桑基图（Python）

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桑基图用宽度正比于流量的弧带在分阶段节点间路由流量——是患者旅程（筛查 → 治疗 → 结局）、细胞类型转换或测序通量分配的自然展示。matplotlib 没有可用的桑基实现；plotly 的 go.Sankey 处理节点布局与交互悬停，quarto 可将结果嵌入独立 HTML。

示例

环境配置

• 系统要求：跨平台（Linux/MacOS/Windows）
• 编程语言：Python
• 依赖包：pandas、numpy、plotly

import pandas as pd
import numpy as np
import plotly.graph_objects as go

数据准备

我们把临床队列旅程汇总为节点到节点的流量：300 名患者从确诊经两个治疗阶段到结局。流量是（源，目标，数量）三元组。

flows = pd.DataFrame([
    # 阶段 1：确诊 -> 初始治疗
    ('Diagnosed', 'Surgery', 140),
    ('Diagnosed', 'Chemo', 110),
    ('Diagnosed', 'Watchful waiting', 50),
    # 阶段 2：初始治疗 -> 结局
    ('Surgery', 'Disease-free', 95),
    ('Surgery', 'Adjuvant chemo', 45),
    ('Chemo', 'Disease-free', 55),
    ('Chemo', 'Progressed', 55),
    ('Watchful waiting', 'Disease-free', 38),
    ('Watchful waiting', 'Progressed', 12),
    # 阶段 3：辅助/进展 -> 最终状态
    ('Adjuvant chemo', 'Disease-free', 34),
    ('Adjuvant chemo', 'Progressed', 11),
    ('Progressed', 'Second-line', 55),
    ('Progressed', 'Palliative', 12),
    ('Second-line', 'Disease-free', 18),
    ('Second-line', 'Stable disease', 22),
    ('Second-line', 'Palliative', 15),
], columns=['Source', 'Target', 'Value'])

nodes = list(dict.fromkeys(
    flows.Source.tolist() + flows.Target.tolist()))
node_index = {n: i for i, n in enumerate(nodes)}
node_colors = ['#8da0cb' if n in ('Diagnosed', 'Surgery', 'Chemo',
                                 'Watchful waiting', 'Adjuvant chemo',
                                 'Second-line')
               else '#66c2a5' if 'Disease-free' in n or 'Stable' in n
               else '#e63946'
               for n in nodes]

可视化

队列旅程桑基图

节点声明一次，之后每条流量按索引引用；给每条弧带分配其源节点颜色可保持阶段可读。

fig = go.Figure(data=[go.Sankey(
    node=dict(label=nodes, pad=14, thickness=16,
              color=node_colors),
    link=dict(
        source=[node_index[s] for s, _, _ in flows.itertuples(index=False)],
        target=[node_index[t] for _, t, _ in flows.itertuples(index=False)],
        value=flows.Value,
        color=['rgba(141,160,203,0.45)' if node_index[s] < 6
               else 'rgba(230,57,70,0.35)'
               for s, _, _ in flows.itertuples(index=False)],
    ))])
fig.update_layout(title_text='Cohort journey (n = 300)',
                  font_size=11, width=880, height=480)
fig.show()

图 1: 从确诊到结局的患者流（n = 300）

渲染结果是交互式的：悬停弧带显示确切患者数，悬停节点显示总入/出流量。

参考文献

1. Plotly Technologies Inc. Sankey diagram in Python. https://plotly.com/python/sankey-diagram/
2. Schmidt, M. The Sankey diagram in energy and material flow accounting. Journal of Industrial Ecology (2008).