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)