def recog_history_boll(pl, x, p, code):
"""在历史数据中找到相似的曲线
x : np.ndarray 基准曲线
p : float pearson相似度
"""
df = stock.getFiveHisdatDf(code, method='local')
upper, middle, lower = stock.TDX_BOLL(df['c'].values)
df['upper'] = upper
df = df[-1000:]
#upper = upper[np.isnan(upper) == False]
upper = df['upper'].values
n = 30
report_list = []
x = stock.GuiYiHua(x - np.min(x))
for i in range(0, len(upper) - 30, 2):
y = upper[i:i + n]
assert (len(y) == 30)
y = stock.GuiYiHua(y - np.min(y))
pearson_v = pearson(x, y)
if pearson_v > p:
df2 = pd.DataFrame(x)
df2['2'] = y
df2.plot()
pl.show()
pl.close()
fimg = pl.get_CurImgFname()
report_list.append([code, pearson_v, df.index[i], fimg])
return report_list
def run():
fpath = env.get_root_path()
for code in stock.get_codes():
fname = '/datasources/%s.csv' % (code)
fname = fpath + fname
df = stock.getFiveHisdatDf(code)
df.to_csv(fname)
def watch_four():
"""观察当前数据源的four情况"""
from autoxd.pinyin import stock_pinyin3 as jx
code = jx.ZXJT
df = stock.getFiveHisdatDf(code, method='tdx')
#print(df)
four = stock.FOUR(df['c'].values)
print(four)
from autoxd import ui
from autoxd.pypublish import publish
pl = publish.Publish()
ui.DrawTs(pl, four)
def get_boll_up_base():
"""获取一个用来作为标准的曲线
return : np.ndarray
"""
code = jx.HCGD华灿光电
t = '2018-12-3 10:30:00'
t = '2018-11-30 10:00:00'
key = myredis.gen_keyname(__file__, get_boll_up_base)
df = myredis.createRedisVal(
key, lambda: stock.getFiveHisdatDf(code, method='tdx')).get()
upper, middle, lower = stock.TDX_BOLL(df['c'].values)
df['upper'] = upper
df = df[t:]
df = df[df.index[20]:]
df = df[:df.index[29]]
#ui.DrawTs(pl, df['upper'].values)
#pl.show()
return df['upper'].values
def example2():
"""测试排版输出， 让单元数据在一行内"""
from autoxd import stock
import pandas as pd
print(example2.__doc__)
pl = Publish(explicit=True)
codes = stock.get_codes(flag=stock.myenum.randn, n=6)
result = []
for code in codes:
df_five = stock.getFiveHisdatDf(code, method='tdx')
df_five.plot()
pl.show()
pl.close()
img_name = pl.get_CurImgFname()
result.append([code, img_name, img_name])
df = pd.DataFrame(result)
pl.reset(df_to_html_table(df, df_img_col_indexs=[-2, -1]))
pl.publish()
def _test_horizontal(self):
code = jx.THS
df = stock.getFiveHisdatDf(code)
df = df['2017-5-1':]
df = df['2017-11-1':]
rects = []
bHit = False
for i in range(100, len(df), 5):
cur_df = df[:i]
#bFind, (h,l,left,right) = horizontal(cur_df)
bFind, (h, l, left, right) = Combo(cur_df)
if bFind:
bHit = True
print(cur_df.index[-1], bFind, (h, l, left, right))
left = i + left
right = i
rects.append((h, l, left, right))
if bHit:
ui.drawKlineUseDf(pl, df, rects)
def load_data(code):
df = stock.getFiveHisdatDf(code, method='tdx')
upper, middle, lower = stock.TDX_BOLL(df['c'].values)
df['upper'] = upper
df['middle'] = middle
df['lower'] = lower
highs = pd.Series(df[colname.high]).values
lows = pd.Series(df[colname.low]).values
closes = pd.Series(df[colname.close]).values
adx, pdi, mdi = stock.TDX_ADX2(highs, lows, closes)
df[colname.adx] = adx
df[colname.pdi] = pdi
df[colname.mdi] = mdi
rsi = stock.RSI(closes)
df[colname.rsi] = rsi
return df
def test_AsynDrawKline(self):
from autoxd import stock
code = jx.ZCKJ.b
start_day = '2017-8-25'
#df = stock.getHisdatDataFrameFromRedis(code, start_day)
df = stock.getFiveHisdatDf(code, start_day=start_day, method='tdx')
import account
account = account.LocalAcount(account.BackTesting())
#随机找三个交易点
indexs = agl.GenRandomArray(len(df), 3)
trade_bSell = [0,1,0]
df_trades = df[df.index.map(lambda x: x in df.index[indexs])]
df_trades = df_trades.copy()
df_trades[AsynDrawKline.enum.trade_bSell] = trade_bSell
plt.ion()
for i in range(10):
AsynDrawKline.drawKline(df[i*10:], df_trades)
plt.ioff()
def _test_drawKline2(self):
code = jx.CYJM
start_day = '2017-8-25'
df = stock.getFiveHisdatDf(code, start_day=start_day)
drawKlineUseDf(pl, df)
def _test_DrawZZ(self):
code = '300033'
df_five_hisdat = stock.getFiveHisdatDf(code)
closes = df_five_hisdat['c'][-500:]
zz = stock.ZigZag(closes,percent=1)
DrawDvsAndZZ(pl, closes, zz)
def loadData(self, code):
""" return: df five hisdat"""
data_path = self._getPath()
return stock.getFiveHisdatDf(code, method='path', path=data_path)
