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from __future__ import print_function
from __future__ import division
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
sns.set_context(rc={'figure.figsize': (14, 7) } )
figzize_me = figsize =(14, 7)
import warnings; warnings.filterwarnings('ignore')
import os
import sys
# 使用insert 0即只使用github，避免交叉使用了pip安装的abupy，导致的版本不一致问题
sys.path.insert(0, os.path.abspath('../'))
import abupy
abupy.env.enable_example_env_ipython()
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from abupy import ABuSymbolPd
tsla_df = ABuSymbolPd.make_kl_df('usTSLA', n_folds=2)
tsla_df.tail()
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from abupy import tl
jumps = tl.jump.calc_jump(tsla_df)
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jumps
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# sw[0]代表非时间因素的jump_power，sw[1]代表时间加权因素的jump_power，当sw[0]=1时与非加权方式相同，具体实现请参考源代码
jump_pd = tl.jump.calc_jump_line_weight(tsla_df, sw=(0.5, 0.5))
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tl.wave.calc_wave_abs(tsla_df, xd=21, show=True)
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from abupy import EStoreAbu, abu
abu_result_tuple_train = abu.load_abu_result_tuple(n_folds=5, store_type=EStoreAbu.E_STORE_CUSTOM_NAME,
custom_name='train_cn')
# 只筛选orders中有交易结果的单子
has_result = abu_result_tuple_train.orders_pd[
abu_result_tuple_train.orders_pd.result == -1]
# 随便拿一个交易数据作为示例
sample_order = has_result.ix[100]
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abupy.env.disable_example_env_ipython()
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from abupy import ABuMarketDrawing
_ = ABuMarketDrawing.plot_candle_from_order(sample_order)
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from abupy import nd
nd.macd.plot_macd_from_order(sample_order, date_ext=252)
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nd.boll.plot_boll_from_order(has_result.ix[100], date_ext=252)
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nd.ma.plot_ma_from_order(has_result.ix[100], date_ext=252, time_period=[10, 20, 30, 60, 90, 120])
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