def _getCodes(self):
codes = stock.get_codes()
#codes = codes.tolist()
#codes = [x for x in codes if x[0]=='3']
#codes = ['300244','300033','300032','002695']
#codes.append('510050')
return codes
def main_run():
cpu_num = 1
codes = stock.get_codes(stock.myenum.randn, cpu_num)
#agl.startDebug()
if agl.IsDebug():
codes = [jx.HCGD]
exec(agl.Marco.IMPLEMENT_MULTI_PROCESS)
def Test3():
import stock
codes = stock.get_codes()
#codes = codes[:10]
print(
SerialMgr.serialAuto(stock.Guider.getDf,
codes, ('', ''),
restart=True))
def BackTesting():
p = backtest_runner.BackTestPolicy()
codes = stock.get_codes()
codes = [u'002440']
p.SetStockCodes(codes)
backtesting = backtest_policy.Backtest()
backtesting.createAccount(account_type=None, username=None, pwd=None)
p.Regist(Strategy(backtesting, is_backtesting=True))
p.Run('2014-11-1', '2014-12-10')
def test_strategy():
codes = stock.get_codes(flag=myenum.randn, n=4)
cpu_num = 2
#codes = ['300434']
agl.startDebug()
if agl.IsDebug():
codes = [jx.ZCKJ.b]
#backtest_policy.MultiProcessRun(cpu_num, codes, Run, __file__)
exec(agl.Marco.IMPLEMENT_MULTI_PROCESS)
def SelectCodes():
df_year = stock.THS().df_year
df_year = df_year.ix['2010':'2016']
#历史平均市盈率小于25且净利润逐年上升
codes = stock.get_codes()
codes = jbm.find_avg_syl(codes, df_year, 25)
df_year = df_year[df_year['code'].map(lambda x: x in codes)]
codes = jbm.find_jll_increase(df_year)
#codes = agl.array_shuffle(codes)
#max_row = min(len(codes)-1, 5)
return codes
def test_strategy(self):
codes = stock.DataSources.getCodes()
cpu_num = 5
codes = stock.get_codes(stock.myenum.randn, cpu_num * 2)
agl.startDebug()
if agl.IsDebug():
codes = [codes[0]]
codes = [jx.XRSW]
#codes = ['000001']
codes = [jx.THS]
exec agl.Marco.IMPLEMENT_MULTI_PROCESS
def test_find_avg_syl(self):
#统计历史平均市盈率小于某值的个数
scopre = [10, 15, 20, 30]
nums = []
codes = stock.get_codes()
#codes = ['300033']
df_jll = stock.THS().df_year
for v in scopre:
cur_codes = find_avg_syl(codes, df_jll, syl=v)
print len(cur_codes)
nums.append(len(cur_codes))
ui.bar(pl, scopre, nums)
def recog_boll(pl, report_list):
import stock_pinyin as jx
codes = [jx.HCGD, jx.HYGY]
codes = stock.get_codes(stock.myenum.randn, 2)
#import tushare_handle as th
up1 = get_upper(codes[0])
up2 = get_upper(codes[1])
#print(len(up1), len(up2))
n = 30
a = up1[-n:]
b = up2[-n:]
a = stock.GuiYiHua(a - np.min(a))
b = stock.GuiYiHua(b - np.min(b))
v = pearson(a, b)
df = pd.DataFrame(a)
df['2'] = b
df.plot()
pl.show()
fimg = pl.get_CurImgFname()
report_list.append([v, fimg])
def _getCodes(self):
return stock.get_codes()
def testCreate(self):
codes = stock.get_codes(myenum.randn, 10)
codes = [u'002072']
for code in codes:
genOne(code)
def getAllFenshi():
for code in stock.get_codes():
genOne(code)
if not os.path.isdir(img_path):
os.mkdir(img_path)
def getData(code):
df = stock.getFiveHisdatDf(code)
upper, middle, lower = stock.TDX_BOLL(df['c'].values)
return upper, middle, lower, df
def gen_fname(code,index, df):
t = str(df.index[index])
t1 = t.replace(' ', '_')
t1 = t1.replace(':', '_')
fname = code +'_'+ t1+'.png'
return fname
def load_img(code):
datas = getData(code)
df = datas[-1]
if len(df)<200:
return
for index in range(200,len(df),2):
judge_boll_sign.drawfig(index, datas)
fname = gen_fname(code, index, df)
fname = img_path + fname
pl.savefig(fname)
#pl.show()
init()
for code in stock.get_codes(stock.myenum.randn, 10):
load_img(code)
