diff --git a/src/Plots.jl b/src/Plots.jl index e1ccbfa6..319a64a2 100644 --- a/src/Plots.jl +++ b/src/Plots.jl @@ -10,7 +10,6 @@ using Base.Meta @reexport using PlotThemes import Showoff import StatsBase -import NaNMath: extrema, maximum, minimum export grid, @@ -107,6 +106,15 @@ export # --------------------------------------------------------- +import NaNMath +# define functions (e.g. `_extrema`, that uses the NaNMath version (which ignores NaNs)) when the type is applicable +for fun in (:extrema, :minimum, :maximum, :mean) + @eval $(Symbol(string("_",fun)))(x) = Base.$(fun)(x) + @eval $(Symbol(string("_",fun))){F <: AbstractFloat}(x::AbstractVector{F}) = NaNMath.$(fun)(x) +end + +# --------------------------------------------------------- + import Measures import Measures: Length, AbsoluteLength, Measure, BoundingBox, mm, cm, inch, pt, width, height, w, h const BBox = Measures.Absolute2DBox diff --git a/src/axes.jl b/src/axes.jl index 8d66278c..8722d539 100644 --- a/src/axes.jl +++ b/src/axes.jl @@ -118,7 +118,7 @@ Base.show(io::IO, axis::Axis) = dumpdict(axis.d, "Axis", true) # Base.getindex(axis::Axis, k::Symbol) = getindex(axis.d, k) Base.setindex!(axis::Axis, v, ks::Symbol...) = setindex!(axis.d, v, ks...) Base.haskey(axis::Axis, k::Symbol) = haskey(axis.d, k) -extrema(axis::Axis) = (ex = axis[:extrema]; (ex.emin, ex.emax)) #This is the NaNMath version, not the Base version +_extrema(axis::Axis) = (ex = axis[:extrema]; (ex.emin, ex.emax)) const _scale_funcs = Dict{Symbol,Function}( @@ -349,11 +349,11 @@ function expand_extrema!(sp::Subplot, d::KW) bw = d[:bar_width] if bw == nothing - bw = d[:bar_width] = mean(diff(data)) + bw = d[:bar_width] = _mean(diff(data)) end axis = sp.attr[Symbol(dsym, :axis)] - expand_extrema!(axis, maximum(data) + 0.5maximum(bw)) - expand_extrema!(axis, minimum(data) - 0.5minimum(bw)) + expand_extrema!(axis, _maximum(data) + 0.5_maximum(bw)) + expand_extrema!(axis, _minimum(data) - 0.5_minimum(bw)) end end diff --git a/src/backends.jl b/src/backends.jl index a402bc5f..72bef57e 100644 --- a/src/backends.jl +++ b/src/backends.jl @@ -75,7 +75,7 @@ function tick_padding(axis::Axis) vals, labs = ticks isempty(labs) && return 0mm # ptsz = axis[:tickfont].pointsize * pt - longest_label = maximum(length(lab) for lab in labs) + longest_label = _maximum(length(lab) for lab in labs) # generalize by "rotating" y labels rot = axis[:rotation] + (axis[:letter] == :y ? 90 : 0) diff --git a/src/backends/glvisualize.jl b/src/backends/glvisualize.jl index e97d81fd..cf2c9f1c 100644 --- a/src/backends/glvisualize.jl +++ b/src/backends/glvisualize.jl @@ -218,7 +218,7 @@ end function gl_marker(shape::Shape) points = Point2f0[Vec{2,Float32}(p) for p in zip(shape.x, shape.y)] bb = GeometryTypes.AABB(points) - mini, maxi = minimum(bb), maximum(bb) + mini, maxi = _minimum(bb), _maximum(bb) w3 = maxi-mini origin, width = Point2f0(mini[1], mini[2]), Point2f0(w3[1], w3[2]) map!(p -> ((p - origin) ./ width) - 0.5f0, points) # normalize and center @@ -347,7 +347,7 @@ function extract_any_color(d, kw_args) kw_args[:color_norm] = Vec2f0(clims) end elseif clims == :auto - kw_args[:color_norm] = Vec2f0(extrema(d[:y])) + kw_args[:color_norm] = Vec2f0(_extrema(d[:y])) end end else @@ -358,7 +358,7 @@ function extract_any_color(d, kw_args) kw_args[:color_norm] = Vec2f0(clims) end elseif clims == :auto - kw_args[:color_norm] = Vec2f0(extrema(d[:y])) + kw_args[:color_norm] = Vec2f0(_extrema(d[:y])) else error("Unsupported limits: $clims") end @@ -513,7 +513,7 @@ function hover(to_hover, to_display, window) end GLVisualize._view(robj, popup, camera = cam) bb = GLAbstraction.boundingbox(robj).value - mini = minimum(bb) + mini = _minimum(bb) w = GeometryTypes.widths(bb) wborder = w * 0.08f0 #8 percent border bb = GeometryTypes.AABB{Float32}(mini - wborder, w + 2 * wborder) @@ -525,7 +525,7 @@ function hover(to_hover, to_display, window) end function extract_extrema(d, kw_args) - xmin, xmax = extrema(d[:x]); ymin, ymax = extrema(d[:y]) + xmin, xmax = extrema(d[:x]); ymin, ymax = _extrema(d[:y]) kw_args[:primitive] = GeometryTypes.SimpleRectangle{Float32}(xmin, ymin, xmax-xmin, ymax-ymin) nothing end @@ -552,7 +552,7 @@ function extract_colornorm(d, kw_args) else d[:y] end - kw_args[:color_norm] = Vec2f0(extrema(z)) + kw_args[:color_norm] = Vec2f0(_extrema(z)) kw_args[:intensity] = map(Float32, collect(z)) end end @@ -824,7 +824,7 @@ function gl_bar(d, kw_args) # compute half-width of bars bw = nothing hw = if bw == nothing - mean(diff(x)) + _mean(diff(x)) else Float64[cycle(bw,i)*0.5 for i=1:length(x)] end @@ -907,7 +907,7 @@ function gl_boxplot(d, kw_args) end # change q1 and q5 to show outliers # using maximum and minimum values inside the limits - q1, q5 = extrema(inside) + q1, q5 = _extrema(inside) end # Box if notch @@ -1361,7 +1361,7 @@ function gl_contour(x, y, z, kw_args) T = eltype(z) levels = Contour.contours(map(T, x), map(T, y), z, h) result = Point2f0[] - zmin, zmax = get(kw_args, :limits, Vec2f0(extrema(z))) + zmin, zmax = get(kw_args, :limits, Vec2f0(_extrema(z))) cmap = get(kw_args, :color_map, get(kw_args, :color, RGBA{Float32}(0,0,0,1))) colors = RGBA{Float32}[] for c in levels.contours @@ -1382,7 +1382,7 @@ end function gl_heatmap(x,y,z, kw_args) - get!(kw_args, :color_norm, Vec2f0(extrema(z))) + get!(kw_args, :color_norm, Vec2f0(_extrema(z))) get!(kw_args, :color_map, Plots.make_gradient(cgrad())) delete!(kw_args, :intensity) I = GLVisualize.Intensity{1, Float32} @@ -1425,7 +1425,7 @@ function label_scatter(d, w, ho) if isapprox(bbw[3], 0) bbw = Vec3f0(bbw[1], bbw[2], 1) end - mini = minimum(bb) + mini = _minimum(bb) m = GLAbstraction.translationmatrix(-mini) m *= GLAbstraction.scalematrix(1 ./ bbw) kw[:primitive] = m * p diff --git a/src/backends/gr.jl b/src/backends/gr.jl index d2e34390..8fe8082a 100644 --- a/src/backends/gr.jl +++ b/src/backends/gr.jl @@ -262,7 +262,7 @@ end normalize_zvals(zv::Void) = zv function normalize_zvals(zv::AVec) - vmin, vmax = extrema(zv) + vmin, vmax = _extrema(zv) if vmin == vmax zeros(length(zv)) else @@ -637,7 +637,7 @@ function gr_display(sp::Subplot{GRBackend}, w, h, viewport_canvas) elseif ispolar(sp) r = gr_set_viewport_polar() - rmin, rmax = GR.adjustrange(minimum(r), maximum(r)) + rmin, rmax = GR.adjustrange(_minimum(r), _maximum(r)) # rmin, rmax = axis_limits(sp[:yaxis]) gr_polaraxes(rmin, rmax) @@ -822,7 +822,7 @@ function gr_display(sp::Subplot{GRBackend}, w, h, viewport_canvas) # create the colorbar of contour levels if sp[:colorbar] != :none gr_set_viewport_cmap(sp) - l = round(Int32, 1000 + (h - minimum(h)) / (maximum(h) - minimum(h)) * 255) + l = round(Int32, 1000 + (h - _minimum(h)) / (_maximum(h) - _minimum(h)) * 255) GR.setwindow(xmin, xmax, zmin, zmax) GR.cellarray(xmin, xmax, zmax, zmin, 1, length(l), l) ztick = 0.5 * GR.tick(zmin, zmax) diff --git a/src/backends/plotly.jl b/src/backends/plotly.jl index 814e4775..2dba181e 100644 --- a/src/backends/plotly.jl +++ b/src/backends/plotly.jl @@ -546,7 +546,7 @@ function plotly_series(plt::Plot, series::Series) else # grad = ColorGradient(series[:markercolor], alpha=series[:markeralpha]) grad = as_gradient(series[:markercolor], series[:markeralpha]) - zmin, zmax = extrema(series[:marker_z]) + zmin, zmax = _extrema(series[:marker_z]) 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) [rgba_string(grad[(zi - zmin) / zrange]) for zi in series[:marker_z]] end diff --git a/src/backends/pyplot.jl b/src/backends/pyplot.jl index 69fbe426..579c1401 100644 --- a/src/backends/pyplot.jl +++ b/src/backends/pyplot.jl @@ -705,11 +705,11 @@ function py_add_series(plt::Plot{PyPlotBackend}, series::Series) # contours on the axis planes if series[:contours] for (zdir,mat) in (("x",x), ("y",y), ("z",z)) - offset = (zdir == "y" ? maximum : minimum)(mat) + offset = (zdir == "y" ? _maximum : _minimum)(mat) handle = ax[:contourf](x, y, z, levelargs...; zdir = zdir, cmap = py_fillcolormap(series), - offset = (zdir == "y" ? maximum : minimum)(mat) # where to draw the contour plane + offset = (zdir == "y" ? _maximum : _minimum)(mat) # where to draw the contour plane ) push!(handles, handle) needs_colorbar = true @@ -778,7 +778,7 @@ function py_add_series(plt::Plot{PyPlotBackend}, series::Series) end clims = sp[:clims] - zmin, zmax = extrema(z) + zmin, zmax = _extrema(z) extrakw[:vmin] = (is_2tuple(clims) && isfinite(clims[1])) ? clims[1] : zmin extrakw[:vmax] = (is_2tuple(clims) && isfinite(clims[2])) ? clims[2] : zmax @@ -926,7 +926,7 @@ function py_compute_axis_minval(axis::Axis) for series in series_list(sp) v = series.d[axis[:letter]] if !isempty(v) - minval = min(minval, minimum(abs(v))) + minval = min(minval, _minimum(abs(v))) end end end diff --git a/src/components.jl b/src/components.jl index b20eb3d0..37e0e1c3 100644 --- a/src/components.jl +++ b/src/components.jl @@ -501,7 +501,7 @@ immutable ZValues zrange::Tuple{Float64,Float64} end -function zvalues{T<:Real}(values::AVec{T}, zrange::Tuple{T,T} = (minimum(values), maximum(values))) +function zvalues{T<:Real}(values::AVec{T}, zrange::Tuple{T,T} = (_minimum(values), _maximum(values))) ZValues(collect(float(values)), map(Float64, zrange)) end @@ -645,8 +645,8 @@ function (bc::BezierCurve)(t::Real) p end -Base.mean(x::Real, y::Real) = 0.5*(x+y) -Base.mean{N,T<:Real}(ps::FixedSizeArrays.Vec{N,T}...) = sum(ps) / length(ps) +_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 diff --git a/src/layouts.jl b/src/layouts.jl index a5814ba1..ff6f955a 100644 --- a/src/layouts.jl +++ b/src/layouts.jl @@ -301,10 +301,10 @@ bottompad(layout::GridLayout) = layout.minpad[4] function _update_min_padding!(layout::GridLayout) map(_update_min_padding!, layout.grid) layout.minpad = ( - maximum(map(leftpad, layout.grid[:,1])), - maximum(map(toppad, layout.grid[1,:])), - maximum(map(rightpad, layout.grid[:,end])), - maximum(map(bottompad, layout.grid[end,:])) + _maximum(map(leftpad, layout.grid[:,1])), + _maximum(map(toppad, layout.grid[1,:])), + _maximum(map(rightpad, layout.grid[:,end])), + _maximum(map(bottompad, layout.grid[end,:])) ) end @@ -349,10 +349,10 @@ function update_child_bboxes!(layout::GridLayout, minimum_perimeter = [0mm,0mm,0 # get the max horizontal (left and right) padding over columns, # and max vertical (bottom and top) padding over rows # TODO: add extra padding here - pad_left = maximum(minpad_left, 1) - pad_top = maximum(minpad_top, 2) - pad_right = maximum(minpad_right, 1) - pad_bottom = maximum(minpad_bottom, 2) + pad_left = _maximum(minpad_left, 1) + pad_top = _maximum(minpad_top, 2) + pad_right = _maximum(minpad_right, 1) + pad_bottom = _maximum(minpad_bottom, 2) # make sure the perimeter match the parent pad_left[1] = max(pad_left[1], minimum_perimeter[1]) @@ -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 diff --git a/src/pipeline.jl b/src/pipeline.jl index 70644055..e385b8a8 100644 --- a/src/pipeline.jl +++ b/src/pipeline.jl @@ -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, diff --git a/src/recipes.jl b/src/recipes.jl index 1bc4cad5..4be5018f 100644 --- a/src/recipes.jl +++ b/src/recipes.jl @@ -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 @@ -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 @@ -550,7 +550,7 @@ 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) _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: @@ -920,7 +920,7 @@ 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) @@ -985,8 +985,8 @@ 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 @@ -1007,7 +1007,7 @@ 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...) diff --git a/src/utils.jl b/src/utils.jl index da1d1cb6..efdddb45 100644 --- a/src/utils.jl +++ b/src/utils.jl @@ -3,7 +3,7 @@ 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] @@ -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 @@ -283,7 +283,7 @@ 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) + e1, e2 = _extrema(x) lims[1] = min(lims[1], e1) lims[2] = max(lims[2], e2) # catch err @@ -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) + xmin, xmax = _extrema(x) + ymin, ymax = _extrema(y) r = 0.5 * min(xmax - xmin, ymax - ymin) - extrema(r) + _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)) diff --git a/test/runtests.jl b/test/runtests.jl index 94f95a1b..8434a45f 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -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