[yt-dev] Numpy-like ops YTEP

[Matthew Turk]

Hi all,

Added the pixelizer, and updated the YTEP:

https://bitbucket.org/yt_analysis/ytep/pull-requests/55/ytep-0026-numpy-like-operations

Comments sought!  If we can get the YTEP accepted, I will add
documentation and finish up the main PR.

-Matt

On Tue, Sep 29, 2015 at 1:37 PM, Matthew Turk <matthewturk at gmail.com> wrote:
> I've implemented arbitrary_grid pulling from fluid fields with a port
> of the pixelizer code; tests are added in current state of PR, too.
> Still one more thing to do there, which is to get multiple fields in a
> single pass.
>
> On Fri, Sep 25, 2015 at 7:15 PM, Matthew Turk <matthewturk at gmail.com> wrote:
>> Hi Cameron,
>>
>> Yeah, a kwarg for the actual .arbitrary_grid would be great, but that
>> can't be expressed in the slicing notation (or rather, it can, but
>> it's unnatural).  So getting the default is what I was hoping for; for
>> particle quantities, we'll just have it do the standard "deposit"
>> machinery which lets you do any type of interpolation you like, so
>> it's less of a thing.
>>
>> -Matt
>>
>> On Fri, Sep 25, 2015 at 7:13 PM, Cameron Hummels <chummels at gmail.com> wrote:
>>> How about default to one of the options, but have a kwarg to decide which
>>> method to choose?  I sort of like trilinear interp but I'm just thinking of
>>> grid-based data.  Maybe default to trilinear interp for grid-based
>>> quantities and nearest neighbor for particle based quantities?
>>>
>>> On Fri, Sep 25, 2015 at 4:46 PM, Nathan Goldbaum <nathan12343 at gmail.com>
>>> wrote:
>>>>
>>>> I'd say nearest neighbor. Then it's also a generalization of what the
>>>> FixedResolutionBuffer does.
>>>>
>>>>
>>>> On Friday, September 25, 2015, Matthew Turk <matthewturk at gmail.com> wrote:
>>>>>
>>>>> Hi everyone,
>>>>>
>>>>> Thanks for the feedback -- I've made a bunch of changes and additions.
>>>>> One thing I wanted to ask was about 3D slicing that includes steps.
>>>>> For instance, in numpy style:
>>>>>
>>>>> ds = yt.load(...)
>>>>> ds.d[ (-5, 'km') : (5, 'km') : 128j, (-10, 'km') : (10, 'km') : 256j,
>>>>> (-2.5, 'km') : (2.5, 'km'): 64j]
>>>>>
>>>>> this should return a 128x256x64 3D array.  But, how do we generate that?
>>>>>
>>>>> The obvious thing would be to do either covering grid or arbitrary
>>>>> grids.  The former requires alignment with cell boundaries, and the
>>>>> latter currently only supports particles.  I think "arbitrary_grid"
>>>>> maps a lot more naturally to the situation, though.  So it would
>>>>> require implementing mesh fields in the arbitrary_grid object, which
>>>>> is fine, but it's not clear to me the right *way* to do that.  I think
>>>>> the choice might be between nearest neighbor and trilinear
>>>>> interpolation.  So, for the *default* behavior, should we do:
>>>>>
>>>>>  * Trilinear interpolation (maybe nicer, but also subject to
>>>>> crazytimes with stuff that isn't a volume quantity, like mass)
>>>>>  * Nearest neighbor (way, way faster, but also lower quality values in
>>>>> many cases)?
>>>>>
>>>>> My inclination is #2, but I wanted a sanity check...
>>>>>
>>>>> -Matt
>>>>>
>>>>> On Mon, Sep 21, 2015 at 3:17 PM, Matthew Turk <matthewturk at gmail.com>
>>>>> wrote:
>>>>> > Hi all,
>>>>> >
>>>>> > I'd very much appreciate feedback on this YTEP:
>>>>> >
>>>>> >
>>>>> > https://bitbucket.org/yt_analysis/ytep/pull-requests/55/ytep-0026-numpy-like-operations/diff
>>>>> >
>>>>> > The related PR that starts implementing them is here:
>>>>> >
>>>>> >
>>>>> > https://bitbucket.org/yt_analysis/yt/pull-requests/1763/wip-proposed-set-of-new-numpy-like-ops/diff
>>>>> >
>>>>> > Two things that I think need some bikeshedding -- histogram and the
>>>>> > step argument to slicing.
>>>>> >
>>>>> > -Matt
>>>>> _______________________________________________
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>>>>
>>>>
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>>>
>>>
>>>
>>> --
>>> Cameron Hummels
>>> NSF Postdoctoral Fellow
>>> Department of Astronomy
>>> California Institute of Technology
>>> http://chummels.org
>>>
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