def testFilteredSecurityValueHolder(self):
benchmark = SecurityLatestValueHolder(dependency='close') > 0
filtered = FilteredSecurityValueHolder(benchmark, benchmark)
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)
filtered.push(data)
try:
_ = filtered['aapl']
self.assertTrue(benchmark['aapl'])
except KeyError:
self.assertFalse(benchmark['aapl'])
try:
_ = filtered['ibm']
self.assertTrue(benchmark['ibm'])
except KeyError:
self.assertFalse(benchmark['ibm'])
def testFilterSecurityValueHolderWorkWithStr(self):
filter = SecurityLatestValueHolder('code') == 'ibm'
ma = FilteredSecurityValueHolder(SecurityMovingAverage(10, 'close'),
filter)
data = {
'aapl': {
'code': 'aapl',
'close': 15.
},
'ibm': {
'code': 'ibm',
'close': 10.
},
'goog': {
'code': 'goog',
'close': 7.
}
}
ma.push(data)
expected = {'ibm': 10.0}
calculated = ma.value
for name in calculated.index():
self.assertAlmostEqual(expected[name], calculated[name], 15)
def testFilteredSecurityValueHolder(self):
benchmark = SecurityLatestValueHolder(dependency='close') > 0
filtered = FilteredSecurityValueHolder(benchmark, benchmark)
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)
filtered.push(data)
if np.isnan(filtered['aapl']):
self.assertTrue(filtered['aapl'])
if np.isnan(filtered['ibm']):
self.assertTrue(filtered['ibm'])
def testFilteredSecurityValueHolder(self):
benchmark = SecurityLatestValueHolder(dependency='close') > 0
filtered = FilteredSecurityValueHolder(benchmark, benchmark)
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)
filtered.push(data)
if np.isnan(filtered['aapl']):
self.assertTrue(filtered['aapl'])
if np.isnan(filtered['ibm']):
self.assertTrue(filtered['ibm'])
def testGeSecurityValueHolder(self):
filter = SecurityMovingAverage(1, 'close') >= 10.0
ma = FilteredSecurityValueHolder(SecurityMovingAverage(10, 'close'),
filter)
data = {
'aapl': {
'close': 15.
},
'ibm': {
'close': 10.
},
'goog': {
'close': 7.
}
}
ma.push(data)
expected = {'aapl': 15., 'ibm': 10.}
calculated = ma.value
for name in expected:
self.assertAlmostEqual(expected[name], calculated[name], 15)
data = {
'aapl': {
'close': 10.
},
'ibm': {
'close': 11.
},
'goog': {
'close': 8.
}
}
ma.push(data)
expected = {'aapl': 12.5, 'ibm': 10.5}
calculated = ma.value
for name in expected:
self.assertAlmostEqual(expected[name], calculated[name], 15)