def test_wma2(self):
wma2 = LinearWeightedMovingAverage(inputs=(USEquityPricing.close, ),
window_length=10)
today = pd.Timestamp("2015")
assets = np.arange(5, dtype=np.int64)
data = np.arange(50, dtype=np.float64).reshape((10, 5))
out = np.zeros(data.shape[1])
wma2.compute(today, assets, out, data)
assert_equal(out, np.array([30.0, 31.0, 32.0, 33.0, 34.0]))
def test_wma1(self):
wma1 = LinearWeightedMovingAverage(inputs=(USEquityPricing.close, ),
window_length=10)
today = pd.Timestamp("2015")
assets = np.arange(5, dtype=np.int64)
data = np.ones((10, 5))
out = np.zeros(data.shape[1])
wma1.compute(today, assets, out, data)
assert_equal(out, np.ones(5))
def test_wma2(self):
wma2 = LinearWeightedMovingAverage(
inputs=(USEquityPricing.close,),
window_length=10
)
today = pd.Timestamp('2015')
assets = np.arange(5, dtype=np.int64)
data = np.arange(50, dtype=float).reshape((10, 5))
out = np.zeros(data.shape[1])
wma2.compute(today, assets, out, data)
assert_equal(out, np.array([30., 31., 32., 33., 34.]))
def test_wma1(self):
wma1 = LinearWeightedMovingAverage(
inputs=(USEquityPricing.close,),
window_length=10
)
today = pd.Timestamp('2015')
assets = np.arange(5, dtype=np.int64)
data = np.ones((10, 5))
out = np.zeros(data.shape[1])
wma1.compute(today, assets, out, data)
assert_equal(out, np.ones(5))