedges))
end
@ -838,7 +835,7 @@ end
function attr!(series::Series; kw...)
plotattributes = KW(kw)
preprocessArgs!(plotattributes)
preprocess_attributes!(plotattributes)
for (k,v) in plotattributes
if haskey(_series_defaults, k)
series[k] = v
@ -852,7 +849,7 @@ end
function attr!(sp::Subplot; kw...)
plotattributes = KW(kw)
preprocessArgs!(plotattributes)
preprocess_attributes!(plotattributes)
for (k,v) in plotattributes
if haskey(_subplot_defaults, k)
sp[k] = v