diff --git a/app/api/v1/app_valuations/app_valuations.py b/app/api/v1/app_valuations/app_valuations.py index 6bd45df..2bd7c4f 100644 --- a/app/api/v1/app_valuations/app_valuations.py +++ b/app/api/v1/app_valuations/app_valuations.py @@ -142,6 +142,7 @@ async def _perform_valuation_calculation(user_id: int, data: UserValuationCreate "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) @@ -346,7 +347,7 @@ async def _extract_calculation_params_b1(data: UserValuationCreate) -> Dict[str, # 行业均值S2 - 从数据库查询行业数据计算 from app.utils.industry_calculator import calculate_industry_average_s2 industry_average_s2 = await calculate_industry_average_s2(data.industry) - # 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 + # 社交媒体传播度S3 # likes: 点赞数(API获取) # comments: 评论数(API获取) # shares: 转发数(API获取) @@ -434,10 +435,11 @@ async def _extract_calculation_params_b2(data: UserValuationCreate) -> Dict[str, # 纹样基因值B22相关参数 # 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 - + # 历史传承度HI(用户填写) historical_inheritance = sum([safe_float(i) for i in data.historical_evidence]) - structure_complexity = 0.75 - normalized_entropy = 0.85 + structure_complexity = 0.75 # TODO 需要依赖图片和模型 结构复杂度SC(系统计算) + normalized_entropy = 0.85 # TODO 需要依赖图片和模型 归一化信息熵H(系统计算) + return { "inheritor_level_coefficient": inheritor_level_coefficient, "offline_sessions": offline_sessions, @@ -477,16 +479,17 @@ async def _extract_calculation_params_c(data: UserValuationCreate) -> Dict[str, # TODO 需要客户确认 三个数值 expert_valuations = 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) + daily_browse_volume = 500.0 # 近7日日均浏览量(默认占位) 是否 使用该商品近12个月的链接浏览量？？？ + collection_count = 50 # 收藏数(默认占位) 无 # 稀缺性乘数C3 发行量 - circulation = data.circulation or '限量' + circulation = data.scarcity_level 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 - recent_market_activity = data.last_market_activity + recent_market_activity = data.market_activity_time # 如果为空、None或"0"，设置默认值 if not recent_market_activity or recent_market_activity == "0": - recent_market_activity = '2024-01-15' + # recent_market_activity = '2024-01-15' + recent_market_activity = '近一月' return { # 计算市场竞价C1 # C1 的实现接受 transaction_data={'weighted_average_price': x} diff --git a/app/schemas/valuation.py b/app/schemas/valuation.py index 643ffe8..361c2b9 100644 --- a/app/schemas/valuation.py +++ b/app/schemas/valuation.py @@ -24,7 +24,7 @@ class ValuationAssessmentBase(BaseModel): heritage_level: Optional[str] = Field(None, description="非遗等级") heritage_asset_level: Optional[str] = Field(None, description="非遗资产等级") patent_application_no: Optional[str] = Field(None, description="非遗资产所用专利的申请号") - patent_remaining_years: Optional[str] = Field(None, description="专利剩余年限") + patent_remaining_years: Optional[str] = Field(None, description="专利剩余年限") # 未使用 historical_evidence: Optional[Dict[str, int]] = Field(None, description="非遗资产历史证明证据及数量") patent_certificates: Optional[List[str]] = Field(None, description="非遗资产所用专利的证书") pattern_images: Optional[List[str]] = Field(None, description="非遗纹样图片") @@ -37,7 +37,7 @@ class ValuationAssessmentBase(BaseModel): cooperation_depth: Optional[str] = Field(None, description="非遗资产跨界合作深度") collaboration_type: Optional[str] = Field(None, description="非遗资产跨界合作深度") offline_activities: Optional[str] = Field(None, description="近12个月线下相关宣讲活动次数") - offline_teaching_count: Optional[int] = Field(None, description="近12个月线下相关演讲活动次数") + offline_teaching_count: Optional[int] = Field(None, description="近12个月线下相关演讲活动次数") # 未使用 online_accounts: Optional[List[Any]] = Field(None, description="线上相关宣传账号信息") platform_accounts: Optional[Dict[str, Dict[str, Union[str, int]]]] = Field(None, description="线上相关宣传账号信息") @@ -51,8 +51,8 @@ class ValuationAssessmentBase(BaseModel): monthly_transaction: Optional[str] = Field(None, description="月交易额") monthly_transaction_amount: Optional[str] = Field(None, description="月交易额") price_fluctuation: Optional[List[Union[str, int, float]]] = Field(None, description="该商品近30天价格波动区间") - price_range: Optional[Dict[str, Union[int, float]]] = Field(None, description="资产商品的价格波动率") - market_price: Optional[Union[int, float]] = Field(None, description="市场价格（单位：万元）") + price_range: Optional[Dict[str, Union[int, float]]] = Field(None, description="资产商品的价格波动率") # 未使用 + market_price: Optional[Union[int, float]] = Field(None, description="市场价格（单位：万元）") # 未使用 # 内置API计算字段 infringement_record: Optional[str] = Field(None, description="侵权记录") 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 index d6717c6..8e72b1f 100644 --- a/app/utils/calculation_engine/final_value_ab/final_value_a.py +++ b/app/utils/calculation_engine/final_value_ab/final_value_a.py @@ -8,7 +8,7 @@ from typing import Dict import os import sys - +from app.log.log import logger 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: @@ -46,8 +46,20 @@ class FinalValueACalculator: float: 最终估值A """ + logger.info("final_value_a.calculate_final_value_a 开始计算最终估值A: 模型估值B={}万元 市场估值C={}万元", + model_value_b, market_value_c) - final_value = model_value_b * 0.7 + market_value_c * 0.3 + # 计算加权值 + model_weighted = model_value_b * 0.7 + market_weighted = market_value_c * 0.3 + + logger.info("final_value_a.weighted_values 加权计算: 模型估值B加权值={}万元(权重0.7) 市场估值C加权值={}万元(权重0.3)", + model_weighted, market_weighted) + + final_value = model_weighted + market_weighted + + logger.info("final_value_a.final_calculation 最终估值A计算: 模型估值B={}万元 市场估值C={}万元 模型加权值={}万元 市场加权值={}万元 最终估值AB={}万元", + model_value_b, market_value_c, model_weighted, market_weighted, final_value) return final_value @@ -60,23 +72,125 @@ class FinalValueACalculator: 包含所有中间计算结果和最终结果的字典 """ + import time + start_time = time.time() + + # 记录输入参数 + logger.info("final_value_a.calculation_start input_data_keys={} model_data_keys={} market_data_keys={}", + list(input_data.keys()), + list(input_data.get('model_data', {}).keys()), + list(input_data.get('market_data', {}).keys())) + + # 详细记录模型数据参数 + model_data = input_data.get('model_data', {}) + if 'economic_data' in model_data: + economic_data = model_data['economic_data'] + logger.info("final_value_a.economic_data 经济价值B1参数: 近三年机构收益={} 专利分={} 普及地域分={} 侵权分={} 创新投入比={} ESG分={} 专利使用量={} 行业修正系数={}", + economic_data.get('three_year_income'), + economic_data.get('patent_score'), + economic_data.get('popularity_score'), + economic_data.get('infringement_score'), + economic_data.get('innovation_ratio'), + economic_data.get('esg_score'), + economic_data.get('patent_count'), + economic_data.get('industry_coefficient')) + + if 'cultural_data' in model_data: + cultural_data = model_data['cultural_data'] + logger.info("final_value_a.cultural_data 文化价值B2参数: 传承人等级系数={} 跨境深度={} 线下教学次数={} 抖音浏览量={} 快手浏览量={} 哔哩哔哩浏览量={} 结构复杂度={} 归一化信息熵={} 历史传承度={}", + cultural_data.get('inheritor_level_coefficient'), + cultural_data.get('cross_border_depth'), + cultural_data.get('offline_sessions'), + cultural_data.get('douyin_views'), + cultural_data.get('kuaishou_views'), + cultural_data.get('bilibili_views'), + cultural_data.get('structure_complexity'), + cultural_data.get('normalized_entropy'), + cultural_data.get('historical_inheritance')) + + if 'risky_data' in model_data: + risky_data = model_data['risky_data'] + logger.info("final_value_a.risky_data 风险调整B3参数: 最高价={} 最低价={} 诉讼状态={} 传承人年龄={}", + risky_data.get('highest_price'), + risky_data.get('lowest_price'), + risky_data.get('lawsuit_status'), + risky_data.get('inheritor_ages')) + + # 详细记录市场数据参数 + market_data = input_data.get('market_data', {}) + logger.info("final_value_a.market_data 市场估值C参数: 平均交易价={} 手动出价={} 专家估值={} 日浏览量={} 收藏数量={} 发行等级={} 最近市场活动={}", + market_data.get('average_transaction_price'), + market_data.get('manual_bids'), + market_data.get('expert_valuations'), + market_data.get('daily_browse_volume'), + market_data.get('collection_count'), + market_data.get('issuance_level'), + market_data.get('recent_market_activity')) + # 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'] + logger.info("final_value_a.calculating_model_value_b 开始计算模型估值B") + model_start_time = time.time() + + try: + model_result = self.model_value_calculator.calculate_complete_model_value_b( + input_data['model_data'] + ) + model_value_b = model_result['model_value_b'] + model_duration = time.time() - model_start_time + + logger.info("final_value_a.model_value_b_calculated 模型估值B计算完成: 模型估值B={}万元 耗时={}ms 返回字段={}", + model_value_b, + int(model_duration * 1000), + list(model_result.keys())) + + except Exception as e: + logger.error("final_value_a.model_value_b_calculation_failed 模型估值B计算失败: 错误={} 输入数据={}", str(e), input_data.get('model_data', {})) + raise # 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'] + logger.info("final_value_a.calculating_market_value_c 开始计算市场估值C") + market_start_time = time.time() + + try: + market_result = self.market_value_calculator.calculate_complete_market_value_c( + input_data['market_data'] + ) + market_value_c = market_result['market_value_c'] + market_duration = time.time() - market_start_time + + logger.info("final_value_a.market_value_c_calculated 市场估值C计算完成: 市场估值C={}万元 耗时={}ms 返回字段={}", + market_value_c, + int(market_duration * 1000), + list(market_result.keys())) + + except Exception as e: + logger.error("final_value_a.market_value_c_calculation_failed 市场估值C计算失败: 错误={} 输入数据={}", str(e), input_data.get('market_data', {})) + raise # 计算最终估值A - final_value_a = self.calculate_final_value_a( - model_value_b, - market_value_c - ) + logger.info("final_value_a.calculating_final_value_a 开始计算最终估值A: 模型估值B={}万元 市场估值C={}万元", + model_value_b, market_value_c) + + try: + final_value_a = self.calculate_final_value_a( + model_value_b, + market_value_c + ) + + # 记录最终计算结果 + total_duration = time.time() - start_time + logger.info("final_value_a.calculation_completed 最终估值A计算完成: 最终估值AB={}万元 模型估值B={}万元 市场估值C={}万元 总耗时={}ms 模型计算耗时={}ms 市场计算耗时={}ms", + final_value_a, + model_value_b, + market_value_c, + int(total_duration * 1000), + int(model_duration * 1000), + int(market_duration * 1000)) + + except Exception as e: + logger.error("final_value_a.final_value_calculation_failed 最终估值A计算失败: 错误={} 模型估值B={}万元 市场估值C={}万元", + str(e), model_value_b, market_value_c) + raise return { 'model_value_b': model_value_b, @@ -149,7 +263,7 @@ if __name__ == "__main__": 'daily_browse_volume': 500.0, 'collection_count': 50, 'issuance_level': '限量', - 'recent_market_activity': '2024-01-15' + 'recent_market_activity': '近一月' } } diff --git a/app/utils/calculation_engine/market_value_c/sub_formulas/market_bidding_c1.py b/app/utils/calculation_engine/market_value_c/sub_formulas/market_bidding_c1.py index 0a5f447..ccd0a3b 100644 --- a/app/utils/calculation_engine/market_value_c/sub_formulas/market_bidding_c1.py +++ b/app/utils/calculation_engine/market_value_c/sub_formulas/market_bidding_c1.py @@ -61,15 +61,7 @@ if __name__ == "__main__": transaction_volume = 500 # 交易量 (API获取) transaction_frequency = "中频" # 交易频率 (用户填写) market_liquidity = "中" # 市场流动性 (用户填写) - - # 获取平均交易价格 - average_transaction_price = calculator.get_average_transaction_price(asset_type, time_period) - - # 计算市场活跃度系数 - market_activity_coefficient = calculator.calculate_market_activity_coefficient( - transaction_volume, transaction_frequency, market_liquidity - ) - + # 示例数据 # 优先级1：近3个月交易数据 transaction_data = {"weighted_average_price": 1000.0} # API获取 diff --git a/app/utils/calculation_engine/market_value_c/sub_formulas/scarcity_multiplier_c3.py b/app/utils/calculation_engine/market_value_c/sub_formulas/scarcity_multiplier_c3.py index fa5ea79..824f9b9 100644 --- a/app/utils/calculation_engine/market_value_c/sub_formulas/scarcity_multiplier_c3.py +++ b/app/utils/calculation_engine/market_value_c/sub_formulas/scarcity_multiplier_c3.py @@ -50,8 +50,11 @@ class ScarcityMultiplierC3Calculator: "稀有": 0.4, "流通": 0.1 } + for s_key,s_value in scarcity_scores.items(): + if s_key in issuance_level: + return s_value - return scarcity_scores.get(issuance_level, 0.1) + return 0.1 # 示例使用 diff --git a/app/utils/calculation_engine/market_value_c/sub_formulas/temporal_decay_c4.py b/app/utils/calculation_engine/market_value_c/sub_formulas/temporal_decay_c4.py index 8fdb7c7..3dd9b65 100644 --- a/app/utils/calculation_engine/market_value_c/sub_formulas/temporal_decay_c4.py +++ b/app/utils/calculation_engine/market_value_c/sub_formulas/temporal_decay_c4.py @@ -30,7 +30,7 @@ class TemporalDecayC4Calculator: "其他": 0.1 } - return timeliness_coefficients.get(self.classify_date_distance(time_elapsed), 0.1) + return timeliness_coefficients.get(time_elapsed, 0.1) @staticmethod def classify_date_distance(target_date): """