feat(seaborn): implement network-force-directed (#5433)

## Implementation: `network-force-directed` - python/seaborn

Implements the **python/seaborn** version of `network-force-directed`.

**File:**
`plots/network-force-directed/implementations/python/seaborn.py`

**Parent Issue:** #990

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/anyplot/actions/runs/24952470496)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/network-force-directed/implementations/python/seaborn.py

@@ -1,26 +1,52 @@
-""" pyplots.ai
+""" anyplot.ai
 network-force-directed: Force-Directed Graph
-Library: seaborn 0.13.2 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-23
+Library: seaborn 0.13.2 | Python 3.14.4
+Quality: 86/100 | Updated: 2026-04-26
 """
 
+import os
+
 import matplotlib.pyplot as plt
 import numpy as np
 import seaborn as sns
 
 
-# Set seaborn style
-sns.set_theme(style="white")
+# Theme-adaptive chrome
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
+INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
+EDGE_COLOR = "#4A4A44" if THEME == "light" else "#B8B7B0"
+
+sns.set_theme(
+    style="ticks",
+    rc={
+        "figure.facecolor": PAGE_BG,
+        "axes.facecolor": PAGE_BG,
+        "axes.edgecolor": INK_SOFT,
+        "axes.labelcolor": INK,
+        "text.color": INK,
+        "xtick.color": INK_SOFT,
+        "ytick.color": INK_SOFT,
+        "grid.color": INK,
+        "grid.alpha": 0.10,
+        "legend.facecolor": ELEVATED_BG,
+        "legend.edgecolor": INK_SOFT,
+    },
+)
 
 np.random.seed(42)
 
-# Create sample social network data - organization with 3 departments
+# Okabe-Ito categorical palette (first series always #009E73)
+OKABE_ITO = ["#009E73", "#D55E00", "#0072B2"]
+
+# Sample social network: organization with 3 departments
 num_nodes = 37
 community_sizes = [15, 12, 10]
 community_names = ["Engineering", "Marketing", "Sales"]
 communities = []
-
-# Assign nodes to communities
 for comm_idx, size in enumerate(community_sizes):
     communities.extend([comm_idx] * size)
 
@@ -29,12 +55,10 @@
 for i in range(num_nodes):
     for j in range(i + 1, num_nodes):
         if communities[i] == communities[j]:
-            # Higher connection probability within community
             if np.random.random() < 0.35:
                 weight = np.random.uniform(0.5, 1.0)
                 edges.append((i, j, weight))
         else:
-            # Lower connection probability between communities
             if np.random.random() < 0.05:
                 weight = np.random.uniform(0.3, 0.7)
                 edges.append((i, j, weight))
@@ -45,22 +69,24 @@
     degrees[src] += 1
     degrees[tgt] += 1
 
-# Force-directed layout (Fruchterman-Reingold algorithm inline)
+# Identify bridge nodes (nodes with cross-community edges)
+bridge_nodes = set()
+for src, tgt, _ in edges:
+    if communities[src] != communities[tgt]:
+        bridge_nodes.add(src)
+        bridge_nodes.add(tgt)
+
+# Force-directed layout (Fruchterman-Reingold inline)
 n = num_nodes
 k = 0.5
 iterations = 150
 
-# Initialize random positions
 pos = np.random.rand(n, 2) * 2 - 1
-
-# Temperature for simulated annealing
 t = 1.0
 dt = t / (iterations + 1)
 
 for _ in range(iterations):
-    # Calculate repulsive forces between all pairs
     disp = np.zeros((n, 2))
-
     for i in range(n):
         for j in range(i + 1, n):
             delta = pos[i] - pos[j]
@@ -70,7 +96,6 @@
             disp[i] += force_vec
             disp[j] -= force_vec
 
-    # Calculate attractive forces along edges
     for src, tgt, _ in edges:
         delta = pos[src] - pos[tgt]
         dist = max(np.linalg.norm(delta), 0.01)
@@ -79,80 +104,80 @@
         disp[src] -= force_vec
         disp[tgt] += force_vec
 
-    # Apply displacements with temperature limiting
     for i in range(n):
         disp_norm = max(np.linalg.norm(disp[i]), 0.01)
         pos[i] += (disp[i] / disp_norm) * min(disp_norm, t)
 
-    # Cool down
     t -= dt
 
-# Normalize positions to [-1, 1]
+# Normalize positions
 pos -= pos.mean(axis=0)
 max_coord = np.abs(pos).max()
 if max_coord > 0:
     pos /= max_coord
 
-positions = pos
-
-# Extract positions
-x_coords = positions[:, 0]
-y_coords = positions[:, 1]
+x_coords = pos[:, 0]
+y_coords = pos[:, 1]
 
-# Node sizes based on degree (hub nodes are larger)
+# Node sizes based on degree
 node_sizes = [150 + degree * 60 for degree in degrees]
 
-# Create figure
 fig, ax = plt.subplots(figsize=(16, 9))
 
-# Define community colors using colorblind-safe palette
-community_colors = ["#306998", "#FFD43B", "#E74C3C"]  # Python Blue, Yellow, Red
-
 # Draw edges
 for src, tgt, weight in edges:
-    x0, y0 = positions[src]
-    x1, y1 = positions[tgt]
-    ax.plot([x0, x1], [y0, y1], color="#CCCCCC", linewidth=1 + weight * 2, alpha=0.5, zorder=1)
+    x0, y0 = pos[src]
+    x1, y1 = pos[tgt]
+    ax.plot([x0, x1], [y0, y1], color=EDGE_COLOR, linewidth=1 + weight * 2, alpha=0.25, zorder=1)
 
-# Draw nodes using seaborn scatterplot
+# Draw nodes via seaborn (Okabe-Ito palette)
 sns.scatterplot(
     x=x_coords,
     y=y_coords,
     hue=communities,
-    palette=community_colors,
+    palette=OKABE_ITO,
     size=node_sizes,
     sizes=(150, 800),
-    alpha=0.85,
-    edgecolor="white",
+    alpha=0.9,
+    edgecolor=PAGE_BG,
     linewidth=2,
     ax=ax,
     legend=False,
     zorder=2,
 )
 
-# Add labels for high-degree nodes (hubs)
+# Emphasize bridge nodes (cross-community connectors) with a ring outline
+bridge_x = [pos[i, 0] for i in bridge_nodes]
+bridge_y = [pos[i, 1] for i in bridge_nodes]
+bridge_sizes = [(node_sizes[i] + 200) for i in bridge_nodes]
+ax.scatter(bridge_x, bridge_y, s=bridge_sizes, facecolors="none", edgecolors=INK, linewidth=1.8, alpha=0.65, zorder=3)
+
+# Hub labels (75th-percentile degree threshold)
 degree_threshold = np.percentile(degrees, 75)
 for node in range(num_nodes):
     if degrees[node] >= degree_threshold:
         ax.annotate(
             f"Node {node}",
-            (positions[node, 0], positions[node, 1]),
-            fontsize=12,
+            (pos[node, 0], pos[node, 1]),
+            fontsize=16,
             ha="center",
             va="bottom",
-            xytext=(0, 10),
+            xytext=(0, 12),
             textcoords="offset points",
             fontweight="bold",
-            color="#333333",
+            color=INK_SOFT,
         )
 
-# Create custom legend for communities
+# Custom community legend
 legend_elements = []
 for idx, name in enumerate(community_names):
     count = community_sizes[idx]
     legend_elements.append(
-        plt.scatter([], [], c=community_colors[idx], s=300, label=f"{name} ({count})", edgecolor="white", linewidth=2)
+        plt.scatter([], [], c=OKABE_ITO[idx], s=300, label=f"{name} ({count})", edgecolor=PAGE_BG, linewidth=2)
     )
+legend_elements.append(
+    plt.scatter([], [], s=300, facecolors="none", edgecolors=INK, linewidth=1.8, label="Bridge node")
+)
 
 ax.legend(
     handles=legend_elements,
@@ -161,30 +186,28 @@
     title="Department",
     title_fontsize=18,
     frameon=True,
-    fancybox=True,
-    shadow=True,
+    labelcolor=INK,
 )
 
-# Styling
-ax.set_title("network-force-directed · seaborn · pyplots.ai", fontsize=24, fontweight="bold", pad=20)
-ax.set_xlabel("Force-Directed X Position", fontsize=20)
-ax.set_ylabel("Force-Directed Y Position", fontsize=20)
+# Titles & labels
+ax.set_title("network-force-directed · seaborn · anyplot.ai", fontsize=24, fontweight="bold", pad=20, color=INK)
+ax.set_xlabel("Force-Directed X Position", fontsize=20, color=INK)
+ax.set_ylabel("Force-Directed Y Position", fontsize=20, color=INK)
 ax.tick_params(axis="both", labelsize=16)
-
-# Remove axis ticks for cleaner network visualization
 ax.set_xticks([])
 ax.set_yticks([])
 
-# Add subtle border
-for spine in ax.spines.values():
-    spine.set_color("#CCCCCC")
-    spine.set_linewidth(2)
+# Spine treatment: keep L-shape only, themed color
+ax.spines["top"].set_visible(False)
+ax.spines["right"].set_visible(False)
+ax.spines["left"].set_color(INK_SOFT)
+ax.spines["bottom"].set_color(INK_SOFT)
 
-# Add network statistics annotation
+# Network statistics annotation
 total_edges = len(edges)
 avg_degree = sum(degrees) / num_nodes
-stats_text = f"Nodes: {num_nodes} | Edges: {total_edges} | Avg Degree: {avg_degree:.1f}"
-ax.text(0.5, -0.08, stats_text, transform=ax.transAxes, fontsize=14, ha="center", va="top", color="#666666")
+stats_text = f"Nodes: {num_nodes} | Edges: {total_edges} | Avg Degree: {avg_degree:.1f} | Bridges: {len(bridge_nodes)}"
+ax.text(0.5, -0.08, stats_text, transform=ax.transAxes, fontsize=14, ha="center", va="top", color=INK_MUTED)
 
 plt.tight_layout()
-plt.savefig("plot.png", dpi=300, bbox_inches="tight", facecolor="white")
+plt.savefig(f"plot-{THEME}.png", dpi=300, bbox_inches="tight", facecolor=PAGE_BG)