Files
foxhunt/ml/tests/action_loader_real_csv_test.rs
jgrusewski 3853988af7 feat(hyperopt): Complete DQN hyperopt analysis and PSO optimizer fix
- Fixed PSO budget calculation bug in ml/src/hyperopt/optimizer.rs
  - Root cause: Division by n_particles in sequential execution
  - Now correctly calculates max_iters = remaining_trials (no division)
  - Result: 50 trials complete instead of 23 (100% vs 46%)

- Added comprehensive DQN hyperopt results analysis
  - 39/50 trials analyzed across 2 RunPod deployments
  - Best hyperparameters identified: LR 4.89e-5 (ultra-low)
  - Created DQN_HYPEROPT_RESULTS_SUMMARY.md with expert validation

- GitLab CI/CD pipeline operational (48 lines fixed)
  - Fixed YAML syntax errors (unquoted colons)
  - All 7 jobs validated and working

- Warning cleanup complete (136 → 0 warnings)
  - Removed 143 lines dead code
  - Fixed visibility, unused imports, Debug traits

- Archived Wave D reports to docs/archive/
  - 8 early stopping reports moved
  - Root directory cleaned up

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

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-02 21:49:07 +01:00

99 lines
3.3 KiB
Rust

// ml/tests/action_loader_real_csv_test.rs
// Test loading the real DQN actions CSV file
use ml::backtesting::load_actions_from_csv;
#[test]
fn test_load_real_csv_file() {
// Test loading the real CSV file with 13,552 actions
let csv_path = "/tmp/dqn_actions_wave3.csv";
// Skip test if CSV file doesn't exist
if !std::path::Path::new(csv_path).exists() {
eprintln!("Skipping test: {} not found", csv_path);
return;
}
let actions = load_actions_from_csv(csv_path).unwrap();
// Verify count (13,552 actions)
assert_eq!(actions.len(), 13_552, "Expected 13,552 actions from CSV");
// Verify first action
assert_eq!(actions[0].action, 2, "First action should be 2 (Hold)");
assert_eq!(actions[0].q_buy, -658.8440);
assert_eq!(actions[0].q_sell, 355.0268);
assert_eq!(actions[0].q_hold, 538.5875);
assert_eq!(actions[0].open, 5914.50);
assert_eq!(actions[0].high, 5914.75);
assert_eq!(actions[0].low, 5914.25);
assert_eq!(actions[0].close, 5914.25);
assert_eq!(actions[0].volume, 27);
// Verify all actions have valid bounds (0-2)
for (i, action) in actions.iter().enumerate() {
assert!(
action.action <= 2,
"Action {} at index {} exceeds bounds",
action.action,
i
);
}
// Verify all Q-values are finite
for (i, action) in actions.iter().enumerate() {
assert!(
action.q_buy.is_finite(),
"q_buy at index {} is not finite",
i
);
assert!(
action.q_sell.is_finite(),
"q_sell at index {} is not finite",
i
);
assert!(
action.q_hold.is_finite(),
"q_hold at index {} is not finite",
i
);
}
// Verify timestamp ordering (monotonically increasing)
for i in 1..actions.len() {
assert!(
actions[i].timestamp >= actions[i - 1].timestamp,
"Timestamp ordering violation at index {}: {} < {}",
i,
actions[i].timestamp,
actions[i - 1].timestamp
);
}
// Verify action distribution (sanity check)
let mut buy_count = 0;
let mut sell_count = 0;
let mut hold_count = 0;
for action in &actions {
match action.action {
0 => buy_count += 1,
1 => sell_count += 1,
2 => hold_count += 1,
_ => panic!("Invalid action: {}", action.action),
}
}
// Note: Buy count might be 0 for certain datasets (DQN-specific behavior)
assert_eq!(buy_count + sell_count + hold_count, 13_552, "Action counts must sum to total");
println!("Action distribution:");
println!(" Buy: {} ({:.2}%)", buy_count, 100.0 * buy_count as f64 / actions.len() as f64);
println!(" Sell: {} ({:.2}%)", sell_count, 100.0 * sell_count as f64 / actions.len() as f64);
println!(" Hold: {} ({:.2}%)", hold_count, 100.0 * hold_count as f64 / actions.len() as f64);
// Verify expected distribution for this specific CSV (no buy actions)
assert_eq!(buy_count, 0, "Expected 0 buy actions for this dataset");
assert_eq!(sell_count, 7_668, "Expected 7,668 sell actions");
assert_eq!(hold_count, 5_884, "Expected 5,884 hold actions");
}