def test():
pl = publish.Publish()
base_boll_up = get_boll_up_base()
base_boll_lower = get_boll_lower_base()
def get_data():
code = jx.HCGD
df = tdx.getFive(code)
return df
key = myredis.gen_keyname(__file__, Recognize_boll.test)
df = myredis.createRedisVal(key, get_data).get()
df = stock.TDX_BOLL_df(df)
for i in range(60, len(df)):
df_cur = df[:i]
c = Recognize_boll(base_boll_up, df_cur)
c2 = Recognize_boll(base_boll_lower, df_cur)
b = c._calc_beta_up()
b2 = c._calc_beta_lower()
#if c2.is_matched():
#print(b2)
if abs(c.sign()) > 0 or abs(c2.sign()) > 0:
df_cur = df_cur[['c', 'boll_up', 'boll_mid', 'boll_lower']]
df_cur.index = range(len(df_cur))
df_cur.plot()
pl.show()
def get_data(code):
"""
return: df ['o', 'c', 'h', 'l', 'upper', 'middle', 'lower']"""
#df = load_data(code)
#myredis.delkey(myredis.gen_keyname(__file__, get_data))
df = myredis.createRedisVal(myredis.gen_keyname(__file__, get_data),
lambda: load_data(code)).get()
size = len(df)
if size > g_scope_len:
index = gen_random_int(0, size - g_scope_len)
df = load_data_at_point(df, index, length=g_scope_len)
return df
def combin_cur_dir(sub_dir):
"""组合目录
当前执行文件的目录作为根目录, 支持多进程
sub_dir: 当前执行文件下的子目录, 前面不带/
return: 绝对路径
"""
key = myredis.gen_keyname(__file__, combin_cur_dir)
enter_file = sys.argv[0]
root_dir = os.path.dirname(os.path.abspath(enter_file))
if root_dir.lower().find('multisubprocess') >= 0:
root_dir = myredis.get_obj(key)
else:
myredis.set_obj(key, root_dir)
return root_dir + '/' + sub_dir
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 getData():
def get():
from autoxd.warp_pytdx import getFive
from autoxd.pinyin import stock_pinyin3 as jx
code = jx.HWWH
df = getFive(code)
df = stock.TDX_BOLL_df(df)
return df
def getLocal():
import pandas as pd
fname = '../datas/002304.csv'
df = pd.read_csv(fname)
df.index = pd.DatetimeIndex( df[df.columns[0]])
df = stock.TDX_BOLL_df(df)
return df
key = myredis.gen_keyname(__file__, getData)
#myredis.delkey(key)
return myredis.createRedisVal(key, getLocal).get()
def test_recog_history_boll():
from pypublish import publish
pl = publish.Publish(explicit=True)
code = jx.ZCKJ.b
def get_local_codes():
data_path = 'cnn_boll/datasources/'
return np.array([str(f).split('.')[0] for f in os.listdir(data_path)])
from sklearn.utils import shuffle
key = myredis.gen_keyname(__file__, test_recog_history_boll)
codes = myredis.createRedisVal(key, get_local_codes).get()
code = shuffle(codes)[0]
#ui.DrawTs(pl, x)
#x = get_boll_up_base()
x = get_boll_lower_base()
p = 0.75
#report = ['init', pl.get_CurImgFname()]
report = recog_history_boll(pl, x, p, code)
pl.RePublish(report)
