def testNormalizeDataWithVolume(self):
"""Test the normalize data function with a selected RateOfReturn divisor row"""
data = np.random.rand(3, 100)
data = np.array(data.tolist() + np.random.randint(100, 10000, (1, 100)).tolist())
ndata = normalizeData(data, volume_row=3)
assert np.shape(ndata) == (4, 99), "Normalize Data gave incorrect shape"
for nd, d in izip(ndata[0:3], data[0:3]):
assert close_enough(nd, rateOfReturn(d)), "Normalize Data did not use Rate of Return correctly"
assert close_enough(
ndata[3], normalizeVolume(data[3][1:])
), "Normalize Data did not use Normalize Volume correctly"
def testMakeNormalizeDataGenerator(self):
"""Test the normalize data generator function"""
data = np.random.rand(3, 100)
simple_norm = DataNormalizer()
ndata = simple_norm(data)
assert np.shape(ndata) == (3, 99), "Normalize Data gave incorrect shape"
for nd, d in izip(ndata, data):
assert close_enough(nd, rateOfReturn(d)), "Normalize Data did not use Rate of Return function correctly"
data = np.array(data.tolist() + np.random.randint(100, 10000, (1, 100)).tolist())
complex_norm = DataNormalizer(1, 3)
ndata = complex_norm(data)
assert np.shape(ndata) == (4, 99), "Normalize Data gave incorrect shape"
for nd, d in izip(ndata[0:3], data[0:3]):
assert close_enough(
nd, rateOfReturn(d, data[1][0:-1])
), "Normalize Data did not use Rate of Return correctly"
assert close_enough(
ndata[3], normalizeVolume(data[3][1:])
), "Normalize Data did not use Normalize Volume correctly"
def testNormalizeVolume(self):
"""Test the normalize volume function"""
data = range(1, 10)
norm_data = normalizeVolume(data)
assert len(norm_data) == 9, "NormalizeVolume changed length of vector"
assert close_enough(norm_data, np.arange(0.2, 2, 0.2)), "NormalizeVolume gave incorrect output"
