numpy.average() has a weights option, but numpy.std() does not. Does anyone have suggestions for a workaround?
How about the following short "manual calculation"?
def weighted_avg_and_std(values, weights):
"""
Return the weighted average and standard deviation.
They weights are in effect first normalized so that they
sum to 1 (and so they must not all be 0).
values, weights -- NumPy ndarrays with the same shape.
"""
average = numpy.average(values, weights=weights)
# Fast and numerically precise:
variance = numpy.average((values-average)**2, weights=weights)
return (average, math.sqrt(variance))