up b11 params
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vendored
@ -11,6 +11,7 @@ db.sqlite3
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db.sqlite3-journal
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db.sqlite3-shm
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db.sqlite3-wal
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test-api.py
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test_api.py
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.DS_Store
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._.DS_Store
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@ -13,41 +13,67 @@ from app.schemas.valuation import (
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from app.schemas.base import Success, SuccessExtra
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from app.utils.app_user_jwt import get_current_app_user_id
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from app.utils.calculation_engine.economic_value_b1.economic_value_b1 import EconomicValueB1Calculator
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from app.utils.calculation_engine.economic_value_b1.sub_formulas.basic_value_b11 import calculate_popularity_score, \
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calculate_infringement_score, calculate_patent_usage_score
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from app.utils.calculation_engine.economic_value_b1.sub_formulas.traffic_factor_b12 import calculate_search_index_s1
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from app.models.esg import ESG
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from app.models.industry import Industry
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from app.models.policy import Policy
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app_valuations_router = APIRouter(tags=["用户端估值评估"])
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@app_valuations_router.post("/calculation", summary="计算估值")
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async def calculate_valuation(
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data: UserValuationCreate,
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user_id: int = Depends(get_current_app_user_id)
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data: UserValuationCreate,
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user_id: int = Depends(get_current_app_user_id)
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):
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"""
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计算估值评估
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根据用户提交的估值评估数据，调用计算引擎进行经济价值B1计算
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"""
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try:
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# 创建计算器实例
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calculator = EconomicValueB1Calculator()
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# 从用户数据中提取计算所需的参数
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# 根据行业查询 ESG 基准分（优先用行业名称匹配，如用的是行业代码就把 name 改成 code）
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esg_obj = await ESG.filter(name=data.industry).first()
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esg_score = float(esg_obj.number) if esg_obj else 0.0
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# 根据行业查询 行业修正系数与ROE
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industry_obj = await Industry.filter(name=data.industry).first()
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# roe_score = industry_obj.roe
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fix_num_score = industry_obj.fix_num
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# 根据行业查询 政策匹配度
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policy_obj = await Policy.filter(name=data.industry).first()
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policy_match_score = policy_obj.score
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# 提取计算参数
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input_data = _extract_calculation_params(data)
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# 调用计算引擎进行估值计算
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# ESG关联价值 ESG分 (0-10分)
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input_data["esg_score"] = esg_score
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# 行业修正系数I
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input_data["industry_coefficient"] = fix_num_score
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# 政策匹配度
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input_data["policy_match_score"] = policy_match_score
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# 调用计算引擎
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calculation_result = calculator.calculate_complete_economic_value_b1(input_data)
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# 创建估值评估记录
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result = await user_valuation_controller.create_valuation(
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user_id=user_id,
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data=data
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)
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# 将计算结果添加到返回数据中
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# 组装返回
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result_dict = json.loads(result.model_dump_json())
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result_dict['calculation_result'] = calculation_result
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return Success(data=result_dict, msg="估值计算完成")
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except Exception as e:
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raise HTTPException(status_code=400, detail=f"计算失败: {str(e)}")
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@ -66,15 +92,22 @@ def _extract_calculation_params(data: UserValuationCreate) -> Dict[str, Any]:
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# 财务价值所需数据 从近三年收益计算
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three_year_income = data.three_year_income or [0, 0, 0]
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# 法律强度L相关参数 - 需要用户额外提供评分
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# 这里使用默认值，实际应用中需要用户填写
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patent_score = 5.0 # 专利分 (0-10分)
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popularity_score = 5.0 # 普及地域分 (0-10分)
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infringement_score = 5.0 # 侵权分 (0-10分)
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# 法律强度L相关参数
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# 普及地域分值 默认 7分
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popularity_score = calculate_popularity_score(data.application_coverage)
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# TODO 专利剩余年限【专利证书】 需要使用第三方API
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patent = data.patent_application_no
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patent_score = 0
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# 侵权分 默认 6 TODO 需要使用第三方API 无侵权记录(10分)，历史侵权已解决(6分)，现存纠纷(2分)
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# infringement_score = calculate_infringement_score()
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infringement_score = 0
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# 发展潜力D相关参数
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esg_score = 5.0 # ESG分 (0-10分)
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# 专利使用量 TODO 需要使用第三方API
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patent_score = calculate_patent_usage_score(0)
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# 创新投入比 = (研发费用/营收) * 100
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try:
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rd_investment = float(data.rd_investment or 0)
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@ -82,39 +115,44 @@ def _extract_calculation_params(data: UserValuationCreate) -> Dict[str, Any]:
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innovation_ratio = (rd_investment / annual_revenue) * 100 if annual_revenue > 0 else 0
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except (ValueError, TypeError):
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innovation_ratio = 0.0
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# 行业系数I - 系统配置值
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target_industry_roe = 0.15 # 目标行业平均ROE
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benchmark_industry_roe = 0.12 # 基准行业ROE
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#
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# 流量因子B12相关参数
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# 近30天搜索指数S1 - 从社交媒体数据计算
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search_index_s1 = 4500.0 # 默认值，实际应从API获取
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industry_average_s2 = 5000.0 # 行业均值，系统配置
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# 社交媒体传播度S3 - 从线上账号信息计算
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social_media_spread_s3 = 1.07 # 默认值，实际应从API获取
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# 近30天搜索指数S1 - 从社交媒体数据计算 TODO 需要使用第三方API
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search_index_s1 = calculate_search_index_s1() # 默认值，实际应从API获取
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# 行业均值S2 TODO 系统内置 未找到相关内容
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industry_average_s2 = 0.0
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# 社交媒体传播度S3 - TODO 需要使用第三方API,click_count view_count 未找到对应参数
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# likes: 点赞数(API获取)
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# comments: 评论数(API获取)
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# shares: 转发数(API获取)
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# followers: 粉丝数
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# click_count: 商品链接点击量(用户填写) sales_volume 使用 sales_volume 销售量
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# view_count: 内容浏览量(用户填写) link_views
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# 政策乘数B13相关参数
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# 政策契合度评分P - 根据行业和资助情况计算
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policy_compatibility_score = 9.1 # 默认值，实际应系统计算
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# 实施阶段
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implementation_stage = data.implementation_stage
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# 资金支持
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funding_support = data.funding_status
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return {
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# 基础价值B11相关参数
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'financial_value': financial_value,
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'three_year_income': three_year_income,
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'patent_score': patent_score,
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'popularity_score': popularity_score,
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'infringement_score': infringement_score,
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'esg_score': esg_score,
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'innovation_ratio': innovation_ratio,
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'target_industry_roe': target_industry_roe,
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'benchmark_industry_roe': benchmark_industry_roe,
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# 流量因子B12相关参数
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'search_index_s1': search_index_s1,
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'industry_average_s2': industry_average_s2,
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'social_media_spread_s3': social_media_spread_s3,
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# 'industry_average_s2': industry_average_s2,
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# 'social_media_spread_s3': social_media_spread_s3,
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'click_count': int(data.click_count) or 100,
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'view_count': int(data.link_views) or 100,
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# 政策乘数B13相关参数
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'policy_compatibility_score': policy_compatibility_score
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'implementation_stage': implementation_stage,
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'funding_support':funding_support
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}
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0
app/utils/__init__.py
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app/utils/__init__.py
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@ -8,7 +8,7 @@
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from typing import Dict
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try:
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# 相对导入（当作为包使用时）
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from .sub_formulas.basic_value_b11 import BasicValueB11Calculator
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from .sub_formulas.basic_value_b11 import BasicValueB11Calculator, calculate_popularity_score
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from .sub_formulas.traffic_factor_b12 import TrafficFactorB12Calculator
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from .sub_formulas.policy_multiplier_b13 import PolicyMultiplierB13Calculator
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except ImportError:
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@ -37,12 +37,12 @@ class EconomicValueB1Calculator:
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经济价值B1 = 基础价值B11 × (1 + 流量因子B12) × 政策乘数B13
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Args:
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args:
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basic_value_b11: 基础价值B11 (系统计算)
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traffic_factor_b12: 流量因子B12 (系统计算)
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policy_multiplier_b13: 政策乘数B13 (系统计算)
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Returns:
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returns:
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float: 经济价值B1
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"""
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economic_value = basic_value_b11 * (1 + traffic_factor_b12) * policy_multiplier_b13
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@ -50,27 +50,27 @@ class EconomicValueB1Calculator:
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return economic_value
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def calculate_complete_economic_value_b1(self, input_data: Dict) -> Dict:
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"""
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计算完整的经济价值B1，包含所有子公式
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Args:
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args:
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input_data: 输入数据字典，包含所有必要的参数
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Returns:
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returns:
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Dict: 包含所有中间计算结果和最终结果的字典
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"""
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# 财务价值F 近三年年均收益列表 [1,2,3]
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financial_value = self.basic_value_calculator.calculate_financial_value_f()
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# 计算法律强度L patent_score: 专利分 (0-10分) (用户填写)
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# popularity_score: 普及地域分 (0-10分) (用户填写)
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# infringement_score: 侵权分 (0-10分) (用户填写)
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popularity_score = calculate_popularity_score()
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legal_strength = self.basic_value_calculator.calculate_legal_strength_l()
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# 发展潜力 patent_score: 专利分 (0-10分) (用户填写)
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# esg_score: ESG分 (0-10分) (用户填写)
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# innovation_ratio: 创新投入比 (研发费用/营收) * 100 (用户填写)
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development_potential = self.basic_value_calculator.calculate_development_potential_d()
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# 计算行业系数I target_industry_roe: 目标行业平均ROE (系统配置)
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# benchmark_industry_roe: 基准行业ROE (系统配置)
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@ -19,13 +19,13 @@ class BasicValueB11Calculator:
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基础价值B11 = 财务价值F × (0.45 + 0.05 × 行业系数I) + 法律强度L × (0.35 + 0.05 × 行业系数I) + 发展潜力D × 0.2
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Args:
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args:
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financial_value: 财务价值F (用户填写)
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legal_strength: 法律强度L (用户填写)
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development_potential: 发展潜力D (用户填写)
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industry_coefficient: 行业系数I (系统配置)
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Returns:
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returns:
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float: 基础价值B11
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"""
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basic_value = (financial_value * (0.45 + 0.05 * industry_coefficient) +
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@ -51,11 +51,11 @@ class BasicValueB11Calculator:
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财务价值F = [3年内年均收益 × (1 + 增长率)^5] / 5
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Args:
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args:
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annual_revenue_3_years: 近三年年均收益列表，单位：万元 (用户填写)
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growth_rate: 增长率，如果为None则自动计算 (用户填写)
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Returns:
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returns:
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float: 财务价值F
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"""
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if len(annual_revenue_3_years) != 3:
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@ -76,10 +76,10 @@ class BasicValueB11Calculator:
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"""
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根据三年收益数据计算增长率
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Args:
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args:
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revenue_data: 三年收益数据 (用户填写)
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Returns:
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returns:
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float: 增长率
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"""
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if len(revenue_data) != 3:
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@ -104,12 +104,12 @@ class BasicValueB11Calculator:
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法律强度L = 专利分 × 0.4 + 普及分 × 0.3 + 侵权分 × 0.3
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Args:
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args:
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patent_score: 专利分 (0-10分) (用户填写)
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popularity_score: 普及地域分 (0-10分) (用户填写)
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infringement_score: 侵权分 (0-10分) (用户填写)
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Returns:
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returns:
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float: 法律强度L
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"""
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@ -129,12 +129,12 @@ class BasicValueB11Calculator:
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发展潜力D = 专利分 × 0.5 + ESG分 × 0.2 + 创新投入比 × 0.3
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Args:
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args:
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patent_score: 专利分 (0-10分) (用户填写)
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esg_score: ESG分 (0-10分) (用户填写)
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innovation_ratio: 创新投入比 (研发费用/营收) * 100 (用户填写)
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Returns:
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returns:
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float: 发展潜力D
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"""
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@ -152,11 +152,11 @@ class BasicValueB11Calculator:
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行业系数I = (目标行业平均ROE - 基准行业ROE) / 基准行业ROE
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Args:
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args:
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target_industry_roe: 目标行业平均ROE (系统配置)
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benchmark_industry_roe: 基准行业ROE (系统配置)
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Returns:
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returns:
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float: 行业系数I
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"""
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if benchmark_industry_roe == 0:
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@ -177,10 +177,10 @@ def calculate_patent_score(patent_remaining_years: int) -> float:
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- 5-10年: 7分
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- <5年: 3分
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Args:
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args:
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patent_remaining_years: 专利剩余保护期（年） (用户填写)
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Returns:
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returns:
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float: 专利分
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"""
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if patent_remaining_years > 10:
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@ -201,10 +201,10 @@ def calculate_patent_usage_score(patent_count: int) -> float:
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- 每引用一项: +2.5分
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- 10分封顶
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Args:
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args:
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patent_count: 专利数量 (用户填写)
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Returns:
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returns:
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float: 专利使用量分
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"""
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score = min(patent_count * 2.5, 10.0)
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@ -218,10 +218,10 @@ def calculate_popularity_score(region_coverage: str) -> float:
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全球覆盖(10分)，全国覆盖(7分)，区域覆盖(4分)
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Args:
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args:
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region_coverage: 普及地域类型 (用户填写)
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Returns:
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returns:
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float: 普及地域分
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"""
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coverage_scores = {
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@ -230,7 +230,7 @@ def calculate_popularity_score(region_coverage: str) -> float:
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"区域覆盖": 4.0
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}
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return coverage_scores.get(region_coverage, 0.0)
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return coverage_scores.get(region_coverage, 7.0)
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# 侵权记录评分
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@ -240,10 +240,10 @@ def calculate_infringement_score(infringement_status: str) -> float:
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无侵权记录(10分)，历史侵权已解决(6分)，现存纠纷(2分)
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Args:
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args:
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infringement_status: 侵权记录状态 (用户填写)
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Returns:
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returns:
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float: 侵权记录分
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"""
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infringement_scores = {
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@ -252,7 +252,7 @@ def calculate_infringement_score(infringement_status: str) -> float:
|
||||
"现存纠纷": 2.0
|
||||
}
|
||||
|
||||
return infringement_scores.get(infringement_status, 0.0)
|
||||
return infringement_scores.get(infringement_status, 6.0)
|
||||
|
||||
|
||||
# 示例使用
|
||||
|
||||
@ -15,7 +15,7 @@ class PolicyMultiplierB13Calculator:
|
||||
Args:
|
||||
policy_compatibility_score: 政策契合度评分P (系统计算)
|
||||
|
||||
Returns:
|
||||
returns:
|
||||
float: 政策乘数B13
|
||||
"""
|
||||
#
|
||||
@ -38,7 +38,7 @@ class PolicyMultiplierB13Calculator:
|
||||
implementation_stage_score: 实施阶段评分 (用户填写)
|
||||
funding_support_score: 资金支持度 (用户填写)
|
||||
|
||||
Returns:
|
||||
returns:
|
||||
float: 政策契合度评分P
|
||||
"""
|
||||
#
|
||||
@ -57,7 +57,7 @@ class PolicyMultiplierB13Calculator:
|
||||
Args:
|
||||
industry: 所属行业 (用户填写)
|
||||
|
||||
Returns:
|
||||
returns:
|
||||
float: 政策匹配度
|
||||
"""
|
||||
|
||||
@ -72,7 +72,7 @@ class PolicyMultiplierB13Calculator:
|
||||
Args:
|
||||
implementation_stage: 实施阶段 (用户填写)
|
||||
|
||||
Returns:
|
||||
returns:
|
||||
float: 实施阶段评分
|
||||
"""
|
||||
stage_scores = {
|
||||
@ -81,7 +81,7 @@ class PolicyMultiplierB13Calculator:
|
||||
"试点阶段": 4.0
|
||||
}
|
||||
|
||||
return stage_scores.get(implementation_stage, 0.0)
|
||||
return stage_scores.get(implementation_stage, 10.0)
|
||||
|
||||
def calculate_funding_support_score(self, funding_support: str) -> float:
|
||||
"""
|
||||
@ -92,7 +92,7 @@ class PolicyMultiplierB13Calculator:
|
||||
Args:
|
||||
funding_support: 资金支持情况 (用户填写)
|
||||
|
||||
Returns:
|
||||
returns:
|
||||
float: 资金支持度
|
||||
"""
|
||||
funding_scores = {
|
||||
|
||||
@ -19,12 +19,12 @@ class TrafficFactorB12Calculator:
|
||||
|
||||
流量因子B12 = ln(近30天搜索指数S1/行业均值S2) × 0.3 + 社交媒体传播度S3 × 0.7
|
||||
|
||||
Args:
|
||||
args:
|
||||
search_index_s1: 近30天搜索指数S1 (API获取)
|
||||
industry_average_s2: 行业均值S2 (系统配置)
|
||||
social_media_spread_s3: 社交媒体传播度S3 (API获取)
|
||||
|
||||
Returns:
|
||||
returns:
|
||||
float: 流量因子B12
|
||||
"""
|
||||
# 避免除零和对数计算错误
|
||||
@ -40,30 +40,8 @@ class TrafficFactorB12Calculator:
|
||||
social_media_spread_s3 * 0.7)
|
||||
|
||||
return traffic_factor
|
||||
|
||||
def calculate_search_index_s1(self,
|
||||
baidu_index: float,
|
||||
wechat_index: float,
|
||||
weibo_index: float) -> float:
|
||||
"""
|
||||
计算近30天搜索指数S1
|
||||
|
||||
近30天搜索指数S1 = 百度搜索指数 × 0.4 + 微信搜索指数 × 0.3 + 微博搜索指数 × 0.3
|
||||
|
||||
Args:
|
||||
baidu_index: 百度搜索指数 (API获取)
|
||||
wechat_index: 微信搜索指数 (API获取)
|
||||
weibo_index: 微博搜索指数 (API获取)
|
||||
|
||||
Returns:
|
||||
float: 近30天搜索指数S1
|
||||
"""
|
||||
#
|
||||
search_index = (baidu_index * 0.4 +
|
||||
wechat_index * 0.3 +
|
||||
weibo_index * 0.3)
|
||||
|
||||
return search_index
|
||||
|
||||
|
||||
def calculate_social_media_spread_s3(self,
|
||||
interaction_index: float,
|
||||
@ -73,20 +51,20 @@ class TrafficFactorB12Calculator:
|
||||
计算社交媒体传播度S3
|
||||
|
||||
社交媒体传播度S3 = 互动量指数 × 0.4 + 覆盖人群指数 × 0.3 + 转化效率 × 0.3
|
||||
|
||||
Args:
|
||||
|
||||
args:
|
||||
interaction_index: 互动量指数 (API获取)
|
||||
coverage_index: 覆盖人群指数 (API获取)
|
||||
conversion_efficiency: 转化效率 (用户填写)
|
||||
|
||||
Returns:
|
||||
|
||||
returns:
|
||||
float: 社交媒体传播度S3
|
||||
"""
|
||||
#
|
||||
social_media_spread = (interaction_index * 0.4 +
|
||||
coverage_index * 0.3 +
|
||||
#
|
||||
social_media_spread = (interaction_index * 0.4 +
|
||||
coverage_index * 0.3 +
|
||||
conversion_efficiency * 0.3)
|
||||
|
||||
|
||||
return social_media_spread
|
||||
|
||||
def calculate_interaction_index(self,
|
||||
@ -98,12 +76,12 @@ class TrafficFactorB12Calculator:
|
||||
|
||||
互动量指数 = (点赞 + 评论 + 转发) / 1000
|
||||
|
||||
Args:
|
||||
args:
|
||||
likes: 点赞数 (API获取)
|
||||
comments: 评论数 (API获取)
|
||||
shares: 转发数 (API获取)
|
||||
|
||||
Returns:
|
||||
returns:
|
||||
float: 互动量指数
|
||||
"""
|
||||
#
|
||||
@ -117,10 +95,10 @@ class TrafficFactorB12Calculator:
|
||||
|
||||
覆盖人群指数 = 粉丝数 / 10000
|
||||
|
||||
Args:
|
||||
args:
|
||||
followers: 粉丝数 (API获取)
|
||||
|
||||
Returns:
|
||||
returns:
|
||||
float: 覆盖人群指数
|
||||
"""
|
||||
#
|
||||
@ -137,11 +115,11 @@ class TrafficFactorB12Calculator:
|
||||
：
|
||||
转化效率 = 商品链接点击量 / 内容浏览量
|
||||
|
||||
Args:
|
||||
args:
|
||||
click_count: 商品链接点击量 (用户填写)
|
||||
view_count: 内容浏览量 (用户填写)
|
||||
|
||||
Returns:
|
||||
returns:
|
||||
float: 转化效率
|
||||
"""
|
||||
if view_count == 0:
|
||||
@ -163,10 +141,10 @@ class PlatformDataProcessor:
|
||||
|
||||
输入格式：B站：12345678\n抖音：22334455
|
||||
|
||||
Args:
|
||||
args:
|
||||
platform_data: 平台账号数据字符串 (用户填写)
|
||||
|
||||
Returns:
|
||||
returns:
|
||||
Dict[str, str]: 平台账号字典
|
||||
"""
|
||||
accounts = {}
|
||||
@ -188,10 +166,10 @@ class PlatformDataProcessor:
|
||||
"""
|
||||
计算多平台互动数据
|
||||
|
||||
Args:
|
||||
args:
|
||||
platform_data: 平台数据字典，格式为 {平台名: {likes: int, comments: int, shares: int, followers: int}} (API获取)
|
||||
|
||||
Returns:
|
||||
returns:
|
||||
Tuple[float, float]: (互动量指数, 覆盖人群指数)
|
||||
"""
|
||||
total_interactions = 0
|
||||
@ -227,11 +205,11 @@ def calculate_heat_score(daily_views: float, favorites: int) -> float:
|
||||
- 低热度：近7日日均浏览量 < 100，且收藏数 < 20 → 0.2
|
||||
- 无数据：无任何浏览与互动数据 → 0.0
|
||||
|
||||
Args:
|
||||
args:
|
||||
daily_views: 近7日日均浏览量 (API获取)
|
||||
favorites: 收藏数 (API获取)
|
||||
|
||||
Returns:
|
||||
returns:
|
||||
float: 热度分
|
||||
"""
|
||||
if daily_views > 1000 or favorites > 100:
|
||||
@ -243,7 +221,29 @@ def calculate_heat_score(daily_views: float, favorites: int) -> float:
|
||||
else:
|
||||
return 0.0
|
||||
|
||||
# 30天搜索指数S1
|
||||
def calculate_search_index_s1(baidu_index: float,
|
||||
wechat_index: float,
|
||||
weibo_index: float) -> float:
|
||||
"""
|
||||
计算近30天搜索指数S1
|
||||
|
||||
近30天搜索指数S1 = 百度搜索指数 × 0.4 + 微信搜索指数 × 0.3 + 微博搜索指数 × 0.3
|
||||
|
||||
args:
|
||||
baidu_index: 百度搜索指数 (API获取)
|
||||
wechat_index: 微信搜索指数 (API获取)
|
||||
weibo_index: 微博搜索指数 (API获取)
|
||||
|
||||
returns:
|
||||
float: 近30天搜索指数S1
|
||||
"""
|
||||
#
|
||||
search_index = (baidu_index * 0.4 +
|
||||
wechat_index * 0.3 +
|
||||
weibo_index * 0.3)
|
||||
|
||||
return search_index
|
||||
# 示例使用
|
||||
if __name__ == "__main__":
|
||||
# 创建计算器实例
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user