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WebUI Guide

The Shinka WebUI provides real-time visualization of the evolutionary process: monitoring experiments, exploring solution genealogies, and analyzing metrics.

Overview

  • Real-time Updates — Live monitoring of ongoing experiments
  • Evolution Tree — Interactive visualization of solution genealogies
  • Performance Metrics — Fitness charts over generations
  • Code Diff Viewer — Side-by-side comparison of evolved solutions
  • Island Visualization — Multi-island evolution monitoring
  • Database Browser — Explore archived solutions and metadata

WebUI Screenshot

Quick Start

Local experiment

# Start evolution
shinka_launch

# In another terminal, launch the WebUI
shinka_visualize --port 8888 --open

# Or specify a results directory
shinka_visualize results_20241201_120000/ --port 8888 --open

# Or target a specific database file
shinka_visualize --db results_20241201_120000/evolution_db.sqlite --port 8888 --open

Remote experiment

# On remote machine
shinka_visualize --port 8888

# On local machine (SSH tunnel)
ssh -L 8888:localhost:8888 username@remote-host

# Open http://localhost:8888

Async runner support

# Start async evolution
python run_evo.py

# Auto-detects database in current directory
shinka_visualize --open

# Or with specific results directory / database
shinka_visualize results_20241201_120000/ --open
shinka_visualize --db results_20241201_120000/evolution_db.sqlite --open

Launch Options

Argument Default Description
root_directory Current dir Root directory to search for database files
-p, --port 8000 Port for the web server
--db Auto-detect Path to specific SQLite database file
--open False Auto-open browser

Features

Evolution Tree

Genealogical relationships between solutions:

  • Nodes — Individual solutions with fitness scores
  • Edges — Parent-child relationships
  • Colors — Performance-based color coding
  • Interactive — Click nodes for details; zoom, pan, select, double-click to reset

Performance Metrics

  • Best/average fitness per generation
  • Population diversity measures
  • Mutation success rate
  • Computational time per generation
  • Island comparison and convergence analysis

Code Diff Viewer

  • Side-by-side parent vs child comparison
  • Syntax highlighting and change highlighting
  • Diff statistics (lines changed, complexity)
  • Unified or split view

Solution Browser

  • Search, filter, and sort by fitness/generation/date
  • Metadata view and export options
  • Filter by generation range, fitness threshold, island ID, success status

Island Visualization

  • Island status and performance overview
  • Migration tracking between islands
  • Population diversity comparison

Real-time Updates

  • Configurable refresh intervals
  • Progress indicators for ongoing evaluations
  • Auto-scroll to follow latest generations

Remote Access

SSH tunneling

# Basic tunnel
ssh -L 8888:localhost:8888 username@remote-host

# Persistent connection
ssh -L 8888:localhost:8888 -N username@remote-host

Cluster access

# Through login node to compute node
ssh -L 8888:compute-node:8888 username@cluster-login-node

Multiple experiments

shinka_visualize exp1/ --port 8888
shinka_visualize exp2/ --port 8889

Troubleshooting

Issue Solution
Database not found Specify path: shinka_visualize --db /full/path/to/evolution_db.sqlite
Port in use Use different port: --port 9000
No data displayed Check experiment has started, verify path, check permissions
SSH tunnel issues Test with curl http://localhost:8888; debug with ssh -v ...
Browser issues Hard refresh (Ctrl+F5), check firewall, try different browser

Advanced Usage

API endpoints

Endpoint Description
GET /api/generations List all generations
GET /api/generation/{id} Specific generation data
GET /api/solutions/{id} Solution details
GET /api/metrics Performance metrics
GET /api/islands Island information

Embedding in Jupyter

from IPython.display import IFrame
import subprocess, time

subprocess.Popen(['shinka_visualize', '--port', '8888'])
time.sleep(2)
IFrame('http://localhost:8888', width=1000, height=600)

Best practices

  • Use SSH tunnels for remote access; never expose ports publicly
  • Reduce refresh frequency for large experiments
  • Regularly backup evolution databases
  • Close WebUI when not actively monitoring