checkpoint: real-scale 数据链 + 统计引擎 + ABLUP 稀疏性能修复
init 后首次落盘,累计工作: - 数据侧:simulate_breeding_data real-scale 3.5万树重建 + 分层观测 - 引擎侧:ABLUP 稀疏生产档 EM-REML(blup 1.6.0/1.7.0);性能倒挂修复—— 系谱闭包收口为 BFS 可达祖先 + N_EXACT 3000 对齐 N_SUBSAMPLE(选中 200~3000 树 不再顶进数小时精确迹尾),A/B 数值等价实证 + 守卫探针 - 前端:观测过滤 + 表单/HTTP 工具链完善 - 文档:业务链/观测梳理 + 引擎实施记录 + 规划对照总表 - gitignore:排除 Temp/调试脚本/一次性验证输出
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@@ -12,6 +12,7 @@ from app.utils.dict_util import DictLabelResolver, dict_value_to_label
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from app.utils.number_gen import NumberGenService
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from .crud import BreedingTreeCRUD
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from .model import TreeModel
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from .schema import (
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TreeCreateSchema,
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TreeOutSchema,
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@@ -370,8 +371,10 @@ class TreeService:
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await BreedingTreeCRUD(self.auth, self.db).delete(ids=ids)
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async def list_options(self) -> list[dict[str, Any]]:
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"""供前端下拉选择使用:返回 [{value, label}]。"""
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obj_list = await BreedingTreeCRUD(self.auth, self.db).get_list(order_by=[{"id": "asc"}])
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"""供前端下拉选择使用:返回 [{value, label}]。只取 id/tree_no 两列,避免全表列加载拖慢下拉。"""
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obj_list = await BreedingTreeCRUD(self.auth, self.db).get_list(
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order_by=[{"id": "asc"}], load_columns=[TreeModel.id, TreeModel.tree_no]
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)
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return [{"value": o.id, "label": o.tree_no} for o in obj_list]
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@staticmethod
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