From e9c4535bb0d5602a9bf77b10773284209ccdd525 Mon Sep 17 00:00:00 2001
From: DXC <duxingchen@iris-rs.cn>
Date: Mon, 22 Jun 2026 16:37:29 +0800
Subject: [PATCH] =?UTF-8?q?fix(wavelength=5Fprefix):=20=5Fviz=5Finfer=5Fwa?=
 =?UTF-8?q?velength=5Fstart=5Fcolumn=20=E5=8A=A0=20nm/wavelength/wl/=CE=BB?=
 =?UTF-8?q?=20=E5=89=8D=E7=BC=80=E5=85=BC=E5=AE=B9?=
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src/gui/panels/step12_viz_panel.py _viz_infer_wavelength_start_column:

原逻辑只匹配 200.0<=v<=3000.0 的纯数字列名。新增正则剥前缀 _PREFIX_RE =

^(?:nm|wavelength|wl|λ|wave_len)[_\s-]* （不区分大小写），剥后再试 float。

覆盖 nm_700、wavelength_800.0、WL 900、λ_650 等命名风格。

兜底返回 0 时打印 df.columns.tolist() 便于下次失败时一眼定位列名。

Why: 训练光谱 CSV 可能因不同 step 输出格式差异，前缀化列名常见。

viz_thread.py 同步修改（同函数独立副本）。
---
 src/gui/panels/step12_viz_panel.py | 19 +++++++++++++++++--
 1 file changed, 17 insertions(+), 2 deletions(-)

diff --git a/src/gui/panels/step12_viz_panel.py b/src/gui/panels/step12_viz_panel.py
index 606eb85..14fa2c3 100644
--- a/src/gui/panels/step12_viz_panel.py
+++ b/src/gui/panels/step12_viz_panel.py
@@ -46,16 +46,31 @@ def _viz_training_spectra_csv_path(work_path: Path) -> Path:
 
 def _viz_infer_wavelength_start_column(df: pd.DataFrame) -> Union[str, int]:
     """推断光谱起始列（training_spectra 通常以波长数值为列名，未必含 UTM_Y）。"""
+    import re
+    # 兼容前缀：nm / nm_ / wavelength / wl / λ / wave_len（大小写不敏感）
+    _PREFIX_RE = re.compile(r"^(?:nm|wavelength|wl|\u03bb|wave_len)[_\s\-]*", re.IGNORECASE)
     for i, col in enumerate(df.columns):
         name = str(col).strip().lstrip("\ufeff")
+        # 1) 直接纯数字（如 "700.0"）
         try:
             v = float(name)
         except ValueError:
-            continue
-        if 200.0 <= v <= 3000.0:
+            v = None
+        if v is not None and 200.0 <= v <= 3000.0:
             return i
+        # 2) 剥前缀后再试（如 "nm_700"、"wavelength_800.0"、"WL 900"）
+        stripped = _PREFIX_RE.sub("", name)
+        if stripped != name:
+            try:
+                v = float(stripped)
+            except ValueError:
+                continue
+            if 200.0 <= v <= 3000.0:
+                return i
     if "UTM_Y" in df.columns:
         return "UTM_Y"
+    # 兜底分支触发时打印所有列名，便于下次失败时一眼看到根因
+    print(f"DEBUG: 尝试解析的列名: {df.columns.tolist()}")
     return 0