石油焦日度预测,调试完成
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@ -2223,16 +2223,17 @@ def addtimecharacteristics(df, dataset):
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# 从数据库获取百川数据,接收一个百川id列表,返回df格式的数据
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def get_baichuan_data(baichuanidnamedict):
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baichuanidlist = [str(k) for k in baichuanidnamedict.keys()]
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baichuanidlist= [f"'{id}'" for id in baichuanidlist]
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# 连接数据库
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db = config.db_mysql
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db.connect()
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if db is None:
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db.connect()
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# 执行SQL查询 select BAICHUAN_ID,DATA_DATE,DATA_VALUE from V_TBL_BAICHUAN_YINGFU_VALUE where BAICHUAN_ID in ('1588348470396475286','1666');
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sql = f"SELECT BAICHUAN_ID,DATA_DATE,DATA_VALUE FROM {global_config['baichuan_table_name']} WHERE BAICHUAN_ID in ({','.join(baichuanidlist)})"
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# 获取查询结果
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results = db.execute_query(sql)
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formatted_results = [tuple(item) for item in results]
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df = pd.DataFrame(formatted_results, columns=[
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df = pd.DataFrame(results, columns=[
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'BAICHUAN_ID', 'DATA_DATE', 'DATA_VALUE'])
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df['BAICHUAN_ID'] = df['BAICHUAN_ID'].astype('string')
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df.to_csv('百川数据test.csv', index=False)
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@ -32,6 +32,7 @@ global_config.update({
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'modelsindex': modelsindex,
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'rote': rote,
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'bdwd_items': bdwd_items,
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'baichuanidnamedict': baichuanidnamedict,
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# 特征工程开关
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'is_del_corr': is_del_corr,
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@ -429,16 +430,8 @@ def predict_main():
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logger.info('制作报告end')
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logger.info('模型训练完成')
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# push_market_value()
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push_market_value()
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# # LSTM 单变量模型
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# ex_Lstm(df,input_seq_len=input_size,output_seq_len=horizon,is_debug=is_debug,dataset=dataset)
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# # lstm 多变量模型
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# ex_Lstm_M(df,n_days=input_size,out_days=horizon,is_debug=is_debug,datasetpath=dataset)
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# # GRU 模型
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# # ex_GRU(df)
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# 发送邮件
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# m = SendMail(
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2088
百川数据test.csv
Normal file
2088
百川数据test.csv
Normal file
File diff suppressed because it is too large
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