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WAVE 12.5.2 - ML Pipeline Integration Tests - Quick Reference
Status: ✅ COMPLETE (11/11 tests, 100% pass rate) Test Time: 0.08 seconds Commit: c96a1533, 79c6fb20
🚀 Run Tests
# Run all ML pipeline integration tests
cargo test -p foxhunt_e2e --test ml_pipeline_integration_test
# Run with output
cargo test -p foxhunt_e2e --test ml_pipeline_integration_test -- --nocapture
# Run single test
cargo test -p foxhunt_e2e --test ml_pipeline_integration_test test_full_ml_pipeline_end_to_end
📝 Test Summary (11 Tests)
| # | Test Name | Purpose | Status |
|---|---|---|---|
| 1 | test_full_ml_pipeline_end_to_end | Complete pipeline (7 stages) | ✅ |
| 2 | test_real_time_prediction_pipeline | Streaming predictions | ✅ |
| 3 | test_multi_symbol_pipeline | ES.FUT + ZN.FUT | ✅ |
| 4 | test_dbn_to_ml_features | DBN → 16 features | ✅ |
| 5 | test_ml_predictions_to_trading_decisions | Predictions → Orders | ✅ |
| 6 | test_trading_decisions_to_orders | Decisions → Executable | ✅ |
| 7 | test_adaptive_ensemble_real_data | Ensemble validation | ✅ |
| 8 | test_shared_ml_strategy_integration | ONE SINGLE SYSTEM | ✅ |
| 9 | test_regime_detection_accuracy | Bull/Bear/Sideways | ✅ |
| 10 | test_ml_inference_latency | <100ms target | ✅ |
| 11 | test_backtesting_throughput | >100 bars/s target | ✅ |
📁 Key Files
tests/e2e/
├── tests/
│ └── ml_pipeline_integration_test.rs # 850+ lines, 11 tests
└── Cargo.toml # Added dbn + candle-core deps
test_data/real/databento/ml_training/
└── ES.FUT_ohlcv-1m_2024-03-25.dbn # 1,674+ bars
🔧 Pipeline Stages
1. Data Ingestion → Load DBN binary files
2. Feature Engineering → Extract 16 technical indicators
3. ML Prediction → Generate ensemble predictions (mock)
4. Trading Agent → Universe/Asset/Allocation decisions
5. Order Generation → Create executable orders
6. Trading Execution → Execute orders (simulated)
7. Backtesting → Calculate performance metrics
📊 Features Extracted (16 Total)
| Feature | Type | Lookback |
|---|---|---|
| Open, High, Low, Close, Volume | OHLCV | Current bar |
| Returns | Momentum | 1 bar |
| MA5 | Moving Avg | 5 bars |
| Volatility | Std Dev | 10 bars |
| RSI | Oscillator | 14 bars |
| MACD, Signal | Trend | 12/26 bars |
| Bollinger Upper/Lower | Volatility | 20 bars |
| ATR | Volatility | 14 bars |
| EMA12, EMA26 | Moving Avg | 12/26 bars |
⚡ Performance Targets
| Metric | Target | Actual | Status |
|---|---|---|---|
| Full pipeline time | <30s | 0.08s | ✅ 375x faster |
| Inference latency | <100ms | <1ms | ✅ 100x faster (mock) |
| Backtest throughput | >100 bars/s | >10K bars/s | ✅ 100x faster |
🔄 Mock vs Real
Current (Mock)
- Strategy: Moving Average Crossover (5 vs 20 period)
- Purpose: Validate infrastructure
- Performance: <1ms per prediction
- Status: ✅ All tests passing
Next Wave (Real)
- Models: MAMBA-2, DQN, PPO, TFT (6 models total)
- Purpose: Production predictions
- Expected: 10-50ms per prediction (GPU)
- Status: ⏳ Pending trained checkpoints
📈 Usage Examples
Load DBN Data
let bars = load_dbn_data("test_data/real/databento/ml_training/ES.FUT_ohlcv-1m_2024-03-25.dbn").await?;
// Returns: Vec<OhlcvBar> with timestamp, OHLCV, symbol
Extract Features
let features = extract_features(&bars)?;
// Returns: Vec<Vec<f64>> - 16 features per bar
Generate Predictions
let predictions = mock_ensemble_predictions(&bars, &features)?;
// Returns: Vec<f64> - prediction scores (0.0-1.0)
Create Trading Decisions
let decisions = generate_trading_decisions(&predictions)?;
// Returns: Vec<TradingDecision> with action (Buy/Sell/Hold)
🐛 Known Issues
None! All 11 tests passing.
🎯 Next Steps
-
Load Real Models (Priority 1)
- Replace mock with MAMBA-2, DQN, PPO, TFT
- Test with trained checkpoints
- Validate GPU inference
-
Expand Symbols (Priority 2)
- Add NQ.FUT, 6E.FUT, GC.FUT
- Test multi-symbol coordination
- Validate cross-symbol strategies
-
Real Trading Integration (Priority 3)
- Connect to Trading Service gRPC
- Test paper trading execution
- Real-time market data streaming
-
Production Deployment (Priority 4)
- Add monitoring and alerts
- Production logging
- Error handling and recovery
📚 Documentation
- Full Report:
WAVE_12_5_2_ML_PIPELINE_INTEGRATION_COMPLETE.md - Test File:
tests/e2e/tests/ml_pipeline_integration_test.rs - CLAUDE.md: Section on ML Pipeline Testing (updated)
🔗 Related Waves
- Wave 12.4.1: Trading Service ML Migration (SharedMLStrategy)
- Wave 12.4.2: Backtesting E2E Migration (Real implementations)
- Wave 206: MAMBA-2 Shape Bug Fix (Ready for training)
Quick Command:
cargo test -p foxhunt_e2e --test ml_pipeline_integration_test -- --nocapture
Expected Output: test result: ok. 11 passed; 0 failed; 0 ignored
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