fix color

task3/02_pairing.py

@@ -26,10 +26,10 @@ INPUT_FILE = '01_distance.xlsx'
 OUTPUT_FILE = '02_pairing.xlsx'
 
 # 约束参数
-L_MAX = 50          # 距离阈值 (英里)
+L_MAX = 30          # 距离阈值 (英里)
-MU_SUM_MAX = 450    # 需求和上限
+MU_SUM_MAX = 350    # 需求和上限
-CV_MAX = 0.5        # 变异系数上限
+CV_MAX = 0.3        # 变异系数上限
-Q = 400             # 卡车容量
+Q = 350             # 卡车容量
 
 # 价值函数权重
 ALPHA = 1.0         # 容量利用率权重

task3/07_sensitivity.py

@@ -16,17 +16,66 @@ Task 3 - Step 7: 敏感性分析 (Refined)
 import pandas as pd
 import numpy as np
 from scipy import stats
-import matplotlib.pyplot as plt
 import warnings
 import os
+import tempfile
 from pathlib import Path
 
 warnings.filterwarnings('ignore')
 
-# 设置绘图风格
+# Matplotlib cache dirs（避免 home 目录不可写导致的警告）
-plt.style.use('seaborn-v0_8-whitegrid')
+_mpl_config_dir = Path(tempfile.gettempdir()) / "mm_task3_mplconfig"
-plt.rcParams['font.sans-serif'] = ['Arial Unicode MS', 'SimHei', 'DejaVu Sans']  # 适配中文
+_xdg_cache_dir = Path(tempfile.gettempdir()) / "mm_task3_xdg_cache"
-plt.rcParams['axes.unicode_minus'] = False
+_mpl_config_dir.mkdir(parents=True, exist_ok=True)
+_xdg_cache_dir.mkdir(parents=True, exist_ok=True)
+os.environ.setdefault("MPLCONFIGDIR", str(_mpl_config_dir))
+os.environ.setdefault("XDG_CACHE_HOME", str(_xdg_cache_dir))
+
+import matplotlib.pyplot as plt
+from cycler import cycler
+
+# 设置绘图风格（低饱和度 Morandi 色系）
+MORANDI = {
+    "bg": "#F5F2ED",
+    "grid": "#D7D1C7",
+    "text": "#3F3F3F",
+    "muted_blue": "#8FA3A7",
+    "muted_blue_dark": "#6E858A",
+    "sage": "#AEB8A6",
+    "terracotta": "#B07A6A",
+    "warm_gray": "#8C857A",
+}
+
+plt.rcParams.update(
+    {
+        "figure.facecolor": MORANDI["bg"],
+        "axes.facecolor": MORANDI["bg"],
+        "savefig.facecolor": MORANDI["bg"],
+        "axes.edgecolor": MORANDI["grid"],
+        "axes.labelcolor": MORANDI["text"],
+        "xtick.color": MORANDI["text"],
+        "ytick.color": MORANDI["text"],
+        "text.color": MORANDI["text"],
+        "grid.color": MORANDI["grid"],
+        "grid.alpha": 0.55,
+        "axes.grid": True,
+        "axes.prop_cycle": cycler(
+            "color",
+            [
+                MORANDI["muted_blue"],
+                MORANDI["sage"],
+                MORANDI["terracotta"],
+                MORANDI["warm_gray"],
+            ],
+        ),
+        "legend.frameon": True,
+        "legend.framealpha": 0.9,
+        "legend.facecolor": MORANDI["bg"],
+        "legend.edgecolor": MORANDI["grid"],
+        "font.sans-serif": ["Arial Unicode MS", "SimHei", "DejaVu Sans"],
+        "axes.unicode_minus": False,
+    }
+)
 
 # ============================================
 # 基础参数和函数 (保持不变)
@@ -333,16 +382,38 @@ for i, param in enumerate(params_list):
     data = df_results[df_results['param'] == param].sort_values('value')
     
     # 绘制 E1/E2 - 左轴
-    line1, = ax.plot(data['value'], data['E1'], 'b-', linewidth=1.6, label='Expected Service (E1)')
+    line1, = ax.plot(
-    line2, = ax.plot(data['value'], data['E2'], 'g-', linewidth=1.6, alpha=0.9, label='Quality-weighted (E2)')
+        data['value'],
+        data['E1'],
+        linestyle='-',
+        color=MORANDI["muted_blue_dark"],
+        linewidth=1.8,
+        label='Expected Service (E1)',
+    )
+    line2, = ax.plot(
+        data['value'],
+        data['E2'],
+        linestyle='-',
+        color=MORANDI["sage"],
+        linewidth=1.8,
+        alpha=0.95,
+        label='Quality-weighted (E2)',
+    )
     ax.set_xlabel(param_labels[param][0])
     ax.set_ylabel('Service (E1/E2)')
     
     # 绘制 R1 (风险) - 右轴
     ax2 = ax.twinx()
-    line3, = ax2.plot(data['value'], data['R1'], 'r--', linewidth=1.6, label='Shortfall Risk (R1)')
+    line3, = ax2.plot(
-    ax2.set_ylabel('Risk Probability (R1)', color='r')
+        data['value'],
-    ax2.tick_params(axis='y', labelcolor='r')
+        data['R1'],
+        linestyle='--',
+        color=MORANDI["terracotta"],
+        linewidth=1.8,
+        label='Shortfall Risk (R1)',
+    )
+    ax2.set_ylabel('Risk Probability (R1)', color=MORANDI["terracotta"])
+    ax2.tick_params(axis='y', labelcolor=MORANDI["terracotta"])
     
     # 添加基准线
     if param == 'merge_ratio':
@@ -354,7 +425,7 @@ for i, param in enumerate(params_list):
     elif param == 'cv_max':
         base_val = BASE_CV_MAX
         
-    ax.axvline(x=base_val, color='gray', linestyle=':', alpha=0.5)
+    ax.axvline(x=base_val, color=MORANDI["warm_gray"], linestyle=':', alpha=0.65)
     
     # 图例
     lines = [line1, line2, line3]
@@ -362,7 +433,7 @@ for i, param in enumerate(params_list):
     ax.legend(lines, labels, loc='best', frameon=True)
     
     ax.set_title(f'Effect of {param_labels[param][0]}')
-    ax.grid(True, alpha=0.3)
+    ax.grid(True, alpha=0.55)
 
 plt.tight_layout(rect=[0, 0.03, 1, 0.95])
 plt.savefig(OUTPUT_FIG, dpi=300)

task3/08_visualize.py

@@ -19,6 +19,7 @@ Task 3 - Step 8: 可视化（Fig.1/2/4/5）
 from __future__ import annotations
 
 from dataclasses import dataclass
+import json
 from pathlib import Path
 
 import os
@@ -38,11 +39,62 @@ import matplotlib
 
 matplotlib.use("Agg")
 import matplotlib.pyplot as plt
+from matplotlib import colors as mcolors
+from cycler import cycler
 
 
 BASE_DIR = Path(__file__).resolve().parent
 
 
+MORANDI = {
+    "bg": "#F5F2ED",
+    "grid": "#D7D1C7",
+    "text": "#3F3F3F",
+    "muted_blue": "#8FA3A7",
+    "muted_blue_dark": "#6E858A",
+    "sage": "#AEB8A6",
+    "clay": "#C6AA9B",
+    "rose": "#D2B8B3",
+    "warm_gray": "#8C857A",
+    "terracotta": "#B07A6A",
+}
+
+
+def _apply_morandi_style() -> None:
+    plt.rcParams.update(
+        {
+            "figure.facecolor": MORANDI["bg"],
+            "axes.facecolor": MORANDI["bg"],
+            "savefig.facecolor": MORANDI["bg"],
+            "axes.edgecolor": MORANDI["grid"],
+            "axes.labelcolor": MORANDI["text"],
+            "xtick.color": MORANDI["text"],
+            "ytick.color": MORANDI["text"],
+            "text.color": MORANDI["text"],
+            "grid.color": MORANDI["grid"],
+            "grid.alpha": 0.55,
+            "axes.grid": True,
+            "axes.titleweight": "semibold",
+            "axes.titlesize": 11,
+            "axes.labelsize": 10,
+            "legend.frameon": True,
+            "legend.framealpha": 0.9,
+            "legend.facecolor": MORANDI["bg"],
+            "legend.edgecolor": MORANDI["grid"],
+            "axes.prop_cycle": cycler(
+                "color",
+                [
+                    MORANDI["muted_blue"],
+                    MORANDI["sage"],
+                    MORANDI["clay"],
+                    MORANDI["rose"],
+                    MORANDI["warm_gray"],
+                ],
+            ),
+        }
+    )
+
+
 @dataclass(frozen=True)
 class Paths:
     distance_xlsx: Path
@@ -76,6 +128,15 @@ def _pair_key(a: int, b: int) -> tuple[int, int]:
 
 
 def fig1_pairing_map(paths: Paths) -> Path:
+    _apply_morandi_style()
+
+    # Warmer + higher contrast for Fig.1 specifically (clearer on paper/screens)
+    fig1_colors = {
+        "paired": "#e76f51",
+        "unpaired": "#6c757d",
+        "link": "#bc6c25",
+    }
+
     sites = pd.read_excel(paths.distance_xlsx, sheet_name="sites")
     pairs = pd.read_excel(paths.pairing_xlsx, sheet_name="selected_pairs")
 
@@ -97,9 +158,9 @@ def fig1_pairing_map(paths: Paths) -> Path:
         ax.plot(
             [si["lon"], sj["lon"]],
             [si["lat"], sj["lat"]],
-            color="#2c7fb8",
+            color=fig1_colors["link"],
-            alpha=0.35,
+            alpha=0.5,
-            linewidth=1.0,
+            linewidth=1.2,
             zorder=1,
         )
 
@@ -110,8 +171,8 @@ def fig1_pairing_map(paths: Paths) -> Path:
         paired["lon"],
         paired["lat"],
         s=18,
-        color="#d95f0e",
+        color=fig1_colors["paired"],
-        alpha=0.85,
+        alpha=0.9,
         label=f"Paired sites (n={len(paired)})",
         zorder=2,
     )
@@ -120,7 +181,7 @@ def fig1_pairing_map(paths: Paths) -> Path:
             unpaired["lon"],
             unpaired["lat"],
             s=22,
-            color="#636363",
+            color=fig1_colors["unpaired"],
             alpha=0.9,
             marker="x",
             label=f"Unpaired sites (n={len(unpaired)})",
@@ -130,7 +191,7 @@ def fig1_pairing_map(paths: Paths) -> Path:
     ax.set_title("Fig.1 Pairing map (sites + selected 34 links)")
     ax.set_xlabel("Longitude")
     ax.set_ylabel("Latitude")
-    ax.grid(True, alpha=0.2)
+    ax.grid(True, alpha=0.55)
     ax.legend(loc="best", frameon=True)
 
     out = paths.figures_dir / "fig1_pairing_map.png"
@@ -140,7 +201,58 @@ def fig1_pairing_map(paths: Paths) -> Path:
     return out
 
 
+def export_fig1_points_js(paths: Paths) -> Path:
+    sites = pd.read_excel(paths.distance_xlsx, sheet_name="sites").copy()
+    pairs = pd.read_excel(paths.pairing_xlsx, sheet_name="selected_pairs").copy()
+
+    sites["site_id"] = sites["site_id"].astype(int)
+    sites["k"] = sites["k"].astype(int)
+
+    paired_ids = set(pairs["site_i_id"].astype(int)).union(
+        set(pairs["site_j_id"].astype(int))
+    )
+
+    points = []
+    for _, r in sites.iterrows():
+        points.append(
+            {
+                "site_id": int(r["site_id"]),
+                "site_name": str(r["site_name"]),
+                "lat": float(r["lat"]),
+                "lng": float(r["lon"]),
+                "mu": float(r["mu"]),
+                "sigma": float(r["sigma"]),
+                "k": int(r["k"]),
+                "is_paired": int(r["site_id"]) in paired_ids,
+            }
+        )
+
+    links = []
+    for _, r in pairs.iterrows():
+        links.append(
+            {
+                "site_i_id": int(r["site_i_id"]),
+                "site_j_id": int(r["site_j_id"]),
+                "site_i_name": str(r["site_i_name"]),
+                "site_j_name": str(r["site_j_name"]),
+                "distance": float(r["distance"]),
+            }
+        )
+
+    out = BASE_DIR / "fig1_points.js"
+    payload = (
+        "// Auto-generated from `task3/01_distance.xlsx` (sites) + `task3/02_pairing.xlsx` (selected_pairs)\n"
+        "// Usage: open `task3/fig1_carto.html` in a browser (same directory must contain this file).\n"
+        f"window.FIG1_POINTS = {json.dumps(points, ensure_ascii=False, separators=(',', ':'))};\n"
+        f"window.FIG1_LINKS = {json.dumps(links, ensure_ascii=False, separators=(',', ':'))};\n"
+    )
+    out.write_text(payload, encoding="utf-8")
+    return out
+
+
 def fig2_allocation_scatter(paths: Paths) -> Path:
+    _apply_morandi_style()
+
     df = pd.read_excel(paths.allocation_xlsx, sheet_name="allocation")
 
     q_ratio = df["q_ratio"].to_numpy(dtype=float)
@@ -157,15 +269,22 @@ def fig2_allocation_scatter(paths: Paths) -> Path:
     ]
 
     for ax, (title, x) in zip(axes, panels):
-        ax.scatter(x, q_ratio, s=22, alpha=0.75, color="#3182bd", edgecolor="none")
+        ax.scatter(
+            x,
+            q_ratio,
+            s=22,
+            alpha=0.8,
+            color=MORANDI["muted_blue"],
+            edgecolor="none",
+        )
         if np.isfinite(x).all() and np.isfinite(q_ratio).all() and len(x) >= 2:
             coef = np.polyfit(x, q_ratio, 1)
             xx = np.linspace(float(np.min(x)), float(np.max(x)), 100)
             yy = coef[0] * xx + coef[1]
-            ax.plot(xx, yy, color="#de2d26", linewidth=2.0, alpha=0.9)
+            ax.plot(xx, yy, color=MORANDI["terracotta"], linewidth=2.0, alpha=0.95)
         ax.set_title(title)
         ax.set_xlabel("x")
-        ax.grid(True, alpha=0.2)
+        ax.grid(True, alpha=0.55)
 
     axes[0].set_ylabel("$q^*/Q$")
     fig.suptitle("Fig.2 Allocation strategy scatter (34 pairs)", y=1.02)
@@ -178,6 +297,8 @@ def fig2_allocation_scatter(paths: Paths) -> Path:
 
 
 def fig4_calendar_heatmap(paths: Paths) -> Path:
+    _apply_morandi_style()
+
     sites = pd.read_excel(paths.distance_xlsx, sheet_name="sites")[["site_id", "mu"]]
     sites["site_id"] = sites["site_id"].astype(int)
     mu_by_id = dict(zip(sites["site_id"], sites["mu"]))
@@ -212,7 +333,17 @@ def fig4_calendar_heatmap(paths: Paths) -> Path:
                 expected[day - 1, slot - 1] = pair_E.get(_pair_key(i_id, j_id), np.nan)
 
     fig, ax = plt.subplots(figsize=(12, 2.6), dpi=200)
-    im = ax.imshow(expected.T, aspect="auto", cmap="viridis")
+    cmap = mcolors.LinearSegmentedColormap.from_list(
+        "morandi",
+        [
+            MORANDI["bg"],
+            "#E7E1D7",
+            MORANDI["sage"],
+            MORANDI["muted_blue"],
+            "#5F7478",
+        ],
+    )
+    im = ax.imshow(expected.T, aspect="auto", cmap=cmap)
     ax.set_yticks([0, 1], labels=["Slot 1", "Slot 2"])
     ax.set_xlabel("Day of year")
     ax.set_title("Fig.4 Calendar heatmap (expected service per slot)")
@@ -233,6 +364,8 @@ def fig4_calendar_heatmap(paths: Paths) -> Path:
 
 
 def fig5_risk_distribution(paths: Paths) -> Path:
+    _apply_morandi_style()
+
     risk = pd.read_excel(paths.evaluate_xlsx, sheet_name="pair_risk").copy()
     p = risk["shortfall_prob_either"].to_numpy(dtype=float)
     p = p[np.isfinite(p)]
@@ -240,21 +373,36 @@ def fig5_risk_distribution(paths: Paths) -> Path:
     fig, axes = plt.subplots(1, 2, figsize=(11, 3.8), dpi=200)
 
     ax = axes[0]
-    ax.hist(p, bins=10, color="#3182bd", alpha=0.85, edgecolor="white")
+    ax.hist(p, bins=10, color=MORANDI["sage"], alpha=0.9, edgecolor=MORANDI["bg"])
-    ax.axvline(float(np.mean(p)), color="#de2d26", linewidth=2.0, label=f"mean={np.mean(p):.3f}")
+    ax.axvline(
+        float(np.mean(p)),
+        color=MORANDI["terracotta"],
+        linewidth=2.2,
+        label=f"mean={np.mean(p):.3f}",
+    )
     ax.set_title("Histogram")
     ax.set_xlabel("Shortfall probability (either site)")
     ax.set_ylabel("Count")
-    ax.grid(True, alpha=0.2)
+    ax.grid(True, alpha=0.55)
     ax.legend(loc="best", frameon=True)
 
     ax = axes[1]
     p_sorted = np.sort(p)[::-1]
-    ax.plot(np.arange(1, len(p_sorted) + 1), p_sorted, marker="o", markersize=3.5, linewidth=1.5)
+    ax.plot(
+        np.arange(1, len(p_sorted) + 1),
+        p_sorted,
+        marker="o",
+        markersize=3.2,
+        linewidth=1.6,
+        color=MORANDI["muted_blue_dark"],
+        markerfacecolor=MORANDI["muted_blue"],
+        markeredgecolor=MORANDI["bg"],
+        markeredgewidth=0.6,
+    )
     ax.set_title("Sorted by risk (descending)")
     ax.set_xlabel("Pair rank")
     ax.set_ylabel("Shortfall probability")
-    ax.grid(True, alpha=0.2)
+    ax.grid(True, alpha=0.55)
 
     fig.suptitle("Fig.5 Risk distribution across 34 pairs", y=1.02)
     fig.tight_layout()
@@ -282,6 +430,8 @@ def main() -> None:
 
     out1 = fig1_pairing_map(paths)
     print(f"Saved: {out1.relative_to(BASE_DIR)}")
+    out1_js = export_fig1_points_js(paths)
+    print(f"Saved: {out1_js.relative_to(BASE_DIR)}")
     out2 = fig2_allocation_scatter(paths)
     print(f"Saved: {out2.relative_to(BASE_DIR)}")
     out4 = fig4_calendar_heatmap(paths)

task3/README.md

@@ -643,6 +643,8 @@ $$R_1 = P(S_i / D_i < 0.8 \text{ 或 } S_j / D_j < 0.8)$$
 
 ```
 task3/
+├── fig1_carto.html          # 交互地图（CartoDB 底图）
+├── fig1_points.js           # ✅ 自动生成（08_visualize.py）
 ├── 08_visualize.py      # 可视化脚本
 └── figures/
     ├── fig1_pairing_map.png
@@ -656,6 +658,8 @@ task3/
 
 ![Fig.1 站点配对地图](figures/fig1_pairing_map.png)
 
+交互版：用浏览器打开 `task3/fig1_carto.html`（同目录需有 `task3/fig1_points.js`；需联网加载 CartoDB 底图）。
+
 ![Fig.2 分配策略散点图](figures/fig2_allocation_scatter.png)
 
 ![Fig.4 日历热力图](figures/fig4_calendar_heatmap.png)

task3/fig1_carto.html

@@ -0,0 +1,175 @@
+<!doctype html>
+<html lang="zh-CN">
+  <head>
+    <meta charset="utf-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1" />
+    <title>Task 3 Fig.1 (CartoDB + Leaflet)</title>
+    <link
+      rel="stylesheet"
+      href="https://unpkg.com/leaflet@1.9.4/dist/leaflet.css"
+      crossorigin=""
+    />
+    <style>
+      html,
+      body,
+      #map {
+        height: 100%;
+        margin: 0;
+      }
+      .legend {
+        background: rgba(255, 249, 240, 0.95);
+        padding: 10px 12px;
+        border-radius: 8px;
+        box-shadow: 0 1px 10px rgba(0, 0, 0, 0.15);
+        font: 12px/1.3 system-ui, -apple-system, Segoe UI, Roboto, Helvetica, Arial, sans-serif;
+        border: 1px solid rgba(188, 108, 37, 0.25);
+      }
+      .legend .title {
+        font-weight: 700;
+        margin-bottom: 6px;
+      }
+      .legend .row {
+        display: flex;
+        justify-content: space-between;
+        gap: 12px;
+        white-space: nowrap;
+      }
+      .legend .swatch {
+        width: 12px;
+        height: 12px;
+        border-radius: 10px;
+        display: inline-block;
+        margin-right: 6px;
+        border: 1px solid rgba(255, 255, 255, 0.95);
+        vertical-align: -1px;
+      }
+      .legend .muted {
+        color: rgba(0, 0, 0, 0.65);
+        margin-top: 6px;
+      }
+      .legend .line {
+        height: 2px;
+        background: rgba(188, 108, 37, 0.75);
+        border-radius: 2px;
+        margin-top: 6px;
+      }
+    </style>
+  </head>
+  <body>
+    <div id="map"></div>
+
+    <script src="https://unpkg.com/leaflet@1.9.4/dist/leaflet.js" crossorigin=""></script>
+    <script src="./fig1_points.js"></script>
+    <script>
+      const points = window.FIG1_POINTS || [];
+      const links = window.FIG1_LINKS || [];
+      if (!points.length) {
+        alert("FIG1_POINTS 为空：请先运行 task3/08_visualize.py 生成 fig1_points.js，或确认该文件与本页面同目录。");
+      }
+
+      const map = L.map("map", { preferCanvas: true });
+
+      // CartoDB basemap (Positron)
+      L.tileLayer("https://{s}.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png", {
+        subdomains: "abcd",
+        maxZoom: 20,
+        attribution:
+          '&copy; <a href="https://www.openstreetmap.org/copyright">OSM</a> contributors &copy; <a href="https://carto.com/attributions">CARTO</a>',
+      }).addTo(map);
+
+      const byId = new Map(points.map((p) => [p.site_id, p]));
+      const muValues = points.map((p) => p.mu);
+      const muMin = Math.min(...muValues);
+      const muMax = Math.max(...muValues);
+
+      const COLORS = {
+        // warmer + higher contrast
+        paired: "#e76f51",
+        unpaired: "#6c757d",
+        link: "#bc6c25",
+      };
+
+      function clamp01(x) {
+        return Math.max(0, Math.min(1, x));
+      }
+      function lerp(a, b, t) {
+        return a + (b - a) * t;
+      }
+      function radiusForMu(mu) {
+        const t = clamp01((mu - muMin) / (muMax - muMin || 1));
+        return lerp(5, 20, t);
+      }
+      function colorForPaired(isPaired) {
+        return isPaired ? COLORS.paired : COLORS.unpaired;
+      }
+
+      const siteLayer = L.featureGroup();
+      for (const p of points) {
+        const marker = L.circleMarker([p.lat, p.lng], {
+          radius: radiusForMu(p.mu),
+          color: "rgba(255,255,255,0.96)",
+          weight: 1.35,
+          fillColor: colorForPaired(p.is_paired),
+          fillOpacity: 0.92,
+        });
+        marker.bindPopup(
+          `<div style="font: 13px/1.35 system-ui, -apple-system, Segoe UI, Roboto, Helvetica, Arial, sans-serif;">\n` +
+            `<div style="font-weight:700;margin-bottom:6px;">${p.site_id}. ${p.site_name}</div>` +
+            `<div><b>mu</b>: ${p.mu.toFixed(1)}</div>` +
+            `<div><b>sigma</b>: ${p.sigma.toFixed(1)}</div>` +
+            `<div><b>k</b>: ${p.k}</div>` +
+            `<div><b>paired</b>: ${p.is_paired ? "yes" : "no"}</div>` +
+            `</div>`
+        );
+        siteLayer.addLayer(marker);
+      }
+      siteLayer.addTo(map);
+
+      const linkLayer = L.featureGroup();
+      for (const e of links) {
+        const a = byId.get(e.site_i_id);
+        const b = byId.get(e.site_j_id);
+        if (!a || !b) continue;
+        const line = L.polyline(
+          [
+            [a.lat, a.lng],
+            [b.lat, b.lng],
+          ],
+          {
+            color: COLORS.link,
+            weight: 2.6,
+            opacity: 0.5,
+          }
+        );
+        line.bindPopup(
+          `<div style="font: 13px/1.35 system-ui, -apple-system, Segoe UI, Roboto, Helvetica, Arial, sans-serif;">\n` +
+            `<div style="font-weight:700;margin-bottom:6px;">Pair</div>` +
+            `<div>${e.site_i_id}. ${e.site_i_name}</div>` +
+            `<div>${e.site_j_id}. ${e.site_j_name}</div>` +
+            `<div><b>distance</b>: ${e.distance.toFixed(2)} mi</div>` +
+            `</div>`
+        );
+        linkLayer.addLayer(line);
+      }
+      linkLayer.addTo(map);
+
+      const all = L.featureGroup([siteLayer, linkLayer]);
+      map.fitBounds(all.getBounds().pad(0.12));
+
+      const legend = L.control({ position: "bottomleft" });
+      legend.onAdd = function () {
+        const pairedCount = points.filter((p) => p.is_paired).length;
+        const div = L.DomUtil.create("div", "legend");
+        div.innerHTML =
+          `<div class="title">Task 3 Fig.1 配对地图（交互）</div>` +
+          `<div class="row"><span><span class="swatch" style="background:${COLORS.paired}"></span>已配对站点</span><span>${pairedCount}</span></div>` +
+          `<div class="row"><span><span class="swatch" style="background:${COLORS.unpaired}"></span>未配对站点</span><span>${points.length - pairedCount}</span></div>` +
+          `<div class="muted">点大小: mu（线性缩放）</div>` +
+          `<div class="line"></div>` +
+          `<div class="muted">连线: 34条配对（点击查看距离）</div>`;
+        return div;
+      };
+      legend.addTo(map);
+    </script>
+  </body>
+</html>