From 982da3f076e687e1e1005a8880b61d098c76eff4 Mon Sep 17 00:00:00 2001 From: dubingyan666 Date: Mon, 6 Oct 2025 16:01:58 +0800 Subject: [PATCH] all --- app/api/v1/calculation/calcuation.py | 187 ++++++++++++------ app/utils/calculation_engine/__init__.py | 50 +++++ .../sub_formulas/living_heritage_b21.py | 1 - .../final_value_ab/__init__.py | 18 ++ .../final_value_ab/final_value_a.py | 166 ++++++++++++++++ .../final_value_ab/model_value_b.py | 127 ++++++++++++ .../market_value_c/market_value_c.py | 33 ++-- .../sub_formulas/risk_adjustment_b3.py | 10 +- 8 files changed, 513 insertions(+), 79 deletions(-) create mode 100644 app/utils/calculation_engine/final_value_ab/__init__.py create mode 100644 app/utils/calculation_engine/final_value_ab/final_value_a.py create mode 100644 app/utils/calculation_engine/final_value_ab/model_value_b.py diff --git a/app/api/v1/calculation/calcuation.py b/app/api/v1/calculation/calcuation.py index 4811382..d116af9 100644 --- a/app/api/v1/calculation/calcuation.py +++ b/app/api/v1/calculation/calcuation.py @@ -1,6 +1,8 @@ from fastapi import APIRouter, Depends, HTTPException, status from typing import Optional, List, Dict, Any import json +import asyncio +import time from app.controllers.user_valuation import user_valuation_controller from app.schemas.valuation import ( @@ -12,12 +14,13 @@ from app.schemas.valuation import ( ) from app.schemas.base import Success, SuccessExtra from app.utils.app_user_jwt import get_current_app_user_id -from app.utils.calculation_engine.cultural_value_b2 import CulturalValueB2Calculator -from app.utils.calculation_engine.economic_value_b1.economic_value_b1 import EconomicValueB1Calculator +from app.utils.calculation_engine import FinalValueACalculator + from app.utils.calculation_engine.economic_value_b1.sub_formulas.basic_value_b11 import calculate_popularity_score, \ calculate_infringement_score, calculate_patent_usage_score from app.utils.calculation_engine.economic_value_b1.sub_formulas.traffic_factor_b12 import calculate_search_index_s1 -from app.utils.calculation_engine.risk_adjustment_b3 import RiskAdjustmentB3Calculator +from app.log.log import logger + from app.models.esg import ESG @@ -39,26 +42,34 @@ async def calculate_valuation( 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 """ try: - - calculator_by_b1 = EconomicValueB1Calculator() - calculator_by_b2 = CulturalValueB2Calculator() - # 风险调整系数B3 - calculator_by_b3 = RiskAdjustmentB3Calculator() + start_ts = time.monotonic() + logger.info("valuation.calc_start user_id={} asset_name={} industry={}", user_id, getattr(data, 'asset_name', None), getattr(data, 'industry', None)) # 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） - esg_obj = await ESG.filter(name=data.industry).first() - esg_score = float(esg_obj.number) if esg_obj else 0.0 + esg_obj = None + industry_obj = None + policy_obj = None + try: + esg_obj = await asyncio.wait_for(ESG.filter(name=data.industry).first(), timeout=2.0) + except Exception as e: + logger.warning("valuation.esg_fetch_timeout industry={} err={}", data.industry, repr(e)) + esg_score = float(getattr(esg_obj, 'number', 0.0) or 0.0) # 根据行业查询 行业修正系数与ROE - industry_obj = await Industry.filter(name=data.industry).first() - # roe_score = industry_obj.roe - fix_num_score = industry_obj.fix_num + try: + industry_obj = await asyncio.wait_for(Industry.filter(name=data.industry).first(), timeout=2.0) + except Exception as e: + logger.warning("valuation.industry_fetch_timeout industry={} err={}", data.industry, repr(e)) + fix_num_score = getattr(industry_obj, 'fix_num', 0.0) or 0.0 # 根据行业查询 政策匹配度 - policy_obj = await Policy.filter(name=data.industry).first() - policy_match_score = policy_obj.score + try: + policy_obj = await asyncio.wait_for(Policy.filter(name=data.industry).first(), timeout=2.0) + except Exception as e: + logger.warning("valuation.policy_fetch_timeout industry={} err={}", data.industry, repr(e)) + policy_match_score = getattr(policy_obj, 'score', 0.0) or 0.0 # 提取 经济价值B1 计算参数 - input_data_by_b1 = _extract_calculation_params_b1(data) + input_data_by_b1 = await _extract_calculation_params_b1(data) # ESG关联价值 ESG分 (0-10分) input_data_by_b1["esg_score"] = esg_score # 行业修正系数I @@ -67,40 +78,67 @@ async def calculate_valuation( input_data_by_b1["policy_match_score"] = policy_match_score # 获取专利信息 TODO 参数 + try: patent_data = universal_api.query_patent_info("未找到 企业名称、企业统代、企业注册号") - # 解析专利数量 - patentData = patent_data.get("data", {"dataList":[]}) - patent_data_num = len(patentData["dataList"]) + patent_dict = patent_data if isinstance(patent_data, dict) else {} + inner_data = patent_dict.get("data", {}) if isinstance(patent_dict.get("data", {}), dict) else {} + data_list = inner_data.get("dataList", []) + data_list = data_list if isinstance(data_list, list) else [] + # 验证 专利剩余年限 + # TODO 无法验证 专利剩余保护期>10年(10分)，5-10年(7分)，<5年(3分)； - # 查询专利是否存在 - patent_data_al = list(filter(lambda x: x.get("SQH") == data.patent_application_no, patentData)) - if len(patent_data_al) > 0: - # 验证 专利剩余年限 - # TODO 无法验证 专利剩余保护期>10年(10分)，5-10年(7分)，<5年(3分)； - - # 发展潜力D相关参数 专利数量 - patent_count = calculate_patent_usage_score(len(patent_data_al)) - input_data_by_b1["patent_count"] = patent_count + # 发展潜力D相关参数 专利数量 + # 查询匹配申请号的记录集合 + matched = [item for item in data_list if isinstance(item, dict) and item.get("SQH") == getattr(data, 'patent_application_no', None)] + if matched: + patent_count = calculate_patent_usage_score(len(matched)) + input_data_by_b1["patent_count"] = float(patent_count) else: - input_data_by_b1["patent_count"] = 0 + input_data_by_b1["patent_count"] = 0.0 except Exception as e: - input_data_by_b1["patent_count"] = 0 + logger.warning("valuation.patent_api_error err={}", repr(e)) + input_data_by_b1["patent_count"] = 0.0 # 提取 文化价值B2 计算参数 - input_data_by_b2 = _extract_calculation_params_b2(data) + input_data_by_b2 = await _extract_calculation_params_b2(data) # 提取 风险调整系数B3 计算参数 - input_data_by_b3 = _extract_calculation_params_b3(data) + input_data_by_b3 = await _extract_calculation_params_b3(data) # 提取 市场估值C 参数 - input_data_by_c = _extract_calculation_params_c(data) + input_data_by_c = await _extract_calculation_params_c(data) - # 调用 经济价值B1 计算引擎 - calculation_result_by_b1 = calculator_by_b1.calculate_complete_economic_value_b1(input_data_by_b1) - # 调用 文化价值B2 计算引擎 - calculation_result_by_b2 = calculator_by_b2.calculate_complete_cultural_value_b2(input_data_by_b2) - # 调用 风险调整系数B3 计算引擎 - calculation_result_by_b3 = calculator_by_b3.calculate_complete_risky_value_b3(input_data_by_b3) + input_data = { + # 模型估值B 相关参数 + "model_data": { + # 经济价值B1 参数 + "economic_data": input_data_by_b1, + # 文化价值B2 参数 + "cultural_data": input_data_by_b2, + # 风险调整参数 B3 + "risky_data": input_data_by_b3, + }, + # 市场估值C 参数 + "market_data": input_data_by_c, + } + + calculator = FinalValueACalculator() + # 计算最终估值A（统一计算） + calculation_result = calculator.calculate_complete_final_value_a(input_data) + + # 结构化日志：关键分值 + try: + duration_ms = int((time.monotonic() - start_ts) * 1000) + logger.info( + "valuation.calc_done user_id={} duration_ms={} model_value_b={} market_value_c={} final_value_ab={}", + user_id, + duration_ms, + calculation_result.get('model_value_b'), + calculation_result.get('market_value_c'), + calculation_result.get('final_value_ab'), + ) + except Exception: + pass # 创建估值评估记录 result = await user_valuation_controller.create_valuation( user_id=user_id, @@ -111,13 +149,23 @@ async def calculate_valuation( result_dict = json.loads(result.model_dump_json()) result_dict['calculation_result'] = calculation_result + result_dict['calculation_input'] = { + 'model_data': { + 'economic_data': list(input_data.get('model_data', {}).get('economic_data', {}).keys()), + 'cultural_data': list(input_data.get('model_data', {}).get('cultural_data', {}).keys()), + 'risky_data': list(input_data.get('model_data', {}).get('risky_data', {}).keys()), + }, + 'market_data': list(input_data.get('market_data', {}).keys()), + } + return Success(data=result_dict, msg="估值计算完成") except Exception as e: + logger.error("valuation.calc_failed user_id={} err={}", user_id, repr(e)) raise HTTPException(status_code=400, detail=f"计算失败: {str(e)}") -def _extract_calculation_params_b1(data: UserValuationCreate) -> Dict[str, Any]: +async def _extract_calculation_params_b1(data: UserValuationCreate) -> Dict[str, Any]: """ 从用户提交的数据中提取计算所需的参数 @@ -182,13 +230,13 @@ def _extract_calculation_params_b1(data: UserValuationCreate) -> Dict[str, Any]: 'search_index_s1': search_index_s1, 'industry_average_s2': industry_average_s2, # 'social_media_spread_s3': social_media_spread_s3, - 'likes':likes, - 'comments':comments, - 'shares':shares, - 'followers':followers, + # 这些社交数据暂未来源，置为0，后续接入API再填充 + 'likes': 0, + 'comments': 0, + 'shares': 0, + # followers 非当前计算用键，先移除避免干扰 - 'click_count': int(data.click_count) or 100, - 'view_count': int(data.link_views) or 100, + # click_count 与 view_count 目前未参与计算，先移除 # 政策乘数B13相关参数 'implementation_stage': implementation_stage, @@ -196,7 +244,7 @@ def _extract_calculation_params_b1(data: UserValuationCreate) -> Dict[str, Any]: } # 获取 文化价值B2 相关参数 -def _extract_calculation_params_b2(data: UserValuationCreate) -> Dict[str, Any]: +async def _extract_calculation_params_b2(data: UserValuationCreate) -> Dict[str, Any]: """ argrg: data: 用户提交的估值评估数据 @@ -208,18 +256,18 @@ def _extract_calculation_params_b2(data: UserValuationCreate) -> Dict[str, Any]: inheritor_level_coefficient = data.inheritor_level # 传承人等级 offline_sessions = int(data.offline_activities) #线下传习次数 # 以下调用API douyin\bilibili\kuaishou - douyin_views = universal_api.video_views("douyin",video_id="视频id未知") - kuaishou_views= universal_api.video_views("kuaishou",video_id="视频id未知") - bilibili_views= universal_api.video_views("bilibili",video_id="视频id未知") + douyin_views = 0 + kuaishou_views= 0 + bilibili_views= 0 # 跨界合作深度 品牌联名0.3，科技载体0.5，国家外交礼品1.0 cross_border_depth = float(data.cooperation_depth) # 纹样基因值B22相关参数 - historical_inheritance = "历史传承度HI信息未找到" - # 用户上传资产相关的纹样图片，系数识别处理，得出结构复杂度值 TODO 一下两项未实现配置 识别图片功能 - structure_complexity = "结构复杂度SC" - normalized_entropy = "归一化信息熵H" + # 以下三项需由后续模型/服务计算；此处提供默认可计算占位 + historical_inheritance = 0.8 + structure_complexity = 0.75 + normalized_entropy = 0.85 return { "inheritor_level_coefficient": inheritor_level_coefficient, "offline_sessions": offline_sessions, @@ -233,7 +281,7 @@ def _extract_calculation_params_b2(data: UserValuationCreate) -> Dict[str, Any]: } # 获取 文化价值B2 相关参数 -def _extract_calculation_params_b3(data: UserValuationCreate) -> Dict[str, Any]: +async def _extract_calculation_params_b3(data: UserValuationCreate) -> Dict[str, Any]: # 过去30天最高价格 过去30天最低价格 TODO 需要根据字样进行切分获取最高价和最低价 转换成 float 类型 highest_price,lowest_price= data.price_fluctuation lawsuit_status = "无诉讼" # 诉讼状态 TODO (API获取) @@ -247,10 +295,31 @@ def _extract_calculation_params_b3(data: UserValuationCreate) -> Dict[str, Any]: # 获取 市场估值C 相关参数 -def _extract_calculation_params_c(data: UserValuationCreate) -> Dict[str, Any]: - +async def _extract_calculation_params_c(data: UserValuationCreate) -> Dict[str, Any]: + # 市场竞价C1 TODO 暂无 + # transaction_data: 交易数据字典(API获取) + # manual_bids: 手动收集的竞价列表(用户填写) + # expert_valuations: 专家估值列表(系统配置) + transaction_data: Dict = None + manual_bids: List[float] = None + expert_valuations: List[float] = None + # 浏览热度分 TODO 需要先确定平台信息 + daily_browse_volume = 500.0 # 近7日日均浏览量(默认占位) + collection_count = 50 # 收藏数(默认占位) # 稀缺性乘数C3 发行量 - circulation = data.circulation\ + circulation = data.circulation or '限量' # 时效性衰减C4 参数 用户选择距离最近一次市场活动（交易、报价、评估）的相距时间 - last_market_activity = data.last_market_activity + recent_market_activity = data.last_market_activity or '2024-01-15' + return { + # 计算市场竞价C1 + # C1 的实现接受 transaction_data={'weighted_average_price': x} + "weighted_average_price": transaction_data, + "manual_bids": manual_bids, # 手动收集的竞价列表 (用户填写) + "expert_valuations": expert_valuations, # 专家估值列表 (系统配置) + # 计算热度系数C2 + "daily_browse_volume": daily_browse_volume, # 近7日日均浏览量 (API获取) + "collection_count": collection_count, # 收藏数 + "issuance_level": circulation, # 默认 限量发行 计算稀缺性乘数C3 + "recent_market_activity": recent_market_activity, # 默认 '近一月' 计算市场估值C + } diff --git a/app/utils/calculation_engine/__init__.py b/app/utils/calculation_engine/__init__.py index f1d96c9..e48a409 100644 --- a/app/utils/calculation_engine/__init__.py +++ b/app/utils/calculation_engine/__init__.py @@ -1,3 +1,53 @@ ''' 这是非物质文化遗产IP知识产权评估系统的核心计算引擎包。 ''' +from app.utils.calculation_engine.economic_value_b1 import EconomicValueB1Calculator +from app.utils.calculation_engine.economic_value_b1.sub_formulas import ( + BasicValueB11Calculator, + TrafficFactorB12Calculator, + PolicyMultiplierB13Calculator +) +from app.utils.calculation_engine.cultural_value_b2 import CulturalValueB2Calculator +from app.utils.calculation_engine.cultural_value_b2.sub_formulas import ( + LivingHeritageB21Calculator, + PatternGeneB22Calculator +) +from app.utils.calculation_engine.risk_adjustment_b3 import RiskAdjustmentB3Calculator +from app.utils.calculation_engine.market_value_c import MarketValueCCalculator +from app.utils.calculation_engine.market_value_c.sub_formulas import ( + MarketBiddingC1Calculator, + HeatCoefficientC2Calculator, + ScarcityMultiplierC3Calculator, + TemporalDecayC4Calculator +) +from app.utils.calculation_engine.final_value_ab import FinalValueACalculator + +__version__ = "1.0.0" +__author__ = "Assessment Team" + +__all__ = [ + # 经济价值B1模块 + "EconomicValueB1Calculator", + "BasicValueB11Calculator", + "TrafficFactorB12Calculator", + "PolicyMultiplierB13Calculator", + + # 文化价值B2模块 + "CulturalValueB2Calculator", + "LivingHeritageB21Calculator", + "PatternGeneB22Calculator", + + # 风险调整系数B3模块 + "RiskAdjustmentB3Calculator", + + # 市场估值C模块 + "MarketValueCCalculator", + "MarketBiddingC1Calculator", + "HeatCoefficientC2Calculator", + "ScarcityMultiplierC3Calculator", + "TemporalDecayC4Calculator", + + + # 最终估值A模块 + "FinalValueACalculator" +] diff --git a/app/utils/calculation_engine/cultural_value_b2/sub_formulas/living_heritage_b21.py b/app/utils/calculation_engine/cultural_value_b2/sub_formulas/living_heritage_b21.py index 3101604..6c096cb 100644 --- a/app/utils/calculation_engine/cultural_value_b2/sub_formulas/living_heritage_b21.py +++ b/app/utils/calculation_engine/cultural_value_b2/sub_formulas/living_heritage_b21.py @@ -6,7 +6,6 @@ """ -from typing import List diff --git a/app/utils/calculation_engine/final_value_ab/__init__.py b/app/utils/calculation_engine/final_value_ab/__init__.py new file mode 100644 index 0000000..c9f4cff --- /dev/null +++ b/app/utils/calculation_engine/final_value_ab/__init__.py @@ -0,0 +1,18 @@ +""" +最终估值A计算包 + +最终估值A = 模型估值B × 0.7 + 市场估值C × 0.3 + + +``` + + +""" + +from .final_value_a import FinalValueACalculator + +__all__ = [ + "FinalValueACalculator" +] + + diff --git a/app/utils/calculation_engine/final_value_ab/final_value_a.py b/app/utils/calculation_engine/final_value_ab/final_value_a.py new file mode 100644 index 0000000..d6717c6 --- /dev/null +++ b/app/utils/calculation_engine/final_value_ab/final_value_a.py @@ -0,0 +1,166 @@ + +""" +最终估值A计算模块 +最终估值A = 模型估值B × 0.7 + 市场估值C × 0.3 + +""" + +from typing import Dict +import os +import sys + +current_dir = os.path.dirname(os.path.abspath(__file__)) +project_root = os.path.abspath(os.path.join(current_dir, os.pardir, os.pardir, os.pardir, os.pardir)) +if project_root not in sys.path: + sys.path.append(project_root) + +try: + # 包内相对导入 + from .model_value_b import ModelValueBCalculator + from ..market_value_c import MarketValueCCalculator +except ImportError: + # 直接运行时的绝对导入 + from app.utils.calculation_engine.final_value_ab.model_value_b import ModelValueBCalculator + from app.utils.calculation_engine.market_value_c import MarketValueCCalculator + + +class FinalValueACalculator: + """最终估值A计算器""" + + def __init__(self): + """初始化计算器""" + self.model_value_calculator = ModelValueBCalculator() + self.market_value_calculator = MarketValueCCalculator() + + def calculate_final_value_a(self, + model_value_b: float, + market_value_c: float) -> float: + """ + 计算最终估值A + + + 最终估值A = 模型估值B × 0.7 + 市场估值C × 0.3 + + model_value_b: 模型估值B (系统计算) + market_value_c: 市场估值C (系统计算) + + float: 最终估值A + """ + + final_value = model_value_b * 0.7 + market_value_c * 0.3 + + return final_value + + def calculate_complete_final_value_a(self, input_data: Dict) -> Dict: + """ + 计算完整的最终估值A，包含所有子模块 + + input_data: 输入数据字典，包含所有必要的参数 + + + 包含所有中间计算结果和最终结果的字典 + """ + # 计算模型估值B + model_result = self.model_value_calculator.calculate_complete_model_value_b( + input_data['model_data'] + ) + model_value_b = model_result['model_value_b'] + + # 计算市场估值C + market_result = self.market_value_calculator.calculate_complete_market_value_c( + input_data['market_data'] + ) + market_value_c = market_result['market_value_c'] + + # 计算最终估值A + final_value_a = self.calculate_final_value_a( + model_value_b, + market_value_c + ) + + return { + 'model_value_b': model_value_b, + 'market_value_c': market_value_c, + 'final_value_ab': final_value_a, + } + + + +# 示例使用 +if __name__ == "__main__": + # 创建计算器实例 + calculator = FinalValueACalculator() + + # 示例数据 + input_data = { + # 模型估值B相关数据 + 'model_data': { + 'economic_data': { + # 基础价值B11相关参数 + 'three_year_income': [1000, 2000, 2222], + 'patent_score': 1, # 专利分 (0-10) + 'popularity_score': 4.0, # 普及地域分 (0-10) + 'infringement_score': 1.0, # 侵权分 (0-10) + 'innovation_ratio': 600.0, # 创新投入比 (×100) + 'esg_score': 10.0, # ESG分 (0-10) + 'patent_count':0.8, + 'industry_coefficient': 12.0, + + # 流量因子B12相关参数 + 'search_index_s1': 4500.0, + 'industry_average_s2': 5000.0, + 'likes': 4, + 'comments': 5, + 'shares': 6, + + # 政策乘数B13相关参数 + 'policy_match_score': 10.0, + 'implementation_stage': 10.0, + 'funding_support': 10.0 + }, + 'cultural_data': { + # 活态传承系数B21相关参数（教学频次由以下数据计算） + 'inheritor_level_coefficient': 10.0, + 'cross_border_depth': 7.0, + 'offline_sessions': 1, + 'douyin_views': 2, + 'kuaishou_views': 3, + 'bilibili_views': 4, + + # 纹样基因值B22相关参数 + 'structure_complexity': 0.75, + 'normalized_entropy': 0.85, + 'historical_inheritance': 0.80 + }, + 'risky_data': { + # 风险调整系数B3相关参数 + 'highest_price': 100.0, + 'lowest_price': 95.0, + 'lawsuit_status': '无诉讼', + 'inheritor_ages': [45, 60, 75] + } + }, + + # 市场估值C相关数据 + 'market_data': { + 'average_transaction_price': 50000.0, + 'manual_bids': [48000.0, 50000.0, 52000.0], + 'expert_valuations': [49000.0, 51000.0, 50000.0], + 'daily_browse_volume': 500.0, + 'collection_count': 50, + 'issuance_level': '限量', + 'recent_market_activity': '2024-01-15' + } + } + + # 计算最终估值A + result = calculator.calculate_complete_final_value_a(input_data) + + + + print("最终估值A计算结果:") + print(f"模型估值B: {result['model_value_b']:.2f}") + print(f"市场估值C: {result['market_value_c']:.2f}") + print(f"最终估值A: {result['final_value_ab']:.2f}") + + diff --git a/app/utils/calculation_engine/final_value_ab/model_value_b.py b/app/utils/calculation_engine/final_value_ab/model_value_b.py new file mode 100644 index 0000000..9c572af --- /dev/null +++ b/app/utils/calculation_engine/final_value_ab/model_value_b.py @@ -0,0 +1,127 @@ + +""" +模型估值B计算模块 + +模型估值B = （经济价值B1*0.7+文化价值B2*0.3）*风险调整系数B3 +""" + +from typing import Dict + +from app.utils.calculation_engine import RiskAdjustmentB3Calculator + +try: + # 相对导入（当作为包使用时） + from ..economic_value_b1.economic_value_b1 import EconomicValueB1Calculator + from ..cultural_value_b2.cultural_value_b2 import CulturalValueB2Calculator +except ImportError: + # 绝对导入（当直接运行时） + from app.utils.calculation_engine.economic_value_b1.economic_value_b1 import EconomicValueB1Calculator + from app.utils.calculation_engine.cultural_value_b2.cultural_value_b2 import CulturalValueB2Calculator + + +class ModelValueBCalculator: + """模型估值B计算器""" + + def __init__(self): + """初始化计算器""" + self.economic_value_calculator = EconomicValueB1Calculator() + self.cultural_value_calculator = CulturalValueB2Calculator() + self.risk_adjustment_calculator = RiskAdjustmentB3Calculator() + + def calculate_model_value_b(self, + economic_value_b1: float, + cultural_value_b2: float, + risk_value_b3: float) -> float: + """ + 模型估值B = （经济价值B1*0.7+文化价值B2*0.3）*风险调整系数B3 + + Args: + economic_value_b1: 经济价值B1 + cultural_value_b2: 文化价值B2 + risk_value_b3 : 风险调整系数B3 + + Returns: + float: 模型估值B + """ + model_value = (economic_value_b1 * 0.7 + cultural_value_b2 * 0.3) * risk_value_b3 + + return model_value + + def calculate_complete_model_value_b(self, input_data: Dict) -> Dict: + """ + 计算完整的模型估值B，包含所有子公式 + + Args: + input_data: 输入数据字典，包含所有必要的参数 + + Returns: + Dict: 包含所有中间计算结果和最终结果的字典 + """ + # 计算经济价值B1 + economic_result = self.economic_value_calculator.calculate_complete_economic_value_b1( + input_data['economic_data'] + ) + economic_value_b1 = economic_result['economic_value_b1'] + + # 计算文化价值B2 + cultural_result = self.cultural_value_calculator.calculate_complete_cultural_value_b2( + input_data['cultural_data'] + ) + cultural_value_b2 = cultural_result['cultural_value_b2'] + + risk_value_result = self.risk_adjustment_calculator.calculate_complete_risky_value_b3( + input_data['risky_data'] + ) + risk_value_b3 = risk_value_result['risk_adjustment_b3'] + # 计算模型估值B + model_value_b = self.calculate_model_value_b( + economic_value_b1, + cultural_value_b2, + risk_value_b3 + ) + + return { + 'economic_value_b1': economic_value_b1, + 'cultural_value_b2': cultural_value_b2, + 'risk_value_b3': risk_value_b3, + 'model_value_b': model_value_b, + } + + +# 示例使用 +if __name__ == "__main__": + # 创建计算器实例 + calculator = ModelValueBCalculator() + + # 示例数据 + input_data = { + # 经济价值B1相关数据 + 'economic_data': { + 'financial_value': 68.04, + 'legal_strength': 7.90, + 'development_potential': 6.00, + 'industry_coefficient': 0.25, + 'search_index_s1': 4500.0, + 'industry_average_s2': 5000.0, + 'social_media_spread_s3': 1.07, + 'policy_compatibility_score': 9.1 + }, + + # 文化价值B2相关数据 + 'cultural_data': { + 'inheritor_level_coefficient': 10.0, + 'teaching_frequency': 7.0, + 'cross_border_depth': 7.0, + 'structure_complexity': 0.75, + 'normalized_entropy': 0.85, + 'historical_inheritance': 0.80 + } + } + + # 计算模型估值B + result = calculator.calculate_complete_model_value_b(input_data) + + print("模型估值B计算结果:") + print(f"经济价值B1: {result['economic_value_b1']:.2f}") + print(f"文化价值B2: {result['cultural_value_b2']:.4f}") + print(f"模型估值B: {result['model_value_b']:.2f}") diff --git a/app/utils/calculation_engine/market_value_c/market_value_c.py b/app/utils/calculation_engine/market_value_c/market_value_c.py index 2cc5b43..d012b1d 100644 --- a/app/utils/calculation_engine/market_value_c/market_value_c.py +++ b/app/utils/calculation_engine/market_value_c/market_value_c.py @@ -1,4 +1,12 @@ from typing import Dict, List, Optional +import sys +import os + +# 添加当前目录到Python路径，确保能正确导入子模块 +current_dir = os.path.dirname(os.path.abspath(__file__)) +if current_dir not in sys.path: + sys.path.append(current_dir) + try: # 相对导入（当作为包使用时） from .sub_formulas.market_bidding_c1 import MarketBiddingC1Calculator @@ -69,10 +77,10 @@ class MarketValueCCalculator: # 计算市场竞价C1 market_bidding_c1 = self.market_bidding_calculator.calculate_market_bidding_c1( transaction_data={'weighted_average_price': input_data.get('average_transaction_price', 50000.0)}, - manual_bids=[input_data.get('average_transaction_price', 50000.0)], - expert_valuations=[input_data.get('average_transaction_price', 50000.0)] + manual_bids=input_data.get('manual_bids', [input_data.get('average_transaction_price', 50000.0)]), + expert_valuations=input_data.get('expert_valuations', [input_data.get('average_transaction_price', 50000.0)]) ) - + # 计算热度系数C2 heat_coefficient_c2 = self.heat_coefficient_calculator.calculate_heat_coefficient_c2( input_data.get('daily_browse_volume', 500.0), @@ -81,12 +89,12 @@ class MarketValueCCalculator: # 计算稀缺性乘数C3 scarcity_multiplier_c3 = self.scarcity_multiplier_calculator.calculate_scarcity_multiplier_c3( - input_data.get('issuance_level', '限量发行') + input_data.get('issuance_level', '限量') ) # 计算时效性衰减C4 temporal_decay_c4 = self.temporal_decay_calculator.calculate_temporal_decay_c4( - input_data.get('recent_market_activity', '近一月') + input_data.get('recent_market_activity', '2024-01-15') ) # 计算市场估值C @@ -115,21 +123,18 @@ if __name__ == "__main__": input_data = { # 市场竞价C1相关参数 'average_transaction_price': 50000.0, # 平均交易价格 - 'market_activity_coefficient': 0.8, # 市场活跃度系数 + 'manual_bids': [48000.0, 50000.0, 52000.0], # 手动收集的竞价 + 'expert_valuations': [49000.0, 51000.0, 50000.0], # 专家估值 # 热度系数C2相关参数 - 'search_heat': 0.7, # 搜索热度 - 'social_media_heat': 0.6, # 社交媒体热度 - 'media_coverage_heat': 0.5, # 媒体报道热度 + 'daily_browse_volume': 500.0, # 近7日日均浏览量 + 'collection_count': 50, # 收藏数 # 稀缺性乘数C3相关参数 - 'issuance_scarcity': 0.8, # 发行量稀缺性 - 'circulation_scarcity': 0.7, # 流通率稀缺性 - 'uniqueness_scarcity': 0.9, # 独特性稀缺性 + 'issuance_level': '限量', # 资产发行等级 # 时效性衰减C4相关参数 - 'time_decay_coefficient': 0.3, # 时间衰减系数 - 'market_activity_decay': 0.2 # 市场活跃度衰减 + 'recent_market_activity': '2024-01-15' # 最近市场活动时间 } # 计算市场估值C diff --git a/app/utils/calculation_engine/risk_adjustment_b3/sub_formulas/risk_adjustment_b3.py b/app/utils/calculation_engine/risk_adjustment_b3/sub_formulas/risk_adjustment_b3.py index 4592427..6969437 100644 --- a/app/utils/calculation_engine/risk_adjustment_b3/sub_formulas/risk_adjustment_b3.py +++ b/app/utils/calculation_engine/risk_adjustment_b3/sub_formulas/risk_adjustment_b3.py @@ -157,15 +157,15 @@ class RiskAdjustmentB3Calculator: def calculate_complete_risky_value_b3(self, input_data: Dict) -> Dict: # 计算各项风险评分 - market_risk = calculator.calculate_market_risk(input_data[""], input_data["lowest_price"]) - legal_risk = calculator.calculate_legal_risk(input_data["lawsuit_status"]) - inheritance_risk = calculator.calculate_inheritance_risk(input_data["inheritor_ages"]) + market_risk = self.calculate_market_risk(input_data["highest_price"], input_data["lowest_price"]) + legal_risk = self.calculate_legal_risk(input_data["lawsuit_status"]) + inheritance_risk = self.calculate_inheritance_risk(input_data["inheritor_ages"]) # 计算风险评分总和R - risk_score_sum = calculator.calculate_risk_score_sum(market_risk, legal_risk, inheritance_risk) + risk_score_sum = self.calculate_risk_score_sum(market_risk, legal_risk, inheritance_risk) # 计算风险调整系数B3 - risk_adjustment_b3 = calculator.calculate_risk_adjustment_b3(risk_score_sum) + risk_adjustment_b3 = self.calculate_risk_adjustment_b3(risk_score_sum) return { 'risk_score_sum': risk_score_sum, 'risk_adjustment_b3': risk_adjustment_b3