Plots.jl/src/plot.jl

268 lines
8.0 KiB
Julia

type CurrentPlot
nullableplot::Nullable{AbstractPlot}
end
const CURRENT_PLOT = CurrentPlot(Nullable{AbstractPlot}())
isplotnull() = isnull(CURRENT_PLOT.nullableplot)
function current()
if isplotnull()
error("No current plot/subplot")
end
get(CURRENT_PLOT.nullableplot)
end
current(plot::AbstractPlot) = (CURRENT_PLOT.nullableplot = Nullable(plot))
# ---------------------------------------------------------
Base.string(plt::Plot) = "Plot{$(plt.backend) n=$(plt.n)}"
Base.print(io::IO, plt::Plot) = print(io, string(plt))
Base.show(io::IO, plt::Plot) = print(io, string(plt))
getplot(plt::Plot) = plt
getplotargs(plt::Plot, idx::Int = 1) = plt.plotargs
convertSeriesIndex(plt::Plot, n::Int) = n
# ---------------------------------------------------------
"""
The main plot command. Use `plot` to create a new plot object, and `plot!` to add to an existing one:
```
plot(args...; kw...) # creates a new plot window, and sets it to be the current
plot!(args...; kw...) # adds to the `current`
plot!(plotobj, args...; kw...) # adds to the plot `plotobj`
```
There are lots of ways to pass in data, and lots of keyword arguments... just try it and it will likely work as expected.
When you pass in matrices, it splits by columns. See the documentation for more info.
"""
# this creates a new plot with args/kw and sets it to be the current plot
function plot(args...; kw...)
pkg = backend()
d = KW(kw)
preprocessArgs!(d)
dumpdict(d, "After plot preprocessing")
plotargs = merge(d, getPlotArgs(pkg, d, 1))
dumpdict(plotargs, "Plot args")
plt = _create_plot(pkg, plotargs) # create a new, blank plot
delete!(d, :background_color)
plot!(plt, args...; d...) # add to it
end
# this adds to the current plot, or creates a new plot if none are current
function plot!(args...; kw...)
local plt
try
plt = current()
catch
return plot(args...; kw...)
end
plot!(current(), args...; kw...)
end
# this adds to a specific plot... most plot commands will flow through here
function plot!(plt::Plot, args...; kw...)
d = KW(kw)
preprocessArgs!(d)
# for plotting recipes, swap out the args and update the parameter dictionary
args = _apply_recipe(d, args...; kw...)
dumpdict(d, "After plot! preprocessing")
warnOnUnsupportedArgs(plt.backend, d)
# just in case the backend needs to set up the plot (make it current or something)
_before_add_series(plt)
# # grouping
groupby = if haskey(d, :group)
extractGroupArgs(d[:group], args...)
else
nothing
end
_add_series(plt, d, groupby, args...)
_add_annotations(plt, d)
warnOnUnsupportedScales(plt.backend, d)
# add title, axis labels, ticks, etc
if !haskey(d, :subplot)
merge!(plt.plotargs, d)
handlePlotColors(plt.backend, plt.plotargs)
dumpdict(plt.plotargs, "Updating plot items")
_update_plot(plt, plt.plotargs)
end
_update_plot_pos_size(plt, d)
current(plt)
# note: lets ignore the show param and effectively use the semicolon at the end of the REPL statement
# # do we want to show it?
if haskey(d, :show) && d[:show]
gui()
end
plt
end
# handle the grouping
function _add_series(plt::Plot, d::KW, groupby::GroupBy, args...)
starting_n = plt.n
for (i, glab) in enumerate(groupby.groupLabels)
tmpd = copy(d)
tmpd[:numUncounted] = plt.n - starting_n
_add_series(plt, tmpd, nothing, args...;
idxfilter = groupby.groupIds[i],
grouplabel = string(glab))
end
end
filter_data(v::AVec, idxfilter::AVec{Int}) = v[idxfilter]
filter_data(v, idxfilter) = v
function filter_data!(d::KW, idxfilter)
for s in (:x, :y, :z)
d[s] = filter_data(get(d, s, nothing), idxfilter)
end
end
# no grouping
function _add_series(plt::Plot, d::KW, ::Void, args...;
idxfilter = nothing,
grouplabel = "")
# get the list of dictionaries, one per series
dumpdict(d, "before process_inputs")
process_inputs(plt, d, args...)
dumpdict(d, "after process_inputs")
if idxfilter != nothing
# add the group name as the label if there isn't one passed in
get!(d, :label, grouplabel)
# filter the data
filter_data!(d, idxfilter)
end
seriesArgList, xmeta, ymeta = build_series_args(plt, d) #, idxfilter)
# seriesArgList, xmeta, ymeta = build_series_args(plt, groupargs..., args...; d...)
# if we were able to extract guide information from the series inputs, then update the plot
# @show xmeta, ymeta
updateDictWithMeta(d, plt.plotargs, xmeta, true)
updateDictWithMeta(d, plt.plotargs, ymeta, false)
# now we can plot the series
for (i,di) in enumerate(seriesArgList)
plt.n += 1
if !stringsSupported()
setTicksFromStringVector(d, di, :x, :xticks)
setTicksFromStringVector(d, di, :y, :yticks)
setTicksFromStringVector(d, di, :z, :zticks)
end
# remove plot args
for k in keys(_plotDefaults)
delete!(di, k)
end
# merge in plotarg_overrides
plotarg_overrides = pop!(di, :plotarg_overrides, nothing)
if plotarg_overrides != nothing
merge!(plt.plotargs, plotarg_overrides)
end
# dumpdict(plt.plotargs, "pargs", true)
dumpdict(di, "Series $i")
_add_series(plt.backend, plt, di)
end
end
# --------------------------------------------------------------------
# if x or y are a vector of strings, we should create a list of unique strings,
# and map x/y to be the index of the string... then set the x/y tick labels
function setTicksFromStringVector(d::KW, di::KW, sym::Symbol, ticksym::Symbol)
# if the x or y values are strings, set ticks to the unique values, and x/y to the indices of the ticks
v = di[sym]
isa(v, AbstractArray) || return
T = eltype(v)
if T <: @compat(AbstractString) || (!isempty(T.types) && all(x -> x <: @compat(AbstractString), T.types))
ticks = unique(di[sym])
di[sym] = Int[findnext(ticks, v, 1) for v in di[sym]]
if !haskey(d, ticksym) || d[ticksym] == :auto
d[ticksym] = (collect(1:length(ticks)), UTF8String[t for t in ticks])
end
end
end
# --------------------------------------------------------------------
_before_add_series(plt::Plot) = nothing
# --------------------------------------------------------------------
# should we update the x/y label given the meta info during input slicing?
function updateDictWithMeta(d::KW, plotargs::KW, meta::Symbol, isx::Bool)
lsym = isx ? :xlabel : :ylabel
if plotargs[lsym] == default(lsym)
d[lsym] = string(meta)
end
end
updateDictWithMeta(d::KW, plotargs::KW, meta, isx::Bool) = nothing
# --------------------------------------------------------------------
annotations(::@compat(Void)) = []
annotations{X,Y,V}(v::AVec{@compat(Tuple{X,Y,V})}) = v
annotations{X,Y,V}(t::@compat(Tuple{X,Y,V})) = [t]
annotations(v::AVec{PlotText}) = v
annotations(v::AVec) = map(PlotText, v)
annotations(anns) = error("Expecting a tuple (or vector of tuples) for annotations: ",
"(x, y, annotation)\n got: $(typeof(anns))")
function _add_annotations(plt::Plot, d::KW)
anns = annotations(get(d, :annotation, nothing))
if !isempty(anns)
# if we just have a list of PlotText objects, then create (x,y,text) tuples
if typeof(anns) <: AVec{PlotText}
x, y = plt[plt.n]
anns = Tuple{Float64,Float64,PlotText}[(x[i], y[i], t) for (i,t) in enumerate(anns)]
end
_add_annotations(plt, anns)
end
end
# --------------------------------------------------------------------
function Base.copy(plt::Plot)
backend(plt.backend)
plt2 = plot(; plt.plotargs...)
for sargs in plt.seriesargs
sargs = filter((k,v) -> haskey(_seriesDefaults,k), sargs)
plot!(plt2; sargs...)
end
plt2
end
# --------------------------------------------------------------------