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ump中内部类重构
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@bbfamily
bbfamily committed Oct 23, 2017
1 parent 46e005e commit 20ac4f4
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Showing 18 changed files with 949 additions and 934 deletions.
Empty file modified abupy/MarketBu/ABuSymbol.py
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Empty file modified abupy/MetricsBu/ABuGridSearch.py
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180 changes: 91 additions & 89 deletions abupy/UmpBu/ABuUmpEdgeDeg.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,88 +14,88 @@
__weixin__ = 'abu_quant'


class AbuUmpEdgeDeg(AbuUmpEdgeBase, BuyUmpMixin):
"""边裁走势拟合角度特征类，AbuUmpEdgeBase子类，混入BuyUmpMixin，做为买入ump类"""

class UmpDegFiter(AbuMLPd):
class UmpDegFiter(AbuMLPd):
"""
只需要实现make_xy，且使用ump_edge_make_xy装饰
在边裁__init__中通过：
self.fiter_cls = self.get_fiter_class()
self.fiter = self.fiter_cls(orders_pd=orders_pd, **kwarg)
构造裁判的filter以及重要的self.fiter.df，即pd.DataFrame对象特征
"""

@ump_edge_make_xy
def make_xy(self, **kwarg):
"""
make_xy通过装饰器ump_edge_make_xy进行包装，调用make_xy前将有交易结果的单子进行筛选：
order_has_ret = orders_pd[orders_pd['result'] != 0]，且赋予self.order_has_ret
make_xy只需要使用filter选取需要的特征，即从self.order_has_ret中使用filter选取特征列形成df
:param kwarg: ump_edge_make_xy装饰器中使用kwarg
kwargs['orders_pd'] 做为必须要有的关键字参数：交易训练集数据，pd.DataFrame对象
:return: self.order_has_ret中使用filter选取特征列形成deg_df
ump_edge_make_xy装饰器在make_xy返回deg_df后做转换matrix，形成x，y等工作
"""
内部类，只需要实现make_xy，且使用ump_edge_make_xy装饰

在边裁__init__中通过：
self.fiter_cls = self.get_fiter_class()
self.fiter = self.fiter_cls(orders_pd=orders_pd, **kwarg)
构造裁判的filter以及重要的self.fiter.df，即pd.DataFrame对象特征
filter_list = ['profit', 'profit_cg']
cols = AbuFeatureDeg().get_feature_ump_keys(ump_cls=AbuUmpEdgeDeg)
# filter_list: ['profit', 'profit_cg', 'buy_deg_ang42', 'buy_deg_ang252', 'buy_deg_ang60', 'buy_deg_ang21']
filter_list.extend(cols)

# noinspection PyUnresolvedReferences
deg_df = self.order_has_ret.filter(filter_list)
"""
eg: deg_df
profit profit_cg buy_deg_ang42 buy_deg_ang252 \
2014-09-24 -22618.04 -0.0566 3.378 3.458
2014-10-24 -29690.28 -0.0742 0.191 2.889
2014-10-29 18959.19 0.0542 -2.026 16.689
2014-10-29 148209.36 0.5022 -3.427 -11.956
2014-10-29 24867.60 0.0952 -2.915 39.469
2014-10-29 18959.19 0.0542 -2.026 16.689
2014-11-03 1250.80 0.0045 0.103 39.202
2014-11-11 59888.21 0.1857 8.341 -9.450
2014-11-12 -3578.78 -0.0140 3.963 6.595
2014-11-26 -29085.19 -0.0946 14.052 6.061
... ... ... ... ...
2016-03-14 16220.57 0.0559 4.002 -10.559
2016-03-14 -25328.12 -0.1218 0.129 -6.649
2016-03-30 -29858.44 -0.0863 13.121 -8.461
2016-04-04 5373.76 0.0244 4.409 -33.097
2016-04-13 -28044.40 -0.1159 6.603 -31.459
2016-04-14 -18645.93 -0.0467 4.611 18.428
2016-04-15 -32484.79 -0.1149 4.238 -13.247
2016-04-15 -32484.79 -0.1149 4.238 -13.247
2016-04-29 290.96 0.0007 1.445 16.266
2016-04-29 290.96 0.0007 1.445 16.266
buy_deg_ang60 buy_deg_ang21
2014-09-24 3.458 1.818
2014-10-24 2.809 -1.089
2014-10-29 -0.761 1.980
2014-10-29 -8.296 6.507
2014-10-29 -6.043 7.046
2014-10-29 -0.761 1.980
2014-11-03 -4.614 10.125
2014-11-11 0.730 12.397
2014-11-12 -7.524 6.671
2014-11-26 7.566 12.494
... ... ...
2016-03-14 -7.992 9.324
2016-03-14 -10.880 5.201
2016-03-30 4.498 4.070
2016-04-04 -6.281 5.618
2016-04-13 0.191 4.457
2016-04-14 3.134 0.733
2016-04-15 4.693 1.162
2016-04-15 4.693 1.162
2016-04-29 4.615 -1.115
2016-04-29 4.615 -1.115
"""
return deg_df

@ump_edge_make_xy
def make_xy(self, **kwarg):
"""
make_xy通过装饰器ump_edge_make_xy进行包装，调用make_xy前将有交易结果的单子进行筛选：
order_has_ret = orders_pd[orders_pd['result'] != 0]，且赋予self.order_has_ret
make_xy只需要使用filter选取需要的特征，即从self.order_has_ret中使用filter选取特征列形成df
:param kwarg: ump_edge_make_xy装饰器中使用kwarg
kwargs['orders_pd'] 做为必须要有的关键字参数：交易训练集数据，pd.DataFrame对象
:return: self.order_has_ret中使用filter选取特征列形成deg_df
ump_edge_make_xy装饰器在make_xy返回deg_df后做转换matrix，形成x，y等工作
"""

filter_list = ['profit', 'profit_cg']
cols = AbuFeatureDeg().get_feature_ump_keys(ump_cls=AbuUmpEdgeDeg)
# filter_list: ['profit', 'profit_cg', 'buy_deg_ang42', 'buy_deg_ang252', 'buy_deg_ang60', 'buy_deg_ang21']
filter_list.extend(cols)

# noinspection PyUnresolvedReferences
deg_df = self.order_has_ret.filter(filter_list)
"""
eg: deg_df
profit profit_cg buy_deg_ang42 buy_deg_ang252 \
2014-09-24 -22618.04 -0.0566 3.378 3.458
2014-10-24 -29690.28 -0.0742 0.191 2.889
2014-10-29 18959.19 0.0542 -2.026 16.689
2014-10-29 148209.36 0.5022 -3.427 -11.956
2014-10-29 24867.60 0.0952 -2.915 39.469
2014-10-29 18959.19 0.0542 -2.026 16.689
2014-11-03 1250.80 0.0045 0.103 39.202
2014-11-11 59888.21 0.1857 8.341 -9.450
2014-11-12 -3578.78 -0.0140 3.963 6.595
2014-11-26 -29085.19 -0.0946 14.052 6.061
... ... ... ... ...
2016-03-14 16220.57 0.0559 4.002 -10.559
2016-03-14 -25328.12 -0.1218 0.129 -6.649
2016-03-30 -29858.44 -0.0863 13.121 -8.461
2016-04-04 5373.76 0.0244 4.409 -33.097
2016-04-13 -28044.40 -0.1159 6.603 -31.459
2016-04-14 -18645.93 -0.0467 4.611 18.428
2016-04-15 -32484.79 -0.1149 4.238 -13.247
2016-04-15 -32484.79 -0.1149 4.238 -13.247
2016-04-29 290.96 0.0007 1.445 16.266
2016-04-29 290.96 0.0007 1.445 16.266
buy_deg_ang60 buy_deg_ang21
2014-09-24 3.458 1.818
2014-10-24 2.809 -1.089
2014-10-29 -0.761 1.980
2014-10-29 -8.296 6.507
2014-10-29 -6.043 7.046
2014-10-29 -0.761 1.980
2014-11-03 -4.614 10.125
2014-11-11 0.730 12.397
2014-11-12 -7.524 6.671
2014-11-26 7.566 12.494
... ... ...
2016-03-14 -7.992 9.324
2016-03-14 -10.880 5.201
2016-03-30 4.498 4.070
2016-04-04 -6.281 5.618
2016-04-13 0.191 4.457
2016-04-14 3.134 0.733
2016-04-15 4.693 1.162
2016-04-15 4.693 1.162
2016-04-29 4.615 -1.115
2016-04-29 4.615 -1.115
"""
return deg_df

class AbuUmpEdgeDeg(AbuUmpEdgeBase, BuyUmpMixin):
"""边裁走势拟合角度特征类，AbuUmpEdgeBase子类，混入BuyUmpMixin，做为买入ump类"""

def get_predict_col(self):
"""
Expand All @@ -109,7 +109,7 @@ def get_fiter_class(self):
边裁特征走势拟合角度返回的AbuMLPd子类：AbuUmpEdgeDeg.UmpDegFiter
:return: AbuUmpEdgeDeg.UmpDegFiter
"""
return AbuUmpEdgeDeg.UmpDegFiter
return UmpDegFiter

@classmethod
def class_unique_id(cls):
Expand All @@ -121,25 +121,27 @@ def class_unique_id(cls):
return 'deg_edge'


class UmpExtendEdgeFiter(AbuMLPd):
"""角度边裁扩展类make_xy"""
@ump_edge_make_xy
def make_xy(self, **kwarg):
filter_list = ['profit', 'profit_cg']
col = AbuFeatureDegExtend().get_feature_ump_keys(ump_cls=AbuUmpEegeDegExtend)
filter_list.extend(col)
mul_df = self.order_has_ret.filter(filter_list)
return mul_df


class AbuUmpEegeDegExtend(AbuUmpEdgeBase, BuyUmpMixin):
"""边裁使用新的视角来决策交易，AbuUmpEdgeBase子类，混入BuyUmpMixin，做为买入ump类"""

class UmpExtendEdgeFiter(AbuMLPd):
@ump_edge_make_xy
def make_xy(self, **kwarg):
filter_list = ['profit', 'profit_cg']
col = AbuFeatureDegExtend().get_feature_ump_keys(ump_cls=AbuUmpEegeDegExtend)
filter_list.extend(col)
mul_df = self.order_has_ret.filter(filter_list)
return mul_df

def get_predict_col(self):
# 这里使用get_feature_ump_keys，只需要传递当前类名称即可，其根据是买入ump还是卖出ump返回对应特征列
col = AbuFeatureDegExtend().get_feature_ump_keys(ump_cls=AbuUmpEegeDegExtend)
return col

def get_fiter_class(self):
return AbuUmpEegeDegExtend.UmpExtendEdgeFiter
return UmpExtendEdgeFiter

@classmethod
def class_unique_id(cls):
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