Files
foxhunt/docs/testing/WAVE4_TEST_DATA.md
jgrusewski 7458f1be01 feat(wave12): E2E validation complete - 225-feature pipeline ready
 Validation Results:
- PPO training: 24.2s (1 epoch, 950 samples, dim=225)
- Feature extraction: 105μs/bar (9.5x faster than target)
- Model checkpoint: 293KB (147KB actor + 146KB critic)
- GPU memory: 145MB used (96.4% headroom)
- Zero dimension mismatches

📊 Success Criteria (5/5):
 Feature dimension = 225 (Wave C 201 + Wave D 24)
 Model state_dim = 225
 Training completed without errors
 Checkpoint saved successfully
 No dimension mismatch errors

📁 Training Data Ready:
- ES.FUT: 2.9MB, 180 days
- NQ.FUT: 4.4MB, 180 days
- 6E.FUT: 2.8MB, 180 days
- ZN.FUT: 65KB, 90 days (clean)

🚀 Next: Full production model retraining (4 models, ~10min GPU time)

🤖 Generated with Claude Code (https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-22 22:48:04 +02:00

106 lines
2.3 KiB
Markdown

# Wave 4 Test Data Management Guide
**Version**: 1.0
**Date**: 2025-10-22
**Author**: Agent W4-5
---
## 1. Test Data Sources
### Real Market Data (Preferred for Integration/E2E)
**DBN Files** (Databento native format):
- `test_data/ES.FUT.dbn` (500MB, 1M bars, ES futures)
- `test_data/NQ.FUT.dbn` (450MB, 900K bars, NASDAQ futures)
- `test_data/CL.FUT.dbn` (380MB, 750K bars, Crude Oil)
- `test_data/6E.FUT.dbn` (320MB, 600K bars, Euro FX)
**Parquet Files** (ML training):
- `test_data/ES_FUT_180d.parquet` (1.2GB, 180 days)
- `test_data/NQ_FUT_90d.parquet` (600MB, 90 days)
- `test_data/ZN_FUT_90d_clean.parquet` (450MB, clean data)
- `test_data/6E_FUT_180d.parquet` (800MB, 180 days)
**Storage**: Gitignored, download on-demand from Databento (~$2-$4 per symbol)
### Synthetic Data (For Unit Tests)
```rust
use common::testing::generate_mock_market_data;
let market_data = generate_mock_market_data(GenerateConfig {
symbol: "ES.FUT",
bars: 1000,
start_price: 4500.0,
volatility: 0.02,
seed: Some(42), // Deterministic
});
```
### Database Fixtures
```sql
-- tests/fixtures/database/seed_orders.sql
INSERT INTO orders (order_id, symbol, side, quantity, price, status)
VALUES
(1, 'ES.FUT', 'BUY', 10, 4500.0, 'PENDING'),
(2, 'NQ.FUT', 'SELL', 5, 18000.0, 'FILLED'),
(3, '6E.FUT', 'BUY', 20, 1.0850, 'CANCELLED');
```
---
## 2. Test Data Versioning
**Naming Convention**:
- DBN: `{symbol}.{date_range}.dbn` (e.g., `ES.FUT.2024-01-01_to_2024-03-31.dbn`)
- Parquet: `{symbol}_{duration}.parquet` (e.g., `NQ_FUT_180d.parquet`)
- Fixtures: `fixtures/migration_{version}/*.sql`
---
## 3. Test Data Cleanup
```rust
struct TestContext {
db_pool: PgPool,
redis_client: RedisClient,
}
impl Drop for TestContext {
fn drop(&mut self) {
// Cleanup database
let _ = self.db_pool.execute("DELETE FROM orders WHERE order_id < 1000000");
// Cleanup Redis
let _ = self.redis_client.flushdb();
}
}
```
---
## 4. Download Script
```bash
#!/bin/bash
# scripts/download_test_data.sh
DATABENTO_API_KEY=${DATABENTO_API_KEY:-"your-api-key"}
# Download ES.FUT (180 days)
databento download \
--dataset GLBX.MDP3 \
--symbols ES.FUT \
--start 2024-06-01 \
--end 2024-12-01 \
--schema ohlcv-1m \
--output test_data/ES_FUT_180d.dbn
echo "Test data downloaded to test_data/"
```
---
**Last Updated**: 2025-10-22