雷达图（Julia）

🤖 AI Skill — Download the Bizard unified skill for your AI assistant ⬇️ Download Skill ZIP

🔌 MCP Server — Let AI agents (Claude Code, Cursor, …) query Bizard live: claude mcp add bizard -- npx @openbiox/bizard-mcp — or the free hosted instance (no install, faster from mainland China): claude mcp add --transport http bizard http://biotree.top:38123/bizard-mcp/mcp 📖 MCP Docs

📖 Cite Bizard — if Bizard helps your research, please cite: Li, K., Zheng, H., Huang, K., et al. (2026). Bizard: A Community-Driven Platform for Accelerating and Enhancing Biomedical Data Visualization. iMetaMed, e70038. 🔗 DOI / BibTeX

雷达图（蛛网图）在极坐标上以多个可比轴刻画一个或少数样本的画像——适合每根轴都是同一 0–1 量尺的评分（免疫签名、质控面板），量纲不同时则有误导性。CairoMakie 提供 PolarAxis 区块，但把辐条手工投影到直角坐标轴上可以完全掌控外侧标签，三角计算只有两行。

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

using CairoMakie
using DataFrames
using Statistics
using Random

数据准备

我们为两款 CAR-T 产品在八个归一化（0–1）免疫功能轴上打分，并将首点重复以闭合多边形。

axes_names = ["Killing", "Cytokine", "Prolif.", "Persist.",
              "Traffic", "Exhaust.", "Memory", "Safety"]
scores = DataFrame(
    Product = ["CAR-19", "CAR-22"],
    Values = [[0.9, 0.7, 0.8, 0.6, 0.5, 0.8, 0.65, 0.75],
              [0.7, 0.85, 0.6, 0.8, 0.7, 0.6, 0.8, 0.85]])
K = length(axes_names)
angles = [2π * k / K for k in 0:K]                 # 首角重复用于闭合
profile(v) = [v; v[1]]
xy(r, θ) = Point2f(r * cos(θ), r * sin(θ))

xy (generic function with 1 method)

可视化

网格、辐条与单产品画像

同心参考环、辐条与轴标签各是三行小循环；画像本身就是一个闭合多边形。

θ_grid = range(0, 2π; length = 181)
fig = Figure(size = (480, 440))
ax = Axis(fig[1, 1]; aspect = DataAspect())
for r in 0.25:0.25:1.0                                   # 参考环
    lines!(ax, [xy(r, θ) for θ in θ_grid]; color = :gray85, linewidth = 0.8)
end
for k in 1:K                                             # 辐条 + 标签
    lines!(ax, [xy(0.0, angles[k]), xy(1.0, angles[k])];
           color = :gray85, linewidth = 0.8)
    text!(ax, xy(1.16, angles[k]); text = axes_names[k],
          align = (:center, :center), fontsize = 11)
end
poly!(ax, [xy(v, θ) for (v, θ) in zip(profile(scores.Values[1]), angles)];
      color = (:steelblue, 0.30), strokecolor = :steelblue, strokewidth = 1.8)
ax.xticks = []; ax.yticks = []
hidespines!(ax)
fig

图 1: CAR-19 产品的免疫功能画像

双产品叠加

同一组辐条上的两个半透明填充，让权衡关系（杀伤 vs 持续性）一目了然。

θ_grid = range(0, 2π; length = 181)
fig = Figure(size = (540, 440))
ax = Axis(fig[1, 1]; aspect = DataAspect())
for r in 0.25:0.25:1.0
    lines!(ax, [xy(r, θ) for θ in θ_grid]; color = :gray85, linewidth = 0.8)
end
for k in 1:K
    lines!(ax, [xy(0.0, angles[k]), xy(1.0, angles[k])];
           color = :gray85, linewidth = 0.8)
    text!(ax, xy(1.16, angles[k]); text = axes_names[k],
          align = (:center, :center), fontsize = 11)
end
product_colors = [:steelblue, :tomato]
for (i, row) in enumerate(eachrow(scores))
    poly!(ax, [xy(v, θ) for (v, θ) in zip(profile(row.Values), angles)];
          color = (product_colors[i], 0.25),
          strokecolor = product_colors[i], strokewidth = 1.8)
end
elements = [PolyElement(polycolor = c) for c in product_colors]
Legend(fig[1, 2], elements, scores.Product, framevisible = false)
ax.xticks = []; ax.yticks = []
hidespines!(ax)
fig

图 2: 两款 CAR-T 产品免疫功能画像叠加

参考文献

1. Makie development team. Makie.jl documentation — PolarAxis. https://docs.makie.org/stable/reference/blocks/polaraxis
2. Danisch, S., & Krumbiegel, J. (2021). Makie.jl: Flexible high-performance data visualization for Julia. Journal of Open Source Software, 6(65), 3349.