fix: drop NaN timestamps, use facecolor to suppress matplotlib warning

ts_anomaly_td/io_csv.py

@@ -41,6 +41,15 @@ def read_csv(path: str | Path, value_col: str = "value") -> tuple[list[int], lis
 
         fixed = raw_strs.apply(_fix_hour60)
         timestamps.loc[na_mask] = pd.to_datetime(fixed, errors="coerce")
+    # 丢弃时间戳仍为 NaN 的行（coerce 后无法恢复的异常时间戳）
+    valid_mask = timestamps.notna()
+    if not valid_mask.all():
+        n_drop = (~valid_mask).sum()
+        import logging
+        logging.getLogger(__name__).warning("dropping %d rows with invalid timestamps", n_drop)
+        timestamps = timestamps[valid_mask].reset_index(drop=True)
+        df = df[valid_mask].reset_index(drop=True)
+
     timestamps_ms = (timestamps.astype("int64") // 10**6).tolist()
 
     values = df[value_col].astype(float).tolist()

ts_anomaly_td/visualize.py

@@ -291,7 +291,7 @@ def render_column(
     ax.plot(hours, values, color="#333333", linewidth=0.8, alpha=0.9)
     if has_gt:
         for start_h, end_h in gt_windows_h:
-            ax.axvspan(start_h, end_h, alpha=0.35, color="#FF4444",
+            ax.axvspan(start_h, end_h, alpha=0.35, facecolor="#FF4444",
                        edgecolor="#CC0000", linewidth=1.5)
         # 异常点散点标记
         anom_hours = [hours[i] for i, l in enumerate(gt_labels) if l == 1]
@@ -326,7 +326,7 @@ def render_column(
         for wstart, wend in windows:
             ws_h = (wstart - t0) / 3_600_000
             we_h = (wend - t0) / 3_600_000
-            ax.axvspan(ws_h, we_h, alpha=0.4, color=color,
+            ax.axvspan(ws_h, we_h, alpha=0.4, facecolor=color,
                        edgecolor=color, linewidth=1.5)
             det_hours_list.append((ws_h, we_h))