move RecipesBase -> weakdep

Project.toml

@@ -9,7 +9,6 @@ GenericSchur = "c145ed77-6b09-5dd9-b285-bf645a82121e"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
 SLEEFPirates = "476501e8-09a2-5ece-8869-fb82de89a1fa"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
@@ -19,12 +18,14 @@ StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a"
 Measurements = "eff96d63-e80a-5855-80a2-b1b0885c5ab7"
+RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
 Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 
 [extensions]
 ForwardDiffExt = "ForwardDiff"
 MakieExt = "Makie"
 MeasurementsExt = "Measurements"
+RecipesBaseExt = "RecipesBase"
 UnitfulExt = "Unitful"
 
 [compat]

ext/RecipesBaseExt.jl

@@ -0,0 +1,231 @@
+module RecipesBaseExt
+
+using MonteCarloMeasurements
+using MonteCarloMeasurements.Random
+import MonteCarloMeasurements: errorbarplot, ribbonplot, mcplot
+using RecipesBase
+
+
+@recipe function plot(p::AbstractParticles)
+    seriestype --> :histogram
+    @series p.particles
+end
+
+# @recipe f(::Type{<:AbstractParticles}, p::AbstractParticles) = p.particles # Does not seem to be needed
+
+
+const RealOrTuple = Union{Real, Tuple}
+handle_args(y::AbstractVecOrMat{<:AbstractParticles}, q::RealOrTuple=0.025) = 1:size(y,1), y, q
+handle_args(x::AbstractVector, y::AbstractVecOrMat{<:AbstractParticles}, q::RealOrTuple=0.025) = x, y, q
+handle_args(p) = handle_args(p.args...)
+handle_args(args...) = throw(ArgumentError("The plot function should be called with the signature plotfun([x=1:length(y)], y::Vector{Particles}, [q=0.025])"))
+
+function quantiles(y,q::Number)
+    m = vec(pmean.(y))
+    q > 0.5 && (q = 1-q)
+    lower = reshape(-(pquantile.(vec(y),q)-m), size(y))
+    upper = reshape(pquantile.(vec(y),1-q)-m, size(y))
+    lower,upper
+end
+
+function quantiles(y,q)
+    m = vec(pmean.(y))
+    lower = reshape(-(pquantile.(vec(y),q[1])-m), size(y))
+    upper = reshape(pquantile.(vec(y),q[2])-m, size(y))
+    lower,upper
+end
+
+@userplot Errorbarplot
+@recipe function plt(p::Errorbarplot; quantile=nothing)
+    x,y,q = handle_args(p)
+    q = quantile === nothing ? q : quantile
+    m = pmean.(y)
+    label --> "Mean with $q quantile"
+    Q = quantiles(y, q)
+    if y isa AbstractMatrix
+        for c in 1:size(y,2)
+            @series begin
+                yerror := (Q[1][:,c], Q[2][:,c])
+                x,m[:,c]
+            end
+        end
+    else
+        yerror := Q
+        @series x,m
+    end
+end
+
+"This is a helper function to make multiple series into one series separated by `Inf`. This makes plotting vastly more efficient."
+function _to1series(x,y)
+    r,c = size(y)
+    y2 = vec([y; fill(Inf, 1, c)])
+    x2 = repeat([x; Inf], c)
+    x2,y2
+end
+
+_to1series(y) = _to1series(1:size(y,1),y)
+
+@userplot MCplot
+@recipe function plt(p::MCplot; oneseries=true)
+    x,y,q = handle_args(p)
+    to1series = oneseries ? _to1series : (x,y) -> (x,y)
+    N = nparticles(y)
+    selected = q > 1 ? randperm(N)[1:q] : 1:N
+    N = length(selected)
+    label --> ""
+    seriesalpha --> 1/log(N)
+    if y isa AbstractMatrix
+        for c in 1:size(y,2)
+            m = Matrix(y[:,c])'
+            @series to1series(x, m[:, selected])
+        end
+    else
+        m = Matrix(y)'
+        @series to1series(x, m[:, selected])
+    end
+end
+
+@userplot Ribbonplot
+@recipe function plt(p::Ribbonplot; N=false, quantile=nothing, oneseries=true)
+    x,y,q = handle_args(p)
+    q = quantile === nothing ? q : quantile
+    to1series = oneseries ? _to1series : identity
+    if N > 0
+        for col = 1:size(y,2)
+            yc = y[:,col]
+            m = pmean.(yc)
+            @series begin
+                label --> "Mean with $q quantile"
+                ribbon := quantiles(yc, q)
+                x,m
+            end
+            @series begin
+                ribbon := quantiles(yc, q)
+                m
+            end
+            @series begin
+                M = Matrix(yc)
+                np,ny = size(M)
+                primary := false
+                nc = N > 1 ? N : min(np, 50)
+                seriesalpha --> max(1/sqrt(nc), 0.1)
+                chosen = randperm(np)[1:nc]
+                to1series(M[chosen, :]')
+            end
+        end
+    else
+        @series begin
+            label --> "Mean with $q quantile"
+            m = pmean.(y)
+            ribbon := quantiles(y, q)
+            x,m
+        end
+    end
+end
+
+
+@recipe function plt(y::Union{MvParticles,AbstractMatrix{<:AbstractParticles}}, q=0.025; N=true, ri=true, quantile=nothing, oneseries=true)
+    q = quantile === nothing ? q : quantile
+    label --> "Mean with ($q, $(1-q)) quantiles"
+    to1series = oneseries ? _to1series : identity
+    for col = 1:size(y,2)
+        yc = y[:,col]
+        if ri
+            @series begin
+                ribbon := quantiles(yc, q)
+                pmean.(yc)
+            end
+        end
+        if N > 0
+            @series begin
+                M = Matrix(yc)
+                np,ny = size(M)
+                primary := !ri
+                nc = N > 1 ? N : min(np, 50)
+                seriesalpha --> max(1/sqrt(nc), 0.1)
+                chosen = randperm(np)[1:nc]
+                M[chosen, :]'
+                to1series(M[chosen, :]') # We want different columns to look different, but M here represents a single column (Matrix(yc)), so each column in M correspond to the same yc
+            end
+        end
+    end
+end
+
+
+@recipe function plt(func::Function, x::Union{MvParticles,AbstractMatrix{<:AbstractParticles}}, q=0.025; quantile=nothing)
+    y = func.(x)
+    q = quantile === nothing ? q : quantile
+    label --> "Mean with ($q, $(1-q)) quantiles"
+    xerror := quantiles(x, q)
+    yerror := quantiles(y, q)
+    pmean.(x), pmean.(y)
+end
+
+@recipe function plt(x::Union{MvParticles,AbstractMatrix{<:AbstractParticles}}, y::Union{MvParticles,AbstractMatrix{<:AbstractParticles}}, q=0.025; points=false, quantile=nothing)
+    my = pmean.(y)
+    mx = pmean.(x)
+    q = quantile === nothing ? q : quantile
+    if points
+        @series begin
+            seriestype --> :scatter
+            primary := true
+            seriesalpha --> 0.1
+            vec(Matrix(x)), vec(Matrix(y))
+        end
+    else
+        @series begin
+            yerror := quantiles(y, q)
+            xerror := quantiles(x, q)
+            label --> "Mean with $q quantile"
+            mx, my
+        end
+    end
+end
+
+@recipe function plt(x::Union{MvParticles,AbstractMatrix{<:AbstractParticles}}, y::AbstractArray, q=0.025; quantile=nothing)
+    mx = pmean.(x)
+    q = quantile === nothing ? q : quantile
+    lower,upper = quantiles(x, q)
+    xerror := (lower,upper)
+    mx, y
+end
+
+@recipe function plt(x::AbstractArray, y::Union{MvParticles,AbstractMatrix{<:AbstractParticles}}, q=0.025; N=true, ri=true, quantile=nothing, oneseries=true)
+    samedim = size(x) === size(y)
+    # layout --> max(size(x, 2), size(y, 2))
+    q = quantile === nothing ? q : quantile
+    to1series = oneseries ? _to1series : (x,y) -> (x,y)
+    if N > 0
+        for col = 1:size(y,2)
+            yc = y[:,col]
+            if ri
+                @series begin
+                    # seriescolor --> col
+                    # subplot --> col
+                    ribbon := quantiles(yc, q)
+                    label --> "Mean with ($q, $(1-q)) quantiles"
+                    x, pmean.(yc)
+                end
+            end
+            @series begin
+                # seriescolor --> col
+                # subplot --> col
+                M = Matrix(yc)
+                np,ny = size(M)
+                primary := !ri
+                nc = N > 1 ? N : min(np, 50)
+                seriesalpha --> max(1/sqrt(nc), 0.1)
+                chosen = randperm(np)[1:nc]
+                to1series(samedim ? x[:, col] : x, M[chosen, :]')
+            end
+        end
+    else
+        @series begin
+            ribbon := quantiles(y, q)
+            label --> "Mean with ($q, $(1-q)) quantiles"
+            x, pmean.(y)
+        end
+    end
+end
+
+end

src/MonteCarloMeasurements.jl

@@ -38,7 +38,7 @@ Particles{Int64,500}
 For further help, see the [documentation](https://baggepinnen.github.io/MonteCarloMeasurements.jl/stable), the [examples folder](https://github.com/baggepinnen/MonteCarloMeasurements.jl/tree/master/examples) or the [arXiv paper](https://arxiv.org/abs/2001.07625).
 """
 module MonteCarloMeasurements
-using LinearAlgebra, Statistics, Random, StaticArrays, RecipesBase, MacroTools, SLEEFPirates, GenericSchur
+using LinearAlgebra, Statistics, Random, StaticArrays, MacroTools, SLEEFPirates, GenericSchur
 import Base: add_sum
 
 using Distributions, StatsBase