riba2534
68b1c6b45d
- Add src/font_config.py: centralized font detection that auto-selects from Noto Sans SC > Hiragino Sans GB > STHeiti > Arial Unicode MS - Replace hardcoded font lists in all 18 modules with unified config - Add .gitignore for __pycache__, .DS_Store, venv, etc. - Regenerate all 70 charts with correct Chinese rendering Previously, 7 modules (fft, wavelet, acf, fractal, hurst, indicators, patterns) had no Chinese font config at all, causing □□□ rendering. The remaining 11 modules used a hardcoded fallback list that didn't prioritize the best available system font. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
65 lines
2.4 KiB
Plaintext
65 lines
2.4 KiB
Plaintext
======================================================================
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BTC/USDT 价格规律性分析 — 综合结论报告
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======================================================================
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"真正有规律" 判定标准（必须同时满足）：
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1. FDR校正后 p < 0.05
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2. 排列检验 p < 0.01（如适用）
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3. 测试集上效果方向一致且显著
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4. >80% bootstrap子样本中成立（如适用）
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5. Cohen's d > 0.2 或经济意义显著
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6. 有合理的经济/市场直觉解释
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----------------------------------------------------------------------
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模块 得分 强度 发现数
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----------------------------------------------------------------------
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fft 0.00 none 0
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fractal 0.00 none 0
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power_law 0.00 none 0
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wavelet 0.00 none 0
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acf 0.00 none 0
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returns 0.00 none 0
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volatility 0.00 none 0
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hurst 0.00 none 0
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volume_price 0.00 none 0
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time_series 0.00 none 0
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causality 0.00 none 0
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calendar 0.00 none 0
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halving 0.00 none 0
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indicators 0.00 none 0
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patterns 0.00 none 0
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clustering 0.00 none 0
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anomaly 0.00 none 0
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----------------------------------------------------------------------
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## 强证据规律（可重复、有经济意义）:
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（无）
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## 中等证据规律（统计显著但效果有限）:
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（无）
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## 弱证据/不显著:
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* fft
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* time_series
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* clustering
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* patterns
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* indicators
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* halving
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* calendar
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* causality
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* volume_price
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* fractal
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* hurst
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* volatility
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* returns
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* acf
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* wavelet
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* power_law
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* anomaly
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======================================================================
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注: 得分基于各模块自报告的统计检验结果。
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具体参数和图表请参见各子目录的输出。
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