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)
