diff --git a/config_jingbo.py b/config_jingbo.py index cc2eeb7..5516e65 100644 --- a/config_jingbo.py +++ b/config_jingbo.py @@ -2,7 +2,7 @@ import logging import os import logging.handlers import datetime -from lib.tools import MySQLDB,SQLiteHandler +from lib.tools import MySQLDB, SQLiteHandler # eta 接口token @@ -10,66 +10,65 @@ APPID = "XNLDvxZHHugj7wJ7" SECRET = "iSeU4s6cKKBVbt94htVY1p0sqUMqb2xa" # eta 接口url -sourcelisturl = 'http://10.189.2.78:8108/v1/edb/source/list' +sourcelisturl = 'http://10.189.2.78:8108/v1/edb/source/list' classifylisturl = 'http://10.189.2.78:8108/v1/edb/classify/list?ClassifyType=' uniquecodedataurl = 'http://10.189.2.78:8108/v1/edb/data?UniqueCode=4991c37becba464609b409909fe4d992&StartDate=2024-02-01' classifyidlisturl = 'http://10.189.2.78:8108/v1/edb/list?ClassifyId=' edbcodedataurl = 'http://10.189.2.78:8108/v1/edb/data?EdbCode=' -edbdatapushurl = 'http://10.189.2.78:8108/v1/edb/push' -edbdeleteurl = 'http://10.189.2.78:8108/v1/edb/business/edb/del' -edbbusinessurl = 'http://10.189.2.78:8108/v1/edb/business/data/del' +edbdatapushurl = 'http://10.189.2.78:8108/v1/edb/push' +edbdeleteurl = 'http://10.189.2.78:8108/v1/edb/business/edb/del' +edbbusinessurl = 'http://10.189.2.78:8108/v1/edb/business/data/del' edbcodelist = ['CO1 Comdty', 'ovx index', 'C2404194834', 'C2404199738', 'dxy curncy', 'C2403128043', 'C2403150124', - 'DOESCRUD Index', 'WTRBM1 EEGC Index', 'FVHCM1 INDEX', 'doedtprd index', 'CFFDQMMN INDEX', - 'C2403083739', 'C2404167878', 'C2403250571', 'lmcads03 lme comdty', 'GC1 COMB Comdty', - 'C2404171822','C2404167855', - # 'W000825','W000826','G.IPE', # 美国汽柴油 - # 'S5131019','ID00135604','FSGAM1 Index','S5120408','ID00136724', # 新加坡汽柴油 - ] + 'DOESCRUD Index', 'WTRBM1 EEGC Index', 'FVHCM1 INDEX', 'doedtprd index', 'CFFDQMMN INDEX', + 'C2403083739', 'C2404167878', 'C2403250571', 'lmcads03 lme comdty', 'GC1 COMB Comdty', + 'C2404171822', 'C2404167855', + # 'W000825','W000826','G.IPE', # 美国汽柴油 + # 'S5131019','ID00135604','FSGAM1 Index','S5120408','ID00136724', # 新加坡汽柴油 + ] # 临时写死用指定的列,与上面的edbcode对应，后面更改 edbnamelist = [ - 'ds','y', - 'Brent c1-c6','Brent c1-c3','Brent-WTI','美国商业原油库存', - 'DFL','美国汽油裂解价差','ovx index','dxy curncy','lmcads03 lme comdty', - 'C2403128043','C2403150124','FVHCM1 INDEX','doedtprd index','CFFDQMMN INDEX', - 'C2403083739','C2404167878', - 'GC1 COMB Comdty','C2404167855', + 'ds', 'y', + 'Brent c1-c6', 'Brent c1-c3', 'Brent-WTI', '美国商业原油库存', + 'DFL', '美国汽油裂解价差', 'ovx index', 'dxy curncy', 'lmcads03 lme comdty', + 'C2403128043', 'C2403150124', 'FVHCM1 INDEX', 'doedtprd index', 'CFFDQMMN INDEX', + 'C2403083739', 'C2404167878', + 'GC1 COMB Comdty', 'C2404167855', # 'A汽油价格','W000826','ICE柴油价格', # '新加坡(含硫0.05%) 柴油现货价','柴油：10ppm：国际市场：FOB中间价：新加坡（日）','Bloomberg Commodity Fair Value Singapore Mogas 92 Swap Month 1','97#汽油FOB新加坡现货价','无铅汽油：97#：国际市场：FOB中间价：新加坡（日）' - ] - +] # eta自有数据指标编码 modelsindex = { - 'NHITS': 'SELF0000001', - 'Informer':'SELF0000057', - 'LSTM':'SELF0000058', - 'iTransformer':'SELF0000059', - 'TSMixer':'SELF0000060', - 'TSMixerx':'SELF0000061', - 'PatchTST':'SELF0000062', - 'RNN':'SELF0000063', - 'GRU':'SELF0000064', - 'TCN':'SELF0000065', - 'BiTCN':'SELF0000066', - 'DilatedRNN':'SELF0000067', - 'MLP':'SELF0000068', - 'DLinear':'SELF0000069', - 'NLinear':'SELF0000070', - 'TFT':'SELF0000071', - 'FEDformer':'SELF0000072', - 'StemGNN':'SELF0000073', - 'MLPMultivariate':'SELF0000074', - 'TiDE':'SELF0000075', - 'DeepNPTS':'SELF0000076' - } + 'NHITS': 'SELF0000001', + 'Informer': 'SELF0000057', + 'LSTM': 'SELF0000058', + 'iTransformer': 'SELF0000059', + 'TSMixer': 'SELF0000060', + 'TSMixerx': 'SELF0000061', + 'PatchTST': 'SELF0000062', + 'RNN': 'SELF0000063', + 'GRU': 'SELF0000064', + 'TCN': 'SELF0000065', + 'BiTCN': 'SELF0000066', + 'DilatedRNN': 'SELF0000067', + 'MLP': 'SELF0000068', + 'DLinear': 'SELF0000069', + 'NLinear': 'SELF0000070', + 'TFT': 'SELF0000071', + 'FEDformer': 'SELF0000072', + 'StemGNN': 'SELF0000073', + 'MLPMultivariate': 'SELF0000074', + 'TiDE': 'SELF0000075', + 'DeepNPTS': 'SELF0000076' +} # eta 上传预测结果的请求体，后面发起请求的时候更改 model datalist 数据 data = { - "IndexCode": "", - "IndexName": "价格预测模型", - "Unit": "无", + "IndexCode": "", + "IndexName": "价格预测模型", + "Unit": "无", "Frequency": "日度", "SourceName": f"价格预测", "Remark": 'ddd', @@ -79,32 +78,35 @@ data = { "Value": 333444 } ] - } +} # eta 分类 # level：3才可以获取到数据，所以需要人工把能源化工下所有的level3级都找到 - # url = 'http://10.189.2.78:8108/v1/edb/list?ClassifyId=1214' - #ParentId ":1160, 能源化工 - # ClassifyId ":1214,原油 - #ParentId ":1214,"，就是原油下所有的数据。 -ClassifyId = 1214 +# url = 'http://10.189.2.78:8108/v1/edb/list?ClassifyId=1214' +# ParentId ":1160, 能源化工 +# ClassifyId ":1214,原油 +# ParentId ":1214,"，就是原油下所有的数据。 +ClassifyId = 1214 - -############################################################################################################### 变量定义--测试环境 +# 变量定义--测试环境 server_host = '192.168.100.53' login_pushreport_url = f"http://{server_host}:8080/jingbo-dev/api/server/login" -upload_url = f"http://{server_host}:8080/jingbo-dev/api/analysis/reportInfo/researchUploadReportSave" # 上传报告 -upload_warning_url = f"http://{server_host}:8080/jingbo-dev/api/basicBuiness/crudeOilWarning/save" # 停更预警 -query_data_list_item_nos_url = f"http://{server_host}:8080/jingbo-dev/api/warehouse/dwDataItem/queryDataListItemNos" # 查询数据项编码 -push_data_value_list_url = f"http://{server_host}:8080/jingbo-dev/api/dw/dataValue/pushDataValueList" # 上传数据项值 +# 上传报告 +upload_url = f"http://{server_host}:8080/jingbo-dev/api/analysis/reportInfo/researchUploadReportSave" +# 停更预警 +upload_warning_url = f"http://{server_host}:8080/jingbo-dev/api/basicBuiness/crudeOilWarning/save" +# 查询数据项编码 +query_data_list_item_nos_url = f"http://{server_host}:8080/jingbo-dev/api/warehouse/dwDataItem/queryDataListItemNos" +# 上传数据项值 +push_data_value_list_url = f"http://{server_host}:8080/jingbo-dev/api/dw/dataValue/pushDataValueList" login_data = { "data": { "account": "api_test", # "password": "MmVmNzNlOWI0MmY0ZDdjZGUwNzE3ZjFiMDJiZDZjZWU=", # Shihua@123456 - "password": "ZTEwYWRjMzk0OWJhNTlhYmJlNTZlMDU3ZjIwZjg4M2U=", # 123456 + "password": "ZTEwYWRjMzk0OWJhNTlhYmJlNTZlMDU3ZjIwZjg4M2U=", # 123456 "tenantHashCode": "8a4577dbd919675758d57999a1e891fe", "terminal": "API" }, @@ -113,167 +115,173 @@ login_data = { } upload_data = { - "groupNo":'', # 用户组id - "funcModule":'研究报告信息', - "funcOperation":'上传原油价格预测报告', - "data":{ - "ownerAccount":'arui', #报告所属用户账号 - "reportType":'OIL_PRICE_FORECAST', # 报告类型，固定为OIL_PRICE_FORECAST - "fileName": '2000-40-5-50--100-原油指标数据.xlsx-Brent活跃合约--2024-09-06-15-01-29-预测报告.pdf', #文件名称 - "fileBase64": '' ,#文件内容base64 - "categoryNo":'yyjgycbg', # 研究报告分类编码 - "smartBusinessClassCode":'YCJGYCBG', #分析报告分类编码 - "reportEmployeeCode":"E40116", # 报告人 - "reportDeptCode" :"D0044" ,# 报告部门 - "productGroupCode":"RAW_MATERIAL" # 商品分类 - } + "groupNo": '', # 用户组id + "funcModule": '研究报告信息', + "funcOperation": '上传原油价格预测报告', + "data": { + "ownerAccount": 'arui', # 报告所属用户账号 + "reportType": 'OIL_PRICE_FORECAST', # 报告类型，固定为OIL_PRICE_FORECAST + "fileName": '2000-40-5-50--100-原油指标数据.xlsx-Brent活跃合约--2024-09-06-15-01-29-预测报告.pdf', # 文件名称 + "fileBase64": '', # 文件内容base64 + "categoryNo": 'yyjgycbg', # 研究报告分类编码 + "smartBusinessClassCode": 'YCJGYCBG', # 分析报告分类编码 + "reportEmployeeCode": "E40116", # 报告人 + "reportDeptCode": "D0044", # 报告部门 + "productGroupCode": "RAW_MATERIAL" # 商品分类 + } } warning_data = { - "groupNo":'', # 用户组id - "funcModule":'原油特征停更预警', - "funcOperation":'原油特征停更预警', - "data":{ - 'WARNING_TYPE_NAME':'特征数据停更预警', - 'WARNING_CONTENT':'', - 'WARNING_DATE':'' - } + "groupNo": '', # 用户组id + "funcModule": '原油特征停更预警', + "funcOperation": '原油特征停更预警', + "data": { + 'WARNING_TYPE_NAME': '特征数据停更预警', + 'WARNING_CONTENT': '', + 'WARNING_DATE': '' + } } query_data_list_item_nos_data = { - "funcModule": "数据项", - "funcOperation": "查询", + "funcModule": "数据项", + "funcOperation": "查询", "data": { - "dateStart":"20200101", - "dateEnd":"20241231", - "dataItemNoList":["Brentzdj","Brentzgj"] # 数据项编码,代表 brent最低价和最高价 + "dateStart": "20200101", + "dateEnd": "20241231", + "dataItemNoList": ["Brentzdj", "Brentzgj"] # 数据项编码,代表 brent最低价和最高价 } } push_data_value_list_data = { - "funcModule": "数据表信息列表", - "funcOperation": "新增", + "funcModule": "数据表信息列表", + "funcOperation": "新增", "data": [ - {"dataItemNo":"91230600716676129", - "dataDate":"20230113", - "dataStatus":"add", - "dataValue":100.11 - }, - {"dataItemNo":"91230600716676129P|ETHYL_BEN|CAPACITY", - "dataDate":"20230113", - "dataStatus":"add", - "dataValue":100.55 - }, - {"dataItemNo":"91230600716676129P|ETHYL_BEN|CAPACITY", - "dataDate":"20230113", - "dataStatus":"add", - "dataValue":100.55 - } -] + {"dataItemNo": "91230600716676129", + "dataDate": "20230113", + "dataStatus": "add", + "dataValue": 100.11 + }, + {"dataItemNo": "91230600716676129P|ETHYL_BEN|CAPACITY", + "dataDate": "20230113", + "dataStatus": "add", + "dataValue": 100.55 + }, + {"dataItemNo": "91230600716676129P|ETHYL_BEN|CAPACITY", + "dataDate": "20230113", + "dataStatus": "add", + "dataValue": 100.55 + } + ] } # 八大维度数据项编码 bdwd_items = { - 'ciri' : 'yyycbdwdcr', + 'ciri': 'yyycbdwdcr', 'benzhou': 'yyycbdwdbz', + 'cizhou': 'yyycbdwdcz', + 'gezhou': 'yyycbdwdgz', + 'ciyue': 'yyycbdwdcy', + 'cieryue': 'yyycbdwdcey', + 'cisanyue': 'yyycbdwdcsy', + 'cisiyue': 'yyycbdwdcsiy', } # 北京环境数据库 host = '192.168.101.27' port = 3306 -dbusername ='root' +dbusername = 'root' password = '123456' dbname = 'jingbo_test' table_name = 'v_tbl_crude_oil_warning' -### 开关 -is_train = False # 是否训练 -is_debug = True # 是否调试 -is_eta = True # 是否使用eta接口 -is_market = True # 是否通过市场信息平台获取特征 ,在is_eta 为true 的情况下生效 -is_timefurture = True # 是否使用时间特征 -is_fivemodels = False # 是否使用之前保存的最佳的5个模型 -is_edbcode = False # 特征使用edbcoding列表中的 -is_edbnamelist = False # 自定义特征，对应上面的edbnamelist -is_update_eta = False # 预测结果上传到eta -is_update_report = False # 是否上传报告 -is_update_warning_data = False # 是否上传预警数据 -is_update_predict_value = True # 是否上传预测值到市场信息平台 -is_del_corr = 0.6 # 是否删除相关性高的特征,取值为 0-1 ，0 为不删除，0.6 表示删除相关性小于0.6的特征 -is_del_tow_month = True # 是否删除两个月不更新的特征 - +# 开关 +is_train = False # 是否训练 +is_debug = True # 是否调试 +is_eta = True # 是否使用eta接口 +is_market = True # 是否通过市场信息平台获取特征 ,在is_eta 为true 的情况下生效 +is_timefurture = True # 是否使用时间特征 +is_fivemodels = False # 是否使用之前保存的最佳的5个模型 +is_edbcode = False # 特征使用edbcoding列表中的 +is_edbnamelist = False # 自定义特征，对应上面的edbnamelist +is_update_eta = False # 预测结果上传到eta +is_update_report = False # 是否上传报告 +is_update_warning_data = False # 是否上传预警数据 +is_update_predict_value = True # 是否上传预测值到市场信息平台 +is_del_corr = 0.6 # 是否删除相关性高的特征,取值为 0-1 ，0 为不删除，0.6 表示删除相关性小于0.6的特征 +is_del_tow_month = True # 是否删除两个月不更新的特征 # 连接到数据库 -db_mysql = MySQLDB(host=host, user=dbusername, password=password, database=dbname) +db_mysql = MySQLDB(host=host, user=dbusername, + password=password, database=dbname) db_mysql.connect() -print("数据库连接成功",host,dbname,dbusername) +print("数据库连接成功", host, dbname, dbusername) # 数据截取日期 -start_year = 2020 # 数据开始年份 -end_time = '' # 数据截取日期 格式为 2024-01-01 +start_year = 2020 # 数据开始年份 +end_time = '' # 数据截取日期 格式为 2024-01-01 freq = 'B' # 时间频率，"D": 天 "W": 周"M": 月"Q": 季度"A": 年 "H": 小时 "T": 分钟 "S": 秒 "B": 工作日 -delweekenday = True if freq == 'B' else False # 是否删除周末数据 -is_corr = False # 特征是否参与滞后领先提升相关系数 -add_kdj = False # 是否添加kdj指标 +delweekenday = True if freq == 'B' else False # 是否删除周末数据 +is_corr = False # 特征是否参与滞后领先提升相关系数 +add_kdj = False # 是否添加kdj指标 if add_kdj and is_edbnamelist: - edbnamelist = edbnamelist+['K','D','J'] + edbnamelist = edbnamelist+['K', 'D', 'J'] -### 模型参数 -y = 'Brent连1合约价格' # 原油指标数据的目标变量 Brent连1合约价格 Brent活跃合约 -# y = 'Brent连1合约价格' # 原油指标数据的目标变量 Brent连1合约价格 Brent活跃合约 -horizon =5 # 预测的步长 +# 模型参数 +y = 'Brent连1合约价格' # 原油指标数据的目标变量 Brent连1合约价格 Brent活跃合约 +# y = 'Brent连1合约价格' # 原油指标数据的目标变量 Brent连1合约价格 Brent活跃合约 +horizon = 5 # 预测的步长 input_size = 40 # 输入序列长度 -train_steps = 50 if is_debug else 1000 # 训练步数,用来限定epoch次数 +train_steps = 50 if is_debug else 1000 # 训练步数,用来限定epoch次数 val_check_steps = 30 # 评估频率 -early_stop_patience_steps = 5 # 早停的耐心步数 +early_stop_patience_steps = 5 # 早停的耐心步数 # --- 交叉验证用的参数 test_size = 100 # 测试集大小，定义100，后面使用的时候重新赋值 -val_size = test_size # 验证集大小,同测试集大小 +val_size = test_size # 验证集大小,同测试集大小 -### 特征筛选用到的参数 -k = 100 # 特征筛选数量，如果是0或者值比特征数量大，代表全部特征 -corr_threshold = 0.6 # 相关性大于0.6的特征 -rote = 0.06 # 绘图上下界阈值 +# 特征筛选用到的参数 +k = 100 # 特征筛选数量，如果是0或者值比特征数量大，代表全部特征 +corr_threshold = 0.6 # 相关性大于0.6的特征 +rote = 0.06 # 绘图上下界阈值 -### 计算准确率 -weight_dict = [0.4,0.15,0.1,0.1,0.25] # 权重 +# 计算准确率 +weight_dict = [0.4, 0.15, 0.1, 0.1, 0.25] # 权重 -### 文件 -data_set = '原油指标数据.xlsx' # 数据集文件 -dataset = 'yuanyoudataset' # 数据集文件夹 +# 文件 +data_set = '原油指标数据.xlsx' # 数据集文件 +dataset = 'yuanyoudataset' # 数据集文件夹 # 数据库名称 -db_name = os.path.join(dataset,'jbsh_yuanyou.db') -sqlitedb = SQLiteHandler(db_name) +db_name = os.path.join(dataset, 'jbsh_yuanyou.db') +sqlitedb = SQLiteHandler(db_name) sqlitedb.connect() -settings = f'{input_size}-{horizon}-{train_steps}--{k}-{data_set}-{y}' +settings = f'{input_size}-{horizon}-{train_steps}--{k}-{data_set}-{y}' # 获取日期时间 # now = datetime.datetime.now().strftime('%Y%m%d%H%M%S') # 获取当前日期时间 -now = datetime.datetime.now().strftime('%Y-%m-%d') # 获取当前日期时间 -reportname = f'Brent原油大模型预测--{end_time}.pdf' # 报告文件名 -reportname = reportname.replace(':', '-') # 替换冒号 +now = datetime.datetime.now().strftime('%Y-%m-%d') # 获取当前日期时间 +reportname = f'Brent原油大模型预测--{end_time}.pdf' # 报告文件名 +reportname = reportname.replace(':', '-') # 替换冒号 if end_time == '': end_time = now -### 邮件配置 -username='1321340118@qq.com' -passwd='wgczgyhtyyyyjghi' +# 邮件配置 +username = '1321340118@qq.com' +passwd = 'wgczgyhtyyyyjghi' # recv=['liurui_test@163.com','52585119@qq.com'] -recv=['liurui_test@163.com','jin.wang@chambroad.com'] +recv = ['liurui_test@163.com', 'jin.wang@chambroad.com'] # recv=['liurui_test@163.com'] -title='reportname' -content='brent价格预测报告请看附件' -file=os.path.join(dataset,'reportname') +title = 'reportname' +content = 'brent价格预测报告请看附件' +file = os.path.join(dataset, 'reportname') # file=os.path.join(dataset,'14-7-50--100-原油指标数据.xlsx-Brent连1合约价格--20240731175936-预测报告.pdf') -ssl=True +ssl = True -### 日志配置 +# 日志配置 # 创建日志目录（如果不存在） log_dir = 'logs' @@ -285,8 +293,10 @@ logger = logging.getLogger('my_logger') logger.setLevel(logging.INFO) # 配置文件处理器，将日志记录到文件 -file_handler = logging.handlers.RotatingFileHandler(os.path.join(log_dir, 'pricepredict.log'), maxBytes=1024 * 1024, backupCount=5) -file_handler.setFormatter(logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')) +file_handler = logging.handlers.RotatingFileHandler(os.path.join( + log_dir, 'pricepredict.log'), maxBytes=1024 * 1024, backupCount=5) +file_handler.setFormatter(logging.Formatter( + '%(asctime)s - %(name)s - %(levelname)s - %(message)s')) # 配置控制台处理器，将日志打印到控制台 console_handler = logging.StreamHandler() @@ -297,4 +307,3 @@ logger.addHandler(file_handler) logger.addHandler(console_handler) # logger.info('当前配置：'+settings) - diff --git a/config_jingbo_zhoudu.py b/config_jingbo_zhoudu.py index 913df5c..c0ae644 100644 --- a/config_jingbo_zhoudu.py +++ b/config_jingbo_zhoudu.py @@ -96,6 +96,8 @@ login_pushreport_url = f"http://{server_host}:8080/jingbo-dev/api/server/login" upload_url = f"http://{server_host}:8080/jingbo-dev/api/analysis/reportInfo/researchUploadReportSave" upload_warning_url = f"http://{server_host}:8080/jingbo-dev/api/basicBuiness/crudeOilWarning/save" query_data_list_item_nos_url = f"http://{server_host}:8080/jingbo-dev/api/warehouse/dwDataItem/queryDataListItemNos" +# 上传数据项值 +push_data_value_list_url = f"http://{server_host}:8080/jingbo-dev/api/dw/dataValue/pushDataValueList" login_data = { "data": { @@ -146,6 +148,39 @@ query_data_list_item_nos_data = { } } +push_data_value_list_data = { + "funcModule": "数据表信息列表", + "funcOperation": "新增", + "data": [ + {"dataItemNo": "91230600716676129", + "dataDate": "20230113", + "dataStatus": "add", + "dataValue": 100.11 + }, + {"dataItemNo": "91230600716676129P|ETHYL_BEN|CAPACITY", + "dataDate": "20230113", + "dataStatus": "add", + "dataValue": 100.55 + }, + {"dataItemNo": "91230600716676129P|ETHYL_BEN|CAPACITY", + "dataDate": "20230113", + "dataStatus": "add", + "dataValue": 100.55 + } + ] +} +# 八大维度数据项编码 +bdwd_items = { + 'ciri': 'yyycbdwdcr', + 'benzhou': 'yyycbdwdbz', + 'cizhou': 'yyycbdwdcz', + 'gezhou': 'yyycbdwdgz', + 'ciyue': 'yyycbdwdcy', + 'cieryue': 'yyycbdwdcey', + 'cisanyue': 'yyycbdwdcsy', + 'cisiyue': 'yyycbdwdcsiy', +} + # 北京环境数据库 host = '192.168.101.27' @@ -168,6 +203,7 @@ is_edbnamelist = False # 自定义特征，对应上面的edbnamelist is_update_eta = False # 预测结果上传到eta is_update_report = False # 是否上传报告 is_update_warning_data = False # 是否上传预警数据 +is_update_predict_value = True # 是否上传预测值到市场信息平台 is_del_corr = 0.6 # 是否删除相关性高的特征,取值为 0-1 ，0 为不删除，0.6 表示删除相关性小于0.6的特征 is_del_tow_month = True # 是否删除两个月不更新的特征 diff --git a/main_yuanyou_zhoudu.py b/main_yuanyou_zhoudu.py index ccddeb2..44108a3 100644 --- a/main_yuanyou_zhoudu.py +++ b/main_yuanyou_zhoudu.py @@ -29,6 +29,7 @@ global_config.update({ 'test_size': test_size, 'modelsindex': modelsindex, 'rote': rote, + 'bdwd_items': bdwd_items, # 特征工程开关 'is_del_corr': is_del_corr, @@ -36,6 +37,7 @@ global_config.update({ 'is_eta': is_eta, 'is_update_eta': is_update_eta, 'is_fivemodels': is_fivemodels, + 'is_update_predict_value': is_update_predict_value, 'early_stop_patience_steps': early_stop_patience_steps, # 时间参数 @@ -54,6 +56,10 @@ global_config.update({ 'query_data_list_item_nos_url': query_data_list_item_nos_url, 'query_data_list_item_nos_data': query_data_list_item_nos_data, + # 上传数据项 + 'push_data_value_list_url': push_data_value_list_url, + 'push_data_value_list_data': push_data_value_list_data, + # eta 配置 'APPID': APPID, 'SECRET': SECRET, @@ -65,12 +71,67 @@ global_config.update({ 'edbdatapushurl': edbdatapushurl, 'edbdeleteurl': edbdeleteurl, 'edbbusinessurl': edbbusinessurl, + 'ClassifyId': ClassifyId, 'classifylisturl': classifylisturl, # 数据库配置 'sqlitedb': sqlitedb, }) + +def push_market_value(): + logger.info('发送预测结果到市场信息平台') + # 读取预测数据和模型评估数据 + predict_file_path = os.path.join(config.dataset, 'predict.csv') + model_eval_file_path = os.path.join(config.dataset, 'model_evaluation.csv') + try: + predictdata_df = pd.read_csv(predict_file_path) + top_models_df = pd.read_csv(model_eval_file_path) + except FileNotFoundError as e: + logger.error(f"文件未找到: {e}") + return + + predictdata = predictdata_df.copy() + + # 取模型前十 + top_models = top_models_df['模型(Model)'].head(10).tolist() + + # 计算前十模型的均值 + predictdata_df['top_models_mean'] = predictdata_df[top_models].mean(axis=1) + + # 打印日期和前十模型均值 + print(predictdata_df[['ds', 'top_models_mean']]) + + # 准备要推送的数据 + first_date = predictdata_df['ds'].iloc[0].replace('-', '') + last_date = predictdata_df['ds'].iloc[-1].replace('-', '') + first_mean = predictdata_df['top_models_mean'].iloc[0] + last_mean = predictdata_df['top_models_mean'].iloc[-1] + + predictdata = [ + { + "dataItemNo": global_config['bdwd_items']['cizhou'], + "dataDate": first_date, + "dataStatus": "add", + "dataValue": first_mean + }, + { + "dataItemNo": global_config['bdwd_items']['gezhou'], + "dataDate": last_date, + "dataStatus": "add", + "dataValue": last_mean + } + ] + + print(predictdata) + + # 推送数据到市场信息平台 + try: + push_market_data(predictdata) + except Exception as e: + logger.error(f"推送数据失败: {e}") + + def predict_main(): """ 主预测函数，用于从 ETA 获取数据、处理数据、训练模型并进行预测。 @@ -116,15 +177,15 @@ def predict_main(): logger.info('从eta获取数据...') signature = BinanceAPI(APPID, SECRET) etadata = EtaReader(signature=signature, - classifylisturl=global_config['classifylisturl'], - classifyidlisturl=global_config['classifyidlisturl'], - edbcodedataurl=global_config['edbcodedataurl'], - edbcodelist=global_config['edbcodelist'], - edbdatapushurl=global_config['edbdatapushurl'], - edbdeleteurl=global_config['edbdeleteurl'], - edbbusinessurl=global_config['edbbusinessurl'], - classifyId=global_config['ClassifyId'], - ) + classifylisturl=global_config['classifylisturl'], + classifyidlisturl=global_config['classifyidlisturl'], + edbcodedataurl=global_config['edbcodedataurl'], + edbcodelist=global_config['edbcodelist'], + edbdatapushurl=global_config['edbdatapushurl'], + edbdeleteurl=global_config['edbdeleteurl'], + edbbusinessurl=global_config['edbbusinessurl'], + classifyId=global_config['ClassifyId'], + ) df_zhibiaoshuju, df_zhibiaoliebiao = etadata.get_eta_api_yuanyou_data( data_set=data_set, dataset=dataset) # 原始数据，未处理