[Numpy-discussion] Documentation error in numpy.random.logseries

josef.pktd@gmai... josef.pktd@gmai...
Sat Jun 26 16:18:48 CDT 2010


On Sat, Jun 26, 2010 at 5:12 PM, Vincent Davis <vincent@vincentdavis.net> wrote:
> On Sat, Jun 26, 2010 at 3:04 PM,  <josef.pktd@gmail.com> wrote:
>> On Sat, Jun 26, 2010 at 4:58 PM, David Goldsmith
>> <d.l.goldsmith@gmail.com> wrote:
>>> On Sat, Jun 26, 2010 at 1:41 PM, Vincent Davis <vincent@vincentdavis.net>
>>> wrote:
>>>>
>>>> numpy.random.logseries(p, size=None)
>>>>
>>>> but the parameters section,
>>>> Parameters:
>>>> loc : float
>>>> scale : float > 0.
>>>> size : {tuple, int}
>>>> Output shape. If the given shape is, e.g., (m, n, k), then m * n * k
>>>> samples are drawn.
>
> Thanks, I'll file a ticket

Don't file a ticket, just edit the docs. It's just the docstring not the source

the Return is also wrong

samples : {ndarray, scalar}
    where the values are all integers in [0, n].

sample values are greater or equal to one, but unbound above

>>> stats.logser.pmf(np.arange(10000, 10005),0.99999)
array([  7.85931402e-06,   7.85844959e-06,   7.85758532e-06,
         7.85672123e-06,   7.85585731e-06])

Josef

> Vincent
>
>>>>
>>>> Notice that p <> loc and what about scale.
>>>>
>>>> I'll file a ticket unless I am mission something,
>>>> Which should it be loc or p
>>>> What about scale.
>>>
>>> The source is opaque (to me; Cython?) so unless you can decipher it, test
>>> actual behavior and document that - my guess is that p is short for
>>> "parameters" and is intended to be a two-element array_like containing both
>>> the loc and scale parameters, but that's the way it should be documented,
>>> not with some unprecedented reference to loc and scale when the signature
>>> specifies p, but as I said, check that first.
>>
>>>>> np.source(stats.distributions.logser_gen)
>>
>> class logser_gen(rv_discrete):
>>    def _rvs(self, pr):
>>        return mtrand.logseries(pr,size=self._size)
>>    def _argcheck(self, pr):
>>        return (pr > 0) & (pr < 1)
>>    def _pmf(self, k, pr):
>>        return -pr**k * 1.0 / k / log(1-pr)
>>
>> p is a probability between in (0,1), just a mistake in the documentation.
>>
>>>
>>>> There is no numpy-dev list right? Should this list be used or the
>>>> scipy-dev list>
>>>
>>> That's a good Q: this is definitely a "bug" in the doc (loc and scale
>>> shouldn't be documented as such when they're not explicitly in the function
>>> signature), in which case scipy-dev is the proper place to post, but if it
>>> turns out to be a bug in the code also, then this is the proper place, since
>>> all numpy devs are subscribed here, and numpy users should know about
>>> potential bugs (numpy devs will correct me if I'm wrong).
>>
>> I think question about the substance/content of the docstrings should
>> always go to the mailing list of the corresponding function.
>>
>> Josef
>>
>>>
>>> DG
>>>>
>>>> Vincent
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>>>
>>>
>>>
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>>> set is non-empty, even if that set has measure zero.
>>>
>>> Hope: noun, that delusive spirit which escaped Pandora's jar and, with her
>>> lies, prevents mankind from committing a general suicide.  (As interpreted
>>> by Robert Graves)
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