Merge pull request #922 from mkborregaard/make-tkelman-happy

remove all 0.5-compliant uses of the transpose operator

.travis.yml

@@ -4,7 +4,7 @@ os:
   - linux
   # - osx
 julia:
-  - 0.5
+  - 0.6
 matrix:
   allow_failures:
     - julia: nightly

NEWS.md

@@ -10,7 +10,9 @@
 
 ---
 
-## 0.11 (current master/dev)
+## 0.12 (current master/dev)
+
+- 0.6 only
 
 #### 0.11.3
 

REQUIRE

@@ -1,6 +1,6 @@
-julia 0.5
+julia 0.6-pre
 
-RecipesBase
+RecipesBase 0.2.0
 PlotUtils 0.4.1
 PlotThemes 0.1.3
 Reexport

src/Plots.jl

@@ -5,6 +5,7 @@ module Plots
 using Reexport
 using FixedSizeArrays
 @reexport using RecipesBase
+import RecipesBase: plot, animate
 using Base.Meta
 @reexport using PlotUtils
 @reexport using PlotThemes
@@ -30,9 +31,6 @@ export
     with,
     twinx,
 
-    @userplot,
-    @shorthands,
-
     pie,
     pie!,
     plot3d,
@@ -107,14 +105,26 @@ export
 # ---------------------------------------------------------
 
 import NaNMath # define functions that ignores NaNs. To overcome the destructive effects of https://github.com/JuliaLang/julia/pull/12563
-ignoreNaN_minimum{F<:AbstractFloat}(x::AbstractArray{F}) = NaNMath.minimum(x)
-ignoreNaN_minimum(x) = Base.minimum(x)
-ignoreNaN_maximum{F<:AbstractFloat}(x::AbstractArray{F}) = NaNMath.maximum(x)
-ignoreNaN_maximum(x) = Base.maximum(x)
-ignoreNaN_mean{F<:AbstractFloat}(x::AbstractArray{F}) = NaNMath.mean(x)
-ignoreNaN_mean(x) = Base.mean(x)
-ignoreNaN_extrema{F<:AbstractFloat}(x::AbstractArray{F}) = NaNMath.extrema(x)
-ignoreNaN_extrema(x) = Base.extrema(x)
+ignorenan_minimum{F<:AbstractFloat}(x::AbstractArray{F}) = NaNMath.minimum(x)
+ignorenan_minimum(x) = Base.minimum(x)
+ignorenan_maximum{F<:AbstractFloat}(x::AbstractArray{F}) = NaNMath.maximum(x)
+ignorenan_maximum(x) = Base.maximum(x)
+ignorenan_mean{F<:AbstractFloat}(x::AbstractArray{F}) = NaNMath.mean(x)
+ignorenan_mean(x) = Base.mean(x)
+ignorenan_extrema{F<:AbstractFloat}(x::AbstractArray{F}) = NaNMath.extrema(x)
+ignorenan_extrema(x) = Base.extrema(x)
+
+# ---------------------------------------------------------
+
+# to cater for block matrices, Base.transpose is recursive.
+# This makes it impossible to create row vectors of String and Symbol with the transpose operator.
+# This solves this issue, internally in Plots at least.
+
+
+# commented out on the insistence of the METADATA maintainers
+
+#Base.transpose(x::Symbol) = x
+#Base.transpose(x::String) = x
 
 # ---------------------------------------------------------
 
@@ -147,16 +157,6 @@ include("backends.jl")
 
 # ---------------------------------------------------------
 
-# define and export shorthand plotting method definitions
-macro shorthands(funcname::Symbol)
-    funcname2 = Symbol(funcname, "!")
-    esc(quote
-        export $funcname, $funcname2
-        $funcname(args...; kw...) = plot(args...; kw..., seriestype = $(quot(funcname)))
-        $funcname2(args...; kw...) = plot!(args...; kw..., seriestype = $(quot(funcname)))
-    end)
-end
-
 @shorthands scatter
 @shorthands bar
 @shorthands barh

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)
-ignoreNaN_extrema(axis::Axis) = (ex = axis[:extrema]; (ex.emin, ex.emax))
+ignorenan_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] = ignoreNaN_mean(diff(data))
+            bw = d[:bar_width] = ignorenan_mean(diff(data))
         end
         axis = sp.attr[Symbol(dsym, :axis)]
-        expand_extrema!(axis, ignoreNaN_maximum(data) + 0.5maximum(bw))
-        expand_extrema!(axis, ignoreNaN_minimum(data) - 0.5minimum(bw))
+        expand_extrema!(axis, ignorenan_maximum(data) + 0.5maximum(bw))
+        expand_extrema!(axis, ignorenan_minimum(data) - 0.5minimum(bw))
     end
 
 end

src/backends/glvisualize.jl

@@ -304,7 +304,7 @@ function extract_any_color(d, kw_args)
                     kw_args[:color_norm] = Vec2f0(clims)
                 end
             elseif clims == :auto
-                kw_args[:color_norm] = Vec2f0(ignoreNaN_extrema(d[:y]))
+                kw_args[:color_norm] = Vec2f0(ignorenan_extrema(d[:y]))
             end
         end
     else
@@ -315,7 +315,7 @@ function extract_any_color(d, kw_args)
                 kw_args[:color_norm] = Vec2f0(clims)
             end
         elseif clims == :auto
-            kw_args[:color_norm] = Vec2f0(ignoreNaN_extrema(d[:y]))
+            kw_args[:color_norm] = Vec2f0(ignorenan_extrema(d[:y]))
         else
             error("Unsupported limits: $clims")
         end
@@ -482,7 +482,7 @@ function hover(to_hover, to_display, window)
 end
 
 function extract_extrema(d, kw_args)
-    xmin, xmax = ignoreNaN_extrema(d[:x]); ymin, ymax = ignoreNaN_extrema(d[:y])
+    xmin, xmax = ignorenan_extrema(d[:x]); ymin, ymax = ignorenan_extrema(d[:y])
     kw_args[:primitive] = GeometryTypes.SimpleRectangle{Float32}(xmin, ymin, xmax-xmin, ymax-ymin)
     nothing
 end
@@ -509,7 +509,7 @@ function extract_colornorm(d, kw_args)
         else
             d[:y]
         end
-        kw_args[:color_norm] = Vec2f0(ignoreNaN_extrema(z))
+        kw_args[:color_norm] = Vec2f0(ignorenan_extrema(z))
         kw_args[:intensity] = map(Float32, collect(z))
     end
 end
@@ -781,9 +781,9 @@ function gl_bar(d, kw_args)
     # compute half-width of bars
     bw = nothing
     hw = if bw == nothing
-        ignoreNaN_mean(diff(x))
+        ignorenan_mean(diff(x))
     else
-        Float64[cycle(bw,i)*0.5 for i=1:length(x)]
+        Float64[_cycle(bw,i)*0.5 for i=1:length(x)]
     end
 
     # make fillto a vector... default fills to 0
@@ -797,7 +797,7 @@ function gl_bar(d, kw_args)
     sx, sy = m[1,1], m[2,2]
     for i=1:ny
         center = x[i]
-        hwi = abs(cycle(hw,i)); yi = y[i]; fi = cycle(fillto,i)
+        hwi = abs(_cycle(hw,i)); yi = y[i]; fi = _cycle(fillto,i)
         if Plots.isvertical(d)
             sz = (hwi*sx, yi*sy)
         else
@@ -833,7 +833,7 @@ function gl_boxplot(d, kw_args)
     sx, sy = m[1,1], m[2,2]
     for (i,glabel) in enumerate(glabels)
         # filter y
-        values = y[filter(i -> cycle(x,i) == glabel, 1:length(y))]
+        values = y[filter(i -> _cycle(x,i) == glabel, 1:length(y))]
         # compute quantiles
         q1,q2,q3,q4,q5 = quantile(values, linspace(0,1,5))
         # notch
@@ -846,7 +846,7 @@ function gl_boxplot(d, kw_args)
 
         # make the shape
         center = Plots.discrete_value!(d[:subplot][:xaxis], glabel)[1]
-        hw = d[:bar_width] == nothing ? Plots._box_halfwidth*2 : cycle(d[:bar_width], i)
+        hw = d[:bar_width] == nothing ? Plots._box_halfwidth*2 : _cycle(d[:bar_width], i)
         l, m, r = center - hw/2, center, center + hw/2
 
         # internal nodes for notches
@@ -864,7 +864,7 @@ function gl_boxplot(d, kw_args)
             end
             # change q1 and q5 to show outliers
             # using maximum and minimum values inside the limits
-            q1, q5 = ignoreNaN_extrema(inside)
+            q1, q5 = ignorenan_extrema(inside)
         end
         # Box
         if notch
@@ -945,7 +945,7 @@ function scale_for_annotations!(series::Series, scaletype::Symbol = :pixels)
         msw, msh = anns.scalefactor
         offsets = Array(Vec2f0, length(anns.strs))
         series[:markersize] = map(1:length(anns.strs)) do i
-            str = cycle(anns.strs, i)
+            str = _cycle(anns.strs, i)
             # get the width and height of the string (in mm)
             sw, sh = text_size(str, anns.font.pointsize)
 
@@ -1058,7 +1058,7 @@ function _display(plt::Plot{GLVisualizeBackend}, visible = true)
                     kw = copy(kw_args)
                     fr = d[:fillrange]
                     ps = if all(x-> x >= 0, diff(d[:x])) # if is monotonic
-                        vcat(points, Point2f0[(points[i][1], cycle(fr, i)) for i=length(points):-1:1])
+                        vcat(points, Point2f0[(points[i][1], _cycle(fr, i)) for i=length(points):-1:1])
                     else
                         points
                     end
@@ -1231,7 +1231,7 @@ function gl_scatter(points, kw_args)
     if haskey(kw_args, :stroke_width)
         s = Reactive.value(kw_args[:scale])
         sw = kw_args[:stroke_width]
-        if sw*5 > cycle(Reactive.value(s), 1)[1] # restrict marker stroke to 1/10th of scale (and handle arrays of scales)
+        if sw*5 > _cycle(Reactive.value(s), 1)[1] # restrict marker stroke to 1/10th of scale (and handle arrays of scales)
             kw_args[:stroke_width] = s[1] / 5f0
         end
     end
@@ -1318,7 +1318,7 @@ 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(ignoreNaN_extrema(z)))
+        zmin, zmax = get(kw_args, :limits, Vec2f0(ignorenan_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
@@ -1339,7 +1339,7 @@ end
 
 
 function gl_heatmap(x,y,z, kw_args)
-    get!(kw_args, :color_norm, Vec2f0(ignoreNaN_extrema(z)))
+    get!(kw_args, :color_norm, Vec2f0(ignorenan_extrema(z)))
     get!(kw_args, :color_map, Plots.make_gradient(cgrad()))
     delete!(kw_args, :intensity)
     I = GLVisualize.Intensity{1, Float32}

src/backends/gr.jl

@@ -124,10 +124,10 @@ function gr_getcolorind(c)
     convert(Int, GR.inqcolorfromrgb(red(c), green(c), blue(c)))
 end
 
-gr_set_linecolor(c)   = GR.setlinecolorind(gr_getcolorind(cycle(c,1)))
-gr_set_fillcolor(c)   = GR.setfillcolorind(gr_getcolorind(cycle(c,1)))
-gr_set_markercolor(c) = GR.setmarkercolorind(gr_getcolorind(cycle(c,1)))
-gr_set_textcolor(c)   = GR.settextcolorind(gr_getcolorind(cycle(c,1)))
+gr_set_linecolor(c)   = GR.setlinecolorind(gr_getcolorind(_cycle(c,1)))
+gr_set_fillcolor(c)   = GR.setfillcolorind(gr_getcolorind(_cycle(c,1)))
+gr_set_markercolor(c) = GR.setmarkercolorind(gr_getcolorind(_cycle(c,1)))
+gr_set_textcolor(c)   = GR.settextcolorind(gr_getcolorind(_cycle(c,1)))
 
 # --------------------------------------------------------------------------------------
 
@@ -264,7 +264,7 @@ end
 
 normalize_zvals(zv::Void) = zv
 function normalize_zvals(zv::AVec)
-    vmin, vmax = ignoreNaN_extrema(zv)
+    vmin, vmax = ignorenan_extrema(zv)
     if vmin == vmax
         zeros(length(zv))
     else
@@ -301,23 +301,23 @@ function gr_draw_markers(series::Series, x, y, msize, mz)
     shapes = series[:markershape]
     if shapes != :none
         for i=1:length(x)
-            msi = cycle(msize, i)
-            shape = cycle(shapes, i)
+            msi = _cycle(msize, i)
+            shape = _cycle(shapes, i)
             cfunc = isa(shape, Shape) ? gr_set_fillcolor : gr_set_markercolor
             cfuncind = isa(shape, Shape) ? GR.setfillcolorind : GR.setmarkercolorind
 
             # draw a filled in shape, slightly bigger, to estimate a stroke
             if series[:markerstrokewidth] > 0
-                cfunc(cycle(series[:markerstrokecolor], i)) #, series[:markerstrokealpha])
+                cfunc(_cycle(series[:markerstrokecolor], i)) #, series[:markerstrokealpha])
                 gr_draw_marker(x[i], y[i], msi + series[:markerstrokewidth], shape)
             end
 
             # draw the shape
             if mz == nothing
-                cfunc(cycle(series[:markercolor], i)) #, series[:markeralpha])
+                cfunc(_cycle(series[:markercolor], i)) #, series[:markeralpha])
             else
                 # pick a color from the pre-loaded gradient
-                ci = round(Int, 1000 + cycle(mz, i) * 255)
+                ci = round(Int, 1000 + _cycle(mz, i) * 255)
                 cfuncind(ci)
                 GR.settransparency(_gr_gradient_alpha[ci-999])
             end
@@ -448,7 +448,6 @@ gr_view_ycenter() = 0.5 * (viewport_plotarea[3] + viewport_plotarea[4])
 
 function gr_legend_pos(s::Symbol,w,h)
     str = string(s)
-    println(str)
     if str == "best"
         str = "topright"
     end
@@ -667,7 +666,7 @@ function gr_display(sp::Subplot{GRBackend}, w, h, viewport_canvas)
 
     elseif ispolar(sp)
         r = gr_set_viewport_polar()
-        rmin, rmax = GR.adjustrange(ignoreNaN_minimum(r), ignoreNaN_maximum(r))
+        rmin, rmax = GR.adjustrange(ignorenan_minimum(r), ignorenan_maximum(r))
         # rmin, rmax = axis_limits(sp[:yaxis])
         gr_polaraxes(rmin, rmax)
 
@@ -706,7 +705,7 @@ function gr_display(sp::Subplot{GRBackend}, w, h, viewport_canvas)
                         rotation = sp[:xaxis][:rotation])
             for (cv, dv) in zip(xticks...)
                 # use xor ($) to get the right y coords
-                xi, yi = GR.wctondc(cv, (flip $ mirror) ? ymax : ymin)
+                xi, yi = GR.wctondc(cv, xor(flip, mirror) ? ymax : ymin)
                 # @show cv dv ymin xi yi flip mirror (flip $ mirror)
                 gr_text(xi, yi + (mirror ? 1 : -1) * 5e-3, string(dv))
             end
@@ -723,7 +722,7 @@ function gr_display(sp::Subplot{GRBackend}, w, h, viewport_canvas)
                         rotation = sp[:yaxis][:rotation])
             for (cv, dv) in zip(yticks...)
                 # use xor ($) to get the right y coords
-                xi, yi = GR.wctondc((flip $ mirror) ? xmax : xmin, cv)
+                xi, yi = GR.wctondc(xor(flip, mirror) ? xmax : xmin, cv)
                 # @show cv dv xmin xi yi
                 gr_text(xi + (mirror ? 1 : -1) * 1e-2, yi, string(dv))
             end
@@ -809,9 +808,9 @@ function gr_display(sp::Subplot{GRBackend}, w, h, viewport_canvas)
                     fr_from, fr_to = (is_2tuple(frng) ? frng : (y, frng))
                     for (i,rng) in enumerate(iter_segments(series[:x], series[:y]))
                         if length(rng) > 1
-                            gr_set_fillcolor(cycle(series[:fillcolor], i))
-                            fx = cycle(x, vcat(rng, reverse(rng)))
-                            fy = vcat(cycle(fr_from,rng), cycle(fr_to,reverse(rng)))
+                            gr_set_fillcolor(_cycle(series[:fillcolor], i))
+                            fx = _cycle(x, vcat(rng, reverse(rng)))
+                            fy = vcat(_cycle(fr_from,rng), _cycle(fr_to,reverse(rng)))
                             # @show i rng fx fy
                             GR.fillarea(fx, fy)
                         end
@@ -852,7 +851,7 @@ 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 - ignoreNaN_minimum(h)) / (ignoreNaN_maximum(h) - ignoreNaN_minimum(h)) * 255)
+                l = round(Int32, 1000 + (h - ignorenan_minimum(h)) / (ignorenan_maximum(h) - ignorenan_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)
@@ -963,11 +962,11 @@ function gr_display(sp::Subplot{GRBackend}, w, h, viewport_canvas)
                     x, y = series[:x][rng], series[:y][rng]
 
                     # draw the interior
-                    gr_set_fill(cycle(series[:fillcolor], i))
+                    gr_set_fill(_cycle(series[:fillcolor], i))
                     GR.fillarea(x, y)
 
                     # draw the shapes
-                    gr_set_line(series[:linewidth], :solid, cycle(series[:linecolor], i))
+                    gr_set_line(series[:linewidth], :solid, _cycle(series[:linecolor], i))
                     GR.polyline(x, y)
                 end
             end

src/backends/inspectdr.jl

@@ -265,8 +265,8 @@ For st in :shape:
             nmax = i
             if length(rng) > 1
                 linewidth = series[:linewidth]
-                linecolor = _inspectdr_mapcolor(cycle(series[:linecolor], i))
-                fillcolor = _inspectdr_mapcolor(cycle(series[:fillcolor], i))
+                linecolor = _inspectdr_mapcolor(_cycle(series[:linecolor], i))
+                fillcolor = _inspectdr_mapcolor(_cycle(series[:fillcolor], i))
                 line = InspectDR.line(
                     style=:solid, width=linewidth, color=linecolor
                 )
@@ -280,8 +280,8 @@ For st in :shape:
         i = (nmax >= 2? div(nmax, 2): nmax) #Must pick one set of colors for legend
         if i > 1 #Add dummy waveform for legend entry:
             linewidth = series[:linewidth]
-            linecolor = _inspectdr_mapcolor(cycle(series[:linecolor], i))
-            fillcolor = _inspectdr_mapcolor(cycle(series[:fillcolor], i))
+            linecolor = _inspectdr_mapcolor(_cycle(series[:linecolor], i))
+            fillcolor = _inspectdr_mapcolor(_cycle(series[:fillcolor], i))
             wfrm = InspectDR.add(plot, Float64[], Float64[], id=series[:label])
             wfrm.line = InspectDR.line(
                 style=:none, width=linewidth, #linewidth affects glyph

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 = ignoreNaN_extrema(series[:marker_z])
+            zmin, zmax = ignorenan_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
@@ -600,18 +600,18 @@ function plotly_series_shapes(plt::Plot, series::Series)
             :x => vcat(x[rng], x[rng[1]]),
             :y => vcat(y[rng], y[rng[1]]),
             :fill => "tozeroy",
-            :fillcolor => rgba_string(cycle(series[:fillcolor], i)),
+            :fillcolor => rgba_string(_cycle(series[:fillcolor], i)),
         ))
         if series[:markerstrokewidth] > 0
             d_out[:line] = KW(
-                :color => rgba_string(cycle(series[:linecolor], i)),
+                :color => rgba_string(_cycle(series[:linecolor], i)),
                 :width => series[:linewidth],
                 :dash => string(series[:linestyle]),
             )
         end
         d_out[:showlegend] = i==1 ? should_add_to_legend(series) : false
         plotly_polar!(d_out, series)
-        plotly_hover!(d_out, cycle(series[:hover], i))
+        plotly_hover!(d_out, _cycle(series[:hover], i))
         push!(d_outs, d_out)
     end
     d_outs

src/backends/pyplot.jl

@@ -495,10 +495,10 @@ function py_add_series(plt::Plot{PyPlotBackend}, series::Series)
                 handle = if is3d(st)
                     for rng in iter_segments(x, y, z)
                         length(rng) < 2 && continue
-                        push!(segments, [(cycle(x,i),cycle(y,i),cycle(z,i)) for i in rng])
+                        push!(segments, [(_cycle(x,i),_cycle(y,i),_cycle(z,i)) for i in rng])
                     end
                     # for i=1:n
-                    #     segments[i] = [(cycle(x,i), cycle(y,i), cycle(z,i)), (cycle(x,i+1), cycle(y,i+1), cycle(z,i+1))]
+                    #     segments[i] = [(_cycle(x,i), _cycle(y,i), _cycle(z,i)), (_cycle(x,i+1), _cycle(y,i+1), _cycle(z,i+1))]
                     # end
                     lc = pyart3d.Line3DCollection(segments; kw...)
                     lc[:set_array](lz)
@@ -507,10 +507,10 @@ function py_add_series(plt::Plot{PyPlotBackend}, series::Series)
                 else
                     for rng in iter_segments(x, y)
                         length(rng) < 2 && continue
-                        push!(segments, [(cycle(x,i),cycle(y,i)) for i in rng])
+                        push!(segments, [(_cycle(x,i),_cycle(y,i)) for i in rng])
                     end
                     # for i=1:n
-                    #     segments[i] = [(cycle(x,i), cycle(y,i)), (cycle(x,i+1), cycle(y,i+1))]
+                    #     segments[i] = [(_cycle(x,i), _cycle(y,i)), (_cycle(x,i+1), _cycle(y,i+1))]
                     # end
                     lc = pycollections.LineCollection(segments; kw...)
                     lc[:set_array](lz)
@@ -581,16 +581,16 @@ function py_add_series(plt::Plot{PyPlotBackend}, series::Series)
             lw = py_dpi_scale(plt, series[:markerstrokewidth])
             for i=1:length(y)
                 extrakw[:c] = if series[:marker_z] == nothing
-                    py_color_fix(py_color(cycle(series[:markercolor],i)), x)
+                    py_color_fix(py_color(_cycle(series[:markercolor],i)), x)
                 else
                     extrakw[:c]
                 end
 
-                push!(handle, ax[:scatter](cycle(x,i), cycle(y,i);
+                push!(handle, ax[:scatter](_cycle(x,i), _cycle(y,i);
                     label = series[:label],
                     zorder = series[:series_plotindex] + 0.5,
-                    marker = py_marker(cycle(shapes,i)),
-                    s =  py_dpi_scale(plt, cycle(series[:markersize],i) .^ 2),
+                    marker = py_marker(_cycle(shapes,i)),
+                    s =  py_dpi_scale(plt, _cycle(series[:markersize],i) .^ 2),
                     edgecolors = msc,
                     linewidths = lw,
                     extrakw...
@@ -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" ? ignoreNaN_maximum : ignoreNaN_minimum)(mat)
+                    offset = (zdir == "y" ? ignorenan_maximum : ignorenan_minimum)(mat)
                     handle = ax[:contourf](x, y, z, levelargs...;
                         zdir = zdir,
                         cmap = py_fillcolormap(series),
-                        offset = (zdir == "y" ? ignoreNaN_maximum : ignoreNaN_minimum)(mat)  # where to draw the contour plane
+                        offset = (zdir == "y" ? ignorenan_maximum : ignorenan_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 = ignoreNaN_extrema(z)
+        zmin, zmax = ignorenan_extrema(z)
         extrakw[:vmin] = (is_2tuple(clims) && isfinite(clims[1])) ? clims[1] : zmin
         extrakw[:vmax] = (is_2tuple(clims) && isfinite(clims[2])) ? clims[2] : zmax
 
@@ -802,8 +802,8 @@ function py_add_series(plt::Plot{PyPlotBackend}, series::Series)
                     path;
                     label = series[:label],
                     zorder = series[:series_plotindex],
-                    edgecolor = py_color(cycle(series[:linecolor], i)),
-                    facecolor = py_color(cycle(series[:fillcolor], i)),
+                    edgecolor = py_color(_cycle(series[:linecolor], i)),
+                    facecolor = py_color(_cycle(series[:fillcolor], i)),
                     linewidth = py_dpi_scale(plt, series[:linewidth]),
                     fill = true
                 )
@@ -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 = NaNMath.min(minval, ignoreNaN_minimum(abs(v)))
+                minval = NaNMath.min(minval, ignorenan_minimum(abs(v)))
             end
         end
     end
@@ -1166,7 +1166,7 @@ function py_add_legend(plt::Plot, sp::Subplot, ax)
                 # add a line/marker and a label
                 push!(handles, if series[:seriestype] == :shape
                     PyPlot.plt[:Line2D]((0,1),(0,0),
-                        color = py_color(cycle(series[:fillcolor],1)),
+                        color = py_color(_cycle(series[:fillcolor],1)),
                         linewidth = py_dpi_scale(plt, 4)
                     )
                 else

src/components.jl

@@ -446,7 +446,7 @@ function series_annotations_shapes!(series::Series, scaletype::Symbol = :pixels)
         msw,msh = anns.scalefactor
         msize = Float64[]
         shapes = Shape[begin
-            str = cycle(anns.strs,i)
+            str = _cycle(anns.strs,i)
 
             # get the width and height of the string (in mm)
             sw, sh = text_size(str, anns.font.pointsize)
@@ -462,7 +462,7 @@ function series_annotations_shapes!(series::Series, scaletype::Symbol = :pixels)
             # and then re-scale a copy of baseshape to match the w/h ratio
             maxscale = max(xscale, yscale)
             push!(msize, maxscale)
-            baseshape = cycle(get(anns.baseshape),i)
+            baseshape = _cycle(get(anns.baseshape),i)
             shape = scale(baseshape, msw*xscale/maxscale, msh*yscale/maxscale, (0,0))
         end for i=1:length(anns.strs)]
         series[:markershape] = shapes
@@ -479,13 +479,13 @@ end
 Base.start(ea::EachAnn) = 1
 Base.done(ea::EachAnn, i) = ea.anns == nothing || isempty(ea.anns.strs) || i > length(ea.y)
 function Base.next(ea::EachAnn, i)
-    tmp = cycle(ea.anns.strs,i)
+    tmp = _cycle(ea.anns.strs,i)
     str,fnt = if isa(tmp, PlotText)
         tmp.str, tmp.font
     else
         tmp, ea.anns.font
     end
-    ((cycle(ea.x,i), cycle(ea.y,i), str, fnt), i+1)
+    ((_cycle(ea.x,i), _cycle(ea.y,i), str, fnt), i+1)
 end
 
 annotations(::Void) = []
@@ -501,13 +501,13 @@ immutable ZValues
   zrange::Tuple{Float64,Float64}
 end
 
-function zvalues{T<:Real}(values::AVec{T}, zrange::Tuple{T,T} = (ignoreNaN_minimum(values), ignoreNaN_maximum(values)))
+function zvalues{T<:Real}(values::AVec{T}, zrange::Tuple{T,T} = (ignorenan_minimum(values), ignorenan_maximum(values)))
   ZValues(collect(float(values)), map(Float64, zrange))
 end
 
 # -----------------------------------------------------------------------
 
-abstract AbstractSurface
+abstract type AbstractSurface end
 
 "represents a contour or surface mesh"
 immutable Surface{M<:AMat} <: AbstractSurface
@@ -659,7 +659,7 @@ function directed_curve(args...; kw...)
 end
 
 function extrema_plus_buffer(v, buffmult = 0.2)
-    vmin,vmax = ignoreNaN_extrema(v)
+    vmin,vmax = ignorenan_extrema(v)
     vdiff = vmax-vmin
     buffer = vdiff * buffmult
     vmin - buffer, vmax + buffer

src/deprecated/backends/gadfly_shapes.jl

@@ -84,7 +84,7 @@ function make_polygon(geom::ShapeGeometry, xs::AbstractArray, ys::AbstractArray,
     x = Compose.x_measure(xs[mod1(i, length(xs))])
     y = Compose.y_measure(ys[mod1(i, length(ys))])
     r = rs[mod1(i, length(rs))]
-    polys[i] = T[(x + r * sx, y + r * sy) for (sx,sy) in cycle(geom.vertices, i)]
+    polys[i] = T[(x + r * sx, y + r * sy) for (sx,sy) in _cycle(geom.vertices, i)]
   end
   Gadfly.polygon(polys, geom.tag)
 end

src/deprecated/colors.jl

@@ -1,5 +1,5 @@
 
-abstract ColorScheme
+abstract type ColorScheme end
 
 Base.getindex(scheme::ColorScheme, i::Integer) = getColor(scheme, i)
 

src/examples.jl

@@ -41,7 +41,7 @@ PlotExample("Colors",
     [:(begin
         y = rand(100)
         plot(0:10:100,rand(11,4),lab="lines",w=3,palette=:grays,fill=0, α=0.6)
-        scatter!(y, zcolor=abs(y-.5), m=(:heat,0.8,stroke(1,:green)), ms=10*abs(y-0.5)+4, lab="grad")
+        scatter!(y, zcolor=abs.(y-.5), m=(:heat,0.8,stroke(1,:green)), ms=10*abs.(y-0.5)+4, lab="grad")
     end)]
 ),
 
@@ -119,17 +119,18 @@ PlotExample("Line styles",
         styles = reshape(styles, 1, length(styles)) # Julia 0.6 unfortunately gives an error when transposing symbol vectors
         n = length(styles)
         y = cumsum(randn(20,n),1)
-        plot(y, line = (5, styles), label = map(string,styles))
+        plot(y, line = (5, styles), label = map(string,styles), legendtitle = "linestyle")
     end)]
 ),
 
 PlotExample("Marker types",
     "",
     [:(begin
-        markers = filter(m -> m in Plots.supported_markers(), Plots._shape_keys)'
+        markers = filter(m -> m in Plots.supported_markers(), Plots._shape_keys)
+        markers = reshape(markers, 1, length(markers))
         n = length(markers)
         x = linspace(0,10,n+2)[2:end-1]
-        y = repmat(reverse(x)', n, 1)
+        y = repmat(reshape(reverse(x),1,:), n, 1)
         scatter(x, y, m=(8,:auto), lab=map(string,markers), bg=:linen, xlim=(0,10), ylim=(0,10))
     end)]
 ),
@@ -215,7 +216,7 @@ PlotExample("Contours",
         x = 1:0.5:20
         y = 1:0.5:10
         f(x,y) = (3x+y^2)*abs(sin(x)+cos(y))
-        X = repmat(x', length(y), 1)
+        X = repmat(reshape(x,1,:), length(y), 1)
         Y = repmat(y, 1, length(x))
         Z = map(f, X, Y)
         p1 = contour(x, y, f, fill=true)
@@ -269,7 +270,7 @@ PlotExample("Polar Plots",
     "",
     [:(begin
         Θ = linspace(0,1.5π,100)
-        r = abs(0.1randn(100)+sin(3Θ))
+        r = abs.(0.1randn(100)+sin.(3Θ))
         plot(Θ, r, proj=:polar, m=2)
     end)]
 ),
@@ -279,7 +280,7 @@ PlotExample("Heatmap, categorical axes, and aspect_ratio",
     [:(begin
         xs = [string("x",i) for i=1:10]
         ys = [string("y",i) for i=1:4]
-        z = float((1:4)*(1:10)')
+        z = float((1:4)*reshape(1:10,1,:))
         heatmap(xs, ys, z, aspect_ratio=1)
     end)]
 ),

src/layouts.jl

@@ -9,8 +9,8 @@ to_pixels(m::AbsoluteLength) = m.value / 0.254
 
 const _cbar_width = 5mm
 
-Base.:.*(m::Measure, n::Number) = m * n
-Base.:.*(n::Number, m::Measure) = m * n
+Base.broadcast(::typeof(Base.:.*), m::Measure, n::Number) = m * n
+Base.broadcast(::typeof(Base.:.*), m::Number, n::Measure) = m * n
 Base.:-(m::Measure, a::AbstractArray) = map(ai -> m - ai, a)
 Base.:-(a::AbstractArray, m::Measure) = map(ai -> ai - m, a)
 Base.zero(::Type{typeof(mm)}) = 0mm
@@ -704,7 +704,7 @@ function link_axes!(axes::Axis...)
     a1 = axes[1]
     for i=2:length(axes)
         a2 = axes[i]
-        expand_extrema!(a1, ignoreNaN_extrema(a2))
+        expand_extrema!(a1, ignorenan_extrema(a2))
         for k in (:extrema, :discrete_values, :continuous_values, :discrete_map)
             a2[k] = a1[k]
         end

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 = [ignoreNaN_minimum(x), ignoreNaN_maximum(x)]
+        sx = [ignorenan_minimum(x), ignorenan_maximum(x)]
         sy = β * sx + α
         push!(kw_list, merge(copy(kw), KW(
             :seriestype => :path,
@@ -262,7 +262,7 @@ function _subplot_setup(plt::Plot, d::KW, kw_list::Vector{KW})
     for kw in kw_list
         # get the Subplot object to which the series belongs.
         sps = get(kw, :subplot, :auto)
-        sp = get_subplot(plt, cycle(sps == :auto ? plt.subplots : plt.subplots[sps], command_idx(kw_list,kw)))
+        sp = get_subplot(plt, _cycle(sps == :auto ? plt.subplots : plt.subplots[sps], command_idx(kw_list,kw)))
         kw[:subplot] = sp
 
         # extract subplot/axis attributes from kw and add to sp_attr

src/plot.jl

@@ -60,7 +60,7 @@ function plot(plt1::Plot, plts_tail::Plot...; kw...)
 
     # build our plot vector from the args
     n = length(plts_tail) + 1
-    plts = Array(Plot, n)
+    plts = Array{Plot}(n)
     plts[1] = plt1
     for (i,plt) in enumerate(plts_tail)
         plts[i+1] = plt

src/recipes.jl

@@ -1,53 +1,4 @@
 
-
-
-"""
-You can easily define your own plotting recipes with convenience methods:
-
-```
-@userplot type GroupHist
-    args
-end
-
-@recipe function f(gh::GroupHist)
-    # set some attributes, add some series, using gh.args as input
-end
-
-# now you can plot like:
-grouphist(rand(1000,4))
-```
-"""
-macro userplot(expr)
-    _userplot(expr)
-end
-
-function _userplot(expr::Expr)
-    if expr.head != :type
-        errror("Must call userplot on a type/immutable expression.  Got: $expr")
-    end
-
-    typename = expr.args[2]
-    funcname = Symbol(lowercase(string(typename)))
-    funcname2 = Symbol(funcname, "!")
-
-    # return a code block with the type definition and convenience plotting methods
-    esc(quote
-        $expr
-        export $funcname, $funcname2
-        $funcname(args...; kw...) = plot($typename(args); kw...)
-        $funcname2(args...; kw...) = plot!($typename(args); kw...)
-    end)
-end
-
-function _userplot(sym::Symbol)
-    _userplot(:(type $sym
-            args
-    end))
-end
-
-
-# ----------------------------------------------------------------------------------
-
 const _series_recipe_deps = Dict()
 
 function series_recipe_dependencies(st::Symbol, deps::Symbol...)
@@ -96,7 +47,7 @@ end
 num_series(x::AMat) = size(x,2)
 num_series(x) = 1
 
-RecipesBase.apply_recipe{T}(d::KW, ::Type{T}, plt::Plot) = throw(MethodError("Unmatched plot recipe: $T"))
+RecipesBase.apply_recipe{T}(d::KW, ::Type{T}, plt::AbstractPlot) = throw(MethodError("Unmatched plot recipe: $T"))
 
 # ---------------------------------------------------------------------------
 
@@ -225,14 +176,14 @@ end
         fr = if yaxis[:scale] == :identity
             0.0
         else
-            NaNMath.min(axis_limits(yaxis)[1], ignoreNaN_minimum(y))
+            NaNMath.min(axis_limits(yaxis)[1], ignorenan_minimum(y))
         end
     end
     newx, newy = zeros(3n), zeros(3n)
     for i=1:n
         rng = 3i-2:3i
         newx[rng] = [x[i], x[i], NaN]
-        newy[rng] = [cycle(fr,i), y[i], NaN]
+        newy[rng] = [_cycle(fr,i), y[i], NaN]
     end
     x := newx
     y := newy
@@ -284,16 +235,16 @@ end
     for rng in iter_segments(args...)
         length(rng) < 2 && continue
         ts = linspace(0, 1, npoints)
-        nanappend!(newx, map(t -> bezier_value(cycle(x,rng), t), ts))
-        nanappend!(newy, map(t -> bezier_value(cycle(y,rng), t), ts))
+        nanappend!(newx, map(t -> bezier_value(_cycle(x,rng), t), ts))
+        nanappend!(newy, map(t -> bezier_value(_cycle(y,rng), t), ts))
         if z != nothing
-            nanappend!(newz, map(t -> bezier_value(cycle(z,rng), t), ts))
+            nanappend!(newz, map(t -> bezier_value(_cycle(z,rng), t), ts))
         end
         if fr != nothing
-            nanappend!(newfr, map(t -> bezier_value(cycle(fr,rng), t), ts))
+            nanappend!(newfr, map(t -> bezier_value(_cycle(fr,rng), t), ts))
         end
         # if lz != nothing
-        #     lzrng = cycle(lz, rng) # the line_z's for this segment
+        #     lzrng = _cycle(lz, rng) # the line_z's for this segment
         #     push!(newlz, 0.0)
         #     append!(newlz, map(t -> lzrng[1+floor(Int, t * (length(rng)-1))], ts))
         # end
@@ -338,9 +289,9 @@ end
     # compute half-width of bars
     bw = d[:bar_width]
     hw = if bw == nothing
-        0.5ignoreNaN_mean(diff(procx))
+        0.5ignorenan_mean(diff(procx))
     else
-        Float64[0.5cycle(bw,i) for i=1:length(procx)]
+        Float64[0.5_cycle(bw,i) for i=1:length(procx)]
     end
 
     # make fillto a vector... default fills to 0
@@ -358,15 +309,15 @@ end
         yi = procy[i]
         if !isnan(yi)
             center = procx[i]
-            hwi = cycle(hw,i)
-            fi = cycle(fillto,i)
+            hwi = _cycle(hw,i)
+            fi = _cycle(fillto,i)
             push!(xseg, center-hwi, center-hwi, center+hwi, center+hwi, center-hwi)
             push!(yseg, yi, fi, fi, yi, yi)
         end
     end
 
     # widen limits out a bit
-    expand_extrema!(axis, widen(ignoreNaN_extrema(xseg.pts)...))
+    expand_extrema!(axis, widen(ignorenan_extrema(xseg.pts)...))
 
     # switch back
     if !isvertical(d)
@@ -414,8 +365,8 @@ end
 
 function _preprocess_binbarlike_weights{T<:AbstractFloat}(::Type{T}, w, wscale::Symbol)
     w_adj = _scale_adjusted_values(T, w, wscale)
-    w_min = ignoreNaN_minimum(w_adj)
-    w_max = ignoreNaN_maximum(w_adj)
+    w_min = ignorenan_minimum(w_adj)
+    w_max = ignorenan_maximum(w_adj)
     baseline = _binbarlike_baseline(w_min, wscale)
     w_adj, baseline
 end
@@ -550,7 +501,7 @@ Plots.@deps stepbins path
 function _auto_binning_nbins{N}(vs::NTuple{N,AbstractVector}, dim::Integer; mode::Symbol = :auto)
     _cl(x) = ceil(Int, NaNMath.max(x, one(x)))
     _iqr(v) = quantile(v, 0.75) - quantile(v, 0.25)
-    _span(v) = ignoreNaN_maximum(v) - ignoreNaN_minimum(v)
+    _span(v) = ignorenan_maximum(v) - ignorenan_minimum(v)
 
     n_samples = length(linearindices(first(vs)))
     # Estimator for number of samples in one row/column of bins along each axis:
@@ -669,7 +620,7 @@ end
     edge_x, edge_y, weights = x, y, z.surf
 
     float_weights = float(weights)
-    if is(float_weights, weights)
+    if float_weights === weights
         float_weights = deepcopy(float_weights)
     end
     for (i, c) in enumerate(float_weights)
@@ -755,9 +706,9 @@ function error_coords(xorig, yorig, ebar)
     x, y = Array(float_extended_type(xorig), 0), Array(Float64, 0)
     # for each point, create a line segment from the bottom to the top of the errorbar
     for i = 1:max(length(xorig), length(yorig))
-        xi = cycle(xorig, i)
-        yi = cycle(yorig, i)
-        ebi = cycle(ebar, i)
+        xi = _cycle(xorig, i)
+        yi = _cycle(yorig, i)
+        ebi = _cycle(ebar, i)
         nanappend!(x, [xi, xi])
         e1, e2 = if istuple(ebi)
             first(ebi), last(ebi)
@@ -810,11 +761,11 @@ function quiver_using_arrows(d::KW)
     x, y = zeros(0), zeros(0)
     for i = 1:max(length(xorig), length(yorig))
         # get the starting position
-        xi = cycle(xorig, i)
-        yi = cycle(yorig, i)
+        xi = _cycle(xorig, i)
+        yi = _cycle(yorig, i)
 
         # get the velocity
-        vi = cycle(velocity, i)
+        vi = _cycle(velocity, i)
         vx, vy = if istuple(vi)
             first(vi), last(vi)
         elseif isscalar(vi)
@@ -847,12 +798,12 @@ function quiver_using_hack(d::KW)
     for i = 1:max(length(xorig), length(yorig))
 
         # get the starting position
-        xi = cycle(xorig, i)
-        yi = cycle(yorig, i)
+        xi = _cycle(xorig, i)
+        yi = _cycle(yorig, i)
         p = P2(xi, yi)
 
         # get the velocity
-        vi = cycle(velocity, i)
+        vi = _cycle(velocity, i)
         vx, vy = if istuple(vi)
             first(vi), last(vi)
         elseif isscalar(vi)
@@ -919,7 +870,7 @@ end
 
 # get the joined vector
 function get_xy(v::AVec{OHLC}, x = 1:length(v))
-    xdiff = 0.3ignoreNaN_mean(abs(diff(x)))
+    xdiff = 0.3ignorenan_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)
@@ -960,7 +911,7 @@ end
 
 # "Sparsity plot... heatmap of non-zero values of a matrix"
 # function spy{T<:Real}(z::AMat{T}; kw...)
-#     mat = map(zi->float(zi!=0), z)'
+#     mat = reshape(map(zi->float(zi!=0), z),1,:)
 #     xn, yn = size(mat)
 #     heatmap(mat; leg=false, yflip=true, aspect_ratio=:equal,
 #         xlim=(0.5, xn+0.5), ylim=(0.5, yn+0.5),
@@ -987,8 +938,8 @@ end
     yflip := true
     aspect_ratio := 1
     rs, cs, zs = findnz(z.surf)
-    xlim := ignoreNaN_extrema(cs)
-    ylim := ignoreNaN_extrema(rs)
+    xlim := ignorenan_extrema(cs)
+    ylim := ignorenan_extrema(rs)
     if d[:markershape] == :none
         markershape := :circle
     end
@@ -1010,7 +961,7 @@ end
 
 "Adds a+bx... straight line over the current plot"
 function abline!(plt::Plot, a, b; kw...)
-    plot!(plt, [ignoreNaN_extrema(plt)...], x -> b + a*x; kw...)
+    plot!(plt, [ignorenan_extrema(plt)...], x -> b + a*x; kw...)
 end
 
 abline!(args...; kw...) = abline!(current(), args...; kw...)
@@ -1054,7 +1005,7 @@ end
     end
 
     library = PlotUtils.color_libraries[cl.args[1]]
-    z = sqrt.((1:15)*(1:20)')
+    z = sqrt.((1:15)*reshape(1:20,1,:))
 
     seriestype := :heatmap
     ticks := nothing
@@ -1078,7 +1029,7 @@ end
     if !(length(grad.args) == 1 && isa(grad.args[1], Symbol))
         error("showgradient takes the name of a color gradient as a Symbol")
     end
-    z = sqrt.((1:15)*(1:20)')
+    z = sqrt.((1:15)*reshape(1:20,1,:))
     seriestype := :heatmap
     ticks := nothing
     legend := false

src/series.jl

@@ -6,7 +6,7 @@
 # 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{F} Union{F, Vector{F}, Matrix{F}}
+const FuncOrFuncs{F} = Union{F, Vector{F}, Matrix{F}}
 
 all3D(d::KW) = trueOrAllTrue(st -> st in (:contour, :contourf, :heatmap, :surface, :wireframe, :contour3d, :image), get(d, :seriestype, :none))
 
@@ -318,7 +318,7 @@ end
 
 @recipe function f{T<:Colorant}(mat::AMat{T})
 	n, m = size(mat)
-	
+
     if is_seriestype_supported(:image)
         seriestype := :image
         SliceIt, 1:m, 1:n, Surface(mat)

src/subplots.jl

@@ -32,7 +32,7 @@ get_subplot(plt::Plot, k) = plt.spmap[k]
 get_subplot(series::Series) = series.d[:subplot]
 
 get_subplot_index(plt::Plot, idx::Integer) = Int(idx)
-get_subplot_index(plt::Plot, sp::Subplot) = findfirst(_ -> _ === sp, plt.subplots)
+get_subplot_index(plt::Plot, sp::Subplot) = findfirst(x -> x === sp, plt.subplots)
 
 series_list(sp::Subplot) = sp.series_list # filter(series -> series.d[:subplot] === sp, sp.plt.series_list)
 

src/types.jl

@@ -8,10 +8,6 @@ const KW = Dict{Symbol,Any}
 
 immutable PlotsDisplay <: Display end
 
-abstract AbstractBackend
-abstract AbstractPlot{T<:AbstractBackend}
-abstract AbstractLayout
-
 # -----------------------------------------------------------
 
 immutable InputWrapper{T}

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 = ignoreNaN_extrema(data)
+  lo, hi = ignorenan_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 = [ignoreNaN_minimum(x), ignoreNaN_maximum(x)]
+  regx = [ignorenan_minimum(x), ignorenan_maximum(x)]
   regy = β * regx + α
   regx, regy
 end
@@ -192,7 +192,7 @@ function iter_segments(args...)
 end
 
 # helpers to figure out if there are NaN values in a list of array types
-anynan(i::Int, args::Tuple) = any(a -> !isfinite(cycle(a,i)), args)
+anynan(i::Int, args::Tuple) = any(a -> !isfinite(_cycle(a,i)), args)
 anynan(istart::Int, iend::Int, args::Tuple) = any(i -> anynan(i, args), istart:iend)
 allnan(istart::Int, iend::Int, args::Tuple) = all(i -> anynan(i, args), istart:iend)
 
@@ -243,19 +243,19 @@ notimpl() = error("This has not been implemented yet")
 isnothing(x::Void) = true
 isnothing(x) = false
 
-cycle(wrapper::InputWrapper, idx::Int) = wrapper.obj
-cycle(wrapper::InputWrapper, idx::AVec{Int}) = wrapper.obj
+_cycle(wrapper::InputWrapper, idx::Int) = wrapper.obj
+_cycle(wrapper::InputWrapper, idx::AVec{Int}) = wrapper.obj
 
-cycle(v::AVec, idx::Int) = v[mod1(idx, length(v))]
-cycle(v::AMat, idx::Int) = size(v,1) == 1 ? v[1, mod1(idx, size(v,2))] : v[:, mod1(idx, size(v,2))]
-cycle(v, idx::Int)       = v
+_cycle(v::AVec, idx::Int) = v[mod1(idx, length(v))]
+_cycle(v::AMat, idx::Int) = size(v,1) == 1 ? v[1, mod1(idx, size(v,2))] : v[:, mod1(idx, size(v,2))]
+_cycle(v, idx::Int)       = v
 
-cycle(v::AVec, indices::AVec{Int}) = map(i -> cycle(v,i), indices)
-cycle(v::AMat, indices::AVec{Int}) = map(i -> cycle(v,i), indices)
-cycle(v, indices::AVec{Int})       = fill(v, length(indices))
+_cycle(v::AVec, indices::AVec{Int}) = map(i -> _cycle(v,i), indices)
+_cycle(v::AMat, indices::AVec{Int}) = map(i -> _cycle(v,i), indices)
+_cycle(v, indices::AVec{Int})       = fill(v, length(indices))
 
-cycle(grad::ColorGradient, idx::Int) = cycle(grad.colors, idx)
-cycle(grad::ColorGradient, indices::AVec{Int}) = cycle(grad.colors, indices)
+_cycle(grad::ColorGradient, idx::Int) = _cycle(grad.colors, idx)
+_cycle(grad::ColorGradient, indices::AVec{Int}) = _cycle(grad.colors, indices)
 
 makevec(v::AVec) = v
 makevec{T}(v::T) = T[v]
@@ -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 = ignoreNaN_extrema(x)
+    e1, e2 = ignorenan_extrema(x)
     lims[1] = NaNMath.min(lims[1], e1)
     lims[2] = NaNMath.max(lims[2], e2)
   # catch err
@@ -292,7 +292,7 @@ function _expand_limits(lims, x)
   nothing
 end
 
-expand_data(v, n::Integer) = [cycle(v, i) for i=1:n]
+expand_data(v, n::Integer) = [_cycle(v, i) for i=1:n]
 
 # if the type exists in a list, replace the first occurence.  otherwise add it to the end
 function addOrReplace(v::AbstractVector, t::DataType, args...; kw...)
@@ -324,7 +324,7 @@ function replaceAliases!(d::KW, aliases::Dict{Symbol,Symbol})
   end
 end
 
-createSegments(z) = collect(repmat(z',2,1))[2:end]
+createSegments(z) = collect(repmat(reshape(z,1,:),2,1))[2:end]
 
 Base.first(c::Colorant) = c
 Base.first(x::Symbol) = x
@@ -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 = ignoreNaN_extrema(v)
+  vmin, vmax = ignorenan_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 = ignoreNaN_extrema(x)
-    ymin, ymax = ignoreNaN_extrema(y)
+    xmin, xmax = ignorenan_extrema(x)
+    ymin, ymax = ignorenan_extrema(y)
     r = 0.5 * NaNMath.min(xmax - xmin, ymax - ymin)
-    ignoreNaN_extrema(r)
+    ignorenan_extrema(r)
 end
 
 function convert_to_polar(x, y, r_extrema = calc_r_extrema(x, y))
@@ -355,8 +355,8 @@ function convert_to_polar(x, y, r_extrema = calc_r_extrema(x, y))
     x = zeros(n)
     y = zeros(n)
     for i in 1:n
-        x[i] = cycle(r,i) * cos(cycle(phi,i))
-        y[i] = cycle(r,i) * sin(cycle(phi,i))
+        x[i] = _cycle(r,i) * cos.(_cycle(phi,i))
+        y[i] = _cycle(r,i) * sin.(_cycle(phi,i))
     end
     x, y
 end
@@ -469,7 +469,7 @@ ok(tup::Tuple) = ok(tup...)
 # compute one side of a fill range from a ribbon
 function make_fillrange_side(y, rib)
     frs = zeros(length(y))
-    for (i, (yi, ri)) in enumerate(zip(y, Base.cycle(rib)))
+    for (i, (yi, ri)) in enumerate(zip(y, Base.Iterators.cycle(rib)))
         frs[i] = yi + ri
     end
     frs
@@ -645,7 +645,7 @@ 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) + ignoreNaN_maximum(v))
+extendSeriesByOne(v::AVec, n::Integer = 1)       = isempty(v) ? (1:n) : vcat(v, (1:n) + ignorenan_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) = ignoreNaN_minimum([ignoreNaN_minimum(series.d[:x]) for series in plt.series_list])
+xmin(plt::Plot) = ignorenan_minimum([ignorenan_minimum(series.d[:x]) for series in plt.series_list])
 "Largest x in plot"
-xmax(plt::Plot) = ignoreNaN_maximum([ignoreNaN_maximum(series.d[:x]) for series in plt.series_list])
+xmax(plt::Plot) = ignorenan_maximum([ignorenan_maximum(series.d[:x]) for series in plt.series_list])
 
 "Extrema of x-values in plot"
-ignoreNaN_extrema(plt::Plot) = (xmin(plt), xmax(plt))
+ignorenan_extrema(plt::Plot) = (xmin(plt), xmax(plt))

test/imgcomp.jl

@@ -13,7 +13,7 @@ try
 end
 
 
-# using Plots # reexported by StatPlots
+using Plots
 using StatPlots
 using FactCheck
 using Glob
@@ -24,7 +24,7 @@ default(size=(500,300))
 # TODO: use julia's Condition type and the wait() and notify() functions to initialize a Window, then wait() on a condition that
 #       is referenced in a button press callback (the button clicked callback will call notify() on that condition)
 
-const _current_plots_version = v"0.11.3"
+const _current_plots_version = v"0.12.0"
 
 
 function image_comparison_tests(pkg::Symbol, idx::Int; debug = false, popup = isinteractive(), sigma = [1,1], eps = 1e-2)
@@ -99,7 +99,7 @@ function image_comparison_facts(pkg::Symbol;
   for i in 1:length(Plots._examples)
     i in skip && continue
     if only == nothing || i in only
-      @fact image_comparison_tests(pkg, i, debug=debug, sigma=sigma, eps=eps) |> success --> true
+      @fact @eval(image_comparison_tests(Symbol(String(Symbol($pkg))[7:end]), $i, debug=$debug, sigma=$sigma, eps=$eps)) |> success --> true
     end
   end
 end

test/runtests.jl

@@ -7,19 +7,6 @@ srand(1234)
 default(show=false, reuse=true)
 img_eps = isinteractive() ? 1e-2 : 10e-2
 
-# facts("Gadfly") do
-#     @fact gadfly() --> Plots.GadflyBackend()
-#     @fact backend() --> Plots.GadflyBackend()
-#
-#     @fact typeof(plot(1:10)) --> Plots.Plot{Plots.GadflyBackend}
-#     @fact plot(Int[1,2,3], rand(3)) --> not(nothing)
-#     @fact plot(sort(rand(10)), rand(Int, 10, 3)) --> not(nothing)
-#     @fact plot!(rand(10,3), rand(10,3)) --> not(nothing)
-#
-#     image_comparison_facts(:gadfly, skip=[4,6,23,24,27], eps=img_eps)
-# end
-
-
 facts("GR") do
     @fact gr() --> Plots.GRBackend()
     @fact backend() --> Plots.GRBackend()
@@ -35,6 +22,13 @@ facts("PyPlot") do
     image_comparison_facts(:pyplot, eps=img_eps)
 end
 
+facts("UnicodePlots") do
+    @fact unicodeplots() --> Plots.UnicodePlotsBackend()
+    @fact backend() --> Plots.UnicodePlotsBackend()
+
+    # lets just make sure it runs without error
+    @fact isa(plot(rand(10)), Plots.Plot) --> true
+end
 
 # The plotlyjs testimages return a connection error on travis:
 # connect: connection refused (ECONNREFUSED)
@@ -105,13 +99,18 @@ end
 # end
 
 
-facts("UnicodePlots") do
-    @fact unicodeplots() --> Plots.UnicodePlotsBackend()
-    @fact backend() --> Plots.UnicodePlotsBackend()
+# facts("Gadfly") do
+#     @fact gadfly() --> Plots.GadflyBackend()
+#     @fact backend() --> Plots.GadflyBackend()
+#
+#     @fact typeof(plot(1:10)) --> Plots.Plot{Plots.GadflyBackend}
+#     @fact plot(Int[1,2,3], rand(3)) --> not(nothing)
+#     @fact plot(sort(rand(10)), rand(Int, 10, 3)) --> not(nothing)
+#     @fact plot!(rand(10,3), rand(10,3)) --> not(nothing)
+#
+#     image_comparison_facts(:gadfly, skip=[4,6,23,24,27], eps=img_eps)
+# end
 
-    # lets just make sure it runs without error
-    @fact isa(plot(rand(10)), Plots.Plot) --> true
-end
 
 
 
@@ -121,12 +120,12 @@ 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 Plots.ignoreNaN_extrema(axis) --> (0.5,1.5)
+    @fact Plots.ignorenan_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 Plots.ignoreNaN_extrema(axis) --> (0.5, 7.5)
+    @fact Plots.ignorenan_extrema(axis) --> (0.5, 7.5)
 end
 
 

test/travis_commands.jl

@@ -1,4 +1,4 @@
-Pkg.clone("ImageMagick")
+Pkg.add("ImageMagick")
 Pkg.build("ImageMagick")
 
 Pkg.clone("GR")