添加新的判断依据

data_provider/main.py

@@ -29,10 +29,10 @@ TIMEFRAME_TO_MS: Dict[str, int] = {
     "1w": 604_800_000,
 }
 DERIVED_TIMEFRAME_PLAN: Dict[str, List[str]] = {
-    "1m": ["2m", "3m", "4m", "5m", "10m", "15m", "20m", "25m", "30m"],
-    "1h": ["2h", "3h", "4h", "6h", "8h", "12h", "16h"],
+    "1m": ["2m", "3m", "4m", "5m", "10m", "15m", "20m", "25m", "30m", "45m"],
+    "1h": ["2h", "3h", "4h", "6h", "8h", "12h", "16h", "20h"],
     "1d": ["2d", "3d", "4d", "5d", "6d"],
-    "1w": ["2w"],
+    "1w": ["2w", "3w"],
 }
 CSV_FIELDNAMES = ["timestamp", "datetime", "open", "high", "low", "close", "volume"]
 DEFAULT_LIMIT = 500
@@ -583,14 +583,14 @@ class DataProvider:
             resampled_df = resampled.copy()
             if "date" in resampled_df.columns:
                 dates = pd.to_datetime(resampled_df["date"], utc=True, errors="coerce")
-                resampled_df["timestamp"] = (dates.view("int64") // 1_000_000).astype("int64")
+                resampled_df["timestamp"] = (dates.astype("int64", copy=False) // 1_000_000).astype("int64")
             elif isinstance(resampled_df.index, pd.DatetimeIndex):
                 idx = resampled_df.index
                 if idx.tz is None:
                     idx = idx.tz_localize("UTC")
                 else:
                     idx = idx.tz_convert("UTC")
-                resampled_df["timestamp"] = (idx.view("int64") // 1_000_000).astype("int64")
+                resampled_df["timestamp"] = (idx.astype("int64", copy=False) // 1_000_000).astype("int64")
             else:
                 raise HTTPException(status_code=500, detail=f"聚合结果缺少 timestamp 列 ({timeframe})")
         resampled_df = resampled_df.dropna(subset=["timestamp"]).sort_values("timestamp")