def test_normal_calc_template_deprecated(self):
a = np.array([(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (11, 12),
(13, 14)])
b = np.array([(11, 12), (13, 14), (15, 16), (17, 18), (19, 110),
(111, 112), (113, 114)])
sa = CommonObject(id=3, code='test1', transaction=a)
sb = CommonObject(id=3, code='test2', transaction=b)
dates = np.array([1, 2])
sdata = {'sa': sa, 'sb': sb}
fbuy = lambda x: np.array([1, 0])
fsell = lambda x, y: np.array([0, 1])
ftrade = lambda x, y, z, a: (1, 2)
normal_calc_template_deprecated(sdata, dates, fbuy, fsell, ftrade)
self.assertTrue(True)
#测试异常包容性
def fbuy(x):
raise Exception
se1 = CommonObject(id=3, code='test exception catch 1', transaction=a)
se2 = CommonObject(id=3, code='test exception catch 2', transaction=b)
dates = np.array([1, 2])
edata = {'se1': se1, 'se2': se2}
normal_calc_template_deprecated(edata, dates, fbuy, fsell, ftrade)
self.assertTrue(True)
def test_prepare_catalogs(self): #只测试通路
a = np.array([(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (11, 12),
(13, 14)])
b = np.array([(11, 12), (13, 14), (15, 16), (17, 18), (19, 110),
(111, 112), (113, 114)])
sa = CommonObject(id=3, code='test1', transaction=a)
sb = CommonObject(id=3, code='test2', transaction=b)
sdata = {'sa': sa, 'sb': sb}
ctree, catalogs = prepare_catalogs(sdata)
def get_stocks(codes,begin,end,rid=ref_id): #这里不对is_active进行筛除
#print 'codes:',codes
rev = {}
for code in codes:
sid = code2id[code]
logger.debug('loading stock:%s' % code)
#print code
vo = CDO(id=sid,code=code)
vo.transaction = tuple2array(store.get_refbased_xquotes(get_connection(),ref_id,sid,begin,end))
#t:transaction,d:data,g:global,c:catalog?
rev[sid] = vo
return rev
def test_calc_last(self):
a = np.array([(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (11, 12),
(13, 14)])
b = np.array([(11, 12), (13, 14), (15, 16), (17, 18), (19, 110),
(111, 112), (113, 114)])
sa = CommonObject(id=3, code='test1', transaction=a)
sb = CommonObject(id=3, code='test2', transaction=b)
dates = np.array([1, 2])
sdata = {'sa': sa, 'sb': sb}
fbuy = lambda x: np.array([1, 0])
fsell = lambda x, y: np.array([0, 1])
m = MM_Mediator(fbuy, fsell)
self.assertRaises(NotImplementedError, m.calc_last, sdata, dates)
def test_calc_trades(self):
a = np.array([(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (11, 12),
(13, 14)])
b = np.array([(11, 12), (13, 14), (15, 16), (17, 18), (19, 110),
(111, 112), (113, 114)])
sa = CommonObject(id=3, code='test1', transaction=a)
sb = CommonObject(id=3, code='test2', transaction=b)
sdata = {'sa': sa, 'sb': sb}
dates = np.array([20010101, 20010102])
buyer = lambda x: x.transaction[CLOSE]
name, trades = calc_trades(buyer, atr_seller, sdata, dates, 20010101)
#print name
self.assertTrue(name)
def test_csc_func(self):
a = np.array([(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (11, 12),
(13, 14)])
sa = CommonObject(id=3, transaction=a)
bs = np.array([0, 1])
csc_func(sa, bs)
self.assertTrue(True)
#空测试
a = np.array([(), (), (), (), (), (), ()])
sa = CommonObject(id=3, transaction=a)
bs = np.array([])
csc_func(sa, bs)
self.assertTrue(True)
def test_calc_matched_except(self): #测试异常分支的正确性
def fbuy(s):
raise Exception
a = np.array([(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (11, 12),
(13, 14)])
b = np.array([(11, 12), (13, 14), (15, 16), (17, 18), (19, 110),
(111, 112), (113, 114)])
sa = CommonObject(id=3, code='test1', transaction=a)
sb = CommonObject(id=3, code='test2', transaction=b)
dates = np.array([1, 2])
sdata = {'sa': sa, 'sb': sb}
fsell = lambda x, y: np.array([0, 1])
m = MM_Mediator(fbuy, fsell)
m.calc_matched(sdata, dates)
self.assertTrue(True)
def test_dlimit(self):
dummy = range(45)
a = np.array([dummy, dummy, dummy, dummy, dummy, dummy, dummy, dummy])
b = np.array([dummy, dummy, dummy, dummy, dummy, dummy, dummy, dummy])
sa = CommonObject(id=3, code='test1', transaction=a)
sb = CommonObject(id=3, code='test2', transaction=b)
sdata = {'sa': sa, 'sb': sb}
print sum(a)
self.assertEquals(7920, np.sum(a))
dlimit(sdata.values(), 0)
self.assertEquals(7920, np.sum(a))
dlimit(sdata.values(), 20)
self.assertEquals(7920 + 210 * 5, np.sum(a))
dlimit(sdata.values(), 100)
self.assertEquals(4500 * 5 + 990 * 3, np.sum(a))
self.assertTrue(True)
def test_prepare_gbjg(self): #这里实际上没有测试循环内通道
a = np.array([(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (11, 12),
(13, 14)])
b = np.array([(11, 12), (13, 14), (15, 16), (17, 18), (19, 110),
(111, 112), (113, 114)])
sa = CommonObject(id=3, code='test1', transaction=a)
sb = CommonObject(id=4, code='test2', transaction=b)
sdata = {3: sa, 4: sb}
prepare_gbjg(sdata) #测试stock_id不在sdata数据中
self.assertTrue(True)
sc = CommonObject(id=20, code='test2', transaction=b)
sdata = {3: sa, 4: sb, 20: sc}
prepare_gbjg(sdata) #测试stock_id不在sdata数据中
sdata[20].ag = 500
sdata[20].zgb = 1000
sdata[20].last_date = 200101
def test_calc(self):
a = np.array([(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (11, 12),
(13, 14)])
b = np.array([(11, 12), (13, 14), (15, 16), (17, 18), (19, 110),
(111, 112), (113, 114)])
sa = CommonObject(id=3, code='test1', transaction=a)
sb = CommonObject(id=3, code='test2', transaction=b)
dates = np.array([1, 2])
sdata = {'sa': sa, 'sb': sb}
fbuy = lambda x: np.array([1, 0])
fsell = lambda x, y: np.array([0, 1])
m = NMediator(fbuy, fsell)
m.calc(sdata, dates)
self.assertTrue(True)
#空测试
m.calc_matched({}, np.array([]))
self.assertTrue(True)
def test_mm_batch(self):
dummy = range(45)
a = np.array([dummy, dummy, dummy, dummy, dummy, dummy, dummy, dummy])
b = np.array([dummy, dummy, dummy, dummy, dummy, dummy, dummy, dummy])
sa = CommonObject(id=3, code='test1', transaction=a, atr=dummy)
sb = CommonObject(id=3, code='test2', transaction=b, atr=dummy)
sdata = {'sa': sa, 'sb': sb}
dates = np.arange(20010101, 20010146) #45个采样点，避免在计算CSHARP中线形回归的时候报警
mm_batch([], sdata, dates, 20010101) #空测试
self.assertTrue(True)
buyer = lambda x: np.ones(45, int)
c1 = BaseObject(buyer=buyer, seller=atr_seller, pman=None, dman=None)
c2 = BaseObject(buyer=buyer, seller=atr_seller, pman=None, dman=None)
mm_batch([c1, c2], sdata, dates, 20010101)
self.assertTrue(c1.name)
self.assertEquals(c1.name, c2.name)
self.assertTrue(True)
def test_normal_trade_func_deprecated(self): #只测试通路
a = np.array([(1, 2, 1), (3, 4, 3), (5, 6, 5), (7, 8, 7), (9, 10, 4),
(11, 12, 3), (13, 14, 5)])
sa = CommonObject(id=3, code='TEST', transaction=a)
dates = np.array([1, 2, 3])
sb = np.array([0, 1, 0])
ss = np.array([0, 0, 1])
normal_trade_func_deprecated(dates, sa, sb, ss)
self.assertTrue(True)
def test_trade_func_deprecated(self):
from wolfox.fengine.core.shortcut import _trade_func_deprecated
a = np.array([(1, 2, 1), (3, 4, 3), (5, 6, 5), (7, 8, 7), (9, 10, 4),
(11, 12, 3), (13, 14, 5)])
sa = CommonObject(id=3, code='TEST', transaction=a)
dates = np.array([1, 2, 3])
sb = np.array([0, 1, 0])
ss = np.array([0, 0, 1])
_trade_func_deprecated(dates, sa, sb, ss, prepare_func=B0S0)
self.assertTrue(True)
#空测试
a = np.array([(), (), (), (), (), (), ()])
sa = CommonObject(id=3, code='TEST', transaction=a)
dates = np.array([])
sb = np.array([])
ss = np.array([])
_trade_func_deprecated(dates, sa, sb, ss, prepare_func=B0S0)
self.assertTrue(True)
def test_batch_last(self):
dummy = range(45)
a = np.array([dummy, dummy, dummy, dummy, dummy, dummy, dummy, dummy])
b = np.array([dummy, dummy, dummy, dummy, dummy, dummy, dummy, dummy])
sa = CommonObject(id=3, code='test1', transaction=a)
sb = CommonObject(id=3, code='test2', transaction=b)
sdata = {'sa': sa, 'sb': sb}
dates = np.arange(20010101, 20010146) #45个采样点，避免在计算CSHARP中线形回归的时候报警
batch_last([], sdata, dates, 20010101) #空测试
self.assertTrue(True)
buyer = lambda x: np.ones(45, int)
buyer2 = lambda x: np.ones(40, int)
buyer.__name__ = 'buyer1'
buyer2.__name__ = 'buyer2'
c1 = BaseObject(buyer=buyer, seller=atr_seller)
c2 = BaseObject(buyer=buyer2, seller=atr_seller)
ts = batch_last([c1, c2], sdata, dates, 20010101)
self.assertTrue(True)
def test_batch(self):
dummy = range(45)
a = np.array([dummy, dummy, dummy, dummy, dummy, dummy, dummy, dummy])
b = np.array([dummy, dummy, dummy, dummy, dummy, dummy, dummy, dummy])
sa = CommonObject(id=3, code='test1', transaction=a)
sb = CommonObject(id=3, code='test2', transaction=b)
sdata = {'sa': sa, 'sb': sb}
dates = np.arange(20010101, 20010146) #45个采样点，避免在计算CSHARP中线形回归的时候报警
batch([], sdata, dates, 20010101) #空测试
self.assertTrue(True)
pman = AdvancedPositionManager()
dman = XDateManager(range(20010101, 20010215))
buyer = lambda x: np.ones(45, int)
c1 = BaseObject(buyer=buyer, seller=atr_seller, pman=pman, dman=dman)
c2 = BaseObject(buyer=buyer, seller=atr_seller, pman=pman, dman=dman)
batch([c1, c2], sdata, dates, 20010101)
self.assertTrue(c1.name)
self.assertEquals(c1.name, c2.name)
self.assertTrue(True)
def test_prepare(self):
a = np.array([(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (11, 12),
(13, 14)])
sa = CommonObject(id=3, code='test1', transaction=a)
fbuy = lambda x: np.array([1, 0])
fsell = lambda x, y: np.array([0, 1])
m = Mediator(fbuy, fsell)
#sa.atr = np.array([1000,2000])
m.prepare(sa)
#self.assertEquals([1000,2000],sa.atr.tolist())
self.assertTrue(True)
def test_prepare(self):
a = np.array([(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (11, 12),
(13, 14)])
sa = CommonObject(id=3, code='test1', transaction=a, atr=(100, 200))
fbuy = lambda x: np.array([1, 0])
fsell = lambda x, y: np.array([0, 1])
m = MM_Mediator(fbuy, fsell)
m.prepare(sa)
#self.assertEquals(2,len(sa.atr))
#self.assertEquals([0,0],sa.atr.tolist()) #不到atr cover(默认为20)
self.assertEquals(2, len(sa.mfe))
self.assertEquals(2, len(sa.mae))
def test_merge(self):
pman = AdvancedPositionManager()
dman = XDateManager(range(20010101, 20010215))
dummy = range(45)
a = np.array([dummy, dummy, dummy, dummy, dummy, dummy, dummy, dummy])
b = np.array([dummy, dummy, dummy, dummy, dummy, dummy, dummy, dummy])
sa = CommonObject(id=3, code='test1', transaction=a)
sb = CommonObject(id=3, code='test2', transaction=b)
sdata = {'sa': sa, 'sb': sb}
dates = np.arange(20010101, 20010146) #45个采样点，避免在计算CSHARP中线形回归的时候报警
r1, s1 = merge([], sdata, dates, 20010101, pman, dman) #空测试
self.assertEquals(0, r1.pre_ev.count)
self.assertEquals(0, r1.g_ev.count)
self.assertTrue(True)
buyer = lambda x: np.ones(45, int)
c1 = BaseObject(buyer=buyer, seller=atr_seller, pman=pman, dman=dman)
c2 = BaseObject(buyer=buyer, seller=atr_seller, pman=pman, dman=dman)
r2, s2 = merge([c1, c2], sdata, dates, 20010101, pman, dman)
self.assertEquals(0, r2.pre_ev.count)
self.assertEquals(0, r2.g_ev.count)
self.assertTrue(True)
def test_signals_maker(self):
buyer1 = lambda stock: np.array([0, 1, 1])
buyer2 = lambda stock: np.array([1, 0, 1])
buyer3 = lambda stock: np.array([0, 0, 1])
a = np.array([(1, 2, 1), (1, 3, 4), (1, 5, 6), (1, 7, 8), (1, 9, 10),
(1, 11, 12), (1, 13, 14)])
sa = CommonObject(id=3, transaction=a)
m1 = signals_maker([buyer1, buyer2])
self.assertEquals([1, 1, 1], m1(sa).tolist())
m2 = signals_maker([buyer1, buyer3])
self.assertEquals([0, 1, 1], m2(sa).tolist())
m3 = signals_maker([buyer2, buyer3])
self.assertEquals([1, 0, 1], m3(sa).tolist())
def test__calc(self):
a = np.array([(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (11, 12),
(13, 14)])
b = np.array([(11, 12), (13, 14), (15, 16), (17, 18), (19, 110),
(111, 112), (113, 114)])
sa = CommonObject(id=3, code='test1', transaction=a)
sb = CommonObject(id=3, code='test2', transaction=b)
dates = np.array([1, 2])
sdata = {'sa': sa, 'sb': sb}
fbuy = lambda x: np.array([1, 0])
fsell = lambda x, y: np.array([0, 1])
ftrade = lambda x, y, z, a, c, begin: (1, 2)
m = Mediator(fbuy, fsell)
m._calc(ftrade, sdata, dates)
self.assertTrue(True)
#测试异常包容性
def fbuy(x):
raise Exception('test exception catch')
me = Mediator(fbuy, fsell)
me._calc(ftrade, sdata, dates)
self.assertTrue(True)
def test_names(self):
self.assertEquals((),names())
a,b = CommonObject(id=1),CommonObject(id=2)
a.__name__,b.__name__ = 'af','bf'
self.assertEquals(('af','bf'),names(a,b))
