def get_result_path():
cur_dir = get_root_path()
dir_path = 'datas/' + MyCode.get() + '/'
cur_dir += '/'
cur_dir += dir_path
agl.createDir(cur_dir)
return cur_dir
def save_result(df):
fname = get_result_mid_csv_path()
cur_dir = os.path.dirname(fname)
print(cur_dir)
agl.createDir(cur_dir)
assert(os.path.exists(cur_dir))
df.to_csv(fname)
def main():
code = stock.get_codes(stock.myenum.randn, 1)[0]
points = []
df_result = pd.DataFrame([])
for i, df in enumerate(mydata(code)):
df_result, sign = find_trade_pos(df, df_result, code, i)
if sign:
points.append(i)
#print(points)
fname = 'out/myadx_%s.csv' % (code)
agl.createDir(os.path.dirname(os.path.abspath(fname)))
df_result.to_csv(fname)
#查看信号出现的概率
x = np.arange(len(mydata(code)))
y = np.zeros(len(x))
y[points] = 1
pl.scatter(x, y)
pl.show()
#统计出现的概率
print(len(points) / len(x))
count = 0
for i in range(1, len(points)):
if points[i] - points[i - 1] > 1:
count += 1
print(count)
def genImgToFile(code):
"""产生图形到文件
"""
datas = load_data()
# indexs: list 数据偏移索引
df = pd.read_csv(get_result_csv_path(), index_col=0)
indexs = df['datas_index'].values
cur_dir = get_root_path()
fname = cur_dir + '/img_labels/imgs'
if not os.path.exists(fname):
agl.createDir(fname)
for i in indexs:
i = int(i)
fname1 =fname + '/%s_%d.png'%(code, i)
print(fname1)
pl.figure
draw(datas[i])
pl.savefig(fname1)
pl.close()