Merge pull request #2469 from JuliaPlots/bbs/remove-defaults

remove default recipes

src/Plots.jl

@@ -18,13 +18,31 @@ using Base.Meta
 import Showoff
 import StatsBase
 import JSON
-import RecipePipeline: _process_userrecipe, _process_plotrecipe,
+import RecipePipeline:
-                    _process_seriesrecipe, _preprocess_args,
+    _process_userrecipe,
-                    preprocessArgs!, is_st_supported,
+    _process_plotrecipe,
-                    finalize_subplot!, recipe_pipeline!,
+    _process_seriesrecipe,
-                    _recipe_init!, _recipe_after_user!,
+    _preprocess_args,
-                    _recipe_after_plot!, _recipe_before_series!,
+    preprocessArgs!,
-                    _recipe_finish!, is_st_supported
+    is_st_supported,
+    finalize_subplot!,
+    recipe_pipeline!,
+    _recipe_init!,
+    _recipe_after_user!,
+    _recipe_after_plot!,
+    _recipe_before_series!,
+    _recipe_finish!,
+    is_st_supported,
+    Formatted,
+    SliceIt,
+    FuncOrFuncs,
+    MaybeNumber,
+    MaybeString,
+    DataPoint,
+    trueOrAllTrue,
+    Surface,
+    AbstractSurface,
+    Volume
 
 using Requires
 

src/components.jl

@@ -650,23 +650,6 @@ 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)
-  @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
@@ -686,30 +669,6 @@ 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
-
-# -----------------------------------------------------------------------
 
 # style is :open or :closed (for now)
 struct Arrow
@@ -771,13 +730,6 @@ 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"

src/series.jl

@@ -1,71 +1,4 @@
 
-
-# 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(a::AbstractArray{<:MaybeNumber}) = replace!(
-                                    x -> ismissing(x) || isinf(x) ? NaN : x,
-                                    map(float,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
-convertToAnyVector(x, plotattributes) = Any[prepareSeriesData(x)]
-
-# fixed number of blank series
-convertToAnyVector(n::Integer, plotattributes) = Any[zeros(0) for i in 1:n]
-
-# vector of data points is a single series
-convertToAnyVector(v::AVec{<:DataPoint}, plotattributes) = Any[prepareSeriesData(v)]
-
-# list of things (maybe other vectors, functions, or something else)
-function convertToAnyVector(v::AVec, plotattributes)
-    if all(x -> x isa MaybeNumber, v)
-        convertToAnyVector(Vector{MaybeNumber}(v), plotattributes)
-    elseif all(x -> x isa MaybeString, v)
-        convertToAnyVector(Vector{MaybeString}(v), plotattributes)
-    else
-        vcat((convertToAnyVector(vi, plotattributes) for vi in v)...)
-    end
-end
-
-# Matrix is split into columns
-function convertToAnyVector(v::AMat{<:DataPoint}, plotattributes)
-    if all3D(plotattributes)
-        Any[prepareSeriesData(Surface(v))]
-    else
-        Any[prepareSeriesData(v[:, i]) for i in axes(v, 2)]
-    end
-end
-
-# --------------------------------------------------------------------
-# Fillranges & ribbons
-
-
-process_fillrange(range::Number, plotattributes) = [range]
-process_fillrange(range, plotattributes) = convertToAnyVector(range, plotattributes)
-
-process_ribbon(ribbon::Number, plotattributes) = [ribbon]
-process_ribbon(ribbon, plotattributes) = convertToAnyVector(ribbon, plotattributes)
-# ribbon as a tuple: (lower_ribbons, upper_ribbons)
-process_ribbon(ribbon::Tuple{Any,Any}, plotattributes) = collect(zip(convertToAnyVector(ribbon[1], plotattributes),
-                                                     convertToAnyVector(ribbon[2], plotattributes)))
-
-
 # --------------------------------------------------------------------
 
 # TODO: can we avoid the copy here?  one error that crops up is that mapping functions over the same array
@@ -107,70 +40,6 @@ compute_xyz(x::Nothing, y::Nothing, z::Nothing)        = error("x/y/z are all no
 
 # we are going to build recipes to do the processing and splitting of the args
 
-# ensure we dispatch to the slicer
-struct SliceIt end
-
-# the catch-all recipes
-@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 = convertToAnyVector(x, plotattributes)
-    ys = convertToAnyVector(y, plotattributes)
-    zs = convertToAnyVector(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)
-
-    # @show zs
-
-    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
-
-# this is the default "type recipe"... just pass the object through
-@recipe f(::Type{T}, v::T) where {T<:Any} = 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) = RecipesBase.apply_recipe(plotattributes, typeof(v), v)[1].args[1]
 
@@ -278,7 +147,6 @@ end
 
 @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{T}) where T<:Union{Integer,AbstractFloat,Missing}

src/utils.jl

@@ -717,9 +717,6 @@ makekw(; kw...) = KW(kw)
 wraptuple(x::Tuple) = x
 wraptuple(x) = (x,)
 
-trueOrAllTrue(f::Function, x::AbstractArray) = all(f, x)
-trueOrAllTrue(f::Function, x) = f(x)
-
 allLineTypes(arg)   = trueOrAllTrue(a -> get(_typeAliases, a, a) in _allTypes, arg)
 allStyles(arg)      = trueOrAllTrue(a -> get(_styleAliases, a, a) in _allStyles, arg)
 allShapes(arg)      = trueOrAllTrue(a -> is_marker_supported(get(_markerAliases, a, a)), arg) ||