def test_rsi_same_returns(self):
"""
RSI indicator should be the same for two price series with the same
returns, even if the prices are different.
"""
rsi = RSI()
today = np.datetime64(1, "ns")
assets = np.arange(2)
out = np.empty((2, ), dtype=float)
example_case = np.array([
46.125,
47.125,
46.4375,
46.9375,
44.9375,
44.25,
44.625,
45.75,
47.8125,
47.5625,
47.0,
44.5625,
46.3125,
47.6875,
46.6875,
])
double = example_case * 2
closes = np.vstack((example_case, double)).T
rsi.compute(today, assets, out, closes)
np.testing.assert_almost_equal(out[0], out[1], decimal=8)
def test_rsi(self, seed_value, expected):
rsi = RSI()
today = datetime64(1, 'ns')
assets = arange(3)
out = empty((3, ), dtype=float)
seed(seed_value) # Seed so we get deterministic results.
test_data = abs(randn(15, 3))
out = empty((3, ), dtype=float)
rsi.compute(today, assets, out, test_data)
check_allclose(expected, out)
def test_rsi_all_negative_returns(self):
"""
RSI indicator should be 0 in the case of 14 days of negative returns.
"""
rsi = RSI()
today = np.datetime64(1, "ns")
assets = np.arange(1)
out = np.empty((1, ), dtype=float)
closes = np.linspace(46, 32, num=15)
closes.shape = (15, 1)
rsi.compute(today, assets, out, closes)
assert out[0] == 0.0
def test_rsi(self, seed_value, expected):
rsi = RSI()
today = np.datetime64(1, "ns")
assets = np.arange(3)
out = np.empty((3, ), dtype=float)
np.random.seed(seed_value) # Seed so we get deterministic results.
test_data = np.abs(np.random.randn(15, 3))
out = np.empty((3, ), dtype=float)
rsi.compute(today, assets, out, test_data)
check_allclose(expected, out)
def test_rsi(self, seed_value, expected):
rsi = RSI()
today = datetime64(1, 'ns')
assets = arange(3)
out = empty((3,), dtype=float)
seed(seed_value) # Seed so we get deterministic results.
test_data = abs(randn(15, 3))
out = empty((3,), dtype=float)
rsi.compute(today, assets, out, test_data)
check_allclose(expected, out)
def test_rsi_all_negative_returns(self):
"""
RSI indicator should be 0 in the case of 14 days of negative returns.
"""
rsi = RSI()
today = np.datetime64(1, 'ns')
assets = np.arange(1)
out = np.empty((1,), dtype=float)
closes = np.linspace(46, 32, num=15)
closes.shape = (15, 1)
rsi.compute(today, assets, out, closes)
self.assertEqual(out[0], 0.0)
def test_rsi_all_positive_returns(self):
"""
RSI indicator should be 100 in the case of 14 days of positive returns.
"""
rsi = RSI()
today = np.datetime64(1, 'ns')
assets = np.arange(1)
out = np.empty((1,), dtype=float)
closes = np.linspace(46, 60, num=15)
closes.shape = (15, 1)
rsi.compute(today, assets, out, closes)
self.assertEqual(out[0], 100.0)
def test_rsi_same_returns(self):
"""
RSI indicator should be the same for two price series with the same
returns, even if the prices are different.
"""
rsi = RSI()
today = np.datetime64(1, 'ns')
assets = np.arange(2)
out = np.empty((2,), dtype=float)
example_case = np.array([46.125, 47.125, 46.4375, 46.9375, 44.9375,
44.25, 44.625, 45.75, 47.8125, 47.5625, 47.,
44.5625, 46.3125, 47.6875, 46.6875])
double = example_case * 2
closes = np.vstack((example_case, double)).T
rsi.compute(today, assets, out, closes)
self.assertAlmostEqual(out[0], out[1])
