feat: add visualize + e2e orchestrator + run_e2e.sh

ts_anomaly_td/visualize.py

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+"""可视化模块：双栏对比图（GT 上、TDengine 检测下）。"""
+
+import logging
+from pathlib import Path
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+import matplotlib.font_manager as fm
+
+logger = logging.getLogger(__name__)
+
+ALGO_COLORS = {
+    "ksigma": "#1f77b4",
+    "iqr": "#2ca02c",
+    "grubbs": "#9467bd",
+    "shesd": "#ff7f0e",
+    "lof": "#17becf",
+    "sample_ad_model": "#e377c2",
+}
+
+
+def _find_cjk_font():
+    """查找可用 CJK 字体。"""
+    candidates = ["Noto Serif CJK SC", "Noto Sans CJK SC", "WenQuanYi Micro Hei",
+                  "DejaVu Sans", "sans-serif"]
+    available = {f.name for f in fm.fontManager.ttflist}
+    for name in candidates:
+        if name in available:
+            return name
+    return "sans-serif"
+
+
+def _compute_iou(gt_windows, det_windows):
+    """计算 GT 与检测窗口的 IoU。
+
+    窗口格式: [(start_ts, end_ts), ...]
+    IoU = 交集时长 / 并集时长
+    """
+    if not gt_windows or not det_windows:
+        return 0.0
+
+    def overlap(a_start, a_end, b_start, b_end):
+        o_start = max(a_start, b_start)
+        o_end = min(a_end, b_end)
+        return max(0, o_end - o_start)
+
+    intersection = 0.0
+    union = 0.0
+
+    for gw in gt_windows:
+        union += gw[1] - gw[0]
+        for dw in det_windows:
+            intersection += overlap(gw[0], gw[1], dw[0], dw[1])
+
+    for dw in det_windows:
+        union += dw[1] - dw[0]
+
+    if union == 0:
+        return 0.0
+    return min(intersection / union, 1.0)
+
+
+def render_contrast(
+    timestamps: list[int],
+    values: list[float],
+    gt_labels: list[int],
+    detection_results: dict,
+    output_path: str,
+    title: str = "",
+) -> str:
+    """渲染双栏对比图。
+
+    Args:
+        timestamps: 毫秒时间戳列表
+        values: 数值列表
+        gt_labels: GT 标签（0/1）
+        detection_results: {algo: {"windows": [...]}} 来自 detect_all_algos
+        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_gt, ax_det) = plt.subplots(2, 1, sharex=True, figsize=(14, 8))
+
+    t0 = timestamps[0]
+    hours = [(t - t0) / 3_600_000 for t in timestamps]
+
+    ax_gt.plot(hours, values, color="black", linewidth=0.6, alpha=0.8)
+    ax_gt.set_ylabel("Value")
+    ax_gt.set_title(f"Ground Truth — {title}" if title else "Ground Truth")
+
+    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_gt.axvspan(anom_start, hours[i], alpha=0.25, color="red")
+            gt_windows.append((anom_start, hours[i]))
+
+    if in_anomaly:
+        ax_gt.axvspan(anom_start, hours[-1], alpha=0.25, color="red")
+        gt_windows.append((anom_start, hours[-1]))
+
+    ax_det.plot(hours, values, color="black", linewidth=0.6, alpha=0.3)
+    ax_det.set_ylabel("Value")
+    ax_det.set_xlabel("Time (hours)")
+
+    all_det_windows = []
+    for algo, result in detection_results.items():
+        if result.get("error"):
+            continue
+        color = ALGO_COLORS.get(algo, "#888888")
+        for wstart, wend in result.get("windows", []):
+            wstart_h = (wstart - timestamps[0]) / 3_600_000 if wstart > timestamps[0] else 0
+            wend_h = (wend - timestamps[0]) / 3_600_000
+            ax_det.axvspan(wstart_h, wend_h, alpha=0.2, color=color)
+            all_det_windows.append((wstart_h, wend_h))
+
+    legend_handles = []
+    for algo in detection_results:
+        if algo in ALGO_COLORS and not detection_results[algo].get("error"):
+            from matplotlib.patches import Patch
+            legend_handles.append(Patch(color=ALGO_COLORS[algo], alpha=0.5, label=algo))
+    if legend_handles:
+        ax_det.legend(handles=legend_handles, loc="upper right", fontsize=7)
+
+    ax_det.set_title(f"TDengine Detection — {title}" if title else "TDengine Detection (6 algos)")
+
+    iou = _compute_iou(gt_windows, all_det_windows)
+    total_det = len(all_det_windows)
+    stats_text = f"GT windows: {len(gt_windows)}\nDetected: {total_det}\nIoU: {iou:.3f}"
+    ax_det.text(
+        0.98, 0.97, stats_text,
+        transform=ax_det.transAxes,
+        verticalalignment="top",
+        horizontalalignment="right",
+        bbox=dict(boxstyle="round", facecolor="white", alpha=0.8),
+        fontsize=8,
+    )
+
+    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("chart saved: %s", output_path)
+    return output_path