def testSecurityMovingRank(self):
window = 10
mq = SecurityMovingRank(window, ['close'])
for i in range(len(self.aapl['close'])):
data = dict(aapl=dict(close=self.aapl['close'][i],
open=self.aapl['open'][i]),
ibm=dict(close=self.ibm['close'][i],
open=self.ibm['open'][i]))
mq.push(data)
if i < window:
start = 0
else:
start = i + 1 - window
if i < 1:
continue
value = mq.value
for name in value.index():
con = self.dataSet[name]['close'][start:(i + 1)]
sorted_con = sorted(con)
expected = sorted_con.index(self.dataSet[name]['close'][i])
calculated = value[name]
self.assertAlmostEqual(
expected, calculated, 12, 'at index {0}\n'
'expected: {1:.12f}\n'
'calculated: {2:.12f}'.format(i, expected, calculated))
def testSecurityMovingRank(self):
window = 100
mr = SecurityMovingRank(window, 'x')
for i in range(len(self.aapl['close'])):
data = {
'aapl': {
'y': self.aapl['close'][i],
'x': self.aapl['open'][i]
},
'ibm': {
'y': self.ibm['close'][i],
'x': self.ibm['open'][i]
}
}
mr.push(data)
if i >= window - 1:
for name in mr.value.index():
series_x = getattr(self,
name)['open'][i - window + 1:i + 1]
expected_res = np.argsort(series_x.argsort())[-1]
self.assertAlmostEqual(mr.value[name], expected_res, msg= \
"at index {0} and symbol {1}\n"
"expected: {2}\n"
"calculated: {3}".format(i, name, expected_res, mr.value[name]))
def testSecurityMovingRankPickle(self):
ma = SecurityMovingRank(10, 'x')
data = dict(aapl=dict(x=1., y=2), ibm=dict(x=2., y=3))
data2 = dict(aapl=dict(x=2., y=3), ibm=dict(x=3., y=4))
ma.push(data)
ma.push(data2)
with tempfile.NamedTemporaryFile('w+b', delete=False) as f:
pickle.dump(ma, f)
with open(f.name, 'rb') as f2:
pickled = pickle.load(f2)
os.unlink(f.name)
for i, v in enumerate(np.random.rand(20)):
data['aapl']['x'] = v
data['aapl']['y'] = v + 0.1
data['ibm']['x'] = v + 0.1
data['ibm']['y'] = v + 0.2
ma.push(data)
pickled.push(data)
if i >= 10:
for name in ma.value.index():
self.assertAlmostEqual(ma.value[name], pickled.value[name])
def testSecurityMovingRankDeepcopy(self):
ma = SecurityMovingRank(10, 'x')
data = dict(aapl=dict(x=1., y=2), ibm=dict(x=2., y=3))
data2 = dict(aapl=dict(x=2., y=3), ibm=dict(x=3., y=4))
ma.push(data)
ma.push(data2)
copied = copy.deepcopy(ma)
for i, v in enumerate(np.random.rand(20)):
data['aapl']['x'] = v
data['aapl']['y'] = v + 0.1
data['ibm']['x'] = v + 0.1
data['ibm']['y'] = v + 0.2
ma.push(data)
copied.push(data)
if i >= 10:
for name in ma.value.index():
self.assertAlmostEqual(ma.value[name], copied.value[name])
def MRANK(window, x='x'):
return SecurityMovingRank(window, x)
def RANK(window, dependency='x'):
return SecurityMovingRank(window, dependency)