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(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_returns(self, seed_value, window_length):
returns = Returns(window_length=window_length)
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(window_length, 3))
# Calculate the expected returns
expected = (test_data[-1] - test_data[0]) / test_data[0]
out = empty((3, ), dtype=float)
returns.compute(today, assets, out, test_data)
check_allclose(expected, out)
def test_returns(self, seed_value, window_length):
returns = Returns(window_length=window_length)
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(window_length, 3))
# Calculate the expected returns
expected = (test_data[-1] - test_data[0]) / test_data[0]
out = empty((3,), dtype=float)
returns.compute(today, assets, out, test_data)
check_allclose(expected, out)
