[SciPy-dev] Depreciating functions in scipy.stats
Mon Mar 2 15:59:22 CST 2009
> On Mon, Mar 2, 2009 at 2:09 PM, Bruce Southey <email@example.com> wrote:
>> I am seeing a few functions that should be made depreciated as these
>> appear to duplicate Numpy or Scipy functions.
>> Do you want these as new or old tickets (for example, samplestd has
>> ticket #81 as part of the Statistics Review)?
>> Would you want a large patch or one for each ticket?
> I agree with all the depreciation, and there might be some more (eg. sem and
> stderr are essentially the same). For depreciation warnings I would prefer
> one new ticket with one patch (or easier for me to verify is the
> changed complete
> sourcefile of stats.py)
>> These functions are just renamed functions present in scipy.special just
>> with perhaps slightly more informative names:
> Most calls to these functions can be replaced to calls to the distribution, e.g
> distributions.f.sf, as I did for the t-tests. However, I have seen them used in
> some external packages, and a release with a depreciation warning might be
I agree that these should be first depreciated. I will try to write
these when I get the time.
>> But I do not think we need these as separate functions but there is the
>> issue of depreciation involved if users use these specific functions.
>> There are other like that should be treated as depreciated:
Okay, I have created two tickets with hopefully suitable patches for:
I did not change the info.py and any tests but these will need to be
changed if the patches are applied. Also, if you apply these patches, I
think that tickets 80 and 81 can be closed.
>> Also, stats.py has the histogram and histogram2 functions where I agree
>> with the comment in the code about being obsoleted by numpy.histogram.
>> I would think these should be depreciated although the cumfreq and
>> relfreq functions would need to be rewritten,
> I never looked closely at the histogram and histogram2 functions in stats,
> because I also use the numpy version. So I don't know if they have
> equivalent functionality.
I have not examined it in detail, histogram is different from numpy in
various ways like arguments and implementation. But, after the histogram
discussion on the numpy list, I do not consider that it is sufficiently
different than the numpy version to justify yet another version.
I think histogram2 is just a utility function than a useful function and
it not used elsewhere.
> Neither the histogram functions nor cumfreq and relfreq have tests, so
> before depreciating we should find out what these functions are doing
> for different cases.
When I get to these functions, I will look into providing tests. Also
these may need changes depending on what happens with histogram.
> Thank you for checking this
No problems (yet) especially when I will have more 'issues' as I go
through these functions.
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