数据读取器

using GLMakie
using DelimitedFiles

airports = Point2f.(eachrow(readdlm(assetpath("airportlocations.csv"))))
fig, ax, ds = datashader(airports,
    colormap=[:white, :black],
    # for documentation output we shouldn't calculate the image async,
    # since it won't wait for the render to finish and inline a blank image
    async = false,
    figure = (; figure_padding=0, size=(360*2, 160*2))
)
Colorbar(fig[1, 2], ds, label="Number of airports")
hidedecorations!(ax); hidespines!(ax)
fig

using GLMakie
with_z(p2) = Point3f(p2..., cos(p2[1]) * sin(p2[2]))
points = randn(Point2f, 100_000)
points_with_z = map(with_z, points)

f = Figure()
ax = Axis(f[1, 1], title = "AggMean")
datashader!(ax, points_with_z, agg = Makie.AggMean(), operation = identity)
ax2 = Axis(f[1, 2], title = "AggMean binsize = 3")
datashader!(ax2, points_with_z, agg = Makie.AggMean(), operation = identity, binsize = 3)
f

using GLMakie
# Taken from Lazaro Alonso in Beautiful Makie:
# https://beautiful.makie.org/dev/examples/generated/2d/datavis/strange_attractors/?h=cliffo#trajectory
Clifford((x, y), a, b, c, d) = Point2f(sin(a * y) + c * cos(a * x), sin(b * x) + d * cos(b * y))

function trajectory(fn, x0, y0, kargs...; n=1000) #  kargs = a, b, c, d
    xy = zeros(Point2f, n + 1)
    xy[1] = Point2f(x0, y0)
    @inbounds for i in 1:n
        xy[i+1] = fn(xy[i], kargs...)
    end
    return xy
end

cargs = [[0, 0, -1.3, -1.3, -1.8, -1.9],
    [0, 0, -1.4, 1.6, 1.0, 0.7],
    [0, 0, 1.7, 1.7, 0.6, 1.2],
    [0, 0, 1.7, 0.7, 1.4, 2.0],
    [0, 0, -1.7, 1.8, -1.9, -0.4],
    [0, 0, 1.1, -1.32, -1.03, 1.54],
    [0, 0, 0.77, 1.99, -1.31, -1.45],
    [0, 0, -1.9, -1.9, -1.9, -1.0],
    [0, 0, 0.75, 1.34, -1.93, 1.0],
    [0, 0, -1.32, -1.65, 0.74, 1.81],
    [0, 0, -1.6, 1.6, 0.7, -1.0],
    [0, 0, -1.7, 1.5, -0.5, 0.7]
]

fig = Figure(size=(1000, 1000))
fig_grid = CartesianIndices((3, 4))
cmap = to_colormap(:BuPu_9)
cmap[1] = RGBAf(1, 1, 1, 1) # make sure background is white

let
    # locally, one can go pretty high with n_points,
    # e.g. 4*(10^7), but we don't want the docbuild to become too slow.
    n_points = 10^6
    for (i, arg) in enumerate(cargs)
        points = trajectory(Clifford, arg...; n=n_points)
        r, c = Tuple(fig_grid[i])
        ax, plot = datashader(fig[r, c], points;
            colormap=cmap,
            async=false,
            axis=(; title=join(string.(arg), ", ")))
        hidedecorations!(ax)
        hidespines!(ax)
    end
end
rowgap!(fig.layout,5)
colgap!(fig.layout,1)
fig

datashader(one_category_per_point, points)
datashader(Dict(:category_a => all_points_a, :category_b => all_points_b))

using GLMakie
normaldist = randn(Point2f, 1_000_000)
ds1 = normaldist .+ (Point2f(-1, 0),)
ds2 = normaldist .+ (Point2f(1, 0),)
fig, ax, pl = datashader(Dict("a" => ds1, "b" => ds2); async = false)
hidedecorations!(ax)
fig

@time begin
    f = Figure(figure_padding=0, size=(1200, 600))
    ax = Axis(
        f[1, 1],
        autolimitaspect=1,
        limits=(-74.022, -73.827, 40.696, 40.793),
        backgroundcolor=:black
    )
    datashader!(ax, groups, points)
    hidedecorations!(ax)
    hidespines!(ax)
    # Create a styled legend
    axislegend("Vendor ID"; titlecolor=:white, framecolor=:grey, polystrokewidth=2, polystrokecolor=(:white, 0.5), rowgap=10, backgroundcolor=:black, labelcolor=:white)
    display(f)
end

struct MyAgg{T} <: Makie.AggOp end
MyAgg() = MyAgg{Float64}()
Makie.Aggregation.null(::MyAgg{T}) where {T} = zero(T)
Makie.Aggregation.embed(::MyAgg{T}, x) where {T} = convert(T, x)
Makie.Aggregation.merge(::MyAgg{T}, x::T, y::T) where {T} = x + y
Makie.Aggregation.value(::MyAgg{T}, x::T) where {T} = x