feat(toolkit): add classification and migration

Implement the standard/non-standard/not-macrolactone classification layer
and integrate it into analyzer, fragmenter, and CLI outputs.

Port the remaining legacy package capabilities into new visualization and
workflow modules, restore batch/statistics/SDF scripts on top of the flat
CSV workflow, and update active docs to the new package API.

notebooks/README_analyze_ring16.md

@@ -102,19 +102,15 @@ notebook的最后一个单元格（Section 9）提供了详细的延伸分析建
 notebook中包含了完整的代码示例，可以直接运行或修改。主要功能：
 
 ```python
-# 1. 计算分子性质
-props = calculate_properties(smiles)
+from macro_lactone_toolkit import MacroLactoneAnalyzer
+from macro_lactone_toolkit.workflows import fragment_csv, results_to_dataframe
 
-# 2. 批量断裂
-fragmenter = MacrolactoneFragmenter(ring_size=16)
-batch_results = fragmenter.process_csv(csv_file)
+analyzer = MacroLactoneAnalyzer()
+classification = analyzer.classify_macrocycle(smiles, ring_size=16)
 
-# 3. 统计分析
-df_fragments = fragmenter.batch_to_dataframe(batch_results)
-position_stats = df_fragments.groupby('cleavage_position').agg(...)
-
-# 4. 绘图
-sns.histplot(values, kde=True, ax=ax, bins=30)
+batch_results = fragment_csv(csv_file, ring_size=16)
+df_fragments = results_to_dataframe(batch_results)
+position_stats = df_fragments.groupby("cleavage_position").agg(...)
 ```
 
 ## 关键洞察
@@ -174,10 +170,10 @@ sns.histplot(values, kde=True, ax=ax, bins=30)
 
 ## 参考
 
-- `filter_molecules.ipynb` - 分子过滤和断裂逻辑
-- `test_align_two_molecules.ipynb` - 绘图逻辑参考
-- `src/macrolactone_fragmenter.py` - 封装的断裂器类
-- `src/ring_visualization.py` - 可视化工具
+- `scripts/batch_process_ring16.py` - 16 元环 flat workflow 入口
+- `scripts/analyze_fragments.py` - 位置统计和图表输出
+- `src/macro_lactone_toolkit/fragmenter.py` - 标准大环内酯裂解器
+- `src/macro_lactone_toolkit/visualization.py` - 编号和碎片可视化工具
 
 ## 问题反馈
 
@@ -187,4 +183,3 @@ sns.histplot(values, kde=True, ax=ax, bins=30)
 3. 查看输出目录是否有写入权限
 4. 检查CSV文件路径是否正确
 
-