86 lines
2.6 KiB
Python
86 lines
2.6 KiB
Python
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"""
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Monte Carlo System Envelope Mapping for DOLPHIN NG
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==================================================
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Full-system operational envelope simulation and ML forewarning integration.
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This package implements the Monte Carlo System Envelope Specification for
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the Nautilus-Dolphin trading system. It provides:
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1. Parameter space sampling (Latin Hypercube Sampling)
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2. Internal consistency validation (V1-V4 constraint groups)
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3. Trial execution harness (backtest runner)
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4. Metric extraction (48 metrics, 10 classification labels)
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5. Result persistence (Parquet + SQLite index)
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6. ML envelope learning (One-Class SVM, XGBoost)
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7. Live forewarning API (risk assessment for configurations)
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Usage:
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from nautilus_dolphin.mc import MCSampler, MCValidator, MCExecutor
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# Run envelope testing
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python run_mc_envelope.py --mode run --stage 1 --n-samples 500
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# Train ML models on results
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python run_mc_envelope.py --mode train --output-dir mc_results/
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# Assess a live configuration
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python run_mc_envelope.py --mode assess --assess my_config.json
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Reference:
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MONTE_CARLO_SYSTEM_ENVELOPE_SPEC.md - Complete specification document
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"""
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__version__ = "1.0.0"
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__author__ = "DOLPHIN NG Team"
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# Core modules (lazy import to avoid heavy dependencies on import)
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def __getattr__(name):
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if name == "MCSampler":
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from .mc_sampler import MCSampler
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return MCSampler
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elif name == "MCValidator":
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from .mc_validator import MCValidator
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return MCValidator
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elif name == "MCExecutor":
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from .mc_executor import MCExecutor
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return MCExecutor
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elif name == "MCMetrics":
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from .mc_metrics import MCMetrics
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return MCMetrics
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elif name == "MCStore":
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from .mc_store import MCStore
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return MCStore
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elif name == "MCRunner":
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from .mc_runner import MCRunner
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return MCRunner
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elif name == "MCML":
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from .mc_ml import MCML
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return MCML
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elif name == "DolphinForewarner":
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from .mc_ml import DolphinForewarner
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return DolphinForewarner
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elif name == "MCTrialConfig":
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from .mc_sampler import MCTrialConfig
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return MCTrialConfig
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elif name == "MCTrialResult":
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from .mc_metrics import MCTrialResult
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return MCTrialResult
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raise AttributeError(f"module '{__name__}' has no attribute '{name}'")
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__all__ = [
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# Core classes
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"MCSampler",
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"MCValidator",
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"MCExecutor",
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"MCMetrics",
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"MCStore",
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"MCRunner",
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"MCML",
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"DolphinForewarner",
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"MCTrialConfig",
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"MCTrialResult",
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# Version
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"__version__",
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]
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