Raymond Hettinger <raymond.hettin...@gmail.com> added the comment:
[Uncle Timmy]
> I doubt `fsum()` would add much value here: all the addends have the
> same sign, so cancellation is impossible
fsum() may be overkill for this problem. I mentioned it because the math
module already had the requisite code and because it improved accuracy with
high dimensional data in machine learning examples I've encountered:
>>> from math import fsum, sqrt
>>> n = 1000
>>> sum([0.1] * n)
99.9999999999986
>>> fsum([0.1] * n)
100.0
>>> sqrt(sum([0.1] * n) / n)
0.3162277660168357
>>> sqrt(fsum([0.1] * n) / n)
0.31622776601683794
# fsum() version exactly matches the decimal crosscheck
>>> getcontext().prec = 40
>>> (sum([Decimal(0.1)] * n) / n).sqrt()
Decimal('0.3162277660168379419769730258850242641698')
If we care about those little differences (about 80 ulp in this example), the
single-rounding dot products seems like a better way to go.
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Python tracker <rep...@bugs.python.org>
<https://bugs.python.org/issue33089>
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