update

app/ui/streamlit_app.py

@@ -1260,7 +1260,8 @@ def render_log_viewer() -> None:
 def render_backtest_review() -> None:
     """渲染回测执行、调参与结果复盘页面。"""
     st.header("回测与复盘")
-    cfg = get_config()
+    st.caption("1. 基于历史数据复盘当前策略；2. 借助强化学习/调参探索更优参数组合。")
+    app_cfg = get_config()
     default_start, default_end = _default_backtest_range(window_days=60)
     LOGGER.debug(
         "回测默认参数：start=%s end=%s universe=%s target=%s stop=%s hold_days=%s",
@@ -1273,13 +1274,15 @@ def render_backtest_review() -> None:
         extra=LOG_EXTRA,
     )
 
+    st.markdown("### 回测参数")
     col1, col2 = st.columns(2)
-    start_date = col1.date_input("开始日期", value=default_start)
+    start_date = col1.date_input("开始日期", value=default_start, key="bt_start_date")
-    end_date = col2.date_input("结束日期", value=default_end)
+    end_date = col2.date_input("结束日期", value=default_end, key="bt_end_date")
-    universe_text = st.text_input("股票列表（逗号分隔）", value="000001.SZ")
+    universe_text = st.text_input("股票列表（逗号分隔）", value="000001.SZ", key="bt_universe")
-    target = st.number_input("目标收益（例：0.035 表示 3.5%）", value=0.035, step=0.005, format="%.3f")
+    col_target, col_stop, col_hold = st.columns(3)
-    stop = st.number_input("止损收益（例：-0.015 表示 -1.5%）", value=-0.015, step=0.005, format="%.3f")
+    target = col_target.number_input("目标收益（例：0.035 表示 3.5%）", value=0.035, step=0.005, format="%.3f", key="bt_target")
-    hold_days = st.number_input("持有期（交易日）", value=10, step=1)
+    stop = col_stop.number_input("止损收益（例：-0.015 表示 -1.5%）", value=-0.015, step=0.005, format="%.3f", key="bt_stop")
+    hold_days = col_hold.number_input("持有期（交易日）", value=10, step=1, key="bt_hold_days")
     LOGGER.debug(
         "当前回测表单输入：start=%s end=%s universe_text=%s target=%.3f stop=%.3f hold_days=%s",
         start_date,
@@ -1291,7 +1294,11 @@ def render_backtest_review() -> None:
         extra=LOG_EXTRA,
     )
 
-    if st.button("运行回测"):
+    tab_backtest, tab_rl = st.tabs(["回测验证", "强化学习调参"])
+
+    with tab_backtest:
+        st.markdown("#### 回测执行")
+        if st.button("运行回测", key="bt_run_button"):
             LOGGER.info("用户点击运行回测按钮", extra=LOG_EXTRA)
             decision_log_container = st.container()
             status_box = st.status("准备执行回测...", expanded=True)
@@ -1346,7 +1353,7 @@ def render_backtest_review() -> None:
                     hold_days,
                     extra=LOG_EXTRA,
                 )
-            cfg = BtConfig(
+                backtest_cfg = BtConfig(
                     id="streamlit_demo",
                     name="Streamlit Demo Strategy",
                     start_date=start_date,
@@ -1358,7 +1365,7 @@ def render_backtest_review() -> None:
                         "hold_days": int(hold_days),
                     },
                 )
-            result = run_backtest(cfg, decision_callback=_decision_callback)
+                result = run_backtest(backtest_cfg, decision_callback=_decision_callback)
                 LOGGER.info(
                     "回测完成：nav_records=%s trades=%s",
                     len(result.nav_series),
@@ -1378,12 +1385,136 @@ def render_backtest_review() -> None:
                     }
                 )
                 _update_dashboard_sidebar(metrics)
-            st.json({"nav_records": result.nav_series, "trades": result.trades})
+                st.session_state["backtest_last_result"] = {"nav_records": result.nav_series, "trades": result.trades}
+                st.json(st.session_state["backtest_last_result"])
             except Exception as exc:  # noqa: BLE001
                 LOGGER.exception("回测执行失败", extra=LOG_EXTRA)
                 status_box.update(label="回测执行失败", state="error")
                 st.error(f"回测执行失败：{exc}")
 
+        last_result = st.session_state.get("backtest_last_result")
+        if last_result:
+            st.markdown("#### 最近回测输出")
+            st.json(last_result)
+
+        st.divider()
+        # ADD: Comparison view for multiple backtest configurations
+        with st.expander("历史回测结果对比", expanded=False):
+            st.caption("从历史回测配置中选择多个进行净值曲线与指标对比。")
+            normalize_to_one = st.checkbox("归一化到 1 起点", value=True, key="bt_cmp_normalize")
+            use_log_y = st.checkbox("对数坐标", value=False, key="bt_cmp_log_y")
+            metric_options = ["总收益", "最大回撤", "交易数", "平均换手", "风险事件"]
+            selected_metrics = st.multiselect("显示指标列", metric_options, default=metric_options, key="bt_cmp_metrics")
+            try:
+                with db_session(read_only=True) as conn:
+                    cfg_rows = conn.execute(
+                        "SELECT id, name FROM bt_config ORDER BY rowid DESC LIMIT 50"
+                    ).fetchall()
+            except Exception:  # noqa: BLE001
+                LOGGER.exception("读取 bt_config 失败", extra=LOG_EXTRA)
+                cfg_rows = []
+            cfg_options = [f"{row['id']} | {row['name']}" for row in cfg_rows]
+            selected_labels = st.multiselect("选择配置", cfg_options, default=cfg_options[:2], key="bt_cmp_configs")
+            selected_ids = [label.split(" | ")[0].strip() for label in selected_labels]
+            nav_df = pd.DataFrame()
+            rpt_df = pd.DataFrame()
+            if selected_ids:
+                try:
+                    with db_session(read_only=True) as conn:
+                        nav_df = pd.read_sql_query(
+                            "SELECT cfg_id, trade_date, nav FROM bt_nav WHERE cfg_id IN (%s)" % (",".join(["?"]*len(selected_ids))),
+                            conn,
+                            params=tuple(selected_ids),
+                        )
+                        rpt_df = pd.read_sql_query(
+                            "SELECT cfg_id, summary FROM bt_report WHERE cfg_id IN (%s)" % (",".join(["?"]*len(selected_ids))),
+                            conn,
+                            params=tuple(selected_ids),
+                        )
+                except Exception:  # noqa: BLE001
+                    LOGGER.exception("读取回测结果失败", extra=LOG_EXTRA)
+                    st.error("读取回测结果失败")
+                    nav_df = pd.DataFrame()
+                    rpt_df = pd.DataFrame()
+                if not nav_df.empty:
+                    try:
+                        nav_df["trade_date"] = pd.to_datetime(nav_df["trade_date"], errors="coerce")
+                        # ADD: date window filter
+                        overall_min = pd.to_datetime(nav_df["trade_date"].min()).date()
+                        overall_max = pd.to_datetime(nav_df["trade_date"].max()).date()
+                        col_d1, col_d2 = st.columns(2)
+                        start_filter = col_d1.date_input("起始日期", value=overall_min, key="bt_cmp_start")
+                        end_filter = col_d2.date_input("结束日期", value=overall_max, key="bt_cmp_end")
+                        if start_filter > end_filter:
+                            start_filter, end_filter = end_filter, start_filter
+                        mask = (nav_df["trade_date"].dt.date >= start_filter) & (nav_df["trade_date"].dt.date <= end_filter)
+                        nav_df = nav_df.loc[mask]
+                        pivot = nav_df.pivot_table(index="trade_date", columns="cfg_id", values="nav")
+                        if normalize_to_one:
+                            pivot = pivot.apply(lambda s: s / s.dropna().iloc[0] if s.dropna().size else s)
+                        import plotly.graph_objects as go
+                        fig = go.Figure()
+                        for col in pivot.columns:
+                            fig.add_trace(go.Scatter(x=pivot.index, y=pivot[col], mode="lines", name=str(col)))
+                        fig.update_layout(height=300, margin=dict(l=10, r=10, t=30, b=10))
+                        if use_log_y:
+                            fig.update_yaxes(type="log")
+                        st.plotly_chart(fig, width='stretch')
+                        # ADD: export pivot
+                        try:
+                            csv_buf = pivot.reset_index()
+                            csv_buf.columns = ["trade_date"] + [str(c) for c in pivot.columns]
+                            st.download_button(
+                                "下载曲线(CSV)",
+                                data=csv_buf.to_csv(index=False),
+                                file_name="bt_nav_compare.csv",
+                                mime="text/csv",
+                                key="dl_nav_compare",
+                            )
+                        except Exception:
+                            pass
+                    except Exception:  # noqa: BLE001
+                        LOGGER.debug("绘制对比曲线失败", extra=LOG_EXTRA)
+                if not rpt_df.empty:
+                    try:
+                        metrics_rows: List[Dict[str, object]] = []
+                        for _, row in rpt_df.iterrows():
+                            cfg_id = row["cfg_id"]
+                            try:
+                                summary = json.loads(row["summary"]) if isinstance(row["summary"], str) else (row["summary"] or {})
+                            except json.JSONDecodeError:
+                                summary = {}
+                            record = {
+                                "cfg_id": cfg_id,
+                                "总收益": summary.get("total_return"),
+                                "最大回撤": summary.get("max_drawdown"),
+                                "交易数": summary.get("trade_count"),
+                                "平均换手": summary.get("avg_turnover"),
+                                "风险事件": summary.get("risk_events"),
+                            }
+                            metrics_rows.append({k: v for k, v in record.items() if (k == "cfg_id" or k in selected_metrics)})
+                        if metrics_rows:
+                            dfm = pd.DataFrame(metrics_rows)
+                            st.dataframe(dfm, hide_index=True, width='stretch')
+                            try:
+                                st.download_button(
+                                    "下载指标(CSV)",
+                                    data=dfm.to_csv(index=False),
+                                    file_name="bt_metrics_compare.csv",
+                                    mime="text/csv",
+                                    key="dl_metrics_compare",
+                                )
+                            except Exception:
+                                pass
+                    except Exception:  # noqa: BLE001
+                        LOGGER.debug("渲染指标表失败", extra=LOG_EXTRA)
+            else:
+                st.info("请选择至少一个配置进行对比。")
+
+
+
+    with tab_rl:
+        st.caption("使用 DecisionEnv 对代理权重进行强化学习调参，支持单次与批量实验。")
         with st.expander("离线调参实验 (DecisionEnv)", expanded=False):
             st.caption(
                 "使用 DecisionEnv 对代理权重做离线调参。请选择需要优化的代理并设定权重范围，"
@@ -1881,119 +2012,6 @@ def render_backtest_review() -> None:
                         st.session_state.pop("decision_env_batch_select", None)
                         st.success("已清除批量调参结果缓存。")
 
-    # ADD: Comparison view for multiple backtest configurations
-    with st.expander("回测结果对比", expanded=False):
-        st.caption("从历史回测配置中选择多个进行净值曲线与指标对比。")
-        normalize_to_one = st.checkbox("归一化到 1 起点", value=True)
-        use_log_y = st.checkbox("对数坐标", value=False)
-        metric_options = ["总收益", "最大回撤", "交易数", "平均换手", "风险事件"]
-        selected_metrics = st.multiselect("显示指标列", metric_options, default=metric_options)
-        try:
-            with db_session(read_only=True) as conn:
-                cfg_rows = conn.execute(
-                    "SELECT id, name FROM bt_config ORDER BY rowid DESC LIMIT 50"
-                ).fetchall()
-        except Exception:  # noqa: BLE001
-            LOGGER.exception("读取 bt_config 失败", extra=LOG_EXTRA)
-            cfg_rows = []
-        cfg_options = [f"{row['id']} | {row['name']}" for row in cfg_rows]
-        selected_labels = st.multiselect("选择配置", cfg_options, default=cfg_options[:2])
-        selected_ids = [label.split(" | ")[0].strip() for label in selected_labels]
-        nav_df = pd.DataFrame()
-        rpt_df = pd.DataFrame()
-        if selected_ids:
-            try:
-                with db_session(read_only=True) as conn:
-                    nav_df = pd.read_sql_query(
-                        "SELECT cfg_id, trade_date, nav FROM bt_nav WHERE cfg_id IN (%s)" % (",".join(["?"]*len(selected_ids))),
-                        conn,
-                        params=tuple(selected_ids),
-                    )
-                    rpt_df = pd.read_sql_query(
-                        "SELECT cfg_id, summary FROM bt_report WHERE cfg_id IN (%s)" % (",".join(["?"]*len(selected_ids))),
-                        conn,
-                        params=tuple(selected_ids),
-                    )
-            except Exception:  # noqa: BLE001
-                LOGGER.exception("读取回测结果失败", extra=LOG_EXTRA)
-                st.error("读取回测结果失败")
-                nav_df = pd.DataFrame()
-                rpt_df = pd.DataFrame()
-            if not nav_df.empty:
-                try:
-                    nav_df["trade_date"] = pd.to_datetime(nav_df["trade_date"], errors="coerce")
-                    # ADD: date window filter
-                    overall_min = pd.to_datetime(nav_df["trade_date"].min()).date()
-                    overall_max = pd.to_datetime(nav_df["trade_date"].max()).date()
-                    col_d1, col_d2 = st.columns(2)
-                    start_filter = col_d1.date_input("起始日期", value=overall_min)
-                    end_filter = col_d2.date_input("结束日期", value=overall_max)
-                    if start_filter > end_filter:
-                        start_filter, end_filter = end_filter, start_filter
-                    mask = (nav_df["trade_date"].dt.date >= start_filter) & (nav_df["trade_date"].dt.date <= end_filter)
-                    nav_df = nav_df.loc[mask]
-                    pivot = nav_df.pivot_table(index="trade_date", columns="cfg_id", values="nav")
-                    if normalize_to_one:
-                        pivot = pivot.apply(lambda s: s / s.dropna().iloc[0] if s.dropna().size else s)
-                    import plotly.graph_objects as go
-                    fig = go.Figure()
-                    for col in pivot.columns:
-                        fig.add_trace(go.Scatter(x=pivot.index, y=pivot[col], mode="lines", name=str(col)))
-                    fig.update_layout(height=300, margin=dict(l=10, r=10, t=30, b=10))
-                    if use_log_y:
-                        fig.update_yaxes(type="log")
-                    st.plotly_chart(fig, width='stretch')
-                    # ADD: export pivot
-                    try:
-                        csv_buf = pivot.reset_index()
-                        csv_buf.columns = ["trade_date"] + [str(c) for c in pivot.columns]
-                        st.download_button(
-                            "下载曲线(CSV)",
-                            data=csv_buf.to_csv(index=False),
-                            file_name="bt_nav_compare.csv",
-                            mime="text/csv",
-                            key="dl_nav_compare",
-                        )
-                    except Exception:
-                        pass
-                except Exception:  # noqa: BLE001
-                    LOGGER.debug("绘制对比曲线失败", extra=LOG_EXTRA)
-            if not rpt_df.empty:
-                try:
-                    metrics_rows: List[Dict[str, object]] = []
-                    for _, row in rpt_df.iterrows():
-                        cfg_id = row["cfg_id"]
-                        try:
-                            summary = json.loads(row["summary"]) if isinstance(row["summary"], str) else (row["summary"] or {})
-                        except json.JSONDecodeError:
-                            summary = {}
-                        record = {
-                            "cfg_id": cfg_id,
-                            "总收益": summary.get("total_return"),
-                            "最大回撤": summary.get("max_drawdown"),
-                            "交易数": summary.get("trade_count"),
-                            "平均换手": summary.get("avg_turnover"),
-                            "风险事件": summary.get("risk_events"),
-                        }
-                        metrics_rows.append({k: v for k, v in record.items() if (k == "cfg_id" or k in selected_metrics)})
-                    if metrics_rows:
-                        dfm = pd.DataFrame(metrics_rows)
-                        st.dataframe(dfm, hide_index=True, width='stretch')
-                        try:
-                            st.download_button(
-                                "下载指标(CSV)",
-                                data=dfm.to_csv(index=False),
-                                file_name="bt_metrics_compare.csv",
-                                mime="text/csv",
-                                key="dl_metrics_compare",
-                            )
-                        except Exception:
-                            pass
-                except Exception:  # noqa: BLE001
-                    LOGGER.debug("渲染指标表失败", extra=LOG_EXTRA)
-        else:
-            st.info("请选择至少一个配置进行对比。")
-
     
 def render_config_overview() -> None:
     """Render a concise overview of persisted configuration values."""