modify: cleanup project structure and docs

ui_sections/model_eval.py

@@ -0,0 +1,32 @@
+from __future__ import annotations
+
+import pandas as pd
+import streamlit as st
+
+from services.metrics import evaluate_models
+
+
+def render_model_eval(base: pd.DataFrame):
+    st.subheader("模型预测效果对比")
+    with st.form(key="model_eval_form"):
+        horizon_sel = st.slider("评估窗口（天）", 7, 60, 30, step=1)
+        submit_eval = st.form_submit_button("应用评估参数")
+
+    if not submit_eval:
+        st.info("请设置评估窗口并点击“应用评估参数”按钮。")
+        return
+
+    try:
+        df_metrics = evaluate_models(base['accident_count'], horizon=int(horizon_sel))
+        st.dataframe(df_metrics, use_container_width=True)
+        best_model = df_metrics['RMSE'].idxmin()
+        st.success(f"过去 {int(horizon_sel)} 天中，RMSE 最低的模型是：**{best_model}**")
+        st.download_button(
+            "下载评估结果 CSV",
+            data=df_metrics.to_csv().encode('utf-8-sig'),
+            file_name="model_evaluation.csv",
+            mime="text/csv",
+        )
+    except ValueError as err:
+        st.warning(str(err))
+