def compute(self, today, assets, out, data):
ndays = data.shape[0]
# Initialize weights array
weights = arange(1, ndays + 1, dtype=float64_dtype).reshape(ndays, 1)
# Compute normalizer
normalizer = (ndays * (ndays + 1)) / 2
# Weight the data
weighted_data = data * weights
# Compute weighted averages
out[:] = nansum(weighted_data, axis=0) / normalizer
def compute(self, today, assets, out, data):
ndays = data.shape[0]
# Initialize weights array
weights = arange(1, ndays + 1, dtype=float64_dtype).reshape(ndays, 1)
# Compute normalizer
normalizer = (ndays * (ndays + 1)) / 2
# Weight the data
weighted_data = data * weights
# Compute weighted averages
out[:] = nansum(weighted_data, axis=0) / normalizer
def compute(self, today, assets, out, close, volume):
out[:] = nansum(close * volume, axis=0) / len(close)
def compute(self, today, assets, out, base, weight):
out[:] = nansum(base * weight, axis=0) / nansum(weight, axis=0)
def compute(self, today, assets, out, close, volume):
out[:] = nansum(close * volume, axis=0) / len(close)
def compute(self, today, assets, out, base, weight):
out[:] = nansum(base * weight, axis=0) / nansum(weight, axis=0)