Fix log-scale for 1D bar/bin/histogram series types
This commit is contained in:
Oliver Schulz
parent
1188230641
commit
56a9389023
@ -156,6 +156,8 @@ const _markerAliases = Dict{Symbol,Symbol}(
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)
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const _allScales = [:identity, :ln, :log2, :log10, :asinh, :sqrt]
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const _logScales = [:ln, :log2, :log10]
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const _logScaleBases = Dict(:ln => e, :log2 => 2.0, :log10 => 10.0)
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const _scaleAliases = Dict{Symbol,Symbol}(
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:none => :identity,
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:log => :log10,
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@ -277,6 +277,13 @@ function _subplot_setup(plt::Plot, d::KW, kw_list::Vector{KW})
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attr[Symbol(letter,k)] = v
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end
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end
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for k in (:scale,), letter in (:x,:y,:z)
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# Series recipes may need access to this information
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lk = Symbol(letter,k)
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if haskey(attr, lk)
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kw[lk] = attr[lk]
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end
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end
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end
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sp_attrs[sp] = attr
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end
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149
src/recipes.jl
149
src/recipes.jl
@ -323,10 +323,11 @@ end
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# create a bar plot as a filled step function
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@recipe function f(::Type{Val{:bar}}, x, y, z)
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nx, ny = length(x), length(y)
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procx, procy, xscale, yscale, baseline = _preprocess_binlike(d, x, y)
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nx, ny = length(procx), length(procy)
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axis = d[:subplot][isvertical(d) ? :xaxis : :yaxis]
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cv = [discrete_value!(axis, xi)[1] for xi=x]
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x = if nx == ny
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cv = [discrete_value!(axis, xi)[1] for xi=procx]
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procx = if nx == ny
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cv
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elseif nx == ny + 1
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0.5diff(cv) + cv[1:end-1]
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@ -337,9 +338,9 @@ end
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# compute half-width of bars
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bw = d[:bar_width]
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hw = if bw == nothing
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0.5mean(diff(x))
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0.5mean(diff(procx))
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else
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Float64[0.5cycle(bw,i) for i=1:length(x)]
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Float64[0.5cycle(bw,i) for i=1:length(procx)]
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end
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# make fillto a vector... default fills to 0
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@ -347,16 +348,21 @@ end
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if fillto == nothing
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fillto = 0
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end
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if (yscale in _logScales) && !all(_is_positive, fillto)
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fillto = map(x -> _is_positive(x) ? typeof(baseline)(x) : baseline, fillto)
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end
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# create the bar shapes by adding x/y segments
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xseg, yseg = Segments(), Segments()
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for i=1:ny
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center = x[i]
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hwi = cycle(hw,i)
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yi = y[i]
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fi = cycle(fillto,i)
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push!(xseg, center-hwi, center-hwi, center+hwi, center+hwi, center-hwi)
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push!(yseg, yi, fi, fi, yi, yi)
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yi = procy[i]
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if !isnan(yi)
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center = procx[i]
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hwi = cycle(hw,i)
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fi = cycle(fillto,i)
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push!(xseg, center-hwi, center-hwi, center+hwi, center+hwi, center-hwi)
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push!(yseg, yi, fi, fi, yi, yi)
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end
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end
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# widen limits out a bit
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@ -384,9 +390,51 @@ end
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_bin_centers(v::AVec) = (v[1:end-1] + v[2:end]) / 2
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_is_positive(x) = (x > 0) && !(x ≈ 0)
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_positive_else_nan{T}(::Type{T}, x::Real) = _is_positive(x) ? T(x) : T(NaN)
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function _scale_adjusted_values{T<:AbstractFloat}(::Type{T}, V::AbstractVector, scale::Symbol)
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if scale in _logScales
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[_positive_else_nan(T, x) for x in V]
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else
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[T(x) for x in V]
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end
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end
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function _hist_ylim_lo{T<:Real}(ymin::T, yscale::Symbol)
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if (yscale in _logScales)
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ymin / T(_logScaleBases[yscale]^log10(2))
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else
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zero(T)
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end
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end
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function _hist_ylim_hi{T<:Real}(ymax::T, yscale::Symbol)
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if (yscale in _logScales)
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ymax * T(_logScaleBases[yscale]^log10(2))
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else
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ymax * T(1.1)
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end
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end
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function _preprocess_binlike(d, x, y)
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xscale = get(d, :xscale, :identity)
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yscale = get(d, :yscale, :identity)
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T = float(promote_type(eltype(x), eltype(y)))
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edge = map(T, x)
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weights = _scale_adjusted_values(T, y, yscale)
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w_min = minimum(weights)
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baseline = _hist_ylim_lo(isnan(w_min) ? one(T) : w_min, yscale)
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edge, weights, xscale, yscale, baseline
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end
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@recipe function f(::Type{Val{:barbins}}, x, y, z)
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edge, weights = x, y
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edge, weights, xscale, yscale, baseline = _preprocess_binlike(d, x, y)
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if (d[:bar_width] == nothing)
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bar_width := diff(edge)
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end
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@ -395,11 +443,11 @@ _bin_centers(v::AVec) = (v[1:end-1] + v[2:end]) / 2
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seriestype := :bar
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()
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end
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@deps barbins bins
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@deps barbins bar
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@recipe function f(::Type{Val{:scatterbins}}, x, y, z)
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edge, weights = x, y
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edge, weights, xscale, yscale, baseline = _preprocess_binlike(d, x, y)
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xerror := diff(edge)/2
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x := _bin_centers(edge)
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y := weights
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@ -409,43 +457,65 @@ end
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@deps scatterbins scatter
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function _stepbins_path(edge, weights)
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function _stepbins_path(edge, weights, baseline::Real, xscale::Symbol, yscale::Symbol)
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log_scale_x = xscale in _logScales
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log_scale_y = yscale in _logScales
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nbins = length(linearindices(weights))
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if length(linearindices(edge)) != nbins + 1
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error("Edge vector must be 1 longer than weight vector")
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end
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x = eltype(edge)[]
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y = eltype(weights)[]
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it_e, it_w = start(edge), start(weights)
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px, it_e = next(edge, it_e)
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py = zero(eltype(weights))
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a, it_e = next(edge, it_e)
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last_w = eltype(weights)(NaN)
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i = 1
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while (!done(edge, it_e) && !done(edge, it_e))
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b, it_e = next(edge, it_e)
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w, it_w = next(weights, it_w)
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npathpts = 2 * nbins + 2
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x = Vector{eltype(px)}(npathpts)
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y = Vector{eltype(py)}(npathpts)
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if (log_scale_x && a ≈ 0)
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a = b/_logScaleBases[xscale]^3
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end
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x[1], y[1] = px, py
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i = 2
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while (i < npathpts - 1)
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py, it_w = next(weights, it_w)
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x[i], y[i] = px, py
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i += 1
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px, it_e = next(edge, it_e)
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x[i], y[i] = px, py
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i += 1
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if isnan(w)
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if !isnan(last_w)
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push!(x, a)
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push!(y, baseline)
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end
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else
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if isnan(last_w)
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push!(x, a)
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push!(y, baseline)
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end
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push!(x, a)
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push!(y, w)
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push!(x, b)
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push!(y, w)
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end
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a = b
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last_w = w
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end
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if (last_w != baseline)
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push!(x, a)
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push!(y, baseline)
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end
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assert(i == npathpts)
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x[end], y[end] = px, zero(py)
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(x, y)
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end
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@recipe function f(::Type{Val{:stepbins}}, x, y, z)
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edge, weights = x, y
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@recipe function f(::Type{Val{:stepbins}}, x, y, z)
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axis = d[:subplot][Plots.isvertical(d) ? :xaxis : :yaxis]
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xpts, ypts = _stepbins_path(edge, weights)
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if !Plots.isvertical(d)
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edge, weights, xscale, yscale, baseline = _preprocess_binlike(d, x, y)
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xpts, ypts = _stepbins_path(edge, weights, baseline, xscale, yscale)
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if !isvertical(d)
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xpts, ypts = ypts, xpts
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end
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@ -453,7 +523,7 @@ end
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if d[:markershape] != :none
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@series begin
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seriestype := :scatter
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x := Plots._bin_centers(edge)
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x := _bin_centers(edge)
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y := weights
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fillrange := nothing
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label := ""
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@ -468,7 +538,8 @@ end
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x := xpts
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y := ypts
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seriestype := :path
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ylims --> [0, 1.1 * maximum(weights)]
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ylims --> [baseline, _hist_ylim_hi(maximum(weights), yscale)]
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()
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end
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Plots.@deps stepbins path
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@ -568,9 +639,11 @@ end
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if d[:seriestype] == :scatterbins
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# Workaround, error bars currently not set correctly by scatterbins
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edge, weights, xscale, yscale, baseline = _preprocess_binlike(d, h.edges[1], h.weights)
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info("xscale = $xscale, yscale = $yscale")
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xerror --> diff(h.edges[1])/2
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seriestype := :scatter
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(Plots._bin_centers(h.edges[1]), h.weights)
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(Plots._bin_centers(edge), weights)
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else
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(h.edges[1], h.weights)
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end
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