def tq_prVar(qx): print('\nobj:qx') zt.xobjPr(qx) # print('\nzsys.xxx') print(' rdat0,', zsys.rdat0) print(' rdatCN,', zsys.rdatCN) print(' rdatCNX,', zsys.rdatCNX) print(' rdatInx,', zsys.rdatInx) print(' rdatMin0,', zsys.rdatMin0) print(' rdatTick,', zsys.rdatTick) # print('\ncode list:', qx.stkCodeLst) print(' inx list:', qx.inxCodeLst) # zt.prx('stk info', qx.wrkStkInfo) zt.prx('inx info', qx.wrkInxInfo) zt.prx('wrkStkDat', qx.wrkStkDat.tail()) # zt.prx('btTimLst', qx.btTimLst) zt.prx('usrPools', qx.usrPools) #用户股票池资产数据 字典格式 print('\nusrMoney,usrTotal:', qx.usrMoney, qx.usrTotal) # tq_prTrdlib(qx)
这种因为版本变化,引发的程序代码冲突,称为:版本冲突 所以,使用开源软件,要养成多动手搜索/查看最新版本的软件文档/函数接口餐宿 ''') #----------------- #1 print('\n#1,set.sys') pd.set_option('display.width', 450) pd.set_option('display.float_format', zt.xfloat3) rlog = '/ailib/log_tmp' if os.path.exists(rlog): tf.gfile.DeleteRecursively(rlog) #2.1 print('\n#2.1,读取数据') rss, fsgn, ksgn = '/ailib/TDS/', 'TDS2_zz500', 'avg' xlst = zsys.TDS_xlst9 zt.prx('xlst', xlst) num_in, num_out = len(xlst), 1 print('\nnum_in,num_out:', num_in, num_out) # df_train, df_test, x_train, y_train, x_test, y_test = zdat.frd_TDS( rss, fsgn, ksgn, xlst) print('\ndf_test.tail()') print(df_test.tail()) print('\nx_train.shape,', x_train.shape) print('\ntype(x_train),', type(x_train)) # #2.2 print('\n#2.2,转换数据格式shape') rxn, txn = x_train.shape[0], x_test.shape[0]
print('\n#8.2 display_monthly_return') m1=perf[xcod].display_monthly_returns() print(m1) print('\n#8.3 xcod.stats') m2=perf[xcod].stats print(m2) #9 print('\n#9 r2') ret = df.to_log_returns().dropna() r2=ret.calc_mean_var_weights().as_format('.2%') print(r2) #======== # zt.prx('df.describe()',df.describe()) # dfq=qx.trdLib zt.prx('qx.trdLib.describe()',qx.trdLib.describe()) zt.prx('qx.trdLib',qx.trdLib.tail()) ''' ret: 165.75 % '''
import zpd_talib as zta # # #------------------------------------ #1 print('\n#1,set.sys') pd.set_option('display.width', 450) pd.set_option('display.float_format', zt.xfloat3) #2 print('\n#2,读取数据') fss = 'data/df_mlp020.csv' df = pd.read_csv(fss) zt.prx('df', df.tail()) # #3 print('\n#3 整理数据') df2 = df[df.y_pred > 0] zt.prx('df2', df2.tail()) print('\ndf.num,', len(df.index)) print('\ndf2.num,', len(df2.index)) #4 print('\n#4 acc准确度分析') print('\nky0=10') dacc, dfx, a10 = ztq.ai_acc_xed2ext(df2.y, df2.y_pred, ky0=10, fgDebug=True) print('\nky0=5')
import zpd_talib as zta # # #------------------------------------ #1 print('\n#1,set.sys') pd.set_option('display.width', 450) pd.set_option('display.float_format', zt.xfloat3) #2 print('\n#2,读取数据') fss = 'data/df_lstm020typ.csv' df = pd.read_csv(fss) zt.prx('df', df.tail()) # #3 print('\n#3 整理数据') df2 = df[df.y_pred > 0] zt.prx('df2', df2.tail()) print('\ndf.num,', len(df.index)) print('\ndf2.num,', len(df2.index)) #4 print('\n#4 acc准确度分析') print('\nky0=10') dacc, dfx, a10 = ztq.ai_acc_xed2ext(df2.y, df2.y_pred, ky0=10, fgDebug=True) print('\nky0=5')
#6 save.var print('\n#6,save.var') fss = ftg0 + 'x1.pkl' zt.f_varWr(fss, qx) qx = zt.f_varRd(fss) #ztq.tq_prVar(qx) #-----------step #2,BT-main # 7 print('\n#7 bt-main') qx = zbt.bt_main(qx) # ztq.tq_prWrk(qx) zt.prx('\nusrPools', qx.usrPools) #-------------- #8 print('\n#8 qx.rw') fss = ftg0 + 'x2.pkl' zt.f_varWr(fss, qx) qx = zt.f_varRd(fss) # #-----------step #3,ret-mini #9 print('\n#9 ret') # print('\n#9.1 tq_prTrdlib') ztq.tq_prTrdlib(qx) zt.prx('userPools', qx.usrPools)
#----------------- # #------------------------------------ #1 print('\n#1,set.sys') pd.set_option('display.width', 450) pd.set_option('display.float_format', zt.xfloat3) rlog = '/ailib/log_tmp' if os.path.exists(rlog): tf.gfile.DeleteRecursively(rlog) #2.1 print('\n#2.1,读取数据') rss, fsgn, ksgn = '/ailib/TDS/', 'TDS2_sz50', 'avg' xlst = zsys.TDS_xlst9 zt.prx('xlst', xlst) # df_train, df_test, x_train, y_train, x_test, y_test = zdat.frd_TDS( rss, fsgn, ksgn, xlst) # df_train, df_test, y_train, y_test = zdat.df_xed_xtyp2x(df_train, df_test, '3', k0=99.5, k9=100.5) y_train, y_test = pd.get_dummies(df_train['y']).values, pd.get_dummies( df_test['y']).values # typ_lst = y_train[0] num_in, num_out = len(xlst), len(typ_lst)
def tq_prWrk(qx): print('\n\t bt_main_1day,', qx.wrkStkCod, qx.wrkTimStr) # zt.prx('stk info', qx.wrkStkInfo) zt.prx('inx info', qx.wrkInxInfo) zt.prx('wrkStkDat.head', qx.wrkStkDat.head(10)) zt.prx('wrkStkDat.tail', qx.wrkStkDat.tail(10)) # zt.prx('btTimLst', qx.btTimLst) zt.prx('usrPools', qx.usrPools) #用户股票池资产数据 字典格式 print('\nusrMoney,usrTotal:', qx.usrMoney, qx.usrTotal) # #zt.prx('qx.trdLib',qx.trdLib.head()) #zt.prx('qx.trdLib',qx.trdLib.tail()) tq_prTrdlib(qx, 30)