changed createKWArgsList to build_series_args and moved into series_args.jl; added Cairo and Fontconfig to test/REQUIRE

This commit is contained in:
Thomas Breloff 2016-03-17 10:08:03 -04:00
parent 1d1e1beca5
commit 0b403a4c5d
6 changed files with 378 additions and 382 deletions

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@ -17,7 +17,7 @@ script:
# - julia -e 'Pkg.clone("ImageMagick"); Pkg.build("ImageMagick")' # - julia -e 'Pkg.clone("ImageMagick"); Pkg.build("ImageMagick")'
- julia -e 'Pkg.clone("https://github.com/tbreloff/VisualRegressionTests.jl.git");' - julia -e 'Pkg.clone("https://github.com/tbreloff/VisualRegressionTests.jl.git");'
- julia -e 'Pkg.clone("https://github.com/tbreloff/ExamplePlots.jl.git");' - julia -e 'Pkg.clone("https://github.com/tbreloff/ExamplePlots.jl.git");'
- julia -e 'Pkg.clone("Cairo"); Pkg.build("Cairo")' # - julia -e 'Pkg.add("Cairo"); Pkg.build("Cairo")'
- julia -e 'ENV["PYTHON"] = ""; Pkg.clone("PyPlot"); Pkg.build("PyPlot")' # - julia -e 'ENV["PYTHON"] = ""; Pkg.add("PyPlot"); Pkg.build("PyPlot")'
- julia -e 'Pkg.test("Plots"; coverage=false)' - julia -e 'Pkg.test("Plots"; coverage=false)'
# - julia -e 'cd(Pkg.dir("Plots")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(process_folder()); Codecov.submit(process_folder())' # - julia -e 'cd(Pkg.dir("Plots")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(process_folder()); Codecov.submit(process_folder())'

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@ -141,6 +141,7 @@ include("components.jl")
include("backends.jl") include("backends.jl")
include("args.jl") include("args.jl")
include("plot.jl") include("plot.jl")
include("series_args.jl")
include("subplot.jl") include("subplot.jl")
include("layouts.jl") include("layouts.jl")
include("recipes.jl") include("recipes.jl")

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@ -88,7 +88,7 @@ function plot!(plt::Plot, args...; kw...)
_before_add_series(plt) _before_add_series(plt)
# get the list of dictionaries, one per series # get the list of dictionaries, one per series
seriesArgList, xmeta, ymeta = createKWargsList(plt, groupargs..., args...; d...) seriesArgList, xmeta, ymeta = build_series_args(plt, groupargs..., args...; d...)
# if we were able to extract guide information from the series inputs, then update the plot # if we were able to extract guide information from the series inputs, then update the plot
# @show xmeta, ymeta # @show xmeta, ymeta
@ -214,381 +214,3 @@ function Base.copy(plt::Plot)
end end
# -------------------------------------------------------------------- # --------------------------------------------------------------------
# create a new "createKWargsList" 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
typealias FuncOrFuncs @compat(Union{Function, AVec{Function}})
all3D(d::Dict) = trueOrAllTrue(lt -> lt in (:contour, :heatmap, :surface, :wireframe), get(d, :linetype, :none))
# missing
convertToAnyVector(v::@compat(Void), d::Dict) = Any[nothing], nothing
# fixed number of blank series
convertToAnyVector(n::Integer, d::Dict) = Any[zeros(0) for i in 1:n], nothing
# numeric vector
convertToAnyVector{T<:Real}(v::AVec{T}, d::Dict) = Any[v], nothing
# string vector
convertToAnyVector{T<:@compat(AbstractString)}(v::AVec{T}, d::Dict) = Any[v], nothing
# numeric matrix
function convertToAnyVector{T<:Real}(v::AMat{T}, d::Dict)
if all3D(d)
Any[Surface(v)]
else
Any[v[:,i] for i in 1:size(v,2)]
end, nothing
end
# function
convertToAnyVector(f::Function, d::Dict) = Any[f], nothing
# surface
convertToAnyVector(s::Surface, d::Dict) = Any[s], nothing
# vector of OHLC
convertToAnyVector(v::AVec{OHLC}, d::Dict) = Any[v], nothing
# dates
convertToAnyVector{D<:Union{Date,DateTime}}(dts::AVec{D}, d::Dict) = Any[dts], nothing
# list of things (maybe other vectors, functions, or something else)
function convertToAnyVector(v::AVec, d::Dict)
if all(x -> typeof(x) <: Real, v)
# all real numbers wrap the whole vector as one item
Any[convert(Vector{Float64}, v)], nothing
else
# something else... treat each element as an item
vcat(Any[convertToAnyVector(vi, d)[1] for vi in v]...), nothing
# Any[vi for vi in v], nothing
end
end
# --------------------------------------------------------------------
# in computeXandY, we take in any of the possible items, convert into proper x/y vectors, then return.
# this is also where all the "set x to 1:length(y)" happens, and also where we assert on lengths.
computeX(x::@compat(Void), y) = 1:size(y,1)
computeX(x, y) = copy(x)
computeY(x, y::Function) = map(y, x)
computeY(x, y) = copy(y)
function computeXandY(x, y)
if x == nothing && isa(y, Function)
error("If you want to plot the function `$y`, you need to define the x values somehow!")
end
x, y = computeX(x,y), computeY(x,y)
# @assert length(x) == length(y)
x, y
end
# --------------------------------------------------------------------
# create n=max(mx,my) series arguments. the shorter list is cycled through
# note: everything should flow through this
function createKWargsList(plt::AbstractPlot, x, y; kw...)
kwdict = Dict(kw)
xs, xmeta = convertToAnyVector(x, kwdict)
ys, ymeta = convertToAnyVector(y, kwdict)
mx = length(xs)
my = length(ys)
ret = Any[]
for i in 1:max(mx, my)
# try to set labels using ymeta
d = copy(kwdict)
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 = get(d, :numUncounted, 0)
n = plt.n + i + numUncounted
dumpdict(d, "before getSeriesArgs")
d = getSeriesArgs(plt.backend, getplotargs(plt, n), d, i + numUncounted, convertSeriesIndex(plt, n), n)
dumpdict(d, "after getSeriesArgs")
d[:x], d[:y] = computeXandY(xs[mod1(i,mx)], ys[mod1(i,my)])
lt = d[:linetype]
if isa(d[:y], Surface)
if lt in (:contour, :heatmap, :surface, :wireframe)
z = d[:y]
d[:y] = 1:size(z,2)
d[:z] = z
end
end
if haskey(d, :idxfilter)
d[:x] = d[:x][d[:idxfilter]]
d[:y] = d[:y][d[:idxfilter]]
end
# 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
# map functions to vectors
if isa(d[:zcolor], Function)
d[:zcolor] = map(d[:zcolor], d[:x])
end
if isa(d[:fillrange], Function)
d[:fillrange] = map(d[:fillrange], d[:x])
end
# cleanup those fields that were used only for generating kw args
for k in (:idxfilter, :numUncounted, :dataframe)
delete!(d, k)
end
# add it to our series list
push!(ret, d)
end
ret, xmeta, ymeta
end
# handle grouping
function createKWargsList(plt::AbstractPlot, groupby::GroupBy, args...; kw...)
ret = Any[]
for (i,glab) in enumerate(groupby.groupLabels)
# TODO: don't automatically overwrite labels
kwlist, xmeta, ymeta = createKWargsList(plt, args...; kw...,
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
# pass it off to the x/y version
function createKWargsList(plt::AbstractPlot, y; kw...)
createKWargsList(plt, nothing, y; kw...)
end
# 3d line or scatter
function createKWargsList(plt::AbstractPlot, x::AVec, y::AVec, zvec::AVec; kw...)
d = Dict(kw)
if !(get(d, :linetype, :none) in _3dTypes)
d[:linetype] = :path3d
end
createKWargsList(plt, x, y; z=zvec, d...)
end
function createKWargsList{T<:Real}(plt::AbstractPlot, z::AMat{T}; kw...)
d = Dict(kw)
if all3D(d)
n,m = size(z)
createKWargsList(plt, 1:n, 1:m, z; kw...)
else
createKWargsList(plt, nothing, z; kw...)
end
end
# contours or surfaces... function grid
function createKWargsList(plt::AbstractPlot, x::AVec, y::AVec, zf::Function; kw...)
# only allow sorted x/y for now
# TODO: auto sort x/y/z properly
@assert x == sort(x)
@assert y == sort(y)
surface = Float64[zf(xi, yi) for xi in x, yi in y]
createKWargsList(plt, x, y, surface; kw...) # passes it to the zmat version
end
# contours or surfaces... matrix grid
function createKWargsList{T<:Real}(plt::AbstractPlot, x::AVec, y::AVec, zmat::AMat{T}; kw...)
# only allow sorted x/y for now
# TODO: auto sort x/y/z properly
@assert x == sort(x)
@assert y == sort(y)
@assert size(zmat) == (length(x), length(y))
# surf = Surface(convert(Matrix{Float64}, zmat))
# surf = Array(Any,1,1)
# surf[1,1] = convert(Matrix{Float64}, zmat)
d = Dict(kw)
d[:z] = Surface(convert(Matrix{Float64}, zmat))
if !(get(d, :linetype, :none) in (:contour, :heatmap, :surface, :wireframe))
d[:linetype] = :contour
end
createKWargsList(plt, x, y; d...) #, z = surf)
end
# contours or surfaces... general x, y grid
function createKWargsList{T<:Real}(plt::AbstractPlot, x::AMat{T}, y::AMat{T}, zmat::AMat{T}; kw...)
@assert size(zmat) == size(x) == size(y)
surf = Surface(convert(Matrix{Float64}, zmat))
# surf = Array(Any,1,1)
# surf[1,1] = convert(Matrix{Float64}, zmat)
d = Dict(kw)
d[:z] = Surface(convert(Matrix{Float64}, zmat))
if !(get(d, :linetype, :none) in (:contour, :heatmap, :surface, :wireframe))
d[:linetype] = :contour
end
createKWargsList(plt, Any[x], Any[y]; d...) #kw..., z = surf, linetype = :contour)
end
# plotting arbitrary shapes/polygons
function createKWargsList(plt::AbstractPlot, shape::Shape; kw...)
x, y = unzip(shape.vertices)
createKWargsList(plt, x, y; linetype = :shape, kw...)
end
function shape_coords(shapes::AVec{Shape})
xs = map(get_xs, shapes)
ys = map(get_ys, shapes)
x, y = unzip(shapes[1].vertices)
for shape in shapes[2:end]
tmpx, tmpy = unzip(shape.vertices)
x = vcat(x, NaN, tmpx)
y = vcat(y, NaN, tmpy)
end
x, y
end
function createKWargsList(plt::AbstractPlot, shapes::AVec{Shape}; kw...)
x, y = shape_coords(shapes)
createKWargsList(plt, x, y; linetype = :shape, kw...)
end
function createKWargsList(plt::AbstractPlot, shapes::AMat{Shape}; kw...)
x, y = [], []
for j in 1:size(shapes, 2)
tmpx, tmpy = shape_coords(vec(shapes[:,j]))
push!(x, tmpx)
push!(y, tmpy)
end
createKWargsList(plt, x, y; linetype = :shape, kw...)
end
function createKWargsList(plt::AbstractPlot, surf::Surface; kw...)
createKWargsList(plt, 1:size(surf.surf,1), 1:size(surf.surf,2), convert(Matrix{Float64}, surf.surf); kw...)
end
function createKWargsList(plt::AbstractPlot, x::AVec, y::AVec, surf::Surface; kw...)
createKWargsList(plt, x, y, convert(Matrix{Float64}, surf.surf); kw...)
end
function createKWargsList(plt::AbstractPlot, f::FuncOrFuncs; kw...)
createKWargsList(plt, f, xmin(plt), xmax(plt); kw...)
end
# list of functions
function createKWargsList(plt::AbstractPlot, f::FuncOrFuncs, x; kw...)
@assert !(typeof(x) <: FuncOrFuncs) # otherwise we'd hit infinite recursion here
createKWargsList(plt, x, f; kw...)
end
# special handling... xmin/xmax with function(s)
function createKWargsList(plt::AbstractPlot, f::FuncOrFuncs, xmin::Real, xmax::Real; kw...)
width = get(plt.plotargs, :size, (100,))[1]
x = collect(linspace(xmin, xmax, width)) # we don't need more than the width
createKWargsList(plt, x, f; kw...)
end
mapFuncOrFuncs(f::Function, u::AVec) = map(f, u)
mapFuncOrFuncs(fs::AVec{Function}, u::AVec) = [map(f, u) for f in fs]
# special handling... xmin/xmax with parametric function(s)
createKWargsList{T<:Real}(plt::AbstractPlot, fx::FuncOrFuncs, fy::FuncOrFuncs, u::AVec{T}; kw...) = createKWargsList(plt, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u); kw...)
createKWargsList{T<:Real}(plt::AbstractPlot, u::AVec{T}, fx::FuncOrFuncs, fy::FuncOrFuncs; kw...) = createKWargsList(plt, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u); kw...)
createKWargsList(plt::AbstractPlot, fx::FuncOrFuncs, fy::FuncOrFuncs, umin::Real, umax::Real, numPoints::Int = 1000; kw...) = createKWargsList(plt, fx, fy, linspace(umin, umax, numPoints); kw...)
# special handling... 3D parametric function(s)
createKWargsList{T<:Real}(plt::AbstractPlot, fx::FuncOrFuncs, fy::FuncOrFuncs, fz::FuncOrFuncs, u::AVec{T}; kw...) = createKWargsList(plt, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u), mapFuncOrFuncs(fz, u); kw...)
createKWargsList{T<:Real}(plt::AbstractPlot, u::AVec{T}, fx::FuncOrFuncs, fy::FuncOrFuncs, fz::FuncOrFuncs; kw...) = createKWargsList(plt, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u), mapFuncOrFuncs(fz, u); kw...)
createKWargsList(plt::AbstractPlot, fx::FuncOrFuncs, fy::FuncOrFuncs, fz::FuncOrFuncs, umin::Real, umax::Real, numPoints::Int = 1000; kw...) = createKWargsList(plt, fx, fy, fz, linspace(umin, umax, numPoints); kw...)
# (x,y) tuples
function createKWargsList{R1<:Real,R2<:Real}(plt::AbstractPlot, xy::AVec{Tuple{R1,R2}}; kw...)
createKWargsList(plt, unzip(xy)...; kw...)
end
function createKWargsList{R1<:Real,R2<:Real}(plt::AbstractPlot, xy::Tuple{R1,R2}; kw...)
createKWargsList(plt, [xy[1]], [xy[2]]; kw...)
end
# special handling... no args... 1 series
function createKWargsList(plt::AbstractPlot; kw...)
d = Dict(kw)
if !haskey(d, :y)
# assume we just want to create an empty plot object which can be added to later
return [], nothing, nothing
# error("Called plot/subplot without args... must set y in the keyword args. Example: plot(; y=rand(10))")
end
if haskey(d, :x)
return createKWargsList(plt, d[:x], d[:y]; kw...)
else
return createKWargsList(plt, d[:y]; kw...)
end
end
# --------------------------------------------------------------------
# @require FixedSizeArrays begin
unzip{T}(x::AVec{FixedSizeArrays.Vec{2,T}}) = T[xi[1] for xi in x], T[xi[2] for xi in x]
unzip{T}(x::FixedSizeArrays.Vec{2,T}) = T[x[1]], T[x[2]]
function createKWargsList{T<:Real}(plt::AbstractPlot, xy::AVec{FixedSizeArrays.Vec{2,T}}; kw...)
createKWargsList(plt, unzip(xy)...; kw...)
end
function createKWargsList{T<:Real}(plt::AbstractPlot, xy::FixedSizeArrays.Vec{2,T}; kw...)
createKWargsList(plt, [xy[1]], [xy[2]]; kw...)
end
# end
# --------------------------------------------------------------------
# For DataFrame support. Imports DataFrames and defines the necessary methods which support them.
function setup_dataframes()
@require DataFrames begin
function createKWargsList(plt::AbstractPlot, df::DataFrames.AbstractDataFrame, args...; kw...)
createKWargsList(plt, args...; kw..., dataframe = df)
end
# expecting the column name of a dataframe that was passed in... anything else should error
function extractGroupArgs(s::Symbol, df::DataFrames.AbstractDataFrame, args...)
if haskey(df, s)
return extractGroupArgs(df[s])
else
error("Got a symbol, and expected that to be a key in d[:dataframe]. s=$s d=$d")
end
end
function getDataFrameFromKW(d::Dict)
get(d, :dataframe) do
error("Missing dataframe argument!")
end
end
# the conversion functions for when we pass symbols or vectors of symbols to reference dataframes
convertToAnyVector(s::Symbol, d::Dict) = Any[getDataFrameFromKW(d)[s]], s
convertToAnyVector(v::AVec{Symbol}, d::Dict) = (df = getDataFrameFromKW(d); Any[df[s] for s in v]), v
end
end
# --------------------------------------------------------------------

371
src/series_args.jl Normal file
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@ -0,0 +1,371 @@
# 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
typealias FuncOrFuncs @compat(Union{Function, AVec{Function}})
all3D(d::Dict) = trueOrAllTrue(lt -> lt in (:contour, :heatmap, :surface, :wireframe), get(d, :linetype, :none))
# missing
convertToAnyVector(v::@compat(Void), d::Dict) = Any[nothing], nothing
# fixed number of blank series
convertToAnyVector(n::Integer, d::Dict) = Any[zeros(0) for i in 1:n], nothing
# numeric vector
convertToAnyVector{T<:Real}(v::AVec{T}, d::Dict) = Any[v], nothing
# string vector
convertToAnyVector{T<:@compat(AbstractString)}(v::AVec{T}, d::Dict) = Any[v], nothing
# numeric matrix
function convertToAnyVector{T<:Real}(v::AMat{T}, d::Dict)
if all3D(d)
Any[Surface(v)]
else
Any[v[:,i] for i in 1:size(v,2)]
end, nothing
end
# function
convertToAnyVector(f::Function, d::Dict) = Any[f], nothing
# surface
convertToAnyVector(s::Surface, d::Dict) = Any[s], nothing
# vector of OHLC
convertToAnyVector(v::AVec{OHLC}, d::Dict) = Any[v], nothing
# dates
convertToAnyVector{D<:Union{Date,DateTime}}(dts::AVec{D}, d::Dict) = Any[dts], nothing
# list of things (maybe other vectors, functions, or something else)
function convertToAnyVector(v::AVec, d::Dict)
if all(x -> typeof(x) <: Real, v)
# all real numbers wrap the whole vector as one item
Any[convert(Vector{Float64}, v)], nothing
else
# something else... treat each element as an item
vcat(Any[convertToAnyVector(vi, d)[1] for vi in v]...), nothing
# Any[vi for vi in v], nothing
end
end
# --------------------------------------------------------------------
# in computeXandY, we take in any of the possible items, convert into proper x/y vectors, then return.
# this is also where all the "set x to 1:length(y)" happens, and also where we assert on lengths.
computeX(x::@compat(Void), y) = 1:size(y,1)
computeX(x, y) = copy(x)
computeY(x, y::Function) = map(y, x)
computeY(x, y) = copy(y)
function computeXandY(x, y)
if x == nothing && isa(y, Function)
error("If you want to plot the function `$y`, you need to define the x values somehow!")
end
x, y = computeX(x,y), computeY(x,y)
# @assert length(x) == length(y)
x, y
end
# --------------------------------------------------------------------
# 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, x, y; kw...)
kwdict = Dict(kw)
xs, xmeta = convertToAnyVector(x, kwdict)
ys, ymeta = convertToAnyVector(y, kwdict)
mx = length(xs)
my = length(ys)
ret = Any[]
for i in 1:max(mx, my)
# try to set labels using ymeta
d = copy(kwdict)
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 = get(d, :numUncounted, 0)
n = plt.n + i + numUncounted
dumpdict(d, "before getSeriesArgs")
d = getSeriesArgs(plt.backend, getplotargs(plt, n), d, i + numUncounted, convertSeriesIndex(plt, n), n)
dumpdict(d, "after getSeriesArgs")
d[:x], d[:y] = computeXandY(xs[mod1(i,mx)], ys[mod1(i,my)])
lt = d[:linetype]
if isa(d[:y], Surface)
if lt in (:contour, :heatmap, :surface, :wireframe)
z = d[:y]
d[:y] = 1:size(z,2)
d[:z] = z
end
end
if haskey(d, :idxfilter)
d[:x] = d[:x][d[:idxfilter]]
d[:y] = d[:y][d[:idxfilter]]
end
# 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
# map functions to vectors
if isa(d[:zcolor], Function)
d[:zcolor] = map(d[:zcolor], d[:x])
end
if isa(d[:fillrange], Function)
d[:fillrange] = map(d[:fillrange], d[:x])
end
# cleanup those fields that were used only for generating kw args
for k in (:idxfilter, :numUncounted, :dataframe)
delete!(d, k)
end
# add it to our series list
push!(ret, d)
end
ret, xmeta, ymeta
end
# handle grouping
function build_series_args(plt::AbstractPlot, groupby::GroupBy, args...; kw...)
ret = Any[]
for (i,glab) in enumerate(groupby.groupLabels)
# TODO: don't automatically overwrite labels
kwlist, xmeta, ymeta = build_series_args(plt, args...; kw...,
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
# pass it off to the x/y version
function build_series_args(plt::AbstractPlot, y; kw...)
build_series_args(plt, nothing, y; kw...)
end
# 3d line or scatter
function build_series_args(plt::AbstractPlot, x::AVec, y::AVec, zvec::AVec; kw...)
d = Dict(kw)
if !(get(d, :linetype, :none) in _3dTypes)
d[:linetype] = :path3d
end
build_series_args(plt, x, y; z=zvec, d...)
end
function build_series_args{T<:Real}(plt::AbstractPlot, z::AMat{T}; kw...)
d = Dict(kw)
if all3D(d)
n,m = size(z)
build_series_args(plt, 1:n, 1:m, z; kw...)
else
build_series_args(plt, nothing, z; kw...)
end
end
# contours or surfaces... function grid
function build_series_args(plt::AbstractPlot, x::AVec, y::AVec, zf::Function; kw...)
# only allow sorted x/y for now
# TODO: auto sort x/y/z properly
@assert x == sort(x)
@assert y == sort(y)
surface = Float64[zf(xi, yi) for xi in x, yi in y]
build_series_args(plt, x, y, surface; kw...) # passes it to the zmat version
end
# contours or surfaces... matrix grid
function build_series_args{T<:Real}(plt::AbstractPlot, x::AVec, y::AVec, zmat::AMat{T}; kw...)
# only allow sorted x/y for now
# TODO: auto sort x/y/z properly
@assert x == sort(x)
@assert y == sort(y)
@assert size(zmat) == (length(x), length(y))
# surf = Surface(convert(Matrix{Float64}, zmat))
# surf = Array(Any,1,1)
# surf[1,1] = convert(Matrix{Float64}, zmat)
d = Dict(kw)
d[:z] = Surface(convert(Matrix{Float64}, zmat))
if !(get(d, :linetype, :none) in (:contour, :heatmap, :surface, :wireframe))
d[:linetype] = :contour
end
build_series_args(plt, x, y; d...) #, z = surf)
end
# contours or surfaces... general x, y grid
function build_series_args{T<:Real}(plt::AbstractPlot, x::AMat{T}, y::AMat{T}, zmat::AMat{T}; kw...)
@assert size(zmat) == size(x) == size(y)
surf = Surface(convert(Matrix{Float64}, zmat))
# surf = Array(Any,1,1)
# surf[1,1] = convert(Matrix{Float64}, zmat)
d = Dict(kw)
d[:z] = Surface(convert(Matrix{Float64}, zmat))
if !(get(d, :linetype, :none) in (:contour, :heatmap, :surface, :wireframe))
d[:linetype] = :contour
end
build_series_args(plt, Any[x], Any[y]; d...) #kw..., z = surf, linetype = :contour)
end
# plotting arbitrary shapes/polygons
function build_series_args(plt::AbstractPlot, shape::Shape; kw...)
x, y = unzip(shape.vertices)
build_series_args(plt, x, y; linetype = :shape, kw...)
end
function shape_coords(shapes::AVec{Shape})
xs = map(get_xs, shapes)
ys = map(get_ys, shapes)
x, y = unzip(shapes[1].vertices)
for shape in shapes[2:end]
tmpx, tmpy = unzip(shape.vertices)
x = vcat(x, NaN, tmpx)
y = vcat(y, NaN, tmpy)
end
x, y
end
function build_series_args(plt::AbstractPlot, shapes::AVec{Shape}; kw...)
x, y = shape_coords(shapes)
build_series_args(plt, x, y; linetype = :shape, kw...)
end
function build_series_args(plt::AbstractPlot, shapes::AMat{Shape}; kw...)
x, y = [], []
for j in 1:size(shapes, 2)
tmpx, tmpy = shape_coords(vec(shapes[:,j]))
push!(x, tmpx)
push!(y, tmpy)
end
build_series_args(plt, x, y; linetype = :shape, kw...)
end
function build_series_args(plt::AbstractPlot, surf::Surface; kw...)
build_series_args(plt, 1:size(surf.surf,1), 1:size(surf.surf,2), convert(Matrix{Float64}, surf.surf); kw...)
end
function build_series_args(plt::AbstractPlot, x::AVec, y::AVec, surf::Surface; kw...)
build_series_args(plt, x, y, convert(Matrix{Float64}, surf.surf); kw...)
end
function build_series_args(plt::AbstractPlot, f::FuncOrFuncs; kw...)
build_series_args(plt, f, xmin(plt), xmax(plt); kw...)
end
# list of functions
function build_series_args(plt::AbstractPlot, f::FuncOrFuncs, x; kw...)
@assert !(typeof(x) <: FuncOrFuncs) # otherwise we'd hit infinite recursion here
build_series_args(plt, x, f; kw...)
end
# special handling... xmin/xmax with function(s)
function build_series_args(plt::AbstractPlot, f::FuncOrFuncs, xmin::Real, xmax::Real; kw...)
width = get(plt.plotargs, :size, (100,))[1]
x = collect(linspace(xmin, xmax, width)) # we don't need more than the width
build_series_args(plt, x, f; kw...)
end
mapFuncOrFuncs(f::Function, u::AVec) = map(f, u)
mapFuncOrFuncs(fs::AVec{Function}, u::AVec) = [map(f, u) for f in fs]
# special handling... xmin/xmax with parametric function(s)
build_series_args{T<:Real}(plt::AbstractPlot, fx::FuncOrFuncs, fy::FuncOrFuncs, u::AVec{T}; kw...) = build_series_args(plt, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u); kw...)
build_series_args{T<:Real}(plt::AbstractPlot, u::AVec{T}, fx::FuncOrFuncs, fy::FuncOrFuncs; kw...) = build_series_args(plt, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u); kw...)
build_series_args(plt::AbstractPlot, fx::FuncOrFuncs, fy::FuncOrFuncs, umin::Real, umax::Real, numPoints::Int = 1000; kw...) = build_series_args(plt, fx, fy, linspace(umin, umax, numPoints); kw...)
# special handling... 3D parametric function(s)
build_series_args{T<:Real}(plt::AbstractPlot, fx::FuncOrFuncs, fy::FuncOrFuncs, fz::FuncOrFuncs, u::AVec{T}; kw...) = build_series_args(plt, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u), mapFuncOrFuncs(fz, u); kw...)
build_series_args{T<:Real}(plt::AbstractPlot, u::AVec{T}, fx::FuncOrFuncs, fy::FuncOrFuncs, fz::FuncOrFuncs; kw...) = build_series_args(plt, mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u), mapFuncOrFuncs(fz, u); kw...)
build_series_args(plt::AbstractPlot, fx::FuncOrFuncs, fy::FuncOrFuncs, fz::FuncOrFuncs, umin::Real, umax::Real, numPoints::Int = 1000; kw...) = build_series_args(plt, fx, fy, fz, linspace(umin, umax, numPoints); kw...)
# (x,y) tuples
function build_series_args{R1<:Real,R2<:Real}(plt::AbstractPlot, xy::AVec{Tuple{R1,R2}}; kw...)
build_series_args(plt, unzip(xy)...; kw...)
end
function build_series_args{R1<:Real,R2<:Real}(plt::AbstractPlot, xy::Tuple{R1,R2}; kw...)
build_series_args(plt, [xy[1]], [xy[2]]; kw...)
end
# special handling... no args... 1 series
function build_series_args(plt::AbstractPlot; kw...)
d = Dict(kw)
if !haskey(d, :y)
# assume we just want to create an empty plot object which can be added to later
return [], nothing, nothing
# error("Called plot/subplot without args... must set y in the keyword args. Example: plot(; y=rand(10))")
end
if haskey(d, :x)
return build_series_args(plt, d[:x], d[:y]; kw...)
else
return build_series_args(plt, d[:y]; kw...)
end
end
# --------------------------------------------------------------------
unzip{T}(x::AVec{FixedSizeArrays.Vec{2,T}}) = T[xi[1] for xi in x], T[xi[2] for xi in x]
unzip{T}(x::FixedSizeArrays.Vec{2,T}) = T[x[1]], T[x[2]]
function build_series_args{T<:Real}(plt::AbstractPlot, xy::AVec{FixedSizeArrays.Vec{2,T}}; kw...)
build_series_args(plt, unzip(xy)...; kw...)
end
function build_series_args{T<:Real}(plt::AbstractPlot, xy::FixedSizeArrays.Vec{2,T}; kw...)
build_series_args(plt, [xy[1]], [xy[2]]; kw...)
end
# --------------------------------------------------------------------
# For DataFrame support. Imports DataFrames and defines the necessary methods which support them.
function setup_dataframes()
@require DataFrames begin
function build_series_args(plt::AbstractPlot, df::DataFrames.AbstractDataFrame, args...; kw...)
build_series_args(plt, args...; kw..., dataframe = df)
end
# expecting the column name of a dataframe that was passed in... anything else should error
function extractGroupArgs(s::Symbol, df::DataFrames.AbstractDataFrame, args...)
if haskey(df, s)
return extractGroupArgs(df[s])
else
error("Got a symbol, and expected that to be a key in d[:dataframe]. s=$s d=$d")
end
end
function getDataFrameFromKW(d::Dict)
get(d, :dataframe) do
error("Missing dataframe argument!")
end
end
# the conversion functions for when we pass symbols or vectors of symbols to reference dataframes
convertToAnyVector(s::Symbol, d::Dict) = Any[getDataFrameFromKW(d)[s]], s
convertToAnyVector(v::AVec{Symbol}, d::Dict) = (df = getDataFrameFromKW(d); Any[df[s] for s in v]), v
end
end

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@ -210,7 +210,7 @@ function subplot!(subplt::Subplot, args...; kw...)
end end
kwList, xmeta, ymeta = createKWargsList(subplt, groupargs..., args...; d...) kwList, xmeta, ymeta = build_series_args(subplt, groupargs..., args...; d...)
# TODO: something useful with meta info? # TODO: something useful with meta info?

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@ -4,6 +4,8 @@ Colors
Reexport Reexport
Requires Requires
FactCheck FactCheck
Cairo
Fontconfig
Gadfly Gadfly
Images Images
ImageMagick ImageMagick