round / set_printoptions discrepancy
Hi, Is it expected/documented that np.round and np.set_printoptions do not output the same result on screen ? I tumbled into this running this code: import numpy as np mes = np.array([ [16.06, 16.13, 16.06, 16.00, 16.06, 16.00, 16.13, 16.00] ]) avg = np.mean(mes, axis=1) print(np.round(avg, 2)) np.set_printoptions(precision=2) print(avg) Which outputs: [16.06] [16.05] Is that worth a bug report or did I miss something ? I've been able to reproduce this on many windows/linux PCs with python/numpy releases from 2017 up to last week. Thanks.
On Fri, Sep 13, 2019 at 12:58 PM Irvin Probst <irvin.probst@ensta-bretagne.fr> wrote:
Hi, I just want to add that you can use literal 16.055 to reproduce this:
I would think it has to do with "round to nearest even":
But it's as if `round` rounded decimal digits upwards (16.055 -> 16.06, 16.065 -> 16.07), whereas the `repr` rounded to the nearest odd(!) digit (16.055 -> 16.05, 16.065 -> 16.07). Does this make any sense? I'm on numpy 1.17.2. (Scalars or 1-length 1d arrays don't seem to make a difference). Regards, András
On 13/09/2019 14:05, Philip Hodge wrote:
I've just checked and np.set_printoptions behaves as python's round:
I don't know why round and np.round do not behave the same, actually I would even dare to say that I don't care :-) However np.round and np.set_printoptions should provide the same output, shouldn't they ? This discrepancy is really disturbing whereas consistency with python's round looks like the icing on the cake but in no way a required feature. -- Irvin
On 9/13/19 8:45 AM, Irvin Probst wrote:
Python round() is supposed to round to the nearest even value, if the two closest values are equally close. So round(16.055, 2) returning 16.05 was a surprise to me. I checked the documentation and found a note that explained that this was because "most decimal fractions can't be represented exactly as a float." round(16.55) returns 16.6. Phil
See the notes section here. https://numpy.org/devdocs/reference/generated/numpy.around.html. This note was recently added in https://github.com/numpy/numpy/pull/14392 Eric On Fri, Sep 13, 2019 at 9:20 AM Andras Deak <deak.andris@gmail.com> wrote:
On 9/13/19 9:26 AM, Eric Moore wrote:
Hmm, but this example with 16.055 shows the note still isn't quite right. The doc suggests that the floating point error only matters for large values or large `decimals`, but this shows it also happens for small values. Makes sense now that I see the example. We should tweak the docstring. Also, I did make some notes in https://github.com/numpy/numpy/issues/14391 for how we could "fix" this problem efficiently. Unfortunately it's far from trivial to write a correct rounding algorithm, and I'm not sure it's worth the effort: The round error is comparable to normal floating-point error, and I don't think round is heavily used. Best, Allan
On Fri, Sep 13, 2019 at 12:58 PM Irvin Probst <irvin.probst@ensta-bretagne.fr> wrote:
Hi, I just want to add that you can use literal 16.055 to reproduce this:
I would think it has to do with "round to nearest even":
But it's as if `round` rounded decimal digits upwards (16.055 -> 16.06, 16.065 -> 16.07), whereas the `repr` rounded to the nearest odd(!) digit (16.055 -> 16.05, 16.065 -> 16.07). Does this make any sense? I'm on numpy 1.17.2. (Scalars or 1-length 1d arrays don't seem to make a difference). Regards, András
On 13/09/2019 14:05, Philip Hodge wrote:
I've just checked and np.set_printoptions behaves as python's round:
I don't know why round and np.round do not behave the same, actually I would even dare to say that I don't care :-) However np.round and np.set_printoptions should provide the same output, shouldn't they ? This discrepancy is really disturbing whereas consistency with python's round looks like the icing on the cake but in no way a required feature. -- Irvin
On 9/13/19 8:45 AM, Irvin Probst wrote:
Python round() is supposed to round to the nearest even value, if the two closest values are equally close. So round(16.055, 2) returning 16.05 was a surprise to me. I checked the documentation and found a note that explained that this was because "most decimal fractions can't be represented exactly as a float." round(16.55) returns 16.6. Phil
See the notes section here. https://numpy.org/devdocs/reference/generated/numpy.around.html. This note was recently added in https://github.com/numpy/numpy/pull/14392 Eric On Fri, Sep 13, 2019 at 9:20 AM Andras Deak <deak.andris@gmail.com> wrote:
On 9/13/19 9:26 AM, Eric Moore wrote:
Hmm, but this example with 16.055 shows the note still isn't quite right. The doc suggests that the floating point error only matters for large values or large `decimals`, but this shows it also happens for small values. Makes sense now that I see the example. We should tweak the docstring. Also, I did make some notes in https://github.com/numpy/numpy/issues/14391 for how we could "fix" this problem efficiently. Unfortunately it's far from trivial to write a correct rounding algorithm, and I'm not sure it's worth the effort: The round error is comparable to normal floating-point error, and I don't think round is heavily used. Best, Allan
participants (5)
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Allan Haldane -
Andras Deak -
Eric Moore -
Irvin Probst -
Philip Hodge