def testCompoundedSecurityValueHolder(self):
ma = SecurityMovingAverage(2, 'close')
compounded = ma >> SecurityMovingMax(3)
container = {'aapl': deque(maxlen=3), 'ibm': deque(maxlen=3)}
expected = {'aapl': 0.0, 'ibm': 0.0}
for i in range(len(self.datas['aapl']['close'])):
data = {
'aapl': {
Factors.CLOSE: self.datas['aapl'][Factors.CLOSE][i]
},
'ibm': {
Factors.CLOSE: self.datas['ibm'][Factors.CLOSE][i]
}
}
ma.push(data)
maRes = ma.value
for name in maRes.index:
container[name].append(maRes[name])
expected[name] = max(container[name])
compounded.push(data)
calculated = compounded.value
for name in calculated.index:
self.assertAlmostEqual(
expected[name], calculated[name], 12,
"for {0} at index {1}\n"
"expected: {2}\n"
"calculated: {3}".format(name, i, expected[name],
calculated[name]))
def testBasicFunctions(self):
window = 10
pNames = 'close'
symbolList = ['aapl', 'ibm']
testValueHolder = SecurityMovingAverage(window, pNames)
testValueHolder.push({'aapl': {'close': 1.0}, 'ibm': {'close': 2.0}})
self.assertEqual(set(testValueHolder.symbolList), set(symbolList))
self.assertEqual(testValueHolder.window, window)
# test binary operated value holder
window2 = 5
pNames2 = 'open'
test2 = SecurityMovingMax(window2, pNames2)
binaryValueHolder = testValueHolder + test2
self.assertEqual(binaryValueHolder.window, max(window, window2))
# test compounded operated value holder
test3 = SecurityMovingMax(window2, testValueHolder)
self.assertEqual(test3.window, window + window2)
# test compounded twice
test4 = SecurityMovingMax(window2, test3)
self.assertEqual(test4.window, window + 2 * window2)
def testSecurityMovingAverage(self):
window = 10
ma1 = SecurityMovingAverage(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]))
ma1.push(data)
if i < window:
start = 0
else:
start = i + 1 - window
value = ma1.value
for name in value.index():
expected = np.mean(self.dataSet[name]['close'][start:(i + 1)])
calculated = value[name]
self.assertAlmostEqual(expected, calculated, 12, 'at index {0}\n'
'expected: {1:.12f}\n'
'calculated: {2:.12f}'.format(i, expected, calculated))
with self.assertRaises(ValueError):
_ = SecurityMovingAverage(window, ['close', 'open'])
def testDividedSecurityValueHolders(self):
window1 = 10
window2 = 5
dependency1 = Factors.CLOSE
dependency2 = Factors.OPEN
ma = SecurityMovingAverage(window1, dependency1)
mm = SecurityMovingSum(window2, dependency2)
combined = ma / mm
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]
}
}
ma.push(data)
mm.push(data)
combined.push(data)
expected = ma.value / mm.value
calculated = combined.value
for name in expected.index:
self.assertAlmostEqual(expected[name], calculated[name], 12)
def testItemizedValueHolder(self):
window = 10
pNames = 'close'
test = SecurityMovingAverage(window, pNames)
test.push({
'aapl': {
'close': 10.0
},
'ibm': {
'close': 15.0
},
'goog': {
'close': 17.0
}
})
test.push({
'aapl': {
'close': 12.0
},
'ibm': {
'close': 10.0
},
'goog': {
'close': 13.0
}
})
expected = {'ibm': 12.5, 'goog': 15.0}
for s in expected:
self.assertAlmostEqual(test[s], expected[s])
def testSecurityMovingAverageWithErrorValues(self):
window = 5
to_average = SecurityLatestValueHolder(
'open') / SecurityLatestValueHolder('close')
ma = SecurityMovingAverage(window, to_average)
container = {'aapl': deque(maxlen=window), 'ibm': deque(maxlen=window)}
for i in range(len(self.aapl['close'])):
data = dict(aapl=dict(
close=1.0 if self.aapl['close'][i] >= 1.0 else 0.0,
open=self.aapl['open'][i]),
ibm=dict(close=self.ibm['close'][i],
open=self.ibm['open'][i]))
ma.push(data)
for name in data:
res = data[name]['open'] / data[name]['close'] if data[name][
'close'] != 0. else np.nan
if res != np.inf and res != -np.inf and not math.isnan(res):
container[name].append(res)
value = ma.value
for name in value.index():
expected = np.mean(container[name])
calculated = value[name]
self.assertAlmostEqual(
expected, calculated, 12, 'at index {0}\n'
'expected: {1:.12f}\n'
'calculated: {2:.12f}'.format(i, expected, calculated))
def testValueHolderCompounding(self):
window = 10
ma1 = SecurityMovingAverage(window, 'close')
compounded1 = SecurityMovingMax(2, ma1)
compounded2 = SecurityMovingAverage(2, ma1)
self.assertEqual(compounded1.window, window + 2)
container = [np.nan, np.nan]
for i in range(len(self.aapl['close'])):
data = {
'aapl': {
'close': self.aapl['close'][i],
'open': self.aapl['open'][i]
}
}
ma1.push(data)
compounded1.push(data)
compounded2.push(data)
container[i % 2] = ma1.value['aapl']
if i >= 1:
self.assertAlmostEqual(max(container),
compounded1.value['aapl'], 12)
self.assertAlmostEqual(np.mean((container)),
compounded2.value['aapl'], 12)
def testRDividedSecurityValueHoldersWithScalar(self):
window = 10
dependency = 'close'
ma = SecurityMovingAverage(window, dependency)
combined = ma / 2.0
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]}}
ma.push(data)
combined.push(data)
expected = ma.value / 2.0
calculated = combined.value
for name in expected.index():
self.assertAlmostEqual(expected[name], calculated[name], 12)
def testRDividedSecurityValueHoldersWithScalar(self):
window = 10
dependency = ['close']
ma = SecurityMovingAverage(window, dependency, ['aapl', 'ibm'])
combined = ma / 2.0
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]}}
ma.push(data)
combined.push(data)
expected = ma.value / 2.0
calculated = combined.value
for name in expected:
self.assertAlmostEqual(expected[name], calculated[name], 12)
def testBasicFunctions(self):
window = 10
pNames = ['close']
symbolList = ['aapl', 'ibm']
testValueHolder = SecurityMovingAverage(window, pNames)
testValueHolder.push({'aapl': {'close': 1.0}, 'ibm': {'close': 2.0}})
dependency = {
name: pNames for name in symbolList
}
self.assertEqual(set(testValueHolder.symbolList), set(symbolList))
self.assertEqual(testValueHolder.dependency, dependency)
self.assertEqual(testValueHolder.valueSize, 1)
self.assertEqual(testValueHolder.window, window)
# test binary operated value holder
window2 = 5
pNames2 = ['open']
test2 = SecurityMovingMax(window2, pNames2)
binaryValueHolder = testValueHolder + test2
dependency2 = {
name: pNames + pNames2 for name in symbolList
}
self.assertEqual(set(binaryValueHolder.symbolList), set(symbolList))
for name in dependency2:
self.assertEqual(set(binaryValueHolder.dependency[name]), set(dependency2[name]))
self.assertEqual(binaryValueHolder.valueSize, 1)
self.assertEqual(binaryValueHolder.window, max(window, window2))
# test compounded operated value holder
test3 = SecurityMovingMax(window2, testValueHolder)
self.assertEqual(set(test3.symbolList), set(symbolList))
self.assertEqual(test3.dependency, dependency)
self.assertEqual(test3.valueSize, 1)
self.assertEqual(test3.window, window + window2 - 1)
# test compounded twice
test4 = SecurityMovingMax(window2, test3)
self.assertEqual(set(test4.symbolList), set(symbolList))
self.assertEqual(test4.dependency, dependency)
self.assertEqual(test4.valueSize, 1)
self.assertEqual(test4.window, window + 2 * window2 - 2)
def testBasicFunctions(self):
window = 10
pNames = ['close']
symbolList = ['aapl', 'ibm']
testValueHolder = SecurityMovingAverage(window, pNames)
testValueHolder.push({'aapl': {'close': 1.0}, 'ibm': {'close': 2.0}})
dependency = {name: pNames for name in symbolList}
self.assertEqual(set(testValueHolder.symbolList), set(symbolList))
self.assertEqual(testValueHolder.dependency, dependency)
self.assertEqual(testValueHolder.valueSize, 1)
self.assertEqual(testValueHolder.window, window)
# test binary operated value holder
window2 = 5
pNames2 = ['open']
test2 = SecurityMovingMax(window2, pNames2)
binaryValueHolder = testValueHolder + test2
dependency2 = {name: pNames + pNames2 for name in symbolList}
self.assertEqual(set(binaryValueHolder.symbolList), set(symbolList))
for name in dependency2:
self.assertEqual(set(binaryValueHolder.dependency[name]),
set(dependency2[name]))
self.assertEqual(binaryValueHolder.valueSize, 1)
self.assertEqual(binaryValueHolder.window, max(window, window2))
# test compounded operated value holder
test3 = SecurityMovingMax(window2, testValueHolder)
self.assertEqual(set(test3.symbolList), set(symbolList))
self.assertEqual(test3.dependency, dependency)
self.assertEqual(test3.valueSize, 1)
self.assertEqual(test3.window, window + window2 - 1)
# test compounded twice
test4 = SecurityMovingMax(window2, test3)
self.assertEqual(set(test4.symbolList), set(symbolList))
self.assertEqual(test4.dependency, dependency)
self.assertEqual(test4.valueSize, 1)
self.assertEqual(test4.window, window + 2 * window2 - 2)
def testValueHolderCompounding(self):
window = 10
ma1 = SecurityMovingAverage(window, 'close')
compounded1 = SecurityMovingMax(2, ma1)
compounded2 = SecurityMovingAverage(2, ma1)
self.assertEqual(compounded1.window, window + 1)
container = [np.nan, np.nan]
for i in range(len(self.aapl['close'])):
data = {'aapl': {'close': self.aapl['close'][i], 'open': self.aapl['open'][i]}}
ma1.push(data)
compounded1.push(data)
compounded2.push(data)
container[i % 2] = ma1.value['aapl']
if i >= 1:
self.assertAlmostEqual(max(container), compounded1.value['aapl'], 12)
self.assertAlmostEqual(np.mean((container)), compounded2.value['aapl'], 12)
def testItemizedValueHolder(self):
window = 10
pNames = 'close'
symbolList = ['AAPL', 'IBM', 'GOOG']
test = SecurityMovingAverage(window, pNames, symbolList)
test.push({'aapl': {'close': 10.0}, 'ibm': {'close': 15.0}, 'goog': {'close': 17.0}})
test.push({'aapl': {'close': 12.0}, 'ibm': {'close': 10.0}, 'goog': {'close': 13.0}})
# single named value holder
test1 = test['IBM']
self.assertAlmostEqual(test1, 12.5, 15)
# multi-valued named value holder
test2 = test['IBM', 'GOOG']
expected = SecuritiesValues({'ibm': 12.5, 'goog':15.0})
self.assertAlmostEqual(test2, expected)
# wrong type of item
with self.assertRaises(TypeError):
_ = test[1]
def testItemizedValueHolder(self):
window = 10
pNames = 'close'
test = SecurityMovingAverage(window, pNames)
test.push({'aapl': {'close': 10.0}, 'ibm': {'close': 15.0}, 'goog': {'close': 17.0}})
test.push({'aapl': {'close': 12.0}, 'ibm': {'close': 10.0}, 'goog': {'close': 13.0}})
# single named value holder
test1 = test['ibm']
self.assertAlmostEqual(test1, 12.5, 15)
# multi-valued named value holder
test2 = test['ibm', 'goog']
expected = SecuritiesValues({'ibm': 12.5, 'goog':15.0})
for s in test2.index:
self.assertAlmostEqual(test2[s], expected[s])
# wrong type of item
with self.assertRaises(TypeError):
_ = test[1]
def testItemizedValueHolder(self):
window = 10
pNames = 'close'
test = SecurityMovingAverage(window, pNames)
test.push({
'aapl': {
'close': 10.0
},
'ibm': {
'close': 15.0
},
'goog': {
'close': 17.0
}
})
test.push({
'aapl': {
'close': 12.0
},
'ibm': {
'close': 10.0
},
'goog': {
'close': 13.0
}
})
# single named value holder
test1 = test['ibm']
self.assertAlmostEqual(test1, 12.5, 15)
# multi-valued named value holder
test2 = test['ibm', 'goog']
expected = SecuritiesValues({'ibm': 12.5, 'goog': 15.0})
for s in test2.index:
self.assertAlmostEqual(test2[s], expected[s])
# wrong type of item
with self.assertRaises(TypeError):
_ = test[1]
def testDividedSecurityValueHolders(self):
window1 = 10
window2 = 5
dependency1 = Factors.CLOSE
dependency2 = Factors.OPEN
ma = SecurityMovingAverage(window1, dependency1, ['aapl', 'ibm'])
mm = SecurityMovingSum(window2, dependency2, ['aapl', 'ibm'])
combined = ma / mm
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]}}
ma.push(data)
mm.push(data)
combined.push(data)
expected = ma.value / mm.value
calculated = combined.value
for name in expected:
self.assertAlmostEqual(expected[name], calculated[name], 12)
def testGeSecurityValueHolder(self):
filter = SecurityMovingAverage(1, 'close') >= 10.0
ma = 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)
def testCompoundedSecurityValueHolder(self):
ma = SecurityMovingAverage(2, 'close', ['aapl', 'ibm'])
compounded = ma >> SecurityMovingMax(3)
container = {'aapl': deque(maxlen=3), 'ibm': deque(maxlen=3)}
expected = {'aapl': 0.0, 'ibm': 0.0}
for i in range(len(self.datas['aapl']['close'])):
data = {'aapl': {Factors.CLOSE: self.datas['aapl'][Factors.CLOSE][i]},
'ibm': {Factors.CLOSE: self.datas['ibm'][Factors.CLOSE][i]}}
ma.push(data)
maRes = ma.value
for name in maRes:
container[name].append(maRes[name])
expected[name] = max(container[name])
compounded.push(data)
calculated = compounded.value
for name in calculated:
self.assertAlmostEqual(expected[name], calculated[name], 12, "for {0} at index {1}\n"
"expected: {2}\n"
"calculated: {3}"
.format(name, i, expected[name], calculated[name]))
def testGeSecurityValueHolder(self):
filter = SecurityMovingAverage(1, 'close') >= 10.0
ma = 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)
def testSecurityMovingAverage(self):
window = 10
ma1 = SecurityMovingAverage(window, ['close'])
for i in range(len(self.aapl['close'])):
data = {'aapl': {'close': self.aapl['close'][i], 'open': self.aapl['open'][i]}}
data['ibm'] = {'close': self.ibm['close'][i], 'open': self.ibm['open'][i]}
ma1.push(data)
if i < 10:
start = 0
else:
start = i + 1 - window
value = ma1.value
for name in value.index:
expected = np.mean(self.dataSet[name]['close'][start:(i + 1)])
calculated = value[name]
self.assertAlmostEqual(expected, calculated, 12, 'at index {0}\n'
'expected: {1:.12f}\n'
'calculated: {2:.12f}'.format(i, expected, calculated))
with self.assertRaises(ValueError):
_ = SecurityMovingAverage(window, ['close', 'open'])
