Merge 42a07e172194efea63478f56aefa4f7bcba66a65 into 84406f0823132acfb109251295d2ab6e0d803675
This commit is contained in:
Michael Krabbe Borregaard
GitHub
commit
84a7f1f023
13
src/Plots.jl
13
src/Plots.jl
@ -106,6 +106,19 @@ export
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# ---------------------------------------------------------
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import NaNMath
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# define functions (e.g. `_extrema`, that ignores NaNs, when the type is applicable. To overcome the destructive effects of https://github.com/JuliaLang/julia/pull/12563
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for fun in (:extrema, :minimum, :maximum)
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@eval $(Symbol(string("_",fun))){F<:AbstractFloat}(x::AbstractArray{F}) = NaNMath.$(fun)(x)
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@eval $(Symbol(string("_",fun)))(x) = Base.$(fun)(x)
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end
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for fun in (:min, :max)
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@eval $(Symbol(string("_",fun))){F<:AbstractFloat}(x::F, y::F) = NaNMath.$(fun)(x)
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@eval $(Symbol(string("_",fun)))(x...) = Base.$(fun)(x...)
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end
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# ---------------------------------------------------------
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import Measures
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import Measures: Length, AbsoluteLength, Measure, BoundingBox, mm, cm, inch, pt, width, height, w, h
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const BBox = Measures.Absolute2DBox
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22
src/axes.jl
22
src/axes.jl
@ -118,7 +118,7 @@ Base.show(io::IO, axis::Axis) = dumpdict(axis.d, "Axis", true)
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# Base.getindex(axis::Axis, k::Symbol) = getindex(axis.d, k)
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Base.setindex!(axis::Axis, v, ks::Symbol...) = setindex!(axis.d, v, ks...)
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Base.haskey(axis::Axis, k::Symbol) = haskey(axis.d, k)
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Base.extrema(axis::Axis) = (ex = axis[:extrema]; (ex.emin, ex.emax))
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_extrema(axis::Axis) = (ex = axis[:extrema]; (ex.emin, ex.emax))
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const _scale_funcs = Dict{Symbol,Function}(
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@ -260,8 +260,8 @@ end
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function expand_extrema!(ex::Extrema, v::Number)
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ex.emin = min(v, ex.emin)
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ex.emax = max(v, ex.emax)
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ex.emin = _min(v, ex.emin)
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ex.emax = _max(v, ex.emax)
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ex
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end
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@ -276,8 +276,8 @@ expand_extrema!(axis::Axis, ::Bool) = axis[:extrema]
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function expand_extrema!{MIN<:Number,MAX<:Number}(axis::Axis, v::Tuple{MIN,MAX})
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ex = axis[:extrema]
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ex.emin = min(v[1], ex.emin)
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ex.emax = max(v[2], ex.emax)
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ex.emin = _min(v[1], ex.emin)
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ex.emax = _max(v[2], ex.emax)
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ex
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end
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function expand_extrema!{N<:Number}(axis::Axis, v::AVec{N})
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@ -349,11 +349,11 @@ function expand_extrema!(sp::Subplot, d::KW)
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bw = d[:bar_width]
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if bw == nothing
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bw = d[:bar_width] = mean(diff(data))
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bw = d[:bar_width] = _mean(diff(data))
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end
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axis = sp.attr[Symbol(dsym, :axis)]
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expand_extrema!(axis, maximum(data) + 0.5maximum(bw))
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expand_extrema!(axis, minimum(data) - 0.5minimum(bw))
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expand_extrema!(axis, _maximum(data) + 0.5_maximum(bw))
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expand_extrema!(axis, _minimum(data) - 0.5_minimum(bw))
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end
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end
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@ -368,8 +368,8 @@ end
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# push the limits out slightly
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function widen(lmin, lmax)
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span = lmax - lmin
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# eps = max(1e-16, min(1e-2span, 1e-10))
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eps = max(1e-16, 0.03span)
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# eps = _max(1e-16, min(1e-2span, 1e-10))
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eps = _max(1e-16, 0.03span)
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lmin-eps, lmax+eps
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end
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@ -425,7 +425,7 @@ function discrete_value!(axis::Axis, dv)
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# @show axis[:discrete_map], axis[:discrete_values], dv
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if cv_idx == -1
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ex = axis[:extrema]
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cv = max(0.5, ex.emax + 1.0)
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cv = _max(0.5, ex.emax + 1.0)
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expand_extrema!(axis, cv)
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push!(axis[:discrete_values], dv)
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push!(axis[:continuous_values], cv)
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@ -75,7 +75,7 @@ function tick_padding(axis::Axis)
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vals, labs = ticks
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isempty(labs) && return 0mm
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# ptsz = axis[:tickfont].pointsize * pt
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longest_label = maximum(length(lab) for lab in labs)
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longest_label = _maximum(length(lab) for lab in labs)
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# generalize by "rotating" y labels
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rot = axis[:rotation] + (axis[:letter] == :y ? 90 : 0)
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@ -175,7 +175,7 @@ end
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function gl_marker(shape::Shape)
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points = Point2f0[Vec{2,Float32}(p) for p in zip(shape.x, shape.y)]
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bb = GeometryTypes.AABB(points)
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mini, maxi = minimum(bb), maximum(bb)
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mini, maxi = _minimum(bb), _maximum(bb)
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w3 = maxi-mini
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origin, width = Point2f0(mini[1], mini[2]), Point2f0(w3[1], w3[2])
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map!(p -> ((p - origin) ./ width) - 0.5f0, points) # normalize and center
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@ -304,7 +304,7 @@ function extract_any_color(d, kw_args)
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kw_args[:color_norm] = Vec2f0(clims)
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end
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elseif clims == :auto
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kw_args[:color_norm] = Vec2f0(extrema(d[:y]))
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kw_args[:color_norm] = Vec2f0(_extrema(d[:y]))
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end
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end
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else
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@ -315,7 +315,7 @@ function extract_any_color(d, kw_args)
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kw_args[:color_norm] = Vec2f0(clims)
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end
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elseif clims == :auto
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kw_args[:color_norm] = Vec2f0(extrema(d[:y]))
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kw_args[:color_norm] = Vec2f0(_extrema(d[:y]))
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else
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error("Unsupported limits: $clims")
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end
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@ -367,14 +367,14 @@ end
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dist(a, b) = abs(a-b)
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mindist(x, a, b) = min(dist(a, x), dist(b, x))
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mindist(x, a, b) = _min(dist(a, x), dist(b, x))
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function gappy(x, ps)
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n = length(ps)
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x <= first(ps) && return first(ps) - x
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for j=1:(n-1)
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p0 = ps[j]
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p1 = ps[min(j+1, n)]
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p1 = ps[_min(j+1, n)]
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if p0 <= x && p1 >= x
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return mindist(x, p0, p1) * (isodd(j) ? 1 : -1)
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end
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@ -470,7 +470,7 @@ function hover(to_hover, to_display, window)
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end
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GLVisualize._view(robj, popup, camera = cam)
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bb = GLAbstraction.boundingbox(robj).value
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mini = minimum(bb)
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mini = _minimum(bb)
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w = GeometryTypes.widths(bb)
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wborder = w * 0.08f0 #8 percent border
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bb = GeometryTypes.AABB{Float32}(mini - wborder, w + 2 * wborder)
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@ -482,7 +482,7 @@ function hover(to_hover, to_display, window)
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end
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function extract_extrema(d, kw_args)
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xmin, xmax = extrema(d[:x]); ymin, ymax = extrema(d[:y])
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xmin, xmax = _extrema(d[:x]); ymin, ymax = _extrema(d[:y])
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kw_args[:primitive] = GeometryTypes.SimpleRectangle{Float32}(xmin, ymin, xmax-xmin, ymax-ymin)
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nothing
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end
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@ -509,7 +509,7 @@ function extract_colornorm(d, kw_args)
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else
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d[:y]
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end
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kw_args[:color_norm] = Vec2f0(extrema(z))
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kw_args[:color_norm] = Vec2f0(_extrema(z))
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kw_args[:intensity] = map(Float32, collect(z))
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end
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end
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@ -781,7 +781,7 @@ function gl_bar(d, kw_args)
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# compute half-width of bars
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bw = nothing
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hw = if bw == nothing
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mean(diff(x))
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_mean(diff(x))
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else
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Float64[cycle(bw,i)*0.5 for i=1:length(x)]
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end
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@ -864,7 +864,7 @@ function gl_boxplot(d, kw_args)
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end
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# change q1 and q5 to show outliers
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# using maximum and minimum values inside the limits
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q1, q5 = extrema(inside)
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q1, q5 = _extrema(inside)
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end
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# Box
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if notch
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@ -1318,7 +1318,7 @@ function gl_contour(x, y, z, kw_args)
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T = eltype(z)
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levels = Contour.contours(map(T, x), map(T, y), z, h)
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result = Point2f0[]
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zmin, zmax = get(kw_args, :limits, Vec2f0(extrema(z)))
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zmin, zmax = get(kw_args, :limits, Vec2f0(_extrema(z)))
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cmap = get(kw_args, :color_map, get(kw_args, :color, RGBA{Float32}(0,0,0,1)))
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colors = RGBA{Float32}[]
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for c in levels.contours
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@ -1339,7 +1339,7 @@ end
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function gl_heatmap(x,y,z, kw_args)
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get!(kw_args, :color_norm, Vec2f0(extrema(z)))
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get!(kw_args, :color_norm, Vec2f0(_extrema(z)))
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get!(kw_args, :color_map, Plots.make_gradient(cgrad()))
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delete!(kw_args, :intensity)
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I = GLVisualize.Intensity{1, Float32}
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@ -1382,7 +1382,7 @@ function label_scatter(d, w, ho)
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if isapprox(bbw[3], 0)
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bbw = Vec3f0(bbw[1], bbw[2], 1)
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end
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mini = minimum(bb)
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mini = _minimum(bb)
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m = GLAbstraction.translationmatrix(-mini)
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m *= GLAbstraction.scalematrix(1 ./ bbw)
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kw[:primitive] = m * p
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@ -264,7 +264,7 @@ end
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normalize_zvals(zv::Void) = zv
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function normalize_zvals(zv::AVec)
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vmin, vmax = extrema(zv)
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vmin, vmax = _extrema(zv)
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if vmin == vmax
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zeros(length(zv))
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else
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@ -341,7 +341,7 @@ end
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function gr_set_line(lw, style, c) #, a)
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GR.setlinetype(gr_linetype[style])
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w, h = gr_plot_size
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GR.setlinewidth(max(0, lw / ((w + h) * 0.001)))
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GR.setlinewidth(_max(0, lw / ((w + h) * 0.001)))
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gr_set_linecolor(c) #, a)
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end
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@ -394,7 +394,7 @@ function gr_viewport_from_bbox(sp::Subplot{GRBackend}, bb::BoundingBox, w, h, vi
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viewport[4] = viewport_canvas[4] * (1.0 - top(bb) / h)
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if is3d(sp)
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vp = viewport[:]
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extent = min(vp[2] - vp[1], vp[4] - vp[3])
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extent = _min(vp[2] - vp[1], vp[4] - vp[3])
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viewport[1] = 0.5 * (vp[1] + vp[2] - extent)
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viewport[2] = 0.5 * (vp[1] + vp[2] + extent)
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viewport[3] = 0.5 * (vp[3] + vp[4] - extent)
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@ -428,7 +428,7 @@ function gr_set_viewport_polar()
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ymax -= 0.05 * (xmax - xmin)
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xcenter = 0.5 * (xmin + xmax)
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ycenter = 0.5 * (ymin + ymax)
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r = 0.5 * min(xmax - xmin, ymax - ymin)
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r = 0.5 * _min(xmax - xmin, ymax - ymin)
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GR.setviewport(xcenter -r, xcenter + r, ycenter - r, ycenter + r)
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GR.setwindow(-1, 1, -1, 1)
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r
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@ -639,7 +639,7 @@ function gr_display(sp::Subplot{GRBackend}, w, h, viewport_canvas)
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elseif ispolar(sp)
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r = gr_set_viewport_polar()
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rmin, rmax = GR.adjustrange(minimum(r), maximum(r))
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rmin, rmax = GR.adjustrange(_minimum(r), _maximum(r))
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# rmin, rmax = axis_limits(sp[:yaxis])
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gr_polaraxes(rmin, rmax)
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@ -824,7 +824,7 @@ function gr_display(sp::Subplot{GRBackend}, w, h, viewport_canvas)
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# create the colorbar of contour levels
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if sp[:colorbar] != :none
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gr_set_viewport_cmap(sp)
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l = round(Int32, 1000 + (h - minimum(h)) / (maximum(h) - minimum(h)) * 255)
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l = round(Int32, 1000 + (h - _minimum(h)) / (_maximum(h) - _minimum(h)) * 255)
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GR.setwindow(xmin, xmax, zmin, zmax)
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GR.cellarray(xmin, xmax, zmax, zmin, 1, length(l), l)
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ztick = 0.5 * GR.tick(zmin, zmax)
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@ -349,7 +349,7 @@ function _inspectdr_setupsubplot(sp::Subplot{InspectDRBackend})
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ymin, ymax = axis_limits(yaxis)
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if ispolar(sp)
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#Plots.jl appears to give (xmin,xmax) ≜ (Θmin,Θmax) & (ymin,ymax) ≜ (rmin,rmax)
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rmax = max(abs(ymin), abs(ymax))
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rmax = _max(abs(ymin), abs(ymax))
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xmin, xmax = -rmax, rmax
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ymin, ymax = -rmax, rmax
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end
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@ -546,7 +546,7 @@ function plotly_series(plt::Plot, series::Series)
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else
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# grad = ColorGradient(series[:markercolor], alpha=series[:markeralpha])
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grad = as_gradient(series[:markercolor], series[:markeralpha])
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zmin, zmax = extrema(series[:marker_z])
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zmin, zmax = _extrema(series[:marker_z])
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zrange = zmax == zmin ? 1 : zmax - zmin # if all marker_z values are the same, plot all markers same color (avoids division by zero in next line)
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[rgba_string(grad[(zi - zmin) / zrange]) for zi in series[:marker_z]]
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end
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@ -705,11 +705,11 @@ function py_add_series(plt::Plot{PyPlotBackend}, series::Series)
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# contours on the axis planes
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if series[:contours]
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for (zdir,mat) in (("x",x), ("y",y), ("z",z))
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offset = (zdir == "y" ? maximum : minimum)(mat)
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offset = (zdir == "y" ? _maximum : _minimum)(mat)
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handle = ax[:contourf](x, y, z, levelargs...;
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zdir = zdir,
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cmap = py_fillcolormap(series),
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offset = (zdir == "y" ? maximum : minimum)(mat) # where to draw the contour plane
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offset = (zdir == "y" ? _maximum : _minimum)(mat) # where to draw the contour plane
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)
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push!(handles, handle)
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needs_colorbar = true
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@ -778,7 +778,7 @@ function py_add_series(plt::Plot{PyPlotBackend}, series::Series)
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end
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clims = sp[:clims]
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zmin, zmax = extrema(z)
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zmin, zmax = _extrema(z)
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extrakw[:vmin] = (is_2tuple(clims) && isfinite(clims[1])) ? clims[1] : zmin
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extrakw[:vmax] = (is_2tuple(clims) && isfinite(clims[2])) ? clims[2] : zmax
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@ -926,14 +926,14 @@ function py_compute_axis_minval(axis::Axis)
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for series in series_list(sp)
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v = series.d[axis[:letter]]
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if !isempty(v)
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minval = min(minval, minimum(abs(v)))
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minval = _min(minval, _minimum(abs(v)))
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end
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end
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end
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# now if the axis limits go to a smaller abs value, use that instead
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vmin, vmax = axis_limits(axis)
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minval = min(minval, abs(vmin), abs(vmax))
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minval = _min(minval, abs(vmin), abs(vmax))
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minval
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end
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@ -954,7 +954,7 @@ function py_set_scale(ax, axis::Axis)
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elseif scale == :log10
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10
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end
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kw[Symbol(:linthresh,letter)] = max(1e-16, py_compute_axis_minval(axis))
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kw[Symbol(:linthresh,letter)] = _max(1e-16, py_compute_axis_minval(axis))
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"symlog"
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end
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func(arg; kw...)
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@ -1096,10 +1096,10 @@ function _update_min_padding!(sp::Subplot{PyPlotBackend})
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bottompad = 0mm
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for bb in (py_bbox_axis(ax, "x"), py_bbox_axis(ax, "y"), py_bbox_title(ax))
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if ispositive(width(bb)) && ispositive(height(bb))
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leftpad = max(leftpad, left(plotbb) - left(bb))
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toppad = max(toppad, top(plotbb) - top(bb))
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rightpad = max(rightpad, right(bb) - right(plotbb))
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bottompad = max(bottompad, bottom(bb) - bottom(plotbb))
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leftpad = _max(leftpad, left(plotbb) - left(bb))
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toppad = _max(toppad, top(plotbb) - top(bb))
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rightpad = _max(rightpad, right(bb) - right(plotbb))
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bottompad = _max(bottompad, bottom(bb) - bottom(plotbb))
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end
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end
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@ -501,7 +501,7 @@ immutable ZValues
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zrange::Tuple{Float64,Float64}
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end
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function zvalues{T<:Real}(values::AVec{T}, zrange::Tuple{T,T} = (minimum(values), maximum(values)))
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function zvalues{T<:Real}(values::AVec{T}, zrange::Tuple{T,T} = (_minimum(values), _maximum(values)))
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ZValues(collect(float(values)), map(Float64, zrange))
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end
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@ -645,8 +645,8 @@ function (bc::BezierCurve)(t::Real)
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p
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end
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Base.mean(x::Real, y::Real) = 0.5*(x+y)
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Base.mean{N,T<:Real}(ps::FixedSizeArrays.Vec{N,T}...) = sum(ps) / length(ps)
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_mean(x::Real, y::Real) = 0.5*(x+y)
|
||||
_mean{N,T<:Real}(ps::FixedSizeArrays.Vec{N,T}...) = sum(ps) / length(ps)
|
||||
|
||||
@deprecate curve_points coords
|
||||
|
||||
@ -659,7 +659,7 @@ function directed_curve(args...; kw...)
|
||||
end
|
||||
|
||||
function extrema_plus_buffer(v, buffmult = 0.2)
|
||||
vmin,vmax = extrema(v)
|
||||
vmin,vmax = _extrema(v)
|
||||
vdiff = vmax-vmin
|
||||
buffer = vdiff * buffmult
|
||||
vmin - buffer, vmax + buffer
|
||||
|
||||
@ -55,10 +55,10 @@ function Base.:+(bb1::BoundingBox, bb2::BoundingBox)
|
||||
ispositive(width(bb2)) || return bb1
|
||||
ispositive(height(bb2)) || return bb1
|
||||
|
||||
l = min(left(bb1), left(bb2))
|
||||
t = min(top(bb1), top(bb2))
|
||||
r = max(right(bb1), right(bb2))
|
||||
b = max(bottom(bb1), bottom(bb2))
|
||||
l = _min(left(bb1), left(bb2))
|
||||
t = _min(top(bb1), top(bb2))
|
||||
r = _max(right(bb1), right(bb2))
|
||||
b = _max(bottom(bb1), bottom(bb2))
|
||||
BoundingBox(l, t, r-l, b-t)
|
||||
end
|
||||
|
||||
@ -642,7 +642,7 @@ end
|
||||
|
||||
function create_grid_vcat(expr::Expr)
|
||||
rowsizes = map(rowsize, expr.args)
|
||||
rmin, rmax = extrema(rowsizes)
|
||||
rmin, rmax = _extrema(rowsizes)
|
||||
if rmin > 0 && rmin == rmax
|
||||
# we have a grid... build the whole thing
|
||||
# note: rmin is the number of columns
|
||||
@ -704,7 +704,7 @@ function link_axes!(axes::Axis...)
|
||||
a1 = axes[1]
|
||||
for i=2:length(axes)
|
||||
a2 = axes[i]
|
||||
expand_extrema!(a1, extrema(a2))
|
||||
expand_extrema!(a1, _extrema(a2))
|
||||
for k in (:extrema, :discrete_values, :continuous_values, :discrete_map)
|
||||
a2[k] = a1[k]
|
||||
end
|
||||
|
||||
@ -153,7 +153,7 @@ function _add_smooth_kw(kw_list::Vector{KW}, kw::KW)
|
||||
if get(kw, :smooth, false)
|
||||
x, y = kw[:x], kw[:y]
|
||||
β, α = convert(Matrix{Float64}, [x ones(length(x))]) \ convert(Vector{Float64}, y)
|
||||
sx = [minimum(x), maximum(x)]
|
||||
sx = [_minimum(x), _maximum(x)]
|
||||
sy = β * sx + α
|
||||
push!(kw_list, merge(copy(kw), KW(
|
||||
:seriestype => :path,
|
||||
|
||||
@ -225,7 +225,7 @@ end
|
||||
fr = if yaxis[:scale] == :identity
|
||||
0.0
|
||||
else
|
||||
min(axis_limits(yaxis)[1], minimum(y))
|
||||
_min(axis_limits(yaxis)[1], _minimum(y))
|
||||
end
|
||||
end
|
||||
newx, newy = zeros(3n), zeros(3n)
|
||||
@ -338,7 +338,7 @@ end
|
||||
# compute half-width of bars
|
||||
bw = d[:bar_width]
|
||||
hw = if bw == nothing
|
||||
0.5mean(diff(procx))
|
||||
0.5_mean(diff(procx))
|
||||
else
|
||||
Float64[0.5cycle(bw,i) for i=1:length(procx)]
|
||||
end
|
||||
@ -366,7 +366,7 @@ end
|
||||
end
|
||||
|
||||
# widen limits out a bit
|
||||
expand_extrema!(axis, widen(extrema(xseg.pts)...))
|
||||
expand_extrema!(axis, widen(_extrema(xseg.pts)...))
|
||||
|
||||
# switch back
|
||||
if !isvertical(d)
|
||||
@ -414,8 +414,8 @@ end
|
||||
|
||||
function _preprocess_binbarlike_weights{T<:AbstractFloat}(::Type{T}, w, wscale::Symbol)
|
||||
w_adj = _scale_adjusted_values(T, w, wscale)
|
||||
w_min = minimum(w_adj)
|
||||
w_max = maximum(w_adj)
|
||||
w_min = _minimum(w_adj)
|
||||
w_max = _maximum(w_adj)
|
||||
baseline = _binbarlike_baseline(w_min, wscale)
|
||||
w_adj, baseline
|
||||
end
|
||||
@ -548,9 +548,9 @@ Plots.@deps stepbins path
|
||||
|
||||
|
||||
function _auto_binning_nbins{N}(vs::NTuple{N,AbstractVector}, dim::Integer; mode::Symbol = :auto)
|
||||
_cl(x) = max(ceil(Int, x), 1)
|
||||
_cl(x) = _max(ceil(Int, x), 1)
|
||||
_iqr(v) = quantile(v, 0.75) - quantile(v, 0.25)
|
||||
_span(v) = maximum(v) - minimum(v)
|
||||
_span(v) = _maximum(v) - _minimum(v)
|
||||
|
||||
n_samples = length(linearindices(first(vs)))
|
||||
# Estimator for number of samples in one row/column of bins along each axis:
|
||||
@ -919,7 +919,7 @@ end
|
||||
|
||||
# get the joined vector
|
||||
function get_xy(v::AVec{OHLC}, x = 1:length(v))
|
||||
xdiff = 0.3mean(abs(diff(x)))
|
||||
xdiff = 0.3_mean(abs(diff(x)))
|
||||
x_out, y_out = zeros(0), zeros(0)
|
||||
for (i,ohlc) in enumerate(v)
|
||||
ox,oy = get_xy(ohlc, x[i], xdiff)
|
||||
@ -984,8 +984,8 @@ end
|
||||
yflip := true
|
||||
aspect_ratio := 1
|
||||
rs, cs, zs = findnz(z.surf)
|
||||
xlim := extrema(cs)
|
||||
ylim := extrema(rs)
|
||||
xlim := _extrema(cs)
|
||||
ylim := _extrema(rs)
|
||||
if d[:markershape] == :none
|
||||
markershape := :circle
|
||||
end
|
||||
@ -1006,7 +1006,7 @@ end
|
||||
|
||||
"Adds a+bx... straight line over the current plot"
|
||||
function abline!(plt::Plot, a, b; kw...)
|
||||
plot!(plt, [extrema(plt)...], x -> b + a*x; kw...)
|
||||
plot!(plt, [_extrema(plt)...], x -> b + a*x; kw...)
|
||||
end
|
||||
|
||||
abline!(args...; kw...) = abline!(current(), args...; kw...)
|
||||
|
||||
34
src/utils.jl
34
src/utils.jl
@ -3,10 +3,10 @@ calcMidpoints(edges::AbstractVector) = Float64[0.5 * (edges[i] + edges[i+1]) for
|
||||
|
||||
"Make histogram-like bins of data"
|
||||
function binData(data, nbins)
|
||||
lo, hi = extrema(data)
|
||||
lo, hi = _extrema(data)
|
||||
edges = collect(linspace(lo, hi, nbins+1))
|
||||
midpoints = calcMidpoints(edges)
|
||||
buckets = Int[max(2, min(searchsortedfirst(edges, x), length(edges)))-1 for x in data]
|
||||
buckets = Int[_max(2, _min(searchsortedfirst(edges, x), length(edges)))-1 for x in data]
|
||||
counts = zeros(Int, length(midpoints))
|
||||
for b in buckets
|
||||
counts[b] += 1
|
||||
@ -109,7 +109,7 @@ function regressionXY(x, y)
|
||||
β, α = convert(Matrix{Float64}, [x ones(length(x))]) \ convert(Vector{Float64}, y)
|
||||
|
||||
# make a line segment
|
||||
regx = [minimum(x), maximum(x)]
|
||||
regx = [_minimum(x), _maximum(x)]
|
||||
regy = β * regx + α
|
||||
regx, regy
|
||||
end
|
||||
@ -187,7 +187,7 @@ type SegmentsIterator
|
||||
end
|
||||
function iter_segments(args...)
|
||||
tup = Plots.wraptuple(args)
|
||||
n = maximum(map(length, tup))
|
||||
n = _maximum(map(length, tup))
|
||||
SegmentsIterator(tup, n)
|
||||
end
|
||||
|
||||
@ -283,9 +283,9 @@ unzip{T}(xyuv::FixedSizeArrays.Vec{4,T}) = T[xyuv[1]], T[xyuv[2]], T[xyuv[
|
||||
# given 2-element lims and a vector of data x, widen lims to account for the extrema of x
|
||||
function _expand_limits(lims, x)
|
||||
try
|
||||
e1, e2 = extrema(x)
|
||||
lims[1] = min(lims[1], e1)
|
||||
lims[2] = max(lims[2], e2)
|
||||
e1, e2 = _extrema(x)
|
||||
lims[1] = _min(lims[1], e1)
|
||||
lims[2] = _max(lims[2], e2)
|
||||
# catch err
|
||||
# warn(err)
|
||||
end
|
||||
@ -334,17 +334,17 @@ sortedkeys(d::Dict) = sort(collect(keys(d)))
|
||||
|
||||
"create an (n+1) list of the outsides of heatmap rectangles"
|
||||
function heatmap_edges(v::AVec)
|
||||
vmin, vmax = extrema(v)
|
||||
vmin, vmax = _extrema(v)
|
||||
extra = 0.5 * (vmax-vmin) / (length(v)-1)
|
||||
vcat(vmin-extra, 0.5 * (v[1:end-1] + v[2:end]), vmax+extra)
|
||||
end
|
||||
|
||||
|
||||
function calc_r_extrema(x, y)
|
||||
xmin, xmax = extrema(x)
|
||||
ymin, ymax = extrema(y)
|
||||
r = 0.5 * min(xmax - xmin, ymax - ymin)
|
||||
extrema(r)
|
||||
xmin, xmax = _extrema(x)
|
||||
ymin, ymax = _extrema(y)
|
||||
r = 0.5 * _min(xmax - xmin, ymax - ymin)
|
||||
_extrema(r)
|
||||
end
|
||||
|
||||
function convert_to_polar(x, y, r_extrema = calc_r_extrema(x, y))
|
||||
@ -644,8 +644,8 @@ end
|
||||
# ---------------------------------------------------------------
|
||||
# used in updating an existing series
|
||||
|
||||
extendSeriesByOne(v::UnitRange{Int}, n::Int = 1) = isempty(v) ? (1:n) : (minimum(v):maximum(v)+n)
|
||||
extendSeriesByOne(v::AVec, n::Integer = 1) = isempty(v) ? (1:n) : vcat(v, (1:n) + maximum(v))
|
||||
extendSeriesByOne(v::UnitRange{Int}, n::Int = 1) = isempty(v) ? (1:n) : (_minimum(v):_maximum(v)+n)
|
||||
extendSeriesByOne(v::AVec, n::Integer = 1) = isempty(v) ? (1:n) : vcat(v, (1:n) + _maximum(v))
|
||||
extendSeriesData{T}(v::Range{T}, z::Real) = extendSeriesData(float(collect(v)), z)
|
||||
extendSeriesData{T}(v::Range{T}, z::AVec) = extendSeriesData(float(collect(v)), z)
|
||||
extendSeriesData{T}(v::AVec{T}, z::Real) = (push!(v, convert(T, z)); v)
|
||||
@ -871,9 +871,9 @@ mm2px(mm::Real) = float(px / MM_PER_PX)
|
||||
|
||||
|
||||
"Smallest x in plot"
|
||||
xmin(plt::Plot) = minimum([minimum(series.d[:x]) for series in plt.series_list])
|
||||
xmin(plt::Plot) = _minimum([_minimum(series.d[:x]) for series in plt.series_list])
|
||||
"Largest x in plot"
|
||||
xmax(plt::Plot) = maximum([maximum(series.d[:x]) for series in plt.series_list])
|
||||
xmax(plt::Plot) = _maximum([_maximum(series.d[:x]) for series in plt.series_list])
|
||||
|
||||
"Extrema of x-values in plot"
|
||||
Base.extrema(plt::Plot) = (xmin(plt), xmax(plt))
|
||||
_extrema(plt::Plot) = (xmin(plt), xmax(plt))
|
||||
|
||||
@ -78,12 +78,12 @@ facts("Axes") do
|
||||
@fact typeof(axis) --> Plots.Axis
|
||||
@fact Plots.discrete_value!(axis, "HI") --> (0.5, 1)
|
||||
@fact Plots.discrete_value!(axis, :yo) --> (1.5, 2)
|
||||
@fact extrema(axis) --> (0.5,1.5)
|
||||
@fact Plots._extrema(axis) --> (0.5,1.5)
|
||||
@fact axis[:discrete_map] --> Dict{Any,Any}(:yo => 2, "HI" => 1)
|
||||
|
||||
Plots.discrete_value!(axis, ["x$i" for i=1:5])
|
||||
Plots.discrete_value!(axis, ["x$i" for i=0:2])
|
||||
@fact extrema(axis) --> (0.5, 7.5)
|
||||
@fact Plots._extrema(axis) --> (0.5, 7.5)
|
||||
end
|
||||
|
||||
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user