[yt-users] Variance in phase/profiles

[Matthew Turk]

Hi Dave,

If you wanted to add this, you would modify:

yt/data_objects/profiles.py
yt/utilities/data_point_utilities.c

You'd probably be able to copy/paste most of the necessary code to
pass in additional arguments, but you'd want to pass in additional
arrays for the necessary storage to the functions Py_Bin1DProfile,
Py_Bin2DProfile and Py_Bin3DProfile.  (These could some day be turned
into Cython routines.)  Note that in the Python code these lose the
prefix "Py_".  In that article there are comments suggesting that a
different algorithm avoids error better, which isn't on that page but
is in a linked PDF.  Because we may be doing this over many thousands
of individual sets of arrays, that's likely the right one to use.

To contribute, since this will modify a piece of core functionality,
it will require detailed code review.  So I would suggest that you
fork the yt repository on bitbucket:

https://bitbucket.org/yt_analysis/yt/fork

and then push to your new repository your changes.  Issue a pull
request to signify it's ready to be reviewed.

Thanks, and let me know if I can help with more information or assistance,

Matt

On Wed, Oct 5, 2011 at 1:36 PM, David Collins <dcollins at physics.ucsd.edu> wrote:
> Matt and Britton--
>
> Thanks for the input.  I'll poke around with both of those ideas and
> let you know what I come up with.
>
> Thanks!
> d.
>
> On Wed, Oct 5, 2011 at 10:13 AM, Matthew Turk <matthewturk at gmail.com> wrote:
>> Hi Dave,
>>
>> I've thought about this on and off and there is an oustanding bug:
>>
>> https://bitbucket.org/yt_analysis/yt/issue/277/standard-deviation-for-1d-profiles
>>
>> One option is also to simply do it yourself by not using lazy_reader,
>> and loading the data manually.  (Cameron has done this, sort of.)
>> Another is to use a running-stddev algorithm, like one of those listed
>> here:
>>
>> http://www.strchr.com/standard_deviation_in_one_pass
>>
>> If you want to look at this more in depth, please feel free to either
>> ping yt-dev or leave comments in the ticket.  It'd be a great addition
>> to have.
>>
>> -Matt
>>
>> On Wed, Oct 5, 2011 at 12:01 PM, Britton Smith <brittonsmith at gmail.com> wrote:
>>> Hi Dave,
>>>
>>> The best I have been able to do for this is to manually bin up a 3d data
>>> object with the cut_region function and then do the calculation myself bin
>>> by bin.
>>> For example, if you have a sphere, you can do
>>> new_sphere = sphere.cut_region(['grid["Temperature"] > 1e5',
>>> 'grid["Temperature"] < 1e6'])
>>> That'll give you access to all the cells within that bin for a variance
>>> calculation.  Note the quotes around those expressions.  The cuts are
>>> applied in yt using eval functions.
>>>
>>> This will work, but it's slow and requires you to do a lot by hand.
>>>
>>> Britton
>>>
>>> On Wed, Oct 5, 2011 at 11:51 AM, david collins <antpuncher at gmail.com> wrote:
>>>>
>>>> Hi, Everybody!
>>>>
>>>> Does anyone out there have a technique for getting the variance out of
>>>> a profile object?  A profile object is good at getting <X> vs. B, I'd
>>>> then like to get < (X - <X>)^2 > vs B.  Matt and I had spittballed the
>>>> possibility some time ago, but I was wondering if anyone out there had
>>>> successfully done it.
>>>>
>>>> Thanks,
>>>> d.
>>>>
>>>> --
>>>> Sent from my computer.
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>
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