New submission from Warren Weckesser <warren.weckes...@gmail.com>:
The function statistics.harmonic_mean is supposed to raise a StatisticsError if
any element in the input is negative. It fails to do so if the negative
element is preceded by a zero. When there is a zero before the negative
element, the function returns 0:
>>> from statistics import harmonic_mean
>>> harmonic_mean([0, -1, 3])
0
If the zero occurs after the negative value, the StatisticsError exception is
correctly raised:
>>> harmonic_mean([-1, 0, 3])
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/warren/repos/git/forks/cpython/Lib/statistics.py", line 406, in
harmonic_mean
T, total, count = _sum(1/x for x in _fail_neg(data, errmsg))
File "/Users/warren/repos/git/forks/cpython/Lib/statistics.py", line 164, in
_sum
for typ, values in groupby(data, type):
File "/Users/warren/repos/git/forks/cpython/Lib/statistics.py", line 406, in
<genexpr>
T, total, count = _sum(1/x for x in _fail_neg(data, errmsg))
File "/Users/warren/repos/git/forks/cpython/Lib/statistics.py", line 289, in
_fail_neg
raise StatisticsError(errmsg)
statistics.StatisticsError: harmonic mean does not support negative values
>>>
The problem is in this code in the function harmonic_mean:
try:
T, total, count = _sum(1/x for x in _fail_neg(data, errmsg))
except ZeroDivisionError:
return 0
When the zero occurs before the negative value, the ZeroDivisionError is raised
before the negative value has been seen by the generator _fail_neg, and the
function returns 0.
----------
components: Library (Lib)
messages: 354028
nosy: WarrenWeckesser
priority: normal
severity: normal
status: open
title: statistics.harmonic_mean fails to raise error with negative input that
follows a 0
type: behavior
versions: Python 3.9
_______________________________________
Python tracker <rep...@bugs.python.org>
<https://bugs.python.org/issue38382>
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