feat: GUI 面板专题图生成支持多线程并发克里金

- step11_map_panel.run() 串行 for 循环改为 ThreadPoolExecutor 并发
- 默认 2 线程并行，通过过滤已存在文件跳过重复生成
- 支持取消信号：_done Event 通知 worker 线程提前退出
- 线程安全：_lock 保护共享计数器，Qt 信号从 QThread 安全 emit
- 修复 Tuple 类型导入缺失

src/gui/panels/step11_map_panel.py

@@ -7,7 +7,7 @@ Step10 面板 - 专题图生成
 import os
 import traceback
 from pathlib import Path
-from typing import List, Optional
+from typing import List, Optional, Tuple
 
 from src.gui.panels._step_path_resolver import resolve_subdir, get_step_output_path, scan_work_dir_for_input
 
@@ -100,40 +100,104 @@ class Step11MapBatchThread(QThread):
                         f"[警告] 共享上下文失败: {e}，回退逐个处理", "warning"
                     )
 
-            # ── 批量处理 ──
+            # ── 批量处理（多线程并发克里金插值）──
-            for i, csv_p in enumerate(self.csv_paths):
+            # 克里金内部 numpy/scipy 运算释放 GIL，ThreadPoolExecutor 真并行
-                if self._cancelled:
+            import concurrent.futures
-                    self.log_message.emit("专题图批量任务已被用户取消", "warning")
+            import threading
-                    break
-                self.progress.emit(i + 1, n)
-                self.log_message.emit(f"专题图 [{i + 1}/{n}] {csv_p}", "info")
 
+            _all_csvs = list(self.csv_paths)  # 快照副本
+            # 过滤已存在的文件
+            _pending: List[Tuple[str, str]] = []  # [(csv_path, output_file), ...]
+            _skipped = 0
+            for csv_p in _all_csvs:
                 stem = Path(csv_p).stem
-                output_file = (
+                out_f = (
                     str(Path(self.output_dir_optional) / f'{stem}_distribution.png')
                     if self.output_dir_optional
                     else None
                 )
-                # 已存在则跳过（兼容 tif 重定向后的文件名）
+                if out_f and (
-                if output_file and (
+                    Path(out_f).exists()
-                    Path(output_file).exists()
+                    or Path(out_f).with_suffix('.tif').exists()
-                    or Path(output_file).with_suffix('.tif').exists()
                 ):
-                    self.log_message.emit(f"  → 跳过（已存在）", "info")
+                    _skipped += 1
-                    continue
+                    self.log_message.emit(f"  → 跳过（已存在）: {stem}", "info")
+                else:
+                    _pending.append((csv_p, out_f))
 
-                try:
+            if _skipped > 0:
-                    mapper.process_data(
+                self.log_message.emit(
-                        csv_file=csv_p,
+                    f"[跳过] {_skipped} 个已存在，待处理 {len(_pending)} 个", "info")
-                        shp_file=boundary_shp,
+
-                        output_file=output_file,
+            _n_pending = len(_pending)
-                        resolution=resolution,
+            if _n_pending == 0:
-                        output_format='tif',
+                self.log_message.emit("所有专题图均已存在，无需重新生成", "info")
-                        shared_context=shared_ctx,
+                self.finished_ok.emit(n)
-                    )
+                return
-                except Exception as e:
+
-                    self.log_message.emit(f"  → 失败: {e}", "error")
+            _max_workers = max(1, min(2, _n_pending, os.cpu_count() or 4))
-                    continue
+            _completed = 0
+            _lock = threading.Lock()
+            _done = threading.Event()  # 取消信号
+
+            def _process_one(csv_path: str, output_file: str):
+                """单个 CSV → 分布图（在 ThreadPoolExecutor 线程中执行）"""
+                if _done.is_set():
+                    return None, csv_path
+                mapper.process_data(
+                    csv_file=csv_path,
+                    shp_file=boundary_shp,
+                    output_file=output_file,
+                    resolution=resolution,
+                    output_format='tif',
+                    shared_context=shared_ctx,
+                )
+                return output_file, csv_path
+
+            if _max_workers > 1 and _n_pending > 1:
+                self.log_message.emit(
+                    f"[并发] {_n_pending} 个专题图，{_max_workers} 线程并行克里金", "info")
+                with concurrent.futures.ThreadPoolExecutor(
+                        max_workers=_max_workers) as executor:
+                    _futures = {
+                        executor.submit(_process_one, csv_p, out_f): (csv_p, out_f)
+                        for csv_p, out_f in _pending
+                    }
+                    for _future in concurrent.futures.as_completed(_futures):
+                        if self._cancelled:
+                            _done.set()
+                            self.log_message.emit("专题图批量任务已被用户取消", "warning")
+                            executor.shutdown(wait=False, cancel_futures=True)
+                            break
+                        csv_p, _ = _futures[_future]
+                        try:
+                            _future.result()
+                            with _lock:
+                                _completed += 1
+                            self.progress.emit(_completed + _skipped, n)
+                            self.log_message.emit(
+                                f"专题图 [{_completed}/{_n_pending}] ✓: "
+                                f"{Path(csv_p).name}", "info")
+                        except Exception as e:
+                            with _lock:
+                                _completed += 1
+                            self.log_message.emit(
+                                f"专题图 [{_completed}/{_n_pending}] ✗: "
+                                f"{Path(csv_p).name} — {e}", "error")
+            else:
+                for csv_p, out_f in _pending:
+                    if self._cancelled:
+                        self.log_message.emit("专题图批量任务已被用户取消", "warning")
+                        break
+                    _completed += 1
+                    self.progress.emit(_completed + _skipped, n)
+                    self.log_message.emit(
+                        f"专题图 [{_completed}/{_n_pending}] {csv_p}", "info")
+                    try:
+                        _process_one(csv_p, out_f)
+                    except Exception as e:
+                        self.log_message.emit(f"  → 失败: {e}", "error")
+                        continue
 
             self.finished_ok.emit(n)
         except Exception as e: