I have always been puzzled about how to correctly define the python built-in
`round(number, ndigits)` when `number` is a binary float and `ndigits` is
greater than zero.
Apparently CPython and numpy disagree:
>>> round(2.765, 2)
2.77
>>> np.round(2.765, 2)
2.76My question for the numpy devs are: - Is there an authoritative source that explains what `round(number, ndigits)` means when the digits are counted in a base different from the one used in the floating point representation? - Which was the first programming language to implement an intrinsic function `round(number, ndigits)` where ndgits are always decimal, irrespective of the representation of the floating point number? (I’m not interested in algorithms for printing a decimal representation, but in languages that allow to store and perform computations with the rounded value.) - Is `round(number, ndigits)` a useful function that deserves a rigorous definition, or is its use limited to fuzzy situations, where accuracy can be safely traded for speed? Personally I cannot think of sensible uses of `round(number, ndigits)` for binary floats: whenever you positively need `round(number, ndigits)`, you should use a decimal floating point representation. Stefano
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