working on recipes overhaul

This commit is contained in:
Thomas Breloff 2016-05-12 14:00:47 -04:00
parent 6049a9fa0a
commit a5e9ad9f19
3 changed files with 401 additions and 371 deletions

View File

@ -171,7 +171,7 @@ include("backends.jl")
include("args.jl")
include("themes.jl")
include("plot.jl")
# include("series_args.jl")
include("series_args.jl")
include("series_new.jl")
include("subplot.jl")
include("layouts.jl")

View File

@ -97,367 +97,367 @@ compute_xyz(x::Void, y::Void, z::Void) = error("x/y/z are all nothing!")
# --------------------------------------------------------------------
# create n=max(mx,my) series arguments. the shorter list is cycled through
# note: everything should flow through this
function build_series_args(plt::AbstractPlot, kw::KW) #, idxfilter)
x, y, z = map(sym -> pop!(kw, sym, nothing), (:x, :y, :z))
if nothing == x == y == z
return [], nothing, nothing
end
xs, xmeta = convertToAnyVector(x, kw)
ys, ymeta = convertToAnyVector(y, kw)
zs, zmeta = convertToAnyVector(z, kw)
fr = pop!(kw, :fillrange, nothing)
fillranges, _ = if typeof(fr) <: Number
([fr],nothing)
else
convertToAnyVector(fr, kw)
end
mx = length(xs)
my = length(ys)
mz = length(zs)
ret = Any[]
for i in 1:max(mx, my, mz)
# try to set labels using ymeta
d = copy(kw)
if !haskey(d, :label) && ymeta != nothing
if isa(ymeta, Symbol)
d[:label] = string(ymeta)
elseif isa(ymeta, AVec{Symbol})
d[:label] = string(ymeta[mod1(i,length(ymeta))])
end
end
# build the series arg dict
numUncounted = pop!(d, :numUncounted, 0)
commandIndex = i + numUncounted
n = plt.n + i
dumpdict(d, "before getSeriesArgs")
d = getSeriesArgs(plt.backend, getplotargs(plt, n), d, commandIndex, convertSeriesIndex(plt, n), n)
dumpdict(d, "after getSeriesArgs")
d[:x], d[:y], d[:z] = compute_xyz(xs[mod1(i,mx)], ys[mod1(i,my)], zs[mod1(i,mz)])
lt = d[:linetype]
# for linetype `line`, need to sort by x values
if lt == :line
# order by x
indices = sortperm(d[:x])
d[:x] = d[:x][indices]
d[:y] = d[:y][indices]
d[:linetype] = :path
end
# special handling for missing x in box plot... all the same category
if lt == :box && xs[mod1(i,mx)] == nothing
d[:x] = ones(Int, length(d[:y]))
end
# map functions to vectors
if isa(d[:marker_z], Function)
d[:marker_z] = map(d[:marker_z], d[:x])
end
# @show fillranges
d[:fillrange] = fillranges[mod1(i,length(fillranges))]
if isa(d[:fillrange], Function)
d[:fillrange] = map(d[:fillrange], d[:x])
end
# handle error bars
for esym in (:xerror, :yerror)
if get(d, esym, nothing) != nothing
# we make a copy of the KW and apply an errorbar recipe
append!(ret, apply_series_recipe(copy(d), Val{esym}))
end
end
# handle ribbons
if get(d, :ribbon, nothing) != nothing
rib = d[:ribbon]
d[:fillrange] = (d[:y] - rib, d[:y] + rib)
end
# handle quiver plots
# either a series of velocity vectors are passed in (`:quiver` keyword),
# or we just add arrows to the path
# if lt == :quiver
# d[:linetype] = lt = :path
# d[:linewidth] = 0
# end
if get(d, :quiver, nothing) != nothing
append!(ret, apply_series_recipe(copy(d), Val{:quiver}))
elseif lt == :quiver
d[:linetype] = lt = :path
d[:arrow] = arrow()
end
# now that we've processed a given series... optionally split into
# multiple dicts through a recipe (for example, a box plot is split into component
# parts... polygons, lines, and scatters)
# note: we pass in a Val type (i.e. Val{:box}) so that we can dispatch on the linetype
kwlist = apply_series_recipe(d, Val{lt})
append!(ret, kwlist)
# # add it to our series list
# push!(ret, d)
end
ret, xmeta, ymeta
end
# --------------------------------------------------------------------
# process_inputs
# --------------------------------------------------------------------
# These methods take a plot and the keyword arguments, and processes the input
# arguments (x/y/z, group, etc), populating the KW dict with appropriate values.
# --------------------------------------------------------------------
# 0 arguments
# --------------------------------------------------------------------
# don't do anything
function process_inputs(plt::AbstractPlot, d::KW)
end
# --------------------------------------------------------------------
# 1 argument
# --------------------------------------------------------------------
function process_inputs(plt::AbstractPlot, d::KW, n::Integer)
# d[:x], d[:y], d[:z] = zeros(0), zeros(0), zeros(0)
d[:x] = d[:y] = d[:z] = n
end
# no special handling... assume x and z are nothing
function process_inputs(plt::AbstractPlot, d::KW, y)
d[:y] = y
end
# matrix... is it z or y?
function process_inputs{T<:Number}(plt::AbstractPlot, d::KW, mat::AMat{T})
if all3D(d)
n,m = size(mat)
d[:x], d[:y], d[:z] = 1:n, 1:m, mat
else
d[:y] = mat
end
end
# images - grays
function process_inputs{T<:Gray}(plt::AbstractPlot, d::KW, mat::AMat{T})
d[:linetype] = :image
n,m = size(mat)
d[:x], d[:y], d[:z] = 1:n, 1:m, Surface(mat)
# handle images... when not supported natively, do a hack to use heatmap machinery
if !nativeImagesSupported()
d[:linetype] = :heatmap
d[:yflip] = true
d[:z] = Surface(convert(Matrix{Float64}, mat.surf))
d[:fillcolor] = ColorGradient([:black, :white])
end
end
# images - colors
function process_inputs{T<:Colorant}(plt::AbstractPlot, d::KW, mat::AMat{T})
d[:linetype] = :image
n,m = size(mat)
d[:x], d[:y], d[:z] = 1:n, 1:m, Surface(mat)
# handle images... when not supported natively, do a hack to use heatmap machinery
if !nativeImagesSupported()
d[:yflip] = true
imageHack(d)
end
end
# plotting arbitrary shapes/polygons
function process_inputs(plt::AbstractPlot, d::KW, shape::Shape)
d[:x], d[:y] = shape_coords(shape)
d[:linetype] = :shape
end
function process_inputs(plt::AbstractPlot, d::KW, shapes::AVec{Shape})
d[:x], d[:y] = shape_coords(shapes)
d[:linetype] = :shape
end
function process_inputs(plt::AbstractPlot, d::KW, shapes::AMat{Shape})
x, y = [], []
for j in 1:size(shapes, 2)
tmpx, tmpy = shape_coords(vec(shapes[:,j]))
push!(x, tmpx)
push!(y, tmpy)
end
d[:x], d[:y] = x, y
d[:linetype] = :shape
end
# function without range... use the current range of the x-axis
function process_inputs(plt::AbstractPlot, d::KW, f::FuncOrFuncs)
process_inputs(plt, d, f, xmin(plt), xmax(plt))
end
# --------------------------------------------------------------------
# 2 arguments
# --------------------------------------------------------------------
function process_inputs(plt::AbstractPlot, d::KW, x, y)
d[:x], d[:y] = x, y
end
# 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)
function process_inputs(plt::AbstractPlot, d::KW, f::FuncOrFuncs, x)
@assert !(typeof(x) <: FuncOrFuncs) # otherwise we'd hit infinite recursion here
process_inputs(plt, d, x, f)
end
# --------------------------------------------------------------------
# 3 arguments
# --------------------------------------------------------------------
# no special handling... just pass them through
function process_inputs(plt::AbstractPlot, d::KW, x, y, z)
d[:x], d[:y], d[:z] = x, y, z
end
# 3d line or scatter
function process_inputs(plt::AbstractPlot, d::KW, x::AVec, y::AVec, zvec::AVec)
# default to path3d if we haven't set a 3d linetype
lt = get(d, :linetype, :none)
if lt == :scatter
d[:linetype] = :scatter3d
elseif !(lt in _3dTypes)
d[:linetype] = :path3d
end
d[:x], d[:y], d[:z] = x, y, zvec
end
# surface-like... function
function process_inputs{TX,TY}(plt::AbstractPlot, d::KW, x::AVec{TX}, y::AVec{TY}, zf::Function)
x = TX <: Number ? sort(x) : x
y = TY <: Number ? sort(y) : y
# x, y = sort(x), sort(y)
d[:z] = Surface(zf, x, y) # TODO: replace with SurfaceFunction when supported
d[:x], d[:y] = x, y
end
# surface-like... matrix grid
function process_inputs{TX,TY,TZ}(plt::AbstractPlot, d::KW, x::AVec{TX}, y::AVec{TY}, zmat::AMat{TZ})
# @assert size(zmat) == (length(x), length(y))
# if TX <: Number && !issorted(x)
# idx = sortperm(x)
# x, zmat = x[idx], zmat[idx, :]
# end
# if TY <: Number && !issorted(y)
# idx = sortperm(y)
# y, zmat = y[idx], zmat[:, idx]
# end
d[:x], d[:y], d[:z] = x, y, Surface{Matrix{TZ}}(zmat)
if !like_surface(get(d, :linetype, :none))
d[:linetype] = :contour
end
end
# surfaces-like... general x, y grid
function process_inputs{T<:Number}(plt::AbstractPlot, d::KW, x::AMat{T}, y::AMat{T}, zmat::AMat{T})
@assert size(zmat) == size(x) == size(y)
# d[:x], d[:y], d[:z] = Any[x], Any[y], Surface{Matrix{Float64}}(zmat)
d[:x], d[:y], d[:z] = map(Surface{Matrix{Float64}}, (x, y, zmat))
if !like_surface(get(d, :linetype, :none))
d[:linetype] = :contour
end
end
# --------------------------------------------------------------------
# Parametric functions
# --------------------------------------------------------------------
# special handling... xmin/xmax with function(s)
function process_inputs(plt::AbstractPlot, d::KW, f::FuncOrFuncs, xmin::Number, xmax::Number)
width = get(plt.plotargs, :size, (100,))[1]
x = linspace(xmin, xmax, width)
process_inputs(plt, d, x, f)
end
# special handling... xmin/xmax with parametric function(s)
process_inputs{T<:Number}(plt::AbstractPlot, d::KW, fx::FuncOrFuncs, fy::FuncOrFuncs, u::AVec{T}) = process_inputs(plt, d, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u))
process_inputs{T<:Number}(plt::AbstractPlot, d::KW, u::AVec{T}, fx::FuncOrFuncs, fy::FuncOrFuncs) = process_inputs(plt, d, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u))
process_inputs(plt::AbstractPlot, d::KW, fx::FuncOrFuncs, fy::FuncOrFuncs, umin::Number, umax::Number, numPoints::Int = 1000) = process_inputs(plt, d, fx, fy, linspace(umin, umax, numPoints))
# special handling... 3D parametric function(s)
process_inputs{T<:Number}(plt::AbstractPlot, d::KW, fx::FuncOrFuncs, fy::FuncOrFuncs, fz::FuncOrFuncs, u::AVec{T}) = process_inputs(plt, d, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u), mapFuncOrFuncs(fz, u))
process_inputs{T<:Number}(plt::AbstractPlot, d::KW, u::AVec{T}, fx::FuncOrFuncs, fy::FuncOrFuncs, fz::FuncOrFuncs) = process_inputs(plt, d, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u), mapFuncOrFuncs(fz, u))
process_inputs(plt::AbstractPlot, d::KW, fx::FuncOrFuncs, fy::FuncOrFuncs, fz::FuncOrFuncs, umin::Number, umax::Number, numPoints::Int = 1000) = process_inputs(plt, d, fx, fy, fz, linspace(umin, umax, numPoints))
# --------------------------------------------------------------------
# Lists of tuples and FixedSizeArrays
# --------------------------------------------------------------------
# if we get an unhandled tuple, just splat it in
function process_inputs(plt::AbstractPlot, d::KW, tup::Tuple)
process_inputs(plt, d, tup...)
end
# (x,y) tuples
function process_inputs{R1<:Number,R2<:Number}(plt::AbstractPlot, d::KW, xy::AVec{Tuple{R1,R2}})
process_inputs(plt, d, unzip(xy)...)
end
function process_inputs{R1<:Number,R2<:Number}(plt::AbstractPlot, d::KW, xy::Tuple{R1,R2})
process_inputs(plt, d, [xy[1]], [xy[2]])
end
# (x,y,z) tuples
function process_inputs{R1<:Number,R2<:Number,R3<:Number}(plt::AbstractPlot, d::KW, xyz::AVec{Tuple{R1,R2,R3}})
process_inputs(plt, d, unzip(xyz)...)
end
function process_inputs{R1<:Number,R2<:Number,R3<:Number}(plt::AbstractPlot, d::KW, xyz::Tuple{R1,R2,R3})
process_inputs(plt, d, [xyz[1]], [xyz[2]], [xyz[3]])
end
# 2D FixedSizeArrays
function process_inputs{T<:Number}(plt::AbstractPlot, d::KW, xy::AVec{FixedSizeArrays.Vec{2,T}})
process_inputs(plt, d, unzip(xy)...)
end
function process_inputs{T<:Number}(plt::AbstractPlot, d::KW, xy::FixedSizeArrays.Vec{2,T})
process_inputs(plt, d, [xy[1]], [xy[2]])
end
# 3D FixedSizeArrays
function process_inputs{T<:Number}(plt::AbstractPlot, d::KW, xyz::AVec{FixedSizeArrays.Vec{3,T}})
process_inputs(plt, d, unzip(xyz)...)
end
function process_inputs{T<:Number}(plt::AbstractPlot, d::KW, xyz::FixedSizeArrays.Vec{3,T})
process_inputs(plt, d, [xyz[1]], [xyz[2]], [xyz[3]])
end
# --------------------------------------------------------------------
# handle grouping
# --------------------------------------------------------------------
# function process_inputs(plt::AbstractPlot, d::KW, groupby::GroupBy, args...)
# ret = Any[]
# error("unfinished after series reorg")
# for (i,glab) in enumerate(groupby.groupLabels)
# # TODO: don't automatically overwrite labels
# kwlist, xmeta, ymeta = process_inputs(plt, d, args...,
# idxfilter = groupby.groupIds[i],
# label = string(glab),
# numUncounted = length(ret)) # we count the idx from plt.n + numUncounted + i
# append!(ret, kwlist)
# # create n=max(mx,my) series arguments. the shorter list is cycled through
# # note: everything should flow through this
# function build_series_args(plt::AbstractPlot, kw::KW) #, idxfilter)
# x, y, z = map(sym -> pop!(kw, sym, nothing), (:x, :y, :z))
# if nothing == x == y == z
# return [], nothing, nothing
# end
# ret, nothing, nothing # TODO: handle passing meta through
#
# xs, xmeta = convertToAnyVector(x, kw)
# ys, ymeta = convertToAnyVector(y, kw)
# zs, zmeta = convertToAnyVector(z, kw)
#
# fr = pop!(kw, :fillrange, nothing)
# fillranges, _ = if typeof(fr) <: Number
# ([fr],nothing)
# else
# convertToAnyVector(fr, kw)
# end
#
# mx = length(xs)
# my = length(ys)
# mz = length(zs)
# ret = Any[]
# for i in 1:max(mx, my, mz)
#
# # try to set labels using ymeta
# d = copy(kw)
# if !haskey(d, :label) && ymeta != nothing
# if isa(ymeta, Symbol)
# d[:label] = string(ymeta)
# elseif isa(ymeta, AVec{Symbol})
# d[:label] = string(ymeta[mod1(i,length(ymeta))])
# end
# end
#
# # build the series arg dict
# numUncounted = pop!(d, :numUncounted, 0)
# commandIndex = i + numUncounted
# n = plt.n + i
#
# dumpdict(d, "before getSeriesArgs")
# d = getSeriesArgs(plt.backend, getplotargs(plt, n), d, commandIndex, convertSeriesIndex(plt, n), n)
# dumpdict(d, "after getSeriesArgs")
#
# d[:x], d[:y], d[:z] = compute_xyz(xs[mod1(i,mx)], ys[mod1(i,my)], zs[mod1(i,mz)])
# lt = d[:linetype]
#
# # for linetype `line`, need to sort by x values
# if lt == :line
# # order by x
# indices = sortperm(d[:x])
# d[:x] = d[:x][indices]
# d[:y] = d[:y][indices]
# d[:linetype] = :path
# end
#
# # special handling for missing x in box plot... all the same category
# if lt == :box && xs[mod1(i,mx)] == nothing
# d[:x] = ones(Int, length(d[:y]))
# end
#
# # map functions to vectors
# if isa(d[:marker_z], Function)
# d[:marker_z] = map(d[:marker_z], d[:x])
# end
#
# # @show fillranges
# d[:fillrange] = fillranges[mod1(i,length(fillranges))]
# if isa(d[:fillrange], Function)
# d[:fillrange] = map(d[:fillrange], d[:x])
# end
#
# # handle error bars
# for esym in (:xerror, :yerror)
# if get(d, esym, nothing) != nothing
# # we make a copy of the KW and apply an errorbar recipe
# append!(ret, apply_series_recipe(copy(d), Val{esym}))
# end
# end
#
# # handle ribbons
# if get(d, :ribbon, nothing) != nothing
# rib = d[:ribbon]
# d[:fillrange] = (d[:y] - rib, d[:y] + rib)
# end
#
# # handle quiver plots
# # either a series of velocity vectors are passed in (`:quiver` keyword),
# # or we just add arrows to the path
#
# # if lt == :quiver
# # d[:linetype] = lt = :path
# # d[:linewidth] = 0
# # end
# if get(d, :quiver, nothing) != nothing
# append!(ret, apply_series_recipe(copy(d), Val{:quiver}))
# elseif lt == :quiver
# d[:linetype] = lt = :path
# d[:arrow] = arrow()
# end
#
# # now that we've processed a given series... optionally split into
# # multiple dicts through a recipe (for example, a box plot is split into component
# # parts... polygons, lines, and scatters)
# # note: we pass in a Val type (i.e. Val{:box}) so that we can dispatch on the linetype
# kwlist = apply_series_recipe(d, Val{lt})
# append!(ret, kwlist)
#
# # # add it to our series list
# # push!(ret, d)
# end
#
# ret, xmeta, ymeta
# end
#
#
# # --------------------------------------------------------------------
# # process_inputs
# # --------------------------------------------------------------------
#
# # These methods take a plot and the keyword arguments, and processes the input
# # arguments (x/y/z, group, etc), populating the KW dict with appropriate values.
#
# # --------------------------------------------------------------------
# # 0 arguments
# # --------------------------------------------------------------------
#
# # don't do anything
# function process_inputs(plt::AbstractPlot, d::KW)
# end
#
# # --------------------------------------------------------------------
# # 1 argument
# # --------------------------------------------------------------------
#
# function process_inputs(plt::AbstractPlot, d::KW, n::Integer)
# # d[:x], d[:y], d[:z] = zeros(0), zeros(0), zeros(0)
# d[:x] = d[:y] = d[:z] = n
# end
#
# # no special handling... assume x and z are nothing
# function process_inputs(plt::AbstractPlot, d::KW, y)
# d[:y] = y
# end
#
# # matrix... is it z or y?
# function process_inputs{T<:Number}(plt::AbstractPlot, d::KW, mat::AMat{T})
# if all3D(d)
# n,m = size(mat)
# d[:x], d[:y], d[:z] = 1:n, 1:m, mat
# else
# d[:y] = mat
# end
# end
#
# # images - grays
# function process_inputs{T<:Gray}(plt::AbstractPlot, d::KW, mat::AMat{T})
# d[:linetype] = :image
# n,m = size(mat)
# d[:x], d[:y], d[:z] = 1:n, 1:m, Surface(mat)
# # handle images... when not supported natively, do a hack to use heatmap machinery
# if !nativeImagesSupported()
# d[:linetype] = :heatmap
# d[:yflip] = true
# d[:z] = Surface(convert(Matrix{Float64}, mat.surf))
# d[:fillcolor] = ColorGradient([:black, :white])
# end
# end
#
# # images - colors
# function process_inputs{T<:Colorant}(plt::AbstractPlot, d::KW, mat::AMat{T})
# d[:linetype] = :image
# n,m = size(mat)
# d[:x], d[:y], d[:z] = 1:n, 1:m, Surface(mat)
# # handle images... when not supported natively, do a hack to use heatmap machinery
# if !nativeImagesSupported()
# d[:yflip] = true
# imageHack(d)
# end
# end
#
#
# # plotting arbitrary shapes/polygons
# function process_inputs(plt::AbstractPlot, d::KW, shape::Shape)
# d[:x], d[:y] = shape_coords(shape)
# d[:linetype] = :shape
# end
# function process_inputs(plt::AbstractPlot, d::KW, shapes::AVec{Shape})
# d[:x], d[:y] = shape_coords(shapes)
# d[:linetype] = :shape
# end
# function process_inputs(plt::AbstractPlot, d::KW, shapes::AMat{Shape})
# x, y = [], []
# for j in 1:size(shapes, 2)
# tmpx, tmpy = shape_coords(vec(shapes[:,j]))
# push!(x, tmpx)
# push!(y, tmpy)
# end
# d[:x], d[:y] = x, y
# d[:linetype] = :shape
# end
#
#
# # function without range... use the current range of the x-axis
# function process_inputs(plt::AbstractPlot, d::KW, f::FuncOrFuncs)
# process_inputs(plt, d, f, xmin(plt), xmax(plt))
# end
#
# # --------------------------------------------------------------------
# # 2 arguments
# # --------------------------------------------------------------------
#
# function process_inputs(plt::AbstractPlot, d::KW, x, y)
# d[:x], d[:y] = x, y
# end
#
# # 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)
# function process_inputs(plt::AbstractPlot, d::KW, f::FuncOrFuncs, x)
# @assert !(typeof(x) <: FuncOrFuncs) # otherwise we'd hit infinite recursion here
# process_inputs(plt, d, x, f)
# end
#
# # --------------------------------------------------------------------
# # 3 arguments
# # --------------------------------------------------------------------
#
# # no special handling... just pass them through
# function process_inputs(plt::AbstractPlot, d::KW, x, y, z)
# d[:x], d[:y], d[:z] = x, y, z
# end
#
# # 3d line or scatter
# function process_inputs(plt::AbstractPlot, d::KW, x::AVec, y::AVec, zvec::AVec)
# # default to path3d if we haven't set a 3d linetype
# lt = get(d, :linetype, :none)
# if lt == :scatter
# d[:linetype] = :scatter3d
# elseif !(lt in _3dTypes)
# d[:linetype] = :path3d
# end
# d[:x], d[:y], d[:z] = x, y, zvec
# end
#
# # surface-like... function
# function process_inputs{TX,TY}(plt::AbstractPlot, d::KW, x::AVec{TX}, y::AVec{TY}, zf::Function)
# x = TX <: Number ? sort(x) : x
# y = TY <: Number ? sort(y) : y
# # x, y = sort(x), sort(y)
# d[:z] = Surface(zf, x, y) # TODO: replace with SurfaceFunction when supported
# d[:x], d[:y] = x, y
# end
#
# # surface-like... matrix grid
# function process_inputs{TX,TY,TZ}(plt::AbstractPlot, d::KW, x::AVec{TX}, y::AVec{TY}, zmat::AMat{TZ})
# # @assert size(zmat) == (length(x), length(y))
# # if TX <: Number && !issorted(x)
# # idx = sortperm(x)
# # x, zmat = x[idx], zmat[idx, :]
# # end
# # if TY <: Number && !issorted(y)
# # idx = sortperm(y)
# # y, zmat = y[idx], zmat[:, idx]
# # end
# d[:x], d[:y], d[:z] = x, y, Surface{Matrix{TZ}}(zmat)
# if !like_surface(get(d, :linetype, :none))
# d[:linetype] = :contour
# end
# end
#
# # surfaces-like... general x, y grid
# function process_inputs{T<:Number}(plt::AbstractPlot, d::KW, x::AMat{T}, y::AMat{T}, zmat::AMat{T})
# @assert size(zmat) == size(x) == size(y)
# # d[:x], d[:y], d[:z] = Any[x], Any[y], Surface{Matrix{Float64}}(zmat)
# d[:x], d[:y], d[:z] = map(Surface{Matrix{Float64}}, (x, y, zmat))
# if !like_surface(get(d, :linetype, :none))
# d[:linetype] = :contour
# end
# end
#
#
# # --------------------------------------------------------------------
# # Parametric functions
# # --------------------------------------------------------------------
#
# # special handling... xmin/xmax with function(s)
# function process_inputs(plt::AbstractPlot, d::KW, f::FuncOrFuncs, xmin::Number, xmax::Number)
# width = get(plt.plotargs, :size, (100,))[1]
# x = linspace(xmin, xmax, width)
# process_inputs(plt, d, x, f)
# end
#
# # special handling... xmin/xmax with parametric function(s)
# process_inputs{T<:Number}(plt::AbstractPlot, d::KW, fx::FuncOrFuncs, fy::FuncOrFuncs, u::AVec{T}) = process_inputs(plt, d, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u))
# process_inputs{T<:Number}(plt::AbstractPlot, d::KW, u::AVec{T}, fx::FuncOrFuncs, fy::FuncOrFuncs) = process_inputs(plt, d, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u))
# process_inputs(plt::AbstractPlot, d::KW, fx::FuncOrFuncs, fy::FuncOrFuncs, umin::Number, umax::Number, numPoints::Int = 1000) = process_inputs(plt, d, fx, fy, linspace(umin, umax, numPoints))
#
# # special handling... 3D parametric function(s)
# process_inputs{T<:Number}(plt::AbstractPlot, d::KW, fx::FuncOrFuncs, fy::FuncOrFuncs, fz::FuncOrFuncs, u::AVec{T}) = process_inputs(plt, d, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u), mapFuncOrFuncs(fz, u))
# process_inputs{T<:Number}(plt::AbstractPlot, d::KW, u::AVec{T}, fx::FuncOrFuncs, fy::FuncOrFuncs, fz::FuncOrFuncs) = process_inputs(plt, d, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u), mapFuncOrFuncs(fz, u))
# process_inputs(plt::AbstractPlot, d::KW, fx::FuncOrFuncs, fy::FuncOrFuncs, fz::FuncOrFuncs, umin::Number, umax::Number, numPoints::Int = 1000) = process_inputs(plt, d, fx, fy, fz, linspace(umin, umax, numPoints))
#
#
# # --------------------------------------------------------------------
# # Lists of tuples and FixedSizeArrays
# # --------------------------------------------------------------------
#
# # if we get an unhandled tuple, just splat it in
# function process_inputs(plt::AbstractPlot, d::KW, tup::Tuple)
# process_inputs(plt, d, tup...)
# end
#
# # (x,y) tuples
# function process_inputs{R1<:Number,R2<:Number}(plt::AbstractPlot, d::KW, xy::AVec{Tuple{R1,R2}})
# process_inputs(plt, d, unzip(xy)...)
# end
# function process_inputs{R1<:Number,R2<:Number}(plt::AbstractPlot, d::KW, xy::Tuple{R1,R2})
# process_inputs(plt, d, [xy[1]], [xy[2]])
# end
#
# # (x,y,z) tuples
# function process_inputs{R1<:Number,R2<:Number,R3<:Number}(plt::AbstractPlot, d::KW, xyz::AVec{Tuple{R1,R2,R3}})
# process_inputs(plt, d, unzip(xyz)...)
# end
# function process_inputs{R1<:Number,R2<:Number,R3<:Number}(plt::AbstractPlot, d::KW, xyz::Tuple{R1,R2,R3})
# process_inputs(plt, d, [xyz[1]], [xyz[2]], [xyz[3]])
# end
#
# # 2D FixedSizeArrays
# function process_inputs{T<:Number}(plt::AbstractPlot, d::KW, xy::AVec{FixedSizeArrays.Vec{2,T}})
# process_inputs(plt, d, unzip(xy)...)
# end
# function process_inputs{T<:Number}(plt::AbstractPlot, d::KW, xy::FixedSizeArrays.Vec{2,T})
# process_inputs(plt, d, [xy[1]], [xy[2]])
# end
#
# # 3D FixedSizeArrays
# function process_inputs{T<:Number}(plt::AbstractPlot, d::KW, xyz::AVec{FixedSizeArrays.Vec{3,T}})
# process_inputs(plt, d, unzip(xyz)...)
# end
# function process_inputs{T<:Number}(plt::AbstractPlot, d::KW, xyz::FixedSizeArrays.Vec{3,T})
# process_inputs(plt, d, [xyz[1]], [xyz[2]], [xyz[3]])
# end
#
# # --------------------------------------------------------------------
# # handle grouping
# # --------------------------------------------------------------------
#
# # function process_inputs(plt::AbstractPlot, d::KW, groupby::GroupBy, args...)
# # ret = Any[]
# # error("unfinished after series reorg")
# # for (i,glab) in enumerate(groupby.groupLabels)
# # # TODO: don't automatically overwrite labels
# # kwlist, xmeta, ymeta = process_inputs(plt, d, args...,
# # idxfilter = groupby.groupIds[i],
# # label = string(glab),
# # numUncounted = length(ret)) # we count the idx from plt.n + numUncounted + i
# # append!(ret, kwlist)
# # end
# # ret, nothing, nothing # TODO: handle passing meta through
# # end
# --------------------------------------------------------------------
# For DataFrame support. Imports DataFrames and defines the necessary methods which support them.

View File

@ -87,17 +87,47 @@ end
# instead of process_inputs:
# the catch-all recipes
@recipe function f(x, y, z)
@show "HERE", typeof((x,y,z))
xs, _ = convertToAnyVector(x, d)
ys, _ = convertToAnyVector(y, d)
zs, _ = convertToAnyVector(z, d)
@recipe function f{Y<:Number}(y::AVec{Y})
x --> 1:length(y)
y --> y
dumpdict(d,"y",true)
()
fr = pop!(d, :fillrange, nothing)
fillranges, _ = if typeof(fr) <: Number
([fr],nothing)
else
convertToAnyVector(fr, d)
end
mx = length(xs)
my = length(ys)
mz = length(zs)
# ret = Any[]
for i in 1:max(mx, my, mz)
# add a new series
di = copy(d)
di[:x], di[:y], di[:z] = compute_xyz(xs[mod1(i,mx)], ys[mod1(i,my)], zs[mod1(i,mz)])
@show i, di[:x], di[:y], di[:z]
push!(series_list, RecipeData(di, ()))
end
nothing # don't add a series for the main block
end
@recipe function f{X<:Number,Y<:Number}(x::AVec{X}, y::AVec{Y})
x --> x
y --> y
dumpdict(d,"xy",true)
()
end
@recipe f(x, y) = x, y, nothing
@recipe f(y) = nothing, y, nothing
# @recipe function f{Y<:Number}(y::AVec{Y})
# x --> 1:length(y)
# y --> y
# dumpdict(d,"y",true)
# ()
# end
#
# @recipe function f{X<:Number,Y<:Number}(x::AVec{X}, y::AVec{Y})
# x --> x
# y --> y
# dumpdict(d,"xy",true)
# ()
# end