[yt-dev] Testing Intervention

[Anthony Scopatz]

Why do I always get these emails right before I have to get on a plane?!
I'll write a more detailed response soon....
On Sep 21, 2012 6:16 PM, "Casey W. Stark" <caseywstark at gmail.com> wrote:

> Hi Matt.
>
> I would like to help with this, but it's difficult to figure out where to
> start.
>
> Say I want to test projections. I make a fake 3D density field, maybe
> something as simple as np.arange(4**3).reshape((4, 4, 4)). I write down the
> answer to the x-projection. Now all I need to do is call
> assert_allclose(yt_result, answer, rtol=1e-15), but I don't know what
> pieces of low-level yt stuff to call to get to `yt_result`. Hopefully
> that's clear...
>
> Maybe this comes down to creating a fake frontend we can attach fields to?
>
> - Casey
>
>
> On Fri, Sep 21, 2012 at 2:42 PM, Matthew Turk <matthewturk at gmail.com>wrote:
>
>> Hi all,
>>
>> As some of you have seen (at least Stephen), I filed a ticket this
>> morning about increasing testing coverage.  The other night Anthony
>> and I met up in NYC and he had something of an "intervention" about
>> the sufficiency of answer testing for yt; it didn't take too much work
>> on his part to convince me that we should be testing not just against
>> a gold standard, but also performing unit tests.  In the past I had
>> eschewed unit testing simply because the task of mocking data was
>> quite tricky, and by adding tests that use smaller bits we could cover
>> unit testable areas with answer testing.
>>
>> But, this isn't really a good strategy.  Let's move to having both.
>> The testing infrastructure he recommends is the nearly-omnipresent
>> nose:
>>
>> http://nose.readthedocs.org/en/latest/
>>
>> The ticket to track this is here:
>>
>> https://bitbucket.org/yt_analysis/yt/issue/426/increase-unit-test-coverage
>>
>> There are a couple sub-items here:
>>
>> 1) NumPy's nose test plugins provide a lot of necessary functionality
>> that we have reimplemented in the answer testing utilities.  I'd like
>> to start using the numpy plugins, which include things like
>> conditional test execution, array comparisons, "slow" tests, etc etc.
>> 2) We can evaluate, using conditional test execution, moving to nose
>> for answer testing.  But that's not on the agenda now.
>> 3) Writing tests for nose is super easy, and running them is too.  Just
>> do:
>>
>> nosetest -w yt/
>>
>> when in your source directory.
>>
>> 4) I've written a simple sample here:
>>
>>
>> https://bitbucket.org/yt_analysis/yt-3.0/src/da10ffc17f6d/yt/utilities/tests/test_interpolators.py
>>
>> 5) I'll handle writing up some mock data that doesn't require shipping
>> lots of binary files, which can then be used for checking things that
>> absolutely require hierarchies.
>>
>> --
>>
>> The way to organize tests is easy.  Inside each directory with
>> testable items create a new directory called "tests", and in here toss
>> some scripts.  You can stick a bunch of functions in those scripts.
>>
>> Anyway, I'm going to start writing more of these (in the main yt repo,
>> and this change will be grafted there as well) and I'll write back
>> once the data mocking is ready.  I'd like it if we started encouraging
>> or even mandating simple tests (and/or answer tests) for functionality
>> that gets added, but that's a discussion that should be held
>> separately.
>>
>> The items on the ticket:
>>
>>  * kD-tree for nearest neighbor
>>  * Geometric selection routines
>>  * Profiles
>>  * Projections -- underlying quadtree
>>  * Data object selection of data containers
>>  * Data object selection of points
>>  * Orientation class
>>  * Pixelization
>>  * Color maps
>>  * PNG writing
>>
>> Is anyone willing to claim any additional items that they will help
>> write unit tests for?
>>
>> -Matt
>> _______________________________________________
>> yt-dev mailing list
>> yt-dev at lists.spacepope.org
>> http://lists.spacepope.org/listinfo.cgi/yt-dev-spacepope.org
>>
>
>
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