原油数据处理,最高最低价拼接 调试

This commit is contained in:
workpc 2025-05-29 13:51:14 +08:00
commit 6f3680e4c6
4 changed files with 19 additions and 14 deletions

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@ -364,7 +364,7 @@ table_name = 'v_tbl_crude_oil_warning'
# 开关
is_train = True # 是否训练
is_train = False # 是否训练
is_debug = False # 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

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@ -875,6 +875,13 @@ def datachuli(df_zhibiaoshuju, df_zhibiaoliebiao, datecol='date', end_time='', y
dataset, '特征处理后的指标名称及分类.csv'), index=False)
# 数据频度分析
featurePindu(dataset=dataset)
# 原油最高最低价列误删重新拼接,后面更新最高价最低价用,计算准确率用
if 'Brentzgj' not in df.columns and 'Brentzgj' in df_zhibiaoliebiao.columns:
df['Brentzgj'] = df_zhibiaoliebiao['Brentzgj']
if 'Brentzdj' not in df.columns and 'Brentzdj' in df_zhibiaoliebiao.columns:
df['Brentzdj'] = df_zhibiaoliebiao['Brentzdj']
# 向上填充
df = df.ffill()
# 向下填充
@ -972,7 +979,6 @@ def zhoududatachuli(df_zhibiaoshuju, df_zhibiaoliebiao, datecol='date', end_time
return df
def datachuli_juxiting(df_zhibiaoshuju, df_zhibiaoliebiao, datecol='date', end_time='', y='y', dataset='dataset', delweekenday=False, add_kdj=False, is_timefurture=False):
'''
聚烯烃特征数据处理函数
@ -1165,8 +1171,6 @@ def yuedudatachuli_shiyoujiaolvyong(df_zhibiaoshuju, df_zhibiaoliebiao, datecol=
return df
def getdata(filename, datecol='date', y='y', dataset='', add_kdj=False, is_timefurture=False, end_time=''):
config.logger.info('getdata接收'+filename+' '+datecol+' '+end_time)
# 判断后缀名 csv或excel

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@ -294,15 +294,15 @@ def predict_main():
logger.info(f'要更新y的信息{update_y}')
# try:
for row in update_y.itertuples(index=False):
try:
row_dict = row._asdict()
yy = df[df['ds'] == row_dict['ds']]['y'].values[0]
LOW = df[df['ds'] == row_dict['ds']]['Brentzdj'].values[0]
HIGH = df[df['ds'] == row_dict['ds']]['Brentzgj'].values[0]
sqlitedb.update_data(
'accuracy', f"y = {yy},LOW_PRICE = {LOW},HIGH_PRICE = {HIGH}", where_condition=f"ds = '{row_dict['ds']}'")
except:
logger.info(f'更新accuracy表的y值失败{row_dict}')
# try:
row_dict = row._asdict()
yy = df[df['ds'] == row_dict['ds']]['y'].values[0]
LOW = df[df['ds'] == row_dict['ds']]['Brentzdj'].values[0]
HIGH = df[df['ds'] == row_dict['ds']]['Brentzgj'].values[0]
sqlitedb.update_data(
'accuracy', f"y = {yy},LOW_PRICE = {LOW},HIGH_PRICE = {HIGH}", where_condition=f"ds = '{row_dict['ds']}'")
# except:
# logger.info(f'更新accuracy表的y值失败{row_dict}')
# except Exception as e:
# logger.info(f'更新accuracy表的y值失败{e}')

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@ -19,6 +19,7 @@ global_config.update({
'is_update_report': is_update_report,
'settings': settings,
'bdwdname': bdwdname,
'columnsrename': columnsrename,
# 模型参数