How to handle rounding to negative zero in Python docstring tests

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Chapters
00:00 Question
02:20 Accepted answer (Score 2)
02:53 Answer 2 (Score 0)
03:26 Thank you

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Full question
https://stackoverflow.com/questions/6628...

Question links:
[How to have negative zero always formatted as positive zero in a python string?]: https://stackoverflow.com/questions/1101...

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Content licensed under CC BY-SA
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Tags
#python #numpy #docstring #doctest

#avk47

ACCEPTED ANSWER

Score 2

You can print the rounded array plus 0.0 to eliminate the -0:

A = np.array([[1, 0, 1], [0, 1, 0], [1, 0, 1]])
Q = orth(A)
Q[0,1] = -1e-16   # simulate a small floating point deviation

print(np.array2string(Q.round(8)+0.0, precision=8, suppress_small=True))
#[[-0.70710678  0.        ]
# [ 0.          1.        ]
# [-0.70710678  0.        ]]

So your doc string should be:

>>> Q = orth(A)
>>> print(np.array2string(Q.round(8)+0.0, precision=8, suppress_small=True)) # guarantee non-negative zeros
[[-0.70710678  0.        ]
 [ 0.          1.        ]
 [-0.70710678  0.        ]]

ANSWER 2

Score 0

Here's another alternative I came up with, although I think I like rounding the array to the given precision better. In this method, you shift the whole array by some amount that is bigger than the round-off error, but smaller than the precision comparison. That way the small numbers will still always be slightly positive.

    >>> Q = orth(A)
    >>> print(np.array2string(Q + np.full(Q.shape, 1e-14), precision=8, suppress_small=True))
    [[-0.70710678  0.        ]
     [ 0.          1.        ]
     [-0.70710678  0.        ]]