using CairoMakie
using DataFrames
using Statistics
using Random面积图与河流图（Julia）
面积图通过填充折线下的区域，强调一个或多个量随有序轴变化的规模；堆叠变体把总量分解为多层，河流图（streamgraph）则将各层围绕波动基线堆叠。在生物医学研究中，适用于免疫细胞群动态与队列累积。CairoMakie 通过 band! 图层组合而成。
示例
环境配置
- 系统要求：跨平台（Linux/MacOS/Windows）
- 编程语言：Julia
- 依赖包：
CairoMakie、DataFrames、Statistics
数据准备
我们模拟一项 8 周疫苗接种研究中三种淋巴细胞群的每周流式计数。
Random.seed!(71)
weeks = collect(1.0:8)
n_weeks = length(weeks)
counts = DataFrame(
Week = weeks,
CD4 = 400 .* exp.(0.10 .* weeks) .+ 25 .* randn(n_weeks),
CD8 = 300 .* exp.(0.16 .* weeks) .+ 22 .* randn(n_weeks),
B = 200 .* exp.(0.06 .* weeks) .+ 15 .* randn(n_weeks))
series = [counts.CD4, counts.CD8, counts.B]
series_names = ["CD4 T", "CD8 T", "B cells"]
band_colors = [:steelblue, :plum, :seagreen]3-element Vector{Symbol}:
:steelblue
:plum
:seagreen可视化
单序列面积图
band! 填充上下界之间的区域——单个序列的最简强调形式。
fig = Figure(size = (460, 340))
ax = Axis(fig[1, 1], xlabel = "Week", ylabel = "Cell count (×10\$^3\$)")
band!(ax, counts.Week, zero(weeks), counts.CD8; color = (:plum, 0.45))
lines!(ax, counts.Week, counts.CD8; color = :magenta3, linewidth = 1.8)
hidespines!(ax, :t, :r)
fig
堆叠面积图
累加和定义各层边界；自下而上绘制并以白色描边保持层间分隔。
upper = reduce(hcat, series) |> x -> cumsum(x, dims = 2) # n_weeks × 3
lower = hcat(zeros(n_weeks), upper[:, 1:end-1])
fig = Figure(size = (500, 360))
ax = Axis(fig[1, 1], xlabel = "Week", ylabel = "Cell count (×10\$^3\$)")
for k in 1:3
band!(ax, counts.Week, lower[:, k], upper[:, k];
color = (band_colors[k], 0.85), strokecolor = :white, strokewidth = 0.6)
end
hidespines!(ax, :t, :r)
elements = [PolyElement(polycolor = band_colors[k]) for k in 1:3]
Legend(fig[1, 2], elements, series_names, framevisible = false)
fig
河流图
河流图把整个堆叠围绕对称基线偏移，让视线追随各色带的形状而非零线。
total = vec(sum(reduce(hcat, series), dims = 2))
baseline = .-total ./ 2 # 对称基线使堆叠居中
fig = Figure(size = (560, 360))
ax = Axis(fig[1, 1], xlabel = "Week",
ylabel = "Cell count (×10\$^3\$, offset baseline)")
for k in 1:3
band!(ax, counts.Week, baseline .+ (k == 1 ? 0.0 : sum(series[1:k-1]; dims = 1)[1]),
baseline .+ sum(series[1:k]; dims = 1)[1];
color = (band_colors[k], 0.9), strokecolor = :white, strokewidth = 0.6)
end
hidespines!(ax, :t, :r, :l)
hideydecorations!(ax)
elements = [PolyElement(polycolor = band_colors[k]) for k in 1:3]
Legend(fig[1, 2], elements, series_names, framevisible = false)
fig
参考文献
- Makie development team. Makie.jl documentation — band. https://docs.makie.org/stable/reference/plots/band
- Danisch, S., & Krumbiegel, J. (2021). Makie.jl: Flexible high-performance data visualization for Julia. Journal of Open Source Software, 6(65), 3349.