51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
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from __future__ import annotations
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import os
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import pandas as pd
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import streamlit as st
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from services.strategy import generate_output_and_recommendations
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def render_strategy_eval(base: pd.DataFrame, all_strategy_types: list[str], region_sel: str):
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st.info(f"📌 检测到的策略类型：{', '.join(all_strategy_types) or '（数据中没有策略）'}")
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if not all_strategy_types:
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st.warning("数据中没有检测到策略。")
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return
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with st.form(key="strategy_eval_form"):
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horizon_eval = st.slider("评估窗口（天）", 7, 60, 14, step=1)
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submit_strat_eval = st.form_submit_button("应用评估参数")
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if not submit_strat_eval:
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st.info("请设置评估窗口并点击“应用评估参数”按钮。")
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return
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results, recommendation = generate_output_and_recommendations(
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base,
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all_strategy_types,
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region=region_sel if region_sel != '全市' else '全市',
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horizon=horizon_eval,
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)
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if not results:
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st.warning("⚠️ 未能完成策略评估。请尝试缩短评估窗口或扩大日期范围。")
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return
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st.subheader("各策略指标")
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df_res = pd.DataFrame(results).T
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st.dataframe(df_res, use_container_width=True)
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st.success(f"⭐ 推荐：{recommendation}")
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st.download_button(
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"下载策略评估 CSV",
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data=df_res.to_csv().encode('utf-8-sig'),
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file_name="strategy_evaluation_results.csv",
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mime="text/csv",
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)
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if os.path.exists('recommendation.txt'):
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with open('recommendation.txt','r',encoding='utf-8') as f:
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st.download_button("下载推荐文本", data=f.read().encode('utf-8'), file_name="recommendation.txt")
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