feat: add render-algo subcommand for single-algorithm GT+detection PNG

tests/test_render_algo.py

@@ -0,0 +1,37 @@
+"""render_algo 单元测试。"""
+
+import json
+import tempfile
+from pathlib import Path
+
+from ts_anomaly_td.visualize import render_algo
+
+
+def _make_ts_vals_labels(n=200):
+    """生成测试用时间序列。"""
+    ts = [i * 3600_000 for i in range(n)]  # 每小时
+    vals = [float(i % 20) for i in range(n)]
+    labels = [1 if 50 <= i <= 60 else 0 for i in range(n)]
+    return ts, vals, labels
+
+
+def test_render_algo_basic():
+    """render_algo 应生成有效 PNG。"""
+    ts, vals, labels = _make_ts_vals_labels()
+    windows = [[ts[50], ts[60]]]
+
+    with tempfile.TemporaryDirectory() as tmpdir:
+        out = Path(tmpdir) / "test_algo.png"
+        result = render_algo(ts, vals, labels, windows, "ksigma", str(out), title="test")
+        assert Path(result).exists()
+        assert Path(result).stat().st_size > 5000
+
+
+def test_render_algo_empty_windows():
+    """空检测窗口应正常渲染。"""
+    ts, vals, labels = _make_ts_vals_labels(50)
+
+    with tempfile.TemporaryDirectory() as tmpdir:
+        out = Path(tmpdir) / "empty.png"
+        result = render_algo(ts, vals, labels, [], "iqr", str(out))
+        assert Path(result).exists()

ts_anomaly_td/cli.py

@@ -209,9 +209,38 @@ def build_parser() -> argparse.ArgumentParser:
     p_watch.add_argument("--window-sec", type=int, default=30, help="检测间隔秒数 (default: 30)")
     p_watch.add_argument("--url", default="ws://root:taosdata@localhost:6041", help="TDengine WebSocket URL")
 
+    # render-algo
+    p_ra = sub.add_parser("render-algo", help="单算法 GT+检测渲染 PNG")
+    p_ra.add_argument("--gt-csv", required=True, help="GT CSV 文件路径")
+    p_ra.add_argument("--det-json", required=True, help="detect-batch --json 输出的 JSON 文件")
+    p_ra.add_argument("--algo", required=True, help="算法名称")
+    p_ra.add_argument("--output", required=True, help="PNG 输出路径")
+    p_ra.add_argument("--value-col", default="value", help="数值列名 (default: value)")
+    p_ra.add_argument("--title", default="", help="图表标题")
+
     return parser
 
 
+def cmd_render_algo(args):
+    """render-algo 子命令：单算法 GT+检测渲染 PNG。"""
+    logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
+
+    import json
+    from ts_anomaly_td.io_csv import read_csv
+    from ts_anomaly_td.visualize import render_algo
+
+    ts, vals, labels = read_csv(args.gt_csv, value_col=args.value_col)
+
+    with open(args.det_json) as f:
+        det_data = json.load(f)
+
+    # det_json 格式: {"algo": "ksigma", "windows": [[start, end], ...], "error": null}
+    windows = det_data.get("windows", [])
+
+    title = args.title or f"{Path(args.gt_csv).stem} / {args.algo}"
+    render_algo(ts, vals, labels, windows, args.algo, args.output, title=title)
+
+
 def main():
     parser = build_parser()
     args = parser.parse_args()
@@ -223,6 +252,7 @@ def main():
         "e2e": cmd_e2e,
         "visualize": cmd_visualize,
         "watch": cmd_watch,
+        "render-algo": cmd_render_algo,
     }
 
     fn = dispatch.get(args.command)

ts_anomaly_td/visualize.py

@@ -153,3 +153,162 @@ def render_contrast(
     plt.close(fig)
     logger.info("chart saved: %s", output_path)
     return output_path
+
+
+def render_algo(
+    timestamps: list[int],
+    values: list[float],
+    gt_labels: list[int],
+    det_windows: list[list[int]],
+    algo: str,
+    output_path: str,
+    title: str = "",
+) -> str:
+    """单算法渲染：GT（红）+ 该算法检测窗口（算法色）→ PNG。
+
+    Args:
+        timestamps: 毫秒时间戳列表
+        values: 数值列表
+        gt_labels: GT 标签（0/1）
+        det_windows: [[start_ts, end_ts], ...] 该算法检测窗口
+        algo: 算法名称
+        output_path: PNG 输出路径
+        title: 图表标题
+
+    Returns:
+        output_path
+    """
+    font_name = _find_cjk_font()
+    plt.rcParams["font.family"] = font_name
+    plt.rcParams["font.size"] = 9
+
+    fig, ax = plt.subplots(1, 1, figsize=(14, 5))
+
+    t0 = timestamps[0]
+    hours = [(t - t0) / 3_600_000 for t in timestamps]
+
+    # 原始序列
+    ax.plot(hours, values, color="black", linewidth=0.6, alpha=0.8)
+
+    # GT 红色 axvspan
+    in_anomaly = False
+    anom_start = None
+    gt_windows = []
+    for i, label in enumerate(gt_labels):
+        if label == 1 and not in_anomaly:
+            in_anomaly = True
+            anom_start = hours[i]
+        elif label == 0 and in_anomaly:
+            in_anomaly = False
+            ax.axvspan(anom_start, hours[i], alpha=0.15, color="red", label="GT" if len(gt_windows) == 0 else None)
+            gt_windows.append((anom_start, hours[i]))
+    if in_anomaly:
+        ax.axvspan(anom_start, hours[-1], alpha=0.15, color="red", label="GT" if len(gt_windows) == 0 else None)
+        gt_windows.append((anom_start, hours[-1]))
+
+    # 该算法检测窗口
+    color = ALGO_COLORS.get(algo, "#888888")
+    det_hours = []
+    for i, (wstart, wend) in enumerate(det_windows):
+        ws_h = (wstart - t0) / 3_600_000
+        we_h = (wend - t0) / 3_600_000
+        ax.axvspan(ws_h, we_h, alpha=0.2, color=color, label=algo if i == 0 else None)
+        det_hours.append((ws_h, we_h))
+
+    # IoU + 统计
+    iou = _compute_iou(gt_windows, det_hours)
+    stats_text = f"GT: {len(gt_windows)}  Det: {len(det_windows)}  IoU: {iou:.3f}"
+    ax.set_title(f"{title} — {stats_text}" if title else stats_text)
+    ax.set_ylabel("Value")
+    ax.set_xlabel("Time (hours)")
+
+    if gt_windows or det_windows:
+        ax.legend(loc="upper right", fontsize=7)
+
+    plt.tight_layout()
+    Path(output_path).parent.mkdir(parents=True, exist_ok=True)
+    fig.savefig(output_path, dpi=150, bbox_inches="tight")
+    plt.close(fig)
+    logger.info("render_algo saved: %s", output_path)
+    return output_path
+
+
+def montage_pngs(
+    image_paths: list[str],
+    output_path: str,
+    cols: int = 2,
+    title: str = "",
+) -> str:
+    """将多张等宽 PNG 按网格拼成一张对比图。
+
+    Args:
+        image_paths: PNG 文件路径列表
+        output_path: 拼图输出路径
+        cols: 列数
+        title: 总标题
+
+    Returns:
+        output_path
+    """
+    from PIL import Image, ImageDraw, ImageFont
+
+    if not image_paths:
+        raise ValueError("image_paths 为空")
+
+    images = []
+    for p in image_paths:
+        img = Image.open(p)
+        images.append(img)
+
+    # 统一宽度为第一张图的宽度
+    target_w = images[0].width
+    resized = []
+    for img in images:
+        if img.width != target_w:
+            ratio = target_w / img.width
+            new_h = int(img.height * ratio)
+            img = img.resize((target_w, new_h), Image.LANCZOS)
+        resized.append(img)
+
+    n = len(resized)
+    rows_count = (n + cols - 1) // cols
+
+    # 计算每行高度
+    row_heights = []
+    for r in range(rows_count):
+        max_h = max(resized[r * cols + c].height for c in range(cols) if r * cols + c < n)
+        row_heights.append(max_h)
+
+    padding = 10
+    title_h = 40 if title else 0
+    total_w = target_w * cols + padding * (cols + 1)
+    total_h = sum(row_heights) + padding * (rows_count + 1) + title_h
+
+    canvas = Image.new("RGB", (total_w, total_h), "white")
+    draw = ImageDraw.Draw(canvas)
+
+    if title:
+        try:
+            font = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf", 24)
+        except Exception:
+            font = ImageFont.load_default()
+        draw.text((total_w // 2, 15), title, fill="black", anchor="mm", font=font)
+
+    y_offset = title_h + padding
+    for r in range(rows_count):
+        x_offset = padding
+        for c in range(cols):
+            idx = r * cols + c
+            if idx >= n:
+                break
+            img = resized[idx]
+            # 垂直居中
+            y_pad = (row_heights[r] - img.height) // 2
+            canvas.paste(img, (x_offset, y_offset + y_pad))
+            x_offset += target_w + padding
+        y_offset += row_heights[r] + padding
+
+    Path(output_path).parent.mkdir(parents=True, exist_ok=True)
+    canvas.save(output_path)
+    logger.info("montage saved: %s (%d images, %dx%d)", output_path, n, cols, rows_count)
+    return output_path