I wanted to check gaussian and binomial errors of a ratio via
den = Hist1D.from_bincounts(np.array([4.]), np.array([0,1]))
num = Hist1D.from_bincounts(np.array([3.]), np.array([0,1]))
num.divide(den, binomial=True).errors_up
and it should be more user-friendly. First, lists should be converted to numpy arrays internally, so this should work
den = Hist1D.from_bincounts([4.],[0,1])
num = Hist1D.from_bincounts([3.],[0,1])
and edges should be set automatically to np.arange(len(counts))?
den = Hist1D.from_bincounts([4.])
num = Hist1D.from_bincounts([3.])
aminnj
commented
3 years ago
I wanted to check gaussian and binomial errors of a ratio via
and it should be more user-friendly. First, lists should be converted to numpy arrays internally, so this should work
and edges should be set automatically to
np.arange(len(counts))?