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<div id="stats">157 nodes &middot; 334 edges &middot; 10 communities</div>
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"width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_build_mixed_role_dataset", "to": "grpo_train_create_dataset", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_create_dataset", "to": "grpo_train_run_workflow", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_evaluate_bug_sample", "to": "grpo_train_evaluate_solver_fixed_set", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_evaluate_solver_fixed_set", "to": "grpo_train_generate_code", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_evaluate_solver_fixed_set", "to": "grpo_train_summarize_solver_results", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_evaluate_solver_fixed_set", "to": "grpo_train_run_workflow", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_evaluate_proposer_fixed_set", "to": "grpo_train_generate_code", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_evaluate_proposer_fixed_set", "to": "grpo_train_summarize_proposer_results", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_evaluate_proposer_fixed_set", "to": "grpo_train_summarize_proposer_by_seed", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_evaluate_proposer_fixed_set", "to": "grpo_train_summarize_proposer_by_bug_family", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_evaluate_proposer_fixed_set", "to": "grpo_train_run_workflow", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_build_weighted_proposer_rows", "to": "grpo_train_load_prior_seed_break_rates", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_build_weighted_proposer_rows", "to": "grpo_train_choose_proposer_bug_focus", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_save_metrics_artifact", "to": "grpo_train_run_workflow", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_get_training_profile", "to": "grpo_train_create_trainer", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_load_training_model_and_tokenizer", "to": "grpo_train_build_tiny_local_model_and_tokenizer", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_load_training_model_and_tokenizer", "to": "grpo_train_run_workflow", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_get_trl_classes", "to": "grpo_train_create_trainer", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_create_trainer", "to": "grpo_train_run_workflow", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_save_results_plot", "to": "grpo_train_run_workflow", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}, {"from": "grpo_train_run_workflow", "to": "grpo_train_main", "label": "calls", "title": "calls [EXTRACTED]", "dashes": false, "width": 2, "color": {"opacity": 0.7}, "confidence": "EXTRACTED"}];
const LEGEND = [{"cid": 0, "color": "#4E79A7", "label": "Community 0", "count": 34}, {"cid": 1, "color": "#F28E2B", "label": "Community 1", "count": 33}, {"cid": 2, "color": "#E15759", "label": "Community 2", "count": 22}, {"cid": 3, "color": "#76B7B2", "label": "Community 3", "count": 22}, {"cid": 4, "color": "#59A14F", "label": "Community 4", "count": 15}, {"cid": 5, "color": "#EDC948", "label": "Community 5", "count": 13}, {"cid": 6, "color": "#B07AA1", "label": "Community 6", "count": 11}, {"cid": 7, "color": "#FF9DA7", "label": "Community 7", "count": 4}, {"cid": 8, "color": "#9C755F", "label": "Community 8", "count": 2}, {"cid": 9, "color": "#BAB0AC", "label": "Community 9", "count": 1}];
// HTML-escape helper — prevents XSS when injecting graph data into innerHTML
function esc(s) {
return String(s).replace(/&/g,'&amp;').replace(/</g,'&lt;').replace(/>/g,'&gt;').replace(/"/g,'&quot;').replace(/'/g,'&#39;');
}
// Build vis datasets
const nodesDS = new vis.DataSet(RAW_NODES.map(n => ({
id: n.id, label: n.label, color: n.color, size: n.size,
font: n.font, title: n.title,
_community: n.community, _community_name: n.community_name,
_source_file: n.source_file, _file_type: n.file_type, _degree: n.degree,
})));
const edgesDS = new vis.DataSet(RAW_EDGES.map((e, i) => ({
id: i, from: e.from, to: e.to,
label: '',
title: e.title,
dashes: e.dashes,
width: e.width,
color: e.color,
arrows: { to: { enabled: true, scaleFactor: 0.5 } },
})));
const container = document.getElementById('graph');
const network = new vis.Network(container, { nodes: nodesDS, edges: edgesDS }, {
physics: {
enabled: true,
solver: 'forceAtlas2Based',
forceAtlas2Based: {
gravitationalConstant: -60,
centralGravity: 0.005,
springLength: 120,
springConstant: 0.08,
damping: 0.4,
avoidOverlap: 0.8,
},
stabilization: { iterations: 200, fit: true },
},
interaction: {
hover: true,
tooltipDelay: 100,
hideEdgesOnDrag: true,
navigationButtons: false,
keyboard: false,
},
nodes: { shape: 'dot', borderWidth: 1.5 },
edges: { smooth: { type: 'continuous', roundness: 0.2 }, selectionWidth: 3 },
});
network.once('stabilizationIterationsDone', () => {
network.setOptions({ physics: { enabled: false } });
});
function showInfo(nodeId) {
const n = nodesDS.get(nodeId);
if (!n) return;
const neighborIds = network.getConnectedNodes(nodeId);
const neighborItems = neighborIds.map(nid => {
const nb = nodesDS.get(nid);
const color = nb ? nb.color.background : '#555';
return `<span class="neighbor-link" style="border-left-color:${esc(color)}" onclick="focusNode(${JSON.stringify(nid)})">${esc(nb ? nb.label : nid)}</span>`;
}).join('');
document.getElementById('info-content').innerHTML = `
<div class="field"><b>${esc(n.label)}</b></div>
<div class="field">Type: ${esc(n._file_type || 'unknown')}</div>
<div class="field">Community: ${esc(n._community_name)}</div>
<div class="field">Source: ${esc(n._source_file || '-')}</div>
<div class="field">Degree: ${n._degree}</div>
${neighborIds.length ? `<div class="field" style="margin-top:8px;color:#aaa;font-size:11px">Neighbors (${neighborIds.length})</div><div id="neighbors-list">${neighborItems}</div>` : ''}
`;
}
function focusNode(nodeId) {
network.focus(nodeId, { scale: 1.4, animation: true });
network.selectNodes([nodeId]);
showInfo(nodeId);
}
// Track hovered node — hover detection is more reliable than click params
let hoveredNodeId = null;
network.on('hoverNode', params => {
hoveredNodeId = params.node;
container.style.cursor = 'pointer';
});
network.on('blurNode', () => {
hoveredNodeId = null;
container.style.cursor = 'default';
});
container.addEventListener('click', () => {
if (hoveredNodeId !== null) {
showInfo(hoveredNodeId);
network.selectNodes([hoveredNodeId]);
}
});
network.on('click', params => {
if (params.nodes.length > 0) {
showInfo(params.nodes[0]);
} else if (hoveredNodeId === null) {
document.getElementById('info-content').innerHTML = '<span class="empty">Click a node to inspect it</span>';
}
});
const searchInput = document.getElementById('search');
const searchResults = document.getElementById('search-results');
searchInput.addEventListener('input', () => {
const q = searchInput.value.toLowerCase().trim();
searchResults.innerHTML = '';
if (!q) { searchResults.style.display = 'none'; return; }
const matches = RAW_NODES.filter(n => n.label.toLowerCase().includes(q)).slice(0, 20);
if (!matches.length) { searchResults.style.display = 'none'; return; }
searchResults.style.display = 'block';
matches.forEach(n => {
const el = document.createElement('div');
el.className = 'search-item';
el.textContent = n.label;
el.style.borderLeft = `3px solid ${n.color.background}`;
el.style.paddingLeft = '8px';
el.onclick = () => {
network.focus(n.id, { scale: 1.5, animation: true });
network.selectNodes([n.id]);
showInfo(n.id);
searchResults.style.display = 'none';
searchInput.value = '';
};
searchResults.appendChild(el);
});
});
document.addEventListener('click', e => {
if (!searchResults.contains(e.target) && e.target !== searchInput)
searchResults.style.display = 'none';
});
const hiddenCommunities = new Set();
const legendEl = document.getElementById('legend');
LEGEND.forEach(c => {
const item = document.createElement('div');
item.className = 'legend-item';
item.innerHTML = `<div class="legend-dot" style="background:${c.color}"></div>
<span class="legend-label">${c.label}</span>
<span class="legend-count">${c.count}</span>`;
item.onclick = () => {
if (hiddenCommunities.has(c.cid)) {
hiddenCommunities.delete(c.cid);
item.classList.remove('dimmed');
} else {
hiddenCommunities.add(c.cid);
item.classList.add('dimmed');
}
const updates = RAW_NODES
.filter(n => n.community === c.cid)
.map(n => ({ id: n.id, hidden: hiddenCommunities.has(c.cid) }));
nodesDS.update(updates);
};
legendEl.appendChild(item);
});
</script>
<script>
// Render hyperedges as shaded regions
const hyperedges = [];
// afterDrawing passes ctx already transformed to network coordinate space.
// Draw node positions raw — no manual pan/zoom/DPR math needed.
network.on('afterDrawing', function(ctx) {
hyperedges.forEach(h => {
const positions = h.nodes
.map(nid => network.getPositions([nid])[nid])
.filter(p => p !== undefined);
if (positions.length < 2) return;
ctx.save();
ctx.globalAlpha = 0.12;
ctx.fillStyle = '#6366f1';
ctx.strokeStyle = '#6366f1';
ctx.lineWidth = 2;
ctx.beginPath();
// Centroid and expanded hull in network coordinates
const cx = positions.reduce((s, p) => s + p.x, 0) / positions.length;
const cy = positions.reduce((s, p) => s + p.y, 0) / positions.length;
const expanded = positions.map(p => ({
x: cx + (p.x - cx) * 1.15,
y: cy + (p.y - cy) * 1.15
}));
ctx.moveTo(expanded[0].x, expanded[0].y);
expanded.slice(1).forEach(p => ctx.lineTo(p.x, p.y));
ctx.closePath();
ctx.fill();
ctx.globalAlpha = 0.4;
ctx.stroke();
// Label
ctx.globalAlpha = 0.8;
ctx.fillStyle = '#4f46e5';
ctx.font = 'bold 11px sans-serif';
ctx.textAlign = 'center';
ctx.fillText(h.label, cx, cy - 5);
ctx.restore();
});
});
</script>
</body>
</html>