47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
"""
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医疗数据因果推断分析示例（v2）
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本脚本演示如何使用 causal_agent 主包对医疗数据进行完整的因果推断分析。
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"""
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import os
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import sys
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# 将项目根目录加入路径
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project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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sys.path.insert(0, project_root)
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from causal_agent.agent import CausalInferenceAgent
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from causal_agent.core.config import AgentConfig
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def main():
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data_path = "examples/medical_v2/data.xlsx"
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# 如果数据不存在，自动生成示例数据
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if not os.path.exists(data_path):
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print("数据文件不存在，正在生成示例医疗数据...")
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from examples.medical_v2.data_generator import generate_medical_data
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df = generate_medical_data(n_samples=500, treatment_ratio=2 / 3, seed=42)
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df.to_excel(data_path, index=False)
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print(f"数据已保存到：{data_path}")
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# 配置 Agent（可选：自定义 LLM 参数、日志路径等）
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config = AgentConfig.from_env()
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config.log_path = "examples/medical_v2/log.md"
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# 创建 Agent 并执行分析
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agent = CausalInferenceAgent(config)
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result = agent.analyze(data_path)
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print("\n" + "=" * 60)
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print("示例运行完成！")
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print(f"分析 ID：{result['id']}")
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print(f"日志已保存到：{agent.logger.log_path}")
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print("=" * 60)
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if __name__ == "__main__":
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main()
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