def testSecurityValueHolderWithGetItemUseInt(self):
shift = 2
benchmark = SecurityShiftedValueHolder(
SecurityLatestValueHolder(dependency='close'), shift)
testValueHolder = SecurityLatestValueHolder(dependency='close')[shift]
for i in range(len(self.datas['aapl']['close'])):
data = {
'aapl': {
Factors.CLOSE: self.datas['aapl'][Factors.CLOSE][i],
Factors.OPEN: self.datas['aapl'][Factors.OPEN][i]
},
'ibm': {
Factors.CLOSE: self.datas['ibm'][Factors.CLOSE][i],
Factors.OPEN: self.datas['ibm'][Factors.OPEN][i]
}
}
benchmark.push(data)
testValueHolder.push(data)
if i < shift:
continue
calculated = testValueHolder.value
expected = benchmark.value
self.assertEqual(calculated.name_mapping, expected.name_mapping)
np.testing.assert_array_almost_equal(calculated.values,
expected.values)
def testShiftedSecurityValueHolderPickle(self):
tested = SecurityShiftedValueHolder(SecurityLatestValueHolder('close'), 2)
data = dict(aapl=dict(close=1.0),
ibm=dict(close=2.0))
tested.push(data)
data = dict(aapl=dict(close=3.0),
ibm=dict(close=4.0))
tested.push(data)
data = dict(aapl=dict(close=5.0),
ibm=dict(close=6.0))
tested.push(data)
with tempfile.NamedTemporaryFile('w+b', delete=False) as f:
pickle.dump(tested, f)
with open(f.name, 'rb') as f2:
pickled = pickle.load(f2)
expected = tested.value
calcualted = pickled.value
for name in expected.index():
self.assertAlmostEqual(expected[name], calcualted[name])
def testShiftedSecurityValueHolderDeepcopy(self):
tested = SecurityShiftedValueHolder(SecurityLatestValueHolder('close'),
2)
data = dict(aapl=dict(close=1.0), ibm=dict(close=2.0))
tested.push(data)
data = dict(aapl=dict(close=3.0), ibm=dict(close=4.0))
tested.push(data)
data = dict(aapl=dict(close=5.0), ibm=dict(close=6.0))
tested.push(data)
copied = copy.deepcopy(tested)
expected = tested.value
calcualted = copied.value
for name in expected.index():
self.assertAlmostEqual(expected[name], calcualted[name])
def SHIFT(x, n):
return SecurityShiftedValueHolder(x, n)
def SHIFT(dependency, n):
return SecurityShiftedValueHolder(dependency, n)
