# Module: metrics_calculator

## Purpose
The `metrics_calculator` module handles calculation and management of trading metrics including Order Book Imbalance (OBI) and Cumulative Volume Delta (CVD). It provides windowed aggregation with throttled updates for real-time visualization.

## Public Interface

### Classes
- `MetricsCalculator(window_seconds: int = 60, emit_every_n_updates: int = 25)`: Main metrics calculation engine

### Methods
- `update_cvd_from_trade(side: str, size: float) -> None`: Update CVD from individual trade data
- `update_obi_metrics(timestamp: str, total_bids: float, total_asks: float) -> None`: Update OBI metrics from orderbook volumes
- `finalize_metrics() -> None`: Emit final metrics bar at processing end

### Properties
- `cvd_cumulative: float`: Current cumulative volume delta value

### Private Methods  
- `_emit_metrics_bar() -> None`: Emit current metrics to visualization layer

## Usage Examples

```python
from metrics_calculator import MetricsCalculator

# Initialize calculator
calc = MetricsCalculator(window_seconds=60, emit_every_n_updates=25)

# Update CVD from trades
calc.update_cvd_from_trade("buy", 1.5)   # +1.5 CVD
calc.update_cvd_from_trade("sell", 1.0)  # -1.0 CVD, net +0.5

# Update OBI from orderbook
total_bids, total_asks = 150.0, 120.0
calc.update_obi_metrics("1640995200000", total_bids, total_asks)

# Access current CVD
current_cvd = calc.cvd_cumulative  # 0.5

# Finalize at end of processing
calc.finalize_metrics()
```

## Metrics Definitions

### Cumulative Volume Delta (CVD)
- **Formula**: CVD = Σ(buy_volume - sell_volume)
- **Interpretation**: Positive = more buying pressure, Negative = more selling pressure
- **Accumulation**: Running total across all processed trades
- **Update Frequency**: Every trade

### Order Book Imbalance (OBI)
- **Formula**: OBI = total_bid_volume - total_ask_volume
- **Interpretation**: Positive = more bid liquidity, Negative = more ask liquidity
- **Aggregation**: OHLC-style bars per time window (open, high, low, close)
- **Update Frequency**: Throttled per orderbook update

## Dependencies

### Internal
- `viz_io.upsert_metric_bar`: Output interface for visualization

### External
- `logging`: Warning messages for unknown trade sides
- `typing`: Type annotations

## Windowed Aggregation

### OBI Windows
- **Window Size**: Configurable via `window_seconds` (default: 60)
- **Window Alignment**: Aligned to epoch time boundaries
- **OHLC Tracking**: Maintains open, high, low, close values per window
- **Rollover**: Automatic window transitions with final bar emission

### Throttling Mechanism
- **Purpose**: Reduce I/O overhead during high-frequency updates
- **Trigger**: Every N updates (configurable via `emit_every_n_updates`)
- **Behavior**: Emits intermediate updates for real-time visualization
- **Final Emission**: Guaranteed on window rollover and finalization

## State Management

### CVD State
- `cvd_cumulative: float`: Running total across all trades
- **Persistence**: Maintained throughout processor lifetime
- **Updates**: Incremental addition/subtraction per trade

### OBI State
- `metrics_window_start: int`: Current window start timestamp
- `metrics_bar: dict`: Current OBI OHLC values
- `_metrics_since_last_emit: int`: Throttling counter

## Output Format

### Metrics Bar Structure
```python
{
    'obi_open': float,    # First OBI value in window
    'obi_high': float,    # Maximum OBI in window  
    'obi_low': float,     # Minimum OBI in window
    'obi_close': float,   # Latest OBI value
}
```

### Visualization Integration
- Emitted via `viz_io.upsert_metric_bar(timestamp, obi_open, obi_high, obi_low, obi_close, cvd_value)`
- Compatible with existing OHLC visualization infrastructure
- Real-time updates during active processing

## Performance Characteristics

- **Low Memory**: Maintains only current window state
- **Throttled I/O**: Configurable update frequency prevents excessive writes
- **Efficient Updates**: O(1) operations for trade and OBI updates
- **Window Management**: Automatic transitions without manual intervention

## Configuration

### Constructor Parameters
- `window_seconds: int`: Time window for OBI aggregation (default: 60)
- `emit_every_n_updates: int`: Throttling factor for intermediate updates (default: 25)

### Tuning Guidelines
- **Higher throttling**: Reduces I/O load, delays real-time updates
- **Lower throttling**: More responsive visualization, higher I/O overhead
- **Window size**: Affects granularity of OBI trends (shorter = more detail)

## Testing

```bash
uv run pytest test_metrics_calculator.py -v
```

Test coverage includes:
- CVD accumulation accuracy across multiple trades
- OBI window rollover and OHLC tracking
- Throttling behavior verification
- Edge cases (unknown trade sides, empty windows)
- Integration with visualization output

## Known Limitations

- CVD calculation assumes binary buy/sell classification
- No support for partial fills or complex order types
- OBI calculation treats all liquidity equally (no price weighting)
- Window boundaries aligned to absolute timestamps (no sliding windows)