104 lines
3.4 KiB
Python
104 lines
3.4 KiB
Python
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# 读取配置
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from config_jingbo import *
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# from config_tansuanli import *
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from lib.tools import *
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from lib.dataread import *
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from models.nerulforcastmodels import ex_Model,model_losss,brent_export_pdf,tansuanli_export_pdf
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from models.lstmmodels import ex_Lstm_M,ex_Lstm
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from models.grumodels import ex_GRU
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import glob
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import torch
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torch.set_float32_matmul_precision("high")
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if __name__ == '__main__':
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signature = BinanceAPI(APPID, SECRET)
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etadata = EtaReader(signature=signature,
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classifylisturl = classifylisturl,
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classifyidlisturl=classifyidlisturl,
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edbcodedataurl=edbcodedataurl,
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edbcodelist=edbcodelist,
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edbdatapushurl = edbdatapushurl,
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edbdeleteurl = edbdeleteurl,
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edbbusinessurl = edbbusinessurl
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)
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models = [
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'NHITS',
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'Informer',
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'LSTM',
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'iTransformer',
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'TSMixer',
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'TSMixerx',
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'PatchTST',
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'RNN',
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'GRU',
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'TCN',
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'BiTCN',
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'DilatedRNN',
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'MLP',
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'DLinear',
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'NLinear',
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'TFT',
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'FEDformer',
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'StemGNN',
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'MLPMultivariate',
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'TiDE',
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'DeepNPT']
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# eta自由数据指标编码
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modelsindex = {
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'NHITS': 'SELF0000001',
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'Informer':'SELF0000057',
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'LSTM':'SELF0000058',
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'iTransformer':'SELF0000059',
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'TSMixer':'SELF0000060',
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'TSMixerx':'SELF0000061',
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'PatchTST':'SELF0000062',
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'RNN':'SELF0000063',
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'GRU':'SELF0000064',
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'TCN':'SELF0000065',
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'BiTCN':'SELF0000066',
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'DilatedRNN':'SELF0000067',
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'MLP':'SELF0000068',
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'DLinear':'SELF0000069',
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'NLinear':'SELF0000070',
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'TFT':'SELF0000071',
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'FEDformer':'SELF0000072',
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'StemGNN':'SELF0000073',
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'MLPMultivariate':'SELF0000074',
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'TiDE':'SELF0000075',
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'DeepNPT':'SELF0000076'
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}
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# df_predict = pd.read_csv('dataset/predict.csv',encoding='gbk')
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# # df_predict.rename(columns={'ds':'Date'},inplace=True)
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# for m in modelsindex.keys():
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# list = []
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# for date,value in zip(df_predict['ds'],df_predict[m]):
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# list.append({'Date':date,'Value':value})
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# data['DataList'] = list
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# data['IndexCode'] = modelsindex[m]
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# data['IndexName'] = f'价格预测{m}模型'
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# data['Remark'] = m
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# # print(data['DataList'])
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# etadata.push_data(data)
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# 删除指标
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# IndexCodeList = ['SELF0000055']
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# for i in range(1,57):
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# if i < 10 : i = f'0{i}'
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# IndexCodeList.append(f'SELF00000{i}')
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# print(IndexCodeList)
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# etadata.del_zhibiao(IndexCodeList)
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# 删除特定日期的值
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indexcodelist = modelsindex.values()
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for indexcode in indexcodelist:
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data = {
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"IndexCode": indexcode, #指标编码
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"StartDate": "2020-04-20", #指标需要删除的开始日期（>=），如果开始日期和结束日期相等，那么就是删除该日期
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"EndDate": "2024-05-28" #指标需要删除的结束日期（<=），如果开始日期和结束日期相等，那么就是删除该日期
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}
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# etadata.del_business(data)
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