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Added smooth keyword to palette; Updated docstrings

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This commit is contained in:
Giorgio Calderone 2020-04-28 14:14:25 +02:00
parent 4d1768e15e
commit 92380bc468
2 changed files with 55 additions and 32 deletions
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80
src/Gnuplot.jl
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@ -1673,17 +1673,19 @@ end
"""
palette(cmap::ColorScheme; rev=false)
palette(s::Symbol; rev=false)
palette(cmap::ColorScheme; rev=false, smooth=false)
palette(s::Symbol; rev=false, smooth=false)
Convert a `ColorScheme` object into a string containing the gnuplot commands to set up the corresponding palette.
If the argument is a `Symbol` it is interpreted as the name of one of the predefined schemes in [ColorSchemes](https://juliagraphics.github.io/ColorSchemes.jl/stable/basics/#Pre-defined-schemes-1). If `rev=true` the palette is reversed.
If the argument is a `Symbol` it is interpreted as the name of one of the predefined schemes in [ColorSchemes](https://juliagraphics.github.io/ColorSchemes.jl/stable/basics/#Pre-defined-schemes-1).
If `rev=true` the palette is reversed. If `smooth=true` the palette is interpolated in 256 levels.
"""
palette(s::Symbol; rev=false) = palette(colorschemes[s], rev=rev)
function palette(cmap::ColorScheme; rev=false)
palette(s::Symbol; kwargs...) = palette(colorschemes[s]; kwargs...)
function palette(cmap::ColorScheme; rev=false, smooth=false)
levels = Vector{String}()
for x in LinRange(0, 1, length(cmap.colors))
for x in LinRange(0, 1, (smooth ? 256 : length(cmap.colors)))
if rev
color = get(cmap, 1-x)
else
@ -1960,23 +1962,25 @@ struct IsoContourLines
paths::Vector{Path2d}
data::Dataset
z::Float64
function IsoContourLines(paths::Vector{Path2d}, z)
@assert length(z) == 1
# Prepare Dataset object
data = Vector{String}()
for i in 1:length(paths)
append!(data, arrays2datablock(paths[i].x, paths[i].y, z .* fill(1., length(paths[i].x))))
push!(data, "")
push!(data, "")
end
return new(paths, DatasetText(data), z)
prob::Float64
end
function IsoContourLines(paths::Vector{Path2d}, z)
@assert length(z) == 1
# Prepare Dataset object
data = Vector{String}()
for i in 1:length(paths)
append!(data, arrays2datablock(paths[i].x, paths[i].y, z .* fill(1., length(paths[i].x))))
push!(data, "")
push!(data, "")
end
return IsoContourLines(paths, DatasetText(data), z, NaN)
end
"""
contourlines(x::AbstractVector{Float64}, y::AbstractVector{Float64}, z::AbstractMatrix{Float64}, cntrparam="level auto 10")
contourlines(h::Histogram2D, cntrparam="level auto 10")
contourlines(x, y, z, cntrparam="level auto 4")
contourlines(x, y, z, fractions)
contourlines(h::Histogram2D, ...)
Compute paths of contour lines for 2D data, and return a vector of [`IsoContourLines`](@ref) object.
@ -1984,16 +1988,19 @@ Compute paths of contour lines for 2D data, and return a vector of [`IsoContourL
This feature is not available in *dry* mode and will raise an error if used.
# Arguments:
- `x`, `y`: Coordinates;
- `z`: the levels on which iso contour lines are to be calculated
- `cntrparam`: settings to compute contour line paths (see gnuplot documentation for `cntrparam`).
- `x`, `y` (as `AbstractVector{Float64}`): Coordinates;
- `z::AbstractMatrix{Float64}`: the levels on which iso-contour lines are to be calculated;
- `cntrparam::String`: settings to compute contour line paths (see gnuplot documentation for `cntrparam`);
- `fractions::Vector{Float64}`: compute contour lines encompassing these fractions of total counts;
- `h::Histogram2D`: use histogram bins and counts to compute contour lines.
# Example
```julia
x = randn(5000);
y = randn(5000);
x = randn(10^5);
y = randn(10^5);
h = hist(x, y, nbins1=20, nbins2=20);
clines = contourlines(h, "levels discrete 15, 30, 45");
clines = contourlines(h, "levels discrete 500, 1500, 2500");
# Use implicit recipe
@gp clines
@ -2003,6 +2010,13 @@ clines = contourlines(h, "levels discrete 15, 30, 45");
for i in 1:length(clines)
@gp :- clines[i].data "w l t '\$(clines[i].z)' lw \$i dt \$i"
end
# Calculate probability within 0 < r < σ
p(σ) = round(1 - exp(-(σ^2) / 2), sigdigits=3)
# Draw contour lines at 1, 2 and 3 σ
clines = contourlines(h, p.(1:3));
@gp palette(:beach, smooth=true, rev=true) "set grid front" "set size ratio -1" h clines
```
"""
contourlines(h::Histogram2D, args...) = contourlines(h.bins1, h.bins2, h.counts, args...)
@ -2011,24 +2025,28 @@ function contourlines(x::AbstractVector{Float64}, y::AbstractVector{Float64}, z:
@assert minimum(fraction) > 0
@assert maximum(fraction) < 1
@assert length(fraction) >= 1
# The following is necessary since `countourlines` return levels
# sorted in increasing order, corresponding to decreasing order
# top fractions.
@assert issorted(fraction, rev=true) "`fraction` must be sorted in decreasing order"
sorted_fraction = sort(fraction, rev=true)
i = sortperm(z[:], rev=true)
topfrac = cumsum(z[i]) ./ sum(z)
selection = Int[]
for f in fraction
for f in sorted_fraction
push!(selection, minimum(findall(topfrac .>= f)))
end
levels = z[i[selection]]
clines = contourlines(x, y, z, "levels discrete " * join(string.(levels), ", "))
@assert issorted(getfield.(clines, :z))
if length(clines) == length(fraction)
out = [IsoContourLines(clines[i].paths, clines[i].data, clines[i].z,
sorted_fraction[i]) for i in 1:length(clines)]
return out
end
return clines
end
function contourlines(x::AbstractVector{Float64}, y::AbstractVector{Float64}, z::AbstractMatrix{Float64},
cntrparam="level auto 10")
cntrparam="level auto 4")
lines = gp_write_table("set contour base", "unset surface",
"set cntrparam $cntrparam", x, y, z, is3d=true)
level = NaN

7
src/recipes.jl
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@ -29,7 +29,12 @@ recipe(h::Histogram2D) =
Implicit recipes to visualize iso-contour lines.
"""
recipe(c::IsoContourLines) = PlotElement(data=c.data, plot="w l t '$(c.z)'")
function recipe(c::IsoContourLines)
if isnan(c.prob)
return PlotElement(data=c.data, plot="w l t '$(c.z)'")
end
return PlotElement(data=c.data, plot="w l t '$(round(c.prob * 100, sigdigits=6))%'")
end
recipe(v::Vector{IsoContourLines}) = recipe.(v)