make linspace arg a float

NEWS.md

@@ -6,27 +6,11 @@
 - All new development should target 0.12!
 - Minor version 0.11 is the last one to support Julia 0.5!!
 	- Critical bugfixes only
-    - `backports` branch is for Julia 0.5
+    - `backports` branch is for Julia 0.4
 
 ---
 ## (current master)
 
-## 0.12.4
-
-- added a new `framestyle` argument with choices: :box, :semi, :axes, :grid and :none
-- changed the default bar width to 0.8
-- added working ribbon to plotly backend
-- ensure that automatic ticks always generate 4 to 8 ticks
-- group now groups keyword arguments of the same length as the input
-- allow passing DateTime objects as ticks
-- allow specifying the number of ticks as an integre
-- fix bug on errorbars in gr
-- fixed some but not all world age issues
-- better margin with room for text
-- added a `match` option for linecolor
-- better error message un unsupported series types
-- add a 'stride' keyword for the pyplot backend
-
 ## 0.12.3
 
 - new grid line style defaults

src/Plots.jl

@@ -1,4 +1,4 @@
-__precompile__(false)
+__precompile__(true)
 
 module Plots
 

src/arg_desc.jl

@@ -21,7 +21,7 @@ const _arg_desc = KW(
 :markerstrokewidth 	=> "Number. Width of the marker stroke (border. in pixels)",
 :markerstrokecolor 	=> "Color Type. Color of the marker stroke (border).  `:match` will take the value from `:foreground_color_subplot`.",
 :markerstrokealpha 	=> "Number in [0,1]. The alpha/opacity override for the marker stroke (border).  `nothing` (the default) means it will take the alpha value of markerstrokecolor.",
-:bins              	=> "Integer, NTuple{2,Integer}, AbstractVector or Symbol. Default is :auto (the Freedman-Diaconis rule). For histogram-types, defines the approximate number of bins to aim for, or the auto-binning algorithm to use (:sturges, :sqrt, :rice, :scott or :fd). For fine-grained control pass a Vector of break values, e.g. `linspace(extrema(x)..., 25)`",
+:bins              	=> "Integer, NTuple{2,Integer}, AbstractVector or Symbol. Default is :auto. For histogram-types, defines the approximate number of bins to aim for, or the auto-binning algorithm to use (:sturges, :sqrt, :rice, :scott or :fd). For fine-grained control pass a Vector of break values, e.g. `linspace(extrema(x)..., 25)`",
 :smooth            	=> "Bool.  Add a regression line?",
 :group             	=> "AbstractVector. Data is split into a separate series, one for each unique value in `group`.",
 :x                 	=> "Various. Input data. First Dimension",
@@ -40,7 +40,7 @@ const _arg_desc = KW(
 :ribbon            	=> "Number or AbstractVector.  Creates a fillrange around the data points.",
 :quiver            	=> "AbstractVector or 2-Tuple of vectors.  The directional vectors U,V which specify velocity/gradient vectors for a quiver plot.",
 :arrow             	=> "nothing (no arrows), Bool (if true, default arrows), Arrow object, or arg(s) that could be style or head length/widths.  Defines arrowheads that should be displayed at the end of path line segments (just before a NaN and the last non-NaN point).  Used in quiverplot, streamplot, or similar.",
-:normalize         	=> "Bool or Symbol. Histogram normalization mode. Possible values are: false/:none (no normalization, default), true/:pdf (normalize to a discrete Probability Density Function, where the total area of the bins is 1), :probability (bin heights sum to 1) and :density (the area of each bin, rather than the height, is equal to the counts - useful for uneven bin sizes).",
+:normalize         	=> "Bool or Symbol. Histogram normalization mode. Possible values are: false/:none (no normalization, default), true/:pdf (normalize to a PDF with integral of 1) and :density (only normalize in respect to bin sizes).",
 :weights           	=> "AbstractVector. Used in histogram types for weighted counts.",
 :contours          	=> "Bool. Add contours to the side-grids of 3D plots?  Used in surface/wireframe.",
 :match_dimensions  	=> "Bool. For heatmap types... should the first dimension of a matrix (rows) correspond to the first dimension of the plot (x-axis)?  The default is false, which matches the behavior of Matplotlib, Plotly, and others.  Note: when passing a function for z, the function should still map `(x,y) -> z`.",

src/args.jl

@@ -80,13 +80,9 @@ const _typeAliases = Dict{Symbol,Symbol}(
 
 add_non_underscore_aliases!(_typeAliases)
 
-const _histogram_like = [:histogram, :barhist, :barbins]
-const _line_like = [:line, :path, :steppre, :steppost]
-const _surface_like = [:contour, :contourf, :contour3d, :heatmap, :surface, :wireframe, :image]
-
-like_histogram(seriestype::Symbol) = seriestype in _histogram_like
-like_line(seriestype::Symbol)      = seriestype in _line_like
-like_surface(seriestype::Symbol)   = seriestype in _surface_like
+like_histogram(seriestype::Symbol) = seriestype in (:histogram, :barhist, :barbins)
+like_line(seriestype::Symbol)      = seriestype in (:line, :path, :steppre, :steppost)
+like_surface(seriestype::Symbol)   = seriestype in (:contour, :contourf, :contour3d, :heatmap, :surface, :wireframe, :image)
 
 is3d(seriestype::Symbol) = seriestype in _3dTypes
 is3d(series::Series) = is3d(series.d)
@@ -193,8 +189,6 @@ const _framestyleAliases = Dict{Symbol, Symbol}(
     :transparent        => :semi,
     :semitransparent    => :semi,
 )
-
-const _bar_width = 0.8
 # -----------------------------------------------------------------------------
 
 const _series_defaults = KW(
@@ -246,7 +240,6 @@ const _series_defaults = KW(
     :primary            => true,     # when true, this "counts" as a series for color selection, etc.  the main use is to allow
                                      #     one logical series to be broken up (path and markers, for example)
     :hover              => nothing,  # text to display when hovering over the data points
-    :stride             => (1,1),    # array stride for wireframe/surface, the first element is the row stride and the second is the column stride.
 )
 
 
@@ -507,7 +500,6 @@ add_aliases(:series_annotations, :series_ann, :seriesann, :series_anns, :seriesa
 add_aliases(:html_output_format, :format, :fmt, :html_format)
 add_aliases(:orientation, :direction, :dir)
 add_aliases(:inset_subplots, :inset, :floating)
-add_aliases(:stride, :wirefame_stride, :surface_stride, :surf_str, :str)
 add_aliases(:gridlinewidth, :gridwidth, :grid_linewidth, :grid_width, :gridlw, :grid_lw)
 add_aliases(:gridstyle, :grid_style, :gridlinestyle, :grid_linestyle, :grid_ls, :gridls)
 add_aliases(:framestyle, :frame_style, :frame, :axesstyle, :axes_style, :boxstyle, :box_style, :box, :borderstyle, :border_style, :border)
@@ -1280,8 +1272,6 @@ end
 
 # -----------------------------------------------------------------------------
 
-has_black_border_for_default(st) = error("The seriestype attribute only accepts Symbols, you passed the $(typeof(st)) $st.")
-has_black_border_for_default(st::Function) = error("The seriestype attribute only accepts Symbols, you passed the function $st.")
 function has_black_border_for_default(st::Symbol)
     like_histogram(st) || st in (:hexbin, :bar, :shape)
 end

src/axes.jl

@@ -365,7 +365,7 @@ function expand_extrema!(sp::Subplot, d::KW)
 
         bw = d[:bar_width]
         if bw == nothing
-            bw = d[:bar_width] = _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))

src/backends/gr.jl

@@ -580,10 +580,8 @@ function gr_get_ticks_size(ticks, i)
 end
 
 function _update_min_padding!(sp::Subplot{GRBackend})
-    if !haskey(ENV, "GKSwstype")
-        if isijulia() || (isdefined(Main, :Juno) && Juno.isactive())
-            ENV["GKSwstype"] = "svg"
-        end
+    if !haskey(ENV, "GKSwstype") && isijulia()
+        ENV["GKSwstype"] = "svg"
     end
     # Add margin given by the user
     leftpad   = 2mm  + sp[:left_margin]

src/backends/pyplot.jl

@@ -32,7 +32,6 @@ const _pyplot_attr = merge_with_base_supported([
     :inset_subplots,
     :dpi,
     :colorbar_title,
-    :stride,
     :framestyle,
   ])
 const _pyplot_seriestype = [
@@ -705,8 +704,8 @@ function py_add_series(plt::Plot{PyPlotBackend}, series::Series)
             handle = ax[st == :surface ? :plot_surface : :plot_wireframe](x, y, z;
                 label = series[:label],
                 zorder = series[:series_plotindex],
-                rstride = series[:stride][1],
-                cstride = series[:stride][2],
+                rstride = 1,
+                cstride = 1,
                 linewidth = py_dpi_scale(plt, series[:linewidth]),
                 edgecolor = py_linecolor(series),
                 extrakw...

src/components.jl

@@ -89,7 +89,7 @@ end
 "create a shape by picking points around the unit circle.  `n` is the number of point/sides, `offset` is the starting angle"
 function makeshape(n; offset = -0.5, radius = 1.0)
     z = offset * π
-    Shape(partialcircle(z, z + 2π, n+1, radius))
+    Shape(partialcircle(z, z + 2π, n+1., radius))
 end
 
 

src/examples.jl

@@ -290,7 +290,7 @@ PlotExample("Layouts, margins, label rotation, title location",
     [:(begin
         plot(rand(100,6),layout=@layout([a b; c]),title=["A" "B" "C"],
                         title_location=:left, left_margin=[20mm 0mm],
-                        bottom_margin=10px, xrotation=60)
+                        bottom_margin=50px, xrotation=60)
     end)]
 ),
 

src/recipes.jl

@@ -289,7 +289,7 @@ end
     # compute half-width of bars
     bw = d[:bar_width]
     hw = if bw == nothing
-        0.5*_bar_width*ignorenan_mean(diff(procx))
+        0.5ignorenan_mean(diff(procx))
     else
         Float64[0.5_cycle(bw,i) for i=1:length(procx)]
     end
@@ -497,7 +497,6 @@ end
 end
 Plots.@deps stepbins path
 
-wand_edges(x...) = (warn("Load the StatPlots package in order to use :wand bins. Defaulting to :auto", once = true); :auto)
 
 function _auto_binning_nbins{N}(vs::NTuple{N,AbstractVector}, dim::Integer; mode::Symbol = :auto)
     _cl(x) = ceil(Int, NaNMath.max(x, one(x)))
@@ -511,10 +510,8 @@ function _auto_binning_nbins{N}(vs::NTuple{N,AbstractVector}, dim::Integer; mode
     v = vs[dim]
 
     if mode == :auto
-        mode = :fd
-    end
-
-    if mode == :sqrt  # Square-root choice
+        30
+    elseif mode == :sqrt  # Square-root choice
         _cl(sqrt(n))
     elseif mode == :sturges  # Sturges' formula
         _cl(log2(n)) + 1
@@ -524,11 +521,9 @@ function _auto_binning_nbins{N}(vs::NTuple{N,AbstractVector}, dim::Integer; mode
         _cl(_span(v) / (3.5 * std(v) / n^(1/3)))
     elseif mode == :fd  # Freedman–Diaconis rule
         _cl(_span(v) / (2 * _iqr(v) / n^(1/3)))
-    elseif mode == :wand
-        wand_edges(v)  # this makes this function not type stable, but the type instability does not propagate
     else
         error("Unknown auto-binning mode $mode")
-    end
+    end::Int
 end
 
 _hist_edge{N}(vs::NTuple{N,AbstractVector}, dim::Integer, binning::Integer) = StatsBase.histrange(vs[dim], binning, :left)
@@ -555,7 +550,7 @@ end
 
 
 @recipe function f(::Type{Val{:histogram}}, x, y, z)
-    seriestype := length(y) > 1e6 ? :stephist : :barhist
+    seriestype := :barhist
     ()
 end
 @deps histogram barhist

test/imgcomp.jl

@@ -23,7 +23,7 @@ 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"0.12.4"
+const _current_plots_version = v"0.12.3"
 
 
 function image_comparison_tests(pkg::Symbol, idx::Int; debug = false, popup = isinteractive(), sigma = [1,1], eps = 1e-2)