52 lines
1.8 KiB
Python
52 lines
1.8 KiB
Python
#!/usr/bin/env python3
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"""
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调试
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turn/flop阶段EMD在导出的数据与生成的数据间的差异
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"""
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import numpy as np
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from cross_validation import DataValidator
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validator = DataValidator()
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print("解析Turn样本...")
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turn_records = validator.parser.parse_turn_hist_with_cards(max_records=1)
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if turn_records:
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record = turn_records[0]
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player_cards = record.player_cards
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board_cards = record.board_cards
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src_hist = record.bins
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cur_hist = validator.generator.generate_turn_histogram(
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player_cards, board_cards, num_bins=len(src_hist)
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)
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src_hist_norm = src_hist / src_hist.sum() if src_hist.sum() > 0 else src_hist
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print(f"\n牌面: {[str(c) for c in player_cards]} + {[str(c) for c in board_cards]}")
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print(f"bin数量: {len(src_hist)} vs {len(cur_hist)}")
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print(f"原始直方图 - 和: {src_hist.sum():.3f}, 归一化后: {src_hist_norm.sum():.3f}")
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print(f"生成直方图 - 和: {sum(cur_hist):.3f}")
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print("\n前10个bin对比:")
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print("Bin 原始值 归一化 生成值")
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for i in range(min(10, len(src_hist))):
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print(f"{i:3d} {src_hist[i]:8.3f} {src_hist_norm[i]:8.3f} {cur_hist[i]:8.3f}")
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# 查看非零bin的分布
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src_nonzero = np.nonzero(src_hist_norm)[0]
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cur_nonzero = np.nonzero(cur_hist)[0]
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print(f"\n非零bins位置:")
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print(f"原始: {src_nonzero[:10]}...")
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print(f"生成: {cur_nonzero[:10]}...")
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# 计算分布的统计特征
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src_mean = np.average(range(len(src_hist_norm)), weights=src_hist_norm)
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cur_mean = np.average(range(len(cur_hist)), weights=cur_hist)
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print(f"\n分布特征:")
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print(f"原始分布重心: {src_mean:.2f}")
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print(f"生成分布重心: {cur_mean:.2f}")
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print(f"重心差异: {abs(src_mean - cur_mean):.2f}") |