548 lines
24 KiB
Python
548 lines
24 KiB
Python
"""html — moved verbatim from graphify/export.py."""
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from __future__ import annotations
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from graphify.exporters.base import COMMUNITY_COLORS # noqa: E402,F401
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from pathlib import Path
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import html as _html
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from graphify.analyze import _node_community_map
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import json
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import networkx as nx
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from graphify.security import sanitize_label
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MAX_NODES_FOR_VIZ = 5_000
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def _viz_node_limit() -> int:
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"""Return the effective viz node limit, honoring GRAPHIFY_VIZ_NODE_LIMIT env var.
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Falls back to MAX_NODES_FOR_VIZ when the env var is unset, empty, or non-integer.
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Set to 0 to disable HTML viz unconditionally (useful for CI runners).
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"""
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import os
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raw = os.environ.get("GRAPHIFY_VIZ_NODE_LIMIT")
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if raw is None or not raw.strip():
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return MAX_NODES_FOR_VIZ
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try:
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return int(raw)
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except ValueError:
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return MAX_NODES_FOR_VIZ
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def _html_styles() -> str:
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return """<style>
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* { box-sizing: border-box; margin: 0; padding: 0; }
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body { background: #0f0f1a; color: #e0e0e0; font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif; display: flex; height: 100vh; overflow: hidden; }
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#graph { flex: 1; }
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#sidebar { width: 280px; background: #1a1a2e; border-left: 1px solid #2a2a4e; display: flex; flex-direction: column; overflow: hidden; }
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#search-wrap { padding: 12px; border-bottom: 1px solid #2a2a4e; }
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#search { width: 100%; background: #0f0f1a; border: 1px solid #3a3a5e; color: #e0e0e0; padding: 7px 10px; border-radius: 6px; font-size: 13px; outline: none; }
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#search:focus { border-color: #4E79A7; }
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#search-results { max-height: 140px; overflow-y: auto; padding: 4px 12px; border-bottom: 1px solid #2a2a4e; display: none; }
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.search-item { padding: 4px 6px; cursor: pointer; border-radius: 4px; font-size: 12px; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; }
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.search-item:hover { background: #2a2a4e; }
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#info-panel { padding: 14px; border-bottom: 1px solid #2a2a4e; min-height: 140px; }
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#info-panel h3 { font-size: 13px; color: #aaa; margin-bottom: 8px; text-transform: uppercase; letter-spacing: 0.05em; }
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#info-content { font-size: 13px; color: #ccc; line-height: 1.6; }
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#info-content .field { margin-bottom: 5px; }
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#info-content .field b { color: #e0e0e0; }
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#info-content .empty { color: #555; font-style: italic; }
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.neighbor-link { display: block; padding: 2px 6px; margin: 2px 0; border-radius: 3px; cursor: pointer; font-size: 12px; white-space: nowrap; overflow: hidden; text-overflow: ellipsis; border-left: 3px solid #333; }
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.neighbor-link:hover { background: #2a2a4e; }
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#neighbors-list { max-height: 160px; overflow-y: auto; margin-top: 4px; }
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#legend-wrap { flex: 1; overflow-y: auto; padding: 12px; }
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#legend-wrap h3 { font-size: 13px; color: #aaa; margin-bottom: 10px; text-transform: uppercase; letter-spacing: 0.05em; }
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.legend-item { display: flex; align-items: center; gap: 8px; padding: 4px 0; cursor: pointer; border-radius: 4px; font-size: 12px; }
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.legend-item:hover { background: #2a2a4e; padding-left: 4px; }
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.legend-item.dimmed { opacity: 0.35; }
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.legend-dot { width: 12px; height: 12px; border-radius: 50%; flex-shrink: 0; }
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.legend-label { flex: 1; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }
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.legend-count { color: #666; font-size: 11px; }
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#stats { padding: 10px 14px; border-top: 1px solid #2a2a4e; font-size: 11px; color: #555; }
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#legend-controls { display: flex; align-items: center; gap: 8px; margin-bottom: 8px; padding: 4px 0; }
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#legend-controls label { display: flex; align-items: center; gap: 6px; cursor: pointer; font-size: 12px; color: #aaa; user-select: none; }
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#legend-controls label:hover { color: #e0e0e0; }
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.legend-cb, #select-all-cb { appearance: none; -webkit-appearance: none; width: 14px; height: 14px; border: 1.5px solid #3a3a5e; border-radius: 3px; background: #0f0f1a; cursor: pointer; position: relative; flex-shrink: 0; }
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.legend-cb:checked, #select-all-cb:checked { background: #4E79A7; border-color: #4E79A7; }
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.legend-cb:checked::after, #select-all-cb:checked::after { content: ''; position: absolute; left: 3.5px; top: 1px; width: 4px; height: 7px; border: solid #fff; border-width: 0 2px 2px 0; transform: rotate(45deg); }
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#select-all-cb:indeterminate { background: #4E79A7; border-color: #4E79A7; }
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#select-all-cb:indeterminate::after { content: ''; position: absolute; left: 2px; top: 5px; width: 8px; height: 2px; background: #fff; border: none; transform: none; }
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</style>"""
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def _hyperedge_script(hyperedges_json: str) -> str:
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return f"""<script>
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// Render hyperedges as shaded regions
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const hyperedges = {hyperedges_json};
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// afterDrawing passes ctx already transformed to network coordinate space.
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// Draw node positions raw — no manual pan/zoom/DPR math needed.
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network.on('afterDrawing', function(ctx) {{
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hyperedges.forEach(h => {{
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const positions = h.nodes
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.map(nid => network.getPositions([nid])[nid])
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.filter(p => p !== undefined);
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if (positions.length < 2) return;
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ctx.save();
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ctx.globalAlpha = 0.12;
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ctx.fillStyle = '#6366f1';
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ctx.strokeStyle = '#6366f1';
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ctx.lineWidth = 2;
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ctx.beginPath();
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// Centroid and expanded hull in network coordinates
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const cx = positions.reduce((s, p) => s + p.x, 0) / positions.length;
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const cy = positions.reduce((s, p) => s + p.y, 0) / positions.length;
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const expanded = positions.map(p => ({{
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x: cx + (p.x - cx) * 1.15,
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y: cy + (p.y - cy) * 1.15
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}}));
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ctx.moveTo(expanded[0].x, expanded[0].y);
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expanded.slice(1).forEach(p => ctx.lineTo(p.x, p.y));
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ctx.closePath();
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ctx.fill();
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ctx.globalAlpha = 0.4;
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ctx.stroke();
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// Label
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ctx.globalAlpha = 0.8;
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ctx.fillStyle = '#4f46e5';
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ctx.font = 'bold 11px sans-serif';
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ctx.textAlign = 'center';
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ctx.fillText(h.label, cx, cy - 5);
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ctx.restore();
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}});
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}});
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</script>"""
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def _html_script(nodes_json: str, edges_json: str, legend_json: str) -> str:
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return f"""<script>
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const RAW_NODES = {nodes_json};
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const RAW_EDGES = {edges_json};
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const LEGEND = {legend_json};
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// HTML-escape helper — prevents XSS when injecting graph data into innerHTML
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function esc(s) {{
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return String(s).replace(/&/g,'&').replace(/</g,'<').replace(/>/g,'>').replace(/"/g,'"').replace(/'/g,''');
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}}
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// Build vis datasets
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const nodesDS = new vis.DataSet(RAW_NODES.map(n => ({{
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id: n.id, label: n.label, color: n.color, size: n.size,
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font: n.font, title: n.title,
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_community: n.community, _community_name: n.community_name,
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_source_file: n.source_file, _file_type: n.file_type, _degree: n.degree,
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}})));
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const edgesDS = new vis.DataSet(RAW_EDGES.map((e, i) => ({{
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id: i, from: e.from, to: e.to,
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label: '',
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title: e.title,
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dashes: e.dashes,
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width: e.width,
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color: e.color,
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arrows: {{ to: {{ enabled: true, scaleFactor: 0.5 }} }},
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}})));
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const container = document.getElementById('graph');
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const network = new vis.Network(container, {{ nodes: nodesDS, edges: edgesDS }}, {{
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physics: {{
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enabled: true,
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solver: 'forceAtlas2Based',
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forceAtlas2Based: {{
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gravitationalConstant: -60,
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centralGravity: 0.005,
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springLength: 120,
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springConstant: 0.08,
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damping: 0.4,
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avoidOverlap: 0.8,
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}},
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stabilization: {{ iterations: 200, fit: true }},
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}},
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interaction: {{
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hover: true,
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tooltipDelay: 100,
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hideEdgesOnDrag: true,
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navigationButtons: false,
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keyboard: false,
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}},
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nodes: {{ shape: 'dot', borderWidth: 1.5 }},
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edges: {{ smooth: {{ type: 'continuous', roundness: 0.2 }}, selectionWidth: 3 }},
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}});
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network.once('stabilizationIterationsDone', () => {{
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network.setOptions({{ physics: {{ enabled: false }} }});
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}});
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function showInfo(nodeId) {{
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const n = nodesDS.get(nodeId);
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if (!n) return;
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const neighborIds = network.getConnectedNodes(nodeId);
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const neighborItems = neighborIds.map(nid => {{
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const nb = nodesDS.get(nid);
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const color = nb ? nb.color.background : '#555';
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return `<span class="neighbor-link" style="border-left-color:${{esc(color)}}" onclick="focusNode(${{JSON.stringify(nid)}})">${{esc(nb ? nb.label : nid)}}</span>`;
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}}).join('');
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document.getElementById('info-content').innerHTML = `
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<div class="field"><b>${{esc(n.label)}}</b></div>
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<div class="field">Type: ${{esc(n._file_type || 'unknown')}}</div>
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<div class="field">Community: ${{esc(n._community_name)}}</div>
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<div class="field">Source: ${{esc(n._source_file || '-')}}</div>
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<div class="field">Degree: ${{n._degree}}</div>
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${{neighborIds.length ? `<div class="field" style="margin-top:8px;color:#aaa;font-size:11px">Neighbors (${{neighborIds.length}})</div><div id="neighbors-list">${{neighborItems}}</div>` : ''}}
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`;
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}}
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function focusNode(nodeId) {{
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network.focus(nodeId, {{ scale: 1.4, animation: true }});
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network.selectNodes([nodeId]);
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showInfo(nodeId);
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}}
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// Track hovered node — hover detection is more reliable than click params
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let hoveredNodeId = null;
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network.on('hoverNode', params => {{
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hoveredNodeId = params.node;
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container.style.cursor = 'pointer';
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}});
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network.on('blurNode', () => {{
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hoveredNodeId = null;
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container.style.cursor = 'default';
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}});
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container.addEventListener('click', () => {{
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if (hoveredNodeId !== null) {{
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showInfo(hoveredNodeId);
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network.selectNodes([hoveredNodeId]);
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}}
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}});
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network.on('click', params => {{
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if (params.nodes.length > 0) {{
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showInfo(params.nodes[0]);
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}} else if (hoveredNodeId === null) {{
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document.getElementById('info-content').innerHTML = '<span class="empty">Click a node to inspect it</span>';
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}}
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}});
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const searchInput = document.getElementById('search');
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const searchResults = document.getElementById('search-results');
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searchInput.addEventListener('input', () => {{
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const q = searchInput.value.toLowerCase().trim();
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searchResults.innerHTML = '';
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if (!q) {{ searchResults.style.display = 'none'; return; }}
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const matches = RAW_NODES.filter(n => n.label.toLowerCase().includes(q)).slice(0, 20);
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if (!matches.length) {{ searchResults.style.display = 'none'; return; }}
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searchResults.style.display = 'block';
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matches.forEach(n => {{
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const el = document.createElement('div');
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el.className = 'search-item';
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el.textContent = n.label;
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el.style.borderLeft = `3px solid ${{n.color.background}}`;
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el.style.paddingLeft = '8px';
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el.onclick = () => {{
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network.focus(n.id, {{ scale: 1.5, animation: true }});
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network.selectNodes([n.id]);
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showInfo(n.id);
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searchResults.style.display = 'none';
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searchInput.value = '';
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}};
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searchResults.appendChild(el);
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}});
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}});
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document.addEventListener('click', e => {{
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if (!searchResults.contains(e.target) && e.target !== searchInput)
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searchResults.style.display = 'none';
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}});
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const hiddenCommunities = new Set();
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const selectAllCb = document.getElementById('select-all-cb');
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function updateSelectAllState() {{
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const total = LEGEND.length;
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const hidden = hiddenCommunities.size;
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selectAllCb.checked = hidden === 0;
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selectAllCb.indeterminate = hidden > 0 && hidden < total;
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}}
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function toggleAllCommunities(hide) {{
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document.querySelectorAll('.legend-item').forEach(item => {{
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hide ? item.classList.add('dimmed') : item.classList.remove('dimmed');
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}});
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document.querySelectorAll('.legend-cb').forEach(cb => {{
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cb.checked = !hide;
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}});
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LEGEND.forEach(c => {{
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if (hide) hiddenCommunities.add(c.cid); else hiddenCommunities.delete(c.cid);
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}});
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const updates = RAW_NODES.map(n => ({{ id: n.id, hidden: hide }}));
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nodesDS.update(updates);
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updateSelectAllState();
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}}
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const legendEl = document.getElementById('legend');
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LEGEND.forEach(c => {{
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const item = document.createElement('div');
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item.className = 'legend-item';
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const cb = document.createElement('input');
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cb.type = 'checkbox';
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cb.className = 'legend-cb';
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cb.checked = true;
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cb.addEventListener('change', (e) => {{
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e.stopPropagation();
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if (cb.checked) {{
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hiddenCommunities.delete(c.cid);
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item.classList.remove('dimmed');
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}} else {{
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hiddenCommunities.add(c.cid);
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item.classList.add('dimmed');
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}}
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const updates = RAW_NODES
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.filter(n => n.community === c.cid)
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.map(n => ({{ id: n.id, hidden: !cb.checked }}));
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nodesDS.update(updates);
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updateSelectAllState();
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}});
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item.innerHTML = `<div class="legend-dot" style="background:${{c.color}}"></div>
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<span class="legend-label">${{c.label}}</span>
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<span class="legend-count">${{c.count}}</span>`;
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item.prepend(cb);
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item.onclick = (e) => {{
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if (e.target === cb) return;
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cb.checked = !cb.checked;
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cb.dispatchEvent(new Event('change'));
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}};
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legendEl.appendChild(item);
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}});
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</script>"""
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def to_html(
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G: nx.Graph,
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communities: dict[int, list[str]],
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output_path: str,
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community_labels: dict[int, str] | None = None,
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member_counts: dict[int, int] | None = None,
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node_limit: int | None = None,
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learning_overlay: dict | None = None,
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) -> None:
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"""Generate an interactive vis.js HTML visualization of the graph.
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Features: node size by degree, click-to-inspect panel, search box,
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community filter, physics clustering by community, confidence-styled edges.
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Raises ValueError if graph exceeds MAX_NODES_FOR_VIZ.
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If member_counts is provided (aggregated community view), node sizes are
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based on community member counts rather than graph degree.
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If node_limit is set and the graph exceeds it, automatically builds an
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aggregated community-level meta-graph instead of raising ValueError.
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"""
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limit = node_limit if node_limit is not None else _viz_node_limit()
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if G.number_of_nodes() > limit:
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if node_limit is not None:
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# Build aggregated community meta-graph
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from collections import Counter as _Counter
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import networkx as _nx
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print(f"Graph has {G.number_of_nodes()} nodes (above {limit} limit). Building aggregated community view...")
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node_to_community = {nid: cid for cid, members in communities.items() for nid in members}
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meta = _nx.Graph()
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for cid, members in communities.items():
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meta.add_node(str(cid), label=(community_labels or {}).get(cid, f"Community {cid}"))
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edge_counts = _Counter()
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for u, v in G.edges():
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cu, cv = node_to_community.get(u), node_to_community.get(v)
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if cu is not None and cv is not None and cu != cv:
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edge_counts[(min(cu, cv), max(cu, cv))] += 1
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for (cu, cv), w in edge_counts.items():
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meta.add_edge(str(cu), str(cv), weight=w,
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relation=f"{w} cross-community edges", confidence="AGGREGATED")
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if meta.number_of_nodes() <= 1:
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print("Single community - aggregated view not useful. Skipping graph.html.")
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return
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meta_communities = {cid: [str(cid)] for cid in communities}
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mc = {cid: len(members) for cid, members in communities.items()}
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# Remap hyperedges from semantic node IDs to community IDs
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raw_hyperedges = G.graph.get("hyperedges", [])
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if raw_hyperedges:
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remapped = []
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for he in raw_hyperedges:
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he_members = he.get("nodes", [])
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comm_ids, seen = [], set()
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for nid in he_members:
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c = node_to_community.get(nid)
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if c is None:
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continue
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s = str(c)
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if s in seen:
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continue
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seen.add(s)
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comm_ids.append(s)
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if len(comm_ids) < 2:
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continue
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remapped.append({
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"id": he.get("id", ""),
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"label": he.get("label") or he.get("relation", "").replace("_", " "),
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"nodes": comm_ids,
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})
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meta.graph["hyperedges"] = remapped
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to_html(meta, meta_communities, output_path,
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community_labels=community_labels, member_counts=mc)
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print(f"graph.html written (aggregated: {meta.number_of_nodes()} community nodes, {meta.number_of_edges()} cross-community edges)")
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print("Tip: run with --obsidian for full node-level detail.")
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return
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raise ValueError(
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f"Graph has {G.number_of_nodes()} nodes - too large for HTML viz "
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f"(limit: {limit}). Use --no-viz, raise GRAPHIFY_VIZ_NODE_LIMIT, "
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f"or reduce input size."
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)
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node_community = _node_community_map(communities)
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degree = dict(G.degree())
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max_deg = max(degree.values(), default=1) or 1
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max_mc = (max(member_counts.values(), default=1) or 1) if member_counts else 1
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# Work-memory overlay (derived sidecar). When not passed explicitly, load it
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# best-effort from the sibling .graphify_learning.json next to the output
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# graph.html (which lives beside graph.json). Empty/missing => no learning
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# fields, so the un-annotated render is byte-identical to pre-feature.
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if learning_overlay is None:
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learning_overlay = {}
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|
try:
|
|
from graphify.reflect import load_learning_overlay as _llo
|
|
learning_overlay = _llo(Path(output_path))
|
|
except Exception:
|
|
learning_overlay = {}
|
|
# Status -> ring color. preferred=green, contested=amber. Tentative gets no
|
|
# ring (it's not yet trustworthy enough to highlight in the map).
|
|
_RING = {"preferred": "#22c55e", "contested": "#f59e0b"}
|
|
|
|
# Build nodes list for vis.js
|
|
vis_nodes = []
|
|
for node_id, data in G.nodes(data=True):
|
|
cid = node_community.get(node_id, 0)
|
|
color = COMMUNITY_COLORS[cid % len(COMMUNITY_COLORS)]
|
|
label = sanitize_label(data.get("label", node_id))
|
|
deg = degree.get(node_id, 1)
|
|
if member_counts:
|
|
mc = member_counts.get(cid, 1)
|
|
size = 10 + 30 * (mc / max_mc)
|
|
font_size = 12
|
|
else:
|
|
size = 10 + 30 * (deg / max_deg)
|
|
# Only show label for high-degree nodes by default; others show on hover
|
|
font_size = 12 if deg >= max_deg * 0.15 else 0
|
|
node = {
|
|
"id": node_id,
|
|
"label": label,
|
|
"color": {"background": color, "border": color, "highlight": {"background": "#ffffff", "border": color}},
|
|
"size": round(size, 1),
|
|
"font": {"size": font_size, "color": "#ffffff"},
|
|
"title": _html.escape(label),
|
|
"community": cid,
|
|
"community_name": sanitize_label((community_labels or {}).get(cid, f"Community {cid}")),
|
|
"source_file": sanitize_label(str(data.get("source_file") or "")),
|
|
"file_type": data.get("file_type", ""),
|
|
"degree": deg,
|
|
}
|
|
# Conditional learning fields — only present for annotated nodes, so
|
|
# un-annotated output keeps the exact pre-feature node dict shape.
|
|
entry = learning_overlay.get(str(node_id)) if learning_overlay else None
|
|
if entry:
|
|
status = sanitize_label(str(entry.get("status", "")))
|
|
stale = bool(entry.get("stale"))
|
|
node["learning_status"] = status
|
|
node["learning_stale"] = stale
|
|
ring = _RING.get(status)
|
|
if ring:
|
|
# Status-colored ring via the border; stale => desaturated +
|
|
# dashed (vis.js supports per-node `shapeProperties.borderDashes`).
|
|
if stale:
|
|
ring = "#9ca3af"
|
|
node["shapeProperties"] = {"borderDashes": [4, 4]}
|
|
node["borderWidth"] = 3
|
|
node["color"] = {
|
|
"background": color, "border": ring,
|
|
"highlight": {"background": "#ffffff", "border": ring},
|
|
}
|
|
# Lesson line appended to the hover title.
|
|
if status == "contested":
|
|
lesson = f"Lesson: contested (useful {entry.get('uses', 0)} / dead-end {entry.get('neg', 0)})"
|
|
elif status == "preferred":
|
|
lesson = f"Lesson: preferred source ({entry.get('uses', 0)} useful, score={entry.get('score', 0)})"
|
|
else:
|
|
lesson = f"Lesson: {status} ({entry.get('uses', 0)} useful)"
|
|
if stale:
|
|
lesson += " [code changed — re-verify]"
|
|
node["title"] = _html.escape(label) + "\n" + _html.escape(sanitize_label(lesson))
|
|
vis_nodes.append(node)
|
|
|
|
# Build edges list. Restore original edge direction from _src/_tgt
|
|
# (stashed by build.py for exactly this reason): undirected NetworkX
|
|
# canonicalizes endpoint order, which would otherwise flip the arrow
|
|
# for `calls` and `rationale_for` in the rendered graph (#563).
|
|
vis_edges = []
|
|
for u, v, data in G.edges(data=True):
|
|
confidence = data.get("confidence", "EXTRACTED")
|
|
relation = data.get("relation", "")
|
|
true_src = data.get("_src", u)
|
|
true_tgt = data.get("_tgt", v)
|
|
vis_edges.append({
|
|
"from": true_src,
|
|
"to": true_tgt,
|
|
"label": relation,
|
|
"title": _html.escape(f"{relation} [{confidence}]"),
|
|
"dashes": confidence != "EXTRACTED",
|
|
"width": 2 if confidence == "EXTRACTED" else 1,
|
|
"color": {"opacity": 0.7 if confidence == "EXTRACTED" else 0.35},
|
|
"confidence": confidence,
|
|
})
|
|
|
|
# Build community legend data
|
|
legend_data = []
|
|
for cid in sorted((community_labels or {}).keys()):
|
|
color = COMMUNITY_COLORS[cid % len(COMMUNITY_COLORS)]
|
|
lbl = _html.escape(sanitize_label((community_labels or {}).get(cid, f"Community {cid}")))
|
|
n = member_counts.get(cid, len(communities.get(cid, []))) if member_counts else len(communities.get(cid, []))
|
|
legend_data.append({"cid": cid, "color": color, "label": lbl, "count": n})
|
|
|
|
# Escape </script> sequences so embedded JSON cannot break out of the script tag
|
|
def _js_safe(obj) -> str:
|
|
return json.dumps(obj).replace("</", "<\\/")
|
|
|
|
nodes_json = _js_safe(vis_nodes)
|
|
edges_json = _js_safe(vis_edges)
|
|
legend_json = _js_safe(legend_data)
|
|
hyperedges_json = _js_safe(getattr(G, "graph", {}).get("hyperedges", []))
|
|
title = _html.escape(sanitize_label(str(output_path)))
|
|
stats = f"{G.number_of_nodes()} nodes · {G.number_of_edges()} edges · {len(communities)} communities"
|
|
|
|
html = f"""<!DOCTYPE html>
|
|
<html lang="en">
|
|
<head>
|
|
<meta charset="UTF-8">
|
|
<title>graphify - {title}</title>
|
|
<script src="https://unpkg.com/vis-network@9.1.6/standalone/umd/vis-network.min.js"
|
|
integrity="sha384-Ux6phic9PEHJ38YtrijhkzyJ8yQlH8i/+buBR8s3mAZOJrP1gwyvAcIYl3GWtpX1"
|
|
crossorigin="anonymous"></script>
|
|
{_html_styles()}
|
|
</head>
|
|
<body>
|
|
<div id="graph"></div>
|
|
<div id="sidebar">
|
|
<div id="search-wrap">
|
|
<input id="search" type="text" placeholder="Search nodes..." autocomplete="off">
|
|
<div id="search-results"></div>
|
|
</div>
|
|
<div id="info-panel">
|
|
<h3>Node Info</h3>
|
|
<div id="info-content"><span class="empty">Click a node to inspect it</span></div>
|
|
</div>
|
|
<div id="legend-wrap">
|
|
<h3>Communities</h3>
|
|
<div id="legend-controls">
|
|
<label><input type="checkbox" id="select-all-cb" checked onchange="toggleAllCommunities(!this.checked)">Select All</label>
|
|
</div>
|
|
<div id="legend"></div>
|
|
</div>
|
|
<div id="stats">{stats}</div>
|
|
</div>
|
|
{_html_script(nodes_json, edges_json, legend_json)}
|
|
{_hyperedge_script(hyperedges_json)}
|
|
</body>
|
|
</html>"""
|
|
|
|
Path(output_path).write_text(html, encoding="utf-8") # nosec
|