"""
Monte Carlo System Envelope Mapping for DOLPHIN NG
==================================================

Full-system operational envelope simulation and ML forewarning integration.

This package implements the Monte Carlo System Envelope Specification for
the Nautilus-Dolphin trading system. It provides:

1. Parameter space sampling (Latin Hypercube Sampling)
2. Internal consistency validation (V1-V4 constraint groups)
3. Trial execution harness (backtest runner)
4. Metric extraction (48 metrics, 10 classification labels)
5. Result persistence (Parquet + SQLite index)
6. ML envelope learning (One-Class SVM, XGBoost)
7. Live forewarning API (risk assessment for configurations)

Usage:
    from nautilus_dolphin.mc import MCSampler, MCValidator, MCExecutor
    
    # Run envelope testing
    python run_mc_envelope.py --mode run --stage 1 --n-samples 500
    
    # Train ML models on results
    python run_mc_envelope.py --mode train --output-dir mc_results/
    
    # Assess a live configuration
    python run_mc_envelope.py --mode assess --assess my_config.json

Reference:
    MONTE_CARLO_SYSTEM_ENVELOPE_SPEC.md - Complete specification document
"""

__version__ = "1.0.0"
__author__ = "DOLPHIN NG Team"

# Core modules (lazy import to avoid heavy dependencies on import)
def __getattr__(name):
    if name == "MCSampler":
        from .mc_sampler import MCSampler
        return MCSampler
    elif name == "MCValidator":
        from .mc_validator import MCValidator
        return MCValidator
    elif name == "MCExecutor":
        from .mc_executor import MCExecutor
        return MCExecutor
    elif name == "MCMetrics":
        from .mc_metrics import MCMetrics
        return MCMetrics
    elif name == "MCStore":
        from .mc_store import MCStore
        return MCStore
    elif name == "MCRunner":
        from .mc_runner import MCRunner
        return MCRunner
    elif name == "MCML":
        from .mc_ml import MCML
        return MCML
    elif name == "DolphinForewarner":
        from .mc_ml import DolphinForewarner
        return DolphinForewarner
    elif name == "MCTrialConfig":
        from .mc_sampler import MCTrialConfig
        return MCTrialConfig
    elif name == "MCTrialResult":
        from .mc_metrics import MCTrialResult
        return MCTrialResult
    raise AttributeError(f"module '{__name__}' has no attribute '{name}'")

__all__ = [
    # Core classes
    "MCSampler",
    "MCValidator", 
    "MCExecutor",
    "MCMetrics",
    "MCStore",
    "MCRunner",
    "MCML",
    "DolphinForewarner",
    "MCTrialConfig",
    "MCTrialResult",
    # Version
    "__version__",
]