fix all errors reported when building docs

docs/make.jl

@@ -25,6 +25,7 @@ makedocs(
             "Shapes" => "gallery/shapes.md",
         ],
         "Library" => Any[
+            "Gadfly" => "lib/gadfly.md",
             "Geometries" => "lib/geometries.md",
             "Guides" => "lib/guides.md",
             "Statistics" => "lib/statistics.md",

docs/src/dev/pipeline.md

@@ -46,10 +46,10 @@ The specification of each layer has
 
 All layers of a plot share the same
 
-- [Coordinates](@ref) for the geometry (e.g. cartesian, polar, etc.)
-- axis [Scales](@ref) (e.g. loglog, semilog, etc.)
-- plot-wise [Statistics](@ref) (optional) to be applied to all layers
-- [Guides](@ref)
+- [Coordinates](@ref lib_coord) for the geometry (e.g. cartesian, polar, etc.)
+- axis [Scales](@ref lib_scale) (e.g. loglog, semilog, etc.)
+- plot-wise [Statistics](@ref lib_stat) (optional) to be applied to all layers
+- [Guides](@ref lib_guide)
 
 A full plot specification must describe these shared elements as well as all the layer specifications.
 In the example above, we see that only the data source, statistics, geometry, and mapping are specified.
@@ -75,11 +75,11 @@ Once a full plot specification is filled out, the rendering process proceeds as
 
 1. For each layer in the plot, we first map subsets of the data source to a `Data` object. The `Price` and `Cut` columns of the `diamond` dataset are mapped to the `:x` and `:color` fields of `Data`, respectively.
 
-2. Scales are applied to the data to obtain plottable aesthetics. [Scale.x_continuous](@ref) keeps the values of `df[:Price]` unchanged, while [Scale.color_discrete_hue](@ref) maps the unique elements of `df[:Cut]` (an array of strings) to actual color values.
+2. Scales are applied to the data to obtain plottable aesthetics. [`Scale.x_continuous`](@ref) keeps the values of `df[:Price]` unchanged, while [`Scale.color_discrete_hue`](@ref) maps the unique elements of `df[:Cut]` (an array of strings) to actual color values.
 
-3. The aesthetics are transformed by layer-wise and plot-wise statistics, in order. [Stat.histogram](@ref) replaces the `x` field of the aesthetics with bin positions, and sets the `y` field with the corresponding counts.
+3. The aesthetics are transformed by layer-wise and plot-wise statistics, in order. [`Stat.histogram`](@ref) replaces the `x` field of the aesthetics with bin positions, and sets the `y` field with the corresponding counts.
 
-4. Using the position aesthetics from all layers, we create a Compose context with a coordinate system that fits the data to screen coordinates. [Coord.cartesian](@ref) creates a Compose context that maps a vertical distance of `3000` counts to about two inches in the rendered plot.
+4. Using the position aesthetics from all layers, we create a Compose context with a coordinate system that fits the data to screen coordinates. [`Coord.cartesian`](@ref) creates a Compose context that maps a vertical distance of `3000` counts to about two inches in the rendered plot.
 
 5. Each layer renders its own geometry.
 

docs/src/gallery/scales.md

@@ -69,8 +69,9 @@ plot(x=rand(12), y=rand(12), color=repeat([1,2,3], outer=[4]),
 
 !!! note
 
-    To set a default color scale for plots, you can set it in the current
-    [Theme](@ref) using `push_theme`, using `style` to modify the current theme.
+    To set a default color scale for plots, you can set it in the current Theme
+    (see [Themes](@ref)) using `push_theme`, using `style` to modify the
+    current theme.
 
     ```
     Gadfly.push_theme(style(discrete_color_scale=Scale.color_discrete(gen_colors)))

docs/src/lib/coordinates.md

@@ -2,7 +2,7 @@
 Author = "Tamas Nagy"
 ```
 
-# Coordinates
+# [Coordinates](@id lib_coord)
 
 Coordinate systems are mappings between a coordinate space and the 2D rendered output.
 

docs/src/lib/gadfly.md

@@ -0,0 +1,9 @@
+```@meta
+Author = "Ben J. Arthur"
+```
+
+# Gadfly
+
+```@autodocs
+Modules = [Gadfly]
+```

docs/src/lib/geometries.md

@@ -2,7 +2,7 @@
 Author = "Daniel C. Jones"
 ```
 
-# Geometries
+# [Geometries](@id lib_geom)
 
 Geometries are responsible for actually doing the drawing. A geometry takes
 as input one or more aesthetics, and used data bound to these aesthetics to

docs/src/lib/guides.md

@@ -2,9 +2,9 @@
 Author = "Daniel C. Jones"
 ```
 
-# Guides
+# [Guides](@id lib_guide)
 
-Very similar to [Geometries](@ref) are guides, which draw graphics supporting the
+Very similar to Geometries are guides, which draw graphics supporting the
 actual visualization, such as axis ticks and labels and color keys. The major
 distinction is that geometries always draw within the rectangular plot frame,
 while guides have some special layout considerations.

docs/src/lib/scales.md

@@ -2,9 +2,9 @@
 Author = "Daniel C. Jones"
 ```
 
-# Scales
+# [Scales](@id lib_scale)
 
-Scales, similarly to [Statistics](@ref), apply a transformation to the original
+Scales, similarly to Statistics, apply a transformation to the original
 data, typically mapping one aesthetic to the same aesthetic, while retaining
 the original value. For example, the Scale.x_log10 aesthetic maps the
  `x` aesthetic back to the `x` aesthetic after applying a log10 transformation,

docs/src/lib/statistics.md

@@ -2,11 +2,11 @@
 Author = "Daniel C. Jones"
 ```
 
-# Statistics
+# [Statistics](@id lib_stat)
 
 Statistics are functions taking as input one or more aesthetics, operating on
 those values, then output to one or more aesthetics. For example, drawing of
-boxplots typically uses the boxplot statistic ([Stat.boxplot](@ref)) that takes
+boxplots typically uses the boxplot statistic ([`Stat.boxplot`](@ref)) that takes
 as input the `x` and `y` aesthetic, and outputs the middle, and upper and lower
 hinge, and upper and lower fence aesthetics.
 

docs/src/man/plotting.md

@@ -4,11 +4,12 @@ Author = "Daniel C. Jones"
 
 # Plotting
 
-Most interaction with Gadfly is through the `plot` function. Plots are described
-by binding data to **aesthetics**, and specifying a number of plot elements
-including [Scales](@ref), [Coordinates](@ref), [Guides](@ref), and [Geometries](@ref).
-Aesthetics are a set of special named variables that are mapped to plot
-geometry. How this mapping occurs is defined by the plot elements.
+Most interaction with Gadfly is through the `plot` function. Plots are
+described by binding data to **aesthetics**, and specifying a number of plot
+elements including [Scales](@ref lib_scale), [Coordinates](@ref lib_coord),
+[Guides](@ref lib_guide), and [Geometries](@ref lib_geom).  Aesthetics are a
+set of special named variables that are mapped to plot geometry. How this
+mapping occurs is defined by the plot elements.
 
 This "grammar of graphics" approach tries to avoid arcane incantations and
 special cases, instead approaching the problem as if one were drawing a wiring

src/Gadfly.jl

@@ -100,19 +100,17 @@ const gadflyjs = joinpath(dirname(Base.source_path()), "gadfly.js")
 # Set prefereed canvas size when rendering a plot without an explicit call to
 # `draw`.
 """
-```
-set_default_plot_size(width::Compose.MeasureOrNumber, height::Compose.MeasureOrNumber)
-```
+    set_default_plot_size(width::Compose.MeasureOrNumber, height::Compose.MeasureOrNumber)
+
 Sets preferred canvas size when rendering a plot without an explicit call to draw
 """
 set_default_plot_size(width::Compose.MeasureOrNumber, height::Compose.MeasureOrNumber) =
         Compose.set_default_graphic_size(width, height)
 
 
 """
-```
-set_default_plot_format(fmt::Symbol)
-```
+    set_default_plot_format(fmt::Symbol)
+
 Sets the default plot format
 """
 set_default_plot_format(fmt::Symbol) = Compose.set_default_graphic_format(fmt)
@@ -135,10 +133,9 @@ copy(l::Layer) = Layer(l)
 
 
 """
-```
-layer(data_source::@compat(Union{AbstractDataFrame, (@compat Void)}),
-               elements::ElementOrFunction...; mapping...)
-```
+    layer(data_source::@compat(Union{AbstractDataFrame, (@compat Void)}),
+          elements::ElementOrFunction...; mapping...)
+
 Creates layers based on elements
 
 ### Args
@@ -273,8 +270,8 @@ const ElementOrFunctionOrLayers = Union{ElementOrFunction, Vector{Layer}}
 
 """
 ```
-    function plot(data_source::@compat(Union{AbstractMatrix, AbstractDataFrame}),
-              elements::ElementOrFunctionOrLayers...; mapping...)
+    plot(data_source::@compat(Union{AbstractMatrix, AbstractDataFrame}),
+         elements::ElementOrFunctionOrLayers...; mapping...)
 ```
 
 Create a new plot.
@@ -322,10 +319,9 @@ end
 #   A Plot object.
 #
 """
-```
-function plot(data_source::@compat(Union{(@compat Void), AbstractMatrix, AbstractDataFrame}),
-              mapping::Dict, elements::ElementOrFunctionOrLayers...)
-```
+    plot(data_source::@compat(Union{(@compat Void), AbstractMatrix, AbstractDataFrame}),
+         mapping::Dict, elements::ElementOrFunctionOrLayers...)
+
 The old fashioned (pre named arguments) version of plot.
 
 This version takes an explicit mapping dictionary, mapping aesthetics symbols
@@ -856,9 +852,8 @@ end
 
 # A convenience version of Compose.draw that let's you skip the call to render.
 """
-```
-draw(backend::Compose.Backend, p::Plot)
-```
+    draw(backend::Compose.Backend, p::Plot)
+
 A convenience version of Compose.draw without having to call render
 
 ### Args
@@ -935,9 +930,9 @@ gridstack([p1 p1; p1 p1])
 gridstack(Union{Plot,Compose.Context}[p1 p2; p2 p1])
 ```
 """
-_gridstack(ps::Matrix) = gridstack(map(p->typeof(p)==Plot ? render(p) : p, ps))
 gridstack(ps::Matrix{Plot}) = _gridstack(ps)
 gridstack(ps::Matrix{Union{Plot,Context}}) = _gridstack(ps)
+_gridstack(ps::Matrix) = gridstack(map(p->typeof(p)==Plot ? render(p) : p, ps))
 
 # show functions for all supported compose backends.
 

src/geom/bar.jl

@@ -46,7 +46,7 @@ const bar = BarGeometry
 """
     Geom.histogram[(; position, orientation, bincount, minbincount, maxbincount, density)]
 
-Draw histograms. An alias for [Geom.bar](@ref) with [Stat.histogram](@ref).
+Draw histograms. An alias for [`Geom.bar`](@ref) with [`Stat.histogram`](@ref).
 
 # Aesthetics
 - `x`: Sample to draw histogram from.

src/geom/boxplot.jl

@@ -26,7 +26,7 @@ Aesthetics used directly:
 - `upper_fence`
 - `outliers`
 
-With default statistic [Stat.boxplot](@ref), only the following aesthetics need to be
+With default statistic [`Stat.boxplot`](@ref), only the following aesthetics need to be
 defined:
 
 - `x` (optional): Group categorically on the X-axis.

src/geom/hexbin.jl

@@ -20,8 +20,8 @@ Bin data into tiled hexagonal bins and color by count.
 - `xsize`
 - `ysize`
 
-By default [Stat.hexbin](@ref) is applied which bins `x` and `y` observations and
-colors hexagons according to count. To override this, pass [Stat.identity](@ref) to
+By default [`Stat.hexbin`](@ref) is applied which bins `x` and `y` observations and
+colors hexagons according to count. To override this, pass [`Stat.identity`](@ref) to
 `plot` and manually bind the `color` aesthetic.
 
 # Arguments

src/geom/line.jl

@@ -63,7 +63,7 @@ end
     Geom.path
 
 Draw lines between points in the order they appear in the data. This is an
-alias for [Geom.line](@ref) with `preserve_order=true`.
+alias for [`Geom.line`](@ref) with `preserve_order=true`.
 
 # Aesthetics
 - `x`: X-axis position.
@@ -75,8 +75,8 @@ path() = LineGeometry(preserve_order=true)
 """
     Geom.density[(; bandwidth)]
 
-Draw a kernel density estimate from data. An alias for [Geom.line](@ref) with
-[Stat.density](@ref).
+Draw a kernel density estimate from data. An alias for [`Geom.line`](@ref) with
+[`Stat.density`](@ref).
 
 # Aesthetics
 - `x`: Sample to draw density estimate from.
@@ -91,23 +91,23 @@ density(; bandwidth::Real=-Inf) =
 """
     Geom.density2d[(; bandwidth, levels)]
 
-Draw a kernel density estimate from data. An alias for [Geom.contour](@ref) with
-[Stat.density2d](@ref).
+Draw a kernel density estimate from data. An alias for [`Geom.contour`](@ref) with
+[`Stat.density2d`](@ref).
 
 # Aesthetics
 - `x`, `y`: Sample to draw density estimate from.
 
 # Arguments
-- `bandwidth`:  See [Geom.density](@ref).
-- `levels`:  See [Geom.contour](@ref).
+- `bandwidth`:  See [`Geom.density`](@ref).
+- `levels`:  See [`Geom.contour`](@ref).
 """
 density2d(; bandwidth::Tuple{Real,Real}=(-Inf,-Inf), levels=15) =
     LineGeometry(Gadfly.Stat.density2d(bandwidth=bandwidth, levels=levels); preserve_order=true)
 
 """
     Geom.smooth[(; method, smoothing)]
 
-Plot a smooth function estimated from data. An alias for [Geom.line](@ref) with [Stat.smooth](@ref).
+Plot a smooth function estimated from data. An alias for [`Geom.line`](@ref) with [`Stat.smooth`](@ref).
 
 # Aesthetics
 - `x`: Predictor data.
@@ -127,8 +127,8 @@ smooth(; method::Symbol=:loess, smoothing::Float64=0.75) =
 """
     Geom.step[(; direction)]
 
-Connect points using a stepwise function. Equivalent to [Geom.line](@ref) with
-[Stat.step](@ref).
+Connect points using a stepwise function. Equivalent to [`Geom.line`](@ref) with
+[`Stat.step`](@ref).
 
 # Aesthetics
 - `x`: Point x-coordinate.

src/geom/rectbin.jl

@@ -43,7 +43,7 @@ const rectbin = RectangularBinGeometry
 
 Bin data in rectangles and indicate density with color. As in heatmaps, etc.
 
-An alias for [Geom.rectbin](@ref) with [Stat.histogram2d](@ref).
+An alias for [`Geom.rectbin`](@ref) with [`Stat.histogram2d`](@ref).
 
 # Aesthetics
 - `x`: Observations to be binned and plotted on the x coordinate.

src/geom/subplot.jl

@@ -90,7 +90,7 @@ or row of subplots is drawn, if both, a grid.
 
 # Arguments
 
-Unlike most geometries, [Geom.subplot_grid](@ref) is typically passed one or more
+Unlike most geometries, [`Geom.subplot_grid`](@ref) is typically passed one or more
 parameters. The constructor works for the most part like the `layer` function.
 Arbitrary plot elements may be passed, while aesthetic bindings are inherited
 from the parent plot.

src/geom/violin.jl

@@ -18,7 +18,7 @@ Aesthetics used directly:
 - `width`: Density at a given `y` value.
 - `color` (optional): Violin color.  A suitable discrete variable is needed here. See example below.
 
-With the default statistic [Stat.violin](@ref), only the following need be defined:
+With the default statistic [`Stat.violin`](@ref), only the following need be defined:
 
 - `x` (optional): Group categorically on the X-axis.
 - `y`: Sample from which to draw the density plot.

src/misc.jl

@@ -379,10 +379,8 @@ function group_color_isless(a::(Tuple{S, T}),
 end
 
 
-"""
-trim longer arrays to the size of the smallest one
-and zip the arrays.
-"""
+#trim longer arrays to the size of the smallest one
+#and zip the arrays.
 function trim_zip(xs...)
     mx = max(map(length, xs)...)
     mn = min(map(length, xs)...)