def jieba_initialize(self):
#结巴可以添加两个词典，是add过程
log_exp.debug('initialize jieba vocab...')
jieba.load_userdict(project_path() + '/resource/segDic/others.txt')
jieba.load_userdict(project_path() +
'/resource/segDic/THUOCL_caijing.txt')
# jieba.load_userdict(utils.project_path() + '/resource/segDic/vocab.txt') # 当前词典很多和其他词典覆盖的地方，不能直接用
self.stopwords = {
line.strip()
for line in open(
project_path() +
'/resource/segDic/stop_words.txt', 'r').readlines()
}
jieba.initialize()
def get_data(data_name='bitfinex_dataETHUSD.h5',rule_type = '15T'):
'''
读取数据
:return:
'''
# 导入数据
all_data = pd.read_hdf(utils.project_path()+'/data/'+data_name, key='data')
# 转换数据周期
all_data = evaluate.transfer_to_period_data(all_data, rule_type)
# 选取时间段
all_data = all_data[all_data['candle_begin_time'] >= pd.to_datetime('2018-11-01')]
all_data.reset_index(inplace=True, drop=True)
return all_data
def write_2_file_hdf5(kData,path='/result/default.h5'):
'''
读写h5文件
:param kData:df
:param path:
:param is_read:
:return:
'''
path_t = utils.project_path()+path
# HDF5的写入：
# 压缩格式存储
h5 = pd.HDFStore(path_t, 'w', complevel=4, complib='blosc')
h5['data'] = kData
h5.close()
utils.log_exp.info('写入完成')
log_exp.debug('持多仓信号为%d,当前信号为%d, 继续做多！', state[1], flag)
elif state[1] == -2: # 迁移状态为-2
if flag == 0 or flag == 1 or flag == -2:
# ===止损：涨幅达到一定量就平
if ((df_copy.loc[index, 'close'] -
df_copy.loc[state[0], 'close']) /
df_copy.loc[state[0], 'close']) > self.th4:
df_sell.loc[index, 'signal_sell'] = -20
state = (0, 0, -20) # 平仓掉了之前的状态
else: # 智能止盈，由下往上穿越中线并达到波动量则平仓
if (df_copy.loc[index, 'bbPb'] <=
0.5) and (df_copy.loc[index - 1, 'bbPb'] > 0.5):
df_sell.loc[index, 'signal_sell'] = -20
state = (0, 0, -20) # 平仓掉了之前的状态
elif flag == 2 or flag == -1: # 【穿越下线的两种形态】
log_exp.debug('持空仓信号为%d,当前信号为%d, 继续做空！', state[1], flag)
pass
return state
if __name__ == '__main__':
para_now = [90, 3.2, 0.04, 0.05, 1.4, 0.15]
data = pd.read_excel(utils.project_path() + '/excel_output.xls',
sheet_name='src')
# 计算交易信号
ins = BollingAdvanced()
df = ins.signal_bolling(data, para=para_now)
pass
def __init__(self, db_file):
"""
:param db: 数据库文件链接, 默认 在datacache文件夹下
"""
self.db = project_path() + '/datacache/' + db_file
import pandas as pd
from common import utils
if __name__ == '__main__':
all_data = pd.read_hdf(utils.project_path() +
'/data/next/bitfinex_dataXRPUSD.h5')
#temp_data = pd.read_hdf(utils.project_path()+'/data/bitfinex_dataETH.h5')
all_data.rename(columns={
'开盘时间': 'candle_begin_time',
'开盘价': 'open',
'最高价': 'high',
'最低价': 'low',
'收盘价': 'close',
'交易数量': 'volume'
},
inplace=True)
all_data.drop(['交易品种'], axis=1, inplace=True)
all_data.reset_index(inplace=True, drop=True)
# 压缩格式存储
h5 = pd.HDFStore(utils.project_path() + '/data/bitfinex_dataXRPUSD.h5',
'w',
complevel=4,
complib='blosc')
h5['data'] = all_data
h5.close()
pass
async def index(request):
with open(project_path() + '/webUI/templates/search.html', encoding='utf-8') as html_file:
template = Template(html_file.read())
return response.html(template.render(name='index2'))