Melvin Alvarez
9a8032e4ee
- Implement 6 helper functions in src/timeseries_utils.rs: * prepare_for_hmm: Feature engineering for HMM regime detection * rolling_hurst_exponent: Mean-reversion detection (H < 0.5 = mean-reverting) * rolling_half_life: Mean-reversion speed for pairs trading * return_statistics: Risk metrics (mean, std, skew, kurt, sharpe) * create_lagged_features: ML feature matrix creation * rolling_correlation: Rolling correlation for pairs trading - Add PyO3 bindings in src/timeseries_utils/python_bindings.rs: * All functions exposed with _py suffix * Proper signature decorators and error handling * Registered in lib.rs module system - Update Python module exports: * python/optimizr/core.py: Import from _core * python/optimizr/__init__.py: Re-export all functions - Create comprehensive example: * examples/timeseries_integration.py demonstrates all 6 functions * Includes integrated pairs trading workflow * Shows feature engineering for regime detection - Technical details: * Fixed Array1<f64> type conversions for ndarray compatibility * Uses risk_metrics::hurst_exponent and estimate_half_life * Built successfully with maturin develop --release (40.93s) * All functions tested and working correctly Part of Priority 3: Time-series integration helpers (Enhancement Strategy) Addresses v0.3.0 roadmap: Bridge optimization with time-series analysis
66 lines
1.5 KiB
Python
66 lines
1.5 KiB
Python
"""
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OptimizR - High-Performance Optimization Algorithms
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===================================================
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Fast, reliable implementations of advanced optimization and statistical
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inference algorithms with Rust acceleration and pure Python fallbacks.
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.. moduleauthor:: OptimizR Contributors
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"""
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from optimizr.hmm import HMM
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from optimizr.core import (
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mcmc_sample,
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differential_evolution,
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grid_search,
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mutual_information,
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shannon_entropy,
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sparse_pca_py,
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box_tao_decomposition_py,
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elastic_net_py,
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hurst_exponent_py,
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compute_risk_metrics_py,
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estimate_half_life_py,
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bootstrap_returns_py,
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# Time-series utilities
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prepare_for_hmm_py,
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rolling_hurst_exponent_py,
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rolling_half_life_py,
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return_statistics_py,
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create_lagged_features_py,
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rolling_correlation_py,
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)
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# Try to import maths_toolkit from Rust backend
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try:
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from optimizr import _core
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maths_toolkit = _core
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except (ImportError, AttributeError):
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maths_toolkit = None
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__version__ = "0.2.0"
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__all__ = [
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"HMM",
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"mcmc_sample",
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"differential_evolution",
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"grid_search",
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"mutual_information",
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"shannon_entropy",
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"sparse_pca_py",
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"box_tao_decomposition_py",
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"elastic_net_py",
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"hurst_exponent_py",
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"compute_risk_metrics_py",
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"estimate_half_life_py",
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"bootstrap_returns_py",
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# Time-series utilities
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"prepare_for_hmm_py",
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"rolling_hurst_exponent_py",
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"rolling_half_life_py",
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"return_statistics_py",
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"create_lagged_features_py",
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"rolling_correlation_py",
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"maths_toolkit",
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]
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