Hermes CI Fix
3dddd36866
包含前后端完整代码： - 前端：Vue3+Vite+ElementPlus - 后端：FastAPI+SQLAlchemy - 模块：驾驶舱/KPI/战略地图/预警/预算/成本/预测/改善行动 - 当前版本：v1.0.0
98 lines
4.4 KiB
Python
98 lines
4.4 KiB
Python
"""阈值智能推荐 API"""
|
|
from fastapi import APIRouter, Depends, Query
|
|
from sqlalchemy.orm import Session
|
|
from app.database import get_db
|
|
from app.auth_middleware import require_auth, require_role
|
|
from app.models import KPIDefinition, KPIValue, OperationLog
|
|
import json
|
|
|
|
router = APIRouter(prefix="/api/cma/thresholds", tags=["阈值分析"],
|
|
dependencies=[Depends(require_role("ceo", "finance", "business", "it"))],
|
|
)
|
|
|
|
KPI_TYPES = {
|
|
"higher_better": ["SALES_TOTAL", "CUSTOMER_COUNT", "SALES_PROFIT_RATE",
|
|
"CUSTOMER_SATISFACTION", "ORDER_DELIVERY_RATE", "TRAINING_COMPLETION",
|
|
"RECEIVABLE_TURNOVER", "TURNOVER_RATE"],
|
|
"lower_better": ["COST_CONTROL_RATE"],
|
|
"middle_best": ["TOP5_CUSTOMER_RATIO"],
|
|
}
|
|
|
|
@router.get("/suggest/{kpi_id}")
|
|
def suggest_threshold(kpi_id: int, db: Session = Depends(get_db)):
|
|
"""根据历史数据自动推荐阈值"""
|
|
kpi = db.query(KPIDefinition).filter(KPIDefinition.id == kpi_id).first()
|
|
if not kpi:
|
|
return {"error": "KPI不存在"}
|
|
|
|
values = db.query(KPIValue).filter(KPIValue.kpi_id == kpi_id).order_by(KPIValue.period.asc()).all()
|
|
|
|
if not values:
|
|
# 无历史数据，按行业标准推荐
|
|
return suggest_by_type(kpi)
|
|
|
|
nums = [v.actual_value for v in values if v.actual_value is not None]
|
|
|
|
if len(nums) < 2:
|
|
return suggest_by_type(kpi)
|
|
|
|
avg = sum(nums) / len(nums)
|
|
# 计算标准差
|
|
variance = sum((x - avg) ** 2 for x in nums) / len(nums)
|
|
std = variance ** 0.5
|
|
|
|
target = kpi.target_value or avg
|
|
|
|
# 根据KPI类型生成推荐区间
|
|
if kpi.kpi_code in KPI_TYPES["higher_better"]:
|
|
green_min = round(target * 0.8, 2)
|
|
yellow_min = round(target * 0.5, 2)
|
|
red_max = round(target * 0.5, 2)
|
|
suggestion = {
|
|
"type": "higher_better",
|
|
"description": "越高越好型",
|
|
"green": {"min": green_min, "max": None, "label": f">={green_min}"},
|
|
"yellow": {"min": yellow_min, "max": green_min, "label": f"{yellow_min}~{green_min}"},
|
|
"red": {"min": None, "max": red_max, "label": f"<{red_max}"},
|
|
"current_avg": round(avg, 2),
|
|
"target": target,
|
|
}
|
|
elif kpi.kpi_code in KPI_TYPES["lower_better"]:
|
|
green_max = round(target * 1.2, 2)
|
|
yellow_max = round(target * 2.0, 2)
|
|
suggestion = {
|
|
"type": "lower_better",
|
|
"description": "越低越好型",
|
|
"green": {"min": None, "max": green_max, "label": f"<={green_max}"},
|
|
"yellow": {"min": green_max, "max": yellow_max, "label": f"{green_max}~{yellow_max}"},
|
|
"red": {"min": yellow_max, "max": None, "label": f">{yellow_max}"},
|
|
"current_avg": round(avg, 2),
|
|
"target": target,
|
|
}
|
|
else:
|
|
tolerance = max(std * 1.5, target * 0.2)
|
|
suggestion = {
|
|
"type": "middle_best",
|
|
"description": "适中最好型",
|
|
"green": {"min": round(target - tolerance, 2), "max": round(target + tolerance, 2), "label": f"{round(target-tolerance,2)}~{round(target+tolerance,2)}"},
|
|
"yellow": {"min": round(target - tolerance*2, 2), "max": round(target + tolerance*2, 2), "label": f"偏离{(tolerance*2):.0f}%"},
|
|
"red": {"min": None, "max": round(target - tolerance*2, 2), "label": f"偏离>{tolerance*2:.0f}%"},
|
|
"current_avg": round(avg, 2),
|
|
"target": target,
|
|
}
|
|
|
|
return {"kpi_id": kpi_id, "kpi_name": kpi.kpi_name, "suggestion": suggestion}
|
|
|
|
def suggest_by_type(kpi):
|
|
"""无历史数据时按类型推荐"""
|
|
target = kpi.target_value or 100
|
|
if kpi.kpi_code in KPI_TYPES["higher_better"]:
|
|
return {"kpi_id": kpi.id, "kpi_name": kpi.kpi_name, "message": "无历史数据",
|
|
"suggestion": {"type": "higher_better", "green": {"min": round(target*0.8,2)}, "yellow": {"min": round(target*0.5,2)}, "red": {"max": round(target*0.5,2)}}}
|
|
elif kpi.kpi_code in KPI_TYPES["lower_better"]:
|
|
return {"kpi_id": kpi.id, "kpi_name": kpi.kpi_name, "message": "无历史数据",
|
|
"suggestion": {"type": "lower_better", "green": {"max": round(target*1.2,2)}, "yellow": {"max": round(target*2,2)}, "red": {"min": round(target*2,2)}}}
|
|
else:
|
|
return {"kpi_id": kpi.id, "kpi_name": kpi.kpi_name, "message": "无历史数据",
|
|
"suggestion": {"type": "middle_best", "green": {"min": round(target*0.8,2), "max": round(target*1.2,2)}}}
|