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1620 1621 1622 1623 1624 1625 1626 1627 1628 1629 1630 1631 1632 1633 1634 1635 1636 1637 1638 1639 1640 | <!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>BioEnv</title>
<style>
@import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700;800&family=JetBrains+Mono:wght@400;500;600&display=swap');
:root {
--bg: #07090d;
--bg-surface: #0c0f16;
--bg-raised: #111827;
--bg-hover: #1a2235;
--border: #1e293b;
--border-active: #334155;
--text: #e2e8f0;
--text-dim: #94a3b8;
--text-muted: #475569;
--accent: #38bdf8;
--accent-dim: rgba(56,189,248,0.12);
--green: #34d399;
--green-dim: rgba(52,211,153,0.10);
--amber: #fbbf24;
--amber-dim: rgba(251,191,36,0.10);
--red: #f87171;
--red-dim: rgba(248,113,113,0.10);
--cyan: #22d3ee;
--cyan-dim: rgba(34,211,238,0.10);
--pink: #f472b6;
--purple: #a78bfa;
}
* { margin: 0; padding: 0; box-sizing: border-box; }
html, body { height: 100%; overflow: hidden; }
body {
font-family: 'Inter', -apple-system, sans-serif;
background: var(--bg);
color: var(--text);
display: flex;
flex-direction: column;
}
/* ---- Top Bar ---- */
.topbar {
height: 48px;
min-height: 48px;
background: var(--bg-surface);
border-bottom: 1px solid var(--border);
display: flex;
align-items: center;
padding: 0 20px;
gap: 16px;
z-index: 10;
}
.topbar-logo {
font-size: 15px;
font-weight: 800;
letter-spacing: -0.5px;
background: linear-gradient(135deg, #38bdf8, #22d3ee);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
}
.topbar-sep { width: 1px; height: 20px; background: var(--border); }
.topbar-env {
font-size: 12px;
color: var(--text-dim);
font-family: 'JetBrains Mono', monospace;
}
.topbar-status {
display: flex;
align-items: center;
gap: 6px;
margin-left: auto;
font-size: 12px;
color: var(--text-dim);
}
.status-dot {
width: 7px; height: 7px;
border-radius: 50%;
background: var(--text-muted);
}
.status-dot.live {
background: var(--green);
box-shadow: 0 0 8px var(--green);
animation: pulse 2s infinite;
}
@keyframes pulse {
0%, 100% { opacity: 1; }
50% { opacity: 0.5; }
}
.topbar-btn {
font-size: 12px;
font-weight: 600;
padding: 6px 14px;
border-radius: 6px;
border: none;
cursor: pointer;
transition: all 0.15s;
font-family: inherit;
}
.btn-primary { background: var(--accent); color: #07090d; font-weight: 700; }
.btn-primary:hover { background: #7dd3fc; }
.btn-primary:disabled { opacity: 0.4; cursor: not-allowed; }
.btn-ghost {
background: transparent;
color: var(--text-dim);
border: 1px solid var(--border);
}
.btn-ghost:hover { background: var(--bg-hover); color: var(--text); }
/* ---- Main Layout ---- */
.main {
flex: 1;
display: grid;
grid-template-columns: 260px 1fr 340px;
overflow: hidden;
}
/* ---- Left Sidebar ---- */
.sidebar {
background: var(--bg-surface);
border-right: 1px solid var(--border);
display: flex;
flex-direction: column;
overflow-y: auto;
}
.sidebar-section {
padding: 16px;
border-bottom: 1px solid var(--border);
}
.sidebar-heading {
font-size: 10px;
font-weight: 600;
text-transform: uppercase;
letter-spacing: 1.5px;
color: var(--text-muted);
margin-bottom: 10px;
}
.scenario-list { display: flex; flex-direction: column; gap: 4px; }
.scenario-opt {
display: flex;
align-items: center;
gap: 10px;
padding: 8px 10px;
border-radius: 6px;
cursor: pointer;
transition: all 0.15s;
border: 1px solid transparent;
}
.scenario-opt:hover { background: var(--bg-hover); }
.scenario-opt.active {
background: var(--accent-dim);
border-color: rgba(56,189,248,0.2);
}
.scenario-opt .sc-dot { width: 8px; height: 8px; border-radius: 50%; flex-shrink: 0; }
.scenario-opt .sc-name {
font-size: 12px; font-weight: 500; flex: 1;
white-space: nowrap; overflow: hidden; text-overflow: ellipsis;
}
.scenario-opt .sc-diff {
font-size: 10px; font-weight: 600;
text-transform: uppercase; letter-spacing: 0.5px;
}
.gauge { margin-bottom: 14px; }
.gauge:last-child { margin-bottom: 0; }
.gauge-header {
display: flex; justify-content: space-between;
align-items: baseline; margin-bottom: 6px;
}
.gauge-label { font-size: 12px; color: var(--text-dim); font-weight: 500; }
.gauge-value {
font-size: 12px; font-weight: 600;
font-family: 'JetBrains Mono', monospace;
}
.gauge-track {
height: 4px; background: var(--bg-hover);
border-radius: 4px; overflow: hidden;
}
.gauge-fill {
height: 100%; border-radius: 4px;
transition: width 0.8s cubic-bezier(0.4,0,0.2,1);
}
.pipeline-steps { display: flex; flex-direction: column; gap: 2px; }
.pipe-step {
display: flex; align-items: center; gap: 8px;
padding: 5px 8px; border-radius: 4px;
font-size: 11px; font-family: 'JetBrains Mono', monospace;
color: var(--text-muted);
opacity: 0; transform: translateX(-8px);
transition: all 0.3s ease;
}
.pipe-step.visible { opacity: 1; transform: translateX(0); }
.pipe-step.active { color: var(--text); background: var(--accent-dim); }
.pipe-step.done { color: var(--text-dim); }
.pipe-step .step-icon {
width: 16px; height: 16px; border-radius: 50%;
border: 1.5px solid var(--text-muted);
display: flex; align-items: center; justify-content: center;
font-size: 8px; flex-shrink: 0; transition: all 0.3s;
}
.pipe-step.done .step-icon {
background: var(--green-dim); border-color: var(--green); color: var(--green);
}
.pipe-step.active .step-icon {
border-color: var(--accent); background: var(--accent-dim);
color: var(--accent); animation: pulse 1.5s infinite;
}
/* ---- Center: Lab + Terminal ---- */
.center {
display: flex;
flex-direction: column;
overflow: hidden;
background: var(--bg);
}
/* Lab canvas */
.lab-panel {
height: 300px;
min-height: 300px;
background: var(--bg-surface);
border-bottom: 1px solid var(--border);
position: relative;
overflow: hidden;
}
.lab-panel canvas {
display: block;
width: 100%;
height: 100%;
}
.lab-label {
position: absolute;
top: 8px;
left: 12px;
font-size: 10px;
font-weight: 600;
text-transform: uppercase;
letter-spacing: 1.5px;
color: var(--text-muted);
z-index: 2;
pointer-events: none;
}
.lab-action-label {
position: absolute;
bottom: 10px;
left: 50%;
transform: translateX(-50%);
font-size: 11px;
font-family: 'JetBrains Mono', monospace;
color: var(--text-dim);
background: rgba(12,15,22,0.85);
padding: 4px 14px;
border-radius: 100px;
border: 1px solid var(--border);
z-index: 2;
pointer-events: none;
opacity: 0;
transition: opacity 0.3s;
}
.lab-action-label.visible { opacity: 1; }
.center-header {
height: 36px;
min-height: 36px;
display: flex;
align-items: center;
padding: 0 16px;
background: var(--bg-surface);
border-bottom: 1px solid var(--border);
gap: 8px;
}
.tab {
font-size: 11px; font-weight: 500;
padding: 4px 12px; border-radius: 4px;
color: var(--text-dim); cursor: pointer;
transition: all 0.15s;
}
.tab.active { color: var(--text); background: var(--bg-hover); }
.tab:hover { color: var(--text); }
.terminal {
flex: 1;
overflow-y: auto;
padding: 16px 20px;
font-family: 'JetBrains Mono', monospace;
font-size: 12.5px;
line-height: 1.9;
scrollbar-width: thin;
scrollbar-color: var(--border) transparent;
}
.terminal::-webkit-scrollbar { width: 6px; }
.terminal::-webkit-scrollbar-track { background: transparent; }
.terminal::-webkit-scrollbar-thumb { background: var(--border); border-radius: 3px; }
.t-line {
white-space: pre-wrap;
opacity: 0;
animation: lineIn 0.25s ease forwards;
}
@keyframes lineIn {
from { opacity: 0; transform: translateY(4px); }
to { opacity: 1; transform: translateY(0); }
}
.t-prompt { color: var(--green); }
.t-cmd { color: var(--text); }
.t-dim { color: var(--text-muted); }
.t-label { color: var(--accent); }
.t-str { color: var(--amber); }
.t-kw { color: var(--pink); }
.t-fn { color: var(--cyan); }
.t-num { color: var(--purple); }
.t-ok { color: var(--green); }
.t-warn { color: var(--amber); }
.t-err { color: var(--red); }
.t-sub { color: var(--text-dim); }
/* ---- Right Panel ---- */
.right {
background: var(--bg-surface);
border-left: 1px solid var(--border);
display: flex;
flex-direction: column;
overflow-y: auto;
scrollbar-width: thin;
scrollbar-color: var(--border) transparent;
}
.panel-section {
padding: 16px;
border-bottom: 1px solid var(--border);
}
.panel-heading {
font-size: 10px; font-weight: 600;
text-transform: uppercase; letter-spacing: 1.5px;
color: var(--text-muted); margin-bottom: 12px;
display: flex; align-items: center; justify-content: space-between;
}
.reward-row {
display: flex; align-items: center; gap: 10px; margin-bottom: 8px;
}
.reward-row:last-child { margin-bottom: 0; }
.rw-label {
font-size: 11px; font-weight: 500; width: 80px;
color: var(--text-dim); text-align: right;
}
.rw-track {
flex: 1; height: 18px;
background: rgba(255,255,255,0.03);
border-radius: 4px; overflow: hidden; position: relative;
}
.rw-fill {
height: 100%; border-radius: 4px; width: 0%;
transition: width 0.6s cubic-bezier(0.4,0,0.2,1);
display: flex; align-items: center; justify-content: flex-end;
padding-right: 6px; font-size: 10px; font-weight: 600;
font-family: 'JetBrains Mono', monospace;
color: rgba(255,255,255,0.85); min-width: fit-content;
}
.rw-fill.validity { background: linear-gradient(90deg, rgba(52,211,153,0.5), rgba(52,211,153,0.85)); }
.rw-fill.ordering { background: linear-gradient(90deg, rgba(34,211,238,0.5), rgba(34,211,238,0.85)); }
.rw-fill.info_gain { background: linear-gradient(90deg, rgba(56,189,248,0.5), rgba(56,189,248,0.85)); }
.rw-fill.efficiency { background: linear-gradient(90deg, rgba(251,191,36,0.5), rgba(251,191,36,0.85)); }
.rw-fill.novelty { background: linear-gradient(90deg, rgba(167,139,250,0.5), rgba(167,139,250,0.85)); }
.rw-fill.penalty { background: linear-gradient(90deg, rgba(248,113,113,0.5), rgba(248,113,113,0.85)); }
.cumulative-row {
display: flex; align-items: baseline; justify-content: space-between;
margin-top: 12px; padding-top: 12px; border-top: 1px solid var(--border);
}
.cum-label { font-size: 11px; color: var(--text-dim); }
.cum-value {
font-size: 20px; font-weight: 700;
font-family: 'JetBrains Mono', monospace; color: var(--green);
}
.discovery-list { display: flex; flex-direction: column; gap: 6px; }
.discovery {
display: flex; align-items: flex-start; gap: 8px;
padding: 8px 10px; background: var(--bg-raised);
border-radius: 6px; border: 1px solid var(--border);
opacity: 0; transform: scale(0.95); transition: all 0.3s ease;
}
.discovery.visible { opacity: 1; transform: scale(1); }
.disc-icon {
width: 20px; height: 20px; border-radius: 4px;
display: flex; align-items: center; justify-content: center;
font-size: 10px; flex-shrink: 0; margin-top: 1px;
}
.disc-body { flex: 1; }
.disc-title { font-size: 11px; font-weight: 600; }
.disc-detail {
font-size: 10px; color: var(--text-dim); margin-top: 2px;
font-family: 'JetBrains Mono', monospace;
}
.empty-state {
font-size: 11px; color: var(--text-muted);
font-style: italic; padding: 8px 0;
}
.step-reward-mini {
display: flex; align-items: center; justify-content: space-between;
padding: 6px 10px; background: var(--bg-raised);
border-radius: 6px; margin-bottom: 4px;
font-size: 11px; font-family: 'JetBrains Mono', monospace;
opacity: 0; transition: all 0.3s;
}
.step-reward-mini.visible { opacity: 1; }
.step-reward-mini .srm-name { color: var(--text-dim); }
.step-reward-mini .srm-val { font-weight: 600; }
.step-reward-mini .srm-val.pos { color: var(--green); }
.step-reward-mini .srm-val.neg { color: var(--red); }
</style>
</head>
<body>
<!-- Top Bar -->
<div class="topbar">
<div class="topbar-logo">BioEnv</div>
<div class="topbar-sep"></div>
<div class="topbar-env">biomarker_validation_lung</div>
<div class="topbar-status">
<div class="status-dot" id="statusDot"></div>
<span id="statusText">Ready</span>
</div>
<button class="topbar-btn btn-ghost" id="resetBtn" onclick="resetDemo()">Reset</button>
<button class="topbar-btn btn-primary" id="runBtn" onclick="startDemo()">Run Episode</button>
</div>
<div class="main">
<!-- Left Sidebar -->
<div class="sidebar">
<div class="sidebar-section">
<div class="sidebar-heading">Scenario</div>
<div class="scenario-list">
<div class="scenario-opt" onclick="selectScenario(this)">
<div class="sc-dot" style="background: var(--green);"></div>
<span class="sc-name">Cardiac Disease DE</span>
<span class="sc-diff" style="color: var(--green);">Easy</span>
</div>
<div class="scenario-opt" onclick="selectScenario(this)">
<div class="sc-dot" style="background: var(--amber);"></div>
<span class="sc-name">Hematopoiesis Trajectory</span>
<span class="sc-diff" style="color: var(--amber);">Med</span>
</div>
<div class="scenario-opt" onclick="selectScenario(this)">
<div class="sc-dot" style="background: var(--amber);"></div>
<span class="sc-name">Perturbation Immune</span>
<span class="sc-diff" style="color: var(--amber);">Med</span>
</div>
<div class="scenario-opt active" onclick="selectScenario(this)">
<div class="sc-dot" style="background: var(--red);"></div>
<span class="sc-name">Biomarker Validation (Lung)</span>
<span class="sc-diff" style="color: var(--red);">Hard</span>
</div>
</div>
</div>
<div class="sidebar-section">
<div class="sidebar-heading">Environment State</div>
<div class="gauge">
<div class="gauge-header">
<span class="gauge-label">Budget</span>
<span class="gauge-value" id="budgetVal">$100,000</span>
</div>
<div class="gauge-track"><div class="gauge-fill" id="budgetFill" style="width:100%;background:var(--green);"></div></div>
</div>
<div class="gauge">
<div class="gauge-header">
<span class="gauge-label">Time</span>
<span class="gauge-value" id="timeVal">180 / 180 days</span>
</div>
<div class="gauge-track"><div class="gauge-fill" id="timeFill" style="width:100%;background:var(--cyan);"></div></div>
</div>
<div class="gauge">
<div class="gauge-header">
<span class="gauge-label">Steps</span>
<span class="gauge-value" id="stepVal">0 / 30</span>
</div>
<div class="gauge-track"><div class="gauge-fill" id="stepFill" style="width:0%;background:var(--accent);"></div></div>
</div>
</div>
<div class="sidebar-section" style="flex:1;overflow-y:auto;">
<div class="sidebar-heading">Pipeline</div>
<div class="pipeline-steps" id="pipelineSteps"></div>
</div>
</div>
<!-- Center: Lab + Terminal -->
<div class="center">
<div class="lab-panel">
<div class="lab-label">Virtual Lab</div>
<div class="lab-action-label" id="labActionLabel"></div>
<canvas id="labCanvas"></canvas>
</div>
<div class="center-header">
<div class="tab active">Agent Log</div>
<div class="tab">Raw JSON</div>
</div>
<div class="terminal" id="terminal"></div>
</div>
<!-- Right Panel -->
<div class="right">
<div class="panel-section">
<div class="panel-heading">
Step Reward
<span id="stepRewardLabel" style="font-family:'JetBrains Mono',monospace;font-size:11px;color:var(--text-dim);">--</span>
</div>
<div id="rewardBars">
<div class="reward-row"><span class="rw-label">Validity</span><div class="rw-track"><div class="rw-fill validity" id="rw-validity"></div></div></div>
<div class="reward-row"><span class="rw-label">Ordering</span><div class="rw-track"><div class="rw-fill ordering" id="rw-ordering"></div></div></div>
<div class="reward-row"><span class="rw-label">Info Gain</span><div class="rw-track"><div class="rw-fill info_gain" id="rw-info_gain"></div></div></div>
<div class="reward-row"><span class="rw-label">Efficiency</span><div class="rw-track"><div class="rw-fill efficiency" id="rw-efficiency"></div></div></div>
<div class="reward-row"><span class="rw-label">Novelty</span><div class="rw-track"><div class="rw-fill novelty" id="rw-novelty"></div></div></div>
<div class="reward-row"><span class="rw-label">Penalty</span><div class="rw-track"><div class="rw-fill penalty" id="rw-penalty"></div></div></div>
</div>
<div class="cumulative-row">
<span class="cum-label">Cumulative Reward</span>
<span class="cum-value" id="cumReward">0.00</span>
</div>
</div>
<div class="panel-section">
<div class="panel-heading">Reward History</div>
<div id="rewardHistory"><div class="empty-state">No steps yet</div></div>
</div>
<div class="panel-section">
<div class="panel-heading">Discoveries</div>
<div class="discovery-list" id="discoveries"><div class="empty-state">No discoveries yet</div></div>
</div>
<div class="panel-section">
<div class="panel-heading">Violations</div>
<div id="violations"><div class="empty-state">No violations</div></div>
</div>
</div>
</div>
<script>
// =====================================================
// VIRTUAL LAB - Canvas rendering
// =====================================================
const labCanvas = document.getElementById('labCanvas');
const ctx = labCanvas.getContext('2d');
let labW, labH, dpr;
function resizeLab() {
const rect = labCanvas.parentElement.getBoundingClientRect();
dpr = window.devicePixelRatio || 1;
labW = rect.width;
labH = rect.height;
labCanvas.width = labW * dpr;
labCanvas.height = labH * dpr;
ctx.setTransform(dpr, 0, 0, dpr, 0, 0);
}
resizeLab();
window.addEventListener('resize', () => { resizeLab(); });
// Lab stations (positions as fractions of canvas, converted in draw)
const STATIONS = {
idle: { fx: 0.06, fy: 0.55, label: 'ENTRANCE', icon: 'door', color: '#475569' },
sample: { fx: 0.20, fy: 0.35, label: 'SAMPLE BENCH', icon: 'bench', color: '#34d399' },
cohort: { fx: 0.20, fy: 0.75, label: 'COHORT SELECT', icon: 'people', color: '#34d399' },
prep: { fx: 0.38, fy: 0.35, label: 'LIBRARY PREP', icon: 'flask', color: '#2dd4bf' },
sequencer: { fx: 0.38, fy: 0.75, label: 'SEQUENCER', icon: 'machine', color: '#22d3ee' },
computer: { fx: 0.62, fy: 0.50, label: 'COMPUTE', icon: 'screen', color: '#38bdf8' },
whiteboard: { fx: 0.84, fy: 0.45, label: 'SYNTHESIS', icon: 'board', color: '#a78bfa' },
};
// Map actions to stations
const ACTION_STATION = {
collect_sample: 'sample',
select_cohort: 'cohort',
prepare_library: 'prep',
sequence_cells: 'sequencer',
run_qc: 'computer',
normalize_data: 'computer',
cluster_cells: 'computer',
differential_expression: 'computer',
pathway_enrichment: 'computer',
marker_selection: 'computer',
validate_marker: 'computer',
synthesize_conclusion: 'whiteboard',
};
// Agent state
let agent = { x: 0, y: 0, targetX: 0, targetY: 0, station: 'idle', working: false };
let agentTrail = [];
let workingTick = 0;
let terminalLines = []; // fake terminal on computer screen
let activeStationKey = null;
let particlesLab = [];
function stationPos(key) {
const s = STATIONS[key];
return { x: s.fx * labW, y: s.fy * labH };
}
function initAgent() {
const p = stationPos('idle');
agent.x = p.x; agent.y = p.y;
agent.targetX = p.x; agent.targetY = p.y;
agent.station = 'idle';
agent.working = false;
agent.facing = 1;
agentTrail = [];
terminalLines = [];
activeStationKey = null;
particlesLab = [];
}
initAgent();
function moveAgentTo(stationKey) {
const p = stationPos(stationKey);
agent.targetX = p.x;
agent.targetY = p.y;
agent.station = stationKey;
agent.working = false;
activeStationKey = stationKey;
}
function setAgentWorking(actionName) {
agent.working = true;
workingTick = 0;
// If at computer, set up terminal lines
if (agent.station === 'computer') {
terminalLines = [];
typeComputerLines(actionName);
}
}
const COMP_COMMANDS = {
run_qc: ['$ scanpy.pp.filter_cells()', ' filtering 11847 cells...', ' 10234 passed QC', ' doublet rate: 3.2%'],
normalize_data: ['$ scran.normalize(adata)', ' computing size factors...', ' log1p transform', ' HVGs: 3000 selected'],
cluster_cells: ['$ sc.tl.leiden(adata, 0.8)', ' building kNN graph...', ' optimizing modularity', ' 14 clusters found'],
differential_expression: ['$ DESeq2.run(IPF, Ctrl)', ' fitting GLM...', ' 1847 DE genes', ' SPP1 log2FC=3.42 ***'],
pathway_enrichment: ['$ gseapy.enrich(de_genes)', ' KEGG + Reactome...', ' ECM-receptor p=4.2e-12', ' TGF-beta p=1.8e-09'],
marker_selection: ['$ rank_markers(candidates)', ' SPP1 AUROC: 0.94', ' MMP7 AUROC: 0.87', ' COL1A1 AUROC: 0.81'],
validate_marker: ['$ cross_validate("SPP1")', ' fold 1: 0.93', ' fold 2: 0.89', ' mean AUROC: 0.91 OK'],
};
async function typeComputerLines(actionName) {
const lines = COMP_COMMANDS[actionName] || ['$ processing...', ' computing...', ' done'];
for (let i = 0; i < lines.length; i++) {
await wait(250);
terminalLines.push(lines[i]);
if (terminalLines.length > 5) terminalLines.shift();
}
}
// Particles burst
function spawnParticles(x, y, color, count = 8) {
for (let i = 0; i < count; i++) {
const angle = (Math.PI * 2 / count) * i + Math.random() * 0.5;
particlesLab.push({
x, y,
vx: Math.cos(angle) * (1.5 + Math.random() * 2),
vy: Math.sin(angle) * (1.5 + Math.random() * 2),
life: 1,
color,
size: 2 + Math.random() * 2,
});
}
}
// ---- Draw loop ----
let frameCount = 0;
const FLOOR_COLOR = '#0f1520';
const WALL_COLOR = '#1a2332';
const FLOOR_TILE_A = '#0d1219';
const FLOOR_TILE_B = '#10161f';
function drawLab() {
frameCount++;
ctx.clearRect(0, 0, labW, labH);
// Floor - checkerboard tiles
const tileSize = 24;
for (let ty = 0; ty < labH; ty += tileSize) {
for (let tx = 0; tx < labW; tx += tileSize) {
const checker = ((Math.floor(tx / tileSize) + Math.floor(ty / tileSize)) % 2 === 0);
ctx.fillStyle = checker ? FLOOR_TILE_A : FLOOR_TILE_B;
ctx.fillRect(tx, ty, tileSize, tileSize);
}
}
// Walls - top and bottom border
ctx.fillStyle = WALL_COLOR;
ctx.fillRect(0, 0, labW, 18);
ctx.fillRect(0, labH - 8, labW, 8);
ctx.strokeStyle = '#253040';
ctx.lineWidth = 1;
ctx.beginPath(); ctx.moveTo(0, 18); ctx.lineTo(labW, 18); ctx.stroke();
// Draw equipment at each station (behind the person)
for (const [key, s] of Object.entries(STATIONS)) {
const pos = stationPos(key);
const isActive = key === activeStationKey;
drawEquipment(key, pos.x, pos.y, s.color, isActive);
}
// Draw walking path (subtle floor markings)
ctx.strokeStyle = 'rgba(56,189,248,0.06)';
ctx.lineWidth = 16;
ctx.lineCap = 'round';
ctx.lineJoin = 'round';
const pathOrder = ['idle','sample','prep','computer','whiteboard'];
ctx.beginPath();
const p0 = stationPos(pathOrder[0]);
ctx.moveTo(p0.x, p0.y + 10);
for (let i = 1; i < pathOrder.length; i++) {
const p = stationPos(pathOrder[i]);
ctx.lineTo(p.x, p.y + 10);
}
ctx.stroke();
// Lower path
ctx.beginPath();
const pl0 = stationPos('idle');
ctx.moveTo(pl0.x, pl0.y + 10);
const pl1 = stationPos('cohort');
ctx.lineTo(pl1.x, pl1.y + 10);
const pl2 = stationPos('sequencer');
ctx.lineTo(pl2.x, pl2.y + 10);
const pl3 = stationPos('computer');
ctx.lineTo(pl3.x, pl3.y + 10);
ctx.stroke();
ctx.lineCap = 'butt';
// Floating terminal popup at computer
if (agent.station === 'computer' && agent.working && terminalLines.length > 0) {
const cp = stationPos('computer');
const sx = cp.x + 55, sy = cp.y - 65;
const sw = 170, sh = 95;
// Shadow
ctx.fillStyle = 'rgba(0,0,0,0.4)';
roundRect(ctx, sx + 3, sy + 3, sw, sh, 6);
ctx.fill();
ctx.fillStyle = 'rgba(7,9,13,0.97)';
ctx.strokeStyle = 'rgba(56,189,248,0.3)';
ctx.lineWidth = 1;
roundRect(ctx, sx, sy, sw, sh, 6);
ctx.fill(); ctx.stroke();
// Title bar
ctx.fillStyle = 'rgba(30,41,59,0.5)';
ctx.fillRect(sx + 1, sy + 1, sw - 2, 14);
ctx.fillStyle = '#475569';
ctx.font = '500 7px Inter, sans-serif';
ctx.textAlign = 'left';
ctx.fillText('terminal', sx + 6, sy + 10);
// dots
ctx.fillStyle = '#f87171'; ctx.beginPath(); ctx.arc(sx + sw - 28, sy + 7, 3, 0, Math.PI*2); ctx.fill();
ctx.fillStyle = '#fbbf24'; ctx.beginPath(); ctx.arc(sx + sw - 18, sy + 7, 3, 0, Math.PI*2); ctx.fill();
ctx.fillStyle = '#34d399'; ctx.beginPath(); ctx.arc(sx + sw - 8, sy + 7, 3, 0, Math.PI*2); ctx.fill();
ctx.font = '500 9px JetBrains Mono, monospace';
const startY = sy + 28;
for (let i = 0; i < terminalLines.length; i++) {
const line = terminalLines[i];
ctx.fillStyle = line.startsWith('$') ? '#34d399' : line.includes('***') || line.includes('OK') ? '#34d399' : '#94a3b8';
ctx.fillText(terminalLines[i].substring(0, 24), sx + 8, startY + i * 14);
}
if (frameCount % 60 < 30) {
ctx.fillStyle = '#34d399';
ctx.fillRect(sx + 8, startY + terminalLines.length * 14 - 8, 6, 11);
}
}
// Whiteboard popup
if (agent.station === 'whiteboard' && agent.working) {
const wp = stationPos('whiteboard');
const bx = wp.x - 60, by = wp.y - 75;
const bw = 120, bh = 72;
ctx.fillStyle = 'rgba(0,0,0,0.3)';
roundRect(ctx, bx + 3, by + 3, bw, bh, 6);
ctx.fill();
ctx.fillStyle = 'rgba(17,24,39,0.95)';
ctx.strokeStyle = 'rgba(167,139,250,0.3)';
ctx.lineWidth = 1;
roundRect(ctx, bx, by, bw, bh, 6);
ctx.fill(); ctx.stroke();
ctx.font = '600 8px JetBrains Mono, monospace';
ctx.textAlign = 'left';
ctx.fillStyle = '#a78bfa';
ctx.fillText('CONCLUSION', bx + 8, by + 14);
ctx.font = '400 7.5px JetBrains Mono, monospace';
const synthLines = ['SPP1 validated', 'AUROC = 0.91', 'Confidence: 0.85', 'Match: 4/5'];
for (let i = 0; i < synthLines.length; i++) {
ctx.fillStyle = i === 0 ? '#34d399' : '#94a3b8';
ctx.fillText(synthLines[i], bx + 8, by + 28 + i * 12);
}
}
// Activity text above active station
if (agent.working && activeStationKey && activeStationKey !== 'idle') {
const sp = stationPos(activeStationKey);
const actTexts = {
sample: 'collecting tissue...', cohort: 'selecting cohort...',
prep: 'preparing library...', sequencer: 'sequencing...',
computer: 'computing...', whiteboard: 'synthesizing...',
};
ctx.fillStyle = STATIONS[activeStationKey].color;
ctx.font = '500 9px JetBrains Mono, monospace';
ctx.textAlign = 'center';
ctx.globalAlpha = 0.5 + 0.3 * Math.sin(frameCount * 0.06);
const yOff = ['sample','prep'].includes(activeStationKey) ? -55 : -50;
ctx.fillText(actTexts[activeStationKey] || 'working...', sp.x, sp.y + yOff);
ctx.globalAlpha = 1;
}
// Move agent smoothly
const dx = agent.targetX - agent.x;
const dy = agent.targetY - agent.y;
const dist = Math.sqrt(dx * dx + dy * dy);
const isWalking = dist > 2;
if (isWalking) {
const speed = 0.05;
agent.x += dx * speed;
agent.y += dy * speed;
agent.facing = dx > 0 ? 1 : dx < -0.5 ? -1 : agent.facing;
}
// Draw person
drawPerson(agent.x, agent.y, isWalking, agent.working, agent.facing || 1);
// Particles
for (let i = particlesLab.length - 1; i >= 0; i--) {
const p = particlesLab[i];
p.x += p.vx; p.y += p.vy;
p.vx *= 0.95; p.vy *= 0.95;
p.life -= 0.02;
if (p.life <= 0) { particlesLab.splice(i, 1); continue; }
ctx.globalAlpha = p.life * 0.6;
ctx.fillStyle = p.color;
ctx.beginPath();
ctx.arc(p.x, p.y, p.size * p.life, 0, Math.PI * 2);
ctx.fill();
}
ctx.globalAlpha = 1;
// Station labels
for (const [key, s] of Object.entries(STATIONS)) {
if (key === 'idle') continue;
const pos = stationPos(key);
const isActive = key === activeStationKey;
ctx.fillStyle = isActive ? s.color : '#334155';
ctx.font = `600 ${isActive ? 9 : 8}px Inter, sans-serif`;
ctx.textAlign = 'center';
const ly = key === 'cohort' || key === 'sequencer' ? pos.y + 45 : pos.y + 42;
ctx.fillText(s.label, pos.x, ly);
}
requestAnimationFrame(drawLab);
}
// ---- Draw person (lab coat researcher) ----
function drawPerson(x, y, walking, working, facing) {
const f = facing;
const t = frameCount;
// Walking cycle
const walkCycle = walking ? Math.sin(t * 0.15) : 0;
const bobY = walking ? Math.abs(Math.sin(t * 0.15)) * 2 : 0;
// Working arm animation
const workArm = working ? Math.sin(t * 0.08) * 0.3 : 0;
const py = y - bobY; // feet position base
ctx.save();
ctx.translate(x, py);
// Shadow
ctx.fillStyle = 'rgba(0,0,0,0.25)';
ctx.beginPath();
ctx.ellipse(0, 12, 10, 4, 0, 0, Math.PI * 2);
ctx.fill();
// Legs
const legSpread = walking ? walkCycle * 5 : 0;
ctx.strokeStyle = '#1e3a5f';
ctx.lineWidth = 3;
ctx.lineCap = 'round';
// Left leg
ctx.beginPath();
ctx.moveTo(-3, 4);
ctx.lineTo(-3 + legSpread, 12);
ctx.stroke();
// Right leg
ctx.beginPath();
ctx.moveTo(3, 4);
ctx.lineTo(3 - legSpread, 12);
ctx.stroke();
// Shoes
ctx.fillStyle = '#1e293b';
ctx.beginPath(); ctx.arc(-3 + legSpread, 12, 2.5, 0, Math.PI * 2); ctx.fill();
ctx.beginPath(); ctx.arc(3 - legSpread, 12, 2.5, 0, Math.PI * 2); ctx.fill();
// Body / lab coat
ctx.fillStyle = '#e2e8f0'; // white lab coat
ctx.beginPath();
ctx.moveTo(-7, -4);
ctx.lineTo(-6, 6);
ctx.lineTo(6, 6);
ctx.lineTo(7, -4);
ctx.quadraticCurveTo(7, -10, 0, -10);
ctx.quadraticCurveTo(-7, -10, -7, -4);
ctx.fill();
// Coat outline
ctx.strokeStyle = '#94a3b8';
ctx.lineWidth = 0.5;
ctx.stroke();
// Coat split at bottom
ctx.beginPath();
ctx.moveTo(0, 1);
ctx.lineTo(0, 6);
ctx.strokeStyle = '#cbd5e1';
ctx.lineWidth = 0.5;
ctx.stroke();
// Pocket
ctx.strokeStyle = '#94a3b8';
ctx.lineWidth = 0.5;
ctx.strokeRect(f > 0 ? 1 : -5, -1, 4, 3);
// Arms
ctx.strokeStyle = '#e2e8f0';
ctx.lineWidth = 3.5;
ctx.lineCap = 'round';
// Back arm
const backArmSwing = walking ? -walkCycle * 4 : 0;
ctx.beginPath();
ctx.moveTo(-f * 6, -6);
ctx.lineTo(-f * 6 + backArmSwing, 2);
ctx.stroke();
// Front arm (active arm)
if (working) {
// Arm reaching forward/up for work
ctx.beginPath();
ctx.moveTo(f * 6, -6);
ctx.lineTo(f * 10 + workArm * 5, -8 + workArm * 3);
ctx.stroke();
// Hand/tool
ctx.fillStyle = '#fde68a';
ctx.beginPath();
ctx.arc(f * 10 + workArm * 5, -8 + workArm * 3, 2, 0, Math.PI * 2);
ctx.fill();
} else {
const frontArmSwing = walking ? walkCycle * 4 : 0;
ctx.beginPath();
ctx.moveTo(f * 6, -6);
ctx.lineTo(f * 6 + frontArmSwing, 2);
ctx.stroke();
}
// Skin for hands
ctx.fillStyle = '#fde68a';
ctx.beginPath(); ctx.arc(-f * 6 + backArmSwing, 2, 1.8, 0, Math.PI * 2); ctx.fill();
if (!working) {
const fs = walking ? walkCycle * 4 : 0;
ctx.beginPath(); ctx.arc(f * 6 + fs, 2, 1.8, 0, Math.PI * 2); ctx.fill();
}
// Head
ctx.fillStyle = '#fde68a'; // skin
ctx.beginPath();
ctx.arc(0, -15, 7, 0, Math.PI * 2);
ctx.fill();
// Hair
ctx.fillStyle = '#1e293b';
ctx.beginPath();
ctx.arc(0, -17, 7, Math.PI, 0);
ctx.fill();
// Face details
ctx.fillStyle = '#1e293b';
// Eyes
ctx.beginPath();
ctx.arc(f * 2.5, -15.5, 1, 0, Math.PI * 2);
ctx.fill();
ctx.beginPath();
ctx.arc(f * -1.5, -15.5, 1, 0, Math.PI * 2);
ctx.fill();
// Glasses
ctx.strokeStyle = '#475569';
ctx.lineWidth = 0.7;
ctx.beginPath();
ctx.arc(f * 2.5, -15.5, 2.5, 0, Math.PI * 2);
ctx.stroke();
ctx.beginPath();
ctx.arc(f * -1.5, -15.5, 2.5, 0, Math.PI * 2);
ctx.stroke();
ctx.beginPath();
ctx.moveTo(f * 0.5, -15.5);
ctx.lineTo(f * -0.5, -15.5);
ctx.stroke();
// Mouth
if (working) {
ctx.fillStyle = '#1e293b';
ctx.beginPath();
ctx.arc(f * 0.5, -12.5, 1, 0, Math.PI);
ctx.fill();
}
// ID Badge
ctx.fillStyle = '#38bdf8';
ctx.fillRect(f > 0 ? -6 : 2, -3, 4, 5);
ctx.fillStyle = '#fff';
ctx.font = 'bold 3px Inter, sans-serif';
ctx.textAlign = 'center';
ctx.fillText('AI', f > 0 ? -4 : 4, 0.5);
ctx.restore();
}
// ---- Draw lab equipment ----
function drawEquipment(stationKey, cx, cy, color, active) {
ctx.save();
switch (stationKey) {
case 'idle':
// Door frame
ctx.strokeStyle = '#334155';
ctx.lineWidth = 2;
ctx.strokeRect(cx - 12, cy - 30, 24, 40);
ctx.fillStyle = '#1a2332';
ctx.fillRect(cx - 10, cy - 28, 20, 36);
ctx.fillStyle = '#475569';
ctx.beginPath(); ctx.arc(cx + 6, cy - 10, 2, 0, Math.PI * 2); ctx.fill();
break;
case 'sample':
// Lab bench with sample tubes
// Bench surface
ctx.fillStyle = '#1a2332';
ctx.fillRect(cx - 30, cy - 8, 60, 6);
// Bench legs
ctx.fillStyle = '#253040';
ctx.fillRect(cx - 28, cy - 2, 4, 20);
ctx.fillRect(cx + 24, cy - 2, 4, 20);
// Tube rack
ctx.fillStyle = '#253040';
ctx.fillRect(cx - 18, cy - 18, 36, 10);
// Test tubes
const tubeColors = ['#34d399', '#22d3ee', '#fbbf24', '#f472b6', '#34d399', '#22d3ee'];
for (let i = 0; i < 6; i++) {
const tx = cx - 14 + i * 6;
ctx.fillStyle = active ? tubeColors[i] : '#334155';
ctx.globalAlpha = active ? 0.7 : 0.4;
ctx.fillRect(tx, cy - 28, 4, 12);
// Tube caps
ctx.globalAlpha = 1;
ctx.fillStyle = active ? tubeColors[i] : '#475569';
ctx.fillRect(tx - 0.5, cy - 29, 5, 2);
}
ctx.globalAlpha = 1;
// Pipette if active
if (active) {
const pipY = cy - 32 + Math.sin(frameCount * 0.08) * 4;
ctx.strokeStyle = '#94a3b8';
ctx.lineWidth = 2;
ctx.beginPath();
ctx.moveTo(cx + 5, pipY);
ctx.lineTo(cx + 5, pipY - 14);
ctx.stroke();
ctx.fillStyle = '#64748b';
ctx.fillRect(cx + 3, pipY - 18, 5, 6);
// Droplet
if (frameCount % 60 < 20) {
ctx.fillStyle = '#34d399';
ctx.globalAlpha = 0.6;
ctx.beginPath();
ctx.arc(cx + 5, pipY + 3, 1.5, 0, Math.PI * 2);
ctx.fill();
ctx.globalAlpha = 1;
}
}
break;
case 'cohort':
// Filing cabinet / patient records
ctx.fillStyle = '#1a2332';
ctx.fillRect(cx - 20, cy - 22, 40, 40);
ctx.strokeStyle = '#253040';
ctx.lineWidth = 1;
for (let i = 0; i < 3; i++) {
const dy = cy - 18 + i * 13;
ctx.strokeRect(cx - 18, dy, 36, 11);
ctx.fillStyle = active ? '#475569' : '#253040';
ctx.fillRect(cx - 4, dy + 4, 8, 3);
}
// Clipboard
ctx.fillStyle = '#253040';
ctx.fillRect(cx + 24, cy - 16, 14, 20);
ctx.strokeStyle = '#475569';
ctx.lineWidth = 0.5;
for (let i = 0; i < 4; i++) {
ctx.beginPath();
ctx.moveTo(cx + 27, cy - 12 + i * 4);
ctx.lineTo(cx + 35, cy - 12 + i * 4);
ctx.stroke();
}
if (active) {
ctx.fillStyle = color;
ctx.globalAlpha = 0.5;
ctx.beginPath(); ctx.arc(cx + 31, cy - 14, 2, 0, Math.PI * 2); ctx.fill();
ctx.globalAlpha = 1;
}
break;
case 'prep':
// Library prep station - PCR machine + bench
// Bench
ctx.fillStyle = '#1a2332';
ctx.fillRect(cx - 28, cy - 6, 56, 6);
ctx.fillStyle = '#253040';
ctx.fillRect(cx - 26, cy, 4, 18);
ctx.fillRect(cx + 22, cy, 4, 18);
// PCR/thermocycler machine
ctx.fillStyle = active ? '#192535' : '#172030';
ctx.strokeStyle = active ? color : '#253040';
ctx.lineWidth = 1;
roundRect(ctx, cx - 18, cy - 26, 36, 20, 3);
ctx.fill(); ctx.stroke();
// Display on machine
ctx.fillStyle = active ? 'rgba(45,212,191,0.15)' : 'rgba(30,41,59,0.3)';
ctx.fillRect(cx - 14, cy - 22, 16, 8);
if (active) {
ctx.fillStyle = color;
ctx.font = '500 6px JetBrains Mono, monospace';
ctx.textAlign = 'left';
ctx.fillText('72.0°C', cx - 12, cy - 16);
// LED
ctx.fillStyle = color;
ctx.beginPath(); ctx.arc(cx + 12, cy - 18, 2, 0, Math.PI * 2); ctx.fill();
}
// Microplate
ctx.fillStyle = '#1e293b';
ctx.fillRect(cx - 20, cy - 3, 18, 12);
ctx.strokeStyle = '#334155';
ctx.lineWidth = 0.3;
for (let r = 0; r < 3; r++) {
for (let c = 0; c < 4; c++) {
ctx.beginPath();
ctx.arc(cx - 17 + c * 4.5, cy + 1 + r * 3.5, 1.2, 0, Math.PI * 2);
ctx.stroke();
}
}
break;
case 'sequencer':
// Big sequencing machine (NovaSeq-like)
// Machine body
ctx.fillStyle = '#172030';
ctx.strokeStyle = active ? color : '#253040';
ctx.lineWidth = active ? 1.5 : 1;
roundRect(ctx, cx - 24, cy - 28, 48, 44, 4);
ctx.fill(); ctx.stroke();
// Front panel / screen
ctx.fillStyle = active ? 'rgba(34,211,238,0.1)' : 'rgba(30,41,59,0.3)';
roundRect(ctx, cx - 18, cy - 22, 36, 18, 2);
ctx.fill();
if (active) {
// Progress bar on screen
ctx.fillStyle = 'rgba(34,211,238,0.2)';
ctx.fillRect(cx - 14, cy - 12, 28, 4);
const progress = (frameCount % 120) / 120;
ctx.fillStyle = color;
ctx.fillRect(cx - 14, cy - 12, 28 * progress, 4);
ctx.fillStyle = color;
ctx.font = '500 6px JetBrains Mono, monospace';
ctx.textAlign = 'center';
ctx.fillText('SEQUENCING', cx, cy - 16);
}
// Slot
ctx.fillStyle = '#0f1520';
ctx.fillRect(cx - 10, cy, 20, 4);
// Status LEDs
ctx.fillStyle = active ? '#34d399' : '#334155';
ctx.beginPath(); ctx.arc(cx - 14, cy + 10, 2, 0, Math.PI * 2); ctx.fill();
if (active && frameCount % 30 < 15) {
ctx.fillStyle = '#fbbf24';
} else {
ctx.fillStyle = '#334155';
}
ctx.beginPath(); ctx.arc(cx - 8, cy + 10, 2, 0, Math.PI * 2); ctx.fill();
break;
case 'computer':
// Computer desk with dual monitors
// Desk
ctx.fillStyle = '#1a2332';
ctx.fillRect(cx - 36, cy + 2, 72, 5);
ctx.fillStyle = '#253040';
ctx.fillRect(cx - 32, cy + 7, 4, 16);
ctx.fillRect(cx + 28, cy + 7, 4, 16);
// Chair
ctx.fillStyle = '#1e293b';
ctx.beginPath();
ctx.arc(cx, cy + 28, 8, 0, Math.PI * 2);
ctx.fill();
ctx.fillStyle = '#253040';
ctx.fillRect(cx - 1, cy + 20, 2, 8);
// Monitor 1 (main)
ctx.fillStyle = active ? '#0c1219' : '#131c28';
ctx.strokeStyle = active ? 'rgba(56,189,248,0.4)' : '#253040';
ctx.lineWidth = 1;
roundRect(ctx, cx - 30, cy - 28, 32, 24, 2);
ctx.fill(); ctx.stroke();
// Monitor stand
ctx.fillStyle = '#334155';
ctx.fillRect(cx - 16, cy - 4, 4, 6);
ctx.fillRect(cx - 20, cy + 1, 12, 2);
// Monitor 2
ctx.fillStyle = active ? '#0c1219' : '#131c28';
ctx.strokeStyle = active ? 'rgba(56,189,248,0.3)' : '#253040';
roundRect(ctx, cx + 2, cy - 24, 26, 20, 2);
ctx.fill(); ctx.stroke();
ctx.fillStyle = '#334155';
ctx.fillRect(cx + 13, cy - 4, 4, 6);
ctx.fillRect(cx + 9, cy + 1, 12, 2);
// Screen content
if (active) {
ctx.fillStyle = 'rgba(56,189,248,0.08)';
ctx.fillRect(cx - 28, cy - 26, 28, 20);
// Code lines
for (let i = 0; i < 5; i++) {
ctx.fillStyle = `rgba(56,189,248,${0.15 + i * 0.06})`;
const w = 8 + Math.sin(i * 2.3 + frameCount * 0.02) * 6;
ctx.fillRect(cx - 26, cy - 24 + i * 4, w, 2);
}
// Second screen - graph
ctx.fillStyle = 'rgba(56,189,248,0.06)';
ctx.fillRect(cx + 4, cy - 22, 22, 16);
ctx.strokeStyle = 'rgba(34,211,238,0.3)';
ctx.lineWidth = 1;
ctx.beginPath();
ctx.moveTo(cx + 6, cy - 8);
for (let i = 0; i < 8; i++) {
ctx.lineTo(cx + 6 + i * 2.5, cy - 10 - Math.sin(i * 0.8 + frameCount * 0.03) * 5);
}
ctx.stroke();
}
// Keyboard
ctx.fillStyle = '#1e293b';
ctx.fillRect(cx - 14, cy + 4, 28, 6);
// Typing effect
if (active && agent.working) {
const keyX = cx - 12 + (frameCount % 20) * 1.2;
ctx.fillStyle = 'rgba(56,189,248,0.4)';
ctx.fillRect(keyX, cy + 5, 3, 4);
}
break;
case 'whiteboard':
// Whiteboard on wall + standing desk
// Board on wall
ctx.fillStyle = '#1e293b';
ctx.strokeStyle = '#334155';
ctx.lineWidth = 1;
ctx.fillRect(cx - 28, cy - 34, 56, 32);
ctx.strokeRect(cx - 28, cy - 34, 56, 32);
// Board content
if (active) {
ctx.fillStyle = 'rgba(167,139,250,0.1)';
ctx.fillRect(cx - 26, cy - 32, 52, 28);
// Diagram elements
ctx.strokeStyle = 'rgba(167,139,250,0.4)';
ctx.lineWidth = 0.8;
// Boxes
ctx.strokeRect(cx - 20, cy - 28, 14, 8);
ctx.strokeRect(cx + 6, cy - 28, 14, 8);
ctx.strokeRect(cx - 8, cy - 16, 16, 8);
// Arrows
ctx.beginPath();
ctx.moveTo(cx - 6, cy - 24); ctx.lineTo(cx + 6, cy - 24); ctx.stroke();
ctx.beginPath();
ctx.moveTo(cx, cy - 20); ctx.lineTo(cx, cy - 16); ctx.stroke();
// Checkmark
ctx.strokeStyle = '#34d399';
ctx.lineWidth = 1.5;
ctx.beginPath();
ctx.moveTo(cx - 4, cy - 12);
ctx.lineTo(cx - 1, cy - 9);
ctx.lineTo(cx + 5, cy - 15);
ctx.stroke();
} else {
// Faint lines
ctx.strokeStyle = '#253040';
ctx.lineWidth = 0.5;
for (let i = 0; i < 4; i++) {
ctx.beginPath();
ctx.moveTo(cx - 22, cy - 28 + i * 7);
ctx.lineTo(cx + 22, cy - 28 + i * 7);
ctx.stroke();
}
}
// Standing desk
ctx.fillStyle = '#1a2332';
ctx.fillRect(cx - 16, cy + 2, 32, 4);
ctx.fillStyle = '#253040';
ctx.fillRect(cx - 2, cy + 6, 4, 14);
break;
}
ctx.restore();
}
function roundRect(ctx, x, y, w, h, r) {
ctx.beginPath();
ctx.moveTo(x + r, y);
ctx.lineTo(x + w - r, y);
ctx.quadraticCurveTo(x + w, y, x + w, y + r);
ctx.lineTo(x + w, y + h - r);
ctx.quadraticCurveTo(x + w, y + h, x + w - r, y + h);
ctx.lineTo(x + r, y + h);
ctx.quadraticCurveTo(x, y + h, x, y + h - r);
ctx.lineTo(x, y + r);
ctx.quadraticCurveTo(x, y, x + r, y);
ctx.closePath();
}
drawLab();
// =====================================================
// EPISODE DATA + APP LOGIC
// =====================================================
const EPISODE = [
{
action: 'collect_sample', params: 'n_samples=8, tissue="lung"', category: 'wet',
budget: 92400, budgetPct: 92.4, time: 165, timePct: 91.7,
output: ['Collected 8 lung tissue samples (4 IPF, 4 control)','Tissue quality: excellent | Storage: -80C'],
reward: { validity: 0.90, ordering: 1.00, info_gain: 0.10, efficiency: 0.72, novelty: 1.00, penalty: 0.0 },
total: 0.45,
},
{
action: 'select_cohort', params: 'criteria="age_matched, sex_balanced"', category: 'wet',
budget: 91800, budgetPct: 91.8, time: 162, timePct: 90.0,
output: ['Cohort selected: 4 IPF patients (2M/2F, age 58-67)','Controls matched: 4 healthy donors (2M/2F, age 55-65)'],
reward: { validity: 0.85, ordering: 0.90, info_gain: 0.15, efficiency: 0.80, novelty: 0.90, penalty: 0.0 },
total: 0.38,
},
{
action: 'prepare_library', params: 'protocol="10x_chromium_v3"', category: 'wet',
budget: 84200, budgetPct: 84.2, time: 155, timePct: 86.1,
output: ['Library prep complete using 10x Chromium v3','Estimated cell capture: ~12,000 cells','cDNA yield: 42ng (good)'],
reward: { validity: 0.95, ordering: 1.00, info_gain: 0.20, efficiency: 0.70, novelty: 0.95, penalty: 0.0 },
total: 0.52,
},
{
action: 'sequence_cells', params: 'depth="standard", platform="NovaSeq"', category: 'wet',
budget: 68500, budgetPct: 68.5, time: 142, timePct: 78.9,
output: ['11,847 cells sequenced | 22,438 genes detected','Median reads/cell: 45,200 | Median genes/cell: 3,842','Sequencing saturation: 78.3%'],
reward: { validity: 0.95, ordering: 1.00, info_gain: 0.55, efficiency: 0.60, novelty: 0.90, penalty: 0.0 },
total: 0.68,
},
{
action: 'run_qc', params: 'tool="scanpy", min_genes=200', category: 'comp',
budget: 68100, budgetPct: 68.1, time: 141, timePct: 78.3,
output: ['QC complete: 10,234 / 11,847 cells passed (86.4%)','Removed: 382 doublets (3.2%), 1,231 low-quality cells','Mitochondrial threshold: 20% (flagged 847 cells)'],
reward: { validity: 0.95, ordering: 1.00, info_gain: 0.35, efficiency: 0.85, novelty: 0.80, penalty: 0.0 },
total: 0.55,
},
{
action: 'normalize_data', params: 'method="scran", log_transform=true', category: 'comp',
budget: 67900, budgetPct: 67.9, time: 140, timePct: 77.8,
output: ['Size-factor normalization (scran) applied','Log1p transform complete | HVG selection: 3,000 genes'],
reward: { validity: 0.90, ordering: 1.00, info_gain: 0.25, efficiency: 0.90, novelty: 0.70, penalty: 0.0 },
total: 0.42,
},
{
action: 'cluster_cells', params: 'algorithm="leiden", resolution=0.8', category: 'comp',
budget: 67500, budgetPct: 67.5, time: 139, timePct: 77.2,
output: ['Leiden clustering: 14 clusters identified','AT1 (8.2%), AT2 (12.1%), Fibroblast (15.7%), Macrophage (18.3%)','Endothelial (9.4%), Basal (6.1%), Ciliated (5.8%), NK/T (7.2%)','Smooth Muscle (4.1%), Mast (2.9%), B cell (3.4%), pDC (2.0%)','Mesothelial (2.6%), Aberrant Basaloid (2.2%)'],
reward: { validity: 0.95, ordering: 1.00, info_gain: 0.65, efficiency: 0.85, novelty: 0.85, penalty: 0.0 },
total: 0.72,
discovery: { title: '14 cell populations identified', detail: 'Including Aberrant Basaloid cells (IPF-associated)', color: 'var(--cyan)', bg: 'var(--cyan-dim)' },
},
{
action: 'differential_expression', params: 'method="DESeq2", contrast="IPF_vs_Ctrl"', category: 'comp',
budget: 67000, budgetPct: 67.0, time: 137, timePct: 76.1,
output: ['1,847 DE genes (|log2FC| > 1, padj < 0.05)','Top upregulated in IPF:',' SPP1 log2FC=3.42 padj=1.2e-18',' MMP7 log2FC=2.89 padj=3.4e-15',' COL1A1 log2FC=2.67 padj=8.7e-14',' TGFB1 log2FC=1.95 padj=2.1e-09','Top downregulated: AGER (-3.1), SFTPC (-2.8), HOPX (-2.3)'],
reward: { validity: 0.95, ordering: 1.00, info_gain: 0.78, efficiency: 0.80, novelty: 0.88, penalty: 0.0 },
total: 0.82,
discovery: { title: 'SPP1 strongly upregulated in IPF', detail: 'log2FC=3.42, padj=1.2e-18', color: 'var(--pink)', bg: 'rgba(244,114,182,0.10)' },
},
{
action: 'pathway_enrichment', params: 'tool="gseapy", gene_sets="KEGG,Reactome"', category: 'comp',
budget: 66600, budgetPct: 66.6, time: 136, timePct: 75.6,
output: ['Top enriched pathways (IPF vs Control):',' ECM-receptor interaction padj=4.2e-12',' TGF-beta signaling padj=1.8e-09',' PI3K-Akt signaling padj=3.1e-07',' Focal adhesion padj=8.9e-07','SPP1 participates in 3/4 top pathways'],
reward: { validity: 0.90, ordering: 1.00, info_gain: 0.60, efficiency: 0.85, novelty: 0.75, penalty: 0.0 },
total: 0.58,
discovery: { title: 'SPP1 in ECM/TGF-beta/PI3K pathways', detail: 'Core fibrosis signaling axis confirmed', color: 'var(--purple)', bg: 'rgba(167,139,250,0.10)' },
},
{
action: 'marker_selection', params: 'candidates=["SPP1","MMP7","COL1A1"]', category: 'comp',
budget: 66200, budgetPct: 66.2, time: 135, timePct: 75.0,
output: ['Marker ranking by discriminative power:',' 1. SPP1 - AUROC: 0.94, specificity: 0.89',' 2. MMP7 - AUROC: 0.87, specificity: 0.82',' 3. COL1A1 - AUROC: 0.81, specificity: 0.76','SPP1 selected as primary biomarker candidate'],
reward: { validity: 0.90, ordering: 1.00, info_gain: 0.50, efficiency: 0.88, novelty: 0.70, penalty: 0.0 },
total: 0.55,
},
{
action: 'validate_marker', params: 'gene="SPP1", method="cross_validation"', category: 'comp',
budget: 65200, budgetPct: 65.2, time: 130, timePct: 72.2,
output: ['SPP1 Biomarker Validation Report:',' 5-fold CV AUROC: 0.91 (+/- 0.03)',' Sensitivity: 0.88',' Specificity: 0.87',' Positive LR: 6.77',' Expression in Aberrant Basaloid: 94.2% of cells',' Status: VALIDATED as IPF biomarker'],
reward: { validity: 0.95, ordering: 1.00, info_gain: 0.72, efficiency: 0.82, novelty: 0.85, penalty: 0.0 },
total: 0.76,
discovery: { title: 'SPP1 validated as IPF biomarker', detail: 'AUROC=0.91, specificity=0.87', color: 'var(--green)', bg: 'var(--green-dim)' },
},
{
action: 'synthesize_conclusion', params: 'confidence=0.85', category: 'meta',
budget: 65000, budgetPct: 65.0, time: 129, timePct: 71.7,
output: ['CONCLUSION (confidence: 0.85):','','SPP1 is a validated biomarker for IPF with strong','discriminative power (AUROC=0.91). It is upregulated','3.42-fold in IPF lungs, concentrated in Aberrant Basaloid','cells (94.2%), and participates in ECM-receptor, TGF-beta,','and PI3K-Akt signaling pathways.','','Literature match: 4/5 expected findings confirmed','Calibration: Well-calibrated (no overconfidence penalty)'],
reward: { validity: 1.00, ordering: 1.00, info_gain: 0.40, efficiency: 0.90, novelty: 0.50, penalty: 0.0 },
total: 0.91, terminal: true,
},
];
// State
let running = false;
let cumReward = 0;
// DOM refs
const terminalEl = document.getElementById('terminal');
const statusDot = document.getElementById('statusDot');
const statusText = document.getElementById('statusText');
const runBtn = document.getElementById('runBtn');
const labActionLabel = document.getElementById('labActionLabel');
// Helpers
function addLine(html) {
const div = document.createElement('div');
div.className = 't-line';
div.innerHTML = html || ' ';
terminalEl.appendChild(div);
terminalEl.scrollTop = terminalEl.scrollHeight;
}
function setGauge(id, value, pct, color) {
document.getElementById(id + 'Val').textContent = value;
const fill = document.getElementById(id + 'Fill');
fill.style.width = pct + '%';
if (color) fill.style.background = color;
}
function setRewardBars(r) {
for (const key of ['validity','ordering','info_gain','efficiency','novelty','penalty']) {
const el = document.getElementById('rw-' + key);
el.style.width = (r[key] * 100) + '%';
el.textContent = r[key] > 0.01 ? r[key].toFixed(2) : '';
}
}
function clearRewardBars() {
for (const key of ['validity','ordering','info_gain','efficiency','novelty','penalty']) {
const el = document.getElementById('rw-' + key);
el.style.width = '0%';
el.textContent = '';
}
}
function addPipeStep(step, index) {
const el = document.createElement('div');
el.className = 'pipe-step';
el.id = 'pipe-' + index;
const catColor = step.category === 'wet' ? 'var(--green)' : step.category === 'comp' ? 'var(--accent)' : 'var(--pink)';
el.innerHTML = `<div class="step-icon" style="color:${catColor};border-color:${catColor};">${index + 1}</div><span>${step.action}</span>`;
document.getElementById('pipelineSteps').appendChild(el);
requestAnimationFrame(() => el.classList.add('visible'));
return el;
}
function addDiscovery(d) {
const c = document.getElementById('discoveries');
if (c.querySelector('.empty-state')) c.innerHTML = '';
const el = document.createElement('div');
el.className = 'discovery';
el.innerHTML = `<div class="disc-icon" style="background:${d.bg};color:${d.color};">◆</div><div class="disc-body"><div class="disc-title">${d.title}</div><div class="disc-detail">${d.detail}</div></div>`;
c.appendChild(el);
requestAnimationFrame(() => el.classList.add('visible'));
}
function addRewardHistory(step, index) {
const c = document.getElementById('rewardHistory');
if (c.querySelector('.empty-state')) c.innerHTML = '';
const el = document.createElement('div');
el.className = 'step-reward-mini';
el.innerHTML = `<span class="srm-name">${index + 1}. ${step.action}</span><span class="srm-val ${step.total >= 0 ? 'pos' : 'neg'}">${step.total >= 0 ? '+' : ''}${step.total.toFixed(2)}</span>`;
c.appendChild(el);
requestAnimationFrame(() => el.classList.add('visible'));
}
function selectScenario(el) {
if (running) return;
document.querySelectorAll('.scenario-opt').forEach(e => e.classList.remove('active'));
el.classList.add('active');
}
function wait(ms) { return new Promise(r => setTimeout(r, ms)); }
// ---- Run ----
async function startDemo() {
if (running) return;
running = true;
runBtn.disabled = true;
runBtn.textContent = 'Running...';
statusDot.classList.add('live');
statusText.textContent = 'Running';
terminalEl.innerHTML = '';
cumReward = 0;
document.getElementById('pipelineSteps').innerHTML = '';
document.getElementById('discoveries').innerHTML = '<div class="empty-state">No discoveries yet</div>';
document.getElementById('rewardHistory').innerHTML = '<div class="empty-state">No steps yet</div>';
document.getElementById('violations').innerHTML = '<div class="empty-state">No violations</div>';
clearRewardBars();
document.getElementById('cumReward').textContent = '0.00';
document.getElementById('stepRewardLabel').textContent = '--';
initAgent();
addLine('<span class="t-label">[BioEnv]</span> <span class="t-dim">Initializing environment...</span>');
await wait(500);
addLine('<span class="t-label">[BioEnv]</span> Scenario: <span class="t-str">biomarker_validation_lung</span> (Hard)');
await wait(200);
addLine('<span class="t-label">[BioEnv]</span> Organism: <span class="t-str">Homo sapiens</span> | Tissue: <span class="t-str">Lung</span>');
await wait(200);
addLine('<span class="t-label">[BioEnv]</span> Budget: <span class="t-num">$100,000</span> | Time: <span class="t-num">180 days</span> | Max steps: <span class="t-num">30</span>');
await wait(200);
addLine('<span class="t-label">[BioEnv]</span> Task: Validate <span class="t-kw">SPP1</span> as biomarker for idiopathic pulmonary fibrosis');
await wait(400);
addLine('');
for (let i = 0; i < EPISODE.length; i++) {
await runStep(i);
await wait(500);
}
// Done
moveAgentTo('idle');
labActionLabel.classList.remove('visible');
addLine('');
addLine('<span class="t-label">[BioEnv]</span> <span class="t-ok">Episode complete!</span>');
addLine('<span class="t-label">[BioEnv]</span> Total reward: <span class="t-ok">+' + cumReward.toFixed(2) + '</span> | Steps: <span class="t-num">' + EPISODE.length + '</span> | Budget remaining: <span class="t-num">$65,000</span>');
addLine('<span class="t-label">[BioEnv]</span> Literature match: <span class="t-ok">4/5 expected findings confirmed</span>');
addLine('<span class="t-label">[BioEnv]</span> Calibration: <span class="t-ok">Well-calibrated</span> (no overconfidence penalty)');
statusDot.classList.remove('live');
statusText.textContent = 'Complete';
runBtn.textContent = 'Run Episode';
runBtn.disabled = false;
running = false;
}
async function runStep(i) {
const step = EPISODE[i];
const station = ACTION_STATION[step.action] || 'computer';
// Move agent in lab
moveAgentTo(station);
labActionLabel.textContent = step.action + '()';
labActionLabel.classList.add('visible');
await wait(800); // wait for agent to travel
// Start working animation
setAgentWorking(step.action);
spawnParticles(agent.targetX, agent.targetY, STATIONS[station].color);
// Pipeline sidebar
const pipeEl = addPipeStep(step, i);
if (i > 0) {
const prev = document.getElementById('pipe-' + (i - 1));
prev.classList.remove('active');
prev.classList.add('done');
prev.querySelector('.step-icon').innerHTML = '✓';
}
pipeEl.classList.add('active');
// Gauges
setGauge('budget', '$' + step.budget.toLocaleString(), step.budgetPct,
step.budgetPct > 50 ? 'var(--green)' : step.budgetPct > 25 ? 'var(--amber)' : 'var(--red)');
setGauge('time', step.time + ' / 180 days', step.timePct, 'var(--cyan)');
setGauge('step', (i + 1) + ' / 30', ((i + 1) / 30 * 100), 'var(--accent)');
// Terminal output
const catTag = step.category === 'wet' ? '<span class="t-ok">WET</span>'
: step.category === 'comp' ? '<span class="t-label">CMP</span>'
: '<span class="t-kw">META</span>';
addLine(`<span class="t-dim">Step ${i + 1}</span> ${catTag} <span class="t-fn">${step.action}</span>(<span class="t-str">${step.params}</span>)`);
await wait(300);
for (const line of step.output) {
addLine(' <span class="t-sub">' + line + '</span>');
await wait(80);
}
// Reward
cumReward += step.total;
document.getElementById('stepRewardLabel').textContent = 'Step ' + (i + 1) + ': ' + step.action;
setRewardBars(step.reward);
document.getElementById('cumReward').textContent = cumReward.toFixed(2);
addRewardHistory(step, i);
const rewardStr = step.total >= 0
? '<span class="t-ok">+' + step.total.toFixed(2) + '</span>'
: '<span class="t-err">' + step.total.toFixed(2) + '</span>';
addLine(` <span class="t-dim">reward: ${rewardStr} <span class="t-dim">(cumulative: ${cumReward.toFixed(2)})</span></span>`);
addLine('');
if (step.discovery) addDiscovery(step.discovery);
// Done working
agent.working = false;
spawnParticles(agent.targetX, agent.targetY, '#34d399', 6);
if (step.terminal) {
pipeEl.classList.remove('active');
pipeEl.classList.add('done');
pipeEl.querySelector('.step-icon').innerHTML = '✓';
}
}
function resetDemo() {
if (running) return;
terminalEl.innerHTML = '';
cumReward = 0;
document.getElementById('pipelineSteps').innerHTML = '';
document.getElementById('discoveries').innerHTML = '<div class="empty-state">No discoveries yet</div>';
document.getElementById('rewardHistory').innerHTML = '<div class="empty-state">No steps yet</div>';
document.getElementById('violations').innerHTML = '<div class="empty-state">No violations</div>';
clearRewardBars();
document.getElementById('cumReward').textContent = '0.00';
document.getElementById('stepRewardLabel').textContent = '--';
setGauge('budget', '$100,000', 100, 'var(--green)');
setGauge('time', '180 / 180 days', 100, 'var(--cyan)');
setGauge('step', '0 / 30', 0, 'var(--accent)');
statusDot.classList.remove('live');
statusText.textContent = 'Ready';
labActionLabel.classList.remove('visible');
initAgent();
addLine('<span class="t-dim">Environment reset. Click "Run Episode" to start.</span>');
}
// Init
addLine('<span class="t-dim">BioEnv v1.0 | biomarker_validation_lung</span>');
addLine('<span class="t-dim">Click "Run Episode" to start the demo.</span>');
</script>
</body>
</html>
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