def testCorrelation(self):
mm = Correlation(dependency=['close', 'open'])
for i, (openPrice, closePrice) in enumerate(zip(self.samplesOpen, self.samplesClose)):
mm.push(dict(open=openPrice, close=closePrice))
if i == 0:
self.assertTrue(np.isnan(mm.result()))
if i >= 1:
expected = np.corrcoef(self.samplesOpen[:i + 1], self.samplesClose[:i + 1])[0, 1]
calculated = mm.result()
self.assertAlmostEqual(expected, calculated, 10, "at index {0:d}\n"
"expected correlation: {1:f}\n"
"calculated correlation: {2:f}".format(i, expected,
calculated))
def testCompoundedOperator(self):
ma5 = MovingAverage(5, 'x')
maxer = Max('close')
max5ma = Max('close') >> MovingAverage(5)
max5ma2 = MovingAverage(5, Max('close'))
average = Average('close')
sumM = Sum('close')
mvTest = Correlation(dependency=('x', 'y'))
mvCorr = (Average('close') ^ Sum('close')) >> Correlation(dependency=('x', 'y'))
for i, close in enumerate(self.sampleClose):
data = {'close': close, 'open': open}
maxer.push(data)
data2 = {'x': maxer.result()}
ma5.push(data2)
max5ma.push(data)
max5ma2.push(data)
average.push(data)
sumM.push(data)
data3 = {'x': average.result(), 'y': sumM.result()}
mvTest.push(data3)
mvCorr.push(data)
expected = ma5.result()
calculated = max5ma.result()
self.assertAlmostEqual(calculated, expected, 12, "at index {0:d}\n"
"expected: {1:f}\n"
"calculated: {2:f}".format(i, expected, calculated))
calculated = max5ma2.result()
self.assertAlmostEqual(calculated, expected, 12, "at index {0:d}\n"
"expected: {1:f}\n"
"calculated: {2:f}".format(i, expected, calculated))
if i >= 1:
expected = mvTest.result()
calculated = mvCorr.result()
self.assertAlmostEqual(calculated, expected, 12, "at index {0:d}\n"
"expected: {1:f}\n"
"calculated: {2:f}".format(i, expected, calculated))
with self.assertRaises(ValueError):
_ = Max('close') >> math.sqrt
with self.assertRaises(ValueError):
_ = (Max('close') ^ Minimum('close')) >> MovingCorrelation(20, dependency=('x', 'y', 'z'))
(Max('close') ^ Minimum('close')) >> MovingCorrelation(20, dependency=('x', 'y'))
def testCompoundedOperator(self):
ma5 = MovingAverage(5, 'x')
maxer = Max('close')
max5ma = Max('close') >> MovingAverage(5)
max5ma2 = MovingAverage(5, Max('close'))
average = Average('close')
sumM = Sum('close')
mvTest = Correlation(dependency=('x', 'y'))
mvCorr = (Average('close')
^ Sum('close')) >> Correlation(dependency=('x', 'y'))
for i, close in enumerate(self.sampleClose):
data = {'close': close, 'open': 1.}
maxer.push(data)
data2 = {'x': maxer.result()}
ma5.push(data2)
max5ma.push(data)
max5ma2.push(data)
average.push(data)
sumM.push(data)
data3 = {'x': average.result(), 'y': sumM.result()}
mvTest.push(data3)
mvCorr.push(data)
expected = ma5.result()
calculated = max5ma.result()
self.assertAlmostEqual(
calculated, expected, 12, "at index {0:d}\n"
"expected: {1:f}\n"
"calculated: {2:f}".format(i, expected, calculated))
calculated = max5ma2.result()
self.assertAlmostEqual(
calculated, expected, 12, "at index {0:d}\n"
"expected: {1:f}\n"
"calculated: {2:f}".format(i, expected, calculated))
if i >= 1:
expected = mvTest.result()
calculated = mvCorr.result()
self.assertAlmostEqual(
calculated, expected, 12, "at index {0:d}\n"
"expected: {1:f}\n"
"calculated: {2:f}".format(i, expected, calculated))
with self.assertRaises(ValueError):
_ = Max('close') >> math.sqrt
with self.assertRaises(ValueError):
_ = (Max('close') ^ Min('close')) >> MovingCorrelation(
20, dependency=('x', 'y', 'z'))
(Max('close') ^ Min('close')) >> MovingCorrelation(
20, dependency=('x', 'y'))
def testCorrelation(self):
mm = Correlation(dependency=['close', 'open'])
for i, (openPrice, closePrice) in enumerate(
zip(self.samplesOpen, self.samplesClose)):
mm.push(dict(open=openPrice, close=closePrice))
if i == 0:
self.assertTrue(np.isnan(mm.result()))
if i >= 1:
expected = np.corrcoef(self.samplesOpen[:i + 1],
self.samplesClose[:i + 1])[0, 1]
calculated = mm.result()
self.assertAlmostEqual(
expected, calculated, 10, "at index {0:d}\n"
"expected correlation: {1:f}\n"
"calculated correlation: {2:f}".format(
i, expected, calculated))