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Deploy Aureon OS (deploy/selfhost stack: nginx edge + fusion API x2 + console + HNC organ + redis + postgres; paper mode) (part 3)
1ccf652 verified | #!/usr/bin/env python3 | |
| """ | |
| 📊 BOT SHAPE 3D VIEWER 📊 | |
| ═══════════════════════════════════════════════════════════════════════════════ | |
| Visualizes the spectral fingerprints generated by the Bot Shape Scanner. | |
| Outputs: | |
| - `bot_shapes.html`: Interactive 3D plot (open in browser) | |
| Usage: | |
| python bot_shape_viewer.py | |
| Gary Leckey | January 2026 | |
| ═══════════════════════════════════════════════════════════════════════════════ | |
| """ | |
| from aureon.core.aureon_baton_link import link_system as _baton_link; _baton_link(__name__) | |
| import json | |
| import os | |
| import sys | |
| import time | |
| try: | |
| import plotly.graph_objects as go | |
| from plotly.subplots import make_subplots | |
| except ImportError: | |
| print("❌ Plotly not found. Please install: pip install plotly") | |
| sys.exit(1) | |
| SNAPSHOT_FILE = "bot_shape_snapshot.json" | |
| OUTPUT_HTML = "bot_shapes.html" | |
| def render_viewer(): | |
| if not os.path.exists(SNAPSHOT_FILE): | |
| print(f"⚠️ Snapshot file '{SNAPSHOT_FILE}' not found. Run aureon_bot_shape_scanner.py first.") | |
| return | |
| try: | |
| with open(SNAPSHOT_FILE, "r") as f: | |
| data = json.load(f) | |
| except Exception as e: | |
| print(f"❌ Error reading snapshot: {e}") | |
| return | |
| shapes = data.get("shapes", []) | |
| if not shapes: | |
| print("⚠️ No shapes found in snapshot.") | |
| return | |
| print(f"🎨 Rendering 3D Bot Shapes for {len(shapes)} symbols...") | |
| feature_x = [] # Symbol Index | |
| feature_y = [] # Frequency | |
| feature_z = [] # Amplitude | |
| hover_text = [] | |
| colors = [] | |
| marker_sizes = [] | |
| symbol_map = {s['symbol']: i for i, s in enumerate(shapes)} | |
| for i, shape in enumerate(shapes): | |
| sym = shape['symbol'] | |
| freqs = shape['dominant_freqs'] | |
| amps = shape['amplitudes'] | |
| bot_class = shape['bot_class'] | |
| # Base color based on bot class | |
| base_color = 0 # Default | |
| if "HFT" in bot_class: base_color = 1 | |
| elif "MM" in bot_class: base_color = 2 | |
| elif "ACCUM" in bot_class: base_color = 3 | |
| for f, a in zip(freqs, amps): | |
| feature_x.append(i) # Symbol on X axis (categorical) | |
| feature_y.append(f) # Frequency on Y | |
| feature_z.append(a) # Amplitude (Magnitude) on Z | |
| hover_text.append( | |
| f"<b>{sym}</b><br>" + | |
| f"Class: {bot_class}<br>" + | |
| f"Freq: {f:.2f}Hz<br>" + | |
| f"Amp: {a:.2f}" | |
| ) | |
| colors.append(base_color) | |
| marker_sizes.append(min(50, max(5, a * 20))) # Scale size by amplitude | |
| # Create 3D Scatter Plot | |
| fig = go.Figure(data=[go.Scatter3d( | |
| x=feature_x, | |
| y=feature_y, | |
| z=feature_z, | |
| mode='markers', | |
| marker=dict( | |
| size=marker_sizes, | |
| color=colors, | |
| colorscale='Viridis', | |
| opacity=0.8 | |
| ), | |
| text=hover_text, | |
| hoverinfo='text' | |
| )]) | |
| # Update layout | |
| tick_vals = list(range(len(shapes))) | |
| tick_text = [s['symbol'] for s in shapes] | |
| fig.update_layout( | |
| title=f"Aureon Bot Shape Quantum Telescope (Timestamp: {time.ctime(data['timestamp'])})", | |
| scene=dict( | |
| xaxis=dict( | |
| title='Asset (Reality Branch)', | |
| tickmode='array', | |
| tickvals=tick_vals, | |
| ticktext=tick_text | |
| ), | |
| yaxis=dict(title='Frequency (Hz) - The "Loop"'), | |
| zaxis=dict(title='Amplitude (Magnitude)'), | |
| ), | |
| margin=dict(r=0, l=0, b=0, t=40) | |
| ) | |
| fig.write_html(OUTPUT_HTML) | |
| print(f"✅ 3D View saved to: {os.path.abspath(OUTPUT_HTML)}") | |
| if __name__ == "__main__": | |
| while True: | |
| render_viewer() | |
| print("Waiting 10s for next update...") | |
| time.sleep(10) | |